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Record W4214759458 · doi:10.1016/j.celrep.2022.110410

Gain control by sparse, ultra-slow glycinergic synapses

2022· article· en· W4214759458 on OpenAlexafffund
Varsha Jain, Laura Hanson, Santhosh Sethuramanujam, Tracy Michaels, Jerram Gawley, Ronald G. Gregg, Ian Scott Pyle, Chi Zhang, Robert G. Smith, David M. Berson, Maureen A. McCall, Gautam B. Awatramani

Bibliographic record

VenueCell Reports · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsUniversity of Victoria
FundersNational Eye InstituteCanadian Institutes of Health ResearchNational Institutes of HealthPeking University
KeywordsGlycine receptorInhibitory postsynaptic potentialNeuroscienceGABAergicRetinaAmacrine cellBiologyRetinalGlycineStimulus (psychology)PsychologyBiochemistry

Abstract

fetched live from OpenAlex

In the retina, ON starburst amacrine cells (SACs) play a crucial role in the direction-selective circuit, but the sources of inhibition that shape their response properties remain unclear. Previous studies demonstrate that ∼95% of their inhibitory synapses are GABAergic, yet we find that the light-evoked inhibitory currents measured in SACs are predominantly glycinergic. Glycinergic inhibition is extremely slow, relying on non-canonical glycine receptors containing α4 subunits, and is driven by both the ON and OFF retinal pathways. These attributes enable glycine inputs to summate and effectively control the output gain of SACs, expanding the range over which they compute direction. Serial electron microscopic reconstructions reveal three specific types of ON and OFF narrow-field amacrine cells as the presumptive sources of glycinergic inhibition. Together, these results establish an unexpected role for specific glycinergic amacrine cells in the retinal computation of stimulus direction by SACs.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.501
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.004
GPT teacher head0.195
Teacher spread0.191 · 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 designNot applicable
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

Citations18
Published2022
Admission routes2
Has abstractyes

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