Medial Temporal Lobe Amnesia Is Associated with a Deficit in Recovering Temporal Context
Bibliographic record
Abstract
Medial-temporal lobe (MTL) lesions are associated with severe impairments in episodic memory. In the framework of the temporal context model, the hypothesized mechanism for episodic memory is the reinstatement of a prior experienced context (i.e., "jump back in time"), which relies upon the MTL [Howard, M. W., Fotedar, M. S., Datey, A. V., & Hasselmo, M. E. The temporal context model in spatial navigation and relational learning: Toward a common explanation of medial temporal lobe function across domains. Psychological Review, 112, 75-116, 2005]. This hypothesis has proven difficult to test in amnesia because of the floor-level performance by patients in recall tasks. To circumvent this issue, in this study, we used a "looped-list" format, in which a set of verbal stimuli was presented multiple times in a consistent order. This allowed for comparison of statistical properties such as probability of first recall and lag-conditional response probability (lag-CRP) between amnesic patients and healthy controls. Results revealed that the lag-CRP, but not the probability of first recall, is altered in amnesia, suggesting a selective disruption of temporal contiguity. To further characterize the results, we fit a scale-invariant version of the temporal context model [Howard, M. W., Shankar, K. H., Aue, W. R., & Criss, A. H. A distributed representation of internal time. Psychological Review, 122, 24-53, 2015] to the probability of first recall and lag-CRP curves. The modeling results suggested that the deficit in temporal contiguity in amnesia is best described as a failure to recover temporal context. These results provide the first direct evidence for an impairment in a jump-back-in-time mechanism in patients with MTL amnesia.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".