ArticleNature neuroscience2025
Nonlinear recurrent inhibition through facilitating serotonin release in the raphe.
Article in Nature neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The trial behind it
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Who cites it
2 citing papers in PubMed.
- Optical insights into spatial precision and release heterogeneity of neuromodulatory transmission.iScience · 2026Article
- Ventrolateral orbital cortex as a functional hub in chronic pain and comorbid depression.Frontiers in neuroscience · 2026Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Serotonin (5-HT) neurons in the dorsal raphe nucleus (DRN) receive a constellation of long-range inputs, yet guiding principles of local circuit organization and underlying computations in this nucleus are largely unknown. Using inputs from the lateral habenula to interrogate the processing features of the mouse DRN, we uncovered 5-HT1A receptor-mediated recurrent connections between 5-HT neurons, refuting classical theories of autoinhibition. Cellular electrophysiology and imaging of a genetically encoded 5-HT sensor revealed that these recurrent inhibitory connections spanned the raphe, were slow, stochastic, strongly facilitating and gated spike output. These features collectively conveyed highly nonlinear dynamics to this network, generating excitation-driven inhibition and winner-take-all computations. In vivo optogenetic activation of lateral habenula inputs to DRN, at frequencies where these computations are predicted to ignite, transiently disrupted expression of a reward-conditioned response in an auditory conditioning task. Together, these data identify a core computation supported by an unsuspected slow serotonergic recurrent inhibitory network.
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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.