Neural subspaces of imagined movements in parietal cortex remain stable over several years in humans
Luke Bashford, Isabelle A. Rosenthal, Spencer Kellis, David A. Bjånes, Kelsie Pejsa, Bingni W. Brunton, RA Andersen
Abstract
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