Familiarity Deficits for Words and Objects in Amnestic Mild Cognitive Impairment in a Context Minimizing the Role of Recollection
Bibliographic record
Abstract
OBJECTIVES: Amnestic mild cognitive impairment (aMCI) is associated with cortical thinning in perirhinal and entorhinal cortices, key regions of the brain supporting familiarity. Individuals with aMCI demonstrate familiarity deficits in their behavior, often repeating questions in the same conversation. While familiarity deficits in healthy aging are minimal, past studies measuring familiarity in aMCI have mixed results, perhaps due to the influence of recollection. We therefore used a paradigm that minimized the influence of recollection, and hypothesized that familiarity would be impaired in aMCI relative to age-matched controls, but not in healthy older adults relative to younger adults. We also hypothesized that familiarity deficits in aMCI would be greater for objects than words because the perirhinal cortex plays a significant role in visual discrimination. METHODS: A sample of 36 younger adults, 38 cognitively intact older adults, and 30 older adults with aMCI made absolute frequency judgments for words and objects seen a variable number of times in an incidental encoding task. Estimates of familiarity were derived from correlating participants' frequency judgments with the actual frequency of presentation. RESULTS: Familiarity was largely spared in healthy aging, with minor deficits in familiarity for words. Familiarity deficits were evident in aMCI comparably for words and objects. DISCUSSION: The present research underscores the need to study familiarity in contexts minimizing recollection, particularly when comparing groups with different levels of recollection, and adds to our understanding of the phenomenology of aMCI. Familiarity deficits may provide an early biomarker of dementia risk.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".