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Background <p>The globus pallidus (GP) is a critical basal ganglia nucleus for motor and cognitive control. However, traditional single-modality parcellations provide an incomplete understanding of its internal organization, thereby increasing the risk of imprecision and side effects during therapeutic targeting of its subregions.</p> Methods <p>In this study, we developed a multi-modal approach that combines structural and functional connectivity, termed hybrid pallidum parcellation (HPP), to parcellate the GP into anterior (aGP), middle (mGP), and posterior (pGP) subregions. This approach was rigorously evaluated for reproducibility and homogeneity in healthy individuals and behavioral prediction accuracy in healthy individuals and patients with Parkinson’s disease (PD). Connectivity and behavioral prediction analyses were further used to explore the structural and functional differences in the GP subregions.</p> Results <p>Compared with unimodal (structural or functional connectivity-based) and two public parcellations, HPP demonstrated superior reproducibility and homogeneity. In addition, the HPP-based subregions revealed a posterior-to-anterior structural and functional connectivity gradient in GP, reflecting a transition from primary to higher-order networks. Specifically, the pGP dominated in sensorimotor function prediction and the aGP in emotional processing, while the mGP exhibited a more flexible pattern in cognition and higher-order motor control. Furthermore, the HPP parcellation demonstrated generalizability and superiority in better predicting behavioral measures than other parcellations in both healthy individuals and patients with PD.</p> Conclusions <p>Overall, HPP provides new insights into the GP’s hierarchical functional organization and its subregional roles in PD motor and non-motor symptoms, offering potential to improve patient stratification for PD and related disorders.</p>

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A multi-modal parcellation of human globus pallidus and its implications for symptom prediction and stratification in Parkinson’s disease

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月9日

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  • Tianyi Yan,
  • Kexin Wang,
  • Ziteng Han,
  • Yunxiao Ma,
  • Xiu Wang,
  • Kai Zhang,
  • Guoyuan Yang,
  • Tiantian Liu

摘要

Background

The globus pallidus (GP) is a critical basal ganglia nucleus for motor and cognitive control. However, traditional single-modality parcellations provide an incomplete understanding of its internal organization, thereby increasing the risk of imprecision and side effects during therapeutic targeting of its subregions.

Methods

In this study, we developed a multi-modal approach that combines structural and functional connectivity, termed hybrid pallidum parcellation (HPP), to parcellate the GP into anterior (aGP), middle (mGP), and posterior (pGP) subregions. This approach was rigorously evaluated for reproducibility and homogeneity in healthy individuals and behavioral prediction accuracy in healthy individuals and patients with Parkinson’s disease (PD). Connectivity and behavioral prediction analyses were further used to explore the structural and functional differences in the GP subregions.

Results

Compared with unimodal (structural or functional connectivity-based) and two public parcellations, HPP demonstrated superior reproducibility and homogeneity. In addition, the HPP-based subregions revealed a posterior-to-anterior structural and functional connectivity gradient in GP, reflecting a transition from primary to higher-order networks. Specifically, the pGP dominated in sensorimotor function prediction and the aGP in emotional processing, while the mGP exhibited a more flexible pattern in cognition and higher-order motor control. Furthermore, the HPP parcellation demonstrated generalizability and superiority in better predicting behavioral measures than other parcellations in both healthy individuals and patients with PD.

Conclusions

Overall, HPP provides new insights into the GP’s hierarchical functional organization and its subregional roles in PD motor and non-motor symptoms, offering potential to improve patient stratification for PD and related disorders.