Detailed descriptions of routes traveled, but not map‐like knowledge, correlates with tests of hippocampal function in older adults
Bibliographic record
Abstract
We examined hippocampal contribution to remote spatial memory in older adults by correlating their performance on tests sensitive to hippocampal damage with their description of routes they traversed many times or only once, and with their map-like knowledge of downtown Toronto. We found that performance on table-top tests of spatial location (Smith and Milner (1981) Neuropsychologia 19:781-793) and on paired-associate learning, and the number of Internal Details on the Autobiographical Interview (Levine et al., (2002) Psychol Aging 17:677-689), all correlated significantly with the number and type of perceptual details used in describing routes one has traversed, but not with map-like knowledge of Toronto. No significant correlations were found with performance on tests of frontal function (WCST, phonemic fluency, and backward digit span). We conclude that the hippocampus is implicated in vivid re-experiencing of a familiar route, but not with map-like knowledge of a large-scale environment. These findings are interpreted as consistent with Multiple Trace Theory's prediction that it is the degree of detail of a retrieved memory that is crucially dependent on the hippocampus.
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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 | 0.004 |
| 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 | 0.001 | 0.001 |
| 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".