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在连续观看自然电影期间,将 EEG 源成像和 fMRI 进行整合。

Integration of EEG source imaging and fMRI during continuous viewing of natural movies.

机构信息

Max Planck Institute for Biological Cybernetics, Spemannstrasse 38, Tübingen, Germany.

出版信息

Magn Reson Imaging. 2010 Oct;28(8):1135-42. doi: 10.1016/j.mri.2010.03.042. Epub 2010 Jun 25.

Abstract

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are noninvasive neuroimaging tools which can be used to measure brain activity with excellent temporal and spatial resolution, respectively. By combining the neural and hemodynamic recordings from these modalities, we can gain better insight into how and where the brain processes complex stimuli, which may be especially useful in patients with different neural diseases. However, due to their vastly different spatial and temporal resolutions, the integration of EEG and fMRI recordings is not always straightforward. One fundamental obstacle has been that paradigms used for EEG experiments usually rely on event-related paradigms, while fMRI is not limited in this regard. Therefore, here we ask whether one can reliably localize stimulus-driven EEG activity using the continuously varying feature intensities occurring in natural movie stimuli presented over relatively long periods of time. Specifically, we asked whether stimulus-driven aspects in the EEG signal would be co-localized with the corresponding stimulus-driven BOLD signal during free viewing of a movie. Secondly, we wanted to integrate the EEG signal directly with the BOLD signal, by estimating the underlying impulse response function (IRF) that relates the BOLD signal to the underlying current density in the primary visual area (V1). We made sequential fMRI and 64-channel EEG recordings in seven subjects who passively watched 2-min-long segments of a James Bond movie. To analyze EEG data in this natural setting, we developed a method based on independent component analysis (ICA) to reject EEG artifacts due to blinks, subject movement, etc., in a way unbiased by human judgment. We then calculated the EEG source strength of this artifact-free data at each time point of the movie within the entire brain volume using low-resolution electromagnetic tomography (LORETA). This provided for every voxel in the brain (i.e., in 3D space) an estimate of the current density at every time point. We then carried out a correlation between the time series of visual contrast changes in the movie with that of EEG voxels. We found the most significant correlations in visual area V1, just as seen in previous fMRI studies (Bartels A, Zeki, S, Logothetis NK. Natural vision reveals regional specialization to local motion and to contrast-invariant, global flow in the human brain. Cereb Cortex 2008;18(3):705-717), but on the time scale of milliseconds rather than of seconds. To obtain an estimate of how the EEG signal relates to the BOLD signal, we calculated the IRF between the BOLD signal and the estimated current density in area V1. We found that this IRF was very similar to that observed using combined intracortical recordings and fMRI experiments in nonhuman primates. Taken together, these findings open a new approach to noninvasive mapping of the brain. It allows, firstly, the localization of feature-selective brain areas during natural viewing conditions with the temporal resolution of EEG. Secondly, it provides a tool to assess EEG/BOLD transfer functions during processing of more natural stimuli. This is especially useful in combined EEG/fMRI experiments, where one can now potentially study neural-hemodynamic relationships across the whole brain volume in a noninvasive manner.

摘要

脑电图(EEG)和功能磁共振成像(fMRI)是两种非侵入性的神经影像学工具,分别能够以优异的时间和空间分辨率测量大脑活动。通过结合这些模态的神经和血液动力学记录,我们可以更好地了解大脑如何以及在何处处理复杂刺激,这在患有不同神经疾病的患者中可能特别有用。然而,由于它们的空间和时间分辨率差异很大,EEG 和 fMRI 记录的整合并不总是那么简单。一个基本的障碍是,用于 EEG 实验的范式通常依赖于事件相关范式,而 fMRI 在这方面不受限制。因此,我们在这里询问是否可以使用在相对较长时间段内呈现的自然电影刺激中不断变化的特征强度,可靠地定位刺激驱动的 EEG 活动。具体来说,我们询问在观看电影时,是否可以将 EEG 信号中的刺激驱动方面与相应的刺激驱动 BOLD 信号进行共定位。其次,我们希望通过直接估计将 EEG 信号与初级视觉区域(V1)中的基础电流密度相关联的基础脉冲响应函数(IRF),将 EEG 信号与 BOLD 信号整合在一起。我们在七名受试者中进行了连续的 fMRI 和 64 通道 EEG 记录,这些受试者被动观看了 2 分钟长的詹姆斯邦德电影片段。为了在这种自然环境中分析 EEG 数据,我们开发了一种基于独立成分分析(ICA)的方法,以在不受人为判断影响的情况下,拒绝由于眨眼、受试者运动等引起的 EEG 伪影。然后,我们使用低分辨率电磁断层扫描(LORETA)在整个大脑体积内,在电影的每个时间点计算该无伪影数据的 EEG 源强度。这为大脑中的每个体素(即在 3D 空间中)提供了在每个时间点的电流密度的估计。然后,我们在电影中的视觉对比度变化的时间序列与 EEG 体素的时间序列之间进行了相关性分析。我们在视觉区域 V1 中发现了最显著的相关性,就像以前的 fMRI 研究一样(Bartels A、Zeki、S、Logothetis NK。自然视觉揭示了人类大脑中对局部运动和对比度不变的全局流的区域专业化。大脑皮层 2008 年;18(3):705-717),但在毫秒而不是秒的时间尺度上。为了获得 EEG 信号与 BOLD 信号之间关系的估计,我们计算了 BOLD 信号与 V1 区估计电流密度之间的 IRF。我们发现,该 IRF 与在非人类灵长类动物中使用联合皮层内记录和 fMRI 实验观察到的非常相似。总之,这些发现为无创性大脑映射开辟了新途径。它首先允许在自然观察条件下使用 EEG 的时间分辨率对特征选择的大脑区域进行定位。其次,它提供了一种工具来评估更自然刺激处理过程中的 EEG/BOLD 转移函数。这在 EEG/fMRI 联合实验中特别有用,在这种实验中,现在可以以非侵入性的方式在整个大脑体积中研究神经-血液动力学关系。

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