帕金森低氧症患者动态功能连接改变和高阶信息交互减少。

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Sneha Ray, Navkiran Kalsi, Henning Boecker, Neeraj Upadhyay, Rajanikant Panda
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引用次数: 0

摘要

低嗅觉是帕金森病(PD)中一种常见的非运动症状,与气味敏感性降低有关,与大脑结构和功能变化有关,但大脑动态活动和区域信息交换的改变仍未得到充分研究,限制了对潜在大脑状态的了解。我们选择了15例重度低氧PD患者(PD- sh)、15例认知正常PD患者(PD- cn)和15例健康对照(HC)。利用功能性MRI,我们评估了大脑的时空连通性(大脑状态)变化,以及大脑的高阶信息交换能力(协同和冗余)。与HC相比,PD-SH和PD-CN组具有复杂远程连接的动态脑状态明显减少。由感觉运动区和额叶区模块簇组成的脑状态在PD-SH中比PD-CN和HC中更常见。PD患者的高阶信息流减少,PD- sh显示额叶、岛叶和左侧感觉运动的协同信息流减少更大。这些发现提示了PD-SH潜在的鉴别性生物标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Altered dynamic functional connectivity and reduced higher order information interaction in Parkinson's patients with hyposmia.

Hyposmia, a common non-motor symptom in Parkinson's disease (PD) linked to reduced odor sensitivity, is associated with brain structural and functional changes, but dynamic brain activity and altered regional information exchange remain underexplored, limiting insight into underlying brain states. We selected 15 PD patients with severe hyposmia (PD-SH), 15 PD patients with normal cognition (PD-CN), and 15 healthy controls (HC). Using functional MRI, we assessed the brain's spatiotemporal connectivity (brain-state) alterations, and the brain's capacity for higher-order information exchange (synergy and redundancy). A dynamic brain state with complex-long-range connections was significantly reduced in PD-SH and PD-CN, compared to HC. Brain-states consisting of modular-clusters in sensorimotor and frontal areas occurred more frequently in PD-SH than in PD-CN and HC. Higher-order information flow was reduced in PD patients, with PD-SH showing a greater reduction in synergetic information flow in frontal, insula, and left sensory-motor. These findings suggest potential discriminative biomarkers for PD-SH.

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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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