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Lookup NU author(s): Dr Luke BashfordORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2024 The Author(s). Published by IOP Publishing Ltd. Abstract: Objective. A crucial goal in brain-machine interfacing is the long-term stability of neural decoding performance, ideally without regular retraining. Long-term stability has only been previously demonstrated in non-human primate experiments and only in primary sensorimotor cortices. Here we extend previous methods to determine long-term stability in humans by identifying and aligning low-dimensional structures in neural data. Approach. Over a period of 1106 and 871 d respectively, two participants completed an imagined center-out reaching task. The longitudinal accuracy between all day pairs was assessed by latent subspace alignment using principal components analysis and canonical correlations analysis of multi-unit intracortical recordings in different brain regions (Brodmann Area 5, Anterior Intraparietal Area and the junction of the postcentral and intraparietal sulcus). Main results. We show the long-term stable representation of neural activity in subspaces of intracortical recordings from higher-order association areas in humans. Significance. These results can be practically applied to significantly expand the longevity and generalizability of brain-computer interfaces. Clinical Trials NCT01849822, NCT01958086, NCT01964261.
Author(s): Bashford L, Rosenthal IA, Kellis S, Bjanes D, Pejsa K, Brunton BW, Andersen RA
Publication type: Article
Publication status: Published
Journal: Journal of Neural Engineering
Year: 2024
Volume: 21
Issue: 4
Online publication date: 28/08/2024
Acceptance date: 12/08/2024
Date deposited: 05/03/2025
ISSN (print): 1741-2560
ISSN (electronic): 1741-2552
Publisher: Institute of Physics
URL: https://doi.org/10.1088/1741-2552/ad6e19
DOI: 10.1088/1741-2552/ad6e19
Data Access Statement: All data that support the findings of this study are included within the article (and any supplementary files). Code availability: All analyses were implemented using custom Matlab (The Mathworks Inc.) code. Code to replicate the main results are available upon reasonable request.
PubMed id: 39134021
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