Individual Differences in Multisensory Processing Are Related to Broad Differences in the Balance of Local versus Distributed Information

Abstract

Abstract The brain's ability to extract information from multiple sensory channels is crucial to perception and effective engagement with the environment, but the individual differences observed in multisensory processing lack mechanistic explanation. We hypothesized that, from the perspective of information theory, individuals with more effective multisensory processing will exhibit a higher degree of shared information among distributed neural populations while engaged in a multisensory task, representing more effective coordination of information among regions. To investigate this, healthy young adults completed an audiovisual simultaneity judgment task to measure their temporal binding window (TBW), which quantifies the ability to distinguish fine discrepancies in timing between auditory and visual stimuli. EEG was then recorded during a second run of the simultaneity judgment task, and partial least squares was used to relate individual differences in the TBW width to source-localized EEG measures of local entropy and mutual information, indexing local and distributed processing of information, respectively. The narrowness of the TBW, reflecting more effective multisensory processing, was related to a broad pattern of higher mutual information and lower local entropy at multiple timescales. Furthermore, a small group of temporal and frontal cortical regions, including those previously implicated in multisensory integration and response selection, respectively, played a prominent role in this pattern. Overall, these findings suggest that individual differences in multisensory processing are related to widespread individual differences in the balance of distributed versus local information processing among a large subset of brain regions, with more distributed information being associated with more effective multisensory processing. The balance of distributed versus local information processing may therefore be a useful measure for exploring individual differences in multisensory processing, its relationship to higher cognitive traits, and its disruption in neurodevelopmental disorders and clinical conditions.