Brain networks associated with anticipatory postural adjustments in Parkinson’s disease patients with freezing of gait
Bibliographic record
Abstract
Specific impairments of anticipatory postural adjustment (APA) during step initiation have been reported in patients with Parkinson's disease (PD) and freezing of gait (FoG). Although APA disruption has been associated with FoG, there is scarce knowledge about its neural correlates. We sought to better understand the neural networks involved with APA in patients with FoG by assessing the level of hemodynamic response of specific brain regions and the functional connectivity during the leg lifting task. In the current investigation, APAs of patients with PD, with and without (nFoG) freezing were assessed during a leg lifting task in an event-related, functional magnetic resonance imaging (er-fMRI) protocol. Results identified a high hemodynamic response in the right anterior insula (AI) and supplementary motor area (SMA) in the FoG group when an APA was required. The nFoG had stronger connectivity between the right and left insulae than the FoG group. The strength of this connectivity was negatively correlated with the severity of FoG. Both groups showed different brain network organizations comprising the SMA and the bilateral AI. The SMA was found to be a hub in patients with FoG when an APA was required for the task. Our findings suggest that both groups used compensatory mechanism comprising the insulae during APA. Neither group used the entire network comprised of the insulae and SMA to accomplish the task. The FoG group relied more on SMA as a hub than as part of a broader network to exchange information during the APA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".