Mind Wandering and the Adaptive Control of Attentional Resources
Bibliographic record
Abstract
Mind wandering is a natural, transient state wherein our neurocognitive systems become temporarily decoupled from the external sensory environment as our thoughts drift away from the current task at hand. Yet despite the ubiquity of mind wandering in everyday human life, we rarely seem impaired in our ability to adaptively respond to the external environment when mind wandering. This suggests that despite widespread neurocognitive decoupling during mind wandering states, we may nevertheless retain some capacity to attentionally monitor external events. But what specific capacities? In Experiment 1, using traditional performance measures, we found that both volitional and automatic forms of visual-spatial attentional orienting were significantly attenuated when mind wandering. In Experiment 2, however, ERPs revealed that, during mind wandering states, there was a relative preservation of sensitivity to deviant or unexpected sensory events, as measured via the auditory N1 component. Taken together, our findings suggest that, although some selective attentional processes may be subject to down-regulation during mind wandering, we may adaptively compensate for these neurocognitively decoupled states by maintaining automatic deviance-detection functions.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".