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Record W2943146256 · doi:10.1186/s13041-019-0451-6

Differential sensitivity of three forms of hippocampal synaptic potentiation to depotentiation

2019· article· en· W2943146256 on OpenAlexafffund
Pojeong Park, Thomas M. Sanderson, Zuner A. Bortolotto, John Georgiou, Min Zhuo, Bong-Kiun Kaang, Graham L. Collingridge

Bibliographic record

VenueMolecular Brain · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsCanada Research ChairsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
FundersEuropean Research CouncilMedical Research CouncilCanadian Institutes of Health ResearchHealth CanadaNational Research FoundationFondation Brain Canada
KeywordsLong-term potentiationSchaffer collateralCTBSNeuroscienceHippocampal formationSynaptic plasticityChemistryStimulationLTP inductionMetaplasticityPsychologyReceptorBiochemistry

Abstract

fetched live from OpenAlex

Theta-burst stimulation (TBS) induces short-term potentiation (STP) plus two types of transcriptionally-independent forms of long-term potentiation (LTP), termed LTP1 and LTP2. We have compared the susceptibility of these three types of synaptic plasticity to depotentiation, induced by low frequency stimulation (LFS; 2 Hz for 10 min) at the Schaffer collateral-commissural pathway in area CA1 of adult rat hippocampal slices. In interleaved experiments, STP and LTP were induced by three episodes of either compressed or spaced TBS (cTBS or sTBS). LFS had a more pronounced effect on the LTP induced by the cTBS. One traditional interpretation of these results is a difference in the time-dependent immunity against depotentiation. We suggest an alternative explanation: LFS rapidly reverses STP to reveal a slowly developing LTP. The cTBS protocol induces LTP1 that is moderately sensitive to depotentiation. The sTBS induces an additional component of LTP (LTP2) that is resistant to depotentiation.

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 score0.024
Threshold uncertainty score0.454

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 head0.020
GPT teacher head0.288
Teacher spread0.268 · 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

Citations14
Published2019
Admission routes2
Has abstractyes

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