ArticleNature biotechnology2018
Mood variations decoded from multi-site intracranial human brain activity.
Article in Nature biotechnology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 109 papers.
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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.
Adjunct Cortical Stimulation With Deep Brain Stimulation (DBS) to Treat Obsessive Compulsive Disorder (OCD)
Model-based Electrical Brain Stimulation
Who cites it
109 citing papers in PubMed.
- Deep Brain Stimulation for Depression Informed by Intracranial Recordings.Biological psychiatry · 2022Trial
- Prioritized nonlinear modeling of shared dynamics across neural populations.Journal of neural engineering · 2026Article
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- Detrended fluctuation analysis of amygdala-hippocampal beta synchrony reveals network rigidity in depression associated with temporal lobe epilepsy.Journal of neural engineering · 2026Article
- Dietary habits and nutritional status of adolescent girls in environmentally vulnerable coastal areas of Bangladesh.Journal of health, population, and nutrition · 2026Article
- Increased Aperiodic Exponents Track Depression Symptom Severity.bioRxiv : the preprint server for biology · 2026Article
- Age differences in neural discriminability of rumination and worry.Communications biology · 2026Article
- Distinct neural temporal architectures encode rapid social expressions and sustained internal mood states.bioRxiv : the preprint server for biology · 2025Article
- Prioritized learning of cross-population neural dynamics.Journal of neural engineering · 2025Article
- Intracranial electrophysiological biomarkers of compulsivity in obsessive-compulsive disorder.Nature. Mental health · 2025Article
- Intracranial directed connectivity links subregions of the prefrontal cortex to major depression.Nature communications · 2025Article
- Naturalistic acute pain states decoded from neural and facial dynamics.Nature communications · 2025Article
- Challenges and opportunities of acquiring cortical recordings for chronic adaptive deep brain stimulation.Nature biomedical engineering · 2025Review
- Scalp EEG predicts intracranial brain activity in humans.bioRxiv : the preprint server for biology · 2025Article
- Intracranial substrates of meditation-induced neuromodulation in the amygdala and hippocampus.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- BaRISTA: Brain Scale Informed Spatiotemporal Representation of Human Intracranial Neural Activity.Advances in neural information processing systems · 2025Article
- Exploring the suitability of piecewise-linear dynamical system models for cognitive neural dynamics.Frontiers in neuroscience · 2025Article
- Functional brain connectivity changes associated with day-to-day fluctuations in affective states.Cognitive, affective & behavioral neuroscience · 2024Article
- Neural decoding and feature selection methods for closed-loop control of avoidance behavior.Journal of neural engineering · 2024Article
49 more citing papers are in PubMed but not listed here.
Corrections and comments
- Commented on byDecoding mood.2018
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The ability to decode mood state over time from neural activity could enable closed-loop systems to treat neuropsychiatric disorders. However, this decoding has not been demonstrated, partly owing to the difficulty of modeling distributed mood-relevant neural dynamics while dealing with the sparsity of mood state measurements. Here we develop a modeling framework to decode mood state variations from multi-site intracranial recordings in seven human subjects with epilepsy who self-reported their mood state intermittently over multiple days. We built dynamic neural encoding models of mood state and corresponding decoders for each individual and demonstrated that mood state variations over time can be decoded from neural activity. Across subjects, the decoders largely recruited neural signals from limbic regions, whose spectro-spatial features were tuned to mood variations. The dynamic models also provided an analytical tool to compute the timescales of the decoded mood state. These results provide an initial line of evidence indicating the feasibility of mood state decoding.
Indexed as
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30199076What OpenQuestion holds
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.