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帕金森病和健康个体使用结构性MRI的独特大脑网络识别号码

Tanmayee Samantaray¹, Utsav Gupta¹, Jitender Saini²

¹Neural Engineering Lab, Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Guwahati 781039, India.

|September 28, 2023

概括

一个新的算法,独特的大脑网络识别号 (UBNIN),使用结构性MRI独特编码单个大脑网络. 这种方法揭示了与年龄相关的大脑连接的变化,为网络退化提供了洞察力.

科学领域:

神经成像是一种神经成像.
计算神经科学是一种神经科学.
生物物理学的生物物理.

背景情况:

个体大脑网络的变化给神经成像分析带来了挑战.
了解与年龄相关的大脑连接的变化对于诊断神经系统疾病至关重要.

研究的目的:

引入一种新的算法,即独特的大脑网络识别号码 (UBNIN),用于编码单个的大脑网络.
在帕金森病 (PD) 患者和健康对照者 (HC) 中调查大脑网络拓和连接模式的年龄相关变化.

主要方法:

分析了180名PD患者和70名HC患者的结构性MRI数据.
通过使用灰色物质体积的相关矩阵构建大脑网络,并得出独特的代码 (UBNIN).
连接指标,包括聚类系数,在五个年龄队列中使用稀疏度值计算.

主要成果:

对于每个大脑网络,UBNIN算法产生了不同的数值表示.
观察到平均聚类系数的下降趋势,所有年龄组的稀疏性增加.
在PD和HC队列中,在不同年龄组之间发现了集群系数的显著差异,这表明网络拓学的年龄相关变化.

结论:

该UBNIN算法为个体大脑连接提供了一个独特的神经签名,适用于神经成像模式.
大脑网络连接模式显然随着年龄的增长而变化,这表明与年龄相关的网络退化和信息传输的改变.
这些发现突显了UBNIN在脑印应用和理解与衰老相关的神经病理变化的潜力.

关键词:

帕金森病是帕金森氏症的一种疾病.独特的大脑网络识别号码独特的大脑网络识别号码年龄的年龄年龄的年龄.大脑的连接性大脑的连接性聚类系数的聚类系数

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