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Publisher: Elsevier   (Total: 3161 journals)

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Showing 1 - 200 of 3161 Journals sorted alphabetically
A Practical Logic of Cognitive Systems     Full-text available via subscription   (Followers: 9)
AASRI Procedia     Open Access   (Followers: 15)
Academic Pediatrics     Hybrid Journal   (Followers: 35, SJR: 1.655, CiteScore: 2)
Academic Radiology     Hybrid Journal   (Followers: 24, SJR: 1.015, CiteScore: 2)
Accident Analysis & Prevention     Partially Free   (Followers: 98, SJR: 1.462, CiteScore: 3)
Accounting Forum     Hybrid Journal   (Followers: 27, SJR: 0.932, CiteScore: 2)
Accounting, Organizations and Society     Hybrid Journal   (Followers: 37, SJR: 1.771, CiteScore: 3)
Achievements in the Life Sciences     Open Access   (Followers: 5)
Acta Anaesthesiologica Taiwanica     Open Access   (Followers: 7)
Acta Astronautica     Hybrid Journal   (Followers: 418, SJR: 0.758, CiteScore: 2)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Biomaterialia     Hybrid Journal   (Followers: 28, SJR: 1.967, CiteScore: 7)
Acta Colombiana de Cuidado Intensivo     Full-text available via subscription   (Followers: 2)
Acta de Investigación Psicológica     Open Access   (Followers: 3)
Acta Ecologica Sinica     Open Access   (Followers: 10, SJR: 0.18, CiteScore: 1)
Acta Haematologica Polonica     Free   (Followers: 1, SJR: 0.128, CiteScore: 0)
Acta Histochemica     Hybrid Journal   (Followers: 3, SJR: 0.661, CiteScore: 2)
Acta Materialia     Hybrid Journal   (Followers: 266, SJR: 3.263, CiteScore: 6)
Acta Mathematica Scientia     Full-text available via subscription   (Followers: 5, SJR: 0.504, CiteScore: 1)
Acta Mechanica Solida Sinica     Full-text available via subscription   (Followers: 9, SJR: 0.542, CiteScore: 1)
Acta Oecologica     Hybrid Journal   (Followers: 12, SJR: 0.834, CiteScore: 2)
Acta Otorrinolaringologica (English Edition)     Full-text available via subscription  
Acta Otorrinolaringológica Española     Full-text available via subscription   (Followers: 3, SJR: 0.307, CiteScore: 0)
Acta Pharmaceutica Sinica B     Open Access   (Followers: 1, SJR: 1.793, CiteScore: 6)
Acta Poética     Open Access   (Followers: 4, SJR: 0.101, CiteScore: 0)
Acta Psychologica     Hybrid Journal   (Followers: 27, SJR: 1.331, CiteScore: 2)
Acta Sociológica     Open Access   (Followers: 1)
Acta Tropica     Hybrid Journal   (Followers: 6, SJR: 1.052, CiteScore: 2)
Acta Urológica Portuguesa     Open Access  
Actas Dermo-Sifiliograficas     Full-text available via subscription   (Followers: 3, SJR: 0.374, CiteScore: 1)
Actas Dermo-Sifiliográficas (English Edition)     Full-text available via subscription   (Followers: 2)
Actas Urológicas Españolas     Full-text available via subscription   (Followers: 3, SJR: 0.344, CiteScore: 1)
Actas Urológicas Españolas (English Edition)     Full-text available via subscription   (Followers: 1)
Actualites Pharmaceutiques     Full-text available via subscription   (Followers: 6, SJR: 0.19, CiteScore: 0)
Actualites Pharmaceutiques Hospitalieres     Full-text available via subscription   (Followers: 3)
Acupuncture and Related Therapies     Hybrid Journal   (Followers: 8)
Acute Pain     Full-text available via subscription   (Followers: 14, SJR: 2.671, CiteScore: 5)
Ad Hoc Networks     Hybrid Journal   (Followers: 11, SJR: 0.53, CiteScore: 4)
Addictive Behaviors     Hybrid Journal   (Followers: 17, SJR: 1.29, CiteScore: 3)
Addictive Behaviors Reports     Open Access   (Followers: 8, SJR: 0.755, CiteScore: 2)
Additive Manufacturing     Hybrid Journal   (Followers: 11, SJR: 2.611, CiteScore: 8)
Additives for Polymers     Full-text available via subscription   (Followers: 23)
Advanced Drug Delivery Reviews     Hybrid Journal   (Followers: 164, SJR: 4.09, CiteScore: 13)
Advanced Engineering Informatics     Hybrid Journal   (Followers: 12, SJR: 1.167, CiteScore: 4)
Advanced Powder Technology     Hybrid Journal   (Followers: 17, SJR: 0.694, CiteScore: 3)
Advances in Accounting     Hybrid Journal   (Followers: 8, SJR: 0.277, CiteScore: 1)
Advances in Agronomy     Full-text available via subscription   (Followers: 15, SJR: 2.384, CiteScore: 5)
Advances in Anesthesia     Full-text available via subscription   (Followers: 28, SJR: 0.126, CiteScore: 0)
Advances in Antiviral Drug Design     Full-text available via subscription   (Followers: 2)
Advances in Applied Mathematics     Full-text available via subscription   (Followers: 10, SJR: 0.992, CiteScore: 1)
Advances in Applied Mechanics     Full-text available via subscription   (Followers: 11, SJR: 1.551, CiteScore: 4)
Advances in Applied Microbiology     Full-text available via subscription   (Followers: 24, SJR: 2.089, CiteScore: 5)
Advances In Atomic, Molecular, and Optical Physics     Full-text available via subscription   (Followers: 14, SJR: 0.572, CiteScore: 2)
Advances in Biological Regulation     Hybrid Journal   (Followers: 4, SJR: 2.61, CiteScore: 7)
Advances in Botanical Research     Full-text available via subscription   (Followers: 2, SJR: 0.686, CiteScore: 2)
Advances in Cancer Research     Full-text available via subscription   (Followers: 33, SJR: 3.043, CiteScore: 6)
Advances in Carbohydrate Chemistry and Biochemistry     Full-text available via subscription   (Followers: 9, SJR: 1.453, CiteScore: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5, SJR: 1.992, CiteScore: 5)
Advances in Cell Aging and Gerontology     Full-text available via subscription   (Followers: 4)
Advances in Cellular and Molecular Biology of Membranes and Organelles     Full-text available via subscription   (Followers: 13)
Advances in Chemical Engineering     Full-text available via subscription   (Followers: 27, SJR: 0.156, CiteScore: 1)
Advances in Child Development and Behavior     Full-text available via subscription   (Followers: 10, SJR: 0.713, CiteScore: 1)
Advances in Chronic Kidney Disease     Full-text available via subscription   (Followers: 10, SJR: 1.316, CiteScore: 2)
Advances in Clinical Chemistry     Full-text available via subscription   (Followers: 26, SJR: 1.562, CiteScore: 3)
Advances in Colloid and Interface Science     Full-text available via subscription   (Followers: 19, SJR: 1.977, CiteScore: 8)
Advances in Computers     Full-text available via subscription   (Followers: 14, SJR: 0.205, CiteScore: 1)
Advances in Dermatology     Full-text available via subscription   (Followers: 15)
Advances in Developmental Biology     Full-text available via subscription   (Followers: 12)
Advances in Digestive Medicine     Open Access   (Followers: 9)
Advances in DNA Sequence-Specific Agents     Full-text available via subscription   (Followers: 7)
Advances in Drug Research     Full-text available via subscription   (Followers: 25)
Advances in Ecological Research     Full-text available via subscription   (Followers: 44, SJR: 2.524, CiteScore: 4)
Advances in Engineering Software     Hybrid Journal   (Followers: 28, SJR: 1.159, CiteScore: 4)
Advances in Experimental Biology     Full-text available via subscription   (Followers: 8)
Advances in Experimental Social Psychology     Full-text available via subscription   (Followers: 46, SJR: 5.39, CiteScore: 8)
Advances in Exploration Geophysics     Full-text available via subscription   (Followers: 1)
Advances in Fluorine Science     Full-text available via subscription   (Followers: 9)
Advances in Food and Nutrition Research     Full-text available via subscription   (Followers: 60, SJR: 0.591, CiteScore: 2)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 16)
Advances in Genetics     Full-text available via subscription   (Followers: 18, SJR: 1.354, CiteScore: 4)
Advances in Genome Biology     Full-text available via subscription   (Followers: 10, SJR: 12.74, CiteScore: 13)
Advances in Geophysics     Full-text available via subscription   (Followers: 6, SJR: 1.193, CiteScore: 3)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 24, SJR: 0.368, CiteScore: 1)
Advances in Heterocyclic Chemistry     Full-text available via subscription   (Followers: 12, SJR: 0.749, CiteScore: 3)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 23)
Advances in Imaging and Electron Physics     Full-text available via subscription   (Followers: 2, SJR: 0.193, CiteScore: 0)
Advances in Immunology     Full-text available via subscription   (Followers: 36, SJR: 4.433, CiteScore: 6)
Advances in Inorganic Chemistry     Full-text available via subscription   (Followers: 8, SJR: 1.163, CiteScore: 2)
Advances in Insect Physiology     Full-text available via subscription   (Followers: 2, SJR: 1.938, CiteScore: 3)
Advances in Integrative Medicine     Hybrid Journal   (Followers: 6, SJR: 0.176, CiteScore: 0)
Advances in Intl. Accounting     Full-text available via subscription   (Followers: 3)
Advances in Life Course Research     Hybrid Journal   (Followers: 8, SJR: 0.682, CiteScore: 2)
Advances in Lipobiology     Full-text available via subscription   (Followers: 1)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 8)
Advances in Marine Biology     Full-text available via subscription   (Followers: 18, SJR: 0.88, CiteScore: 2)
Advances in Mathematics     Full-text available via subscription   (Followers: 11, SJR: 3.027, CiteScore: 2)
Advances in Medical Sciences     Hybrid Journal   (Followers: 7, SJR: 0.694, CiteScore: 2)
Advances in Medicinal Chemistry     Full-text available via subscription   (Followers: 5)
Advances in Microbial Physiology     Full-text available via subscription   (Followers: 4, SJR: 1.158, CiteScore: 3)
Advances in Molecular and Cell Biology     Full-text available via subscription   (Followers: 23)
Advances in Molecular and Cellular Endocrinology     Full-text available via subscription   (Followers: 8)
Advances in Molecular Toxicology     Full-text available via subscription   (Followers: 7, SJR: 0.182, CiteScore: 0)
Advances in Nanoporous Materials     Full-text available via subscription   (Followers: 3)
Advances in Oncobiology     Full-text available via subscription   (Followers: 2)
Advances in Organ Biology     Full-text available via subscription   (Followers: 2)
Advances in Organometallic Chemistry     Full-text available via subscription   (Followers: 17, SJR: 1.875, CiteScore: 4)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7, SJR: 0.174, CiteScore: 0)
Advances in Parasitology     Full-text available via subscription   (Followers: 5, SJR: 1.579, CiteScore: 4)
Advances in Pediatrics     Full-text available via subscription   (Followers: 24, SJR: 0.461, CiteScore: 1)
Advances in Pharmaceutical Sciences     Full-text available via subscription   (Followers: 12)
Advances in Pharmacology     Full-text available via subscription   (Followers: 16, SJR: 1.536, CiteScore: 3)
Advances in Physical Organic Chemistry     Full-text available via subscription   (Followers: 8, SJR: 0.574, CiteScore: 1)
Advances in Phytomedicine     Full-text available via subscription  
Advances in Planar Lipid Bilayers and Liposomes     Full-text available via subscription   (Followers: 3, SJR: 0.109, CiteScore: 1)
Advances in Plant Biochemistry and Molecular Biology     Full-text available via subscription   (Followers: 10)
Advances in Plant Pathology     Full-text available via subscription   (Followers: 5)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Protein Chemistry     Full-text available via subscription   (Followers: 19)
Advances in Protein Chemistry and Structural Biology     Full-text available via subscription   (Followers: 20, SJR: 0.791, CiteScore: 2)
Advances in Psychology     Full-text available via subscription   (Followers: 65)
Advances in Quantum Chemistry     Full-text available via subscription   (Followers: 6, SJR: 0.371, CiteScore: 1)
Advances in Radiation Oncology     Open Access   (Followers: 1, SJR: 0.263, CiteScore: 1)
Advances in Small Animal Medicine and Surgery     Hybrid Journal   (Followers: 3, SJR: 0.101, CiteScore: 0)
Advances in Space Biology and Medicine     Full-text available via subscription   (Followers: 6)
Advances in Space Research     Full-text available via subscription   (Followers: 404, SJR: 0.569, CiteScore: 2)
Advances in Structural Biology     Full-text available via subscription   (Followers: 5)
Advances in Surgery     Full-text available via subscription   (Followers: 12, SJR: 0.555, CiteScore: 2)
Advances in the Study of Behavior     Full-text available via subscription   (Followers: 34, SJR: 2.208, CiteScore: 4)
Advances in Veterinary Medicine     Full-text available via subscription   (Followers: 18)
Advances in Veterinary Science and Comparative Medicine     Full-text available via subscription   (Followers: 14)
Advances in Virus Research     Full-text available via subscription   (Followers: 5, SJR: 2.262, CiteScore: 5)
Advances in Water Resources     Hybrid Journal   (Followers: 47, SJR: 1.551, CiteScore: 3)
Aeolian Research     Hybrid Journal   (Followers: 6, SJR: 1.117, CiteScore: 3)
Aerospace Science and Technology     Hybrid Journal   (Followers: 351, SJR: 0.796, CiteScore: 3)
AEU - Intl. J. of Electronics and Communications     Hybrid Journal   (Followers: 8, SJR: 0.42, CiteScore: 2)
African J. of Emergency Medicine     Open Access   (Followers: 6, SJR: 0.296, CiteScore: 0)
Ageing Research Reviews     Hybrid Journal   (Followers: 11, SJR: 3.671, CiteScore: 9)
Aggression and Violent Behavior     Hybrid Journal   (Followers: 465, SJR: 1.238, CiteScore: 3)
Agri Gene     Hybrid Journal   (Followers: 1, SJR: 0.13, CiteScore: 0)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 17, SJR: 1.818, CiteScore: 5)
Agricultural Systems     Hybrid Journal   (Followers: 31, SJR: 1.156, CiteScore: 4)
Agricultural Water Management     Hybrid Journal   (Followers: 42, SJR: 1.272, CiteScore: 3)
Agriculture and Agricultural Science Procedia     Open Access   (Followers: 4)
Agriculture and Natural Resources     Open Access   (Followers: 3)
Agriculture, Ecosystems & Environment     Hybrid Journal   (Followers: 57, SJR: 1.747, CiteScore: 4)
Ain Shams Engineering J.     Open Access   (Followers: 5, SJR: 0.589, CiteScore: 3)
Air Medical J.     Hybrid Journal   (Followers: 6, SJR: 0.26, CiteScore: 0)
AKCE Intl. J. of Graphs and Combinatorics     Open Access   (SJR: 0.19, CiteScore: 0)
Alcohol     Hybrid Journal   (Followers: 12, SJR: 1.153, CiteScore: 3)
Alcoholism and Drug Addiction     Open Access   (Followers: 11)
Alergologia Polska : Polish J. of Allergology     Full-text available via subscription   (Followers: 1)
Alexandria Engineering J.     Open Access   (Followers: 1, SJR: 0.604, CiteScore: 3)
Alexandria J. of Medicine     Open Access   (Followers: 1, SJR: 0.191, CiteScore: 1)
Algal Research     Partially Free   (Followers: 10, SJR: 1.142, CiteScore: 4)
Alkaloids: Chemical and Biological Perspectives     Full-text available via subscription   (Followers: 2)
Allergologia et Immunopathologia     Full-text available via subscription   (Followers: 1, SJR: 0.504, CiteScore: 1)
Allergology Intl.     Open Access   (Followers: 5, SJR: 1.148, CiteScore: 2)
Alpha Omegan     Full-text available via subscription   (SJR: 3.521, CiteScore: 6)
ALTER - European J. of Disability Research / Revue Européenne de Recherche sur le Handicap     Full-text available via subscription   (Followers: 10, SJR: 0.201, CiteScore: 1)
Alzheimer's & Dementia     Hybrid Journal   (Followers: 52, SJR: 4.66, CiteScore: 10)
Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring     Open Access   (Followers: 4, SJR: 1.796, CiteScore: 4)
Alzheimer's & Dementia: Translational Research & Clinical Interventions     Open Access   (Followers: 4, SJR: 1.108, CiteScore: 3)
Ambulatory Pediatrics     Hybrid Journal   (Followers: 6)
American Heart J.     Hybrid Journal   (Followers: 53, SJR: 3.267, CiteScore: 4)
American J. of Cardiology     Hybrid Journal   (Followers: 58, SJR: 1.93, CiteScore: 3)
American J. of Emergency Medicine     Hybrid Journal   (Followers: 44, SJR: 0.604, CiteScore: 1)
American J. of Geriatric Pharmacotherapy     Full-text available via subscription   (Followers: 10)
American J. of Geriatric Psychiatry     Hybrid Journal   (Followers: 13, SJR: 1.524, CiteScore: 3)
American J. of Human Genetics     Hybrid Journal   (Followers: 34, SJR: 7.45, CiteScore: 8)
American J. of Infection Control     Hybrid Journal   (Followers: 29, SJR: 1.062, CiteScore: 2)
American J. of Kidney Diseases     Hybrid Journal   (Followers: 35, SJR: 2.973, CiteScore: 4)
American J. of Medicine     Hybrid Journal   (Followers: 48)
American J. of Medicine Supplements     Full-text available via subscription   (Followers: 3, SJR: 1.967, CiteScore: 2)
American J. of Obstetrics and Gynecology     Hybrid Journal   (Followers: 224, SJR: 2.7, CiteScore: 4)
American J. of Ophthalmology     Hybrid Journal   (Followers: 66, SJR: 3.184, CiteScore: 4)
American J. of Ophthalmology Case Reports     Open Access   (Followers: 5, SJR: 0.265, CiteScore: 0)
American J. of Orthodontics and Dentofacial Orthopedics     Full-text available via subscription   (Followers: 6, SJR: 1.289, CiteScore: 1)
American J. of Otolaryngology     Hybrid Journal   (Followers: 25, SJR: 0.59, CiteScore: 1)
American J. of Pathology     Hybrid Journal   (Followers: 28, SJR: 2.139, CiteScore: 4)
American J. of Preventive Medicine     Hybrid Journal   (Followers: 29, SJR: 2.164, CiteScore: 4)
American J. of Surgery     Hybrid Journal   (Followers: 38, SJR: 1.141, CiteScore: 2)
American J. of the Medical Sciences     Hybrid Journal   (Followers: 12, SJR: 0.767, CiteScore: 1)
Ampersand : An Intl. J. of General and Applied Linguistics     Open Access   (Followers: 7)
Anaerobe     Hybrid Journal   (Followers: 4, SJR: 1.144, CiteScore: 3)
Anaesthesia & Intensive Care Medicine     Full-text available via subscription   (Followers: 63, SJR: 0.138, CiteScore: 0)
Anaesthesia Critical Care & Pain Medicine     Full-text available via subscription   (Followers: 18, SJR: 0.411, CiteScore: 1)
Anales de Cirugia Vascular     Full-text available via subscription   (Followers: 1)
Anales de Pediatría     Full-text available via subscription   (Followers: 3, SJR: 0.277, CiteScore: 0)
Anales de Pediatría (English Edition)     Full-text available via subscription  
Anales de Pediatría Continuada     Full-text available via subscription  
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 5, SJR: 4.849, CiteScore: 10)
Analytica Chimica Acta     Hybrid Journal   (Followers: 42, SJR: 1.512, CiteScore: 5)
Analytical Biochemistry     Hybrid Journal   (Followers: 186, SJR: 0.633, CiteScore: 2)
Analytical Chemistry Research     Open Access   (Followers: 12, SJR: 0.411, CiteScore: 2)
Analytical Spectroscopy Library     Full-text available via subscription   (Followers: 12)
Anesthésie & Réanimation     Full-text available via subscription   (Followers: 2)
Anesthesiology Clinics     Full-text available via subscription   (Followers: 23, SJR: 0.683, CiteScore: 2)
Angiología     Full-text available via subscription   (SJR: 0.121, CiteScore: 0)
Angiologia e Cirurgia Vascular     Open Access   (Followers: 1, SJR: 0.111, CiteScore: 0)
Animal Behaviour     Hybrid Journal   (Followers: 203, SJR: 1.58, CiteScore: 3)

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Journal Cover
NeuroImage
Journal Prestige (SJR): 3.679
Citation Impact (citeScore): 6
Number of Followers: 70  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1053-8119 - ISSN (Online) 1095-9572
Published by Elsevier Homepage  [3161 journals]
  • Impact of years of blindness on neural circuits underlying auditory
           spatial representation
    • Abstract: Publication date: 1 May 2019Source: NeuroImage, Volume 191Author(s): Maria Bianca Amadeo, Claudio Campus, Monica Gori Early visual deprivation impacts negatively on spatial bisection abilities. Recently, an early (50–90 ms) ERP response, selective for sound position in space, has been observed in the visual cortex of sighted individuals during the spatial but not the temporal bisection task.Here, we clarify the role of vision on spatial bisection abilities and neural correlates by studying late blind individuals. Results highlight that a shorter period of blindness is linked to a stronger contralateral activation in the visual cortex and a better performance during the spatial bisection task. Contrarily, not lateralized visual activation and lower performance are observed in individuals with a longer period of blindness.To conclude, the amount of time spent without vision may gradually impact on neural circuits underlying the construction of spatial representations in late blind participants. These findings suggest a key relationship between visual deprivation and auditory spatial abilities in humans.
       
  • Acute stress alters the ‘default’ brain processing
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Wei Zhang, Mahur M. Hashemi, Reinoud Kaldewaij, Saskia B.J. Koch, Christian Beckmann, Floris Klumpers, Karin Roelofs Active adaptation to acute stress is essential for coping with daily life challenges. The stress hormone cortisol, as well as large scale re-allocations of brain resources have been implicated in this adaptation. Stress-induced shifts between large-scale brain networks, including salience (SN), central executive (CEN) and default mode networks (DMN), have however been demonstrated mainly under task-conditions. It remains unclear whether such network shifts also occur in the absence of ongoing task-demands, and most critically, whether these network shifts are predictive of individual variation in the magnitude of cortisol stress-responses.In a sample of 335 healthy participants, we investigated stress-induced functional connectivity changes (delta-FC) of the SN, CEN and DMN, using resting-state fMRI data acquired before and after a socially evaluated cold-pressor test and a mental arithmetic task. To investigate which network changes are associated with acute stress, we evaluated the association between cortisol increase and delta-FC of each network.Stress-induced cortisol increase was associated with increased connectivity within the SN, but with decreased coupling of DMN at both local (within network) and global (synchronization with brain regions also outside the network) levels.These findings indicate that acute stress prompts immediate connectivity changes in large-scale resting-state networks, including the SN and DMN in the absence of explicit ongoing task-demands. Most interestingly, this brain reorganization is coupled with individuals’ cortisol stress-responsiveness. These results suggest that the observed stress-induced network reorganization might function as a neural mechanism determining individual stress reactivity and, therefore, it could serve as a promising marker for future studies on stress resilience and vulnerability.
       
  • The association of health-related quality of life and cerebral gray matter
           volume in the context of aging: A voxel-based morphometry study with a
           general population sample
    • Abstract: Publication date: Available online 19 February 2019Source: NeuroImageAuthor(s): Stefanie Hahm, Martin Lotze, Martin Domin, Silke Schmidt Health-related quality of life is likely associated with the brain via processes relating to physiology, behavior, cognition, emotion and stress. Previous studies with small student or clinical samples have identified associations with gray matter volume in the anterior cingulate cortex, prefrontal cortex, insular cortex, (para)hippocampal area, amygdala, and precuneus. The present study investigated the association of gray matter volume of these brain areas with mental and physical components of health, as well as general health perception, measured with the 12-item Short Form Health Survey, in a large sample of 3027 participants from the Study of Health in Pomerania, using voxel-based morphometry for T1-weighted magnetic resonance imaging. Higher physical, but not mental, health-related quality of life and general health perception were associated with larger gray matter volume of the anterior cingulate cortex, medial prefrontal cortex, insular cortex, and the precuneus with a substantial decrease when controlling for lifestyle, comorbidity and symptoms. Age-stratified analyses revealed significantly higher partial correlations of physical health and left insular gray matter volume in the oldest age group. Our study emphasizes the importance of high medial prefrontal and anterior insula gray matter volume for health-related quality of life on the basis of a large sample size.
       
  • Contributions of non-primary cortical sources to auditory temporal
           processing
    • Abstract: Publication date: Available online 19 February 2019Source: NeuroImageAuthor(s): Ehsan Darestani Farahani, Jan Wouters, Astrid van Wieringen Temporal processing is essential for speech perception and directional hearing. However, the number and locations of cortical sources involved in auditory temporal processing are still a matter of debate. Using source reconstruction of human EEG responses, we show that, in addition to primary sources in the auditory cortices, sources outside the auditory cortex, designated as non-primary sources, are involved in auditory temporal processing. Non-primary sources within the left and right motor areas, the superior parietal lobe and the right occipital lobe were activated by amplitude-modulated stimuli, and were involved in the functional network. The robustness of these findings was checked for different stimulation conditions. The non-primary sources showed weaker phase-locking and lower activity than primary sources. These findings suggest that the non-primary sources belong to the non-primary auditory pathway. This pathway and non-primary sources detected in motor area explain how, in temporal prediction of upcoming stimuli and motor theory of speech perception, the motor area receives auditory inputs.
       
  • Age differences in specific neural connections within the Default Mode
           Network underlie theory of mind
    • Abstract: Publication date: Available online 19 February 2019Source: NeuroImageAuthor(s): Colleen Hughes, Brittany S. Cassidy, Joshua Faskowitz, Andrea Avena-Koenigsberger, Olaf Sporns, Anne C. Krendl Theory of mind (i.e., the ability to infer others' mental states) – a fundamental social cognitive ability – declines with increasing age. Prior investigations have focused on identifying task-evoked differences in neural activation that underlie these performance declines. However, these declines could also be related to dysregulation of the baseline, or ‘intrinsic’, functional connectivity of the brain. If so, age differences in intrinsic connectivity may provide novel insight into the mechanisms that contribute to poorer theory of mind in older adults. To examine this possibility, we assessed younger and older adults' theory of mind while they underwent task-based fMRI, as well as the intrinsic functional connectivity measured during resting-state within the (task-defined) theory of mind network. Older adults exhibited poorer theory of mind behavioral performance and weaker intrinsic connectivity within this network compared to younger adults. Intrinsic connectivity between the right temporoparietal junction and the right temporal pole mediated age differences in theory of mind. Specifically, older adults had weaker intrinsic connectivity between right temporoparietal junction and right temporal pole that explained their poorer theory of mind behavioral performance. These findings broaden our understanding of aging and social cognition and reveal more specific mechanisms of how aging impacts theory of mind.
       
  • Age-related alterations in axonal microstructure in the corpus callosum
           measured by high-gradient diffusion MRI
    • Abstract: Publication date: Available online 18 February 2019Source: NeuroImageAuthor(s): Qiuyun Fan, Qiyuan Tian, Ned A. Ohringer, Aapo Nummenmaa, Thomas Witzel, Sean M. Tobyne, Eric C. Klawiter, Choukri Mekkaoui, Bruce R. Rosen, Lawrence L. Wald, David H. Salat, Susie Y. Huang Cerebral white matter exhibits age-related degenerative changes during the course of normal aging, including decreases in axon density and alterations in axonal structure. Noninvasive approaches to measure these microstructural alterations throughout the lifespan would be invaluable for understanding the substrate and regional variability of age-related white matter degeneration. Recent advances in diffusion magnetic resonance imaging (MRI) have leveraged high gradient strengths to increase sensitivity toward axonal size and density in the living human brain. Here, we examined the relationship between age and indices of axon diameter and packing density using high-gradient strength diffusion MRI in 36 healthy adults (aged 22–72) in well-defined central white matter tracts in the brain. A recently validated method for inferring the effective axonal compartment size and packing density from diffusion MRI measurements acquired with 300 mT/m maximum gradient strength was applied to the in vivo human experiment to obtain indices of axon diameter and density in the corpus callosum, its sub-regions, and adjacent anterior and posterior fibers in the forceps minor and forceps major. The relationships between the axonal metrics, corpus callosum area and regional gray matter volume were also explored. Results revealed a significant increase in axon diameter index with advancing age in the whole corpus callosum. Similar analyses in sub-regions of the corpus callosum showed that age-related alterations in axon diameter index and axon density were most pronounced in the genu of the corpus callosum and relatively absent in the splenium, in keeping with findings from previous histological studies. The significance of these correlations was mirrored in the forceps minor and forceps major, consistent with previously reported decreases in FA in the forceps minor but not in the forceps major with age. Alterations in the axonal imaging metrics paralleled decreases in corpus callosum area and regional gray matter volume with age. Among older adults, results from cognitive testing suggested an association between larger effective compartment size in the corpus callosum, particularly within the genu of the corpus callosum, and lower scores on the Montreal Cognitive Assessment, largely driven by deficits in short-term memory. The current study suggests that high-gradient diffusion MRI may be sensitive to the axonal substrate of age-related white matter degeneration reflected in traditional DTI metrics and provides further evidence for regionally selective alterations in white matter microstructure with advancing age.
       
  • Amygdala-prefrontal cortex white matter tracts are widespread, variable
           and implicated in amygdala modulation in adolescents
    • Abstract: Publication date: Available online 18 February 2019Source: NeuroImageAuthor(s): Leigh G. Goetschius, Tyler C. Hein, Whitney I. Mattson, Nestor Lopez-Duran, Hailey L. Dotterer, Robert C. Welsh, Colter Mitchell, Luke W. Hyde, Christopher S. Monk The amygdala is critically involved in processing emotion. Through bidirectional connections, the prefrontal cortex (PFC) is hypothesized to influence amygdala reactivity. However, research that elucidates the nature of amygdala-PFC interactions – through mapping amygdala-prefrontal tracts, quantifying variability among tracts, and linking this variability to amygdala activation – is lacking. Using probabilistic tractography to map amygdala-prefrontal white matter connectivity in 142 adolescents, the present study found that white matter connectivity was greater between the amygdala and the subgenual cingulate, orbitofrontal (OFC), and dorsomedial (dmPFC) prefrontal regions than with the dorsal cingulate and dorsolateral regions. Then, using a machine-learning regression, we found that greater amygdala-PFC white matter connectivity related to attenuated amygdala reactivity. This effect was driven by amygdala white matter connectivity with the dmPFC and OFC, supporting implicit emotion processing theories which highlight the critical role of these regions in amygdala regulation. This study is among the first to map and compare specific amygdala-prefrontal white matter tracts and to relate variability in connectivity to amygdala activation, particularly among a large sample of adolescents from a well-sampled study. By examining the association between specific amygdala-PFC tracts and amygdala activation, the present study provides novel insight into the nature of this emotion-based circuit.
       
  • Separable neural representations of sound sources: Speaker identity and
           musical timbre
    • Abstract: Publication date: 1 May 2019Source: NeuroImage, Volume 191Author(s): Mattson Ogg, Dustin Moraczewski, Stefanie E. Kuchinsky, L. Robert Slevc Human listeners can quickly and easily recognize different sound sources (objects and events) in their environment. Understanding how this impressive ability is accomplished can improve signal processing and machine intelligence applications along with assistive listening technologies. However, it is not clear how the brain represents the many sounds that humans can recognize (such as speech and music) at the level of individual sources, categories and acoustic features. To examine the cortical organization of these representations, we used patterns of fMRI responses to decode 1) four individual speakers and instruments from one another (separately, within each category), 2) the superordinate category labels associated with each stimulus (speech or instrument), and 3) a set of simple synthesized sounds that could be differentiated entirely on their acoustic features. Data were collected using an interleaved silent steady state sequence to increase the temporal signal-to-noise ratio, and mitigate issues with auditory stimulus presentation in fMRI. Largely separable clusters of voxels in the temporal lobes supported the decoding of individual speakers and instruments from other stimuli in the same category. Decoding the superordinate category of each sound was more accurate and involved a larger portion of the temporal lobes. However, these clusters all overlapped with areas that could decode simple, acoustically separable stimuli. Thus, individual sound sources from different sound categories are represented in separate regions of the temporal lobes that are situated within regions implicated in more general acoustic processes. These results bridge an important gap in our understanding of cortical representations of sounds and their acoustics.
       
  • Prolonged functional development of the parahippocampal place area and
           occipital place area
    • Abstract: Publication date: 1 May 2019Source: NeuroImage, Volume 191Author(s): Tobias W. Meissner, Marisa Nordt, Sarah Weigelt Successful navigation of our surroundings is of high environmental relevance and involves processing of the visual scenery. Scene-processing undergoes a major behavioral improvement during childhood. However, possible neural changes that underlie this cognitive development in scene perception are understudied in comparison to other stimulus categories. We used a functional magnetic resonance imaging (fMRI) scene localizer and behavioral recognition and memory tasks in 7-8-year-olds, 11-12-year-olds, and adults to test whether scene-selective areas—the parahippocampal place area (PPA), the retrosplenial cortex (RSC), and the occipital place area (OPA)—show a change in volume and selectivity with age, and whether this change is correlated with behavioral perception and memory performance. We find that children have a smaller PPA and OPA than adults, while the size of RSC does not differ. Furthermore, selectivity for scenes in the PPA and the OPA, but not in the RSC, increases with age. This increase seems to be driven by both increasing responses to preferred stimuli and decreasing responses to non-preferred stimuli. Our findings extend previous knowledge about visual cortex development by unveiling the underlying mechanisms of age-related volume and selectivity increases in the scene network especially elucidating the poorly understood development of the OPA.
       
  • Exploring the limits of network topology estimation using diffusion-based
           tractography and tracer studies in the macaque cortex
    • Abstract: Publication date: 1 May 2019Source: NeuroImage, Volume 191Author(s): Kelly Shen, Alexandros Goulas, David S. Grayson, John Eusebio, Joseph S. Gati, Ravi S. Menon, Anthony R. McIntosh, Stefan Everling Reconstructing the anatomical pathways of the brain to study the human connectome has become an important endeavour for understanding brain function and dynamics. Reconstruction of the cortico-cortical connectivity matrix in vivo often relies on noninvasive diffusion-weighted imaging (DWI) techniques but the extent to which they can accurately represent the topological characteristics of structural connectomes remains unknown. We addressed this question by constructing connectomes using DWI data collected from macaque monkeys in vivo and with data from published invasive tracer studies. We found the strength of fiber tracts was well estimated from DWI and topological properties like degree and modularity were captured by tractography-based connectomes. Rich-club/core-periphery type architecture could also be detected but the classification of hubs using betweenness centrality, participation coefficient and core-periphery identification techniques was inaccurate. Our findings indicate that certain aspects of cortical topology can be faithfully represented in noninvasively-obtained connectomes while other network analytic measures warrant cautionary interpretations.
       
  • Attention modulates event-related spectral power in multisensory
           self-motion perception
    • Abstract: Publication date: 1 May 2019Source: NeuroImage, Volume 191Author(s): Ben Townsend, Joey K. Legere, Shannon O'Malley, Martin v. Mohrenschildt, Judith M. Shedden Humans integrate visual and physical (vestibular and proprioceptive) cues to motion during self-motion perception. Theta and alpha-band oscillations have been associated with the processing of visual motion (e.g. optic flow). Alpha and beta-band oscillations have been shown to be associated with sensory-motor processing (e.g. walking). The present study examined modulation of theta, alpha, and beta oscillations while participants made heading direction judgments during a passive self-motion task which required selective attention to one of the simultaneously presented visual or physical motion stimuli. Attention to physical (while ignoring visual) motion produced a different time course of changes in spectral power compared to attention to visual (while ignoring physical) motion. We observed weaker theta event-related synchronization (ERS), as well as stronger beta and later onset of alpha event-related desynchronization (ERD) in the attend-physical condition compared to the attend-visual condition. We observed individual differences in terms of ability to perform the task. Specifically, some participants were not able to ignore or discount the visual input when visual and physical heading direction was incongruent; this was reflected by similar event-related spectral power for both conditions. The results demonstrated a possible electrophysiological signature of the time course of 1) cue conflict (congruency effects), 2) attention to specific motion cues, and 3) individual differences in perceptual weighting of motion stimuli (high-vs. low-accuracy effects).
       
  • Performance of semi-automated hippocampal subfield segmentation methods
           across ages in a pediatric sample
    • Abstract: Publication date: 1 May 2019Source: NeuroImage, Volume 191Author(s): Margaret L. Schlichting, Michael L. Mack, Katharine F. Guarino, Alison R. Preston Episodic memory function has been shown to depend critically on the hippocampus. This region is made up of a number of subfields, which differ in both cytoarchitectural features and functional roles in the mature brain. Recent neuroimaging work in children and adolescents has suggested that these regions may undergo different developmental trajectories—a fact that has important implications for how we think about learning and memory processes in these populations. Despite the growing research interest in hippocampal structure and function at the subfield level in healthy young adults, comparatively fewer studies have been carried out looking at subfield development. One barrier to studying these questions has been that manual segmentation of hippocampal subfields—considered by many to be the best available approach for defining these regions—is laborious and can be infeasible for large cross-sectional or longitudinal studies of cognitive development. Moreover, manual segmentation requires some subjectivity and is not impervious to bias or error. In a developmental sample of individuals spanning 6–30 years, we assessed the degree to which two semi-automated segmentation approaches—one approach based on Automated Segmentation of Hippocampal Subfields (ASHS) and another utilizing Advanced Normalization Tools (ANTs)—approximated manual subfield delineation on each individual by a single expert rater. Our main question was whether performance varied as a function of age group. Across several quantitative metrics, we found negligible differences in subfield validity across the child, adolescent, and adult age groups, suggesting that these methods can be reliably applied to developmental studies. We conclude that ASHS outperforms ANTs overall and is thus preferable for analyses carried out in individual subject space. However, we underscore that ANTs is also acceptable and may be well-suited for analyses requiring normalization to a single group template (e.g., voxelwise analyses across a wide age range). Previous work has supported the use of such methods in healthy young adults, as well as several special populations such as older adults and those suffering from mild cognitive impairment. Our results extend these previous findings to show that ASHS and ANTs can also be used in pediatric populations as young as six.
       
  • The emergence of long-range language network structural covariance and
           language abilities
    • Abstract: Publication date: 1 May 2019Source: NeuroImage, Volume 191Author(s): Ting Qi, Gesa Schaadt, Riccardo Cafiero, Jens Brauer, Michael A. Skeide, Angela D. Friederici Language skills increase as the brain matures. Language processing, especially the comprehension of syntactically complex sentences, is supported by a brain network involving functional interactions between left inferior frontal and left temporal regions in the adult brain, with reduced functional interactions in children. Here, we examined the gray matter covariance of the cortical thickness network relevant for syntactic processing in relation to language abilities in preschool children (i.e., 5-year-olds) and analyzed the developmental changes of the cortical thickness covariance cross-sectionally by comparing preschool children, school age children, and adults. Further, to demonstrate the agreement of cortical thickness covariance and white matter connectivity, tractography analyses were performed. Covariance of language-relevant seeds in preschoolers was strongest in contralateral homologous regions. A more adult-like, significant cortical thickness covariance between left frontal and left temporal regions, however, was observed in preschoolers with advanced syntactic language abilities. By comparing the three age groups, we could show that the cortical thickness covariance pattern from the language-associated seeds develops progressively from restricted in preschoolers to widely-distributed brain regions in adults. In addition, our results suggest that the cortical thickness covariance difference of the left inferior frontal gyrus to superior temporal gyrus/sulcus between preschoolers and adults is accompanied by distinctions in the white matter tracts linking these two areas, with more mature white matter in the arcuate fasciculus in adults compared to preschoolers. These findings provide anatomical evidence for developmental changes in language both from the perspective of gray matter structure co-variation within the language network and white matter maturity as the anatomical substrate for the structural covariance.
       
  • Investigating the variability of cardiac pulse artifacts across heartbeats
           in simultaneous EEG-fMRI recordings: A 7T study
    • Abstract: Publication date: 1 May 2019Source: NeuroImage, Volume 191Author(s): João Jorge, Charlotte Bouloc, Lucie Bréchet, Christoph M. Michel, Rolf Gruetter Electroencephalography (EEG) recordings performed in magnetic resonance imaging (MRI) scanners are affected by complex artifacts caused by heart function, often termed pulse artifacts (PAs). PAs can strongly compromise EEG data quality, and remain an open problem for EEG-fMRI. This study investigated the properties and mechanisms of PA variability across heartbeats, which has remained largely unaddressed to date, and evaluated its impact on PA correction approaches. Simultaneous EEG-fMRI was performed at 7T on healthy participants at rest or under visual stimulation, with concurrent recordings of breathing and cardiac activity. PA variability was found to contribute to EEG variance with more than 500 μV2 at 7T, which extrapolates to 92 μV2 at 3T. Clustering analyses revealed that PA variability not only is linked to variations in head position/orientation, as previously hypothesized, but also, and more importantly, to the respiratory cycle and to heart rate fluctuations. The latter mechanisms are associated to short-timescale variability (even across consecutive heartbeats), and their importance varied across EEG channels. In light of this PA variability, three PA correction techniques were compared: average artifact subtraction (AAS), optimal basis sets (OBS), and an approach based on K-means clustering. All methods allowed the recovery of visual evoked potentials from the EEG data; nonetheless, OBS and K-means tended to outperform AAS, likely due to the inability of the latter in modeling short-timescale variability. Altogether, these results offer novel insights into the dynamics and underlying mechanisms of the pulse artifact, with important consequences for its correction, relevant to most EEG-fMRI applications.
       
  • Neural responses to heartbeats distinguish self from other during
           imagination
    • Abstract: Publication date: 1 May 2019Source: NeuroImage, Volume 191Author(s): Mariana Babo-Rebelo, Anne Buot, Catherine Tallon-Baudry Imagination is an internally-generated process, where one can make oneself or other people appear as protagonists of a scene. How does the brain tag the protagonist of an imagined scene as being oneself or someone else' Crucially, during imagination, neither external stimuli nor motor feedback are available to disentangle imagining oneself from imagining someone else. Here, we test the hypothesis that an internal mechanism based on the neural monitoring of heartbeats could distinguish between self and other. 23 participants imagined themselves (from a first-person perspective) or a friend (from a third-person perspective) in various scenarios, while their brain activity was recorded with magnetoencephalography and their cardiac activity was simultaneously monitored. We measured heartbeat-evoked responses, i.e. transients of neural activity occurring in response to each heartbeat, during imagination. The amplitude of heartbeat-evoked responses differed between imagining oneself and imagining a friend, in the precuneus and posterior cingulate regions bilaterally. Effect size was modulated by the daydreaming frequency scores of participants but not by their interoceptive abilities. These results could not be accounted for by other characteristics of imagination (e.g., the ability to adopt the perspective, valence or arousal), nor by cardiac parameters (e.g., heart rate) or arousal levels (e.g. arousal ratings, pupil diameter). Heartbeat-evoked responses thus appear as a neural marker distinguishing self from other during imagination.
       
  • An increase in sleep slow waves predicts better working memory performance
           in healthy individuals
    • Abstract: Publication date: 1 May 2019Source: NeuroImage, Volume 191Author(s): Fabio Ferrarelli, Rachel Kaskie, Srinivas Laxminarayan, Sridhar Ramakrishnan, Jaques Reifman, Anne Germain Sleep is imperative for brain health and well-being, and restorative sleep is associated with better cognitive functioning. Increasing evidence indicates that electrophysiological measures of sleep, especially slow wave activity (SWA), regulate the consolidation of motor and perceptual procedural memory. In contrast, the role of sleep EEG and SWA in modulating executive functions, including working memory (WM), has been far less characterized. Here, we investigated across-night changes in sleep EEG that may ameliorate WM performance. Participants (N = 25, M = 100%) underwent two consecutive nights with high-density EEG, along with N-back tasks, which were administered at three time points the day before and after the second night of sleep. Non-rapid eye movement sleep EEG power spectra, power topography, as well as several slow-wave parameters were computed and compared across nights. Improvers on the 1-back, but not non-improvers, showed a significant increase in SWA as well as in down slope and negative peak amplitude, in a fronto-parietal region, and these parameters increases predicted better WM performance. Overall, these findings show that slow-wave sleep has a beneficial effect on WM and that it can occur in the adult brain even after minimal training. This is especially relevant, when considering that WM and other executive function cognitive deficits are present in several neuropsychiatric disorders, and that slow-wave enhancing interventions can improve cognition, thus providing novel insights and treatment strategies for these patients.
       
  • Differentiation of functional networks during long-term memory retrieval
           in children and adolescents
    • Abstract: Publication date: 1 May 2019Source: NeuroImage, Volume 191Author(s): Samuel Fynes-Clinton, Lars Marstaller, Hana Burianová The processes that characterize the neural development of long-term memory (LTM) are largely unknown. In young adults, the degree of activation of a single large-scale memory network corresponds to the level of contextual detail involved; thus, differentiating between autobiographical, episodic, and semantic retrieval. In contrast to young adults, children and adolescents retrieve fewer contextual details, suggesting that they might not yet engage the entire memory circuitry and that this brain recruitment might lack the characteristic contextual differentiation found in adults. Twenty-one children (10–12 years of age), 20 adolescents (14–16 years of age), and 22 young adults (20–35 years of age) were assessed on a previously validated LTM retrieval task, while their brain activity was measured with functional magnetic resonance imaging. The results demonstrate that children, adolescents, and adults recruit a left-lateralized subset of the large-scale memory network, comprising semantic and language processing regions, with neither developmental group showing evidence of contextual differentiation within this network. Additionally, children and adolescents recruited occipital and parietal regions during all memory recall conditions, in contrast to adults who engaged the entire large-scale memory network, as described previously. Finally, a significant covariance between age and brain activation indicates that the reliance on occipital and parietal regions during memory retrieval decreases with age. These results suggest that both children and adolescents rely on semantic processing to retrieve long-term memories, which, we argue, may restrict the integration of contextual detail required for complex episodic and autobiographical memory retrieval.
       
  • Topographic organization of connections between prefrontal cortex and
           mediodorsal thalamus: Evidence for a general principle of indirect
           thalamic pathways between directly connected cortical areas
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Jessica M. Phillips, Lesenia R. Fish, Niranjan A. Kambi, Michelle J. Redinbaugh, Sounak Mohanta, Steven R. Kecskemeti, Yuri B. Saalmann Our ability to act flexibly, according to goals and context, is known as cognitive control. Hierarchical levels of control, reflecting different levels of abstraction, are represented across prefrontal cortex (PFC). Although the mediodorsal thalamic nucleus (MD) is extensively interconnected with PFC, the role of MD in cognitive control is unclear. Tract tracer studies in macaques, involving subsets of PFC areas, have converged on coarse MD-PFC connectivity principles; but proposed finer-grained topographic schemes, which constrain interactions between MD and PFC, disagree in many respects. To investigate a unifying topographic scheme, we performed probabilistic tractography on diffusion MRI data from eight macaque monkeys, and estimated the probable paths connecting MD with each of all 19 architectonic areas of PFC. We found a connectional topography where the orderly progression from ventromedial to anterior to posterolateral PFC was represented from anteromedial to posterolateral MD. The projection zones of posterolateral PFC areas in MD showed substantial overlap, and those of ventral and anteromedial PFC areas in MD overlapped. The exception was cingulate area 24: its projection zone overlapped with projections zones of all other PFC areas. Overall, our data suggest that nearby, functionally related, directly connected PFC areas have partially overlapping projection zones in MD, consistent with a role for MD in coordinating communication across PFC. Indeed, the organizing principle for PFC projection zones in MD appears to reflect the flow of information across the hierarchical, multi-level PFC architecture. In addition, cingulate area 24 may have privileged access to influence thalamocortical interactions involving all other PFC areas.
       
  • A critical assessment of data quality and venous effects in sub-millimeter
           fMRI
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Kendrick Kay, Keith W. Jamison, Luca Vizioli, Ruyuan Zhang, Eshed Margalit, Kamil Ugurbil Advances in hardware, pulse sequences, and reconstruction techniques have made it possible to perform functional magnetic resonance imaging (fMRI) at sub-millimeter resolution while maintaining high spatial coverage and acceptable signal-to-noise ratio. Here, we examine whether sub-millimeter fMRI can be used as a routine method for obtaining accurate measurements of fine-scale local neural activity. We conducted fMRI in human visual cortex during a simple event-related visual experiment (7 T, gradient-echo EPI, 0.8-mm isotropic voxels, 2.2-s sampling rate, 84 slices), and developed analysis and visualization tools to assess the quality of the data. Our results fall along three lines of inquiry. First, we find that the acquired fMRI images, combined with appropriate surface-based processing, provide reliable and accurate measurements of fine-scale blood oxygenation level dependent (BOLD) activity patterns. Second, we show that the highly folded structure of cortex causes substantial biases on spatial resolution and data visualization. Third, we examine the well-recognized issue of venous contributions to fMRI signals. In a systematic assessment of large sections of cortex measured at a fine scale, we show that time-averaged T2*-weighted EPI intensity is a simple, robust marker of venous effects. These venous effects are unevenly distributed across cortex, are more pronounced in gyri and outer cortical depths, and are, to a certain degree, in consistent locations across subjects relative to cortical folding. Furthermore, we show that these venous effects are strongly correlated with BOLD responses evoked by the experiment. We conclude that sub-millimeter fMRI can provide robust information about fine-scale BOLD activity patterns, but special care must be exercised in visualizing and interpreting these patterns, especially with regards to the confounding influence of the brain's vasculature. To help translate these methodological findings to neuroscience research, we provide practical suggestions for both high-resolution and standard-resolution fMRI studies.
       
  • Emerging neural specialization of the ventral occipitotemporal cortex to
           characters through phonological association learning in preschool children
           
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Georgette Pleisch, Iliana I. Karipidis, Christian Brauchli, Martina Röthlisberger, Christoph Hofstetter, Philipp Stämpfli, Susanne Walitza, Silvia Brem The ventral occipitotemporal (vOT) cortex serves as a core region for visual processing, and specific areas of this region show preferential activation for various visual categories such as faces and print. The emergence of such functional specialization in the human cortex represents a pivotal developmental process, which provides a basis for targeted and efficient information processing. For example, functional specialization to print in the left vOT is an important prerequisite for fluent reading. However, it remains unclear, which processes initiate the preferential cortical activations to characters arising in the vOT during child development. Using a multimodal neuroimaging approach with preschool children at familial risk for developmental dyslexia, we demonstrate how varying levels of expertise modulate the neural response to single characters, which represent the building blocks of print units. The level of expertise to characters was manipulated firstly through brief training of false-font speech–sound associations and secondly by comparing characters for which children differed in their level of familiarity and expertise accumulated through abundant exposure in their everyday environment. Neural correlates of character processing were tracked with simultaneous high-density electroencephalography and functional magnetic resonance imaging in a target detection task. We found training performance and expertise-dependent modulation of the visual event-related potential around 220 ms (N1) and the corresponding vOT activation. Additionally, trained false-font characters revealed stronger functional connectivity between the left fusiform gyrus (FFG) seed and left superior parietal/lateral occipital cortex regions with higher training performance. In sum, our results demonstrate that learning artificial-character speech–sound associations enhances activation to trained characters in the vOT and that the magnitude of this activation and the functional connectivity of the left FFG to the parieto-occipital cortex depends on learning performance. This pattern of results suggests emerging development of the reading network after brief training that parallels network specialization during reading acquisition.
       
  • I feel what I do: Relating interoceptive processes and reward-related
           behavior
    • Abstract: Publication date: Available online 16 February 2019Source: NeuroImageAuthor(s): Amanda C. Marshall, Antje Gentsch, Anna-Lucia Blum, Christina Bröring, Simone Schütz-Bosbach Interoceptive signalling has been shown to contribute to action regulation and action experience. Here, we assess whether motor behaviour can be influenced by anticipated homeostatic feeling states induced through different predictable contexts. Participants performed a reward incentive paradigm in which accurate responses increased (gain) or avoided the depletion (averted loss) of a credit score. Across two types of blocks, we varied the predictability of the outcome state. In predictable blocks, a cue signalled a gain, loss or control trial (motor response did not affect the credit score). This allowed participants to anticipate the interoceptive feeling state associated with the outcome. In unpredictable blocks, the cue had no relation to the type of outcome. Thus, participants were unable to anticipate the feeling state it produced. Via EEG, we measured the Heartbeat Evoked Potential (HEP) and the Contingent Negative Variation (CNV) as indices of interoceptive and motor processing respectively. In addition, we measured feedback P3 amplitude following outcome presentation and accuracy and reaction times of the required motor response. We observed higher HEP and CNV amplitudes as well as faster and more accurate motor responses in predictable compared to unpredictable outcome blocks. Similarly, feedback-related P3 amplitudes were significantly lower for predictable relative to unpredictable outcomes. Crucially, HEP amplitudes measured prior to feedback predicted feedback-related P3 amplitudes for anticipated outcome events. Results suggest that accurate anticipation of homeostatic feeling states associated with gain, loss or control outcomes facilitates motor execution and outcome evaluation. Findings are hereby the first to empirically assess the link between interoceptive and motor domains and provide primary evidence for a joint processing structure.
       
  • Reliability of supraspinal correlates to lower urinary tract stimulation
           in healthy participants – A fMRI study
    • Abstract: Publication date: Available online 15 February 2019Source: NeuroImageAuthor(s): Matthias Walter, Lorenz Leitner, Lars Michels, Martina D. Liechti, Patrick Freund, Thomas M. Kessler, Spyros Kollias, Ulrich Mehnert Previous functional neuroimaging studies provided evidence for a specific supraspinal network involved in lower urinary tract (LUT) control. However, data on the reliability of blood oxygenation level-dependent (BOLD) signal changes during LUT task-related functional magnetic resonance imaging (fMRI) across separate measurements are lacking. Proof of the latter is crucial to evaluate whether fMRI can be used to assess supraspinal responses to LUT treatments.Therefore, we prospectively assessed task-specific supraspinal responses from 20 healthy participants undergoing two fMRI measurements (test-retest) within 5–8 weeks. The fMRI measurements, conducted in a 3T magnetic resonance (MR) scanner, comprised a block design of repetitive bladder filling and drainage using an automated MR-compatible and MR-synchronized infusion-drainage device. Following transurethral catheterization and bladder pre-filling with body warm saline until participants perceived a persistent desire to void (START condition), fMRI was recorded during repetitive blocks (each 15 s) of INFUSION and WITHDRAWAL of 100 mL body warm saline into respectively from the bladder. BOLD signal changes were calculated for INFUSION minus START. In addition to whole brain analysis, we assessed BOLD signal changes within multiple ‘a priori’ region of interest (ROI), i.e. brain areas known to be involved in the LUT control from previous literature. To evaluate reliability of the fMRI results between visits, we applied different types of analyses: coefficient of variation (CV), intraclass correlation coefficient (ICC), Sørensen-Dice index, Bland-Altman method, and block-wise BOLD signal comparison.All participants completed the study without adverse events. The desire to void was rated significantly higher for INFUSION compared to START or WITHDRAWAL at both measurements without any effect of visit. At whole brain level, significant (p 
       
  • Distinct visuo-motor brain dynamics for real-world objects versus planar
           images
    • Abstract: Publication date: Available online 15 February 2019Source: NeuroImageAuthor(s): Francesco Marini, Katherine A. Breeding, Jacqueline C. Snow Ultimately, we aim to generalize and translate scientific knowledge to the real world, yet current understanding of human visual perception is based predominantly on studies of two-dimensional (2-D) images. Recent cognitive-behavioral evidence shows that real objects are processed differently to images, although the neural processes that underlie these differences are unknown. Because real objects (unlike images) afford actions, they may trigger stronger or more prolonged activation in neural populations for visuo-motor action planning. Here, we recorded electroencephalography (EEG) when human observers viewed real-world three-dimensional (3-D) objects or closely matched 2-D images of the same items. Although responses to real objects and images were similar overall, there were critical differences. Compared to images, viewing real objects triggered stronger and more sustained event-related desynchronization (ERD) in the μ frequency band (8–13 Hz) – a neural signature of automatic motor preparation. Event-related potentials (ERPs) revealed a transient, early occipital negativity for real objects (versus images), likely reflecting 3-D stereoscopic differences, and a late sustained parietal amplitude modulation consistent with an ‘old-new’ memory advantage for real objects over images. Together, these findings demonstrate that real-world objects trigger stronger and more sustained action-related brain responses than images do. These results highlight important similarities and differences between brain responses to images and richer, more ecologically relevant, real-world objects.
       
  • Desynchronizing to be faster' Perceptual- and attentional-modulation
           of brain rhythms at the sub-millisecond scale
    • Abstract: Publication date: Available online 14 February 2019Source: NeuroImageAuthor(s): Yasuki Noguchi, Yi Xia, Ryusuke Kakigi Neural oscillatory signals has been associated with many high-level functions (e.g. attention and working memory), because they reflect correlated behaviors of neural population that would facilitate the information transfer in the brain. On the other hand, a decreased power of oscillation (event-related desynchronization, ERD) has been associated with an irregular state in which many neurons behave in an uncorrelated manner. In contrast to this view, here we show that the human ERD is linked to the increased regularity of oscillatory signals. Using magnetoencephalography, we found that presenting a visual stimulus not only induced a decrease in power of alpha (8–12 Hz) to beta (13–30 Hz) rhythms in the contralateral visual cortex but also reduced the mean and variance of their inter-peak intervals (IPIs). This indicates that the suppressed alpha/beta rhythms became faster (reduced mean) and more regular (reduced variance) during visual stimulation. The same changes in IPIs, especially those of beta rhythm, were observed when subjects allocated their attention to a contralateral visual field. Those results revealed a new role of the event-related decrease in alpha/beta power and further suggested that our brain regulates and accelerates a clock for neural computations by actively suppressing the oscillation amplitude in task-relevant regions.
       
  • Hierarchical complexity of the adult human structural connectome
    • Abstract: Publication date: Available online 14 February 2019Source: NeuroImageAuthor(s): Keith Smith, Mark E. Bastin, Simon R. Cox, Maria C. Valdés Hernández, Stewart Wiseman, Javier Escudero, Catherine Sudlow The structural network of the human brain has a rich topology which many have sought to characterise using standard network science measures and concepts. However, this characterisation remains incomplete and the non-obvious features of this topology have largely confounded attempts towards comprehensive constructive modelling. This calls for new perspectives. Hierarchical complexity is an emerging paradigm of complex network topology based on the observation that complex systems are composed of hierarchies within which the roles of hierarchically equivalent nodes display highly variable connectivity patterns. Here we test the hierarchical complexity of the human structural connectomes of a group of seventy-nine healthy adults. Binary connectomes are found to be more hierarchically complex than three benchmark random network models. This provides a new key description of brain structure, revealing a rich diversity of connectivity patterns within hierarchically equivalent nodes. Dividing the connectomes into four tiers based on degree magnitudes indicates that the most complex nodes are neither those with the highest nor lowest degrees but are instead found in the middle tiers. Spatial mapping of the brain regions in each hierarchical tier reveals consistency with the current anatomical, functional and neuropsychological knowledge of the human brain. The most complex tier (Tier 3) involves regions believed to bridge high-order cognitive (Tier 1) and low-order sensorimotor processing (Tier 2). We then show that such diversity of connectivity patterns aligns with the diversity of functional roles played out across the brain, demonstrating that hierarchical complexity can characterise functional diversity strictly from the network topology.Graphical abstractImage 1
       
  • The representation of symmetry in multi-voxel response patterns and
           functional connectivity throughout the ventral visual stream
    • Abstract: Publication date: Available online 13 February 2019Source: NeuroImageAuthor(s): Chayenne Van Meel, Annelies Baeck, Céline R. Gillebert, Johan Wagemans, Hans P. Op de Beeck Several computational models explain how symmetry might be detected and represented in the human brain. However, while there is an abundance of psychophysical studies on symmetry detection and several neural studies showing where and when symmetry is detected in the brain, important questions remain about how this detection happens and how symmetric patterns are represented. We studied the representation of (vertical) symmetry in regions of the ventral visual stream, using multi-voxel pattern analyses (MVPA) and functional connectivity analyses. Our results suggest that neural representations gradually change throughout the ventral visual stream, from very similar part-based representations for symmetrical and asymmetrical stimuli in V1 and V2, over increasingly different representations for symmetrical and asymmetrical stimuli which are nevertheless still part-based in both V3 and V4, to a more holistic representation for symmetrical compared to asymmetrical stimuli in high-level LOC. This change in representations is accompanied by increased communication between left and right retinotopic areas, evidenced by higher interhemispheric functional connectivity during symmetry perception in areas V2 and V4.
       
  • Left perirhinal cortex codes for semantic similarity between written words
           defined from cued word association
    • Abstract: Publication date: Available online 10 February 2019Source: NeuroImageAuthor(s): Antonietta Gabriella Liuzzi, Patrick Dupont, Ronald Peeters, Rose Bruffaerts, Simon De Deyne, Gert Storms, Rik Vandenberghe Knowledge of visual and nonvisual attributes of concrete entities is distributed over neocortical uni- and polymodal association cortex. Here we investigated the role of left perirhinal cortex in explicit knowledge retrieval from written words. We examined whether it extended across visual and nonvisual properties, animate and inanimate entities, how this differed from picture input and how specific it was for perirhinal cortex compared to surrounding structures. The semantic similarity between stimuli was determined on the basis of a word association-based model. Eighteen participants participated in this event-related fMRI experiment. During property verification, the left perirhinal cortex coded for the similarity in meaning between written words. No differences were found between visual and nonvisual properties or between animate and inanimate entities. Among the surrounding regions, a semantic similarity effect for written words was also present in the left parahippocampal gyrus, but not in the hippocampus nor in the right perirhinal cortex. Univariate analysis revealed higher activity for visual property verification in visual processing regions and for nonvisual property verification in an extended system encompassing the superior temporal sulcus along its anterior-posterior axis, the inferior and the superior frontal gyrus. The association strength between the concept and the property correlated positively with fMRI response amplitude in visual processing regions, and negatively with response amplitude in left inferior and superior frontal gyrus. The current findings establish that input-modality determines the semantic similarity effect in left perirhinal cortex more than the content of the knowledge retrieved or the semantic control demand do. We propose that left perirhinal cortex codes for the association between a concrete written word and the object it refers to and operates as a connector hub linking written word input to the distributed cortical representation of word meaning.
       
  • Neural correlates of online cooperation during joint force production
    • Abstract: Publication date: Available online 7 February 2019Source: NeuroImageAuthor(s): Masaki O. Abe, Takahiko Koike, Shuntaro Okazaki, Sho K. Sugawara, Kohske Takahashi, Katsumi Watanabe, Norihiro Sadato During joint action, two or more persons depend on each other to accomplish a goal. This mutual recursion, or circular dependency, is one of the characteristics of cooperation. To evaluate the neural substrates of cooperation, we conducted a hyperscanning functional MRI study in which 19 dyads performed a joint force-production task. The goal of the task was to match their average grip forces to the target value (20% of their maximum grip forces) through visual feedback over a 30-s period; the task required taking into account other-produced force to regulate the self-generated one in real time, which represented cooperation. Time-series data of the dyad's exerted grip forces were recorded, and the noise contribution ratio (NCR), a measure of influence from the partner, was computed using a multivariate autoregressive model to identify the degree to which each participant's grip force was explained by that of their partner's, i.e., the degree of cooperation. Compared with the single force-production task, the joint task enhanced the NCR and activated the mentalizing system, including the medial prefrontal cortex, precuneus, and bilateral posterior subdivision of the temporoparietal junction (TPJ). In addition, specific activation of the anterior subdivision of the right TPJ significantly and positively correlated with the NCR across participants during the joint task. The effective connectivity of the anterior to posterior TPJ was upregulated when participants coordinated their grip forces. Finally, the joint task enhanced cross-brain functional connectivity of the right anterior TPJ, indicating shared attention toward the temporal patterns of the motor output of the partner. Since the posterior TPJ is part of the mentalizing system for tracking the intention of perceived agents, our findings indicate that cooperation, i.e., the degree of adjustment of individual motor output depending on that of the partner, is mediated by the interconnected subdivisions of the right TPJ.
       
  • Effects of age on across-participant variability of cortical reinstatement
           effects
    • Abstract: Publication date: Available online 5 February 2019Source: NeuroImageAuthor(s): Preston P. Thakral, Tracy H. Wang, Michael D. Rugg Using functional magnetic resonance imaging data, we assessed whether across-participant variability of content-selective retrieval-related neural activity differs with age. We addressed this question by employing across-participant multi-voxel pattern analysis (MVPA), predicting that increasing age would be associated with reduced variability of retrieval-related cortical reinstatement across participants. During study, 24 young and 24 older participants viewed objects and concrete words. Test items comprised studied words, names of studied objects, and unstudied words. Participants judged whether the items were recollected, familiar, or new by making ‘Remember’, ‘Know’ and ‘New’ responses, respectively. MVPA was conducted on each region belonging to the ‘core recollection network’, dorsolateral prefrontal cortex, and a previously identified content-selective voxel set. A leave-one-participant-out classification approach was employed whereby a classifier was trained on a subset of participants and tested on the data from a yoked pair of held-out participants. Classifiers were trained on the study phase data to discriminate the study trials as a function of content (picture or word). The classifiers were then applied to the test phase data to discriminate studied test words according to their study condition. In all of the examined regions, classifier performance demonstrated little or no sensitivity to age and, for the test data, was robustly above chance. Thus, there was little evidence to support the hypothesis that across-participant variability of retrieval-related cortical reinstatement differs with age. The findings extend prior evidence by demonstrating that content-selective cortical reinstatement is sufficiently invariant to support across-participant multi-voxel classification across the healthy adult lifespan.
       
  • Individual-specific fMRI-Subspaces improve functional connectivity
           prediction of behavior
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Rajan Kashyap, Ru Kong, Sagarika Bhattacharjee, Jingwei Li, Juan Zhou, B.T. Thomas Yeo There is significant interest in using resting-state functional connectivity (RSFC) to predict human behavior. Good behavioral prediction should in theory require RSFC to be sufficiently distinct across participants; if RSFC were the same across participants, then behavioral prediction would obviously be poor. Therefore, we hypothesize that removing common resting-state functional magnetic resonance imaging (rs-fMRI) signals that are shared across participants would improve behavioral prediction. Here, we considered 803 participants from the human connectome project (HCP) with four rs-fMRI runs. We applied the common and orthogonal basis extraction (COBE) technique to decompose each HCP run into two subspaces: a common (group-level) subspace shared across all participants and a subject-specific subspace. We found that the first common COBE component of the first HCP run was localized to the visual cortex and was unique to the run. On the other hand, the second common COBE component of the first HCP run and the first common COBE component of the remaining HCP runs were highly similar and localized to regions within the default network, including the posterior cingulate cortex and precuneus. Overall, this suggests the presence of run-specific (state-specific) effects that were shared across participants. By removing the first and second common COBE components from the first HCP run, and the first common COBE component from the remaining HCP runs, the resulting RSFC improves behavioral prediction by an average of 11.7% across 58 behavioral measures spanning cognition, emotion and personality.Graphical abstractImage 1
       
  • Reducing power line noise in EEG and MEG data via spectrum interpolation
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Sabine Leske, Sarang S. Dalal Electroencephalographic (EEG) and magnetoencephalographic (MEG) signals can often be exposed to strong power line interference at 50 or 60 Hz. A widely used method to remove line noise is the notch filter, but it comes with the risk of potentially severe signal distortions. Among other approaches, the Discrete Fourier Transform (DFT) filter and CleanLine have been developed as alternatives, but they may fail to remove power line noise of highly fluctuating amplitude. Here we introduce spectrum interpolation as a new method to remove line noise in the EEG and MEG signal. This approach had been developed for electromyographic (EMG) signals, and combines the advantages of a notch filter, while synthetic test signals indicate that it introduces less distortion in the time domain. The effectiveness of this method is compared to CleanLine, the notch (Butterworth) and DFT filter. In order to quantify the performance of these three methods, we used synthetic test signals and simulated power line noise with fluctuating amplitude and abrupt on- and offsets that were added to an MEG dataset free of line noise. In addition, all methods were applied to EEG data with massive power line noise due to acquisition in unshielded settings. We show that spectrum interpolation outperforms the DFT filter and CleanLine, when power line noise is nonstationary. At the same time, spectrum interpolation performs equally well as the notch filter in removing line noise artifacts, but shows less distortions in the time domain in many common situations.
       
  • Context-dependent modulation of cognitive control involves different
           temporal profiles of fronto-parietal activity
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Bart Aben, Cristian Buc Calderon, Laurens Van der Cruyssen, Doerte Picksak, Eva Van den Bussche, Tom Verguts To efficiently deal with quickly changing task demands, we often need to organize our behaviour on different time scales. For example, to ignore irrelevant and select relevant information, cognitive control might be applied in reactive (short time scale) or proactive (long time scale) mode. These two control modes play a pivotal role in cognitive-neuroscientific theorizing but the temporal dissociation of the underlying neural mechanisms is not well established empirically. In this fMRI study, a cognitive control task was administered in contexts with mainly congruent (MC) and mainly incongruent (MI) trials to induce reactive and proactive control, respectively. Based on behavioural profiles, we expected cognitive control in the MC context to be characterized by transient activity (measured on-trial) in task-relevant areas. In the MI context, cognitive control was expected to be reflected in sustained activity (measured in the intertrial interval) in similar or different areas. Results show that in the MC context, on-trial transient activity (incongruent – congruent trials) was increased in fronto-parietal areas, compared to the MI context. These areas included dorsolateral prefrontal cortex (dlPFC) and intraparietal sulcus (IPS). In the MI context, sustained activity in similar fronto-parietal areas during the intertrial interval was increased, compared to the MC context. These results illuminate how context-dependent reactive and proactive control subtend the same brain areas but operate on different time scales.
       
  • Multi-modal neuroimaging of dual-task walking: Structural MRI and fNIRS
           analysis reveals prefrontal grey matter volume moderation of brain
           activation in older adults
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Mark E. Wagshul, Melanie Lucas, Kenny Ye, Meltem Izzetoglu, Roee Holtzer It has been well established over the last two decades that walking is not merely an automatic, motoric activity; it also utilizes executive function circuits, which play an increasingly important role in walking for older people and those with mobility and cognitive deficits. Dual-task walking, such as walking while performing a cognitive task, is a necessary skill for everyday functioning, and has been shown to activate prefrontal lobe areas in healthy older people. Another well-established point in healthy aging is the loss of grey matter, and in particular loss of frontal lobe grey matter volume. However, the relationship between increased frontal lobe activity during dual-task walking and loss of frontal grey matter in healthy aging remains unknown.In the current study, we combined oxygenated hemoglobin (HbO2) data from functional near-infrared spectroscopy (fNIRS), taken during dual-task walking, with structural MRI volumetrics in a cohort of healthy older subjects to identify this relationship. We studied fifty-five relatively healthy, older participants (≥65 years) during two separate sessions: fNIRS to measure HbO2 changes between single-task (i.e., normal walking) and dual-task walking-while-talking, and high-resolution, structural MRI to measure frontal lobe grey matter volumes. Linear mixed effects modeling was utilized to determine the moderation effect of grey matter volume on the change in prefrontal oxygenated hemoglobin between the two walking tasks, while controlling for covariates including task performance. We found a highly significant interaction effect between frontal grey matter volume and task on HbO2 levels (p 
       
  • Neuron density fundamentally relates to architecture and connectivity of
           the primate cerebral cortex
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Sarah F. Beul, Claus C. Hilgetag Studies of structural brain connectivity have revealed many intriguing features of complex cortical networks. To advance integrative theories of cortical organization, an understanding is required of how connectivity interrelates with other aspects of brain structure. Recent studies have suggested that interareal connectivity may be related to a variety of macroscopic as well as microscopic architectonic features of cortical areas. However, it is unclear how these features are inter-dependent and which of them most strongly and fundamentally relate to structural corticocortical connectivity. Here, we systematically investigated the relation of a range of microscopic and macroscopic architectonic features of cortical organization, namely layer III pyramidal cell soma cross section, dendritic synapse count, dendritic synapse density and dendritic tree size as well as area neuron density, to multiple properties of cortical connectivity, using a comprehensive, up-to-date structural connectome of the primate brain. Importantly, relationships were investigated by multi-variate analyses to account for the interrelations of features. Of all considered factors, the classical architectonic parameter of neuron density most strongly and consistently related to essential features of cortical connectivity (existence and laminar patterns of projections, area degree), and in conjoint analyses largely abolished effects of cellular morphological features. These results confirm neuron density as a central architectonic indicator of the primate cerebral cortex that is closely related to essential aspects of brain connectivity and is also highly indicative of further features of the architectonic organization of cortical areas, such as the considered cellular morphological measures. Our findings integrate several aspects of cortical micro- and macroscopic organization, with implications for cortical development and function.
       
  • Sex-specific effects of central adiposity and inflammatory markers on
           limbic microstructure
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Claudia Metzler-Baddeley, Jilu P. Mole, Erika Leonaviciute, Rebecca Sims, Emma J. Kidd, Benyamin Ertefai, Aurora Kelso-Mitchell, Florence Gidney, Fabrizio Fasano, John Evans, Derek K. Jones, Roland J. Baddeley Midlife obesity is a risk factor of late onset Alzheimer's disease (LOAD) but why this is the case remains unknown. As systemic inflammation is involved in both conditions, obesity-related neuroinflammation may contribute to damage in limbic structures important in LOAD. Here, we investigated the hypothesis that systemic inflammation would mediate central obesity related effects on limbic tissue microstructure in 166 asymptomatic individuals (38–71 years old). We employed MRI indices sensitive to myelin and neuroinflammation [macromolecular proton fraction (MPF) and kf] from quantitative magnetization transfer (qMT) together with indices from neurite orientation dispersion and density imaging (NODDI) to investigate the effects of central adiposity on the fornix, parahippocampal cingulum, uncinate fasciculus (compared with whole brain white matter and corticospinal tract) and the hippocampus. Central obesity was assessed with the Waist Hip Ratio (WHR) and abdominal visceral and subcutaneous fat area fractions (VFF, SFF), and systemic inflammation with blood plasma concentrations of leptin, adiponectin, C-reactive protein and interleukin 8. Men were significantly more centrally obese and had higher VFF than women. Individual differences in WHR and in VFF were negatively correlated with differences in fornix MPF and kf, but not with any differences in neurite microstructure. In women, age mediated the effects of VFF on fornix MPF and kf, whilst in men differences in the leptin and adiponectin ratio fully mediated the effect of WHR on fornix MPF. These results suggest that visceral fat related systemic inflammation may damage myelin-related properties of the fornix, a key limbic structure known to be involved in LOAD.
       
  • Directional tuning for eye and arm movements in overlapping regions in
           human posterior parietal cortex
    • Abstract: Publication date: Available online 13 February 2019Source: NeuroImageAuthor(s): Caterina Magri, Sara Fabbri, Alfonso Caramazza, Angelika Lingnau A network of frontal and parietal regions is known to be recruited during the planning and execution of arm and eye movements. While movements of the two effectors are typically coupled with each other, it remains unresolved how information is shared between them. Here we aimed to identify regions containing neuronal populations that show directional tuning for both arm and eye movements. In two separate fMRI experiments, the same participants were scanned while performing a center-out arm or eye movement task. Using a whole-brain searchlight-based representational similarity analysis (RSA), we found that a bilateral region in the posterior superior parietal lobule represents both arm and eye movement direction, thus extending previous findings in monkeys.
       
  • Modulation of phase-locked neural responses to speech during different
           arousal states is age-dependent
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Guangting Mai, Tim Schoof, Peter Howell Phase-locked responses are vital for auditory perception and they may vary with participants' arousal state and age. Two phase-locked neural responses that reflect fine-grained acoustic properties of speech were examined in the current study: the frequency-following response (FFR) to the speech fundamental frequency (F0), which originates primarily from the auditory brainstem, and the theta-band phase-locked response (θ-PLV) to the speech envelope that originates from the auditory cortices. The ways these responses were affected by arousal in adults across a wide age-range (19–75 years) were examined. Extracts from electroencephalographic (EEG) responses to repeated syllables were classified into either high or low arousal state based on the occurrence of sleep spindles. The magnitudes of both FFRs and θ-PLVs were statistically greater in the high, than in the low, arousal state. The difference in θ-PLV between the two arousal states was significantly associated with sleep spindle density in the young, but not the older, adults. The results show that (1) arousal affects phase-locked processing of speech at cortical/sub-cortical sensory levels; and that (2) there is an interplay between aging and arousal state which indicates that sleep spindles have an age-dependent neuro-regulatory role on cortical processes. The results lay the grounds for studying how cognitive states affect early-stage neural activity in the auditory system across the lifespan.
       
  • Reproducibility of functional brain alterations in major depressive
           disorder: Evidence from a multisite resting-state functional MRI study
           with 1,434 individuals
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Mingrui Xia, Tianmei Si, Xiaoyi Sun, Qing Ma, Bangshan Liu, Li Wang, Jie Meng, Miao Chang, Xiaoqi Huang, Ziqi Chen, Yanqing Tang, Ke Xu, Qiyong Gong, Fei Wang, Jiang Qiu, Peng Xie, Lingjiang Li, Yong He, DIDA-Major Depressive Disorder Working Group Resting-state functional MRI (R-fMRI) studies have demonstrated widespread alterations in brain function in patients with major depressive disorder (MDD). However, a clear and consistent conclusion regarding a repeatable pattern of MDD-relevant alterations is still limited due to the scarcity of large-sample, multisite datasets. Here, we address this issue by including a large R-fMRI dataset with 1434 participants (709 patients with MDD and 725 healthy controls) from five centers in China. Individual functional activity maps that represent very local to long-range connections are computed using the amplitude of low-frequency fluctuations, regional homogeneity and distance-related functional connectivity strength. The reproducibility analyses involve different statistical strategies, global signal regression, across-center consistency, clinical variables, and sample size. We observed significant hypoactivity in the orbitofrontal, sensorimotor, and visual cortices and hyperactivity in the frontoparietal cortices in MDD patients compared to the controls. These alterations are not affected by different statistical analysis strategies, global signal regression and medication status and are generally reproducible across centers. However, these between-group differences are partially influenced by the episode status and the age of disease onset in patients, and the brain-clinical variable relationship exhibits poor cross-center reproducibility. Bootstrap analyses reveal that at least 400 subjects in each group are required to replicate significant alterations (an extent threshold of P 
       
  • A novel training-free externally-regulated neurofeedback (ER-NF) system
           using phase-guided visual stimulation for alpha modulation
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Gan Huang, Jia Liu, Linling Li, Li Zhang, Yixuan Zeng, Lijie Ren, Shiqing Ye, Zhiguo Zhang The efficacy of neurofeedback is a point of great controversy, because a certain proportion of users cannot properly regulate their brain activities and thereby fail to benefit from neurofeedback. To address the neurofeedback inefficacy problem, the present study is aimed to design and implement a new neurofeedback system that can more effectively and consistently regulate users’ brain activities than the conventional way of training users to voluntarily regulate brain activities. The new neurofeedback system delivers external visual stimuli continuously at a specific alpha phase, which is real-time decoded from ongoing alpha wave, to regulate the alpha wave. Experimental results show that the proposed training-free externally-regulated neurofeedback (ER-NF) system can achieve consistent (effective in almost all sessions for almost all users), flexible (either increasing or decreasing peak alpha frequency and alpha power), and immediate (taking or losing effect immediately after stimulation is on or off) modulation effects on alpha wave. Therefore, the ER-NF system holds great potential to be able to more reliably and flexibly modulate cognition and behavior.
       
  • The individual functional connectome is unique and stable over months to
           years
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Corey Horien, Xilin Shen, Dustin Scheinost, R. Todd Constable Functional connectomes computed from fMRI provide a means to characterize individual differences in the patterns of BOLD synchronization across regions of the entire brain. Using four resting-state fMRI datasets with a wide range of ages, we show that individual differences of the functional connectome are stable across 3 months to 1–2 years (and even detectable at above-chance levels across 3 years). Medial frontal and frontoparietal networks appear to be both unique and stable, resulting in high ID rates, as did a combination of these two networks. We conduct analyses demonstrating that these results are not driven by head motion. We also show that edges contributing the most to a successful ID tend to connect nodes in the frontal and parietal cortices, while edges contributing the least tend to connect cross-hemispheric homologs. Our results demonstrate that the functional connectome is stable across years and that high ID rates are not an idiosyncratic aspect of a specific dataset, but rather reflect stable individual differences in the functional connectivity of the brain.
       
  • Hemispheric asymmetries in cortical gray matter microstructure identified
           by neurite orientation dispersion and density imaging
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Judith Schmitz, Christoph Fraenz, Caroline Schlüter, Patrick Friedrich, Rex E. Jung, Onur Güntürkün, Erhan Genç, Sebastian Ocklenburg Histological studies have reported microstructural hemispheric asymmetries in several cortical areas of the human brain, but reliable in vivo assessment methods have been lacking so far. Here, we used neurite orientation dispersion and density imaging (NODDI) to examine microstructural asymmetries in in vivo and determine if findings are in accordance with what has been reported in histological studies. We examined intra-neurite volume fraction (INVF), neurite orientation dispersion (ODI), and isotropic volume fraction (ISO) asymmetries in two independent samples of healthy adults (n = 269 and n = 251). Over both samples, we found greater left-hemispheric INVF in early auditory, inferior parietal and temporal-parietal-occipital areas. In contrast, we found greater right-hemispheric INVF in the fusiform and inferior temporal gyrus, reflecting what has been reported in histological studies. ODI was asymmetric towards the left hemisphere in frontal areas and towards the right hemisphere in early auditory areas. ISO showed less pronounced asymmetries. There were hardly any effects of sex or handedness on microstructural asymmetry as determined by NODDI. Taken together, these findings suggest substantial microstructural asymmetries in gray matter, making NODDI a promising marker for future genetic and behavioral studies on laterality.
       
  • Sliding window correlation analysis: Modulating window shape for dynamic
           brain connectivity in resting state
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Fatemeh Mokhtari, Milad I. Akhlaghi, Sean L. Simpson, Guorong Wu, Paul J. Laurienti The sliding window correlation (SWC) analysis is a straightforward and common approach for evaluating dynamic functional connectivity. Despite the fact that sliding window analyses have been long used, there are still considerable technical issues associated with the approach. A great effort has recently been dedicated to investigate the window setting effects on dynamic connectivity estimation. In this direction, tapered windows have been proposed to alleviate the effect of sudden changes associated with the edges of rectangular windows. Nevertheless, the majority of the windows exploited to estimate brain connectivity tend to suppress dynamic correlations, especially those with faster variations over time. Here, we introduced a window named modulated rectangular (mRect) to address the suppressing effect associated with the conventional windows. We provided a frequency domain analysis using simulated time series to investigate how sliding window analysis (using the regular window functions, e.g. rectangular and tapered windows) may lead to unwanted spectral modulations, and then we showed how this issue can be alleviated through the mRect window. Moreover, we created simulated dynamic network data with altering states over time using simulated fMRI time series, to examine the performance of different windows in tracking network states. We quantified the state identification rate of different window functions through the Jaccard index, and observed superior performance of the mRect window compared to the conventional window functions. Overall, the proposed window function provides an approach that improves SWC estimations, and thus the subsequent inferences and interpretations based on the connectivity network analyses.
       
  • The inner fluctuations of the brain in presymptomatic Frontotemporal
           Dementia: The chronnectome fingerprint
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Enrico Premi, Vince D. Calhoun, Matteo Diano, Stefano Gazzina, Maura Cosseddu, Antonella Alberici, Silvana Archetti, Donata Paternicò, Roberto Gasparotti, John van Swieten, Daniela Galimberti, Raquel Sanchez-Valle, Robert Laforce, Fermin Moreno, Matthis Synofzik, Caroline Graff, Mario Masellis, Maria Carmela Tartaglia, James Rowe, Rik Vandenberghe Frontotemporal Dementia (FTD) is preceded by a long period of subtle brain changes, occurring in the absence of overt cognitive symptoms, that need to be still fully characterized. Dynamic network analysis based on resting-state magnetic resonance imaging (rs-fMRI) is a potentially powerful tool for the study of preclinical FTD.In the present study, we employed a "chronnectome" approach (recurring, time-varying patterns of connectivity) to evaluate measures of dynamic connectivity in 472 at-risk FTD subjects from the Genetic Frontotemporal dementia research Initiative (GENFI) cohort.We considered 249 subjects with FTD-related pathogenetic mutations and 223 mutation non-carriers (HC). Dynamic connectivity was evaluated using independent component analysis and sliding-time window correlation to rs-fMRI data, and meta-state measures of global brain flexibility were extracted.Results show that presymptomatic FTD exhibits diminished dynamic fluidity, visiting less meta-states, shifting less often across them, and travelling through a narrowed meta-state distance, as compared to HC. Dynamic connectivity changes characterize preclinical FTD, arguing for the desynchronization of the inner fluctuations of the brain. These changes antedate clinical symptoms, and might represent an early signature of FTD to be used as a biomarker in clinical trials.
       
  • Brain functional development separates into three distinct time periods in
           the first two years of life
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Weiyan Yin, Meng-Hsiang Chen, Sheng-Che Hung, Kristine R. Baluyot, Tengfei Li, Weili Lin Recently, resting functional MRI has provided invaluable insight into the brain developmental processes of early infancy and childhood. A common feature of previous functional development studies is the use of age to separate subjects into different cohorts for group comparisons. However, functional maturation paces vary tremendously from subject to subject. Since this is particularly true for the first years of life, an alternative to physical age alone is needed for cluster analysis. Here, a data-driven approach based on individual brain functional connectivity was employed to cluster typically developing children who were longitudinally imaged using MRI without sedation for the first two years of life. Specifically, three time periods were determined based on the distinction of brain functional connectivity patterns, including 0–1 month (group 1), 2–7 months (group 2), and 8–24 (group 3) of age, respectively. From groups 1 to 2, connection density increased by almost two-fold, local efficacy (LE) is significantly improved, and there was no change in global efficiency (GE). From groups 2 to 3, connection density increased slightly, LE showed no change, and a significant increase in GE were observed. Furthermore, 27 core brain regions were identified which yielded clustering results that resemble those obtained using all brain regions. These core regions were largely associated with the motor, visual and language functional domains as well as regions associated with higher order cognitive functional domains. Both visual and language functional domains exhibited a persistent and significant increase within domain connection from groups 1 to 3, while no changes were observed for the motor domain. In contrast, while a reduction of inter-domain connection was the general developmental pattern, the motor domain exhibited an interesting “V” shape pattern in its relationship to visual and language associated areas, showing a decrease from groups 1 to 2, followed by an increase from groups 2 to 3. In summary, our results offer new insights into functional brain development and identify 27 core brain regions critically important for early brain development.
       
  • Clinical associations of T2-weighted lesion load and lesion location in
           small vessel disease: Insights from a large prospective cohort study
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Anna Altermatt, Laura Gaetano, Stefano Magon, Lorena Bauer, Regina Feurer, Hans Gnahn, Julia Hartmann, Christian L. Seifert, Holger Poppert, Jens Wuerfel, Ernst-Wilhelm Radue, Ludwig Kappos, Till Sprenger BackgroundSubcortical T2-weighted (T2w) lesions are very common in older adults and have been associated with dementia. However, little is known about the strategic lesion distribution and how lesion patterns relate to vascular risk factors and cognitive impairment.AimThe aim of this study was to analyze the association between T2w lesion load and location, vascular risk factors, and cognitive impairment in a large cohort of older adults.Methods1017 patients participating in a large prospective cohort study (INtervention project on cerebroVAscular disease and Dementia in the district of Ebersberg, INVADE II) were analyzed. Cerebral T2w white matter and deep grey matter lesions, the so-called white matter hyperintensities (WMHs), were outlined semi-automatically on fluid attenuated inversion recovery images and normalized to standard stereotaxic space (MNI152) by non-linear registration. Patients were assigned to either a low-risk or a high-risk group. The risk assessment considered ankle brachial index, intima media thickness, carotid artery stenosis, atrial fibrillation, previous cerebro-/cardiovascular events and peripheral artery disease as well as a score based on cholesterol levels, blood pressure and smoking. Separate lesion distributions were obtained for the two risk groups and compared using voxel-based lesion-symptom mapping. Moreover, we assessed the relation between lesion location and cognitive impairment (demographically adjusted z-scores of the Consortium to Establish a Registry for Alzheimer's Disease Neuropsychological Assessment Battery Plus, CERAD-NAB Plus) using voxel-based statistics (α = 0.05).ResultsA total of 878 out of 1017 subjects (86%) had evaluable MRI data and were included in the analyses (mean age: 68.2 ± 7.6 years, female: 515). Patients in the high-risk group were characterized by a significantly higher age, a higher proportion of men, a higher lesion load (p 
       
  • The spectral exponent of the resting EEG indexes the presence of
           consciousness during unresponsiveness induced by propofol, xenon, and
           ketamine
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Michele Angelo Colombo, Martino Napolitani, Melanie Boly, Olivia Gosseries, Silvia Casarotto, Mario Rosanova, Jean-Francois Brichant, Pierre Boveroux, Steffen Rex, Steven Laureys, Marcello Massimini, Arturo Chieregato, Simone Sarasso Despite the absence of responsiveness during anesthesia, conscious experience may persist. However, reliable, easily acquirable and interpretable neurophysiological markers of the presence of consciousness in unresponsive states are still missing. A promising marker is based on the decay-rate of the power spectral density (PSD) of the resting EEG.We acquired resting electroencephalogram (EEG) in three groups of healthy participants (n = 5 each), before and during anesthesia induced by either xenon, propofol or ketamine. Dosage of each anesthetic agent was tailored to yield unresponsiveness (Ramsay score = 6). Delayed subjective reports assessed whether conscious experience was present (‘Conscious report’) or absent/inaccessible to recall (‘No Report’). We estimated the decay of the PSD of the resting EEG—after removing oscillatory peaks—via the spectral exponent β, for a broad band (1–40 Hz) and narrower sub-bands (1–20 Hz, 20–40 Hz). Within-subject anesthetic changes in β were assessed. Furthermore, based on β, ‘Conscious report’ states were discriminated against ‘no report’ states. Finally, we evaluated the correlation of the resting spectral exponent with a recently proposed index of consciousness, the Perturbational Complexity Index (PCI), derived from a previous TMS-EEG study.The spectral exponent of the resting EEG discriminated states in which consciousness was present (wakefulness, ketamine) from states where consciousness was reduced or abolished (xenon, propofol). Loss of consciousness substantially decreased the (negative) broad-band spectral exponent in each subject undergoing xenon or propofol anesthesia—indexing an overall steeper PSD decay. Conversely, ketamine displayed an overall PSD decay similar to that of wakefulness—consistent with the preservation of consciousness—yet it showed a flattening of the decay in the high-frequencies (20–40 Hz)—consistent with its specific mechanism of action. The spectral exponent was highly correlated to PCI, corroborating its interpretation as a marker of the presence of consciousness. A steeper PSD of the resting EEG reliably indexed unconsciousness in anesthesia, beyond sheer unresponsiveness.
       
  • Choice-predictive activity in parietal cortex during source memory
           decisions
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Roberto Guidotti, Annalisa Tosoni, Mauro Gianni Perrucci, Carlo Sestieri Neurobiological research has classically focused on perceptual decision-making, although many real-life decisions are based on information that is not currently available but stored in long-term memory. Previous studies have suggested that the lateral parietal cortex encodes decision-related signals during item recognition judgments. In the present fMRI study, we employed a parametric manipulation of evidence for source memory judgments and tested several hypotheses concerning memory decision signals in parietal cortex. As expected, the mean BOLD signal in several parietal regions was modulated by decision evidence. An analysis of the locally distributed pattern of activity, moreover, identified a parietal cluster showing significant choice-predictive activity even at the lowest level of decision evidence, with decoding accuracy that increased as a function of evidence. Decoding patterns were consistent across subjects as shown by a leave-one-subject-out classification analysis. Finally, we found that the pattern of choice-predictive activity in parietal lobe was temporally correlated with that observed in medial temporal regions traditionally associated with long-term memory functions. The present findings are consistent with a general role of lateral parietal regions located around the intraparietal sulcus in representing a decision variable for memory-based decisions.
       
  • The human habenula is responsive to changes in luminance and circadian
           rhythm
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Christian Kaiser, Christian Kaufmann, Tobias Leutritz, Yan Luis Arnold, Oliver Speck, Markus Ullsperger The habenula is a pivotal structure in the neural network that implements various forms of cognitive and motivational functions and behaviors. Moreover, it has been suggested to be part of the brain's circadian system, not at least because habenular neurons are responsive to retinal illumination and exhibit circadian modulations of their firing patterns in animal research. However, no study has directly investigated the human habenula in this regard. We developed a paradigm in which alternating phases of high and low luminance are used to study human habenular functioning. In two experiments with independent samples, fMRI data of 24 healthy participants were acquired at a field strength of 7T, and of 21 healthy participants at 3T. Region of interest analyses revealed that the human habenula is responsive to light as well, resulting in a decrease in activation when a change in luminance occurs. Although this pattern is not predicted by animal research, we were able to replicate this finding in a second independent data set. Furthermore, we demonstrate that the strength of decrease in activation is modulated in a circadian fashion, being more strongly deactivated in morning than in afternoon sessions. Taken together, these findings provide strong evidence that changes in illumination elicit changes in habenular activation and that these changes appear to be more pronounced in the morning than in the afternoon.
       
  • Thinking theta and alpha: Mechanisms of intuitive and analytical reasoning
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Chad C. Williams, Mitchel Kappen, Cameron D. Hassall, Bruce Wright, Olave E. Krigolson Humans have a unique ability to engage in different modes of thinking. Intuitive thinking (coined System 1, see Kahneman, 2011) is fast, automatic, and effortless whereas analytical thinking (coined System 2) is slow, contemplative, and effortful. We extend seminal pupillometry research examining these modes of thinking by using electroencephalography (EEG) to decipher their respective underlying neural mechanisms. We demonstrate that System 1 thinking is characterized by an increase in parietal alpha EEG power reflecting autonomic access to long-term memory and a release of attentional resources whereas System 2 thinking is characterized by an increase in frontal theta EEG power indicative of the engagement of cognitive control and working memory processes. Consider our results in terms of an example - a child may need cognitive control and working memory when contemplating a mathematics problem yet an adult can drive a car with little to no attention by drawing on easily accessed memories. Importantly, the unravelling of intuitive and analytical thinking mechanisms and their neural signatures will provide insight as to how different modes of thinking drive our everyday lives.
       
  • EEG microstates distinguish between cognitive components of fluid
           reasoning
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Filippo Zappasodi, Mauro Gianni Perrucci, Aristide Saggino, Pierpaolo Croce, Pasqua Mercuri, Roberta Romanelli, Roberto Colom, Sjoerd J.H. Ebisch Fluid reasoning is considered central to general intelligence. How its psychometric structure relates to brain function remains poorly understood. For instance, what is the dynamic composition of ability-specific processes underlying fluid reasoning' We investigated whether distinct fluid reasoning abilities could be differentiated by electroencephalography (EEG) microstate profiles. EEG microstates specifically capture rapidly altering activity of distributed cortical networks with a high temporal resolution as scalp potential topographies that dynamically vary over time in an organized manner. EEG was recorded simultaneously with functional magnetic resonance imaging (fMRI) in twenty healthy adult participants during cognitively distinct fluid reasoning tasks: induction, spatial relationships and visualization. Microstate parameters successfully discriminated between fluid reasoning and visuomotor control tasks as well as between the fluid reasoning tasks. Mainly, microstate B coverage was significantly higher during spatial relationships and visualization, compared to induction, while microstate C coverage was significantly decreased during spatial relationships and visualization, compared to induction. Additionally, microstate D coverage was highest during spatial relationships and microstate A coverage was most strongly reduced during the same condition. Consistently, multivariate analysis with a leave-one-out cross-validation procedure accurately classified the fluid reasoning tasks based on the coverage parameter. These EEG data and their correlation with fMRI data suggest that especially the tasks most strongly relying on visuospatial processing modulated visual and default mode network activity. We propose that EEG microstates can provide valuable information about neural activity patterns with a dynamic and complex temporal structure during fluid reasoning, suggesting cognitive ability-specific interplays between multiple brain networks.
       
  • Age-related changes in attention control and their relationship with gait
           performance in older adults with high risk of falls
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Natalia B. Fernandez, Mélany Hars, Andrea Trombetti, Patrik Vuilleumier BackgroundFalls are the leading cause of injury-related deaths in the elderly worldwide. Both gait impairment and cognitive decline have been shown to constitute major fall risk factors. However, further investigations are required to establish a more precise link between the influence of age on brain systems mediating executive cognitive functions and their relationship with gait disturbances, and thus help define novel markers and better guide remediation strategies to prevent falls.MethodsEvent-related functional magnetic resonance imaging (fMRI) was used to evaluate age-related effects on the recruitment of executive control brain network in selective attention task, as measured with a flanker paradigm. Brain activation patterns were compared between twenty young (21 years ± 2.5) and thirty-four old participants (72 years ± 5.3) with high fall risks. We then determined to what extend age-related differences in activation patterns were associated with alterations in several gait parameters, measured with electronic devices providing a precise quantitative evaluation of gait, as well as with alterations in several aspects of cognitive and physical abilities.ResultsWe found that both young and old participants recruited a distributed fronto-parietal-occipital network during interference by incongruent distractors in the flanker task. However, additional activations were observed in posterior parieto-occipital areas in the older relative to the younger participants. Furthermore, a differential recruitment of both the left dorsal parieto-occipital sulcus and precuneus was significantly correlated with higher gait variability. Besides, decreased activation in the right cerebellum was found in the older with poorer cognitive processing speed scores.ConclusionsOverall results converge to indicate greater sensitivity to attention interference and heightened recruitment of cortical executive control systems in the elderly with fall risks. Critically, this change was associated with selective increases in gait variability indices, linking attentional control with gait performance in elderly with high risks of falls.
       
  • Intra-axonal diffusivity in brain white matter
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Bibek Dhital, Marco Reisert, Elias Kellner, Valerij G. Kiselev Biophysical modeling lies at the core of evaluating tissue cellular structure using diffusion-weighted MRI, albeit with shortcomings. The challenges lie not only in the complexity of the diffusion phenomenon, but also in the need to know the diffusion-specific properties of diverse cellular compartments in vivo. The likelihood function obtained from the commonly acquired Stejskal-Tanner diffusion-weighted MRI data is degenerate with different parameter constellations explaining the signal equally well, thereby hindering an unambiguous parameter estimation.The aim of this study is to measure the intra-axonal water diffusivity which is one of the central parameters of white matter models. Estimating intra-axonal diffusivity is complicated by (i) the presence of other compartments, and (ii) the orientation dispersion of axons. Our measurement involves an efficient signal suppression of water in extra-axonal space and all cellular processes oriented outside a narrow cone around the principal fiber direction. This is achieved using a planar water mobility filter that suppresses signal from all molecules that are mobile in the plane transverse to the fiber bundle. After the planar filter, the diffusivity of the remaining intra-axonal signal is measured using linear and spherical diffusion encoding.We find the average intra-axonal diffusivity D0=2.25±0.03μm2/ms for the timing of the applied gradients, which gives D0(∞)≈2.0μm2/ms when extrapolated to infinite diffusion time. The result imposes a strong limitation on the parameter selection for biophysical modeling of diffusion-weighted MRI.Graphical abstractImage 1
       
  • Intracortical smoothing of small-voxel fMRI data can provide increased
           detection power without spatial resolution losses compared to conventional
           large-voxel fMRI data
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Anna I. Blazejewska, Bruce Fischl, Lawrence L. Wald, Jonathan R. Polimeni Continued improvement in MRI acquisition technology has made functional MRI (fMRI) with small isotropic voxel sizes down to 1 mm and below more commonly available. Although many conventional fMRI studies seek to investigate regional patterns of cortical activation for which conventional voxel sizes of 3 mm and larger provide sufficient spatial resolution, smaller voxels can help avoid contamination from adjacent white matter (WM) and cerebrospinal fluid (CSF), and thereby increase the specificity of fMRI to signal changes within the gray matter. Unfortunately, temporal signal-to-noise ratio (tSNR), a metric of fMRI sensitivity, is reduced in high-resolution acquisitions, which offsets the benefits of small voxels. Here we introduce a framework that combines small, isotropic fMRI voxels acquired at 7 T field strength with a novel anatomically-informed, surface mesh-navigated spatial smoothing that can provide both higher detection power and higher resolution than conventional voxel sizes. Our smoothing approach uses a family of intracortical surface meshes and allows for kernels of various shapes and sizes, including curved 3D kernels that adapt to and track the cortical folding pattern. Our goal is to restrict smoothing to the cortical gray matter ribbon and avoid noise contamination from CSF and signal dilution from WM via partial volume effects. We found that the intracortical kernel that maximizes tSNR does not maximize percent signal change (ΔS/S), and therefore the kernel configuration that optimizes detection power cannot be determined from tSNR considerations alone. However, several kernel configurations provided a favorable balance between boosting tSNR and ΔS/S, and allowed a 1.1-mm isotropic fMRI acquisition to have higher performance after smoothing (in terms of both detection power and spatial resolution) compared to an unsmoothed 3.0-mm isotropic fMRI acquisition. Overall, the results of this study support the strategy of acquiring voxels smaller than the cortical thickness, even for studies not requiring high spatial resolution, and smoothing them down within the cortical ribbon with a kernel of an appropriate shape to achieve the best performance—thus decoupling the choice of fMRI voxel size from the spatial resolution requirements of the particular study. The improvement of this new intracortical smoothing approach over conventional surface-based smoothing is expected to be modest for conventional resolutions, however the improvement is expected to increase with higher resolutions. This framework can also be applied to anatomically-informed intracortical smoothing of higher-resolution data (e.g. along columns and layers) in studies with prior information about the spatial structure of activation.
       
  • Multimodal assessment of recovery from coma in a rat model of diffuse
           brainstem tegmentum injury
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Patricia Pais-Roldán, Brian L. Edlow, Yuanyuan Jiang, Johannes Stelzer, Ming Zou, Xin Yu Despite the association between brainstem lesions and coma, a mechanistic understanding of coma pathogenesis and recovery is lacking. We developed a coma model in the rat mimicking human brainstem coma, which allowed multimodal analysis of a brainstem tegmentum lesion's effects on behavior, cortical electrophysiology, and global brain functional connectivity. After coma induction, we observed a transient period (∼1h) of unresponsiveness accompanied by cortical burst-suppression. Comatose rats then gradually regained behavioral responsiveness concurrent with emergence of delta/theta-predominant cortical rhythms in primary somatosensory cortex. During the acute stage of coma recovery (∼1–8h), longitudinal resting-state functional MRI revealed an increase in functional connectivity between subcortical arousal nuclei in the thalamus, basal forebrain, and basal ganglia and cortical regions implicated in awareness. This rat coma model provides an experimental platform to systematically study network-based mechanisms of coma pathogenesis and recovery, as well as to test targeted therapies aimed at promoting recovery of consciousness after coma.Graphical abstractImage 1
       
  • Neurofeedback of core language network nodes modulates connectivity with
           the default-mode network: A double-blind fMRI neurofeedback study on
           auditory verbal hallucinations
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Jana Zweerings, Bastian Hummel, Micha Keller, Mikhail Zvyagintsev, Frank Schneider, Martin Klasen, Klaus Mathiak BackgroundThe experience of auditory verbal hallucinations in schizophrenia is associated with changes in brain network function. In particular, studies indicate altered functional coupling between nodes of the language and default mode networks. Neurofeedback based on real-time functional magnetic resonance imaging (rtfMRI) can be used to modulate such aberrant network connectivity.MethodsWe investigated resting-state connectivity changes after neurofeedback (NF) in 21 patients with schizophrenia and 35 healthy individuals. All participants underwent two days of neurofeedback training of important nodes of the left-hemispheric language network including the inferior frontal gyrus (IFG) and posterior superior temporal gyrus (pSTG). In a double-blind randomized cross-over design, participants learned to down- and up-regulate their brain activation in the designated target regions based on NF. Prior to and after each training day, a resting state measurement took place.ResultsCoupling between nodes of the language and the default mode network (DMN) selectively increased after down-as compared to up-regulation NF. Network analyses revealed more pronounced increases in functional connectivity between nodes of the language network and the DMN in patients compared to healthy individuals. In particular, down-regulation NF led to increased coupling between nodes of the language network and bilateral inferior parietal lobe (IPL) as well as posterior cingulate cortex (PCC)/precuneus in patients. Up-regulation strengthened connectivity with the medial prefrontal cortex (mPFC). Improved well-being four weeks after the training predicted increased functional coupling between the left IFG and left IPL.ConclusionModulatory effects emerged as increased internetwork communication, indicating that down-regulation NF selectively enhances coupling between language and DM network nodes in patients with AVH. RtfMRI NF may thus be used to modulate brain network function that is relevant to the phenomenology of AVH. Specific effects of self-regulation on symptom improvement have to be explored in therapeutic interventions.
       
  • General functional connectivity: Shared features of resting-state and task
           fMRI drive reliable and heritable individual differences in functional
           brain networks
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Maxwell L. Elliott, Annchen R. Knodt, Megan Cooke, M. Justin Kim, Tracy R. Melzer, Ross Keenan, David Ireland, Sandhya Ramrakha, Richie Poulton, Avshalom Caspi, Terrie E. Moffitt, Ahmad R. Hariri Intrinsic connectivity, measured using resting-state fMRI, has emerged as a fundamental tool in the study of the human brain. However, due to practical limitations, many studies do not collect enough resting-state data to generate reliable measures of intrinsic connectivity necessary for studying individual differences. Here we present general functional connectivity (GFC) as a method for leveraging shared features across resting-state and task fMRI and demonstrate in the Human Connectome Project and the Dunedin Study that GFC offers better test-retest reliability than intrinsic connectivity estimated from the same amount of resting-state data alone. Furthermore, at equivalent scan lengths, GFC displayed higher estimates of heritability than resting-state functional connectivity. We also found that predictions of cognitive ability from GFC generalized across datasets, performing as well or better than resting-state or task data alone. Collectively, our work suggests that GFC can improve the reliability of intrinsic connectivity estimates in existing datasets and, subsequently, the opportunity to identify meaningful correlates of individual differences in behavior. Given that task and resting-state data are often collected together, many researchers can immediately derive more reliable measures of intrinsic connectivity through the adoption of GFC rather than solely using resting-state data. Moreover, by better capturing heritable variation in intrinsic connectivity, GFC represents a novel endophenotype with broad applications in clinical neuroscience and biomarker discovery.
       
  • Quantification of structural brain connectivity via a conductance model
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Aina Frau-Pascual, Morgan Fogarty, Bruce Fischl, Anastasia Yendiki, Iman Aganj, for the Alzheimer's Disease Neuroimaging Initiative Connectomics has proved promising in quantifying and understanding the effects of development, aging and an array of diseases on the brain. In this work, we propose a new structural connectivity measure from diffusion MRI that allows us to incorporate direct brain connections, as well as indirect ones that would not be otherwise accounted for by standard techniques and that may be key for the better understanding of function from structure. From our experiments on the Human Connectome Project dataset, we find that our measure of structural connectivity better correlates with functional connectivity than streamline tractography does, meaning that it provides new structural information related to function. Through additional experiments on the ADNI-2 dataset, we demonstrate the ability of this new measure to better discriminate different stages of Alzheimer's disease. Our findings suggest that this measure is useful in the study of the normal brain structure, and for quantifying the effects of disease on the brain structure.
       
  • Dynamic causal modelling of fluctuating connectivity in resting-state EEG
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Frederik Van de Steen, Hannes Almgren, Adeel Razi, Karl Friston, Daniele Marinazzo Functional and effective connectivity are known to change systematically over time. These changes might be explained by several factors, including intrinsic fluctuations in activity-dependent neuronal coupling and contextual factors, like experimental condition and time. Furthermore, contextual effects may be subject-specific or conserved over subjects. To characterize fluctuations in effective connectivity, we used dynamic causal modelling (DCM) of cross spectral responses over 1- min of electroencephalogram (EEG) recordings during rest, divided into 1-sec windows. We focused on two intrinsic networks: the default mode and the saliency network. DCM was applied to estimate connectivity in each time-window for both networks. Fluctuations in DCM connectivity parameters were assessed using hierarchical parametric empirical Bayes (PEB). Within-subject, between-window effects were modelled with a second-level linear model with temporal basis functions as regressors. This procedure was conducted for every subject separately. Bayesian model reduction was then used to assess which (combination of) temporal basis functions best explain dynamic connectivity over windows. A third (between-subject) level model was used to infer which dynamic connectivity parameters are conserved over subjects. Our results indicate that connectivity fluctuations in the default mode network and to a lesser extent the saliency network comprised both subject-specific components and a common component. For both networks, connections to higher order regions appear to monotonically increase during the 1- min period. These results not only establish the predictive validity of dynamic connectivity estimates – in virtue of detecting systematic changes over subjects – they also suggest a network-specific dissociation in the relative contribution of fluctuations in connectivity that depend upon experimental context. We envisage these procedures could be useful for characterizing brain state transitions that may be explained by their cognitive or neuropathological underpinnings.
       
  • Reliability of individual differences in neural face identity
           discrimination
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Lisa Stacchi, Joan Liu-Shuang, Meike Ramon, Roberto Caldara Over the past years, much interest has been devoted to understanding how individuals differ in their ability to process facial identity. Fast periodic visual stimulation (FPVS) is a promising technique to obtain objective and highly sensitive neural correlates of face processing across various populations, from infants to neuropsychological patients. Here, we use FPVS to investigate how neural face identity discrimination varies in amplitude and topography across observers. To ascertain more detailed inter-individual differences, we parametrically manipulated the visual input fixated by observers across ten viewing positions (VPs). Specifically, we determined the inter-session reliability of VP-dependent neural face discrimination responses, both across and within observers (6-month inter-session interval). All observers exhibited idiosyncratic VP-dependent neural response patterns, with reliable individual differences in terms of response amplitude for the majority of VPs. Importantly, the topographical reliability varied across VPs and observers, the majority of which exhibited reliable responses only for specific VPs. Crucially, this topographical reliability was positively correlated with the response magnitude over occipito-temporal regions: observers with stronger responses also displayed more reliable response topographies. Our data extend previous findings of idiosyncrasies in visuo-perceptual processing. They highlight the need to consider intra-individual neural response reliability in order to better understand the functional role(s) and underlying basis of such inter-individual differences.
       
  • Predicting emotional arousal and emotional memory performance from an
           identical brain network
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Eva Loos, Tobias Egli, David Coynel, Matthias Fastenrath, Virginie Freytag, Andreas Papassotiropoulos, Dominique J.-F. de Quervain, Annette Milnik Encoding and retrieval of emotionally arousing stimuli depend on the activation of multiple interconnected brain regions, with people showing differences in their individual strength of emotional perception and recollection. Understanding the association between these brain regions and the behavioral outcome might therefore have important clinical implications as dysfunctional emotional memory processes are characteristic of many psychiatric disorders. Based on behavioral and fMRI data collected from healthy young adults (N = 1’385), we investigated brain activation patterns, arousal ratings and memory performance during encoding and retrieval of negative and neutral pictures. We performed multi-voxel pattern analysis (MVPA) and voxel-wise association analyses. Subjects' individual strength of perceived arousal at encoding and subjects' memory performance at recognition could be predicted from the fMRI data of the respective tasks by using a topographically identical network of brain regions. This network was mainly left lateralized including dense clusters of voxels in the occipital and parietal lobe and including the amygdala. Voxel-wise association analyses confirmed the close link between the brain activation of both tasks and their relation to the respective behavioral outcome. These results point to the importance of the here identified brain network for emotional memory processes in health and, possibly, disease.Graphical abstractImage 1
       
  • Magnetoencephalography and the infant brain
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Yu-Han Chen, Joni Saby, Emily Kuschner, William Gaetz, J. Christopher Edgar, Timothy P.L. Roberts Magnetoencephalography (MEG) is a non-invasive neuroimaging technique that provides whole-head measures of neural activity with millisecond temporal resolution. Over the last three decades, MEG has been used for assessing brain activity, most commonly in adults. MEG has been used less often to examine neural function during early development, in large part due to the fact that infant whole-head MEG systems have only recently been developed. In this review, an overview of infant MEG studies is provided, focusing on the period from birth to three years. The advantages of MEG for measuring neural activity in infants are highlighted (See Box 1), including the ability to assess activity in brain (source) space rather than sensor space, thus allowing direct assessment of neural generator activity. Recent advances in MEG hardware and source analysis are also discussed. As the review indicates, efforts in this area demonstrate that MEG is a promising technology for studying the infant brain. As a noninvasive technology, with emerging hardware providing the necessary sensitivity, an expected deliverable is the capability for longitudinal infant MEG studies evaluating the developmental trajectory (maturation) of neural activity. It is expected that departures from neuro-typical trajectories will offer early detection and prognosis insights in infants and toddlers at-risk for neurodevelopmental disorders, thus paving the way for early targeted interventions.
       
  • Generalized diffusion spectrum magnetic resonance imaging (GDSI) for
           model-free reconstruction of the ensemble average propagator
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Qiyuan Tian, Grant Yang, Christoph Leuze, Ariel Rokem, Brian L. Edlow, Jennifer A. McNab Diffusion spectrum MRI (DSI) provides model-free estimation of the diffusion ensemble average propagator (EAP) and orientation distribution function (ODF) but requires the diffusion data to be acquired on a Cartesian q-space grid. Multi-shell diffusion acquisitions are more flexible and more commonly acquired but have, thus far, only been compatible with model-based analysis methods. Here, we propose a generalized DSI (GDSI) framework to recover the EAP from multi-shell diffusion MRI data. The proposed GDSI approach corrects for q-space sampling density non-uniformity using a fast geometrical approach. The EAP is directly calculated in a preferable coordinate system by multiplying the sampling density corrected q-space signals by a discrete Fourier transform matrix, without any need for gridding. The EAP is demonstrated as a way to map diffusion patterns in brain regions such as the thalamus, cortex and brainstem where the tissue microstructure is not as well characterized as in white matter. Scalar metrics such as the zero displacement probability and displacement distances at different fractions of the zero displacement probability were computed from the recovered EAP to characterize the diffusion pattern within each voxel. The probability averaged across directions at a specific displacement distance provides a diffusion property based image contrast that clearly differentiates tissue types. The displacement distance at the first zero crossing of the EAP averaged across directions orthogonal to the primary fiber orientation in the corpus callosum is found to be larger in the body (5.65 ± 0.09 μm) than in the genu (5.55 ± 0.15 μm) and splenium (5.4 ± 0.15 μm) of the corpus callosum, which corresponds well to prior histological studies. The EAP also provides model-free representations of angular structure such as the diffusion ODF, which allows estimation and comparison of fiber orientations from both the model-free and model-based methods on the same multi-shell data. For the model-free methods, detection of crossing fibers is found to be strongly dependent on the maximum b-value and less sensitive compared to the model-based methods. In conclusion, our study provides a generalized DSI approach that allows flexible reconstruction of the diffusion EAP and ODF from multi-shell diffusion data and data acquired with other sampling patterns.
       
  • Patterns of functional connectivity in an aging population: The Rotterdam
           Study
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Hazel I. Zonneveld, Raimon HR. Pruim, Daniel Bos, Henri A. Vrooman, Ryan L. Muetzel, Albert Hofman, Serge ARB. Rombouts, Aad van der Lugt, Wiro J. Niessen, M. Arfan Ikram, Meike W. Vernooij Structural brain markers are studied extensively in the field of neurodegeneration, but are thought to occur rather late in the process. Functional measures such as functional connectivity are gaining interest as potentially more subtle markers of neurodegeneration. However, brain structure and function are also affected by ‘normal’ brain ageing. More information is needed on how functional connectivity relates to aging, particularly in the absence of overt neurodegenerative disease. We investigated the association of age with resting-state functional connectivity in 2878 non-demented persons between 50 and 95 years of age (54.1% women) from the population-based Rotterdam Study. We obtained nine well-known resting state networks using data-driven methodology. Within the anterior default mode network, ventral attention network, and sensorimotor network, functional connectivity was significantly lower with older age. In contrast, functional connectivity was higher with older age within the visual network. Between resting state networks, we found patterns of both increases and decreases in connectivity in approximate equal proportions. Our results reinforce the notion that the aging brain undergoes a reorganization process, and serves as a solid basis for exploring functional connectivity as a preclinical marker of neurodegenerative disease.
       
  • Multi-vendor standardized sequence for edited magnetic resonance
           spectroscopy
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Muhammad G. Saleh, Daniel Rimbault, Mark Mikkelsen, Georg Oeltzschner, Anna M. Wang, Dengrong Jiang, Ali Alhamud, Jamie Near, Michael Schär, Ralph Noeske, James B. Murdoch, Lars Ersland, Alexander R. Craven, Gerard Eric Dwyer, Eli Renate Grüner, Li Pan, Sinyeob Ahn, Richard A.E. Edden Spectral editing allows direct measurement of low-concentration metabolites, such as GABA, glutathione (GSH) and lactate (Lac), relevant for understanding brain (patho)physiology. The most widely used spectral editing technique is MEGA-PRESS, which has been diversely implemented across research sites and vendors, resulting in variations in the final resolved edited signal. In this paper, we describe an effort to develop a new universal MEGA-PRESS sequence with HERMES functionality for the major MR vendor platforms with standardized RF pulse shapes, durations, amplitudes and timings.New RF pulses were generated for the universal sequence. Phantom experiments were conducted on Philips, Siemens, GE and Canon 3 T MRI scanners using 32-channel head coils. In vivo experiments were performed on the same six subjects on Philips and Siemens scanners, and on two additional subjects, one on GE and one on Canon scanners. On each platform, edited MRS experiments were conducted with the vendor-native and universal MEGA-PRESS sequences for GABA (TE = 68 ms) and Lac editing (TE = 140 ms). Additionally, HERMES for GABA and GSH was performed using the universal sequence at TE = 80 ms.The universal sequence improves inter-vendor similarity of GABA-edited and Lac-edited MEGA-PRESS spectra. The universal HERMES sequence yields both GABA- and GSH-edited spectra with negligible levels of crosstalk on all four platforms, and with strong agreement among vendors for both edited spectra. In vivo GABA+/Cr, Lac/Cr and GSH/Cr ratios showed relatively low variation between scanners using the universal sequence.In conclusion, phantom and in vivo experiments demonstrate successful implementation of the universal sequence across all four major vendors, allowing editing of several metabolites across a range of TEs.
       
  • A hierarchical independent component analysis model for longitudinal
           neuroimaging studies
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Yikai Wang, Ying Guo In recent years, longitudinal neuroimaging study has become increasingly popular in neuroscience research to investigate disease-related changes in brain functions, to study neurodevelopment or to evaluate treatment effects on neural processing. One of the important goals in longitudinal imaging analysis is to study changes in brain functional networks across time and how the changes are modulated by subjects' clinical or demographic variables. In current neuroscience literature, one of the most commonly used tools to extract and characterize brain functional networks is independent component analysis (ICA), which separates multivariate signals into linear mixture of independent components. However, existing ICA methods are only applicable to cross-sectional studies and not suited for modeling repeatedly measured imaging data. In this paper, we propose a novel longitudinal independent component model (L-ICA) which provides a formal modeling framework for extending ICA to longitudinal studies. By incorporating subject-specific random effects and visit-specific covariate effects, L-ICA is able to provide more accurate estimates of changes in brain functional networks on both the population- and individual-level, borrow information across repeated scans within the same subject to increase statistical power in detecting covariate effects on the networks, and allow for model-based prediction for brain networks changes caused by disease progression, treatment or neurodevelopment. We develop a fully traceable exact EM algorithm to obtain maximum likelihood estimates of L-ICA. We further develop a subspace-based approximate EM algorithm which greatly reduce the computation time while still retaining high accuracy. Moreover, we present a statistical testing procedure for examining covariate effects on brain network changes. Simulation results demonstrate the advantages of our proposed methods. We apply L-ICA to ADNI2 study to investigate changes in brain functional networks in Alzheimer disease. Results from the L-ICA provide biologically insightful findings which are not revealed using existing methods.
       
  • 3D MRI of whole-brain water permeability with intrinsic diffusivity
           encoding of arterial labeled spin (IDEALS)
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Kenneth Wengler, Lev Bangiyev, Turhan Canli, Tim Q. Duong, Mark E. Schweitzer, Xiang He This work proposes a novel MRI method – Intrinsic Diffusivity Encoding of Arterial Labeled Spin (IDEALS) – for the whole-brain mapping of water permeability in the human brain without an exogenous contrast agent. Quantitative separation of the intravascular and extravascular labeled water MRI signal was achieved in arterial spin labeling experiments with segmented 3D-GRASE acquisition by modulating the relative sensitivity between relaxation, true diffusion, and pseudodiffusion. The intrinsic diffusivity encoding in k-space created different broadening of the image-domain point spread functions for intravascular and extravascular labeled spins, from which blood-brain barrier (BBB) water extraction fraction (Ew) and water permeability surface area product (PSw) were estimated. The feasibility and sensitivity of this method was evaluated in healthy subjects at baseline and after caffeine challenge. The estimated baseline Ew and PSw maps showed contrast among gray matter (GM) and white matter (WM). GM Ew was significantly lower than that of WM (78.8% ± 3.3% in GM vs. 83.9% ± 4.6% in WM; p 
       
  • A behavioral face preference deficit in a monkey with an incomplete face
           patch system
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Kasper Vinken, Rufin Vogels Primates are experts in face perception and naturally show a preference for faces under free-viewing conditions. The primate ventral stream is characterized by a network of face patches that selectively responds to faces, but it remains uncertain how important such parcellation is for face perception. Here we investigated free-viewing behavior in a female monkey who naturally lacks fMRI-defined posterior and middle lateral face patches. We presented a series of content-rich images of scenes that included faces or other objects to that monkey during a free-viewing task and tested a group of 10 control monkeys on the same task for comparison. We found that, compared to controls, the monkey with missing face patches showed a marked reduction of face viewing preference that was most pronounced for the first few fixations. In addition, her gaze fixation patterns were substantially distinct from those of controls, especially for pictures with a face. These data demonstrate an association between the clustering of neurons in face selective patches and a behavioral bias for faces in natural images.
       
  • Adaptive paradigms for mapping phonological regions in individual
           participants
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Melodie Yen, Andrew T. DeMarco, Stephen M. Wilson Phonological encoding depends on left-lateralized regions in the supramarginal gyrus and the ventral precentral gyrus. Localization of these phonological regions in individual participants—including individuals with language impairments—is important in several research and clinical contexts. To localize these regions, we developed two paradigms that load on phonological encoding: a rhyme judgment task and a syllable counting task. Both paradigms relied on an adaptive staircase design to ensure that each individual performed each task at a similarly challenging level. The goal of this study was to assess the validity and reliability of the two paradigms, in terms of their ability to consistently produce left-lateralized activations of the supramarginal gyrus and ventral precentral gyrus in neurologically normal individuals with presumptively normal language localization. Sixteen participants were scanned with fMRI as they performed the rhyme judgment paradigm, the syllable counting paradigm, and an adaptive semantic paradigm that we have described previously. We found that the rhyme and syllable paradigms both yielded left-lateralized supramarginal and ventral precentral activations in the majority of participants. The rhyme paradigm produced more lateralized and more reliable activations, and so should be favored in future applications. In contrast, the semantic paradigm did not reveal supramarginal or precentral activations in most participants, suggesting that the recruitment of these regions is indeed driven by phonological encoding, not language processing in general. In sum, the adaptive rhyme judgment paradigm was effective in localizing left-lateralized phonological encoding regions in individual participants, and, in conjunction with the adaptive semantic paradigm, can be used to map individual language networks.
       
  • Imaging human cortical responses to intraneural microstimulation using
           magnetoencephalography
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): George C. O'Neill, Roger H. Watkins, Rochelle Ackerley, Eleanor L. Barratt, Ayan Sengupta, Michael Asghar, Rosa Maria Sanchez Panchuelo, Matthew J. Brookes, Paul M. Glover, Johan Wessberg, Susan T. Francis The sensation of touch in the glabrous skin of the human hand is conveyed by thousands of fast-conducting mechanoreceptive afferents, which can be categorised into four distinct types. The spiking properties of these afferents in the periphery in response to varied tactile stimuli are well-characterised, but relatively little is known about the spatiotemporal properties of the neural representations of these different receptor types in the human cortex. Here, we use the novel methodological combination of single-unit intraneural microstimulation (INMS) with magnetoencephalography (MEG) to localise cortical representations of individual touch afferents in humans, by measuring the extracranial magnetic fields from neural currents. We found that by assessing the modulation of the beta (13–30 Hz) rhythm during single-unit INMS, significant changes in oscillatory amplitude occur in the contralateral primary somatosensory cortex within and across a group of fast adapting type I mechanoreceptive afferents, which corresponded well to the induced response from matched vibrotactile stimulation. Combining the spatiotemporal specificity of MEG with the selective single-unit stimulation of INMS enables the interrogation of the central representations of different aspects of tactile afferent signalling within the human cortices. The fundamental finding that single-unit INMS ERD responses are robust and consistent with natural somatosensory stimuli will permit us to more dynamically probe the central nervous system responses in humans, to address questions about the processing of touch from the different classes of mechanoreceptive afferents and the effects of varying the stimulus frequency and patterning.
       
  • Effective connectivity within the ventromedial prefrontal
           cortex-hippocampus-amygdala network during the elaboration of emotional
           autobiographical memories
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Norberto Eiji Nawa, Hiroshi Ando Autobiographical memories (AMs) are often colored by emotions experienced during an event or those arising following further appraisals. However, how affective components of memories affect the brain-wide network recruited during the recollection of AMs remains largely unknown. Here, we examined effective connectivity during the elaboration of AMs - when retrieved episodic details are integrated to form a vivid construct - in the network composed by ventromedial prefrontal cortex (vmPFC), hippocampus and amygdala, three key regions associated with memory and affective processes. Functional MRI data was collected while volunteers recollected personal events of different types of valence and emotional intensity. Using dynamic causal modeling, we characterized the connections within the triadic network, and examined how they were modulated by the emotional intensity experienced during an event, and the valence of the affect evoked when recollecting the associated memory. Results primarily indicated the existence of a vmPFC to hippocampus effective connectivity during memory elaboration. Furthermore, the strength of the connectivity increased when participants relived memories of highly emotionally arousing events or that elicited stronger positive affect. These results indicate that the vmPFC drives hippocampal activity during memory elaboration, and plays a critical role in shaping affective responses that emanate from AMs.
       
  • A registration method for improving quantitative assessment in
           probabilistic diffusion tractography
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): J.L. Waugh, J.K. Kuster, M.L. Makhlouf, J.M. Levenstein, T.J. Multhaupt-Buell, S.K. Warfield, N. Sharma, A.J. Blood Diffusion MRI-based probabilistic tractography is a powerful tool for non-invasively investigating normal brain architecture and alterations in structural connectivity associated with disease states. Both voxelwise and region-of-interest methods of analysis are capable of integrating population differences in tract amplitude (streamline count or density), given proper alignment of the tracts of interest. However, quantification of tract differences (between groups, or longitudinally within individuals) has been hampered by two related features of white matter. First, it is unknown to what extent healthy individuals differ in the precise location of white matter tracts, and to what extent experimental factors influence perceived tract location. Second, white matter lacks the gross neuroanatomical features (e.g., gyri, histological subtyping) that make parcellation of grey matter plausible – determining where tracts “should” lie within larger white matter structures is difficult. Accurately quantifying tractographic connectivity between individuals is thus inherently linked to the difficulty of identifying and aligning precise tract location. Tractography is often utilized to study neurological diseases in which the precise structural and connectivity abnormalities are unknown, underscoring the importance of accounting for individual differences in tract location when evaluating the strength of structural connectivity.We set out to quantify spatial variance in tracts aligned through a standard, whole-brain registration method, and to assess the impact of location mismatch on groupwise assessments of tract amplitude. We then developed a method for tract alignment that enhances the existing standard whole brain registration, and then tested whether this method improved the reliability of groupwise contrasts. Specifically, we conducted seed-based probabilistic diffusion tractography from primary motor, supplementary motor, and visual cortices, projecting through the corpus callosum. Streamline counts decreased rapidly with movement from the tract center (−35% per millimeter); tract misalignment of a few millimeters caused substantial compromise of amplitude comparisons. Alignment of tracts “peak-to-peak” is essential for accurate amplitude comparisons. However, for all transcallosal tracts registered through the whole-brain method, the mean separation distance between an individual subject's tract and the average tract (3.2 mm) precluded accurate comparison: at this separation, tract amplitudes were reduced by 74% from peak value. In contrast, alignment of subcortical tracts (thalamo-putaminal, pallido-rubral) was substantially better than alignment for cortical tracts; whole-brain registration was sufficient for these subcortical tracts.We demonstrated that location mismatches in cortical tractography were sufficient to produce false positive and false negative amplitude estimates in both groupwise and longitudinal comparisons. We then showed that our new tract alignment method substantially reduced location mismatch and improved both reliability and statistical power of subsequent quantitative comparisons.
       
  • A parameter-efficient deep learning approach to predict conversion from
           mild cognitive impairment to Alzheimer's disease
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Simeon Spasov, Luca Passamonti, Andrea Duggento, Pietro Liò, Nicola Toschi Some forms of mild cognitive impairment (MCI) are the clinical precursors of Alzheimer's disease (AD), while other MCI types tend to remain stable over-time and do not progress to AD. To identify and choose effective and personalized strategies to prevent or slow the progression of AD, we need to develop objective measures that are able to discriminate the MCI patients who are at risk of AD from those MCI patients who have less risk to develop AD. Here, we present a novel deep learning architecture, based on dual learning and an ad hoc layer for 3D separable convolutions, which aims at identifying MCI patients who have a high likelihood of developing AD within 3 years.Our deep learning procedures combine structural magnetic resonance imaging (MRI), demographic, neuropsychological, and APOe4 genetic data as input measures. The most novel characteristics of our machine learning model compared to previous ones are the following: 1) our deep learning model is multi-tasking, in the sense that it jointly learns to simultaneously predict both MCI to AD conversion as well as AD vs. healthy controls classification, which facilitates relevant feature extraction for AD prognostication; 2) the neural network classifier employs fewer parameters than other deep learning architectures which significantly limits data-overfitting (we use ∼550,000 network parameters, which is orders of magnitude lower than other network designs); 3) both structural MRI images and their warp field characteristics, which quantify local volumetric changes in relation to the MRI template, were used as separate input streams to extract as much information as possible from the MRI data. All analyses were performed on a subset of the database made publicly available via the Alzheimer's Disease Neuroimaging Initiative (ADNI), (n = 785 participants, n = 192 AD patients, n = 409 MCI patients (including both MCI patients who convert to AD and MCI patients who do not covert to AD), and n = 184 healthy controls).The most predictive combination of inputs were the structural MRI images and the demographic, neuropsychological, and APOe4 data. In contrast, the warp field metrics were of little added predictive value. The algorithm was able to distinguish the MCI patients developing AD within 3 years from those patients with stable MCI over the same time-period with an area under the curve (AUC) of 0.925 and a 10-fold cross-validated accuracy of 86%, a sensitivity of 87.5%, and specificity of 85%. To our knowledge, this is the highest performance achieved so far using similar datasets. The same network provided an AUC of 1 and 100% accuracy, sensitivity, and specificity when classifying patients with AD from healthy controls. Our classification framework was also robust to the use of different co-registration templates and potentially irrelevant features/image portions.Our approach is flexible and can in principle integrate other imaging modalities, such as PET, and diverse other sets of clinical data. The convolutional framework is potentially applicable to any 3D image dataset and gives the flexibility to design a computer-aided diagnosis system targeting the prediction of several medical conditions and neuropsychiatric disorders via multi-modal imaging and tabular clinical data.
       
  • Neural signals in amygdala predict implicit prejudice toward an ethnic
           outgroup
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Keise Izuma, Ryuta Aoki, Kazuhisa Shibata, Kiyoshi Nakahara Racial and ethnic prejudice is one of the most pressing problems in modern societies. Although previous social neuroscience research has suggested the amygdala as a key structure in racial prejudice, it still remains elusive whether the amygdala activity reflects negative attitudes toward an outgroup or other unrelated processes. The present study aims to rigorously test the role of the amygdala in negative prejudice toward an outgroup. Seventy Japanese individuals passively viewed images related to an ethnic outgroup (South Korea) inside a functional magnetic resonance imaging scanner. Using Multi-Voxel Pattern Analysis (MVPA), we found that Japanese individuals' level of implicit (but not explicit) evaluations of South Korea could be predicted from neural signals in the left amygdala. Our result further suggested that the medial and lateral parts of amygdala play different roles in implicit evaluations. In contrast to the MVPA findings, conventional univariate analyses failed to find any reliable relationship between brain activation and both implicit and explicit evaluations. Our findings provide evidence for the amygdala's role in representing an implicit form of prejudice and highlight the utility of the multivariate approach to reveal neural signatures of this complex social phenomenon.
       
  • A practical guide to linking brain-wide gene expression and neuroimaging
           data
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Aurina Arnatkevic̆iūtė, Ben D. Fulcher, Alex Fornito The recent availability of comprehensive, brain-wide gene expression atlases such as the Allen Human Brain Atlas (AHBA) has opened new opportunities for understanding how spatial variations on molecular scale relate to the macroscopic neuroimaging phenotypes. A rapidly growing body of literature is demonstrating relationships between gene expression and diverse properties of brain structure and function, but approaches for combining expression atlas data with neuroimaging are highly inconsistent, with substantial variations in how the expression data are processed. The degree to which these methodological variations affect findings is unclear. Here, we outline a seven-step analysis pipeline for relating brain-wide transcriptomic and neuroimaging data and compare how different processing choices influence the resulting data. We suggest that studies using the AHBA should work towards a unified data processing pipeline to ensure consistent and reproducible results in this burgeoning field.Graphical abstractImage 1
       
  • Simultaneous task-based BOLD-fMRI and [18-F] FDG functional PET for
           measurement of neuronal metabolism in the human visual cortex
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Sharna D. Jamadar, Phillip GD. Ward, Shenpeng Li, Francesco Sforazzini, Jakub Baran, Zhaolin Chen, Gary F. Egan Studies of task-evoked brain activity are the cornerstone of cognitive neuroscience, and unravel the spatial and temporal brain dynamics of cognition in health and disease. Blood oxygenation level dependent functional magnetic resonance imaging (BOLD-fMRI) is one of the most common methods of studying brain function in humans. BOLD-fMRI indirectly infers neuronal activity from regional changes in blood oxygenation and is not a quantitative metric of brain function. Regional variation in glucose metabolism, measured using [18-F] fluorodeoxyglucose positron emission tomography (FDG-PET), provides a more direct and interpretable measure of neuronal activity. However, while the temporal resolution of BOLD-fMRI is in the order of seconds, standard FDG-PET protocols provide a static snapshot of glucose metabolism. Here, we develop a novel experimental design for measurement of task-evoked changes in regional blood oxygenation and glucose metabolism with high temporal resolution. Over a 90-min simultaneous BOLD-fMRI/FDG-PET scan, [18F] FDG was constantly infused to 10 healthy volunteers, who viewed a flickering checkerboard presented in a hierarchical block design. Dynamic task-related changes in blood oxygenation and glucose metabolism were examined with temporal resolution of 2.5sec and 1-min, respectively. Task-related, temporally coherent brain networks of haemodynamic and metabolic connectivity were jointly coupled in the visual cortex, as expected. Results demonstrate that the hierarchical block design, together with the infusion FDG-PET technique, enabled both modalities to track task-related neural responses with high temporal resolution. The simultaneous MR-PET approach has the potential to provide unique insights into the dynamic haemodynamic and metabolic interactions that underlie cognition in health and disease.
       
  • Maximising BOLD sensitivity through automated EPI protocol optimisation
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Steffen Volz, Martina F. Callaghan, Oliver Josephs, Nikolaus Weiskopf Gradient echo echo-planar imaging (GE EPI) is used for most fMRI studies but can suffer substantially from image distortions and BOLD sensitivity (BS) loss due to susceptibility-induced magnetic field inhomogeneities. While there are various post-processing methods for correcting image distortions, signal dropouts cannot be recovered and therefore need to be addressed at the data acquisition stage. Common approaches for reducing susceptibility-related BS loss in selected brain areas are: z-shimming, inverting the phase encoding (PE) gradient polarity, optimizing the slice tilt and increasing spatial resolution. The optimization of these parameters can be based on atlases derived from multiple echo-planar imaging (EPI) acquisitions. However, this requires resource and time, which imposes a practical limitation on the range over which parameters can be optimised meaning that the chosen settings may still be sub-optimal. To address this issue, we have developed an automated method that can be used to optimize across a large parameter space. It is based on numerical signal simulations of the BS loss predicted by physical models informed by a large database of magnetic field (B0) maps acquired on a broad cohort of participants. The advantage of our simulation-based approach compared to previous methods is that it saves time and expensive measurements and allows for optimizing EPI protocols by incorporating a broad range of factors, including different resolutions, echo times or slice orientations. To verify the numerical optimisation, results are compared to those from an earlier study and to experimental BS measurements carried out in six healthy volunteers.
       
  • Neural evidence for automatic value-modulated approach behaviour
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Haena Kim, Brian A. Anderson Reward learning has the ability to bias both attention and behaviour. The current study presents behavioural and neural evidence that irrelevant responses evoked by previously reward-associated stimuli are more robustly represented in the motor system using a combined go/no-go and flankers task. Following a colour-reward association training, participants were instructed to respond to a central target only in a response-relevant context, while ignoring flankers that appeared either in a high-value or low-value colour. The motor cortex and cerebellum exhibited reduced activation to low-value flankers in a response-irrelevant context, consistent with goal-directed response suppression. However, these same regions exhibited similar activation to high-value flankers regardless of their response relevance, indicating less effective suppression, and the resulting interaction in motor cortex activation was strongly predicted by the influence of the flankers on behaviour. These findings suggest that associative reward learning produces a general approach bias, which is particularly evident when it conflicts with task goals, extending the principle of value-driven attention to stimulus-evoked responses in the motor system.
       
  • Structural covariability hubs in old age
    • Abstract: Publication date: Available online 19 January 2019Source: NeuroImageAuthor(s): Lars Forsberg, Sigurdur Sigurdsson, Lenore J. Launer, Vilmundur Gudnason, Fredrik Ullén Studies have shown that inter-individual differences in grey matter, as measured by voxel-based morphometry, are coordinated between voxels. This has been done by studying covariance maps based on a limited number of seed regions. Here, we used GPU-based (Graphics Processing Unit) accelerated computing to calculate, for the first time, the aggregated map of the total structural topographical organisation in the brain on voxel level in a large sample of 960 healthy individuals in the age range 68–83 years. This map describes for each voxel the number of significant correlations with all other grey matter voxels in the brain. Voxels that correlate significantly with many other voxels are called hubs. A majority of these hubs were found in the basal ganglia, the thalamus, the brainstem, and the cerebellum; subcortical regions that have been preserved through vertebrate evolution, interact with large portions of the neocortex and play fundamental roles for the control of a wide range of behaviours. No significant difference in the level of covariability could be found with increasing age or between men and women in these hubs.Graphical abstractImage 1
       
  • Modulation of brain function by targeted delivery of GABA through the
           disrupted blood-brain barrier
    • Abstract: Publication date: Available online 16 January 2019Source: NeuroImageAuthor(s): Nick Todd, Yongzhi Zhang, Chanikarn Power, Lino Becerra, David Borsook, Margaret Livingstone, Nathan McDannold The technology of transcranial focused ultrasound (FUS) enables a novel approach to neuromodulation, a tool for selective manipulation of brain function to be used in neurobiology research and with potential applications in clinical treatment. The method uses transcranial focused ultrasound to non-invasively open the blood-brain barrier (BBB) in a localized region such that a systemically injected neurotransmitter chemical can be delivered to the targeted brain site. The approach modulates the chemical signaling that occurs in and between neurons, making it complimentary to most other neuromodulation techniques that affect the electrical properties of neuronal activity. Here, we report delivering the inhibitory neurotransmitter GABA to the right somatosensory cortex of the rat brain during bilateral hind paw electrical stimulation and measure the inhibition of activation using functional MRI (fMRI). In a 2 × 2 factorial design, we evaluated conditions of BBB Closed vs BBB Open and No GABA vs GABA. Results from fMRI measurements of the blood oxygen level-dependent (BOLD) signal show: 1) intravenous GABA injection without FUS-mediated BBB opening does not have an effect on the BOLD response; 2) FUS-mediated BBB opening alone significantly alters the BOLD signal response to the stimulus, both in amplitude and shape of the time course; 3) the combination of FUS-mediated BBB opening and GABA injection further reduces the peak amplitude and spatial extent of the BOLD signal response to the stimulus. The data support the thesis that FUS-mediated opening of the BBB can be used to achieve non-invasive delivery of neuroactive substances for targeted manipulation of brain function.
       
  • Quantifying amide proton exchange rate and concentration in chemical
           exchange saturation transfer imaging of the human brain
    • Abstract: Publication date: Available online 14 January 2019Source: NeuroImageAuthor(s): Hye-Young Heo, Zheng Han, Shanshan Jiang, Michael Schär, Peter C.M. van Zijl, Jinyuan Zhou Current chemical exchange saturation transfer (CEST) neuroimaging protocols typically acquire CEST-weighted images, and, as such, do not essentially provide quantitative proton-specific exchange rates (or brain pH) and concentrations. We developed a dictionary-free MR fingerprinting (MRF) technique to allow CEST parameter quantification with a reduced data set. This was accomplished by subgrouping proton exchange models (SPEM), taking amide proton transfer (APT) as an example, into two-pool (water and semisolid macromolecules) and three-pool (water, semisolid macromolecules, and amide protons) models. A variable radiofrequency saturation scheme was used to generate unique signal evolutions for different tissues, reflecting their CEST parameters. The proposed MRF-SPEM method was validated using Bloch-McConnell equation-based digital phantoms with known ground-truth, which showed that MRF-SPEM can achieve a high degree of accuracy and precision for absolute CEST parameter quantification and CEST phantoms. For in-vivo studies at 3 T, using the same model as in the simulations, synthetic Z-spectra were generated using rates and concentrations estimated from the MRF-SPEM reconstruction and compared with experimentally measured Z-spectra as the standard for optimization. The MRF-SPEM technique can provide rapid and quantitative human brain CEST mapping.
       
  • Linguistic networks associated with lexical, semantic and syntactic
           predictability in reading: A fixation-related fMRI study
    • Abstract: Publication date: Available online 14 January 2019Source: NeuroImageAuthor(s): Benjamin T. Carter, Brent Foster, Nathan Muncy, Steven G. Luke The ability to make predictions is thought to facilitate language processing. During language comprehension such predictions appear to occur at multiple levels of linguistic representations (i.e. semantic, syntactic and lexical). The neural mechanisms that define the network sensitive to linguistic predictability have yet to be adequately defined. The purpose of the present study was to explore the neural network underlying predictability during the normal reading of connected text. Predictability values for different linguistic information were obtained from a pre-existing text corpus. Forty-one subjects underwent simultaneous eye-tracking and fMRI scans while reading these select paragraphs. Lexical, semantic, and syntactic predictability measures were then correlated with functional activation associated with fixation onset on the individual words. Activation patterns showed both positive and negative correlations to lexical, semantic, and syntactic predictabilities. Conjunction analysis revealed regions specific to or shared between each type of predictability. The regions associated with the different predictability measures were largely separate. Results suggest that most linguistic predictions are graded in nature, activating components of the existing language system. A number of regions were also found to be uniquely associated with full lexical predictability, most notably the anterior temporal lobe and the inferior posterior temporal cortex.
       
  • Quantifying normal human brain metabolism using hyperpolarized
           [1–13C]pyruvate and magnetic resonance imaging
    • Abstract: Publication date: Available online 11 January 2019Source: NeuroImageAuthor(s): James T. Grist, Mary A. McLean, Frank Riemer, Rolf F. Schulte, Surrin S. Deen, Fulvio Zaccagna, Ramona Woitek, Charlie J. Daniels, Joshua D. Kaggie, Tomasz Matyz, Ilse Patterson, Rhys Slough, Andrew B. Gill, Anita Chhabra, Rose Eichenberger, Marie-Christine Laurent, Arnaud Comment, Jonathan H. Gillard, Alasdair J. Coles, Damian J. Tyler Hyperpolarized 13C Magnetic Resonance Imaging (13C-MRI) provides a highly sensitive tool to probe tissue metabolism in vivo and has recently been translated into clinical studies. We report the cerebral metabolism of intravenously injected hyperpolarized [1–13C]pyruvate in the brain of healthy human volunteers for the first time. Dynamic acquisition of 13C images demonstrated 13C-labeling of both lactate and bicarbonate, catalyzed by cytosolic lactate dehydrogenase and mitochondrial pyruvate dehydrogenase respectively. This demonstrates that both enzymes can be probed in vivo in the presence of an intact blood-brain barrier: the measured apparent exchange rate constant (kPL) for exchange of the hyperpolarized 13C label between [1–13C]pyruvate and the endogenous lactate pool was 0.012 ± 0.006 s−1 and the apparent rate constant (kPB) for the irreversible flux of [1–13C]pyruvate to [13C]bicarbonate was 0.002 ± 0.002 s−1. Imaging also revealed that [1–13C]pyruvate, [1–13C]lactate and [13C]bicarbonate were significantly higher in gray matter compared to white matter. Imaging normal brain metabolism with hyperpolarized [1–13C]pyruvate and subsequent quantification, have important implications for interpreting pathological cerebral metabolism in future studies.Graphical abstractImage 1
       
  • A distinct cortical network for mathematical knowledge in the human brain
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Marie Amalric, Stanislas Dehaene How does the brain represent and manipulate abstract mathematical concepts' Recent evidence suggests that mathematical processing relies on specific brain areas and dissociates from language. Here, we investigate this dissociation in two fMRI experiments in which professional mathematicians had to judge the truth value of mathematical and nonmathematical spoken statements. Sentences with mathematical content systematically activated bilateral intraparietal sulci and inferior temporal regions, regardless of math domain, problem difficulty, and strategy for judging truth value (memory retrieval, calculation or mental imagery). Second, classical language areas were only involved in the parsing of both nonmathematical and mathematical statements, and their activation correlated with syntactic complexity, not mathematical content. Third, the mere presence, within a sentence, of elementary logical operators such as quantifiers or negation did not suffice to activate math-responsive areas. Instead, quantifiers and negation impacted on activity in right angular gyrus and left inferior frontal gyrus, respectively. Overall, these results support the existence of a distinct, non-linguistic cortical network for mathematical knowledge in the human brain.
       
  • Task activations produce spurious but systematic inflation of task
           functional connectivity estimates
    • Abstract: Publication date: 1 April 2019Source: NeuroImage, Volume 189Author(s): Michael W. Cole, Takuya Ito, Douglas Schultz, Ravi Mill, Richard Chen, Carrisa Cocuzza Most neuroscientific studies have focused on task-evoked activations (activity amplitudes at specific brain locations), providing limited insight into the functional relationships between separate brain locations. Task-state functional connectivity (FC) – statistical association between brain activity time series during task performance – moves beyond task-evoked activations by quantifying functional interactions during tasks. However, many task-state FC studies do not remove the first-order effect of task-evoked activations prior to estimating task-state FC. It has been argued that this results in the ambiguous inference "likely active or interacting during the task", rather than the intended inference "likely interacting during the task". Utilizing a neural mass computational model, we verified that task-evoked activations substantially and inappropriately inflate task-state FC estimates, especially in functional MRI (fMRI) data. Various methods attempting to address this problem have been developed, yet the efficacies of these approaches have not been systematically assessed. We found that most standard approaches for fitting and removing mean task-evoked activations were unable to correct these inflated correlations. In contrast, methods that flexibly fit mean task-evoked response shapes effectively corrected the inflated correlations without reducing effects of interest. Results with empirical fMRI data confirmed the model's predictions, revealing activation-induced task-state FC inflation for both Pearson correlation and psychophysiological interaction (PPI) approaches. These results demonstrate that removal of mean task-evoked activations using an approach that flexibly models task-evoked response shape is an important preprocessing step for valid estimation of task-state FC.
       
  • Univariate and multivariate analyses of functional networks in absolute
           pitch
    • Abstract: Publication date: Available online 11 January 2019Source: NeuroImageAuthor(s): Christian Brauchli, Simon Leipold, Lutz Jäncke Absolute pitch (AP) refers to the rare ability to identify the pitch of any given tone without an external reference tone. Previous studies have shown that during auditory processing, AP musicians activate the auditory cortex (AC), the prefrontal cortex (PFC), and parietal areas of the brain. Therefore, it has been hypothesized that AP is sustained by a widespread functional network. In the present functional magnetic resonance imaging (fMRI) study, we tested this hypothesis by employing a mass-univariate analysis of resting-state functional connectivity within the AC, the PFC, and parietal areas in a large sample of musicians with and without AP (N = 100). AP musicians showed increased functional connectivity in the left middle frontal gyrus (MFG), left intraparietal sulcus (IPS), and right superior parietal lobule (SPL). These results provide the first evidence for an AP-specific network characterized by increased functional connections in higher-order cognitive areas. Interestingly, AP was not associated with increases in functional connectivity of the AC, but AP was successfully decoded from functional connectivity patterns in the left AC using multi-voxel pattern analysis (MVPA), with group classification accuracy being highest for the left Heschl's gyrus (HG). MVPA can capture fine-grained patterns in the brain connectivity profile of AP musicians, whilst a mass-univariate analysis is sensitive to macroscopic trends in the data. The successful differentiation of AP musicians by MVPA but not by a mass-univariate analysis of connectivity in the AC thus indicates that AP musicians differ in the fine-grained rather than the macroscopic AC function. Based on our findings, and in light of current literature, we propose pitch-label associations, tonal working memory, pitch categorization, and multimodal integration as potential mechanisms underlying the AP ability. This set of psychological functions is controlled by a distributed functional network and a particular AC connectivity pattern only present in AP musicians.
       
  • Patch-based super-resolution of arterial spin labeling magnetic resonance
           images
    • Abstract: Publication date: Available online 10 January 2019Source: NeuroImageAuthor(s): Cédric Meurée, Pierre Maurel, Jean-Christophe Ferré, Christian Barillot Arterial spin labeling is a magnetic resonance perfusion imaging technique that, while providing results comparable to methods currently considered as more standard concerning the quantification of the cerebral blood flow, is subject to limitations related to its low signal-to-noise ratio and low resolution. In this work, we investigate the relevance of using a non-local patch-based super-resolution method driven by a high resolution structural image to increase the level of details in arterial spin labeling images. This method is evaluated by comparison with other image dimension increasing techniques on a simulated dataset, on images of healthy subjects and on images of subjects scanned for brain tumors, who had a dynamic susceptibility contrast acquisition. The influence of an increase of ASL images resolution on partial volume effects is also investigated in this work.
       
  • Frontal theta predicts specific cognitive control-induced behavioural
           changes beyond general reaction time slowing
    • Abstract: Publication date: Available online 10 January 2019Source: NeuroImageAuthor(s): Patrick S. Cooper, Frini Karayanidis, Montana McKewen, Samuel McLellan-Hall, Aaron S.W. Wong, Patrick Skippen, James F. Cavanagh Investigations into the neurophysiological underpinnings of control suggest that frontal theta activity is increased with the need for control. However, these studies typically show this link by reporting associations between increased theta and RT slowing – a process that is contemporaneous with cognitive control but does not strictly reflect the specific use of control. In this study, we assessed frontal theta responses that underpinned the switch cost in task switching – a specific index of cognitive control that does not rely exclusively on RT slowing. Here, we utilised a single-trial regression approach to assess 1) how cognitive control demands beyond simple RT slowing were linked to midfrontal theta and 2) whether midfrontal theta effects remained stable over time. In a large cohort that included a longitudinal subsample, we found that midfrontal theta was modulated by switch costs, with enhanced theta power when preparing to switch vs. repeating a task. These effects were reliable after a two-year interval (Cronbach's α.39-0.74). In contrast, we found that trial-by-trial modulations of midfrontal theta power predicted the size of the switch cost – so that switch trials with increased theta produced smaller switch costs. Interestingly, these relationships between theta and behaviour were less stable over time (Cronbach's α 0-0.61), with participants first using both delta and theta bands to influence behaviour whereas after two years only theta associations with behaviour remained. Together, these findings suggest midfrontal theta supports the need for control beyond simple RT slowing and reveal that midfrontal theta effects remain relatively stable over time.
       
  • Slow spindles are associated with cortical high frequency activity
    • Abstract: Publication date: Available online 9 January 2019Source: NeuroImageAuthor(s): Nasrin Sadat Hashemi, Fereshteh Dehnavi, Sahar Moghimi, Maryam Ghorbani Thalamocortical network shows self-sustained oscillations in a broad frequency range especially during slow wave sleep when cortical neurons show synchronized transitions between a quiescent down state and an active up state with beta and gamma oscillations. Inconsistent with previous models, thalamocortical spindles are separated into slow spindles (8_12 Hz) and fast spindles (13_17 Hz) with differential properties. We proposed that cortical high frequency (∼ 25 Hz) activity during up states is the key ingredient for the generation of slow spindles. In fact, the nonlinear interaction between cortical high frequency and thalamic oscillations at fast spindle frequency reproduces oscillations in the range of the difference between the two frequencies that lies into the range of slow spindle. The developed simple deterministic thalamocortical model is able to reproduce up and down states with stochastic high-frequency up-state activity as well as both fast and slow spindles. In agreement with the previous experimental observations, the fast and slow spindles are generated at opposing phases of the up state. To further confirm the causal relationship between slow spindles and cortical high frequency oscillations, we next showed that externally applied high frequency stimulation enhanced the slow spindle activity. Moreover, the prediction of the model was validated experimentally by recording EEG from subjects during nap. Both model and experimental results show increase in high frequency activity before slow spindles. Our findings suggest the important role of cortical high frequency activity in the generation of slow spindles.Graphical abstractImage 1
       
  • Customized head molds reduce motion during resting state fMRI scans
    • Abstract: Publication date: Available online 9 January 2019Source: NeuroImageAuthor(s): Jonathan D. Power, Benjamin M. Silver, Melanie R. Silverman, Eliana L. Ajodan, Dienke J. Bos, Rebecca M. Jones Head motion causes artifacts in functional magnetic resonance imaging (fMRI) scans, a problem especially relevant for task-free resting state paradigms and for developmental, aging, and clinical populations. In a cohort spanning 7–28 years old (mean age 15) we produced customized head-anatomy-specific Styrofoam molds for each subject that inserted into an MRI head coil. We scanned these subjects under two conditions: using our standard procedure of packing the head coil with foam padding about the head to reduce head motion, and using the customized molds to reduce head motion. Here we report the effects found in our first 13 subjects. In 12 of 13 subjects, the molds reduced head motion throughout the scan, and reduced the fraction of a scan with substantial motion (i.e., volumes with motion notably above baseline levels of motion). Motion was reduced in all 6 head position estimates, especially in rotational, left-right, and superior-inferior directions. Motion was reduced throughout the full age range studied, including children, adolescents, and young adults. In terms of the fMRI data itself, quality indices improved with the head mold on, scrubbing analyses detected less distance-dependent artifact in scans with the head mold on, and distant-dependent artifact was less evident in both the entire scan and also during only low-motion volumes. Subjects found the molds comfortable. Head molds are thus effective tools for reducing head motion, and motion artifacts, during fMRI scans.
       
  • Qoala-T: A supervised-learning tool for quality control of FreeSurfer
           segmented MRI data
    • Abstract: Publication date: Available online 8 January 2019Source: NeuroImageAuthor(s): Eduard T. Klapwijk, Ferdi van de Kamp, Mara van der Meulen, Sabine Peters, Lara M. Wierenga Performing quality control to detect image artifacts and data-processing errors is crucial in structural magnetic resonance imaging, especially in developmental studies. Currently, many studies rely on visual inspection by trained raters for quality control. The subjectivity of these manual procedures lessens comparability between studies, and with growing study sizes quality control is increasingly time consuming. In addition, both inter-rater as well as intra-rater variability of manual quality control is high and may lead to inclusion of poor quality scans and exclusion of scans of usable quality. In the current study we present the Qoala-T tool, which is an easy and free to use supervised-learning model to reduce rater bias and misclassification in manual quality control procedures using FreeSurfer-processed scans. First, we manually rated quality of N = 784 FreeSurfer-processed T1-weighted scans acquired in three different waves in a longitudinal study. Different supervised-learning models were then compared to predict manual quality ratings using FreeSurfer segmented output data. Results show that the Qoala-T tool using random forests is able to predict scan quality with both high sensitivity and specificity (mean area under the curve (AUC) = 0.98). In addition, the Qoala-T tool was also able to adequately predict the quality of two novel unseen datasets (total N = 872). Finally, analyses of age effects showed that younger participants were more likely to have lower scan quality, underlining that scan quality might confound findings attributed to age effects. These outcomes indicate that this procedure could further help to reduce variability related to manual quality control, thereby benefiting the comparability of data quality between studies.Graphical abstractImage 1
       
  • Differential impact of reward and punishment on functional connectivity
           after skill learning
    • Abstract: Publication date: Available online 8 January 2019Source: NeuroImageAuthor(s): Adam Steel, Edward H. Silson, Charlotte J. Stagg, Chris I. Baker Reward and punishment shape behavior, but the mechanisms underlying their effect on skill learning are not well understood. Here, we tested whether the functional connectivity of premotor cortex (PMC), a region known to be critical for learning of sequencing skills, is altered after training by reward or punishment given during training. Resting-state fMRI was collected in two experiments before and after participants trained on either a serial reaction time task (SRTT; n = 36) or force-tracking task (FTT; n = 36) with reward, punishment, or control feedback. In each experiment, training-related change in PMC functional connectivity was compared across feedback groups. In both tasks, reward and punishment differentially affected PMC functional connectivity. On the SRTT, participants trained with reward showed an increase in functional connectivity between PMC and cerebellum as well as PMC and striatum, while participants trained with punishment showed an increase in functional connectivity between PMC and medial temporal lobe connectivity. After training on the FTT, subjects trained with control and reward showed increases in PMC connectivity with parietal and temporal cortices after training, while subjects trained with punishment showed increased PMC connectivity with ventral striatum. While the results from the two experiments overlapped in some areas, including ventral pallidum, temporal lobe, and cerebellum, these regions showed diverging patterns of results across the two tasks for the different feedback conditions. These findings suggest that reward and punishment strongly influence spontaneous brain activity after training, and that the regions implicated depend on the task learned.
       
  • Individual variation in brain network topology is linked to emotional
           intelligence
    • Abstract: Publication date: Available online 8 January 2019Source: NeuroImageAuthor(s): George Ling, Ivy Lee, Synthia Guimond, Olivia Lutz, Neeraj Tandon, Uzma Nawaz, Dost Öngür, Shaun Eack, Kathryn Lewandowski, Matcheri Keshavan, Roscoe Brady BackgroundSocial cognitive ability is a significant determinant of functional outcome, and deficits in social cognition are a disabling symptom of psychotic disorders. The neurobiological underpinnings of social cognition are not well understood, hampering our ability to ameliorate these deficits.ObjectiveUsing ‘resting state’ functional magnetic resonance imaging (rsfMRI) and a trans-diagnostic, data-driven analytic strategy, we sought to identify the brain network basis of emotional intelligence, a key domain of social cognition.MethodsThe study included 60 participants with a diagnosis of schizophrenia or schizoaffective disorder and 45 healthy controls. All participants underwent a rsfMRI scan. Emotional Intelligence was measured using the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT). A connectome-wide analysis examined how each individual brain voxel's connectivity correlated with emotional intelligence using multivariate distance matrix regression (MDMR).ResultsWe identified a region in the left superior parietal lobule (SPL) where individual network topology is linked to emotional intelligence. Specifically, in high scoring individuals, this region is a node of the Default Mode Network and in low scoring individuals, it is a node of the Dorsal Attention Network. This relationship was observed in both schizophrenia and healthy comparison participants.ConclusionPrior studies have demonstrated individual variance in the topology of canonical resting state networks but the cognitive or behavioral relevance of these differences has largely been undetermined. We observe that the left SPL, a region of high individual variance at the cytoarchitectonic level, also demonstrates individual variance in its association with large scale resting-state networks and that network topology is linked to emotional intelligence.
       
  • Amyloid-beta induced retrograde axonal degeneration in a mouse tauopathy
           model
    • Abstract: Publication date: Available online 7 January 2019Source: NeuroImageAuthor(s): Christopher Nishioka, Hsiao-Fang Liang, Barsam Barsamian, Shu-Wei Sun White matter abnormalities, revealed by Diffusion Tensor Imaging (DTI), are observed in patients with Alzheimer's Disease (AD), representing neural network deficits that underlie gradual cognitive decline in patients with AD. However, how DTI changes are related to the development of Amyloid beta (Aβ) and tau pathology, two key hallmarks of AD, remains elusive. We hypothesized that tauopathy induced by Aβ could initiate an axonal degeneration process, leading to DTI-detectable white matter abnormalities. We utilized the visual system of the transgenic p301L tau mice as a model system. Aβ was injected in Lateral Geniculate Nucleus (LGN), where the Retinal Ganglion Cell (RGC) axons terminate, and longitudinal DTI was conducted to detect changes in the optic tract (OT, containing the distal segment of RGC axons) and optic nerve (ON, containing the proximal segment of RGC axons). Our results showed early DTI changes in OT (significant 13.2% reduction in axial diffusion, AxD vs. vehicle controls) followed by later significant alterations in ON AxD and fractional anisotropy, FA. Histology data revealed loss of synapses, RGC axons and cell bodies resulting from the Aβ injection. We further tested whether microtubule-stabilizing compound Epothilone D (EpoD) could ameliorate the damage. EpoD co-treatment with Aβ was sufficient to prevent Aβ-induced axon and cell loss. Using an acute injection paradigm, our data suggest that EpoD may mediate its protective effect by blocking localized, acute Aβ-induced tau phosphorylation. This study demonstrates white matter disruption resulting from localized Aβ, the importance of tau pathology induction to changes in white matter connectivity, and the use of EpoD as a potential therapeutic avenue to block axon loss during disease.
       
  • Smell training improves olfactory function and alters brain structure
    • Abstract: Publication date: Available online 7 January 2019Source: NeuroImageAuthor(s): Syrina Al Ain, Daphnée Poupon, Sébastien Hétu, Noémie Mercier, Jason Steffener, Johannes Frasnelli Training and repeated exposure to odorants leads to enhanced olfactory sensitivity. So far, the efficacy of intensive olfactory training on olfactory function in healthy population and its underlying neurobiological basis remain poorly known. This study investigated the effects of a 6-week intensive and well-controlled olfactory training on olfactory function and brain structure/neuroplasticity. Thirty-six healthy young individuals were recruited and randomly distributed in three groups: (1) 12 participants underwent daily intensive olfactory training of at least 20 min that included an (a) odor intensity classification task, an (b) odor quality classification task and an (c) target odor detection task, (2) 12 participants underwent an equivalent visual control training, and (3) 12 control individuals did not participate in any training. Before and after the training period, all participants performed a series of olfactory tests and those from groups 1 and 2 underwent structural magnetic resonance (MR) imaging, from which we obtained measures such as cortical thickness and tissue density.Participantsimproved in the respectively trained tasks throughout the 6-weeks training period. Participants who underwent olfactory training improved general olfactory function compared to control participants, especially in odor identification, thus showing intramodal transfer. Further, MR imaging analysis revealed that olfactory training led to increased cortical thickness in the right inferior frontal gyrus, the bilateral fusiform gyrus and the right entorhinal cortex.This research shows that intensive olfactory training can generally improve olfactory function and that this improvement is associated with changes in the structure of olfactory processing areas of the brain.
       
  • Unbiased age-specific structural brain atlases for Chinese pediatric
           population
    • Abstract: Publication date: Available online 6 January 2019Source: NeuroImageAuthor(s): Tengda Zhao, Xuhong Liao, Vladimir S. Fonov, Qiushi Wang, Weiwei Men, Yanpei Wang, Shaozheng Qin, Shuping Tan, Jia-Hong Gao, Alan Evans, Sha Tao, Qi Dong, Yong He In magnetic resonance (MR) imaging studies of child brain development, structural brain atlases usually serve as important references for the pediatric population, in which individual images are spatially normalized into a common or standard stereotactic space. However, the popular existing pediatric brain atlases (e.g., National Institutes of Health pediatric atlases, NIH-PD) are mostly based on MR images obtained from Caucasian populations and thus are not ideal for the characterization of the brains of Chinese children due to neuroanatomical differences related to genetic and environmental factors. Here, we use an unbiased template construction algorithm to create a set of age-specific Chinese pediatric (CHN-PD) atlases based on high-quality T1-and T2-weighted MR images from 328 cognitively normal Chinese children aged 6–12 years. The CHN-PD brain atlases include asymmetric and symmetric templates, sex-specific templates and tissue probability templates, and contain multiple age-specific templates at one-year intervals. A direct comparison of the CHN-PD and NIH-PD atlases reveals dramatic anatomical differences mainly in the bilateral frontal and parietal regions. After applying the CHN-PD and NIH-PD atlases to two independent Chinese pediatric datasets (N = 114 and N = 71), we find that the CHN-PD atlases result in significantly higher accuracy than the NIH-PD atlases in both predicting “brain age” and guiding brain tissue segmentation. These results suggest that the CHN-PD brain atlases are necessary for studies of the typical and atypical development of the Chinese pediatric population. These CHN-PD atlases have been released on the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) website (https://www.nitrc.org/projects/chn-pd).
       
  • Ahead of time: Early sentence slow cortical modulations associated to
           semantic prediction
    • Abstract: Publication date: Available online 6 January 2019Source: NeuroImageAuthor(s): Patricia León-Cabrera, Amanda Flores, Antoni Rodríguez-Fornells, Joaquín Morís According to prediction-based accounts of language comprehension, incoming contextual information is constantly used to guide the pre-activation of the most probable continuations to the unfolding sentences. However, there is still scarce evidence of the build-up of these predictions during sentence comprehension. Using event-related brain potentials, we investigated sustained processes associated to semantic prediction during online sentence comprehension. To address this, participants read sentences with varying levels of contextual constraint one word at a time. A 1000 ms interval preceded the final word, which could be congruent or incongruent. A slow sustained negativity developed gradually over the course of sentences, showing differences across conditions, with increasingly larger amplitudes for high than low levels of constraint. The effect was maximal in the interval preceding the closing word. This interval elicited a left-dominant slow negative potential with a graded amplitude modulation to contextual constraint, replicating previous results in speech comprehension. We argue that these slow potentials index the engagement of cognitive operations associated to semantic prediction. In addition, we replicated the finding of an earlier onset of the N400 effect (incongruent minus congruent) for high relative to low contextual constraint, suggesting facilitated processing for contextually-supported and highly expected words. Altogether, these results are consistent with prediction-based models of language comprehension and they also strengthen the value of investigating slow components as potential indices of mechanisms linked to language prediction.
       
  • Brain networks for engaging oneself in positive-social emotion regulation
    • Abstract: Publication date: Available online 27 December 2018Source: NeuroImageAuthor(s): Yury Koush, Swann Pichon, Simon B. Eickhoff, Dimitri Van De Ville, Patrik Vuilleumier, Frank Scharnowski Positive emotions facilitate cognitive performance, and their absence is associated with burdening psychiatric disorders. However, the brain networks regulating positive emotions are not well understood, especially with regard to engaging oneself in positive-social situations. Here we report convergent evidence from a multimodal approach that includes functional magnetic resonance imaging (fMRI) brain activations, meta-analytic functional characterization, Bayesian model-driven analysis of effective brain connectivity, and personality questionnaires to identify the brain networks mediating the cognitive up-regulation of positive-social emotions. Our comprehensive approach revealed that engaging in positive-social emotion regulation with a self-referential first-person perspective is characterized by dynamic interactions between functionally specialized prefrontal cortex (PFC) areas, the temporoparietal junction (TPJ) and the amygdala. Increased top-down connectivity from the superior frontal gyrus (SFG) controls affective valuation in the ventromedial and dorsomedial PFC, self-referential processes in the TPJ, and modulate emotional responses in the amygdala via the ventromedial PFC. Understanding the brain networks engaged in the regulation of positive-social emotions that involve a first-person perspective is important as they are known to constitute an effective strategy in therapeutic settings.
       
  • Getting to grips with endoscopy - Learning endoscopic surgical skills
           induces bi-hemispheric plasticity of the grasping network
    • Abstract: Publication date: Available online 21 December 2018Source: NeuroImageAuthor(s): Anke Ninija Karabanov, Friederike Irmen, Kristoffer Hougaard Madsen, Brian Numelin Haagensen, Svend Schulze, Thue Bisgaard, Hartwig Roman Siebner Endoscopic surgery requires skilled bimanual use of complex instruments that extend the peri-personal workspace. To delineate brain structures involved in learning such surgical skills, 48 medical students without surgical experience were randomly assigned to five training sessions on a virtual-reality endoscopy simulator or to a non-training group. Brain activity was probed with functional MRI while participants performed endoscopic tasks. Repeated task performance in the scanner was sufficient to enhance task-related activity in left ventral premotor cortex (PMv) and the anterior Intraparietal Sulcus (aIPS). Simulator training induced additional increases in task-related activation in right PMv and aIPS and reduced effective connectivity from left to right PMv. Skill improvement after training scaled with stronger task-related activation of the lateral left primary motor hand area (M1-HAND). The results suggest that a bilateral fronto-parietal grasping network and left M1-HAND are engaged in bimanual learning of tool-based manipulations in an extended peri-personal space.
       
 
 
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