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Boutet, D.

Publications and source records attributed to Boutet, D..

2 recordsLinked to original sources

Distributed neurophysiological dynamics link perception, action, and language in schizophrenia

Schizophrenia is characterized by disturbances in both perception and expression that profoundly impair social functioning, yet these domains are typically studied in isolation. Predictive processing theories suggest that such symptoms may arise from abnormal updating of internal models, but the neural mechanisms linking perceptual and expressive dysfunction remain unclear. Using magnetoencephalography during multisensory perception and motor tasks, we tested whether beta-band activity (15-30 Hz), a neural signal implicated in predictive control, provides a shared substrate across domains. Compared to healthy individuals, patients with schizophrenia showed attenuated event-related modulation of beta activity, including weaker beta suppression during sensory processing and delayed or reduced post-movement beta rebound. These abnormalities were associated with a widened audiovisual temporal binding window, indicating atypical multisensory integration. Multivariate analyses further revealed that reduced beta modulation across sensory and motor systems covaried with impoverished semantic diversity, simplified syntactic structure in natural speech, and greater clinical symptom burden. Notably, beta abnormalities emerged as distributed latent patterns spanning sensory, motor, and frontotemporal regions. Together, these findings identify diminished event-related beta modulation as a common neural signature linking disrupted multisensory integration, action monitoring, and language organization in schizophrenia. We situate perceptual and expressive impairments within a unified framework of predictive dysfunction and advance a mechanistically grounded account that highlights beta dynamics as a promising target for future mechanistic and translational studies in psychosis. Significance StatementSchizophrenia disrupts both how people perceive the world and how they express their thoughts, yet these symptoms are usually studied separately. Using magnetoencephalography during multisensory and motor tasks, we identify a shared neural mechanism linking these domains: reduced event-related modulation of beta-band (15-30 Hz) activity, a signal implicated in predictive control. Compared to healthy individuals, patients showed diminished beta changes during sensory processing and movement completion, suggesting reduced flexibility in updating internal models. Importantly, this neural pattern covaried with abnormal audiovisual binding, disorganized natural speech, and greater clinical severity. These findings reveal distributed beta modulation as a cross-domain neural marker of predictive dysfunction, offering a unified framework for understanding perceptual and expressive disturbances in schizophrenia.

neuroscience↗

The Cortical Temporal Axis: MEG-Based Cross-Frequency Gradients with Biological Anchors

Neural oscillations have long been used to characterize the temporal dynamics of individual brain regions, yet a parsimonious, system-level representation that integrates multi-rhythmic activity has been lacking. Using source-localized resting-state magnetoencephalography (MEG) data, we computed regional power spectra and assessed spectral similarity, then applied diffusion map embedding to construct cross-frequency neurophysiological gradients that place whole-brain oscillations within a unified, low-dimensional coordinate system. We found the first three gradients accounted for over 40% of the variance, remained stable across individuals, and aligned with established functional, structural, and geometric cortical axes. Computational modeling showed that these gradients reflect local excitation-inhibition balance, while multimodal analyses revealed strong associations with neurotransmitter receptor distributions, cytoarchitecture, and cell-type-specific gene expression. Lifespan analyses further demonstrated systematic gradient reorganization, with distinct cognitive mappings onto functions such as language, memory, and multisensory integration. Clinically, Parkinsons disease patients displayed disrupted gradients, particularly in regions linked to language and social cognition. Finally, these gradient patterns exhibited high test-retest reliability. These findings establish MEG-derived neurophysiological gradients as robust, low-dimensional representations of cortical organization, offering a biologically grounded framework for studying brain aging and disease.

neuroscience↗