Differences between Patterns of Brain Activity Associated with Semantics and Those Linked with Phonological Processing Diminish with Age
Bibliographic record
Abstract
It is widely believed that language function tends to show little age-related performance decline. Indeed, some older individuals seem to use compensatory mechanisms to maintain a high level of performance when submitted to lexical tasks. However, how these mechanisms affect cortical and subcortical activity during semantic and phonological processing has not been extensively explored. The purpose of this study was to look at the effect of healthy aging on cortico-subcortical routes related to semantic and phonological processing using a lexical analogue of the Wisconsin Cart-Sorting Task. Our results indicate that while young adults tend to show increased activity in the ventrolateral prefrontal cortex, the dorsolateral prefrontal cortex, the fusiform gyrus, the ventral temporal lobe and the caudate nucleus during semantic decisions and in the posterior Broca's area (area 44), the temporal lobe (area 37), the temporoparietal junction (area 40) and the motor cortical regions during phonological decisions, older individuals showed increased activity in the dorsolateral prefrontal cortex and motor cortical regions during both semantic and phonological decisions. Furthermore, when semantic and phonological decisions were contrasted with each other, younger individuals showed significant brain activity differences in several regions while older individuals did not. Therefore, in older individuals, the semantic and phonological routes seem to merge into a single pathway. These findings represent most probably neural reserve/compensation mechanisms, characterized by a decrease in specificity, on which the elderly rely to maintain an adequate level of performance.
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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 | 0.001 | 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) | 0.002 | 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".