计算机科学 ›› 2016, Vol. 43 ›› Issue (10): 317-321.doi: 10.11896/j.issn.1002-137X.2016.10.059
马士林,梅雪,李微微,周宇
MA Shi-lin, MEI Xue, LI Wei-wei and ZHOU Yu
摘要： 如何从复杂的fMRI数据中提取 丰富的大脑信息是提高脑部疾病识别精度的关键。传统的静息态功能磁共振成像分析中,功能连接网络被认为是稳定不变的。提出一种基于成组独立成分分析的构建动态功能连接网络的方法,并通过该网络来获取功能网络本身的动态特性。首先,利用成组独立成分分析法提取fMRI数据的空间独立成分作为网络节点,并通过滑动时间窗的方法获取窗口时间序列,构建动态功能连接网络。以动态功能网络作为特征,对精神分裂症患者和正常被试数据进行分类识别。实验结果表明,该方法能够获取fMRI数据的时间维度信息,提高识别效果,在一定程度上能为临床诊断提供客观参照。
| [1] Biswal M J,Mock B J,Sorenson J A.Functional connectivity in the motor cortex of resting human brain using echo-planar MRI[J].Magnetic Resonance in Medicine Official Journal of the Society of Magnetic Resonance in Medicine,1995,34(4):537-541 [2] Liu Guang-yao,Jiang Jian,Yang Xiao-ping,et al.Research Progress of Resting-state fMRI in Nerves and Mental Diseases [J].Progress in Modern Biomedicine,2012,12(35):6998-7000(in Chinese) 刘光耀,蒋健,杨晓萍,等.静息态fMRI在神经、精神类疾病中的研究进展[J].现代生物医学进展,2012,12(35):6998-7000 [3] Meda S A,Gill A,Stevens M C,et al.Differences in resting-state functional magnetic resonance imaging functional network connectivity between schizophrenia and psychotic bipolar probands and their unaffected first-degree relatives[J].Biological Psychiatry,2012,71(10):881-889 [4] Yang Yan-li.The Study of Functional Connectivity AnalysisMethods Based on Resting State fMRI [D].Taiyuan:Taiyuan University of Technology,2012(in Chinese)杨艳丽.基于静息态fMRI的功能连接分析方法研究[D].太原:太原理工大学,2012 [5] Price C J,Friston K J.Functional Imaging Studies of Neuropsychological Patients:Applications and Limitations[J].Neurocase,2002,8(5):345-354 [6] Chen Jun-jie,Li Hai-fang,Xiang Jie,et al.Human Connectome Research:Construction,Analysis and Application [J].Journal of Taiyuan University of Technology,2012,3(3):329-333(in Chinese) 陈俊杰,李海芳,相洁,等.脑网络组学构建分析及应用研究[J].太原理工大学学报,2012,3(3):329-333 [7] Zalesky A,Fornito A,Harding I H,et al.Whole-brain anatomical networks:does the choice of nodes matter?[J].Neuroi-mage,2010,50(3):970-983 [8] Allen E A,Erhardt E B,Wei Y,et al.Capturing inter-subjectvariability with group independent component analysis of fMRI data:a simulation study[J].Neuroimage,2012,59(4):4141-4159 [9] Yang Jian,Chen Shu-shen,Huangfu Hao-ran,et al.Dynamicfunctional connectivity of electroencephalogram in the resting state [J].Acta Physica Sinica,2015,64(5):374-383(in Chinese)杨剑,陈书燊,皇甫浩然,等.静息态脑电信号动态功能连接分析[J].物理学报,2015,64:58701-058701 [10] Smith S M,Miller K L,Salimi-Khorshidi G,et al.Network mo-delling methods for fMRI[J].Neuroimage,2011,54(2):875-891 [11] Hutchison R M,Womelsdorf T,Allen E A,et al.Dynamic functional connectivity:Promise,issues,and interpretations[J].NeuroImage,2013,80(1):360-378 [12] Allen E A,Damaraju F,Plis S M,et al.Tracking Whole-Brain Connectivity Dynamics in the Resting State [J].Cerebral Cortex,2014,24(3):663-676 [13] Calhoun V D,Adali T,Pearlson G,et al.A method for making group inferences from functional MRI data using independent component analysis[J].Human Brain Mapping,2001,14(3):140-151 [14] Leonardi N,Richiardi J,Gschwind M,et al.Principal compo-nents of functional connectivity:a new approach to study dynamic brain connectivity during rest [J].Neuroimage,2013,83(4):844-859 |
| No related articles found! |
|
||
首页