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Record W4367186604 · doi:10.1101/2023.04.27.538595

Ventral hippocampal CCK interneurons gate context-reward memory

2023· preprint· en· W4367186604 on OpenAlexaff
Robin Nguyen, Sanghavy Sivakumaran, Evelyn K. Lambe, Jun Chul Kim

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2023
Typepreprint
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOptogeneticsNeuroscienceConditioned place preferenceHippocampal formationContext (archaeology)Nucleus accumbensHippocampusInhibitory postsynaptic potentialGABAergicExcitatory postsynaptic potentialBiologyDopamine

Abstract

fetched live from OpenAlex

SUMMARY Associating contexts with rewards depends on hippocampal circuits, with local inhibitory interneurons positioned to play an important role in shaping activity. Here, we hypothesize that the encoding of context-reward memory requires a ventral hippocampus (vHPC) to nucleus accumbens (NAc) circuit that is gated by CCK interneurons. In a sucrose conditioned place preference (CPP) task, optogenetically inhibiting vHPC-NAc terminals impaired the acquisition of place preference. Transsynaptic rabies tracing revealed vHPC-NAc neurons were monosynaptically innervated by CCK interneurons. Using intersectional genetic targeting of CCK interneurons, ex vivo optogenetic activation of CCK interneurons increased GABAergic transmission onto vHPC-NAc neurons, while in vivo optogenetic inhibition of CCK interneurons increased cFos in these neurons. Notably, CCK interneuron inhibition during sucrose CPP learning increased time spent in the sucrose-associated location, suggesting enhanced place-reward memory. Our findings reveal a previously unknown hippocampal microcircuit crucial for modulating the strength of contextual reward learning.

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 score0.004

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 integrity0.0000.001
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 head0.065
GPT teacher head0.303
Teacher spread0.237 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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