Age-related differences in prefrontal-hippocampal connectivity are associated with reduced spatial context memory.
Bibliographic record
Abstract
Altered functional connectivity between dorsolateral prefrontal cortex (DLPFC), posterior hippocampus (HC) and other brain regions with advanced age may contribute to age-related differences in episodic memory. In the current fMRI study of spatial context memory, we used seed connectivity analysis to test for age-related differences in the correlations between activity in DLPFC and HC seeds, and the rest of the brain, in an adult life span sample. In young adults, we found that connectivity between right DLPFC and other prefrontal cortex regions, parietal cortex, precuneus, and ventral visual cortices during encoding was positively related to performance. Positive seed connectivity among these regions, and negative connectivity with posterior HC at retrieval was also positively correlated with retrieval accuracy in young adults. In older adults, activity in right DLPFC was positively correlated with activity in this same set of brain regions, and with posterior HC during encoding and retrieval. Interestingly, this pattern of seed connectivity in older adults was negatively correlated with retrieval accuracy. Thus, age-related differences in context memory may be related to altered frontal-parietal and visual cortical interactions with posterior HC. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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".