脑活动和连通性的电生理学成像——挑战与机遇。
Electrophysiological imaging of brain activity and connectivity-challenges and opportunities.
机构信息
Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, USA.
出版信息
IEEE Trans Biomed Eng. 2011 Jul;58(7):1918-31. doi: 10.1109/TBME.2011.2139210. Epub 2011 Apr 7.
Abstract
Unlocking the dynamic inner workings of the brain continues to remain a grand challenge of the 21st century. To this end, functional neuroimaging modalities represent an outstanding approach to better understand the mechanisms of both normal and abnormal brain functions. The ability to image brain function with ever increasing spatial and temporal resolution has made a significant leap over the past several decades. Further delineation of functional networks could lead to improved understanding of brain function in both normal and diseased states. This paper reviews recent advancements and current challenges in dynamic functional neuroimaging techniques, including electrophysiological source imaging, multimodal neuroimaging integrating fMRI with EEG/MEG, and functional connectivity imaging.
摘要
探索大脑的动态内部运作仍然是 21 世纪的重大挑战。为此，功能神经影像学方法是更好地理解正常和异常大脑功能机制的杰出途径。在过去几十年中，功能成像技术在提高空间和时间分辨率方面取得了重大飞跃。进一步描绘功能网络可以促进对正常和疾病状态下大脑功能的理解。本文综述了动态功能神经影像学技术的最新进展和当前挑战，包括电生理源成像、将 fMRI 与 EEG/MEG 相结合的多模态神经影像学以及功能连接成像。
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本文引用的文献
1
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J Cogn Neurosci. 1993 Spring;5(2):162-76. doi: 10.1162/jocn.1993.5.2.162.
2
EEG microstate sequences in healthy humans at rest reveal scale-free dynamics.健康人体在休息时的 EEG 微观状态序列揭示了无标度动力学。
Proc Natl Acad Sci U S A. 2010 Oct 19;107(42):18179-84. doi: 10.1073/pnas.1007841107. Epub 2010 Oct 4.
3
Noninvasive cortical imaging of epileptiform activities from interictal spikes in pediatric patients.儿童患者发作间期棘波的无创性皮质成像显示癫痫样活动。
Neuroimage. 2011 Jan 1;54(1):244-52. doi: 10.1016/j.neuroimage.2010.07.026. Epub 2010 Jul 17.
4
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5
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6
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7
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