Exploring the recognition memory deficit in Parkinson's disease: estimates of recollection versus familiarity
Bibliographic record
Abstract
Current theories postulate that recognition memory can be supported by two independent processes: recollection (i.e. vivid memory for an item and the contextual details surrounding it) versus familiarity (i.e. the mere sense that an item is old). There is conflicting evidence on whether recognition memory is impaired in Parkinson's disease, perhaps because few studies have separated recollection from familiarity. We aimed to explore whether recollection or familiarity is more likely to be affected by Parkinson's disease, using three methods: (i) the word-frequency mirror effect to make inferences about recollection and familiarity based on recognition of high- versus low-frequency words, (ii) subjective estimates of recollection (remembering) versus familiarity (knowing), and (iii) a process-dissociation procedure where participants are required to endorse only some of the previously studied items on a recognition memory test, but not others. We tested Parkinson's disease patients (n = 19 and n = 16, age range = 58-77 years and age range = 50-75 in Experiments 1 and 2, respectively) and age- and education-matched controls (n = 23 and n = 16 in Experiments 1 and 2, respectively). Overall, the Parkinson's disease group showed a reduction in recognition memory, but this appeared to be primarily due to impairment of familiarity, with a lesser decline in recollection. We discuss how this pattern may be related to dysfunction of striatal, prefrontal and/or medial temporal regions in Parkinson's disease.
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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 | 0.002 |
| 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 | 0.001 |
| 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".