The adaptive aging brain: evidence from the preservation of communication abilities with age
Bibliographic record
Abstract
Neurofunctional reorganization with age is suspected to occur for many cognitive components including communication abilities. Several functional neuroimaging studies of elderly individuals have reported the occurrence of an interhemispheric neurofunctional reorganization characterized by more bilateral activation patterns. Other studies have indicated that the preservation of some other cognitive abilities is associated with some intrahemispheric reorganization following either a posterior-anterior or an anterior-posterior shift in aging. Interestingly, other studies have shown that age-related neurofunctional reorganization is task-load-dependent. Taken together, these studies suggest that neurofunctional reorganization in aging is based on a more dynamic, flexible and adaptive neurofunctional process than previously proposed. This review summarizes the different factors that are thought to support the preservation of the semantic processing of words in aging, and highlights a multidetermined and complex set of processes such as the nature of the specific cognitive processes, task complexity and cognitive strategy, characterizing the neurofunctional reorganization in aging that allows for optimal cognitive abilities. In so doing, it provides the background for future study looking at the neurofunctional dimensions of the impact of neurodegenerative diseases on cognitive abilities.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".