Model-based Mind Wandering in Older Adults: Age Differences in the Behavioral and Electrophysiological Correlates of Subjective and Objective Measures of Mind Wandering
Bibliographic record
Abstract
Mind wandering is typically characterized as a failure of attentional control, yet despite age-related executive function deficits, older adults typically report less mind wandering than younger adults during cognitive tasks and in daily life. Self-reported mind wandering episodes usually result in similar behavioral detriments in younger and older adults (e.g., greater RT variability, more task errors). However, the relatively few studies investigating the neural correlates of mind wandering and aging have revealed mixed findings, possibly because they typically rely on infrequent thought probes and, therefore, few trials for neural analyses. In the current study, we propose a method to recover more task data by categorizing trials from a commonly used sustained attention to response task according to RT variability. Behavioral data (n = 49 younger; n = 40 older) revealed that compared with younger adults, older adults reported fewer mind wandering episodes, but showed similar behavioral impacts thereof. Furthermore, in both age groups, subjective reports of mind wandering predicted the more objective sorting of trials into "on-" and "off-task" according to RT variability. Using these objectively sorted trials, we investigated two commonly reported EEG measures of mind wandering (diminished P1 and P3 amplitude) in 26 younger and 24 older adults. Although the P1 did not differ between on- and off-task trials for either group, the P3 was diminished for off-task trials in both age groups (albeit significantly less in older adults) suggesting preserved perceptual but reduced higher-order processing during off-task periods in both groups.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".