Effects of visual adaptation on orientation selectivity in cat secondary visual cortex
Bibliographic record
Abstract
Neuron orientation selectivity, otherwise known as the ability to respond optimally to a preferred orientation, has been extensively described in both primary and secondary visual cortices. This orientation selectivity, conserved through all cortical layers of a given column, is the primary basis for cortical organization and functional network emergence. While this selectivity is programmed and acquired since critical period, it has always been believed that in a mature brain, neurons' inherent functional features could not be changed. However, a plurality of studies has investigated the mature brain plasticity in V1, by changing the cells' orientation selectivity with visual adaptation. Using electrophysiological data in both V1 and V2 areas, this study aims to investigate the effects of adaptation on simultaneously recorded cells in both areas. Visual adaptation had an enhanced effect on V2 units, as they exhibited greater tuning curve shifts and a more pronounced decrease of their OSI. Not only did adaptation have a different effect on V2 neurons, it also elicited a different response depending on the neuron's cortical depth. Indeed, in V2, cells in layers II-III were more affected by visual adaptation, while infragranular layer V units exhibited little to no effect at all.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".