Scientific Reports (May 2022)
Interaction within and between cortical networks subserving multisensory learning and its reorganization due to musical expertise
Abstract
Abstract Recent advancements in the field of network science allow us to quantify inter-network information exchange and model the interaction within and between task-defined states of large-scale networks. Here, we modeled the inter- and intra- network interactions related to multisensory statistical learning. To this aim, we implemented a multifeatured statistical learning paradigm and measured evoked magnetoencephalographic responses to estimate task-defined state of functional connectivity based on cortical phase interaction. Each network state represented the whole-brain network processing modality-specific (auditory, visual and audiovisual) statistical learning irregularities embedded within a multisensory stimulation stream. The way by which domain-specific expertise re-organizes the interaction between the networks was investigated by a comparison of musicians and non-musicians. Between the modality-specific network states, the estimated connectivity quantified the characteristics of a supramodal mechanism supporting the identification of statistical irregularities that are compartmentalized and applied in the identification of uni-modal irregularities embedded within multisensory stimuli. Expertise-related re-organization was expressed by an increase of intra- and a decrease of inter-network connectivity, showing increased compartmentalization.