基于fMRI的大鼠脑功能网络连接研究
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摘要
功能磁共振(functional magnetic resonance imaging, fMRI)是一种描述伴随大脑神经活动的血氧变化的成像方法。目前,fMRI研究中一个重要的领域是研究静息状态下大脑的连接情况。
本文利用fMRI对大鼠的脑网络进行研究,主要工作如下:
1、前爪刺激大鼠的脑功能定位的研究。利用独立成分分析(independent components analysis,ICA)方法对前爪刺激大鼠的fMRI数据进行分析,获得相应的激活区域,从而进行脑功能定位。结果发现,大鼠前爪刺激时刺激对侧的第一躯体感觉皮层(primary somatosensory cortex,S1)和丘脑有较强的正激活,双侧尾状壳核(CPu)有较强的负激活,其中有3例大鼠第二躯体感觉皮层(secondary somatosensory cortex,S2)区检测到了正激活;刺激同侧的S1区和丘脑没有观察到明显的BOLD响应,表明上述区域与感觉系统相关。
2、感觉运动系统静息态和刺激状态的脑网络研究。结合上述激活区域和大鼠脑立体定位图谱,选出感兴趣的脑区,利用相关分析方法计算出区域之间的相关系数矩阵,进而构建网络并探讨大鼠感觉运动系统的脑网络属性。结果发现,大鼠在静息状态时感觉运动皮层内部之间的连接性较强,且左右半球感觉运动皮层之间存在较强的同步低频振荡。此外,丘脑核团之间、左右半球的尾状壳核、海马和扣带回之间的连通性也较明显,而感觉运动皮层与丘脑核团之间的连接较弱。值得关注的是,在静息状态发现大鼠感觉运动系统呈现了较为明显的偏侧性。与静息态相比,刺激状态下脑区之间的整体连通性明显降低。感觉运动系统在静息态时的脑网络具有小世界属性,而在前爪刺激时更偏向于随机网络。可以推测大鼠在脑信息处理中的功能分离和整合可能与人类存在某些相似性。
Functional magnetic resonance imaging (fMRI) is an imaging technology based on the blood oxygenation change during neural activity. At present, the investigation of the brain connectivity during resting state has been an important field using fMRI techniques.
This paper focused on the study of connectivity of the rat brain based on fMRI. Some aspects of this dissertation have been put forward:
1. Study of the brain activation of forepaw stimulation rat. Independent components analysis (ICA) was employed to analyze forepaw stimulation fMRI data, and the activation regions were found. The results showed during forepaw stimulation, the primary somatosensory cortex (S1) and thalamus were significant positively activated, the CPu(caudate putamen nucleus) was significant negatively activated. There were three rats showed positive activation in the secondary somatosensory cortex (S2), and no significant BOLD response in S1 and thalamus of the same hemisphere, which meant these regions were related to somatosensory system.
2. Study of the connectivity of brain inside motor-sensory system during resting state and stimulus state. Based on the rat brain in stereotaxic coordinates and the activation regions mentioned above, regions of interest (ROI) were selected. We used correlation analysis method to find the correlation coefficient matrix between regions, and build the network to explore the brain network properties of rat’s motor-sensory system. The results showed that during the resting state, the strong intracotical connectivity and LFF between bilateral hemisphere motor-sensory cortex were found. Besides, the significant connectivity between bilateral hemisphere putamen, hippocampus and cingulate was found, but the connectivity was weak intrathalamic and between cortex and thalamic. It’s interesting that the motor-sensory system showed significant hemisphere predominance during resting state. Comparing to resting state, the global connectivity between brain regions decreased during stimulus state. The brain network of motor-sensory system showed small-world property during resting state, but random network during forepaw stimulation. It suggested that rat has some similar properties to human in functional separation and integration during brain information processing.
本文利用fMRI对大鼠的脑网络进行研究,主要工作如下:
1、前爪刺激大鼠的脑功能定位的研究。利用独立成分分析(independent components analysis,ICA)方法对前爪刺激大鼠的fMRI数据进行分析,获得相应的激活区域,从而进行脑功能定位。结果发现,大鼠前爪刺激时刺激对侧的第一躯体感觉皮层(primary somatosensory cortex,S1)和丘脑有较强的正激活,双侧尾状壳核(CPu)有较强的负激活,其中有3例大鼠第二躯体感觉皮层(secondary somatosensory cortex,S2)区检测到了正激活;刺激同侧的S1区和丘脑没有观察到明显的BOLD响应,表明上述区域与感觉系统相关。
2、感觉运动系统静息态和刺激状态的脑网络研究。结合上述激活区域和大鼠脑立体定位图谱,选出感兴趣的脑区,利用相关分析方法计算出区域之间的相关系数矩阵,进而构建网络并探讨大鼠感觉运动系统的脑网络属性。结果发现,大鼠在静息状态时感觉运动皮层内部之间的连接性较强,且左右半球感觉运动皮层之间存在较强的同步低频振荡。此外,丘脑核团之间、左右半球的尾状壳核、海马和扣带回之间的连通性也较明显,而感觉运动皮层与丘脑核团之间的连接较弱。值得关注的是,在静息状态发现大鼠感觉运动系统呈现了较为明显的偏侧性。与静息态相比,刺激状态下脑区之间的整体连通性明显降低。感觉运动系统在静息态时的脑网络具有小世界属性,而在前爪刺激时更偏向于随机网络。可以推测大鼠在脑信息处理中的功能分离和整合可能与人类存在某些相似性。
Functional magnetic resonance imaging (fMRI) is an imaging technology based on the blood oxygenation change during neural activity. At present, the investigation of the brain connectivity during resting state has been an important field using fMRI techniques.
This paper focused on the study of connectivity of the rat brain based on fMRI. Some aspects of this dissertation have been put forward:
1. Study of the brain activation of forepaw stimulation rat. Independent components analysis (ICA) was employed to analyze forepaw stimulation fMRI data, and the activation regions were found. The results showed during forepaw stimulation, the primary somatosensory cortex (S1) and thalamus were significant positively activated, the CPu(caudate putamen nucleus) was significant negatively activated. There were three rats showed positive activation in the secondary somatosensory cortex (S2), and no significant BOLD response in S1 and thalamus of the same hemisphere, which meant these regions were related to somatosensory system.
2. Study of the connectivity of brain inside motor-sensory system during resting state and stimulus state. Based on the rat brain in stereotaxic coordinates and the activation regions mentioned above, regions of interest (ROI) were selected. We used correlation analysis method to find the correlation coefficient matrix between regions, and build the network to explore the brain network properties of rat’s motor-sensory system. The results showed that during the resting state, the strong intracotical connectivity and LFF between bilateral hemisphere motor-sensory cortex were found. Besides, the significant connectivity between bilateral hemisphere putamen, hippocampus and cingulate was found, but the connectivity was weak intrathalamic and between cortex and thalamic. It’s interesting that the motor-sensory system showed significant hemisphere predominance during resting state. Comparing to resting state, the global connectivity between brain regions decreased during stimulus state. The brain network of motor-sensory system showed small-world property during resting state, but random network during forepaw stimulation. It suggested that rat has some similar properties to human in functional separation and integration during brain information processing.
引文
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[2] Pauling L and Coryell C D. The Magnetic Properties and Structure of Hemoglobin, Oxyhemoglobin and Carbonmonoxyhemoglobin . Proc Natl Acad Sci , 1936b ,22:210.
[3] Thulborn R A. Speeds and gaits of dinosaurs. Palaeogeogr. Palaeoclimatol. Palaeoecol, 1982, 38:227-256.
[4] Gelnar P A, Krauss B R, Sheehe P R, et al. A comparative fMRI study of cortical representations for thermal painful, vibrotactile, and motor performance tasks. Neuroimage, 1999,10(4): 460-482.
[5] Cordes D, Haughton V M, Arfanakis K, et al. Mapping functionally related regions of brain with functional connectivity MR imaging. AJNR Am J Neuroradiol, 2000,21(9): 1636-1644.
[6] Lowe M J, Mock B J, and Sorenson J A. Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations. Neuroimage, 1998,7(2): 119-132.
[7] Sporns O and Zwi J. The small world of the cerebral cortex. Neuroinformatics, 2004 ,2:145-162.
[8] Sporns, O. Small-world connectivity, motif composition, and complexity of fractal neuronal connections. BioSystems, 2006, 85: 55-64.
[9] Friston K J. Functional and Effective Connectivity in Neuroimaging: A Synthesis[J]. Human Brain Mapping, 1994 ,2: 56-78.
[10] Sokoloff L, Wechsler RL, Mangold R, et al . Cerebral blood flow and oxygen consumption in hyperthyroidism before and after treatment. J Clin Invest, 1953,32(3):202-208.
[11] Raichle M E , MacLeod A M , Snyder A Z , et al . A default mode of brain function . Proc Natl Acad Sci , 2001,98 (2) :676-682.
[12] Biswal B, Yetkin F Z, Haughton V M, et al. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med, 1995,34(4): 537-541.
[13] Ogawa, S, Lee T M. Kay A R, et al. Brain magnetic resonance imaging with contrast dependent on blood oxygenation. Proc Natl Acad Sci , 1990,87(24): 9868-9872.
[14] Cordes D, Haughton V M, Arfanakis K, et al. Frequencies contributing to functional connectivity in the cerebral cortex in "resting-state" data. AJNR Am J Neuroradiol, 2001,22(7): 1326-1333.
[15] Kruger G and Glover G H. Physiological noise in oxygenation-sensitive magnetic resonance imaging. Magn Reson Med, 2001,46(4): 631-637.
[16] Biswal B B, Van Kylen, J and Hyde J S. Simultaneous assessment of flow and BOLD signals in resting-state functional connectivity maps. NMR Biomed, 1997, 10(4-5): 165-170.
[17] Kiviniemi V, Ruohonen J and Tervonen O. Separation of physiological very low frequency fluctuation from aliasing by switched sampling interval fMRI scans. Magn Reson Imaging, 2005,23(1): 41-46.
[18] Friston K J, Frith C D, Liddle P F, et al. Functional connectivity: the principal-component analysis of large (PET) data sets. J Cereb Blood Flow Metab, 1993,13(1): 5-14.
[19] Mitra P P, Ofawa S, Hu X P, et al. The nature of spatiotemporal changes in cerebral hemodynamics as manifested in functional magnetic resonance imaging. Magn Reson Med, 1997,37(4): 511-518.
[20] Wada Y, Nanbu Y, Jiang Z Y, et al. Interhemispheric EEG coherence in never-medicated patients with paranoid schizophrenia: analysis at rest and during photic stimulation. Clin Electroencephalogr, 1998,29(4):p. 170-176.
[21] Peltier S J, Kerssens C, Humann S B, et al. Functional connectivity changes with concentration of sevoflurane anesthesia. Neuroreport, 2005,16(3): 285-288.
[22] Greicius M D, Krasnow B, Reiss A L, et al. Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc Natl Acad Sci, 2003,100(1): 253-258.
[23] De Luca M., Beckmann C F, De Stefano N, et al. fMRI resting state networks define distinct modes of long-distance interactions in the human brain. Neuroimage, 2006,29(4): 1359-67.
[24] Vincent J L , Patel G H , Fox M D , et al. Intrinsic functional architecture in the anaesthetized monkey brain . Nature, 2007,447 (7140):83-86.
[25] Kennedy D P and Courchesne E. The intrinsic functional organization of the brain is altered in autism. Neuroimage, 2008, 39 (4):1877-1885.
[26] Bluhm R L , Miller J , Lanius R A , et al. Spontaneous low frequency fluctuations in the BOLD signal in schizophrenic patient s: anomalies in the default network. Schizophr Bull, 2007,33(4) :1004-1012.
[27] Buckner R L , Andrews Hanna J R and Schacter D L. The brain’s default network: anatomy, function , and relevance to disease. Ann NY Acad Sci, 2008,1124 :1-38.
[28] Damoiseaux J S, Rombouts S A , Barkhof F , et al. Consistent resting state networks across healthy subject s[J ] . Proc Natl Acad Sci , 2006,103(37) :13 848-853.
[29] Salvador R, Suckling J, Coleman M R , et al . Neuro-physiological architecture of functional magnetic resonance images of human brain. Cereb Cortex , 2005,15 (9) :1332-1342.
[30] Kiviniemi V. Low Frequency BOLD Fluctuations and Brain Functional Connectivity. in ISMRM. Seattle. 2006.
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