Electrophysiological Evidence for Biased Competition in V1 for Fear Expressions
Bibliographic record
Abstract
When multiple stimuli are concurrently displayed in the visual field, they must compete for neural representation at the processing expense of their contemporaries. This biased competition is thought to begin as early as primary visual cortex, and can be driven by salient low-level stimulus features. Stimuli important for an organism's survival, such as facial expressions signaling environmental threat, might be similarly prioritized at this early stage of visual processing. In the present study, we used ERP recordings from striate cortex to examine whether fear expressions can bias the competition for neural representation at the earliest stage of retinotopic visuo-cortical processing when in direct competition with concurrently presented visual information of neutral valence. We found that within 50 msec after stimulus onset, information processing in primary visual cortex is biased in favor of perceptual representations of fear at the expense of competing visual information (Experiment 1). Additional experiments confirmed that the facial display's emotional content rather than low-level features is responsible for this prioritization in V1 (Experiment 2), and that this competition is reliant on a face's upright canonical orientation (Experiment 3). These results suggest that complex stimuli important for an organism's survival can indeed be prioritized at the earliest stage of cortical processing at the expense of competing information, with competition possibly beginning before encoding in V1.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.006 |
| 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) | 0.000 | 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 teacher head, 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".