Biophysical mechanisms governing large‐scale brain network dynamics underlying individual‐specific variability of perception

Abstract

Perception necessitates interaction among 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 audiovisual (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 nonspecific associative/integrative regions. Subsequently, we could predict that an extremely weak direct AV coupling results 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 and action task paradigms.

Editorial: Temporal Structure of Neural Processes Coupling Sensory, Motor and Cognitive Functions of the Brain

“…The EEG data further revealed an event-related potential (ERP), phase-locked to the flicker, fluctuating at 10 Hz, suggesting an increase in the certainty about the physical time-dimension in the neural circuits of the brain, which can be analyzed as mutual information. Authors also found desynchronization of spontaneous neural oscillations during the flicker observation period, which is consistent with the presence of desynchronization during information processing (Kumar et al, 2020 ). Furthermore, during time reproduction, there was an increase of the spontaneous alpha oscillation amplitude.…”

Atypical core-periphery brain dynamics in autism

“…In recent work using EEG- and fMRI-based neuroimaging evidence, it was found in healthy young individuals that the time differences of cross-modal perception may particularly tax multisensory processing and temporal dichotomy of dual-stream processing (streams for action versus stimulus awareness), in which local sensory stimuli must be integrated from two modalities (audio and visual, for example). In particular during dynamic perception, the sensory signals are built up and integrated over time (Kumar et al, 2016 ; Kumar, Dutta, Talwar, Roy, & Banerjee, 2012 ; Ray et al, 2020 ).…”

Predicting Response to McGurk Illusion Based on Periodic and Aperiodic Prestimulus EEG Activity

“…Studies have reported variability among participants perceiving the McGurk illusion. This variability arises because some participants experience the McGurk illusion more frequently than others (MMK Benoit et al ., 2010; Nath & Beuchamp, 2012; Strand JF et al ., 2014; Mallick et al ., 2015; Kumar et al ., 2020).…”