Date of Award
1-27-2022
Degree Name
Doctor of Philosophy (PhD)
Degree Type
Dissertation
Abstract
Stroke is a leading source of adult disability. Many chronic stroke patients never fully regain the use of their affected limb. Providing effective rehabilitation to chronically hemiparetic stroke patients is crucial for improving the lives of these patients. Brain-computer interfaces (BCIs) have emerged as a promising approach for developing new, effective therapies for both acute and chronic stroke patients. Specifically, an EEG-based BCI using signals from motor regions of the non-lesioned hemisphere was shown to promote clinically significant upper motor rehabilitation in a chronic stroke population. This is a major advance for expanding therapy access to patients who previously did not substantially benefit from existing therapies. However, we do not yet fully understand how BCIs effect change in the functional organization of the brain to drive motor recovery. Determining how contralesional BCI therapy affects the brain will enable further improvements to BCI therapy systems, as well as targeted approaches for individual patients. Comparing therapy approaches may also inform how the brain generally reacts to stroke rehabilitation. This project examines changes in the resting-state functional organization of the brain by comparing shifts in fMRI and EEG connectivity to contemporaneous motor function improvement in a cohort of chronic stroke patients using a contralesional BCI for 12 weeks. We were particularly interested in the reorganization of the motor network as it related to motor recovery. We measured changes in functional connectivity between several cortical and cerebellar motor regions using fMRI data. Overall, motor network connectivity decreased in these patients, and this decrease correlated with motor recovery. The specific ROI pairs driving this decrease varied among patients. A comparison group of chronic stroke patients using intensive physical therapy to achieve motor recovery did not show these same effects. Contralesional BCI therapy may therefore promote recovery differently from standard approaches. The EEG data offers a complementary perspective to the fMRI data, as it provides a detailed measurement of activity in a few cortical areas as opposed to coarse signal measurements in many specific regions. Alpha-band (8-12 Hz) coherence between two motor electrodes increased following 12 weeks of contralesional BCI therapy, and this increase correlated with motor recovery. Delta (1-4 Hz), alpha, and beta (13-30 Hz) band activity have all been previously implicated in stroke recovery, but we observed effects only in alpha. Although at first glance, an increase in motor coherence and a decrease in BOLD connectivity may seem to disagree with each other, but these signals have different physiological sources. An increase in motor alpha coherence may be driven by a decrease in activity in inhibitory thalamocortical circuits which are thought to drive the alpha rhythm. Future BCI systems may specifically modulate alpha coherence or thalamocortical activity to further boost recovery. Additional research is necessary to improve BCI design, and to potentially enable them to change their behavior to provide the best therapy possible for each individual patient.
Language
English (en)
Chair
Eric Leuthardt
Committee Members
Alexandre Carter