MétaCan
Menu
Back to cohort
Record W1970127868 · doi:10.1111/ejn.12616

Comparative analysis of orientation maps in areas 17 and 18 of the cat primary visual cortex following adaptation

2014· article· en· W1970127868 on OpenAlexaff
Sarah Cattan, Lyes Bachatene, Vishal Bharmauria, Jeyadarshan Jeyabalaratnam, Chantal Milleret, Stéphane Molotchnikoff

Bibliographic record

VenueEuropean Journal of Neuroscience · 2014
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversité de MontréalCégep Marie-Victorin
Fundersnot available
KeywordsVisual cortexOrientation (vector space)NeuroscienceAdaptation (eye)CATSPsychologyMedicineMathematicsInternal medicine

Abstract

fetched live from OpenAlex

Object orientations in the visual field are columned into specific orientation domains in the primary visual cortex [area 17 (A17) and area 18 (A18)] of cats. At the single-cell level, adapting A17 neurons to a non-preferred orientation (adaptor) shifts their preferred orientation either towards the adaptor (attractive shift) or away from it (repulsive shift). As A17 and A18 are reciprocally connected, we sought to determine how changes in preferred orientations in A18 neurons are correlated with changes recorded in A17 anesthetised cats. To this end, we simultaneously traced populations of neurons in A17 and A18, using intrinsic optical imaging, before and after long (12 min) and short (3 min) adaptations. The comparison of A17 and A18 maps pre-adaptation and post-adaptation showed that variance in shift amplitudes is greater in A18 than A17 for short adaptations. Our results indicate a rapid reconfiguration of functional maps that may spread to many cortical areas.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.953
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.077
GPT teacher head0.338
Teacher spread0.260 · 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

Citations30
Published2014
Admission routes1
Has abstractyes

Explore more

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