“Where to?” Remote Memory for Spatial Relations and Landmark Identity in Former Taxi Drivers with Alzheimer's Disease and Encephalitis
Bibliographic record
Abstract
Recent research suggests that the hippocampus is not needed for the maintenance and recovery of extensively used environments learned long ago. Instead, a network of neocortical regions differentially supports memory for locationnavigation knowledge and visual appearance of well-known places. In this study, we present a patient, S. B., who was diagnosed with probable Alzheimer's disease long after retiring from his 40 years as a taxi driver in downtown Toronto, a place that he has visited rarely, if ever, in the last decade. His performance was compared to that of two other retired taxi drivers, L. R., who developed encephalitis after retirement, and I. L., who is without neurological illness, and a group of eight healthy control participants who were never taxi drivers but all of whom worked or lived in downtown Toronto until at least 10 years ago. Despite S. B.'s widespread atrophy, which has affected mainly his hippocampus and part of his occipitotemporal cortex, he performed at least as well as all other participants on remote memory tests of spatial location and mental navigation between well-known Toronto landmarks. Unlike the comparison populations, however, he was unable to discriminate between the appearances of landmarks that he had visited frequently in his many years as a taxi driver from unknown buildings. This profound deficit extended to famous world landmarks but not to famous faces and does not appear to be semantic in nature. These findings add further support to the claim that the hippocampus is not necessary for mental navigation of old environments and suggest that expertise is not sufficient to protect against landmark agnosia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".