Subthalamic deep brain stimulation (DBS) for Parkinson disease (PD) currently requires laborious open-loop programming, which can mitigate the benefits of this treatment. Experimental closed-loop DBS systems are emerging that can sense the electrophysiological surrogates of PD motor signs and respond with delivery of an automatically adapted stimulation. Such biomarker-based neural interfaces constitute a major advance towards improving the outcomes of patients treated with DBS and enhancing our understanding of the pathophysiological mechanisms underlying PD. In this Perspectives article, we argue that closed-loop DBS, in addition to offering advantages in patients with PD, might extend the current indications for DBS to include selected psychiatric disorders in which the symptoms are similarly driven by pathological brain circuit activity. The success of closed-loop DBS in such settings will depend on the identification of symptom-specific biomarkers, which ideally should reflect causal mechanisms of the underlying pathology.
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http://dx.doi.org/10.1038/s41582-019-0166-4 | DOI Listing |
NPJ Parkinsons Dis
January 2025
Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.
Sensing-based deep brain stimulation should optimally consider both the motor and neuropsychiatric domain to maximize quality of life of Parkinson's disease (PD) patients. Here we characterize the neurophysiological properties of the subthalamic nucleus (STN) in 69 PD patients using a newly established neurophysiological gradient metric and contextualize it with motor symptoms and apathy. We could evidence a STN power gradient that holds most of the spectral information between 5 and 30 Hz spanning along the dorsal-ventral axis.
View Article and Find Full Text PDFNat Biomed Eng
December 2024
Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
Deep brain stimulation (DBS), a proven treatment for movement disorders, also holds promise for the treatment of psychiatric and cognitive conditions. However, for DBS to be clinically effective, it may require DBS technology that can alter or trigger stimulation in response to changes in biomarkers sensed from the patient's brain. A growing body of evidence suggests that such adaptive DBS is feasible, it might achieve clinical effects that are not possible with standard continuous DBS and that some of the best biomarkers are signals from the cerebral cortex.
View Article and Find Full Text PDFSTAR Protoc
December 2024
Weldon School of Biomedical Engineering, the Center for Implantable Devices, and the Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN 47907, USA; Department of Biological Sciences, Purdue University, West Lafayette, IN 47907, USA. Electronic address:
Closed-loop neural control is a powerful tool for both the scientific exploration of neural function and for mitigating deficiencies found in open-loop deep brain stimulation (DBS). Here, we present a protocol for artificial intelligence-guided neural control in rats using deep reinforcement learning (RL) and infrared neural stimulation (INS). We describe steps for integrating RL closed-loop control into neuroscience and neuromodulation studies.
View Article and Find Full Text PDFIEEE Trans Affect Comput
April 2024
Department of Psychology, University of Pittsburgh, Pittsburgh, PA 15213 USA.
To develop reliable, valid, and efficient measures of obsessive-compulsive disorder (OCD) severity, comorbid depression severity, and total electrical energy delivered (TEED) by deep brain stimulation (DBS), we trained and compared random forests regression models in a clinical trial of participants receiving DBS for refractory OCD. Six participants were recorded during open-ended interviews at pre- and post-surgery baselines and then at 3-month intervals following DBS activation. Ground-truth severity was assessed by clinical interview and self-report.
View Article and Find Full Text PDFNeuromodulation
December 2024
Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China; Ministry of Education Frontiers Center for Brain Science, Fudan University, Shanghai, China; Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China; Academy for Engineering and Technology, Fudan University, Shanghai, China. Electronic address:
Objective: This study aims to facilitate the translation of innovative closed-loop deep brain stimulation (DBS) strategies from theory to practice by establishing a research platform. The platform addresses the challenges of real-time stimulation artifact removal, low-latency feedback stimulation, and rapid translation from animal to clinical experiments.
Materials And Methods: The platform comprises hardware for neural sensing and stimulation, a closed-loop software framework for real-time data streaming and computation, and an algorithm library for implementing closed-loop DBS strategies.
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