MétaCan
Menu
Back to cohort
Record W2790477621 · doi:10.1111/ejn.13830

Adaptation to stimulus orientation in mouse primary visual cortex

2018· article· en· W2790477621 on OpenAlexafffund
Jillian L. King, Nathan A. Crowder

Bibliographic record

VenueEuropean Journal of Neuroscience · 2018
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVisual cortexStimulus (psychology)NeuroscienceMacaquePerceptionPsychologyVisual perceptionGratingCommunicationCognitive psychologyPhysicsOptics

Abstract

fetched live from OpenAlex

Information processing in the visual system is shaped by recent stimulus history, such that prolonged viewing of an adapting stimulus can alter the perception of subsequently presented test stimuli. In the tilt-after-effect, the perceived orientation of a grating is often repelled away from the orientation of a previously viewed adapting grating. A possible neural correlate for the tilt-after-effect has been described in cat and macaque primary visual cortex (V1), where adaptation produces repulsive shifts in the orientation tuning curves of V1 neurons. We investigated adaptation to stimulus orientation in mouse V1 to determine whether known species differences in orientation processing, notably V1 functional architecture and proportion of tightly tuned cells, are important for these repulsive shifts. Unlike the consistent repulsion reported in other species, we found that repulsion was only about twice as common as attraction in our mouse data. Furthermore, adapted responses were attenuated across all orientations. A simple model that captured key physiological findings reported in cats and mice indicated that the greater proportion of broadly tuned neurons in mice may explain the observed species differences in adaptation.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.074
GPT teacher head0.340
Teacher spread0.266 · 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 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

Citations16
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueEuropean Journal of NeuroscienceSame topicVisual perception and processing mechanismsFrench-language works237,207