A Graph-Based Statistical Approach to Identifying Functional Connectivity Networks in Patients with Traumatic Brain Injury.

IF 0.8 Q4 CLINICAL NEUROLOGY
Iranian Journal of Child Neurology Pub Date : 2025-01-01 Epub Date: 2025-01-07 DOI:10.22037/ijcn.v19i1.44921
Samaneh Talebi, Fatemeh Pourmotahari, Keyvan Olazadeh, Hamid Alavi Majd, Seyyed Mohammad Tabatabaei
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引用次数: 0

Abstract

Objectives: Traumatic brain injury (TBI) is one of the most common types of brain injuries associated with cognitive impairments. Functional magnetic resonance imaging (fMRI) studies can provide a unique opportunity to examine brain connectivity patterns and understand the neural substrates of cognitive outcomes following traumatic injury. Therefore, this study aims to determine changes in functional connectivity patterns in patients with TBI compared to healthy individuals using two graph models, adaptive dense subgraph discovery (ADSD) and variance component.

Materials & methods: This study used fMRI data downloaded from https://openneuro.org. These data included 14 patients with TBI aged between 18 and 36 and 12 healthy individuals (female: N=6, male: N=6) aged between 19 and 52. Out of the 74 regions examined, a cluster of 18 regions related to TBI was identified using the ADSD model. Subsequently, these identified regions were used as input for the variance component model to investigate changes in connectivity patterns.

Results: Functional connectivity between an 18-brain region cluster, such as the Rectus (Left, Right), Supp_Motor_Area (Left, Right), and Middle Cingulum (Left, Right), differed between the patient and healthy groups. Based on the analysis of functional connectivity between pairs of brain regions, 153 connections between pairs of brain regions were compared in the two groups, out of which 63 connections showed significant differences between the two groups. Compared to other regions, Supp_Motor_Area_Right and Rectus_Left had more connections.

Conclusion: The study's results indicate that the functional connectivity between the Cingulum, Hippocampus, Fusiform, Supp_Motor_Area, and Precentral regions differs between the two groups. Since these regions are involved in processes such as memory, learning, spatial orientation, face recognition, coordination, and motor control, changes in their functional connectivity may lead to impairments in these areas.

基于图的统计方法识别创伤性脑损伤患者的功能连接网络。
目的:创伤性脑损伤(TBI)是与认知障碍相关的最常见的脑损伤类型之一。功能磁共振成像(fMRI)研究可以提供一个独特的机会来检查大脑连接模式,并了解创伤性损伤后认知结果的神经基质。因此,本研究旨在通过自适应密集子图发现(ADSD)和方差成分两种图模型来确定TBI患者与健康个体相比功能连接模式的变化。材料与方法:本研究使用从https://openneuro.org下载的fMRI数据。这些数据包括14例18 - 36岁的TBI患者和12例19 - 52岁的健康个体(女性:N=6,男性:N=6)。在研究的74个区域中,使用ADSD模型确定了18个与TBI相关的区域。随后,这些已识别的区域被用作方差成分模型的输入,以研究连接模式的变化。结果:18个脑区群,如直肌(左、右)、辅助运动区(左、右)和中扣带(左、右)之间的功能连通性在患者和健康组之间存在差异。通过对脑区对间功能连通性的分析,比较了两组脑区对间的153个连接,其中有63个连接在两组间表现出显著差异。相比其他区域,Supp_Motor_Area_Right和Rectus_Left有更多的连接。结论:两组脑带、海马、梭状回、运动辅助区和中央前区之间的功能连通性存在差异。由于这些区域涉及记忆、学习、空间定位、面部识别、协调和运动控制等过程,因此它们功能连通性的变化可能导致这些区域的损伤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.40
自引率
0.00%
发文量
35
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