Understanding bimanual coordination across small time scales from an electrophysiological perspective.

Journal article

Bimanual movement involves a variety of coordinated functions, ranging from elementary patterns that are performed automatically to complex patterns that require practice to be performed skillfully. The neural dynamics accompanying these coordination patterns are complex and rapid. By means of electro- and magneto-encephalographic approaches, it has been possible to examine these dynamics during bimanual coordination with excellent temporal resolution, which complements other neuroimaging modalities with superb spatial resolution. This review focuses on EEG/MEG studies that unravel the processes involved in movement planning and execution, motor learning, and executive functions involved in task switching and dual tasking. Evidence is presented for a spatio-temporal reorganization of the neural networks within and between hemispheres to meet increased task difficulty demands, induced or spontaneous switches in coordination mode, or training-induced neuroplastic modulation in coordination dynamics. Future theoretical developments will benefit from the integration of research techniques unraveling neural activity at different time scales. Ultimately this work will contribute to a better understanding of how the human brain orchestrates complex behavior via the implementation of inter- and intra-hemispheric coordination networks.

Authors: Rueda-Delgado, L; Solesio-Jofre, E; Serrien, D; Mantini, D; Daffertshofer, A

• Publication status: Published
• Journal: Neuroscience and biobehavioral reviews
• Volume: 47
• Pages: 614-635
• Publication date: 2014-11-01
• DOI: 10.1016/j.neubiorev.2014.10.003
• EISSN: 1873-7528
• ISSN: 0149-7634
• Language: English
• Keywords: Functional connectivity; Polyrhythms; Event-related potentials (ERPs); Electroencephalography (EEG); Magnetoencephalography (MEG); Coherence Phase synchronization; Event-related (de)synchronization (ERD/ERS); Bimanual coordination; Motor learning