ArticleNeurosurgical focus2020
Clinical applications of neurochemical and electrophysiological measurements for closed-loop neurostimulation.
Article in Neurosurgical focus, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Is Deep Brain Stimulation an Effective Treatment for Psychostimulant Dependency? A Preclinical and Clinical Systematic Review.Neurochemical research · 2023Pooled it
- Closed-Loop Neuromodulation for Brain Fatigue: From Real-Time Biomarkers to Adaptive Intervention.International journal of molecular sciences · 2026Review
- From trade-offs to translation: An interdisciplinary roadmap for neurotechnology.Science advances · 2026Review
- Measurement of electrochemical brain activity with fast-scan cyclic voltammetry during functional magnetic resonance imaging.Nature protocols · 2026Review
- Opportunities and challenges for deep brain stimulation electrode-guided neurofeedback for symptom mitigation in neurological and psychiatric disorders.Journal of neuroengineering and rehabilitation · 2025Review
- Neuromodulation in Small Animal fMRI.Journal of magnetic resonance imaging : JMRI · 2025Review
- Chronic Pain and Obsessive-Compulsive Disorder: A Scoping Review.Pain and therapy · 2025Review
- Regulation of Stress-Induced Immunosuppression in the Context of Neuroendocrine, Cytokine, and Cellular Processes.Biology · 2025Review
- Biomarkers: The Key to Enhancing Deep Brain Stimulation Treatment for Psychiatric Conditions.Brain sciences · 2024Review
- The evolution of neuromodulation for chronic stroke: From neuroplasticity mechanisms to brain-computer interfaces.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2024Review
- Wireless closed-loop deep brain stimulation using microelectrode array probes.Journal of Zhejiang University. Science. B · 2024Review
- Computational Neurosurgery in Deep Brain Stimulation.Advances in experimental medicine and biology · 2024Review
- Cerebellar activity in hemi-parkinsonian rats during volitional gait and freezing.Brain communications · 2024Article
- Dual-Target Deep Brain Stimulation for Obsessive-Compulsive Disorder and Tourette Syndrome.Biological psychiatry · 2023Article
- Closed-Loop Adaptive Deep Brain Stimulation in Parkinson's Disease: Procedures to Achieve It and Future Perspectives.Journal of Parkinson's disease · 2023Review
- Biomarkers for Deep Brain Stimulation in Animal Models of Depression.Neuromodulation : journal of the International Neuromodulation Society · 2022Review
- Closed-Loop Tracking and Regulation of Emotional Valence State From Facial Electromyogram Measurements.Frontiers in computational neuroscience · 2022Article
- Simultaneous fMRI and fast-scan cyclic voltammetry bridges evoked oxygen and neurotransmitter dynamics across spatiotemporal scales.NeuroImage · 2021Article
- Altered plasma glutamate and glutamine levels in patients with drug-resistant and drug-responsive symptomatic focal epilepsy.Neurosciences (Riyadh, Saudi Arabia) · 2021Article
- Therapy for Alzheimer's disease: Missing targets and functional markers?Ageing research reviews · 2021Review
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
The development of closed-loop deep brain stimulation (DBS) systems represents a significant opportunity for innovation in the clinical application of neurostimulation therapies. Despite the highly dynamic nature of neurological diseases, open-loop DBS applications are incapable of modifying parameters in real time to react to fluctuations in disease states. Thus, current practice for the designation of stimulation parameters, such as duration, amplitude, and pulse frequency, is an algorithmic process. Ideal stimulation parameters are highly individualized and must reflect both the specific disease presentation and the unique pathophysiology presented by the individual. Stimulation parameters currently require a lengthy trial-and-error process to achieve the maximal therapeutic effect and can only be modified during clinical visits. The major impediment to the development of automated, adaptive closed-loop systems involves the selection of highly specific disease-related biomarkers to provide feedback for the stimulation platform. This review explores the disease relevance of neurochemical and electrophysiological biomarkers for the development of closed-loop neurostimulation technologies. Electrophysiological biomarkers, such as local field potentials, have been used to monitor disease states. Real-time measurement of neurochemical substances may be similarly useful for disease characterization. Thus, the introduction of measurable neurochemical analytes has significantly expanded biomarker options for feedback-sensitive neuromodulation systems. The potential use of biomarker monitoring to advance neurostimulation approaches for treatment of Parkinson's disease, essential tremor, epilepsy, Tourette syndrome, obsessive-compulsive disorder, chronic pain, and depression is examined. Further, challenges and advances in the development of closed-loop neurostimulation technology are reviewed, as well as opportunities for next-generation closed-loop platforms.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.