Document Type
Article
Publication Date
2-21-2025
Abstract
INTRODUCTION: Intracortical Brain-computer interfaces (iBCIs) are a promising technology to restore function after stroke. It remains unclear whether iBCIs will be able to use the signals available in the neocortex overlying stroke affecting the underlying white matter and basal ganglia.
METHODS: Here, we decoded both local field potentials (LFPs) and spikes recorded from intracortical electrode arrays in a person with chronic cerebral subcortical stroke performing various tasks with his paretic hand, with and without a powered orthosis. Analysis of these neural signals provides an opportunity to explore the electrophysiological activities of a stroke affected brain and inform the design of medical devices that could restore function.
RESULTS: The frequency domain analysis showed that as the distance between an array and the stroke site increased, the low frequency power decreased, and high frequency power increased. Coordinated cross-channel firing of action potentials while attempting a motor task and cross-channel simultaneous low frequency bursts while relaxing were also observed. Using several offline analysis techniques, we propose three features for decoding motor movements in stroke-affected brains.
DISCUSSION: Despite the presence of unique activities that were not reported in previous iBCI studies with intact brain functions, it is possible to decode motor intents from the neural signals collected from a subcortical stroke-affected brain.
Recommended Citation
Shawki, Nabila; Naopli, Alessandro; Vargas-Irwin, Carlos E.; Thompson, Christopher K.; Donoghue, John P.; and Serruya, Mijail D., "Neural Signal Analysis in Chronic Stroke: Advancing Intracortical Brain-Computer Interface Design" (2025). Department of Medicine Faculty Papers. Paper 516.
https://jdc.jefferson.edu/medfp/516
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
PubMed ID
40060267
Language
English
Comments
This article is the author's final published version in Frontiers in Human Neuroscience, Volume 19, February 2025, Article number 1544397.
The published version is available at https://doi.org/10.3389/fnhum.2025.1544397. Copyright © 2025 Shawki, Napoli, Vargas-Irwin, Thompson, Donoghue and Serruya. First publication by Frontiers Media.