Integrity of autobiographical memory and episodic future thinking in older adults varies with cognitive functioning
Bibliographic record
Abstract
Research has documented changes in autobiographical memory and episodic future thinking in mild cognitive impairment (MCI) and Alzheimer’s disease (AD). However, cognitive decline occurs gradually and recent findings suggest that subtle alterations in autobiographical memory may be evident early in the trajectory towards dementia, before AD-related symptoms emerge or a clinical diagnosis has been given. The current study used the Autobiographical Interview to examine the episodic and semantic content of autobiographical past and future events generated by healthy older adults (N=20) and older adults “at risk” of cognitive decline (as defined by their score on the Montreal Cognitive Assessment) but who do not meet criteria for formal diagnosis of MCI (N=18). The Autobiographical Interview was conducted by telephone during the COVID-19 pandemic across six monthly sessions; in each session, participants described two past and two future autobiographical events. Transcripts were scored by classifying each detail as internal (episodic) or external (non-episodic, including semantic) to the main event. Although the at-risk group exhibited a differential reduction for internal details comprising both past and future events, they did not show the expected overproduction of external details that is evident in MCI, possibly because their episodic and executive abilities were not sufficiently compromised. Multilevel modelling demonstrated that on trials lower in episodic content, semantic content was significantly increased in both groups. Although suggestive of a compensatory mechanism, the finding that the magnitude of this relationship did not differ across groups indicates it may reflect an age-related semanticization of autobiographical events that is not affected by cognitive decline. This study contributes to our knowledge of the trajectory of cognitive decline as it pertains to the ability to recollect the personal past and imagine the personal future.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".