The Neural Signature of Impaired <scp>Dual‐Tasking</scp> in Idiopathic Rapid Eye Movement Sleep Behavior Disorder Patients
Bibliographic record
Abstract
Dual-task gait can be a useful biomarker for cognitive decline and a sensitive predictor of future neurodegeneration in certain clinical populations, such as patients with idiopathic rapid eye movement sleep behavior disorder. OBJECTIVES: The objective of this cross-sectional study was to determine the neural signature of dual-tasking deficits in idiopathic rapid eye movement sleep behavior disorder using a validated gait paradigm. METHODS: Fifty-eight participants (28 controls; 30 idiopathic rapid eye movement sleep behavior disorder patients) were recruited; 52 participants had functional MRI scans as they performed a validated dual-task virtual reality gait paradigm using foot pedals. Forty-one participants completed single- and dual-task "overground walking" on a pressure sensor carpet. RESULTS: Idiopathic rapid eye movement sleep behavior disorder patients showed deficits in dual-tasking (i.e., greater mean step time) compared to controls during "overground walking." Functional MRI revealed that idiopathic rapid eye movement sleep behavior disorder patients had reduced blood-oxygen-level-dependent signal change in the dorsal caudate nucleus, and significantly different corticostriatal functional connectivity patterns from controls, when dual-tasking in high versus low cognitive load. While controls showed greater connectivity between frontoparietal and motor networks, idiopathic rapid eye movement sleep behavior disorder patients exhibited less change in this connectivity as a function of cognitive load. CONCLUSIONS: These findings demonstrate evidence of dual-task gait deficits in idiopathic rapid eye movement sleep behavior disorder patients, underpinned by disrupted corticostriatal connectivity. Minimal differences in the level of functional connectivity between dual-tasking conditions of high and low cognitive load suggest that idiopathic rapid eye movement sleep behavior disorder patients recruit cognitive networks to control gait even when the cognitive demands are low. This may indicate a compensatory strategy for early cognitive decline in idiopathic rapid eye movement sleep behavior disorder. © 2020 International Parkinson and Movement Disorder Society.
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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) | 0.001 | 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".