Neural correlates of target enhancement
Bibliographic record
Abstract
When a task-relevant stimulus is presented for a brief duration or with low contrast, neural enhancement is needed to boost the weak responses to the target. Otherwise, the stimulus goes unnoticed, which is the default when the stimulus is task-irrelevant. Here, we used evoked-related potentials (ERPs) to investigate the neural mechanisms of target enhancement. The target consisted of a vernier, i.e., two vertical bars that are slightly offset in the horizontal direction. Observers discriminated the offset direction. First, we compared the ERPs elicited by the vernier when it was task-relevant vs. task-irrelevant. When the vernier was task-relevant, it elicited strong ERPs amplitudes at ~200ms after stimulus-onset with a bilateral negative occipital and positive fronto-central topography. This topography remained stable for around 140ms. When the vernier was task-irrelevant, similar ERPs were elicited but with much weaker amplitudes and for shorter topography durations. In a second experiment, we presented a mask after the target vernier, with varying inter-stimulus-intervals (ISIs). Performance on the target decreased linearly with the ISI, i.e., the shorter the ISI, the worse the performance. Interestingly, the ERPs amplitudes and topography durations decreased with the ISI. When the ISI was 0ms, performance was at chance level and ERPs amplitudes and topography durations were very similar to when the vernier was task-irrelevant. We propose that invisibility can come by either task irrelevance or masking. Under these two conditions, ERPs amplitudes and topographies are identical, suggesting similar brain processing.
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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 | 0.000 |
| 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) | 0.000 | 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".