Attention and Sensory Gain Control: A Peripheral Visual Process?
Bibliographic record
Abstract
Attention-related sensory gain control in human extrastriate cortex is believed to improve the acuity of visual perception. Yet given wide variance in the spatial resolution of vision across the retina, it remains unclear whether sensory gain operates homogenously between foveal and nonfoveal retinotopic locations. To address this issue, we used event-related potentials (ERPs) in a variant of the canonical spatial attention task. Participants were cued to expect targets at either fixation (foveal targets) or at a location several degrees above fixation (parafoveal targets). At both target locations, manual reaction times were shorter for cued relative to uncued targets, indicating that attention was consistently oriented to the cued location. Nevertheless, attention-related increases in sensory-evoked cortical activity were only observed at the parafoveal target location, as measured by the amplitude of the lateral occipital P1 ERP component. A second experiment replicated this data pattern using targets with lower stimulus contrast, indicating that the absence of a P1 effect for foveal targets could not be attributed to a saturated P1 response under higher-contrast stimulus conditions. When considered in light of retinogeniculate projections to cortex showing systematic changes in their physiological organization beginning within a degree of visual angle of the fovea, our findings support the proposal that the strategic functions of visual attention may vary with the retinotopic location involved.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".