School of Psychology and Neuroscience, University of St Andrews, St Andrews, UK.
Hum Brain Mapp. 2023 Apr 1;44(5):1846-1861. doi: 10.1002/hbm.26188. Epub 2023 Jan 18.
Electroencephalography (EEG) is a common and inexpensive method to record neural activity in humans. However, it lacks spatial resolution making it difficult to determine which areas of the brain are responsible for the observed EEG response. Here we present a new easy-to-use method that relies on EEG topographical templates. Using MRI and fMRI scans of 50 participants, we simulated how the activity in each visual area appears on the scalp and averaged this signal to produce functionally defined EEG templates. Once created, these templates can be used to estimate how much each visual area contributes to the observed EEG activity. We tested this method on extensive simulations and on real data. The proposed procedure is as good as bespoke individual source localization methods, robust to a wide range of factors, and has several strengths. First, because it does not rely on individual brain scans, it is inexpensive and can be used on any EEG data set, past or present. Second, the results are readily interpretable in terms of functional brain regions and can be compared across neuroimaging techniques. Finally, this method is easy to understand, simple to use and expandable to other brain sources.
脑电图(EEG)是一种常用且廉价的记录人类神经活动的方法。然而,它的空间分辨率较低,因此很难确定大脑的哪些区域负责观察到的 EEG 反应。在这里,我们提出了一种新的、易于使用的方法,该方法依赖于 EEG 地形图模板。我们使用 50 名参与者的 MRI 和 fMRI 扫描,模拟了每个视觉区域的活动在头皮上的表现方式,并对该信号进行平均处理,以生成功能定义的 EEG 模板。创建后,这些模板可用于估计观察到的 EEG 活动中每个视觉区域的贡献程度。我们在广泛的模拟和真实数据上测试了该方法。该方法与定制的个体源定位方法一样好,对各种因素具有鲁棒性,并且具有多个优势。首先,由于它不依赖于个体的脑部扫描,因此价格低廉,可用于过去或现在的任何 EEG 数据集。其次,结果可以根据功能脑区进行解释,并可以在不同的神经影像学技术之间进行比较。最后,该方法易于理解,使用简单,并且可以扩展到其他脑源。