Assessment of age-related changes in inhibition and binding using eye movement monitoring.
Bibliographic record
Abstract
Age-related memory deficits may result from attending to too much information (inhibition deficit) and/or storing too little information (binding deficit). The present study evaluated the inhibition and binding accounts by exploiting a situation in which deficits of inhibition should benefit relational memory binding. Older adults directed more viewing toward abrupt onsets in scenes compared with younger adults under instructions to ignore any such onsets, providing evidence for age-related inhibitory deficits, which were ameliorated with additional practice. Subsequently, objects that served as abrupt onsets underwent changes in their spatial relations. Despite successful inhibition of the onsets, eye movements of younger adults were attracted to manipulated objects. In contrast, the eye movements of older adults, who directed more viewing to the late onsets compared with younger adults, were not attracted toward manipulated regions. Similar differences between younger and older adults in viewing of manipulated regions were observed under free viewing conditions. These findings provide evidence for concurrent inhibition and binding deficits in older adults and demonstrate that age-related declines in inhibitory processing do not lead to enhanced relational memory for extraneous information.
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 | 0.001 |
| 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 | 0.001 |
| 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".