Don't look here! The relationship between eye movement artifacts, covert attention, and visual working memory in older adults
Bibliographic record
Abstract
The Inhibition Theory of aging suggests that age-related decline in cognition results from a deficit in top-down inhibitory control, a process critical to efficient and effective use of capacity-limited resources, such as visual working memory (VWM). Evidence supporting this theory can be found in studies of overt attentional control (anti-saccades) and VWM. Covertly shifting attention - inhibiting eye movements while moving attention – is a requirement in many EEG studies, due to the artifacts/noise associated with eye-movements. Thus, this skill becomes an implicit data selection criterion, resulting in the exclusion of participants that are simply unable to control their eye movements. This may pose a significant problem when studying older adults. We investigated the relationship between VWM capacity (k) in older and younger adults and the ability to suppress eye-movements during a Localized Attentional Interference (LAI) task, while EEG was recorded. Eye movements were tracked using electrodes placed above, below and at the outer canthi of each eye. Participants were presented with a search array, containing a single coloured target (T) and distractor (L) among gray place-holders, positioned on an invisible circle, centered around a fixation cross. Despite saccade inhibition training, a number of older adults were unable to inhibit their eye movements. Interestingly, their mean k-estimate was significantly lower than the k-estimate of those elderly participates who could inhibit eye movements. Furthermore, a significant negative correlation was found between percent of trials contaminated by saccades and VWM capacity, but only for the older adults. These results suggest that excluding older adult data sets due to excessive eye movement artifacts may result in systematically rejecting lower performing older adults, misconstruing age-related changes in electrophysiology.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".