Kemik Kerem, Ada Emel, Çavuşoğlu Berrin, Aykaç Cansu, Savaş Derya Durusu Emek, Yener Görsev
Department of Neuroscience, Institute of Health Sciences, Dokuz Eylül University, Izmir, Turkey.
Department of Radiology, Dokuz Eylül University Medicine Faculty, Izmir, Turkey.
Brain Behav. 2024 May;14(5):e3518. doi: 10.1002/brb3.3518.
The objective of this study was to investigate the functional changes associated with mild cognitive impairment (MCI) using independent component analysis (ICA) with the word generation task functional magnetic resonance imaging (fMRI) and resting-state fMRI.
In this study 17 patients with MCI and age and education-matched 17 healthy individuals as control group are investigated. All participants underwent resting-state fMRI and task-based fMRI while performing the word generation task. ICA was used to identify the appropriate independent components (ICs) and their associated networks. The Dice Coefficient method was used to determine the relevance of the ICs to the networks of interest.
IC-14 was found relevant to language network in both resting-state and task-based fMRI, IC-4 to visual, and IC-28 to dorsal attention network (DAN) in word generation task-based fMRI by Sorento-Dice Coefficient. ICA showed increased activation in language network, which had a larger voxel size in resting-state functional MRI than word generation task-based fMRI in the bilateral lingual gyrus. Right temporo-occipital fusiform cortex, right hippocampus, and right thalamus were also activated in the task-based fMRI. Decreased activation was found in DAN and visual network MCI patients in word generation task-based fMRI.
Task-based fMRI and ICA are more sophisticated and reliable tools in evaluation cognitive impairments in language processing. Our findings support the neural mechanisms of the cognitive impairments in MCI.
本研究的目的是使用独立成分分析（ICA）结合单词生成任务功能磁共振成像（fMRI）和静息态fMRI来研究与轻度认知障碍（MCI）相关的功能变化。
本研究纳入了17例MCI患者，并以年龄和教育程度相匹配的17名健康个体作为对照组。所有参与者在进行单词生成任务时均接受了静息态fMRI和基于任务的fMRI检查。使用ICA来识别合适的独立成分（IC）及其相关网络。采用骰子系数法来确定IC与感兴趣网络的相关性。
通过索伦托 - 骰子系数发现，在静息态和基于任务的fMRI中，IC - 14与语言网络相关，IC - 4与视觉相关，在基于单词生成任务的fMRI中，IC - 28与背侧注意网络（DAN）相关。ICA显示语言网络激活增加，在双侧舌回中，静息态功能磁共振成像中的体素大小比基于单词生成任务的fMRI更大。在基于任务的fMRI中，右侧颞枕梭状回、右侧海马体和右侧丘脑也被激活。在基于单词生成任务的fMRI中，发现MCI患者的DAN和视觉网络激活减少。
基于任务的fMRI和ICA是评估语言处理中认知障碍更复杂且可靠的工具。我们的研究结果支持了MCI中认知障碍的神经机制。
