Comparative analysis of orientation maps in areas 17 and 18 of the cat primary visual cortex following adaptation
Bibliographic record
Abstract
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 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".