Electrophysiological correlates of suppressive lateral interactions
Bibliographic record
Abstract
The visibility of image elements can be reduced by other elements in their vicinity. This is usually explained by inhibitory lateral interactions among neurons in the primary visual cortex, although there is little evidence for the involvement of intracortical inhibition. Further, the mechanisms underlying these interactions remain unknown. We investigated the neural bases of suppressive lateral interactions by recording visual evoked potentials together with psychophysical measures for visual targets in the presence of flanking stimuli. High-density EEG’s were recorded in eight observers with normal or corrected-to-normal vision in response to a foveally viewed Gabor as a function of the spacing of horizontally adjacent Gabors. Inter-element spacing ranged from 1.5 to 6 cycles from the centre of the target to the centre of either of its adjacent flankers. The central target had the same or a different orientation (0 º, ±15º, ±30º, and ±60º) and spatial frequency as the flankers (0, ±.5, and ±1 octave). Each stimulus configuration was repeated 80 times and stimuli were interleaved. We analyzed the power density and spectral coherence over the time-frequency plane (in the central occipito-parietal region). Power density (p = 0.015) as well as short- (p = 0.005) and long-range (p = 0.005) spectral coherence decreases as inter-element spacing decreased to reach conditions under which the psychophysical test produced the greatest suppression in the apparent contrast of the central Gabor. A similar pattern of results was found when the spatial frequency and orientation of the flankers were systematically varied. These findings support the cortical origin of suppressive lateral interactions through short- and long-range functional connectivity. Further, synaptic inhibition likely causes a breakdown of synchronisation in the network response, consistent with the proposition that a function of surround suppression is to remove the statistical redundancies by increasing the sparseness or selectivity of sensory responses. Meeting abstract presented at VSS 2015
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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 | 0.002 |
| 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".