Memory for familiar environments learned in the remote past: fMRI studies of healthy people and an amnesic person with extensive bilateral hippocampal lesions
Bibliographic record
Abstract
Preserved remote spatial memory in amnesic people with bilateral hippocampal damage, including the well-studied case K.C., challenges spatial theories, which assume that the hippocampus is needed to support all allocentric spatial representations, old or new. It remains possible, however, that residual hippocampal tissue is functional and contributes to successful performance. Here, we examine brain activity with fMRI during the retrieval of spatial information in K.C. and in healthy controls using landmark and route stimuli from a premorbidly familiar neighborhood that K.C. can navigate normally. In all participants, activity was found in the parahippocampal cortex, but not in the hippocampus itself, during all navigational tasks on which K.C. performs well, even though part of his hippocampus remains viable. The opposite pattern was observed on a house recognition task, which is inconsequential to navigation, and on which K.C. performed poorly. On that task, K.C. recruited the right hippocampus presumably because even "familiar" houses were treated as novel by him, whereas controls recruited occipitotemporal cortex, including parahippocampal cortex. The distinction between recent and remote memory, therefore, may apply as much to spatial theories of hippocampal function as it does to theories emphasizing the role of the hippocampus in other types of explicit memory.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".