Parkinson's disease patients show reduced cortical‐subcortical sensorimotor connectivity
Bibliographic record
Abstract
Reduced dopamine input to cortical and subcortical brain structures, particularly those in the sensorimotor network, is a hallmark of Parkinson's disease (PD). The extent to which dopamine dysfunction affects connectivity within this and other brain networks remains to be investigated. The purpose of this study was to measure anatomical and functional connectivity in groups of PD patients and controls to determine whether connectivity deficits within the cortico-basal ganglia thalamocortical system could be attributed to PD, particularly in sensorimotor connections. A neuroimaging paradigm involving diffusion-weighted magnetic resonance imaging (MRI) and resting-state functional MRI was implemented in a large cohort of PD patients and control subjects. Probabilistic tractography and functional correlation analyses were performed to map connections between brain structures and to derive indices of connectivity that were then used to compare groups. Anatomical connectivity deficits were demonstrated in PD patients, specifically for sensorimotor connections. Functional deficits were also found in some of the same connections. In addition, functional connectivity was found to increase in associative and limbic connections in PD patients compared with controls. This study lends support to findings regarding the dysfunction of the sensorimotor circuit in PD. As deficits in anatomical and functional connectivity within this circuit were in some cases concordant in PD patients, a possible link between brain structure and function is suggested. Increases in functional connectivity in other cortico-basal ganglia thalamocortical circuits may be indicative of compensatory effects in response to system deficits elsewhere.
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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 | 0.001 | 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) | 0.002 | 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".