Ebrahiminia Fatemeh, Cichy Radoslaw Martin, Khaligh-Razavi Seyed-Mahdi
Department of Stem Cells and Developmental Biology, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, Academic Center for Education, Culture and Research (ACECR), Tehran, Iran.
School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran.
Front Neurosci. 2022 Oct 18;16:983602. doi: 10.3389/fnins.2022.983602. eCollection 2022.
Today, most neurocognitive studies in humans employ the non-invasive neuroimaging techniques functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG). However, how the data provided by fMRI and EEG relate exactly to the underlying neural activity remains incompletely understood. Here, we aimed to understand the relation between EEG and fMRI data at the level of neural population codes using multivariate pattern analysis. In particular, we assessed whether this relation is affected when we change stimuli or introduce identity-preserving variations to them. For this, we recorded EEG and fMRI data separately from 21 healthy participants while participants viewed everyday objects in different viewing conditions, and then related the data to electrocorticogram (ECoG) data recorded for the same stimulus set from epileptic patients. The comparison of EEG and ECoG data showed that object category signals emerge swiftly in the visual system and can be detected by both EEG and ECoG at similar temporal delays after stimulus onset. The correlation between EEG and ECoG was reduced when object representations tolerant to changes in scale and orientation were considered. The comparison of fMRI and ECoG overall revealed a tighter relationship in occipital than in temporal regions, related to differences in fMRI signal-to-noise ratio. Together, our results reveal a complex relationship between fMRI, EEG, and ECoG signals at the level of population codes that critically depends on the time point after stimulus onset, the region investigated, and the visual contents used.
如今，大多数针对人类的神经认知研究都采用非侵入性神经成像技术，即功能磁共振成像（fMRI）和脑电图（EEG）。然而，fMRI和EEG所提供的数据究竟如何与潜在的神经活动相关，目前仍未完全明确。在此，我们旨在通过多变量模式分析，在神经群体编码层面理解EEG与fMRI数据之间的关系。具体而言，我们评估了在改变刺激或对其引入保持特征不变的变化时，这种关系是否会受到影响。为此，我们在21名健康参与者观看处于不同观看条件下的日常物品时，分别记录了他们的EEG和fMRI数据，然后将这些数据与从癫痫患者针对相同刺激集记录的皮质电图（ECoG）数据相关联。EEG与ECoG数据的比较表明，物体类别信号在视觉系统中迅速出现，并且在刺激开始后的相似时间延迟下，EEG和ECoG都能检测到。当考虑对尺度和方向变化具有耐受性的物体表征时，则EEG与ECoG之间的相关性降低。fMRI与ECoG的比较总体上显示，枕叶区域的关系比颞叶区域更紧密，这与fMRI信噪比的差异有关。综合来看，我们的结果揭示了在群体编码层面，fMRI、EEG和ECoG信号之间存在复杂的关系，这种关系关键取决于刺激开始后的时间点、所研究的区域以及所使用的视觉内容。
