MétaCan
Menu
Back to cohort
Record W4404121443 · doi:10.3389/fncel.2024.1482844

Synaptopodin: a key regulator of Hebbian plasticity

2024· review· en· W4404121443 on OpenAlexafffund
Pei You Wu, Yanis Inglebert, R. Anne McKinney

Bibliographic record

VenueFrontiers in Cellular Neuroscience · 2024
Typereview
Languageen
FieldNeuroscience
TopicNeuroscience and Neuropharmacology Research
Canadian institutionsUniversité de MontréalMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsSynaptopodinRegulatorNeuroscienceHebbian theoryDendritic spineSynaptic plasticityNeuroplasticityBiologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Synaptopodin, an actin-associated protein found in a subset of dendritic spines in telencephalic neurons, has been described to influence both functional and morphological plasticity under various plasticity paradigms. Synaptopodin is necessary and sufficient for the formation of the spine apparatus, stacks of smooth endoplasmic reticulum cisternae. The spine apparatus is a calcium store that locally regulates calcium dynamics in response to different patterns of activity and is also thought to be a site for local protein synthesis. Synaptopodin is present in ~30% of telencephalic large dendritic spines in vivo and in vitro highlighting the heterogeneous microanatomy and molecular architecture of dendritic spines, an important but not well understood aspect of neuroplasticity. In recent years, it has become increasingly clear that synaptopodin is a formidable regulator of multiple mechanisms essential for learning and memory. In fact, synaptopodin appears to be the decisive factor that determines whether plasticity can occur, acting as a key regulator for synaptic changes. In this review, we summarize the current understanding of synaptopodin’s role in various forms of Hebbian synaptic plasticity.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.913
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.006
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0040.001
Research integrity0.0000.002
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 head0.094
GPT teacher head0.366
Teacher spread0.271 · 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.

Study designNot applicable
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

Citations4
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueFrontiers in Cellular NeuroscienceSame topicNeuroscience and Neuropharmacology ResearchFrench-language works237,207