Psychiatric phenotype in neurodevelopmental myoclonus-dystonia is underpinned by abnormality of cerebellar modulation on the cerebral cortex
Bibliographic record
Abstract
Psychiatric symptoms are common in neurodevelopmental movement disorders, including some types of dystonia. However, research has mainly focused on motor manifestations and underlying circuits. Myoclonus-dystonia is a rare and homogeneous neurodevelopmental condition serving as an illustrative paradigm of childhood-onset dystonias, associated with psychiatric symptoms. Here, we assessed the prevalence of psychiatric disorders and the severity of depressive symptoms in patients with myoclonus-dystonia and healthy volunteers (HV). Using resting-state functional neuroimaging, we compared the effective connectivity within and among non-motor and motor brain networks between patients and HV. We further explored the hierarchical organization of these networks and examined the relationship between their connectivity and the depressive symptoms. Comparing 19 patients to 25 HV, we found a higher prevalence of anxiety disorders and more depressive symptoms in the patient group. Patients exhibited abnormal modulation of the cerebellum on the cerebral cortex in the sensorimotor, dorsal attention, salience, and default mode networks. Moreover, the salience network activity was directed by the cerebellum in patients and was related to depressive symptoms. Altogether, our findings highlight the role of the cerebellar drive on both motor and non-motor cortical areas in this disorder, suggesting cerebellar involvement in the complex phenotype of such neurodevelopmental movement disorders.
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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) | 0.001 | 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".