Impact of Weekly Community-Based Dance Training Over 8 Months on Depression and Blood Oxygen Level–Dependent Signals in the Subcallosal Cingulate Gyrus for People With Parkinson Disease: Observational Study
Bibliographic record
Abstract
Background: Dance has emerged as a complementary treatment that may promote adaptive neural plasticity while improving symptoms of Parkinson disease (PD), such as balance, gait, posture, and walking. Understanding brain changes that arise from participation in dance interventions is important as these neural plastic changes play an important role in protecting and healing the brain. Although dance has been shown to improve PD motor and nonmotor symptoms, the neural mechanisms underlying these changes, specifically depression and mood, remain elusive. Further, many side effects of PD drug treatments can be exacerbated or even induced by dopaminergic drugs, particularly depression and anxiety, making these nonmotor symptoms more noticeable throughout the progression of the disease. Objective: In this study, we focused on the impact of dance interventions on PD nonmotor symptoms by conducting an 8-month observational study, tracking the relationship between depression scores and functional neuroimaging measures for people with PD. Methods: A total of 34 dancers-23 (68%) people with PD and 11 (32%) healthy controls-completed the Geriatric Depression Scale (GDS) before and after attending weekly community-based dance classes, referred to as Dance for PD classes. Specifically, we examined changes within the functional magnetic resonance imaging signal from the subcallosal cingulate gyrus (SCG), an important node within the depression network and a controversial target for deep brain stimulation in the treatment of major depressive disorder. Results: Depression scores on the GDS decreased in each preintervention to postintervention comparison (all P<.025). In addition, GDS scores also improved over the 8-month dance period (all P<.01). Blood oxygen level-dependent signals from frontal cortex brain region implicated for emotional regulation within the SCG decreased at each testing time point (all P<.05). Also, a significant decrease in depression scores (GDS) was correlated with reduced blood oxygen level-dependent signals from the SCG (P=.02). Conclusions: This study contributes to an improved understanding of the neural mechanisms that are involved in depression, as well as the beneficial contribution that longitudinal dance interventions have in reducing nonmotor symptoms associated with PD, particularly in depression symptoms.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".