Analysis of person recognition deficits in genetic frontotemporal dementia
Bibliographic record
Abstract
BACKGROUND: Semantic and socioemotional knowledge, including person recognition, can be altered in frontotemporal dementia (FTD), and is often associated with the right temporal lobe variant. Using data from the Genetic FTD Initiative, we investigated person recognition deficits in genetic FTD. METHOD: 901 GENFI participants (279 mutation negative controls, 280 C9orf72 mutation carriers (MCs), 101 MAPTMCs and 241 GRN MCs) were grouped using the Clinical Dementia Rating scale plus National Alzheimer's Coordinating Centre Frontotemporal Lobar Degeneration (CDR plus NACC FTLD) global score where 0 denotes asymptomatic, 0.5 as prodromal, and 1+ as mild to severe symptoms (C9orf72: 135 = 0, 48 = 0.5, 97 = 1+; GRN: 143 = 0, 35 = 0.5, 63 = 1+; MAPT: 50 = 0, 20 = 0.5, 31 = 1+). Person recognition (PR) was assessed using a single question within a structured clinical questionnaire, scoring the ability to recognise people who should be familiar by face or voice to them, with a value between 0 (absent) to 3 (severe), similar to the CDR scale. The percentage of participants with PR deficits was calculated for each group. Logistic regression with bootstrapping compared the PR score between groups with age, gender, and education as covariates. RESULT: 16.1% of C9orf72 MCs (0 = 0.7%, 0.5 = 2.1%, 1+ = 44.3%), 7.5% of GRN (0 = 0.0%, 0.5 = 8.6%, 1+ = 23.8%) and 17.8% of MAPT carriers (0 = 2%, 0.5 = 10%, 1+ = 48.4%) showed PR deficits. Mean (standard deviation) severity in each group was: C9orf72 0 = 0.0(0.0), 0.5 = 0.0(0.1), 1+ = 0.6(0.9); GRN 0 = 0.0(0.0), 0.5 = 0.0(0.1), 1+ = 0.2(0.6); MAPT 0 = 0.0(0.2), 0.5 = 0.1(0.3), 1+ = 0.6(0.8). Each of the symptomatic genetic groups had a significantly greater PR deficit than the control group (p<0.001), with the prodromal MAPT (p = 0.006) and GRN (p<0.001) groups also showing a greater impairment than controls. There was a trend to significance in the C9orf72asymptomatic and prodromal groups compared with controls (p = 0.058 and p = 0.059 respectively). Symptomatic C9orf72 and MAPT carriers showed greater impairment than the symptomatic GRN carriers (both p = 0.005). CONCLUSION: Person recognition is a key early marker of disease in some individuals with genetic FTD and further imaging analyses will help to reveal the underlying mechanism of this deficit.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".