Retrieval of autobiographical memory in Alzheimer's disease: Relation to volumes of medial temporal lobe and other structures
Bibliographic record
Abstract
The representation of autobiographical memory is distributed over a network of brain structures, with the medial temporal lobe (MTL) at its epicenter. Some believe that, over time, all memories become independent of their MTL component ("consolidation theories"). Others have suggested that this is true only of semantic memory, while episodic aspects of autobiographical memories are dependent on the MTL for as long as they exist, such as multiple trace theory (MTT). In the present study, the volumes of 28 brain regions, including the MTL, and their relation to autobiographical memory were investigated in a group of patients with Alzheimer's disease with varying degrees of retrograde memory loss as assessed by the Autobiographical Memory Interview (AMI). We used the multivariate analysis method of partial least squares (PLS) to assess patterns of atrophy that can lead to retrograde amnesia. We found that different aspects of autobiographical memory were associated with different patterns of tissue loss. Personal semantics were related to a pattern of bilateral anterior and posterior lateral temporal cortex degeneration, more pronounced on the left, as well as right frontal degeneration. Autobiographical event memory ("episodic") was associated with combined atrophy in bilateral MTL and anterior lateral temporal neocortex, more pronounced on the right. This pattern was invariant for memories from childhood, early adulthood, and recent memories, in line with the predictions of MTT, suggesting that MTL tissue is crucial for retrieval of episodic memories regardless of their age.
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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) | 0.001 | 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".