Emergence of β and γ networks following multisensory training.

Neuroimage

CEA/DRF/Joliot, Université Paris-Saclay, 91191, Gif-sur-Yvette, France; Cognitive Neuroimaging Unit, INSERM, Université Paris-Sud, Université Paris-Saclay, NeuroSpin Center, 91191, Gif-sur-Yvette, France. Electronic address:

Published: February 2020

Our perceptual reality relies on inferences about the causal structure of the world given by multiple sensory inputs. In ecological settings, multisensory events that cohere in time and space benefit inferential processes: hearing and seeing a speaker enhances speech comprehension, and the acoustic changes of flapping wings naturally pace the motion of a flock of birds. Here, we asked how a few minutes of (multi)sensory training could shape cortical interactions in a subsequent unisensory perceptual task. For this, we investigated oscillatory activity and functional connectivity as a function of individuals' sensory history during training. Human participants performed a visual motion coherence discrimination task while being recorded with magnetoencephalography. Three groups of participants performed the same task with visual stimuli only, while listening to acoustic textures temporally comodulated with the strength of visual motion coherence, or with auditory noise uncorrelated with visual motion. The functional connectivity patterns before and after training were contrasted to resting-state networks to assess the variability of common task-relevant networks, and the emergence of new functional interactions as a function of sensory history. One major finding is the emergence of a large-scale synchronization in the high γ (gamma: 60-120Hz) and β (beta: 15-30Hz) bands for individuals who underwent comodulated multisensory training. The post-training network involved prefrontal, parietal, and visual cortices. Our results suggest that the integration of evidence and decision-making strategies become more efficient following congruent multisensory training through plasticity in network routing and oscillatory regimes.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355235PMC
http://dx.doi.org/10.1016/j.neuroimage.2019.116313DOI Listing

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