Increased variability accompanies frontal lobe damage in dementia
Bibliographic record
Abstract
Performance variability on neuropsychological measures is not a unitary phenomenon, and different measures (consistency, dispersion, diversity) evaluate separate elements of variability. It has been suggested that increased variability may be a specific attribute of frontal lobe pathology. This hypothesis was tested in 2 matched groups of demented subjects, 8 with dementia of the Alzheimer type (DAT), 5 with frontal lobe dementia (FLD), compared with 10 elderly normal controls (ENC). A Stroop test and Reaction Time measures were administered weekly for 5 weeks to all subjects. Both measures contained three subtests varying in degree of complexity. The results from the Stroop task indicated that the FLD group showed significantly greater variability on measures of consistency (fluctuations over time) and diversity (between participant variability) regardless of the complexity of the subtest. For the Reaction Time subtests, measures of consistency and diversity showed significantly greater variability in FLD, but were affected in a different pattern. Greater variability in terms of consistency of performance was manifested only in the more attentionally demanding of the Reaction Time subtests (Choice Reaction Time, CRT). On the measure of diversity, variable performance was found to be greater on the Simple Reaction Time (SRT) subtest than on the more effortful CRT. Dispersion (within participant variability) was only assessed on the reaction time subtests. The results indicate no significant evidence for an increase in dispersion for the FLD patients. The hypothesis that variability will be increased in frontal lobe dementia is thus confirmed, and the independence of the three forms of variability measurement is demonstrated in dementia subjects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".