Investigating the neural signature of multi-modal inhibition of return
Bibliographic record
Abstract
Inhibition of Return (IOR) is a behavioral phenomenon wherein one is slower to respond to targets that are presented at a previously cued location. Early work looking at the event-related potential (ERP) components of IOR using electroencephalography (EEG) suggested that P1 reductions might be an electrophysiological marker of IOR. However, the observation of P1 reductions with and without IOR, and vice versa, made the role of P1 in IOR unclear. We hypothesized that P1 component reductions, and, more generally, early ERP component modulations, are the result of repetitive stimulation along an input (sensory) pathway, not IOR. To test this hypothesis, the neural signature of IOR was investigated in a multi-modal cueing paradigm using all possible pairings of touch and vision. IOR (slower responses to targets in a previously cued location) was obtained in all 4 conditions. In the visual modality, P1 cueing effects were not observed. However, in the tactile modality, an early component (defined as the N80/P100 complex) showed a robust reduction on the cued side, but only following tactile cues. Overall, these results support the hypothesis that repetitive sensory stimulation may be driving the early ERP component modulations originally thought to be indicative of IOR.Acknowledgments: NSERC
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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 | 0.001 |
| 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".