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Abstract Stroke is a leading cause of adult disability worldwide, with approximately 101 million survivors globally. Over 60% of these individuals live with from long-term, often lifelong, movement impairments that significantly hinder their ability to perform essential daily activities and maintain independence. Post-stroke movement disabilities are highly associated with structural and functional changes in motor descending pathways, particularly the corticospinal tract (CST) and other indirect motor pathways via the brainstem. For decades, neuroengineers have been working to quantitively evaluate the post-stroke changes of motor descending pathways, aiming to establish a precision prognosis and tailoring treatments to post-stroke motor impairment. However, a clear and practicable technique has not yet been established as a breakthrough to change the standard of care for current clinical practice. In this review, we outline recent progress in neuroimaging, neuromodulation, and electrophysiological approaches for assessing structural and functional changes of motor descending pathways in stroke. We also discuss their limitations and challenges, arguing the need of artificial intelligence and large multi-modal data registry for a groundbreaking advance to this important topic. 

Abstract Objective: This study quantifies EEG complexity in chronic hemiparetic stroke patients performing hierarchical motor tasks, examining the degree of contralesional motor resource recruitment in maladaptive neural responses. Approach: We applied recurrence quantification analysis (RQA) and nonlinear dynamical measures to examine spatial patterns of motor-related EEG complexity under varying shoulder abduction torque levels (20% and 40%) in both stroke survivors and healthy control participants, enabling comparative analyses of adaptive neural responses. Results: Our findings show a statistically significant increase in EEG signal complexity within the contralesional hemisphere of stroke participants, particularly under higher shoulder abduction loads. Consistent with previous studies, we observed abnormal muscle coactivation patterns between proximal and distal muscles, along with distinct shifts in EMG vector direction in stroke-impaired limbs. These shifts in coactivation patterns suggest constraints in muscle coactivation patterns resulting from losses in corticofugal projections and upregulated brainstem pathways. Significance: We introduce a novel application of RQA to quantify nonlinear EEG complexity during motor execution in chronic stroke. Unlike traditional spectral or connectivity-based EEG methods, RQA quantifies temporally evolving, nonlinear recurrence patterns that reflect maladaptive contralesional motor recruitment. Our findings demonstrate that increased EEG complexity correlates with impaired motor control and reliance on compensatory pathways, offering new insight into neural reorganization after stroke. These results position RQA as a promising, clinically meaningful, and computationally efficient tool to evaluate cortical dynamics and guide targeted neurorehabilitation strategies aimed at minimizing maladaptive plasticity. 

ObjectiveThis quasi-experimental study examined the effect of repetitive finger stimulation on brain activation in eight stroke and seven control subjects, measured by quantitative electroencephalogram. MethodsWe applied 5 mins of 2-Hz repetitive bilateral index finger transcutaneous electrical nerve stimulation and compared differences pre– and post–transcutaneous electrical nerve stimulation using quantitative electroencephalogram metrics delta/alpha ratio and delta-theta/alpha-beta ratio. ResultsBetween-group differences before and after stimulation were significantly different in the delta/alpha ratio (z= −2.88,P= 0.0040) and the delta-theta/alpha-beta ratio variables (z= −3.90 withP< 0.0001). Significant decrease in the delta/alpha ratio and delta-theta/alpha-beta ratio variables after the transcutaneous electrical nerve stimulation was detected only in the stroke group (delta/alpha ratio diff = 3.87,P= 0.0211) (delta-theta/alpha-beta ratio diff = 1.19,P= 0.0074). ConclusionsThe decrease in quantitative electroencephalogram metrics in the stroke group may indicate improved brain activity after transcutaneous electrical nerve stimulation. This finding may pave the way for a future novel therapy based on transcutaneous electrical nerve stimulation and quantitative electroencephalogram measures to improve brain recovery after stroke.