Failing to Ignore: Paradoxical Neural Effects of Perceptual Load on Early Attentional Selection in Normal Aging
Bibliographic record
Abstract
We examined visual selective attention under perceptual load--simultaneous presentation of task-relevant and -irrelevant information--in healthy young and older adult human participants to determine whether age differences are observable at early stages of selection in the visual cortices. Participants viewed 50/50 superimposed face/place images and judged whether the faces were male or female, rendering places perceptible but task-irrelevant. Each stimulus was repeated, allowing us to index dynamic stimulus-driven competition from places. Consistent with intact early selection in young adults, we observed no adaptation to unattended places in parahippocampal place area (PPA) and significant adaptation to attended faces in fusiform face area (FFA). Older adults, however, exhibited both PPA adaptation to places and weak FFA adaptation to faces. We also probed participants' associative recognition for face-place pairs post-task. Older adults with better place recognition memory scores were found to exhibit both the largest magnitudes of PPA adaptation and the smallest magnitudes of FFA adaptation on the attention task. In a control study, we removed the competing perceptual information to decrease perceptual load. These data revealed that the initial age-related impairments in selective attention were not due to a general decline in visual cortical selectivity; both young and older adults exhibited robust FFA adaptation and neither group exhibited PPA adaptation to repeated faces. Accordingly, distracting information does not merely interfere with attended input in older adults, but is co-encoded along with the contents of attended input, to the extent that this information can subsequently be recovered from recognition memory.
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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".