Neural capacity limits on the responses to memory interference during working memory in young and old adults
Bibliographic record
Abstract
Advancing age affects the recruitment of task related neural resources thereby changing the efficiency, capacity and use of compensatory processes. With advancing age, brain activity may therefore increase within a region or be reorganized to utilize different brain regions. The different brain regions may be exclusive to old adults or accessible to young and old alike, but non-optimal. Interference during verbal working memory information retention recruits parahippocampal brain regions in young adults similar to brain activity recruited by old adults in the absence of external interference. The current work tests the hypothesis that old adults recruit neural resources to combat increases in age-related intrinsic noise that young adults recruit during high levels of interference during information retention. This experiment administered a verbal delayed item recognition task with low and high levels of an interfering addition task during information maintenance. Despite strong age-related behavioral effects, brain imaging results demonstrated no significant interaction effects between age group and the interference or memory tasks. Significant effects were only found for the interaction between interference level and memory load within the inferior frontal cortex, supplementary motor cortex and posterior supramarginal regions. Results demonstrate that neural resources were shared when facing increasing memory load and interference. The combined cognitive demands resulted in brain activity reaching a neural capacity limit which was similar for both age groups and which brain activation did not increase above. Despite significant behavioral differences the neural capacity limited the detection of age group differences in brain activity.
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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) | 0.001 | 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".