Intact working memory in non‐manifesting <i><scp>LRRK</scp>2</i> carriers – an <scp>fMRI</scp> study
Bibliographic record
Abstract
Cognitive impairments are prevalent in patients with Parkinson's disease. Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene are the most common cause of genetic Parkinsonism. Non-manifesting carriers of the G2019S mutation in the LRRK2 gene were found to have lower executive functions as measured by the Stroop task. This exploratory study aimed to assess whether the cognitive impairment in non-manifesting carriers is specific for executive functions or includes other cognitive domains such as working memory. We recruited 77 non-manifesting first-degree relatives of Parkinson's disease patients (38 carriers). A block-design fMRI N-back task, with 0-back, 2-back and 3-back conditions, was used in order to assess working memory. Participants were well matched on the Montreal Cognitive Assessment, University of Pennsylvania Smell Identification Test, Unified Parkinson's Disease Rating Scale part III, digit span, age, gender and Beck Depression Inventory. The task achieved the overall expected effect in both groups with longer reaction times and lower accuracy rates with increasing task demands. However, no whole-brain or region-of-interest between-groups differences were found on any of the task conditions. These results indicate that non-manifesting carriers of the G2019S mutation in the LRRK2 gene have a specific cognitive profile with executive functions, as assessed by the Stroop task, demonstrating significant impairment but with working memory, as assessed with the N-back task, remaining relatively intact. These finding shed light on the pre-motor cognitive changes in this unique 'at risk' population and should enable more focused cognitive assessments of these cohorts.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".