 Subjects -> PSYCHOLOGY (Total: 983 journals)
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- A comparison of the methods for detecting dyadic patterns in the
actor-partner interdependence model-
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Abstract: Abstract In the actor-partner interdependence model (APIM), various dyadic patterns between an actor and partner can be examined. One widely used approach is the parameter k method, which tests whether the ratio of the partner effect to the actor effect (p/a) is significantly different from pattern values such as −1 (contrast), 0 (actor-only or partner-only), and 1 (couple). Although using a phantom variable was a useful method for estimating the k ratio, it is no longer necessary due to the availability of statistical packages that allow for a direct estimation of the k ratio without the inclusion of the phantom variable. Moreover, it is possible to examine the patterns by testing new variables defined in different forms from the k or using the χ2 difference test. To date, no previous studies have evaluated and compared the various approaches for detecting the dyadic patterns in APIM. This study aims to assess and compare the performance of four different methods for detecting dyadic patterns: (1) phantom variable approach, (2) direct estimation of the parameter k, (3) new-variable approach, and (4) χ2 difference test. The first two methods frequently included multiple pattern values in there confidence interval. Furthermore, the phantom variable approach was prone to convergence issues. The other two alternatives performed better in detecting the dyadic patterns without convergence problems. Given the findings of the study, we suggest a novel procedure for examining dyadic patterns in APIM.
PubDate: 2023-09-29
- Toolkit to Examine Lifelike Language (TELL): An app to capture speech and
language markers of neurodegeneration-
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Abstract: Abstract Automated speech and language analysis (ASLA) is a promising approach for capturing early markers of neurodegenerative diseases. However, its potential remains underexploited in research and translational settings, partly due to the lack of a unified tool for data collection, encryption, processing, download, and visualization. Here we introduce the Toolkit to Examine Lifelike Language (TELL) v.1.0.0, a web-based app designed to bridge such a gap. First, we outline general aspects of its development. Second, we list the steps to access and use the app. Third, we specify its data collection protocol, including a linguistic profile survey and 11 audio recording tasks. Fourth, we describe the outputs the app generates for researchers (downloadable files) and for clinicians (real-time metrics). Fifth, we survey published findings obtained through its tasks and metrics. Sixth, we refer to TELL’s current limitations and prospects for expansion. Overall, with its current and planned features, TELL aims to facilitate ASLA for research and clinical aims in the neurodegeneration arena. A demo version can be accessed here: https://demo.sci.tellapp.org/.
PubDate: 2023-09-27
- Validating virtual reality for time perception research: Virtual reality
changes expectations about the duration of physical processes, but not the
sense of time-
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Abstract: Immersive virtual reality (VR) provides a versatile method for investigating human time perception, because it allows the manipulation and control of relevant variables (e.g., the speed of environmental changes) that cannot be modified in the real world. However, an important premise for interpreting the results of VR studies, namely that the method itself does not affect time perception, has received little attention. Here we tested this assumption by comparing timing performance in a real environment and a VR scenario. Participants performed two timing tasks, requiring the production of intervals defined either by numerical values ("eight seconds") or by a physical process (“the time it takes for a bottle to run out when turned over"). We found that the experience of immersive VR exclusively altered judgments about the duration of physical processes, whereas judgments about the duration of abstract time units were unaffected. These results demonstrate that effects of VR on timing performance are not driven by changes in time perception itself, but rather by altered expectations regarding the duration of physical processes. The present study validates the use of VR in time perception research and strengthens the interpretation of changed timing behaviour induced by manipulations within VR.
PubDate: 2023-09-26
- Bayesian hierarchical modeling: an introduction and reassessment
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Abstract: Abstract With the recent development of easy-to-use tools for Bayesian analysis, psychologists have started to embrace Bayesian hierarchical modeling. Bayesian hierarchical models provide an intuitive account of inter- and intraindividual variability and are particularly suited for the evaluation of repeated-measures designs. Here, we provide guidance for model specification and interpretation in Bayesian hierarchical modeling and describe common pitfalls that can arise in the process of model fitting and evaluation. Our introduction gives particular emphasis to prior specification and prior sensitivity, as well as to the calculation of Bayes factors for model comparisons. We illustrate the use of state-of-the-art software programs Stan and brms. The result is an overview of best practices in Bayesian hierarchical modeling that we hope will aid psychologists in making the best use of Bayesian hierarchical modeling.
PubDate: 2023-09-25
- Testing delayed, gradual, and temporary treatment effects in randomized
single-case experiments: A general response function framework-
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Abstract: Abstract Randomization tests represent a class of significance tests to assess the statistical significance of treatment effects in randomized single-case experiments. Most applications of single-case randomization tests concern simple treatment effects: immediate, abrupt, and permanent changes in the level of the outcome variable. However, researchers are confronted with delayed, gradual, and temporary treatment effects; in general, with “response functions” that are markedly different from single-step functions. We here introduce a general framework that allows specifying a test statistic for a randomization test based on predicted response functions that is sensitive to a wide variety of data patterns beyond immediate and sustained changes in level: different latencies (degrees of delay) of effect, abrupt versus gradual effects, and different durations of the effect (permanent or temporary). There may be reasonable expectations regarding the kind of effect (abrupt or gradual), entailing a different focal data feature (e.g., level or slope). However, the exact amount of latency and the exact duration of a temporary effect may not be known a priori, justifying an exploratory approach studying the effect of specifying different latencies or delayed effects and different durations for temporary effects. We provide illustrations of the proposal with real data, and we present a user-friendly freely available web application implementing it.
PubDate: 2023-09-25
- Novel item selection strategies for cognitive diagnostic computerized
adaptive testing: A heuristic search framework-
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Abstract: Abstract The computerized adaptive form of cognitive diagnostic testing, CD-CAT, has gained increasing attention in the domain of personalized measurements for its ability to categorize individual mastery status of fine-grained attributes more accurately and efficiently through administering items tailored to one’s ability progressively. How to select the next item based on previous response(s) is crucial for the success of CD-CAT. Previous item selection strategies for CD-CAT have often followed a greedy or semi-greedy approach, which makes it difficult to strike a balance between diagnostic performance and item bank utilization. To address this issue, this study takes a graph perspective and transforms the item selection problem in CD-CAT into a path-searching problem, in which paths refer to possible test construction and nodes refer to individual items. A heuristic function is defined to predict the prospect of a path, indicating how well the corresponding test can diagnose the current examinee. Two search mechanisms with different biases towards item exposure control are proposed to approximate the optimal path with the best prospect. The first unused item on the resulting path is selected as the next item. The above components compose a novel CD-CAT item selection framework based on heuristic search. Simulation studies are conducted under a variety of conditions regarding bank designs, bank-quality conditions, and testing scenarios. The results are compared with different types of classic item selection strategies in CD-CAT, showing that the proposed framework can enhance bank utilization at a smaller cost of diagnostic performance.
PubDate: 2023-09-25
- Extrapolation of affective norms using transformer-based neural networks
and its application to experimental stimuli selection-
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Abstract: Abstract Data on the emotionality of words is important for the selection of experimental stimuli and sentiment analysis on large bodies of text. While norms for valence and arousal have been thoroughly collected in English, most languages do not have access to such large datasets. Moreover, theoretical developments lead to new dimensions being proposed, the norms for which are only partially available. In this paper, we propose a transformer-based neural network architecture for semantic and emotional norms extrapolation that predicts a whole ensemble of norms at once while achieving state-of-the-art correlations with human judgements on each. We improve on the previous approaches with regards to the correlations with human judgments by Δr = 0.1 on average. We precisely discuss the limitations of norm extrapolation as a whole, with a special focus on the introduced model. Further, we propose a unique practical application of our model by proposing a method of stimuli selection which performs unsupervised control by picking words that match in their semantic content. As the proposed model can easily be applied to different languages, we provide norm extrapolations for English, Polish, Dutch, German, French, and Spanish. To aid researchers, we also provide access to the extrapolation networks through an accessible web application.
PubDate: 2023-09-25
- The bright side of words: Norms for 9000 Spanish words in seven discrete
positive emotions-
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Abstract: Abstract In recent years, assumptions about the existence of a single construct of happiness that accounts for all positive emotions have been questioned. Instead, several discrete positive emotions with their own neurobiological and psychological mechanisms have been proposed. Of note, the effects of positive emotions on language processing are not yet properly understood. Here we provide a database for a large set of 9000 Spanish words scored by 3437 participants in the positive emotions of awe, contentment, amusement, excitement, serenity, relief, and pleasure. We also report significant correlations between discrete positive emotions and several affective (e.g., valence, arousal, happiness, negative discrete emotions) and lexico-semantic (e.g., frequency of use, familiarity, concreteness, age of acquisition) characteristics of words. Finally, we analyze differences between words conveying a single emotion (“pure” emotion words) and those denoting more than one emotion (“mixed” emotion words). This study will provide researchers a rich source of information to do research that contributes to expanding the current knowledge on the role of positive emotions in language. The norms are available at https://doi.org/10.6084/m9.figshare.21533571.v2
PubDate: 2023-09-25
- IDLaS-NL – A platform for running customized studies on individual
differences in Dutch language skills via the Internet-
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Abstract: Abstract We introduce the Individual Differences in Language Skills (IDLaS-NL) web platform, which enables users to run studies on individual differences in Dutch language skills via the Internet. IDLaS-NL consists of 35 behavioral tests, previously validated in participants aged between 18 and 30 years. The platform provides an intuitive graphical interface for users to select the tests they wish to include in their research, to divide these tests into different sessions and to determine their order. Moreover, for standardized administration the platform provides an application (an emulated browser) wherein the tests are run. Results can be retrieved by mouse click in the graphical interface and are provided as CSV file output via e-mail. Similarly, the graphical interface enables researchers to modify and delete their study configurations. IDLaS-NL is intended for researchers, clinicians, educators and in general anyone conducting fundamental research into language and general cognitive skills; it is not intended for diagnostic purposes. All platform services are free of charge. Here, we provide a description of its workings as well as instructions for using the platform. The IDLaS-NL platform can be accessed at www.mpi.nl/idlas-nl.
PubDate: 2023-09-25
- Correctly establishing evidence for cue combination via gains in sensory
precision: Why the choice of comparator matters-
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Abstract: Abstract Studying how sensory signals from different sources (sensory cues) are integrated within or across multiple senses allows us to better understand the perceptual computations that lie at the foundation of adaptive behaviour. As such, determining the presence of precision gains – the classic hallmark of cue combination – is important for characterising perceptual systems, their development and functioning in clinical conditions. However, empirically measuring precision gains to distinguish cue combination from alternative perceptual strategies requires careful methodological considerations. Here, we note that the majority of existing studies that tested for cue combination either omitted this important contrast, or used an analysis approach that, unknowingly, strongly inflated false positives. Using simulations, we demonstrate that this approach enhances the chances of finding significant cue combination effects in up to 100% of cases, even when cues are not combined. We establish how this error arises when the wrong cue comparator is chosen and recommend an alternative analysis that is easy to implement but has only been adopted by relatively few studies. By comparing combined-cue perceptual precision with the best single-cue precision, determined for each observer individually rather than at the group level, researchers can enhance the credibility of their reported effects. We also note that testing for deviations from optimal predictions alone is not sufficient to ascertain whether cues are combined. Taken together, to correctly test for perceptual precision gains, we advocate for a careful comparator selection and task design to ensure that cue combination is tested with maximum power, while reducing the inflation of false positives.
PubDate: 2023-09-20
- A conditional judgment procedure for probing evaluative conditioning
effects in the absence of feelings of remembering-
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Abstract: Abstract Attitude research has capitalized on evaluative conditioning procedures to gain insight into how evaluations are formed and may be changed. In evaluative conditioning, a conditioned stimulus (CS; e.g., an unfamiliar soda brand) is paired with an unconditioned stimulus (US) of affective value (e.g., a pleasant picture). Following this pairing, a change in CS liking may be observed (e.g., the soda brand is liked better). A question with far-reaching theoretical and practical implications is whether the change in CS liking is found when participants feel they do not remember the CS–US pairings at the time an evaluation is produced about the CS. Here, we introduce a new conditional judgment procedure—the two-button-sets (TBS) task—for probing evaluative conditioning effects without feelings of remembering about the valence of the US paired with the CS. In three experiments, the TBS is (1) is successfully validated; it is also used to (2) provide preliminary information on the feeling of remembering question, and (3) to examine an affect-consistent bias in memory judgments for CS–US pairings. Results do not support evaluative effects in the absence of feelings of remembering, and they oppose the view that affect-consistent bias is limited to memory uncertainty. We discuss these findings in light of previous evidence and of dual-learning models of attitudes. We also discuss limitations and research avenues related to the new procedure.
PubDate: 2023-09-20
- Examining individual learning patterns using generalised linear mixed
models-
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Abstract: Abstract Everyone learns differently, but individual performance is often ignored in favour of a group-level analysis. Using data from four different experiments, we show that generalised linear mixed models (GLMMs) and extensions can be used to examine individual learning patterns. Producing ellipsoids and cluster analyses based on predicted random effects, individual learning patterns can be identified, clustered and used for comparisons across various experimental conditions or groups. This analysis can handle a range of datasets including discrete, continuous, censored and non-censored, as well as different experimental conditions, sample sizes and trial numbers. Using this approach, we show that learning a face-named paired associative task produced individuals that can learn quickly, with the performance of some remaining high, but with a drop-off in others, whereas other individuals show poor performance throughout the learning period. We see this more clearly in a virtual navigation spatial learning task (NavWell). Two prominent clusters of learning emerged, one showing individuals who produced a rapid learning and another showing a slow and gradual learning pattern. Using data from another spatial learning task (Sea Hero Quest), we show that individuals’ performance generally reflects their age category, but not always. Overall, using this analytical approach may help practitioners in education and medicine to identify those individuals who might need extra help and attention. In addition, identifying learning patterns may enable further investigation of the underlying neural, biological, environmental and other factors associated with these individuals.
PubDate: 2023-09-20
- Mouse tracking performance: A new approach to analyzing continuous mouse
tracking data-
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Abstract: Abstract Mouse tracking is an important source of data in cognitive science. Most contemporary mouse tracking studies use binary-choice tasks and analyze the curvature or velocity of an individual mouse movement during an experimental trial as participants select from one of the two options. However, there are many types of mouse tracking data available beyond what is produced in a binary-choice task, including naturalistic data from web users. In order to utilize these data, cognitive scientists need tools that are robust to the lack of trial-by-trial structure in most normal computer tasks. We use singular value decomposition (SVD) and detrended fluctuation analysis (DFA) to analyze whole time series of unstructured mouse movement data. We also introduce a new technique for describing two-dimensional mouse traces as complex-valued time series, which allows SVD and DFA to be applied in a straightforward way without losing important spatial information. We find that there is useful information at the level of whole time series, and we use this information to predict performance in an online task. We also discuss how the implications of these results can advance the use of mouse tracking research in cognitive science.
PubDate: 2023-09-19
- Long-form recording of infant body position in the home using wearable
inertial sensors-
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Abstract: Abstract Long-form audio recordings have had a transformational effect on the study of infant language acquisition by using mobile, unobtrusive devices to gather full-day, real-time data that can be automatically scored. How can we produce similar data in service of measuring infants’ everyday motor behaviors, such as body position' The aim of the current study was to validate long-form recordings of infant position (supine, prone, sitting, upright, held by caregiver) based on machine learning classification of data from inertial sensors worn on infants’ ankles and thighs. Using over 100 h of video recordings synchronized with inertial sensor data from infants in their homes, we demonstrate that body position classifications are sufficiently accurate to measure infant behavior. Moreover, classification remained accurate when predicting behavior later in the session when infants and caregivers were unsupervised and went about their normal activities, showing that the method can handle the challenge of measuring unconstrained, natural activity. Next, we show that the inertial sensing method has convergent validity by replicating age differences in body position found using other methods with full-day data captured from inertial sensors. We end the paper with a discussion of the novel opportunities that long-form motor recordings afford for understanding infant learning and development.
PubDate: 2023-09-18
- Covariate selection in causal learning under non-Gaussianity
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Abstract: Abstract Understanding causal mechanisms is a central goal in the behavioral, developmental, and social sciences. When estimating and probing causal effects using observational data, covariate adjustment is a crucial element to remove dependencies between focal predictors and the error term. Covariate selection, however, constitutes a challenging task because availability alone is not an adequate criterion to decide whether a covariate should be included in the statistical model. The present study introduces a non-Gaussian method for covariate selection and provides a forward selection algorithm for linear models (i.e., non-Gaussian forward selection; nGFS) to select appropriate covariates from a set of potential control variables to avoid inconsistent and biased estimators of the causal effect of interest. Further, we demonstrate that the forward selection algorithm has properties compatible with principles of direction of dependence, i.e., probing whether the causal target model is correctly specified with respect to the causal direction of effects. Results of a Monte Carlo simulation study suggest that the selection algorithm performs well, in particular when sample sizes are large (i.e., n ≥ 250) and data strongly deviate from Gaussianity (e.g., distributions with skewness beyond 1.5). An empirical example is given for illustrative purposes.
PubDate: 2023-09-13
- Reliability of gaze-contingent perimetry
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Abstract: Abstract Standard automated perimetry, a psychophysical task performed routinely in eyecare clinics, requires observers to maintain fixation for several minutes at a time in order to measure visual field sensitivity. Detection of visual field damage is confounded by eye movements, making the technique unreliable in poorly attentive individuals and those with pathologically unstable fixation, such as nystagmus. Microperimetry, which utilizes ‘partial gaze-contingency’ (PGC), aims to counteract eye movements but only corrects for gaze position errors prior to each stimulus onset. Here, we present a novel method of visual field examination in which stimulus position is updated during presentation, which we refer to as ‘continuous gaze-contingency’ (CGC). In the first part of this study, we present three case examples that demonstrate the ability of CGC to measure the edges of the physiological blind spot in infantile nystagmus with greater accuracy than PGC and standard ‘no gaze-contingency’ (NoGC), as initial proof-of-concept for the utility of the paradigm in measurements of absolute scotomas in these individuals. The second part of this study focused on healthy observers, in which we demonstrate that CGC has the lowest stimulus positional error (gaze-contingent precision: CGC = ± 0.29°, PGC = ± 0.54°, NoGC = ± 0.81°). CGC test–retest variability was shown to be at least as good as both PGC and NoGC. Overall, CGC is supported as a reliable method of visual field examination in healthy observers. Preliminary findings demonstrate the spatially accurate estimation of visual field thresholds related to retinal structure using CGC in individuals with infantile nystagmus.
PubDate: 2023-09-11
- Are they equivalent' An examination of task variants of approximate
number comparison-
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Abstract: Abstract Nonverbal numerical ability supports individuals’ numerical information processing in everyday life and is also correlated with their learning of mathematics. This ability is typically measured with an approximate number comparison paradigm, in which participants are presented with two sets of objects and instructed to choose the numerically larger set. This paradigm has multiple task variants, where the two sets are presented in different ways (e.g., two sets are presented either simultaneously or sequentially, or two sets are presented either intermixed or separately). Despite the fact that different task variants have often been used interchangeably, it remains unclear whether these variants measure the same aspects of nonverbal numerical ability. Using a latent variable modeling approach with 270 participants (Mage = 20.75 years, SDage = 2.03, 94 males), this study examined the degree to which three commonly used task variants tapped into the same construct. The results showed that a bi-factor model corresponding to the hypothesis that task variants had both commonalities and uniqueness was a better fit for the data than a single-factor model, corresponding to the hypothesis that task variants were construct equivalent. These findings suggested that task variants of approximate number comparison did not measure the same construct and cannot be used interchangeably. This study also quantified the extent to which general cognitive abilities were involved in both common and unique parts of these task variants.
PubDate: 2023-09-11
- Social media emotions annotation guide (SMEmo): Development and initial
validity-
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Abstract: Abstract The proper measurement of emotion is vital to understanding the relationship between emotional expression in social media and other factors, such as online information sharing. This work develops a standardized annotation scheme for quantifying emotions in social media using recent emotion theory and research. Human annotators assessed both social media posts and their own reactions to the posts’ content on scales of 0 to 100 for each of 20 (Study 1) and 23 (Study 2) emotions. For Study 1, we analyzed English-language posts from Twitter (N = 244) and YouTube (N = 50). Associations between emotion ratings and text-based measures (LIWC, VADER, EmoLex, NRC-EIL, Emotionality) demonstrated convergent and discriminant validity. In Study 2, we tested an expanded version of the scheme in-country, in-language, on Polish (N = 3648) and Lithuanian (N = 1934) multimedia Facebook posts. While the correlations were lower than with English, patterns of convergent and discriminant validity with EmoLex and NRC-EIL still held. Coder reliability was strong across samples, with intraclass correlations of .80 or higher for 10 different emotions in Study 1 and 16 different emotions in Study 2. This research improves the measurement of emotions in social media to include more dimensions, multimedia, and context compared to prior schemes.
PubDate: 2023-09-11
- Test–retest reliability of reinforcement learning parameters
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Abstract: Abstract It has recently been suggested that parameter estimates of computational models can be used to understand individual differences at the process level. One area of research in which this approach, called computational phenotyping, has taken hold is computational psychiatry. One requirement for successful computational phenotyping is that behavior and parameters are stable over time. Surprisingly, the test–retest reliability of behavior and model parameters remains unknown for most experimental tasks and models. The present study seeks to close this gap by investigating the test–retest reliability of canonical reinforcement learning models in the context of two often-used learning paradigms: a two-armed bandit and a reversal learning task. We tested independent cohorts for the two tasks (N = 69 and N = 47) via an online testing platform with a between-test interval of five weeks. Whereas reliability was high for personality and cognitive measures (with ICCs ranging from .67 to .93), it was generally poor for the parameter estimates of the reinforcement learning models (with ICCs ranging from .02 to .52 for the bandit task and from .01 to .71 for the reversal learning task). Given that simulations indicated that our procedures could detect high test–retest reliability, this suggests that a significant proportion of the variability must be ascribed to the participants themselves. In support of that hypothesis, we show that mood (stress and happiness) can partly explain within-participant variability. Taken together, these results are critical for current practices in computational phenotyping and suggest that individual variability should be taken into account in the future development of the field.
PubDate: 2023-09-08
- Validation of scrambling methods for vocal affect bursts
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Abstract: Abstract Studies on perception and cognition require sound methods allowing us to disentangle the basic sensory processing of physical stimulus properties from the cognitive processing of stimulus meaning. Similar to the scrambling of images, the scrambling of auditory signals is aimed at creating stimulus instances that are unrecognizable but have comparable low-level features. In the present study, we generated scrambled stimuli of short vocalizations taken from the Montreal Affective Voices database (Belin et al., Behav Res Methods, 40(2):531–539, 2008) by applying four different scrambling methods (frequency-, phase-, and two time-scrambling transformations). The original stimuli and their scrambled versions were judged by 60 participants for the apparency of a human voice, gender, and valence of the expressions, or, if no human voice was detected, for the valence of the subjective response to the stimulus. The human-likeness ratings were reduced for all scrambled versions relative to the original stimuli, albeit to a lesser extent for phase-scrambled versions of neutral bursts. For phase-scrambled neutral bursts, valence ratings were equivalent to those of the original neutral burst. All other scrambled versions were rated as slightly unpleasant, indicating that they should be used with caution due to their potential aversiveness.
PubDate: 2023-09-06
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