ArticleNeurosurgery2020
Brain-Responsive Neurostimulation for Loss of Control Eating: Early Feasibility Study.
Article in Neurosurgery, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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.
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.
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Who cites it
9 citing papers in PubMed, 26 citations in OpenAlex.
- Brain activity associated with breakthrough food preoccupation in an individual on tirzepatide.Nature medicine · 2025Article
- Neuromorphic neuromodulation: Towards the next generation of closed-loop neurostimulation.PNAS nexus · 2024Review
- A Comprehensive Review of Emerging Trends and Innovative Therapies in Epilepsy Management.Brain sciences · 2023Review
- Closed-loop enhancement and neural decoding of cognitive control in humans.Nature biomedical engineering · 2023Article
- Editorial: Neurological, psychological and endocrine markers of eating disorders and obesity.Frontiers in nutrition · 2023Article
- Aberrant impulse control circuitry in obesity.Molecular psychiatry · 2022Article
- Neuroimaging and modulation in obesity and diabetes research: 10th anniversary meeting.International journal of obesity (2005) · 2022Review
- Proceedings of the Eighth Annual Deep Brain Stimulation Think Tank: Advances in Optogenetics, Ethical Issues Affecting DBS Research, Neuromodulatory Approaches for Depression, Adaptive Neurostimulation, and Emerging DBS Technologies.Frontiers in human neuroscience · 2021Article
- Accumbens connectivity during deep-brain stimulation differentiates loss of control from physiologic behavioral states.Brain stimulationArticle
Corrections and comments
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Authors and funding
22 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundLoss of control (LOC) is a pervasive feature of binge eating, which contributes significantly to the growing epidemic of obesity; approximately 80 million US adults are obese. Brain-responsive neurostimulation guided by the delta band was previously found to block binge-eating behavior in mice. Following novel preclinical work and a human case study demonstrating an association between the delta band and reward anticipation, the US Food and Drug Administration approved an Investigational Device Exemption for a first-in-human study.
objectiveTo assess feasibility, safety, and nonfutility of brain-responsive neurostimulation for LOC eating in treatment-refractory obesity.
methodsThis is a single-site, early feasibility study with a randomized, single-blinded, staggered-onset design. Six subjects will undergo bilateral brain-responsive neurostimulation of the nucleus accumbens for LOC eating using the RNS® System (NeuroPace Inc). Eligible participants must have treatment-refractory obesity with body mass index ≥ 45 kg/m2. Electrophysiological signals of LOC will be characterized using real-time recording capabilities coupled with synchronized video monitoring. Effects on other eating disorder pathology, mood, neuropsychological profile, metabolic syndrome, and nutrition will also be assessed. EXPECTED OUTCOMES: Safety/feasibility of brain-responsive neurostimulation of the nucleus accumbens will be examined. The primary success criterion is a decrease of ≥1 LOC eating episode/week based on a 28-d average in ≥50% of subjects after 6 mo of responsive neurostimulation. DISCUSSION: This study is the first to use brain-responsive neurostimulation for obesity; this approach represents a paradigm shift for intractable mental health 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.