Mind wandering preferentially attenuates sensory processing in the left visual field
Bibliographic record
Abstract
An emerging theory in visual attention is that it operates in parallel at two distinct timescales – a shorter one associated with moment-to-moment orienting of selective visual spatial attention, and a longer one (>10s) associated with more global aspects of attention-to-task. Our question is whether this slower fluctuation in task-related attention biases the same mechanism of early attentional selection as selective attention. Given that past studies have consistently revealed visual field asymmetries in selective visual attention, the objective of the present study was to determine whether sensory processing in the two visual fields is differentially modulated by whether or not one is paying attention to the current task. Participants performed a simple target detection task at fixation while event-related potentials (ERPs) to task-irrelevant visual probes presented in the left and right visual fields were recorded. At random intervals, participants were asked to report whether they were “on-task” or “mind wandering”. Our results demonstrated that sensory attenuation during periods of “mind wandering” relative to “on-task”, as measured by the visual P1 ERP component, was only observed in the left visual field. Alternatively, the magnitude of sensory responses in the right visual field was insensitive to the two different attentional states. Taken together, our results point to a visual field difference in task-related attention, one that mirrors asymmetry found in selective visual attention.
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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) | 0.002 | 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".