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Roy, D.

Publications and source records attributed to Roy, D..

74 records · Page 5Linked to original sources

Neurodynamic explanation of inter-individual and inter-trial variability in cross-modal perception

A widely used experimental design in multisensory integration is the McGurk paradigm that entail illusory (cross-modal) perception of speech sounds when presented with incongruent audio-visual (AV) stimuli. However, the distribution of responses across trials and individuals is heterogeneous and not necessarily everyone in a given group of individuals perceives the effect. Nonetheless, existing studies in the field primarily focus on addressing the correlation between subjective behavior and cortical activations to reveal the neuronal mechanisms underlying the perception of McGurk effect, typically in the \"frequent perceivers\". Additionally, a solely neuroimaging approach does not provide mechanistic explanation for the observed inter-trial or inter-individual heterogeneity. In the current study we employ high density electroencephalogram (EEG) recordings in a group of 25 human subjects that allow us to distinguish \"frequent perceivers\" from \"rare perceivers\" using behavioral responses as well as from the perspective of large-scale brain functional connectivity (FC). Using global coherence as a measure of large-scale FC, we find that alpha band coherence, a distinctive feature in frequent perceivers is absent in the rare perceivers. Secondly, a decrease in alpha band coherence and increase in gamma band coherence occur during illusory perception trials in both frequent and rare perceivers. Source analysis followed up with source time series reconstructions reveals a large scale network of brain areas involving frontal, temporal and parietal areas that are involved in network level processing of cross-modal perception. Finally, we demonstrate that how a biophysically realistic computational model representing the interaction among key neuronal systems (visual, auditory and multisensory cortical regions) can explain the empirical observations. Each system involves a group of excitatory and inhibitory Hindmarsh Rose neurons that are coupled amongst each other. Large-scale FC between areas is conceptualized using coupling functions and the identity of a specific system, e.g., visual/ auditory/ multisensory is chosen using empirical estimates of the time-scale of information processing in these systems. The model predicts that the disappearance of alpha band coherence observed in rare perceivers stems from a negligible direct A-V (audio-visual) coupling however, an increase in indirect interaction via multisensory node leads to enhanced gamma band and reduced alpha band coherences observed during illusory perception. Overall, we establish the mechanistic basis of large-scale FC patterns underlying cross-modal perception.

neuroscience↗

Integration and segregation in Autism Spectrum Disorders modulated by age, disease, and interaction: A graph-theoretic study of intrinsic functional connectivity

Autism spectrum disorder (ASD) is a neurodevelopmental disorder affecting 1 in 50 children between the ages of 6 and 17 years. Brain connectivity and graph theoretic methods have been particularly very useful in shedding light on the differences between high functioning autistic children compared to typically developing (TD) ones. However, very recent developments in network measures raise a cautionary note by highlighting gross under- and over-connectivity in ASD may be an oversimplified hypothesis. Thus the primary aim of our study is to investigate these notions in functional connectomics of ASD versus TD by subjecting the data to reproducibility experiments using two independent datasets.\n\nFurther, we tested the hypothesis of alteration in network segregation and integration in the ASD subjects. We have analyzed the resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) data from the University of California Los Angeles (UCLA) multimodal connectivity database (n=42 ASD, n=37 TD) and rs-fMRI data from the Autism Brain Imaging Data Exchange (ABIDE) (n=187 ASD, n=176 TD) dataset. We assessed the differences in connection strength between TD and ASD subjects. We also performed graph theoretical analysis to analyze the effect of disease on various network measures. Further, using the larger ABIDE dataset, we performed two-factor ANOVA test, to study the effect of age, disease and their interaction by classifying the TD and ASD participants into two cohorts: children (9-12 years, n=73 TD and n=87 ASD) and adolescents (13-16 years, n=103 TD and n=100 ASD). In ASD, we show the existence of atypical connectivity within and between functional networks as compared to TD. We also found in ASD both hypo-and hyper-connectivity within functional networks such as the default mode network (DMN). Further, graph theoretic analysis showed that there is significant effect of age and disease on modularity, clustering coefficient, and local efficiency. We also identified specific areas within the DMN, sensorimotor, visual and attention networks that are affected by age, disease and their interaction. Overall, our findings suggest that maturation, disease and their interaction are critical for unraveling the biological basis and developmental trajectory in ASD and other neuropsychiatric disorders.

neuroscience↗