Hyperfamiliarity in Amnestic and Vascular Mild Cognitive Impairment
Bibliographic record
Abstract
OBJECTIVE: Hyperfamiliarity is a phenomenon where new stimuli are perceived as familiar. Previous studies have demonstrated familiarity disorder in mild cognitive impairment (MCI), but mostly from the perspective of a neuropsychological approach, and the exact correlation of MCI aetiologies with the phenomenon remains uncertain. Based on current evidence suggesting a frontal-subcortical pathway contributing to familiarity processing, we hypothesize that individuals with a vascular aetiology of MCI will likely suffer more familiarity deficits. This study aims to examine the real-life hyperfamiliarity symptoms in amnestic versus vascular MCI. METHODS: Informants of 11 amnestic and 9 vascular cognitive impairment patients were interviewed about the frequency of hyperfamiliarity symptoms in the previous month. MRI brain images of vascular cognitive impairment patients were analysed as well. RESULTS: Patients with vascular cognitive impairment with no dementia (VCIND) showed a significantly higher frequency of hyperfamiliarity for people but not places or objects. Within VCIND patients, overall basal ganglia hyperintensities, particularly in the putamen, were found to significantly correlate to hyperfamiliarity. CONCLUSIONS: Patients with VCIND suffer more real-life hyperfamiliarity during people recognition compared to patients with amnestic mild cognitive impairment (aMCI), despite a comparative global decline in cognitive. This is likely due to impaired memory retrieval and matching processes resulting from subcortical ischaemic lesions.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| 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".