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Record W2947515856 · doi:10.3389/fncir.2019.00040

Divisive Inhibition Prevails During Simultaneous Optogenetic Activation of All Interneuron Subtypes in Mouse Primary Visual Cortex

2019· article· en· W2947515856 on OpenAlexafffund
Tony G. J. Ingram, Jillian L. King, Nathan A. Crowder

Bibliographic record

VenueFrontiers in Neural Circuits · 2019
Typearticle
Languageen
FieldNeuroscience
TopicPhotoreceptor and optogenetics research
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsOptogeneticsInterneuronNeuroscienceParvalbuminDisinhibitionVisual cortexInhibitory postsynaptic potentialBiologyNeocortexExcitatory postsynaptic potentialVasoactive intestinal peptideNeuropeptideReceptor

Abstract

fetched live from OpenAlex

The mouse primary visual cortex (V1) has become an important brain area for exploring how neural circuits process information. Optogenetic tools have helped to outline the connectivity of a local V1 circuit comprising excitatory pyramidal neurons and several genetically-defined inhibitory interneuron subtypes that express parvalbumin, somatostatin, or vasoactive intestinal peptide. Optogenetic modulation of individual interneuron subtypes can alter the visual responsiveness of pyramidal neurons with distinct forms of inhibition and disinhibition. However, different interneuron subtypes have potentially opposing actions, and the potency of their effects relative to each other remains unclear. Therefore, in this study we simultaneously optogenetically activated all interneuron subtypes during visual processing to explore whether any single inhibitory effect would predominate. This aggregate interneuron activation consistently inhibited pyramidal neurons in a divisive manner, which was essentially identical to the pattern of inhibition produced by activating parvalbumin-expressing interneurons alone.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.924

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 head0.018
GPT teacher head0.274
Teacher spread0.256 · 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

Citations11
Published2019
Admission routes2
Has abstractyes

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