Dysfunction of the Default Mode Network in Parkinson Disease
Bibliographic record
Abstract
OBJECTIVE: To examine the integrity of the default mode network in patients with Parkinson disease (PD). Previous functional neuroimaging experiments have studied executive deficits in patients with PD with regard to task-related brain activation. However, recent studies suggest that executive performance also relies on the integrity of the default mode network (ie, medial prefrontal cortex, posterior cingulate cortex, precuneus, and lateral parietal and medial temporal cortices), characterized by a deactivation of these cortical areas during the performance of executive tasks. DESIGN: We used functional magnetic resonance imaging to investigate cortical deactivations during a card-sorting task (retrieval and manipulation of short-term memory contents) compared with a simple sensory-motor matching task. In addition, a functional connectivity analysis was performed. SETTING: Tertiary outpatient clinic. PARTICIPANTS: Seven patients with mild to moderate PD (not taking medication) and 7 healthy controls. MAIN OUTCOME MEASURE: Cortical deactivations. RESULTS: Both groups showed comparable deactivation of the medial prefrontal cortex but different deactivation in the posterior cingulate cortex and the precuneus. Compared with controls, patients with PD not only showed less deactivation of the posterior cingulate cortex and the precuneus, they even demonstrated a reversed pattern of activation and deactivation. Connectivity analysis yielded that in contrast to healthy individuals, medial prefrontal cortex and the rostral ventromedial caudate nucleus were functionally disconnected in PD. CONCLUSIONS: We describe specific malfunctioning of the default mode network during an executive task in PD. This finding is plausibly linked to dopamine depletion and may critically contribute to the understanding of executive deficits in PD.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".