Neuroplastic Effects of Dance Training in Parkinson’s Disease: Functional and Structural Modulation in Speech-Related Brain Regions
Notice bibliographique
Résumé
Abstract Background Parkinson’s disease (PD) is a neurodegenerative disorder characterized by progressive motor and non-motor impairments, including speech deficits. Dance-based interventions have been proposed as a promising rehabilitative strategy for enhancing motor function, cognitive engagement, and neuroplasticity. However, the neural mechanisms underlying dance-induced neuroplasticity remain poorly understood. Objective This study aimed to investigate the effects of an 8-month dance training program on functional brain activity, cortical structure, and white matter integrity in people with PD (PwPD) using a multi-modal neuroimaging approach. Methods Ten individuals with PD participated in dance training and underwent functional MRI (fMRI) and cortical thickness analysis (T1-weighted MRI) at four time points, and 4 of them underwent diffusion-weighted imaging (DWI) at the last two time points. fMRI examined BOLD signal changes in the motor cortex (inferior frontal gyrus) and the supplementary motor area (SMA) during a dance-imagery task. Cortical thickness was measured in Broca’s area and the left supplementary frontal language (SFL) area. A reference group from the Michael J. Fox Foundation’s Parkinson’s Progression Markers Initiative (PPMI) dataset was selected for cortical thickness analysis. White matter integrity between Broca’s area and the SFL area was assessed using fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD). Additionally, fundamental frequency standard deviation (F0SD), a key indicator of speech prosody, was analyzed in three participants over a 5-year follow-up period to examine the functional relevance of neuroplastic changes. Results Reductions in BOLD signal were observed in the motor cortex (inferior frontal gyrus) between September and January ( p = 0.021), suggesting increased neural efficiency. In contrast, SMA exhibited a significant increase in BOLD signal activity between September and January ( p = 0.010), indicating enhanced motor-speech integration. No further notable changes in functional activity in both regions were detected between January and April. The dance group showed significant changes in cortical thickness in the left SFL area across time, with increases from September to December ( p = 0.049) followed by decreases from December to April ( p = 0.046). However, no changes were detected in Broca’s area for the dance or reference groups. Additionally, the reference group did not exhibit any significant changes in the left SFL area across the same time points. FA increased significantly between January and April ( p = 0.024), suggesting enhanced white matter organization in speech-motor pathways. AD showed a marginal increase during this period ( p = 0.056), while RD and MD remained stable. Critically, voice feature analysis revealed significant improvements in F0SD over the 5-year follow-up period ( p < 0.0001), demonstrating sustained functional benefits in speech prosody that were associated with the earlier neuroplastic adaptations. Conclusion Dance training was associated with significant functional and white matter neuroplastic changes in PD, particularly in motor-related functional activity and white matter connectivity between motor and language networks. The neuroplastic adaptations observed during the 8-month intervention period were associated with sustained improvements in speech prosody that persisted for years, providing compelling evidence for the clinical relevance of dance-induced brain changes. While dynamic cortical thickness changes were observed in the SFL area, the functional and structural connectivity adaptations appear to be the primary drivers of therapeutic benefit. These findings highlight dance as a promising, intervention for enhancing neural efficiency and motor-linguistic integration in PD, with demonstrated long-term functional benefits that warrant further investigation in larger, controlled studies.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».