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Long-Term Depression and Depotentiation in the Sensorimotor Cortex of the Freely Moving Rat

2000· article· en· W2131371406 on OpenAlexaff
David J. Froc, C. Andrew Chapman, Christopher Trepel, Ronald J. Racine

Bibliographic record

VenueJournal of Neuroscience · 2000
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsStimulationNeocortexNeuroscienceLong-term potentiationPsychologyLong-term depressionCortex (anatomy)ChemistryNMDA receptorReceptorAMPA receptor

Abstract

fetched live from OpenAlex

Activity-dependent reductions in synaptic efficacy are central components of recent models of cortical learning and memory. Here, we have examined long-term synaptic depression (LTD) and the reversal of long-term potentiation (depotentiation) of field potentials evoked in sensorimotor cortex by stimulation of the white matter in the adult, freely moving rat. Prolonged, low-frequency stimulation (1 Hz for 15 min) was used to induce either depotentiation or LTD. LTD was expressed as a reduction in the amplitude of both monosynaptic and polysynaptic field potential components. Both LTD and depotentiation were reliably induced by stimulation of the ipsilateral white matter. Stimulation of the contralateral neocortex induced only a depotentiation effect, which decayed more rapidly than that induced by ipsilateral stimulation (hours vs days). Although ipsilateral LTD was effectively induced by a single session of low-frequency stimulation, multiple sessions of stimulation, either massed or spaced, induced LTD effects that were larger in magnitude and longer lasting. Previously, we showed that the induction of long-term potentiation in the neocortex of chronic preparations required multiple, spaced stimulation sessions to reach asymptotic levels. Here, we report that LTD also required multiple stimulation sessions to reach asymptotic levels, but massed and spaced patterns of low-frequency stimulation were equally effective.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score0.264

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.042
GPT teacher head0.332
Teacher spread0.289 · 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

Citations127
Published2000
Admission routes1
Has abstractyes

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