ArticleNature biomedical engineering2026
Invasive neurophysiology and whole brain connectomics for neural decoding in patients with brain implants.
Article in Nature biomedical engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Activity-dependent adaptive deep brain stimulation improves gait in Parkinson's disease.Nature medicine · 2026Article
- Adaptive deep brain stimulation in Parkinson disease: clinical implementation and outlook.Nature reviews. Neurology · 2026Article
- Deep learning-enabled versatile shape perception for soft robots via single-ended multimode fiber.Science advances · 2026Article
- Full-Stack Architectures for Intelligent Brain-Computer Interfaces.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Multitarget brain implants enable generalized decoding of Parkinson's disease symptoms from chronic home recordings.Research square · 2026Article
- AI-based discovery of functional boundaries in the human brain from intraoperative electrophysiology.medRxiv : the preprint server for health sciences · 2026Article
- Neural circuit mechanisms of epilepsy: Maintenance of homeostasis at the cellular, synaptic, and neurotransmitter levels.Neural regeneration research · 2026Article
- Decoding the impact of visual states on adaptive deep brain stimulation feedback signals in movement disorders.NPJ Parkinson's disease · 2026Article
- Translational prospectives for deep brain stimulation and low-intensity focused ultrasound neuromodulation: IFCN Handbook chapter.Clinical neurophysiology practice · 2026Review
- Decoding visual object recognition from EEG signals.PloS one · 2026Article
- Deep brain stimulation clinical trials: a framework to accelerate recruitment, retention, and technology translation.Frontiers in human neuroscience · 2026Article
- Proceedings of the 13th annual deep brain stimulation think tank: the evolving landscape.Frontiers in human neuroscience · 2026Review
- Subthalamic Nucleus Oscillatory Characteristics in Meige, Cervical Dystonia and Generalized Dystonia.Annals of clinical and translational neurology · 2025Article
- Neuromorphic algorithms for brain implants: a review.Frontiers in neuroscience · 2025Review
- Review
- Dopamine and deep brain stimulation accelerate the neural dynamics of volitional action in Parkinson's disease.Brain : a journal of neurology · 2024Article
- Ethological computational psychiatry: Challenges and opportunities.Current opinion in neurobiology · 2024Review
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Authors and funding
31 authors.
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Abstract
Brain-computer interface research can inspire closed-loop neuromodulation therapies, promising spatiotemporal precision for the treatment of brain disorders. Decoding dynamic patient states from brain signals with machine learning is required to leverage this precision, but a standardized framework for invasive brain signal decoding from neural implants does not exist. Here we develop a platform that integrates brain signal decoding with magnetic resonance imaging connectomics and demonstrate its use across 123 h of invasively recorded brain data from 73 neurosurgical patients treated with brain implants for movement disorders, depression and epilepsy. We introduce connectomics-informed movement decoders that generalize across cohorts with Parkinson's disease and epilepsy from the United States, Europe and China. We reveal network targets for emotion decoding in left prefrontal and cingulate circuits in deep brain stimulation patients with major depression. Finally, we showcase opportunities to improve seizure detection in responsive neurostimulation for epilepsy. Our study highlights the clinical use of brain signal decoding for deep brain stimulation and provides methods that allow for rapid, high-accuracy decoding for precision medicine approaches that can dynamically adapt neurotherapies in response to the individual needs of patients.
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