Impairment of episodic memory in genetic frontotemporal dementia: A GENFI study
Bibliographic record
Abstract
Abstract Introduction We aimed to assess episodic memory in genetic frontotemporal dementia (FTD) with the Free and Cued Selective Reminding Test (FCSRT). Methods The FCSRT was administered in 417 presymptomatic and symptomatic mutation carriers (181 chromosome 9 open reading frame 72 [ C9orf72 ], 163 progranulin [ GRN ], and 73 microtubule‐associated protein tau [ MAPT ]) and 290 controls. Group differences and correlations with other neuropsychological tests were examined. We performed voxel‐based morphometry to investigate the underlying neural substrates of the FCSRT. Results All symptomatic mutation carrier groups and presymptomatic MAPT mutation carriers performed significantly worse on all FCSRT scores compared to controls. In the presymptomatic C9orf72 group, deficits were found on all scores except for the delayed total recall task, while no deficits were found in presymptomatic GRN mutation carriers. Performance on the FCSRT correlated with executive function, particularly in C9orf72 mutation carriers, but also with memory and naming tasks in the MAPT group. FCSRT performance also correlated with gray matter volumes of frontal, temporal, and subcortical regions in C9orf72 and GRN , but mainly temporal areas in MAPT mutation carriers. Discussion The FCSRT detects presymptomatic deficits in C9orf72 ‐ and MAPT ‐associated FTD and provides important insight into the underlying cause of memory impairment in different forms of FTD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".