At-Home Movement State Classification Using Totally Implantable Bidirectional Cortical-Basal Ganglia Neural Interface

ABSTRACT Movement decoding from invasive human recordings typically relies on a distributed system employing advanced machine learning algorithms programmed into an external computer for state classification. These brain-computer interfaces are limited to short-term studies in laboratory settings that may not reflect behavior and neural states in the real world. The development of implantable devices with sensing capabilities is revolutionizing the study and treatment of brain circuits. However, it is unknown whether these devices can decode natural movement state from recorded neural activity or accurately classify states in real-time using onboard algorithms. Here, using a totally implanted bidirectional neurostimulator to perform long-term, at-home recordings from the motor cortex and pallidum of four subjects with Parkinson’s disease, we successfully identified highly sensitive and specific personalized signatures of gait state, as determined by wearable sensors. Additionally, we demonstrated the feasibility of using these neural biomarkers to drive adaptive stimulation with the classifier embedded onboard the neurostimulator. These findings offer a pipeline for ecologically valid movement biomarker identification that can advance therapy across a variety of diseases. Competing Interest Statement The authors have declared no competing interest. Clinical Trial NCT03582891 Funding Statement This research was supported by Michael J Fox Foundation (MJFF-010435) (DDW), NIH R01NS130183 (DDW), UCSF Catalyst Grant (DDW, RR, HFA), Tianqiao and Chrissy Chen Institute (DDW). Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Institutional Review Board (IRB) at the University of California, San Francisco provided formal ethical approval for this study (IRB# 20-32847). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data Availability Data from this study can be made available upon reasonable request, provided that patient confidentiality is maintained and disclosure standards are met.