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  Subjects -> PSYCHOLOGY (Total: 871 journals)
Showing 1 - 174 of 174 Journals sorted alphabetically
Acción Psicológica     Open Access   (Followers: 2)
Acta Colombiana de Psicología     Open Access   (Followers: 4)
Acta Comportamentalia     Open Access   (Followers: 3)
Acta de Investigación Psicológica     Open Access   (Followers: 2)
Acta Psychologica     Hybrid Journal   (Followers: 21)
Activités     Open Access   (Followers: 1)
Actualidades en Psicologia     Open Access   (Followers: 1)
Ad verba Liberorum : Journal of Linguistics & Pedagogy & Psychology     Open Access   (Followers: 8)
Addictive Behaviors Reports     Open Access   (Followers: 5)
ADHD Attention Deficit and Hyperactivity Disorders     Hybrid Journal   (Followers: 20)
ADHD Report The     Full-text available via subscription   (Followers: 6)
Advances in Experimental Social Psychology     Full-text available via subscription   (Followers: 38)
Advances in Mental Health     Hybrid Journal   (Followers: 68)
Advances in Physiotherapy     Hybrid Journal   (Followers: 50)
Advances in Psychology     Full-text available via subscription   (Followers: 56)
Advances in the Study of Behavior     Full-text available via subscription   (Followers: 28)
African Journal of Cross-Cultural Psychology and Sport Facilitation     Full-text available via subscription   (Followers: 3)
Aggression and Violent Behavior     Hybrid Journal   (Followers: 388)
Aggressive Behavior     Hybrid Journal   (Followers: 16)
Aging, Neuropsychology, and Cognition     Hybrid Journal   (Followers: 33)
Ágora - studies in psychoanalytic theory     Open Access   (Followers: 3)
Aletheia     Open Access   (Followers: 1)
American Behavioral Scientist     Hybrid Journal   (Followers: 15)
American Imago     Full-text available via subscription   (Followers: 3)
American Journal of Applied Psychology     Open Access   (Followers: 33)
American Journal of Community Psychology     Hybrid Journal   (Followers: 24)
American Journal of Health Behavior     Full-text available via subscription   (Followers: 23)
American Journal of Orthopsychiatry     Hybrid Journal   (Followers: 4)
American Journal of Psychoanalysis     Hybrid Journal   (Followers: 20)
American Journal of Psychotherapy     Full-text available via subscription   (Followers: 33)
American Psychologist     Full-text available via subscription   (Followers: 161)
Anales de Psicología     Open Access   (Followers: 2)
Análise Psicológica     Open Access   (Followers: 1)
Análisis y Modificación de Conducta     Open Access   (Followers: 2)
Analysis     Full-text available via subscription   (Followers: 4)
Annual Review of Clinical Psychology     Full-text available via subscription   (Followers: 66)
Annual Review of Organizational Psychology and Organizational Behavior     Full-text available via subscription   (Followers: 25)
Annual Review of Psychology     Full-text available via subscription   (Followers: 195)
Anuario de Psicología / The UB Journal of Psychology     Open Access   (Followers: 1)
Anuario de Psicología Jurídica     Open Access   (Followers: 1)
Anxiety, Stress & Coping: An International Journal     Hybrid Journal   (Followers: 22)
Applied and Preventive Psychology     Hybrid Journal   (Followers: 13)
Applied Cognitive Psychology     Hybrid Journal   (Followers: 65)
Applied Neuropsychology : Adult     Hybrid Journal   (Followers: 32)
Applied Neuropsychology : Child     Hybrid Journal   (Followers: 18)
Applied Psychological Measurement     Hybrid Journal   (Followers: 17)
Applied Psychology     Hybrid Journal   (Followers: 124)
Applied Psychology: Health and Well-Being     Hybrid Journal   (Followers: 48)
Applied Psychophysiology and Biofeedback     Hybrid Journal   (Followers: 6)
Archive for the Psychology of Religion / Archiv für Religionspychologie     Hybrid Journal   (Followers: 16)
Archives of Clinical Neuropsychology     Hybrid Journal   (Followers: 26)
Archives of Scientific Psychology     Open Access   (Followers: 3)
Arquivos Brasileiros de Psicologia     Open Access   (Followers: 1)
Asia Pacific Journal of Counselling and Psychotherapy     Hybrid Journal   (Followers: 8)
Asia-Pacific Psychiatry     Hybrid Journal   (Followers: 3)
Asian American Journal of Psychology     Full-text available via subscription   (Followers: 5)
Asian Journal of Business Ethics     Hybrid Journal   (Followers: 7)
Assessment     Hybrid Journal   (Followers: 9)
At-Tajdid : Jurnal Ilmu Tarbiyah     Open Access   (Followers: 2)
Attachment: New Directions in Psychotherapy and Relational Psychoanalysis     Full-text available via subscription   (Followers: 16)
Attention, Perception & Psychophysics     Full-text available via subscription   (Followers: 10)
Australian and Aotearoa New Zealand Psychodrama Association Journal     Full-text available via subscription  
Australian Educational and Developmental Psychologist, The     Full-text available via subscription   (Followers: 6)
Australian Journal of Psychology     Hybrid Journal   (Followers: 16)
Australian Psychologist     Hybrid Journal   (Followers: 11)
Autism Research     Hybrid Journal   (Followers: 31)
Autism Research and Treatment     Open Access   (Followers: 29)
Autism's Own     Open Access  
Autism-Open Access     Open Access   (Followers: 5)
Avaliação Psicológica     Open Access  
Avances en Psicologia Latinoamericana     Open Access   (Followers: 1)
Aviation Psychology and Applied Human Factors     Hybrid Journal   (Followers: 17)
Balint Journal     Hybrid Journal   (Followers: 3)
Barbaroi     Open Access  
Basic and Applied Social Psychology     Hybrid Journal   (Followers: 31)
Behavior Analysis in Practice     Full-text available via subscription   (Followers: 6)
Behavior Analysis: Research and Practice     Full-text available via subscription   (Followers: 2)
Behavior Analyst     Hybrid Journal   (Followers: 3)
Behavior Modification     Hybrid Journal   (Followers: 9)
Behavior Research Methods     Hybrid Journal   (Followers: 17)
Behavior Therapy     Hybrid Journal   (Followers: 45)
Behavioral Development Bulletin     Full-text available via subscription  
Behavioral Interventions     Hybrid Journal   (Followers: 7)
Behavioral Neuroscience     Full-text available via subscription   (Followers: 49)
Behavioral Sciences & the Law     Hybrid Journal   (Followers: 20)
Behavioral Sleep Medicine     Hybrid Journal   (Followers: 6)
Behaviour     Hybrid Journal   (Followers: 13)
Behaviour Research and Therapy     Hybrid Journal   (Followers: 17)
Behavioural and Cognitive Psychotherapy     Hybrid Journal   (Followers: 109)
Behavioural Processes     Hybrid Journal   (Followers: 6)
Biofeedback     Hybrid Journal   (Followers: 4)
BioPsychoSocial Medicine     Open Access   (Followers: 6)
BMC Psychology     Open Access   (Followers: 15)
Body, Movement and Dance in Psychotherapy: An International Journal for Theory, Research and Practice     Hybrid Journal   (Followers: 9)
Boletim Academia Paulista de Psicologia     Open Access  
Boletim de Psicologia     Open Access  
Brain Informatics     Open Access   (Followers: 1)
British Journal of Clinical Psychology     Full-text available via subscription   (Followers: 122)
British Journal of Developmental Psychology     Full-text available via subscription   (Followers: 35)
British Journal of Educational Psychology     Hybrid Journal   (Followers: 31)
British Journal of Health Psychology     Full-text available via subscription   (Followers: 42)
British Journal of Mathematical and Statistical Psychology     Full-text available via subscription   (Followers: 19)
British Journal of Psychology     Full-text available via subscription   (Followers: 56)
British Journal of Psychotherapy     Hybrid Journal   (Followers: 66)
British Journal of Social Psychology     Full-text available via subscription   (Followers: 31)
Burnout Research     Open Access   (Followers: 7)
Cadernos de psicanálise (Rio de Janeiro)     Open Access  
Cadernos de Psicologia Social do Trabalho     Open Access  
Canadian Art Therapy Association     Hybrid Journal  
Canadian Journal of Behavioural Science     Full-text available via subscription   (Followers: 6)
Canadian Journal of Experimental Psychology     Full-text available via subscription   (Followers: 11)
Canadian Psychology / Psychologie canadienne     Full-text available via subscription   (Followers: 10)
Cendekia : Jurnal Kependidikan dan Kemasyarakatan     Open Access  
Child Development Perspectives     Hybrid Journal   (Followers: 26)
Child Development Research     Open Access   (Followers: 13)
Ciencia Cognitiva     Open Access   (Followers: 2)
Ciencia e Interculturalidad     Open Access  
Ciências & Cognição     Open Access  
Ciencias Psicológicas     Open Access  
Clínica y Salud     Open Access  
Clinical Medicine Insights : Psychiatry     Open Access   (Followers: 9)
Clinical Practice in Pediatric Psychology     Full-text available via subscription   (Followers: 10)
Clinical Psychological Science     Hybrid Journal   (Followers: 11)
Clinical Psychologist     Hybrid Journal   (Followers: 15)
Clinical Psychology & Psychotherapy     Hybrid Journal   (Followers: 67)
Clinical Psychology and Special Education     Open Access   (Followers: 1)
Clinical Psychology Review     Hybrid Journal   (Followers: 33)
Clinical Psychology: Science and Practice     Hybrid Journal   (Followers: 20)
Clinical Schizophrenia & Related Psychoses     Full-text available via subscription   (Followers: 8)
Coaching Psykologi - The Danish Journal of Coaching Psychology     Open Access   (Followers: 1)
Cogent Psychology     Open Access  
Cógito     Open Access  
Cognition & Emotion     Hybrid Journal   (Followers: 36)
Cognitive Behaviour Therapy     Hybrid Journal   (Followers: 14)
Cognitive Neuropsychology     Hybrid Journal   (Followers: 26)
Cognitive Psychology     Hybrid Journal   (Followers: 58)
Consciousness and Cognition     Hybrid Journal   (Followers: 26)
Construção Psicopedagógica     Open Access  
Consulting Psychology Journal : Practice and Research     Full-text available via subscription   (Followers: 3)
Contagion : Journal of Violence, Mimesis, and Culture     Full-text available via subscription   (Followers: 8)
Contemporary Educational Psychology     Hybrid Journal   (Followers: 21)
Contemporary School Psychology     Hybrid Journal   (Followers: 4)
Contextos Clínicos     Open Access  
Counseling Outcome Research and Evaluation     Hybrid Journal   (Followers: 10)
Counseling Psychologist     Hybrid Journal   (Followers: 14)
Counseling Psychology and Psychotherapy     Open Access   (Followers: 7)
Counselling and Psychotherapy Research : Linking research with practice     Hybrid Journal   (Followers: 19)
Counselling and Values     Hybrid Journal   (Followers: 2)
Counselling Psychology Quarterly     Hybrid Journal   (Followers: 10)
Couple and Family Psychoanalysis     Full-text available via subscription   (Followers: 1)
Couple and Family Psychology : Research and Practice     Full-text available via subscription   (Followers: 4)
Creativity Research Journal     Hybrid Journal   (Followers: 20)
Creativity. Theories - Research - Applications     Open Access   (Followers: 1)
Criminal Justice Ethics     Hybrid Journal   (Followers: 6)
Cuadernos de Neuropsicología     Open Access   (Followers: 1)
Cuadernos de Psicologia del Deporte     Open Access  
Cuadernos de Psicopedagogía     Open Access  
Cultural Diversity and Ethnic Minority Psychology     Full-text available via subscription   (Followers: 12)
Cultural-Historical Psychology     Open Access  
Culturas Psi     Open Access  
Culture and Brain     Hybrid Journal   (Followers: 3)
Current Addiction Reports     Hybrid Journal   (Followers: 9)
Current Behavioral Neuroscience Reports     Hybrid Journal   (Followers: 2)
Current Directions In Psychological Science     Hybrid Journal   (Followers: 46)
Current Opinion in Behavioral Sciences     Hybrid Journal   (Followers: 1)
Current Opinion in Psychology     Hybrid Journal   (Followers: 3)
Current Psychological Research     Hybrid Journal   (Followers: 13)
Current Psychology     Hybrid Journal   (Followers: 14)
Current psychology letters     Open Access   (Followers: 2)
Current Research in Psychology     Open Access   (Followers: 20)
Cyberpsychology, Behavior, and Social Networking     Hybrid Journal   (Followers: 13)
Decision     Full-text available via subscription   (Followers: 2)
Depression and Anxiety     Hybrid Journal   (Followers: 14)
Depression Research and Treatment     Open Access   (Followers: 13)
Developmental Cognitive Neuroscience     Open Access   (Followers: 16)
Developmental Neuropsychology     Hybrid Journal   (Followers: 15)
Developmental Psychobiology     Hybrid Journal   (Followers: 9)
Developmental Psychology     Full-text available via subscription   (Followers: 44)
Diagnostica     Hybrid Journal   (Followers: 2)
Dialectica     Hybrid Journal   (Followers: 1)
Discourse     Full-text available via subscription   (Followers: 8)
Diversitas: Perspectivas en Psicologia     Open Access  
Drama Therapy Review     Hybrid Journal   (Followers: 1)
Dreaming     Full-text available via subscription   (Followers: 11)
Drogues, santé et société     Full-text available via subscription  
Dynamics of Asymmetric Conflict: Pathways toward terrorism and genocide     Hybrid Journal   (Followers: 12)
E-Journal of Applied Psychology     Open Access   (Followers: 7)
Ecopsychology     Hybrid Journal   (Followers: 6)
ECOS - Estudos Contemporâneos da Subjetividade     Open Access  
Educational Psychology Review     Hybrid Journal   (Followers: 25)
Educational Psychology: An International Journal of Experimental Educational Psychology     Hybrid Journal   (Followers: 46)
Educazione sentimentale     Full-text available via subscription  
Electronic Journal of Research in Educational Psychology     Open Access   (Followers: 6)
Elpis - Czasopismo Teologiczne Katedry Teologii Prawosławnej Uniwersytetu w Białymstoku     Open Access  
Emotion     Full-text available via subscription   (Followers: 33)
Emotion Review     Hybrid Journal   (Followers: 17)
En-Claves del pensamiento     Open Access   (Followers: 1)
Enseñanza e Investigacion en Psicologia     Open Access  
Epiphany     Open Access   (Followers: 3)
Escritos de Psicología : Psychological Writings     Open Access   (Followers: 2)

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Journal Cover Brain Informatics
  [1 followers]  Follow
    
  This is an Open Access Journal Open Access journal
   ISSN (Print) 2198-4018 - ISSN (Online) 2198-4026
   Published by SpringerOpen Homepage  [188 journals]
  • Fast assembling of neuron fragments in serial 3D sections

    • Abstract: Abstract Reconstructing neurons from 3D image-stacks of serial sections of thick brain tissue is very time-consuming and often becomes a bottleneck in high-throughput brain mapping projects. We developed NeuronStitcher, a software suite for stitching non-overlapping neuron fragments reconstructed in serial 3D image sections. With its efficient algorithm and user-friendly interface, NeuronStitcher has been used successfully to reconstruct very large and complex human and mouse neurons.
      PubDate: 2017-04-01
       
  • An ontology-based search engine for digital reconstructions of neuronal
           morphology

    • Abstract: Abstract Neuronal morphology is extremely diverse across and within animal species, developmental stages, brain regions, and cell types. This diversity is functionally important because neuronal structure strongly affects synaptic integration, spiking dynamics, and network connectivity. Digital reconstructions of axonal and dendritic arbors are thus essential to quantify and model information processing in the nervous system. NeuroMorpho.Org is an established repository containing tens of thousands of digitally reconstructed neurons shared by several hundred laboratories worldwide. Each neuron is annotated with specific metadata based on the published references and additional details provided by data owners. The number of represented metadata concepts has grown over the years in parallel with the increase of available data. Until now, however, the lack of standardized terminologies and of an adequately structured metadata schema limited the effectiveness of user searches. Here we present a new organization of NeuroMorpho.Org metadata grounded on a set of interconnected hierarchies focusing on the main dimensions of animal species, anatomical regions, and cell types. We have comprehensively mapped each metadata term in NeuroMorpho.Org to this formal ontology, explicitly resolving all ambiguities caused by synonymy and homonymy. Leveraging this consistent framework, we introduce OntoSearch, a powerful functionality that seamlessly enables retrieval of morphological data based on expert knowledge and logical inferences through an intuitive string-based user interface with auto-complete capability. In addition to returning the data directly matching the search criteria, OntoSearch also identifies a pool of possible hits by taking into consideration incomplete metadata annotation.
      PubDate: 2017-03-23
       
  • It’s not what you expect: feedback negativity is independent of reward
           expectation and affective responsivity in a non-probabilistic task

    • Abstract: Abstract ERP studies commonly utilize gambling-based reinforcement tasks to elicit feedback negativity (FN) responses. This study used a pattern learning task in order to limit gambling-related fallacious reasoning and possible affective responses to gambling, while investigating relationships between the FN components between high and low reward expectation conditions. Eighteen undergraduates completed measures of reinforcement sensitivity, trait and state affect, and psychophysiological recording. The pattern learning task elicited a FN component for both high and low win expectancy conditions, which was found to be independent of reward expectation and showed little relationship with task and personality variables. We also observed a P3 component, which showed sensitivity to outcome expectancy variation and relationships to measures of anxiety, appetitive motivation, and cortical asymmetry, although these varied by electrode location and expectancy condition. Findings suggest that the FN reflected a binary reward-related signal, with little relationship to reward expectation found in previous studies, in the absence of positive affective responses.
      PubDate: 2017-03-01
       
  • Name-calling in the hippocampus (and beyond): coming to terms with neuron
           types and properties

    • Abstract: Abstract Widely spread naming inconsistencies in neuroscience pose a vexing obstacle to effective communication within and across areas of expertise. This problem is particularly acute when identifying neuron types and their properties. Hippocampome.org is a web-accessible neuroinformatics resource that organizes existing data about essential properties of all known neuron types in the rodent hippocampal formation. Hippocampome.org links evidence supporting the assignment of a property to a type with direct pointers to quotes and figures. Mining this knowledge from peer-reviewed reports reveals the troubling extent of terminological ambiguity and undefined terms. Examples span simple cases of using multiple synonyms and acronyms for the same molecular biomarkers (or other property) to more complex cases of neuronal naming. New publications often use different terms without mapping them to previous terms. As a result, neurons of the same type are assigned disparate names, while neurons of different types are bestowed the same name. Furthermore, non-unique properties are frequently used as names, and several neuron types are not named at all. In order to alleviate this nomenclature confusion regarding hippocampal neuron types and properties, we introduce a new functionality of Hippocampome.org: a fully searchable, curated catalog of human and machine-readable definitions, each linked to the corresponding neuron and property terms. Furthermore, we extend our robust approach to providing each neuron type with an informative name and unique identifier by mapping all encountered synonyms and homonyms.
      PubDate: 2017-03-01
       
  • Familiarity effects in EEG-based emotion recognition

    • Abstract: Abstract Although emotion detection using electroencephalogram (EEG) data has become a highly active area of research over the last decades, little attention has been paid to stimulus familiarity, a crucial subjectivity issue. Using both our experimental data and a sophisticated database (DEAP dataset), we investigated the effects of familiarity on brain activity based on EEG signals. Focusing on familiarity studies, we allowed subjects to select the same number of familiar and unfamiliar songs; both resulting datasets demonstrated the importance of reporting self-emotion based on the assumption that the emotional state when experiencing music is subjective. We found evidence that music familiarity influences both the power spectra of brainwaves and the brain functional connectivity to a certain level. We conducted an additional experiment using music familiarity in an attempt to recognize emotional states; our empirical results suggested that the use of only songs with low familiarity levels can enhance the performance of EEG-based emotion classification systems that adopt fractal dimension or power spectral density features and support vector machine, multilayer perceptron or C4.5 classifier. This suggests that unfamiliar songs are most appropriate for the construction of an emotion recognition system.
      PubDate: 2017-03-01
       
  • Two-dimensional enrichment analysis for mining high-level imaging genetic
           associations

    • Abstract: Abstract Enrichment analysis has been widely applied in the genome-wide association studies, where gene sets corresponding to biological pathways are examined for significant associations with a phenotype to help increase statistical power and improve biological interpretation. In this work, we expand the scope of enrichment analysis into brain imaging genetics, an emerging field that studies how genetic variation influences brain structure and function measured by neuroimaging quantitative traits (QT). Given the high dimensionality of both imaging and genetic data, we propose to study Imaging Genetic Enrichment Analysis (IGEA), a new enrichment analysis paradigm that jointly considers meaningful gene sets (GS) and brain circuits (BC) and examines whether any given GS–BC pair is enriched in a list of gene–QT findings. Using gene expression data from Allen Human Brain Atlas and imaging genetics data from Alzheimer’s Disease Neuroimaging Initiative as test beds, we present an IGEA framework and conduct a proof-of-concept study. This empirical study identifies 25 significant high-level two-dimensional imaging genetics modules. Many of these modules are relevant to a variety of neurobiological pathways or neurodegenerative diseases, showing the promise of the proposal framework for providing insight into the mechanism of complex diseases.
      PubDate: 2017-03-01
       
  • Pattern recognition of spectral entropy features for detection of
           alcoholic and control visual ERP’s in multichannel EEGs

    • Abstract: Abstract This paper presents a novel ranking method to select spectral entropy (SE) features that discriminate alcoholic and control visual event-related potentials (ERP’S) in gamma sub-band (30–55 Hz) derived from a 64-channel electroencephalogram (EEG) recording. The ranking is based on a t test statistic that rejects the null hypothesis that the group means of SE values in alcoholics and controls are identical. The SE features with high ranks are indicative of maximal separation between their group means. Various sizes of top ranked feature subsets are evaluated by applying principal component analysis (PCA) and k-nearest neighbor (k-NN) classification. Even though ranking does not influence the performance of classifier significantly with the selection of all 61 active channels, the classification efficiency is directly proportional to the number of principal components (pc). The effect of ranking and PCA on classification is predominantly observed with reduced feature subsets of (N = 25, 15) top ranked features. Results indicate that for N = 25, proposed ranking method improves the k-NN classification accuracy from 91 to 93.87% as the number of pcs increases from 5 to 25. With same number of pcs, the k-NN classifier responds with accuracies of 84.42–91.54% with non-ranked features. Similarly for N = 15 and number of pcs varying from 5 to 15, ranking enhances k-NN detection accuracies from 88.9 to 93.08% as compared to 86.75–91.96% without ranking. This shows that the detection accuracy is increased by 6.5 and 2.8%, respectively, for N = 25, whereas it enhances by 2.2 and 1%, respectively, for N = 15 in comparison with non-ranked features. In the proposed t test ranking method for feature selection, the pcs of only top ranked feature candidates take part in classification process and hence provide better generalization.
      PubDate: 2017-01-21
       
  • Optshrink LR + S: accelerated fMRI reconstruction using non-convex
           optimal singular value shrinkage

    • Abstract: Abstract This paper presents a new accelerated fMRI reconstruction method, namely, OptShrink LR + S method that reconstructs undersampled fMRI data using a linear combination of low-rank and sparse components. The low-rank component has been estimated using non-convex optimal singular value shrinkage algorithm, while the sparse component has been estimated using convex l 1 minimization. The performance of the proposed method is compared with the existing state-of-the-art algorithms on real fMRI dataset. The proposed OptShrink LR + S method yields good qualitative and quantitative results.
      PubDate: 2017-01-10
       
  • Test–retest reliability of brain morphology estimates

    • Abstract: Abstract Metrics of brain morphology are increasingly being used to examine inter-individual differences, making it important to evaluate the reliability of these structural measures. Here we used two open-access datasets to assess the intersession reliability of three cortical measures (thickness, gyrification, and fractal dimensionality) and two subcortical measures (volume and fractal dimensionality). Reliability was generally good, particularly with the gyrification and fractal dimensionality measures. One dataset used a sequence previously optimized for brain morphology analyses and had particularly high reliability. Examining the reliability of morphological measures is critical before the measures can be validly used to investigate inter-individual differences.
      PubDate: 2017-01-05
       
  • Reconstructing the brain: from image stacks to neuron synthesis

    • Abstract: Abstract Large-scale brain initiatives such as the US BRAIN initiative and the European Human Brain Project aim to marshall a vast amount of data and tools for the purpose of furthering our understanding of brains. Fundamental to this goal is that neuronal morphologies must be seamlessly reconstructed and aggregated on scales up to the whole rodent brain. The experimental labor needed to manually produce this number of digital morphologies is prohibitively large. The BigNeuron initiative is assembling community-generated, open-source, automated reconstruction algorithms into an open platform, and is beginning to generate an increasing flow of high-quality reconstructed neurons. We propose a novel extension of this workflow to use this data stream to generate an unlimited number of statistically equivalent, yet distinct, digital morphologies. This will bring automated processing of reconstructed cells into digital neurons to the wider neuroscience community, and enable a range of morphologically accurate computational models.
      PubDate: 2016-12-01
       
  • The structure function as new integral measure of spatial and temporal
           properties of multichannel EEG

    • Abstract: Abstract The first-order temporal structure functions (SFs), i.e., the first-order statistical moment of absolute increments of scaled multichannel resting state EEG signals in healthy children and teenagers over a wide range of temporal separation (time lags) are computed. Our research shows that the sill level (asymptote) of the SF is mainly defined by a determinant of EEG correlation matrix reflecting the EEG spatial structure. The temporal structure of EEG is found to be characterized by power-law scaling or statistical-scale invariance over time scales less than 0.028 s and at least by two dominant frequencies differing by less than 0.3 Hz. These frequencies define the oscillation behavior of the SF and are mainly distributed within the range of 7.5–12.0 Hz. In this paper, we propose the combined Bessel and exponential model that fits well the empirical SF. It provides a good fit with the mean relative error fitting of 2.8 % over the time lag range of 1 s, using a sampling interval of 4 ms, for all cases under analysis. We also show that the hyper gamma distribution (HGD) fits to the empirical probability density functions (PDFs) of absolute increments of scaled multichannel resting state EEG signals at any given time lag. It means that only two parameters (sample mean of absolute increments and relevant coefficient of variation) may approximately define the empirical PDFs for a given number of channels. A three-dimensional feature vector constructed from the shape and scale parameters of the HGD and the sill level may be used to estimate the closeness of the real EEG to the “random” EEG characterized by the absence of temporal and spatial correlation.
      PubDate: 2016-12-01
       
  • Visual analytics for concept exploration in subspaces of patient groups

    • Abstract: Abstract Medical doctors and researchers in bio-medicine are increasingly confronted with complex patient data, posing new and difficult analysis challenges. These data are often comprising high-dimensional descriptions of patient conditions and measurements on the success of certain therapies. An important analysis question in such data is to compare and correlate patient conditions and therapy results along with combinations of dimensions. As the number of dimensions is often very large, one needs to map them to a smaller number of relevant dimensions to be more amenable for expert analysis. This is because irrelevant, redundant, and conflicting dimensions can negatively affect effectiveness and efficiency of the analytic process (the so-called curse of dimensionality). However, the possible mappings from high- to low-dimensional spaces are ambiguous. For example, the similarity between patients may change by considering different combinations of relevant dimensions (subspaces). We demonstrate the potential of subspace analysis for the interpretation of high-dimensional medical data. Specifically, we present SubVIS, an interactive tool to visually explore subspace clusters from different perspectives, introduce a novel analysis workflow, and discuss future directions for high-dimensional (medical) data analysis and its visual exploration. We apply the presented workflow to a real-world dataset from the medical domain and show its usefulness with a domain expert evaluation.
      PubDate: 2016-12-01
       
  • A tamper-proof audit and control system for the doctor in the loop

    • Abstract: Abstract The “doctor in the loop” is a new paradigm in information-driven medicine, picturing the doctor as authority inside a loop supplying an expert system with information on actual patients, treatment results, and possible additional (side-)effects, including general information in order to enhance data-driven medical science, as well as giving back treatment advice to the doctor himself. While this approach can be very beneficial for new medical approaches like P4 medicine (personal, predictive, preventive, and participatory), it also relies heavily on the authenticity of the data and thus increases the need for secure and reliable databases. In this paper, we propose a solution in order to protect the doctor in the loop against responsibility derived from manipulated data, thus enabling this new paradigm to gain acceptance in the medical community. This work is an extension of the conference paper  Kieseberg et al. (Brain Informatics and Health, 2015), which includes extensions to the original concept.
      PubDate: 2016-12-01
       
  • Frontal lobe regulation of blood glucose levels: support for the limited
           capacity model in hostile violence-prone men

    • Abstract: Abstract Hostile men have reliably displayed an exaggerated sympathetic stress response across multiple experimental settings, with cardiovascular reactivity for blood pressure and heart rate concurrent with lateralized right frontal lobe stress (Trajanoski et al., in Diabetes Care 19(12):1412–1415, 1996; see Heilman et al., in J Neurol Neurosurg Psychiatry 38(1):69–72, 1975). The current experiment examined frontal lobe regulatory control of glucose in high and low hostile men with concurrent left frontal lobe (Control Oral Word Association Test [verbal]) or right frontal lobe (Ruff Figural Fluency Test [nonverbal]) stress. A significant interaction was found for Group × Condition, F (1,22) = 4.16, p ≤ .05 with glucose levels (mg/dl) of high hostile men significantly elevated as a function of the right frontal stressor (M = 101.37, SD = 13.75) when compared to the verbal stressor (M = 95.79, SD = 11.20). Glucose levels in the low hostile group remained stable for both types of stress. High hostile men made significantly more errors on the right frontal but not the left frontal stressor (M = 17.18, SD = 19.88) when compared to the low hostile men (M = 5.81, SD = 4.33). These findings support our existing frontal capacity model of hostility (Iribarren et al., in J Am Med Assoc 17(19):2546–2551, 2000; McCrimmon et al., in Physiol Behav 67(1):35–39, 1999; Brunner et al., in Diabetes Care 21(4):585–590, 1998), extending the role of the right frontal lobe to regulatory control over glucose mobilization.
      PubDate: 2016-12-01
       
  • Automatic screening and classification of diabetic retinopathy and
           maculopathy using fuzzy image processing

    • Abstract: Abstract Digital retinal imaging is a challenging screening method for which effective, robust and cost-effective approaches are still to be developed. Regular screening for diabetic retinopathy and diabetic maculopathy diseases is necessary in order to identify the group at risk of visual impairment. This paper presents a novel automatic detection of diabetic retinopathy and maculopathy in eye fundus images by employing fuzzy image processing techniques. The paper first introduces the existing systems for diabetic retinopathy screening, with an emphasis on the maculopathy detection methods. The proposed medical decision support system consists of four parts, namely: image acquisition, image preprocessing including four retinal structures localisation, feature extraction and the classification of diabetic retinopathy and maculopathy. A combination of fuzzy image processing techniques, the Circular Hough Transform and several feature extraction methods are implemented in the proposed system. The paper also presents a novel technique for the macula region localisation in order to detect the maculopathy. In addition to the proposed detection system, the paper highlights a novel online dataset and it presents the dataset collection, the expert diagnosis process and the advantages of our online database compared to other public eye fundus image databases for diabetic retinopathy purposes.
      PubDate: 2016-12-01
       
  • Spreading activation in nonverbal memory networks

    • Abstract: Abstract Theories of spreading activation primarily involve semantic memory networks. However, the existence of separate verbal and visuospatial memory networks suggests that spreading activation may also occur in visuospatial memory networks. The purpose of the present investigation was to explore this possibility. Specifically, this study sought to create and describe the design frequency corpus and to determine whether this measure of visuospatial spreading activation was related to right hemisphere functioning and spreading activation in verbal memory networks. We used word frequencies taken from the Controlled Oral Word Association Test and design frequencies taken from the Ruff Figural Fluency Test as measures of verbal and visuospatial spreading activation, respectively. Average word and design frequencies were then correlated with measures of left and right cerebral functioning. The results indicated that a significant relationship exists between performance on a test of right posterior functioning (Block Design) and design frequency. A significant negative relationship also exists between spreading activation in semantic memory networks and design frequency. Based on our findings, the hypotheses were supported. Further research will need to be conducted to examine whether spreading activation exists in visuospatial memory networks as well as the parameters that might modulate this spreading activation, such as the influence of neurotransmitters.
      PubDate: 2016-11-28
       
  • Improved diagonal queue medical image steganography using Chaos theory,
           LFSR, and Rabin cryptosystem

    • Abstract: Abstract In this article, we have proposed an improved diagonal queue medical image steganography for patient secret medical data transmission using chaotic standard map, linear feedback shift register, and Rabin cryptosystem, for improvement of previous technique (Jain and Lenka in Springer Brain Inform 3:39–51, 2016). The proposed algorithm comprises four stages, generation of pseudo-random sequences (pseudo-random sequences are generated by linear feedback shift register and standard chaotic map), permutation and XORing using pseudo-random sequences, encryption using Rabin cryptosystem, and steganography using the improved diagonal queues. Security analysis has been carried out. Performance analysis is observed using MSE, PSNR, maximum embedding capacity, as well as by histogram analysis between various Brain disease stego and cover images.
      PubDate: 2016-09-09
       
  • Fuzzy clustering-based feature extraction method for mental task
           classification

    • Abstract: Abstract A brain computer interface (BCI) is a communication system by which a person can send messages or requests for basic necessities without using peripheral nerves and muscles. Response to mental task-based BCI is one of the privileged areas of investigation. Electroencephalography (EEG) signals are used to represent the brain activities in the BCI domain. For any mental task classification model, the performance of the learning model depends on the extraction of features from EEG signal. In literature, wavelet transform and empirical mode decomposition are two popular feature extraction methods used to analyze a signal having non-linear and non-stationary property. By adopting the virtue of both techniques, a theoretical adaptive filter-based method to decompose non-linear and non-stationary signal has been proposed known as empirical wavelet transform (EWT) in recent past. EWT does not work well for the signals having overlapped in frequency and time domain and failed to provide good features for further classification. In this work, Fuzzy c-means algorithm is utilized along with EWT to handle this problem. It has been observed from the experimental results that EWT along with fuzzy clustering outperforms in comparison to EWT for the EEG-based response to mental task problem. Further, in case of mental task classification, the ratio of samples to features is very small. To handle the problem of small ratio of samples to features, in this paper, we have also utilized three well-known multivariate feature selection methods viz. Bhattacharyya distance (BD), ratio of scatter matrices (SR), and linear regression (LR). The results of experiment demonstrate that the performance of mental task classification has improved considerably by aforesaid methods. Ranking method and Friedman’s statistical test are also performed to rank and compare different combinations of feature extraction methods and feature selection methods which endorse the efficacy of the proposed approach.
      PubDate: 2016-09-03
       
  • Workload regulation by Sudarshan Kriya: an EEG and ECG perspective

    • Abstract: Abstract Sudarshan Kriya Yoga (SKY) is a type of rhythmic breathing activity, trivially a form of Pranayama that stimulates physical, mental, emotional, and social well-being. The objective of the present work is to verify the effect of meditation in optimizing task efficiency and regulating stress. It builds on to quantitatively answer if SKY will increase workload tolerance for divided attention tasks in the people sank in it. EEG and ECG recordings were taken from a total of twenty-five subjects who had volunteered for the experiment. Subjects were randomly assigned to two groups of ‘control’ and ‘experimental.’ Their objective scores were collected from the experiment based on NASA’s multi-attribute task battery II and was utilized for workload assessment. Both the groups had no prior experience of SKY. The experimental group was provided with an intervention of SKY for a duration of 30 min everyday. Pre- and post-meditation data were acquired from both groups over a period of 30 and 90 days. It was observed that subjective score of workload (WL) was significantly reduced in the experimental group and performance of the subject increased in terms of task performance. Another astute observation included a considerable increase and decrease in the alpha and beta energies and root mean square of the EEG signal for the experimental group and control group, respectively. In addition to this sympathovagal balance index also decreased in experimental group which indicated reduction in stress. SKY had an effect on stress regulation which in turn enhanced their WL tolerance capacity for a particular multitask activity.
      PubDate: 2016-07-18
       
  • Exploring stability-based voxel selection methods in MVPA using cognitive
           neuroimaging data: a comprehensive study

    • Abstract: Abstract Feature selection plays a key role in multi-voxel pattern analysis because functional magnetic resonance imaging data are typically noisy, sparse, and high-dimensional. Although the conventional evaluation criterion is the classification accuracy, selecting a stable feature set that is not sensitive to the variance in dataset may provide more scientific insights. In this study, we aim to investigate the stability of feature selection methods and test the stability-based feature selection scheme on two benchmark datasets. Top-k feature selection with a ranking score of mutual information and correlation, recursive feature elimination integrated with support vector machine, and L1 and L2-norm regularizations were adapted to a bootstrapped stability selection framework, and the selected algorithms were compared based on both accuracy and stability scores. The results indicate that regularization-based methods are generally more stable in StarPlus dataset, but in Haxby dataset they failed to perform as well as others.
      PubDate: 2016-04-06
       
 
 
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