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Record W1896960981 · doi:10.1152/jn.00758.2014

Offline reactivation of experience-dependent neuronal firing patterns in the rat ventral tegmental area

2015· article· en· W1896960981 on OpenAlexafffund
José L. Valdés, Bruce L. McNaughton, Jean‐Marc Fellous

Bibliographic record

VenueJournal of Neurophysiology · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversity of Lethbridge
FundersOffice of Naval Research GlobalOffice of Naval ResearchMultidisciplinary University Research InitiativeAlberta InnovatesU.S. Department of Veterans AffairsNational Science Foundation
KeywordsNeuroscienceVentral tegmental areaMemory consolidationStimulus (psychology)PsychologyDopaminergicHippocampusDopamineCognitive psychology

Abstract

fetched live from OpenAlex

In a rest period immediately after a task, neurons in the hippocampus, neocortex, and striatum exhibit spatiotemporal correlation patterns resembling those observed during the task. This reactivation has been proposed as a neurophysiological substrate for memory consolidation. We provide new evidence that rodent ventral tegmental area (VTA) neurons are selective for different types of food stimuli and that stimulus-sensitive neurons strongly reactivate during the rest period following a task that involved those stimuli. Reactivation occurred primarily during slow wave sleep and during quiet awakeness. In these experiments, VTA reactivation patterns were uncompressed and occurred at the firing rate level, rather than on a spike-to-spike basis. Mildly aversive stimuli were reactivated more often than positive ones. The VTA is a pivotal structure involved in the perception and prediction of reward and stimulus salience and is a key neuromodulatory system involved in synaptic plasticity. These results suggest new ways in which dopaminergic signals could contribute to the biophysical mechanisms of selective, system-wide, memory consolidation, and reconsolidation during sleep.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.037
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.131
GPT teacher head0.368
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 teacher head, 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

Citations59
Published2015
Admission routes2
Has abstractyes

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