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Record W2560246131 · doi:10.1155/2016/1401935

Potential Role of Synaptic Activity to Inhibit LTD Induction in Rat Visual Cortex

2016· article· en· W2560246131 on OpenAlexafffund
Matthew Stewart, Hans C. Dringenberg

Bibliographic record

VenueNeural Plasticity · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNeuroscienceVisual cortexPostsynaptic potentialStimulationChemistryLong-term potentiationSynaptic plasticityBrainstemReticular formationPsychologyReceptor

Abstract

fetched live from OpenAlex

Long-term depression (LTD), a widely studied form of activity-dependent synaptic plasticity, is typically induced by prolonged low-frequency stimulation (LFS). Interestingly, LFS is highly effective in eliciting LTD in vitro , but much less so under in vivo conditions; the reasons for the resistance of the intact brain to express LTD are not well understood. We examined if levels of background electrocorticographic (ECoG) activity influence LTD induction in the thalamocortical visual system of rats under very deep urethane anesthesia, inducing a brain state of reduced spontaneous cortical activity. Under these conditions, LFS applied to the lateral geniculate nucleus resulted in LTD of field postsynaptic potentials (fPSPs) recorded in the primary visual cortex (V1). Pairing LFS with stimulation of the brainstem (pedunculopontine) reticular formation resulted in the appearance of faster, more complex activity in V1 and prevented LTD induction, an effect that did not require muscarinic or nicotinic receptors. Reticular stimulation alone (without LFS) had no effect on cortical fPSPs. These results show that excitation of the brainstem activating system blocks the induction of LTD in V1. Thus, higher levels of neural activity may inhibit depression at cortical synapses, a hypothesis that could explain discrepancies regarding LTD induction in previous in vivo and in vitro work.

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 score0.027
Threshold uncertainty score0.502

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.323
Teacher spread0.294 · 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

Citations5
Published2016
Admission routes2
Has abstractyes

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