Neural Coding of Finger Movements in Human Posterior Parietal Cortex and Motor Cortex

Citation

Guan, Charles (2023) Neural Coding of Finger Movements in Human Posterior Parietal Cortex and Motor Cortex. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/31rt-cy14. https://resolver.caltech.edu/CaltechTHESIS:04092023-200347393

Abstract

We use our hands constantly in our everyday lives. This seemingly simple ability is disrupted in individuals with cervical spinal cord injuries. By circumventing injured signal pathways, brain-computer interfaces (BCIs) promise to enable such individuals to control artificial limbs for everyday use. However, existing BCI limb control remains coarse and inflexible, because we do not understand how the recorded neural activity relates to dexterous movement. As a result, BCI control in physical settings remains frustratingly difficult for paralyzed users. To improve dexterous BCI control, I studied the neural coding of individual finger movements in the posterior parietal cortex and motor cortex of tetraplegic participants. These regions are directly involved in dexterous hand movements and are candidates for BCI recording implants. Finger coding matched the correlation structure and dynamics of able-bodied usage, reflecting preserved motor circuits even after paralysis. Individual finger movements of each hand were coded in a factorized, correlated manner that still allowed decoding. Participants controlled artificial fingers with state-of-the-art accuracy. Finally, we studied the temporal dynamics of neural control to understand how existing models of neural activity extend to BCI control. These findings contribute to the understanding of human hand movements and advance the development of dexterous BCIs.

Thesis Files