NeuroImageNeurosciencePeer-reviewed journal article
Emergence of β and γ networks following multisensory training
Daria La RoccaiD, Philippe CiuciuiD, Denis Alexander EngemanniD, Virginie van WassenhoveiD
Abstract
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 perceptual task, and investigated oscillatory activity and functional connectivity as a function of sensory history in training. Human participants performed a visual motion coherence discrimination task while being recorded with magnetoencephalography (MEG). 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 inter-actions following training. One main finding is the emergence of a large-scale synchronization in the high{gamma} (gamma: 60-120Hz) and {beta} (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.
- organism: human
- assay: electronic health records
- research focus: cell-cell communication
- research focus: spatial domain detection
- approach: statistical model
- approach: experimental assay
- Citations
- 10
- FWCI
- 1.47
- Field percentile
- top 15%
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