同时记录电生理数据和磁共振成像的最新进展。

Recent advances in recording electrophysiological data simultaneously with magnetic resonance imaging.

作者信息

Laufs H, Daunizeau J, Carmichael D W, Kleinschmidt A

机构信息

Johann Wolfgang Goethe-Universität, Zentrum der Neurologie und Neurochirurgie, Klinik für Neurologie, Theodor-Stern-Kai 7, 60590 Frankfurt am Main, Germany; Department of Neurology and Brain Imaging Center, Johann Wolfgang Goethe-University, Frankfurt am Main, Germany; Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, Queen Square, London, UK.

Wellcome Trust Centre for Neuroimaging, 12 Queen Square, London, UK.

出版信息

Neuroimage. 2008 Apr 1;40(2):515-528. doi: 10.1016/j.neuroimage.2007.11.039. Epub 2007 Dec 7.

Abstract

Simultaneous recording of brain activity by different neurophysiological modalities can yield insights that reach beyond those obtained by each technique individually, even when compared to those from the post-hoc integration of results from each technique recorded sequentially. Success in the endeavour of real-time multimodal experiments requires special hardware and software as well as purpose-tailored experimental design and analysis strategies. Here, we review the key methodological issues in recording electrophysiological data in humans simultaneously with magnetic resonance imaging (MRI), focusing on recent technical and analytical advances in the field. Examples are derived from simultaneous electroencephalography (EEG) and electromyography (EMG) during functional MRI in cognitive and systems neuroscience as well as in clinical neurology, in particular in epilepsy and movement disorders. We conclude with an outlook on current and future efforts to achieve true integration of electrical and haemodynamic measures of neuronal activity using data fusion models.

摘要

通过不同神经生理学方法同时记录大脑活动,即使与依次记录的每种技术的事后结果整合相比,也能产生超越每种技术单独获得的见解。实时多模态实验的成功需要特殊的硬件和软件,以及量身定制的实验设计和分析策略。在这里,我们回顾了在人类中同时进行磁共振成像(MRI)记录电生理数据的关键方法学问题,重点关注该领域最近的技术和分析进展。实例来自认知和系统神经科学以及临床神经病学(特别是癫痫和运动障碍)的功能MRI期间的同步脑电图(EEG)和肌电图(EMG)。我们最后展望了利用数据融合模型实现神经元活动的电学和血液动力学测量真正整合的当前和未来努力。

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