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<p>Non-motor symptoms in Parkinson’s disease impair quality of life, yet their neural basis is unclear, the link between amygdala subregion fiber properties and these symptoms remains unexplored. We analyzed 114 Parkinson’s disease patients from the PPMI group using diffusion tensor imaging and FreeSurfer to segment nine amygdala subregions. By using fixel-based analysis, each subregion’s volume and diffusion metrics were extracted. Finally, correlation and regression analyses were assessed associations with Non-motor symptoms scores. Diffusion metrics of white matter tracts from amygdala subregions correlated with Non-motor symptoms, like emotion and visuospatial performance. Multiple regression analysis showed that Combined measure of fiber density and cross-section in bilateral amygdala subregions, especially the right cortico-amygdaloid transition, predicted visuospatial function. Right-sided nuclei volume was also correlated with performance. Anxiety severity was linked to bilateral amygdala tract changes, more notably on the left, with reduced white matter integrity and decreased volume in the left basal and paralaminar nuclei. Additionally, fiber density from the left cortical amygdala was negatively correlated with Rapid Eye Movement Sleep Behavior Disorder Questionnaire. This study reveals that alterations in white matter tracts and volume within amygdala subregions are associated with the stability of non-motor symptoms, suggesting their potential as imaging biomarkers for Parkinson’s disease. This finding provides a basis for clinical identification and intervention.</p>

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Association between amygdala subregions and non-motor symptoms in Parkinson’s disease: a fixel-based analysis

  • 期刊论文

  • 发表日期：

    2026年7月2日

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  • Yuchen She,
  • Jiahao Wei,
  • Junyi Wang,
  • Ying Liu,
  • Sicheng Chen,
  • Man Zhang,
  • Qi Yang,
  • Lijuan Mo,
  • Changhong Tan,
  • Xi Liu,
  • Lifen Chen

摘要

Non-motor symptoms in Parkinson’s disease impair quality of life, yet their neural basis is unclear, the link between amygdala subregion fiber properties and these symptoms remains unexplored. We analyzed 114 Parkinson’s disease patients from the PPMI group using diffusion tensor imaging and FreeSurfer to segment nine amygdala subregions. By using fixel-based analysis, each subregion’s volume and diffusion metrics were extracted. Finally, correlation and regression analyses were assessed associations with Non-motor symptoms scores. Diffusion metrics of white matter tracts from amygdala subregions correlated with Non-motor symptoms, like emotion and visuospatial performance. Multiple regression analysis showed that Combined measure of fiber density and cross-section in bilateral amygdala subregions, especially the right cortico-amygdaloid transition, predicted visuospatial function. Right-sided nuclei volume was also correlated with performance. Anxiety severity was linked to bilateral amygdala tract changes, more notably on the left, with reduced white matter integrity and decreased volume in the left basal and paralaminar nuclei. Additionally, fiber density from the left cortical amygdala was negatively correlated with Rapid Eye Movement Sleep Behavior Disorder Questionnaire. This study reveals that alterations in white matter tracts and volume within amygdala subregions are associated with the stability of non-motor symptoms, suggesting their potential as imaging biomarkers for Parkinson’s disease. This finding provides a basis for clinical identification and intervention.