人脑对握力刺激响应特征的数值计算分析方法

doi:10.3969/j.issn.0258-8021. 2014.03.02

摘要
图/表
参考文献
相关文章 (1)

全文: PDF (1608 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要为研究人脑对握力刺激的响应特征，提出一种新的数值计算分析方法：结合独立成分分析和云模型，对握力刺激脑响应特征进行数值计算。采集10名健康受试者不同握力任务下的功能磁共振（fMRI）数据并进行预处理，应用独立成分分析获取不同握力刺激条件下的脑激活区域位置和大小，然后通过云模型计算脑激活区域内的数据分布特征。结果表明,握力刺激的脑激活区域主要分布在对侧大脑Brodmann 2、3、4、6区和同侧小脑，并且随着握力强度的增加，中央前回、中央后回等激活区域增大(激活簇体素个数分别为4 075、4 218、4 965)；在不同握力刺激条件下,激活区域的任务态与非任务态间的期望、熵、超熵（Ex、En、He）均有明显的统计学差异，Ex（P<0001）和En(P<0.005)增大，He(P<0.005)减小；不同握力刺激间三个参数的差异不明显，并且非激活区域内任务状态与非任务状态间的期望、熵、超熵均无统计学差异。该方法可为不同任务下大脑激活区域的数据分布特征研究提供一种新的分析手段。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	程思佳景斌李海云^#*

关键词 ：握力刺激, 功能磁共振, 独立成分分析, 云模型

Abstract：In order to investigate the characteristics of human brain's responses to different gripping force tests, we proposed a novel numerical approach, combining the independent component analysis (ICA) and the cloud model. Firstly, we obtained ten subjects' fMRI image data from MRI scanner under different experimental conditions, and preprocessed those fMRI raw data, then the ICA was used to determine the brain active regions of different tasks, and the cloud model was applied to explore the numerical distribution characteristics of the activated voxels in activated regions under different grip force tests. The results showed that the activated regions mainly located at the contralateral cerebrum such as Brodmann area 2, 3, 4, 6 and ipsilateral cerebellum, and with the increasement of grip force, the number of the activated voxels in precentral gyrus and postcentral gyrus increased (cluster size: 4 075, 4 218, 4 965). In the activated region, the characteristic parameters of cloud model such as expectation, entropy, hyperentropy (Ex, En, He) showed significant differences between task state and control state of different force conditions. The Ex (P<0.001) and En (P<0.005) were significantly increased while the He (P<0.005) was significantly decreased. But these parameters had no significant differences between different force conditions. In the unactivated region, the Ex、En、He had no significant differences between task and control state. The proposed method can be used to investigate the numerical distribution characteristics of brain's response to different tasks in future.

Key words： grip force test functional magnetic resonance imaging (fMRI) independent component analysis(ICA) cloud model

基金资助:北京市自然科学基金（4122018）；首都医科大学基础-临床科研合作基金(13JL49）；首都医科大学基础临床科研合作基金（13JL04)

引用本文:

程思佳景斌李海云^#*. 人脑对握力刺激响应特征的数值计算分析方法[J]. 中国生物医学工程学报, 2014, 33(3): 266-273.
CHENG Si Jia JING Bin LI Hai Yun ^#*. A Numerical Approach to Calculation and Analysis of Characteristics of Brain Functional Response to Grip Test. journal1, 2014, 33(3): 266-273.

链接本文:

http://cjbme.csbme.org/CN/10.3969/j.issn.0258-8021. 2014.03.02 或 http://cjbme.csbme.org/CN/Y2014/V33/I3/266

［1］Yousry TA, Schmid UD, Jassoy AG, et al. Topography of the cortical motor hand area: prospective study with functional MR imaging and direct motor mapping at surgery［J］. Radiology, 1995, 195(1): 23-29.
［2］钟士江，陈静,包春雨，等.功能磁共振成像对正常人脑手运动皮质的定位研究［J］. 武警后勤学院学报(医学版), 2012, 21(11): 851-855.
［3］Coynel D, Marrelec G, Perlbarg V, et al. Dynamics of motorrelated functional integration during motor sequence learning［J］. NeuroImage, 2010, 49(1): 759-766.
［4］Boudrias M, Gonalves CS, Penny WD, et al. Agerelated changes in causal interactions between cortical motor regions during hand grip［J］. NeuroImage, 2012, 59(4): 3398-3405.
［5］Pope P, Wing AM, Praamstra P, et al. Force related activations in rhythmic sequence production［J］. NeuroImage, 2005, 27(4): 909-918.
［6］Jncke L, Specht K, Mirzazade S, et al. A parametric analysis of the ‘rate effect’ in the sensorimotor cortex: a functional magnetic resonance imaging analysis in human subjects［J］. Neuroscience Letters, 1998, 252(1): 37-40.
［7］Jncke L, Peters M, Schlaug G, et al. Differential magnetic resonance signal change in human sensorimotor cortex to finger movements of different rate of the dominant and subdominant hand［J］. Cognitive Brain Research, 1998, 6(4): 279-284.
［8］Lutz K, Koeneke S, Wüstenberg T, et al. Asymmetry of cortical activation during maximum and convenient tapping speed［J］. Neuroscience Letters, 2004, 373(1): 61-66.
［9］Pope P, Wing AM, Praamstra P, et al. Force related activations in rhythmic sequence production［J］. NeuroImage, 2005, 27(4): 909-918.
［10］Noble JW, Eng JJ, Kokotilo KJ, et al. Aging effects on the control of grip force magnitude: An fMRI study［J］. Experimental Gerontology, 2011, 46(6): 453-461.
［11］Mckeown MJ, Makeig S, Brown GG, et al. Analysis of fMRI data by blind separation into independent spatial components［J］. Hum Brain Mapp, 1998, 6(3): 160-188.
［12］Calhoun VD, Adali T, Mcginty VB, et al. fMRI activation in a visualperception task: network of areas detected using the general linear model and independent components analysis［J］. NeuroImage, 2001, 14(5): 1080-1088.
［13］李德毅，孟海军，史雪梅. 隶属云和隶属云发生器［J］. 计算机研究与发展, 1995, 32(6): 15-20.
［14］GonzalezCastillo J, Talavage TM. Reproducibility of fMRI activations associated with auditory sentence comprehension［J］. NeuroImage, 2011, 54(3): 2138-2155.
［15］刘常昱，冯芒，戴晓军，等. 基于云 X 信息的逆向云新算法［J］. 系统仿真学报, 2004, 16 (11): 2417-2420.
［16］Zhao Jing, Li Haiyun. An image fusion algorithm based on multiresolution decomposition for functional magnetic resonance images［J］. Neuroscience Letters, 2011, 487(1): 73-77.
［17］Eickhoff SB, Grefkes C. Approaches for the integrated analysis of structure, function and connectivity of the human brain［J］. Clin EEG Neurosci, 2011, 42(2): 107-121.