Decoding of Brain Functional Connections Underlying Natural Grasp Task Using Time-Frequency Cross Mutual Information

The purpose of using electroencephalogram to explore the dynamic changes of brain functional connectivity during natural grasping tasks is to uncover the underlying mechanisms of information transmission between different brain regions during cognitive processing. This exploration aims to provide new insights for the development of brain-computer interface technology and contribute to the diagnosis and treatment of brain disorders. In this study, we used time-frequency cross mutual information to evaluate the brain functional connectivity during 3-class natural grasping tasks (palmar grasp, lateral grasp and rest state). Specifically, our analysis focused on the functional brain connectivity generated by the amplitude and phase of electroencephalogram signals within the alpha (8-13 Hz) and beta (20-30 Hz) frequency bands. To assess the differences in global coupling strength, we employed two-series correlation coefficients, between different motor periods and between different brain regions for the three motor tasks. Furthermore, it was compared that the differences in the global coupling strength between different motor periods in the same motor task. Finally, the analysis of topologic characteristics in brain functional connectivity networks between the three tasks was investigated. The findings of our study indicate that functional reorganization of frontal region closely related to external visual stimuli occurs during the motor preparation period. The onset of movement leads to a lateralized reorganization of brain functional connectivity, which is associated with the right or left of the executive hand. Both the central and parietal regions contribute prominently to motor execution, and the parietal region in particular plays an important role in the execution of fine motor movements. Further analysis revealed that it is the brain’s dynamic regulation of functional connectivity across frequency bands, amplitudes and phases, enabling it to perform multiple tasks with limited energy resources.