ArticleCognitive neurodynamics2025
Electroencephalography evidence of functional connectivity modulation and its correlation with bimanual visuomotor learning.
Article in Cognitive neurodynamics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Recent studies have shown that neuroplasticity related to sensorimotor adaptation can occur within short time frames, ranging from minutes to hours. However, it remains unclear whether bimanual training can induce similar effects. Therefore, the objective is to investigate immediate functional brain changes following brief bimanual visuomotor adaptation training. Node and edge-level electroencephalogram functional connectivity analysis and principal component regression were employed to examine changes related to visuomotor tracking task performance. The results revealed significant post-training improvements in bimanual performance, along with decreased node closeness centrality in the non-dominant right frontal and sensorimotor regions within the beta band, as well as in the right frontal, sensorimotor, and occipital regions within the gamma band. Edge-wise analysis indicated reduced beta- and gamma-band connectivity in the right hemisphere, aligning with the node-wise findings. Additionally, theta-band closeness centrality in the frontal, centroparietal, occipital, and temporal regions was positively correlated with bimanual performance, indicating a shift toward more centralized processing as performance increased. Principal component regression further demonstrated its predictive value for bimanual visuomotor performance. This study demonstrates that brief bimanual training elicits immediate functional connectivity changes associated with improved motor performance, particularly reduced right hemisphere beta/gamma connectivity and increased theta centrality. These findings highlight dynamic neural reorganization during bimanual adaptation. However, the interpretation of the results is limited by small sample size, EEG's low spatial resolution, and bias in functional connectivity estimation. These findings provide insights into adaptation mechanisms that could inform rehabilitation strategies for individuals with motor impairments.
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