Hippocampal abnormalities and memory deficits in Parkinson disease
Bibliographic record
Abstract
OBJECTIVES: Investigating in a case-control study whether the performance scores of a group of patients with Parkinson disease (PD) without dementia on tests of declarative memory could be predicted by hippocampal volume reduction (as assessed by automatic segmentation of cerebral magnetic resonance [MR] images) or by the rate of microstructural alterations (as evaluated by diffusion tensor analysis of MR images). METHOD: Twenty-five individuals with PD and 25 matched healthy control subjects underwent a 3-T MRI protocol with whole-brain T1-weighted and diffusion tensor imaging and a neuropsychological assessment. Images were processed to obtain indices of macrostructural (volume) and microstructural (mean diffusivity [MD]) variation of bilateral hippocampi. Neuropsychological evaluation included tests of verbal memory (15-minute delayed recall of a 15-word list) and visuospatial memory (20-minute delayed reproduction of Rey complex figure). RESULTS: MD in the hippocampi of patients with PD was significantly increased with respect to that of the group of control subjects. Moreover, patients with high hippocampal MD values obtained low memory scores. In contrast, no difference emerged between patients with PD and healthy control subjects for hippocampal size, and no relationship could be found between hippocampal volumes and memory scores. CONCLUSIONS: These data confirm that the declarative memory impairment in patients with PD without dementia may be predicted by the rate of microstructural alterations in the hippocampal formation as detected by diffusion tensor imaging analysis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".