Neocortical Rebound Depolarization Enhances Visual Perception
Bibliographic record
Abstract
Animals are constantly exposed to the time-varying visual world. Because visual perception is modulated by immediately prior visual experience, visual cortical neurons may register recent visual history into a specific form of offline activity and link it to later visual input. To examine how preceding visual inputs interact with upcoming information at the single neuron level, we designed a simple stimulation protocol in which a brief, orientated flashing stimulus was subsequently coupled to visual stimuli with identical or different features. Using in vivo whole-cell patch-clamp recording and functional two-photon calcium imaging from the primary visual cortex (V1) of awake mice, we discovered that a flash of sinusoidal grating per se induces an early, transient activation as well as a long-delayed reactivation in V1 neurons. This late response, which started hundreds of milliseconds after the flash and persisted for approximately 2 s, was also observed in human V1 electroencephalogram. When another drifting grating stimulus arrived during the late response, the V1 neurons exhibited a sublinear, but apparently increased response, especially to the same grating orientation. In behavioral tests of mice and humans, the flashing stimulation enhanced the detection power of the identically orientated visual stimulation only when the second stimulation was presented during the time window of the late response. Therefore, V1 late responses likely provide a neural basis for admixing temporally separated stimuli and extracting identical features in time-varying visual environments.
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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".