Biology subjects

Kumar, V. G.

Publications and source records attributed to Kumar, V. G..

3 recordsLinked to original sources

bioRxiv2022

Characterizing Variability of Audiovisual Speech Perception Based on Periodic and Aperiodic Features of Prestimulus Brain Activity

Studies have reported that prestimulus brain oscillations guide perceptual experiences during AV speech perception. However, what features of these prestimulus activity drives perception remains unknown. In this electroencephalography (EEG) study, we investigated the relationship between prestimulus periodic oscillations and aperiodic components with subsequent perception of the McGurk illusion at single-trial levels. Using logistic mixed-effect models, we determined which spectral features from different sensor regions predicted response to the illusory perception. We found that lower alpha (8-12 Hz) and beta (15-30 Hz) band oscillations over parieto-occipital sensors predicted illusion perception. We also found lower aperiodic offset values over parieto-temporal sensors, and lower global effect of exponent over the scalp, that predicted the response to McGurk illusion. We conclude that the predominant source of the prestimulus oscillatory state is aperiodic background activity, and that variations in these arrhythmic components account for inter-trial and inter-individual variability in perception of the McGurk illusion.

neuroscience↗

bioRxiv2019

Biophysical mechanisms to relate large-scale brain network dynamics to individual-specific variability of perception

Perception necessitates interaction amongst neuronal ensembles, the dynamics of which can be conceptualized as the emergent behavior of coupled dynamical systems. Here, we propose a detailed neurobiologically realistic model that captures the neural mechanisms of inter-individual variability observed in cross-modal speech perception. From raw EEG signals recorded from human participants when they were presented with speech vocalizations of McGurk-incongruent and congruent audio-visual (AV) stimuli, we computed the global coherence metric to capture the neural variability of large-scale networks. We identified that participants McGurk susceptibility was negatively correlated to their alpha-band global coherence. The proposed biophysical model conceptualized the global coherence dynamics emerge from coupling between the interacting neural masses - representing the sensory specific auditory/visual areas and modality non-specific associative/integrative regions. Subsequently, we could predict that an extremely weak direct AV coupling result in a decrease in alpha band global coherence - mimicking the cortical dynamics of participants with higher McGurk susceptibility. Source connectivity analysis also showed decreased connectivity between sensory specific regions in participants more susceptible to McGurk effect, thus establishing an empirical validation to the prediction. Overall, our study provides an outline to link variability in structural and functional connectivity metrics to variability of performance that can be useful for several perception & action task paradigms.

neuroscience↗

bioRxiv2018

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↗