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Record W2797718870 · doi:10.3389/fnsyn.2018.00005

Memory Synapses Are Defined by Distinct Molecular Complexes: A Proposal

2018· review· en· W2797718870 on OpenAlexafffund
Wayne S. Sossin

Bibliographic record

VenueFrontiers in Synaptic Neuroscience · 2018
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health ResearchMcGill University
KeywordsNeuroscienceSynapseAplysiaNeuronal memory allocationEngramMemristorBiologySynaptic plasticityCognitive sciencePsychologyReceptorSynaptic fatiguePhysicsExcitatory postsynaptic potentialInhibitory postsynaptic potential

Abstract

fetched live from OpenAlex

Synapses are diverse in form and function. While there are strong evidential and theoretical reasons for believing that memories are stored at synapses, the concept of a specialized “memory synapse” is rarely discussed. Here, we review the evidence that memories are stored at the synapse and consider the opposing possibilities. We argue that if memories are stored in an active fashion at synapses, then these memory synapses must have distinct molecular complexes that distinguish them from other synapses. In particular, examples from Aplysia sensory-motor neuron synapses and synapses on defined engram neurons in rodent models are discussed. Specific hypotheses for molecular complexes that define memory synapses are presented, including persistently active kinases, transmitter receptor complexes and trans-synaptic adhesion proteins.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.004
Scholarly communication0.0020.007
Open science0.0020.002
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.002

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 head0.062
GPT teacher head0.353
Teacher spread0.291 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations32
Published2018
Admission routes2
Has abstractyes

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