ArticleFrontiers in neuroscience2014
A neurochemical closed-loop controller for deep brain stimulation: toward individualized smart neuromodulation therapies.
Article in Frontiers in neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.
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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.
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Who cites it
52 citing papers in PubMed, 158 citations in OpenAlex.
- In vivo multimodal neurochemical interfaces for real-time decoding of brain circuit.Nature reviews. Neuroscience · 2026Review
- Parkinsonism-Hyperpyrexia Syndrome Following Deep Brain Stimulation Battery Depletion during the COVID-19 Pandemic: A Case Series and Review of the Literature.Movement disorders clinical practice · 2026Review
- Challenges and opportunities of acquiring cortical recordings for chronic adaptive deep brain stimulation.Nature biomedical engineering · 2025Review
- Recent Progress in Flexible Microelectrode Arrays for Combined Electrophysiological and Electrochemical Sensing.Biosensors · 2025Review
- Vibrotactile auricular vagus nerve stimulation alters limbic system connectivity in humans: A pilot study.PloS one · 2025Article
- Biochemical Sensors for Personalized Therapy in Parkinson's Disease: Where We Stand.Journal of clinical medicine · 2024Review
- Needle-Shaped Biosensors for Precision Diagnoses: From Benchtop Development to In Vitro and In Vivo Applications.Biosensors · 2024Review
- Research progress of cell treatment strategy in Parkinson's disease.Neuroscience applied · 2024Review
- Flexible and Stretchable Bioelectronics.Materials (Basel, Switzerland) · 2022Review
- Developments in Deep Brain Stimulators for Successful Aging Towards Smart Devices-An Overview.Frontiers in aging · 2022Review
- Suppression of Neuronal Firing Following Antidromic High-Frequency Stimulations on the Neuronal Axons in Rat Hippocampal CA1 Region.Frontiers in neuroscience · 2022Article
- Deep brain stimulation in Huntington's disease: a literature review.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2021Review
- Intelligent automated drug administration and therapy: future of healthcare.Drug delivery and translational research · 2021Review
- Spatiotemporal patterns of gene expression around implanted silicon electrode arrays.Journal of neural engineering · 2021Article
- Cholinergic Deep Brain Stimulation for Memory and Cognitive Disorders.Journal of Alzheimer's disease : JAD · 2021Review
- Fractional order controllers increase the robustness of closed-loop deep brain stimulation systems.Chaos, solitons, and fractals · 2020Article
- Evaluation of electrochemical methods for tonic dopamine detectionTrends in analytical chemistry : TRAC · 2020Article
- Toward guiding principles for the design of biologically-integrated electrodes for the central nervous system.Journal of neural engineering · 2020Article
- Recent advances in fast-scan cyclic voltammetry.The Analyst · 2020Review
- Finding the balance between model complexity and performance: Using ventral striatal oscillations to classify feeding behavior in rats.PLoS computational biology · 2019Article
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
Abstract
Current strategies for optimizing deep brain stimulation (DBS) therapy involve multiple postoperative visits. During each visit, stimulation parameters are adjusted until desired therapeutic effects are achieved and adverse effects are minimized. However, the efficacy of these therapeutic parameters may decline with time due at least in part to disease progression, interactions between the host environment and the electrode, and lead migration. As such, development of closed-loop control systems that can respond to changing neurochemical environments, tailoring DBS therapy to individual patients, is paramount for improving the therapeutic efficacy of DBS. Evidence obtained using electrophysiology and imaging techniques in both animals and humans suggests that DBS works by modulating neural network activity. Recently, animal studies have shown that stimulation-evoked changes in neurotransmitter release that mirror normal physiology are associated with the therapeutic benefits of DBS. Therefore, to fully understand the neurophysiology of DBS and optimize its efficacy, it may be necessary to look beyond conventional electrophysiological analyses and characterize the neurochemical effects of therapeutic and non-therapeutic stimulation. By combining electrochemical monitoring and mathematical modeling techniques, we can potentially replace the trial-and-error process used in clinical programming with deterministic approaches that help attain optimal and stable neurochemical profiles. In this manuscript, we summarize the current understanding of electrophysiological and electrochemical processing for control of neuromodulation therapies. Additionally, we describe a proof-of-principle closed-loop controller that characterizes DBS-evoked dopamine changes to adjust stimulation parameters in a rodent model of DBS. The work described herein represents the initial steps toward achieving a "smart" neuroprosthetic system for treatment of neurologic and psychiatric disorders.
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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.