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Record W4403136437 · doi:10.1111/ejn.16558

Psilocybin reduces functional correlation and the encoding of spatial information by neurons in mouse retrosplenial cortex

2024· article· en· W4403136437 on OpenAlexafffund
Victorita E. Ivan, David P. Tomàs‐Cuesta, Ingrid M. Esteves, Artur Luczak, Majid H. Mohajerani, Bruce L. McNaughton, Aaron J. Gruber

Bibliographic record

VenueEuropean Journal of Neuroscience · 2024
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsMcGill UniversityDouglas Mental Health University InstituteUniversity of Lethbridge
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchAlliance de recherche numérique du CanadaAlberta Innovates
KeywordsRetrosplenial cortexPsilocybinNeurosciencePsychologyHallucinogenPerceptionCortex (anatomy)Psychiatry

Abstract

fetched live from OpenAlex

Abstract Psychedelic drugs have profound effects on perception, cognition and mood. How psychedelics affect neural signaling to produce these effects remains poorly understood. We investigated the effect of the classic psychedelic psilocybin on neural activity patterns and spatial encoding in the retrosplenial cortex of head‐fixed mice navigating on a treadmill. The place specificity of neurons to distinct locations along the belt was reduced by psilocybin. Moreover, the stability of place‐related activity across trials decreased. Psilocybin also reduced the functional correlation among simultaneously recorded neurons. The 5‐HT 2A R (serotonin 2A receptor) antagonist ketanserin blocked these effects. These data are consistent with proposals that psychedelics increase the entropy of neural signaling and provide a potential neural mechanism contributing to disorientation frequently reported by humans after taking psychedelics.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.026
GPT teacher head0.276
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2024
Admission routes2
Has abstractyes

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