Aston University, Birmingham, UK.
J Cogn Neurosci. 2018 Mar;30(3):338-352. doi: 10.1162/jocn_a_01209. Epub 2017 Nov 21.
Various neuroimaging and neurophysiological methods have been used to examine neural activation patterns in response to faces. However, much of previous research has relied on static images of faces, which do not allow a complete description of the temporal structure of face-specific neural activities to be made. More recently, insights are emerging from fMRI studies about the neural substrates that underpin our perception of naturalistic dynamic face stimuli, but the temporal and spectral oscillatory activity associated with processing dynamic faces has yet to be fully characterized. Here, we used MEG and beamformer source localization to examine the spatiotemporal profile of neurophysiological oscillatory activity in response to dynamic faces. Source analysis revealed a number of regions showing enhanced activation in response to dynamic relative to static faces in the distributed face network, which were spatially coincident with regions that were previously identified with fMRI. Furthermore, our results demonstrate that perception of realistic dynamic facial stimuli activates a distributed neural network at varying time points facilitated by modulations in low-frequency power within alpha and beta frequency ranges (8-30 Hz). Naturalistic dynamic face stimuli may provide a better means of representing the complex nature of perceiving facial expressions in the real world, and neural oscillatory activity can provide additional insights into the associated neural processes.
各种神经影像学和神经生理学方法已被用于研究对人脸的神经激活模式。然而,之前的大部分研究都依赖于人脸的静态图像,这些图像无法完整描述与人脸相关的神经活动的时间结构。最近,fMRI 研究揭示了与我们对自然动态人脸刺激的感知相关的神经基质的一些见解,但与处理动态人脸相关的时频谱段振荡活动尚未得到充分描述。在这里,我们使用 MEG 和波束形成器源定位来研究动态人脸刺激反应的神经生理振荡活动的时空特征。源分析揭示了在分布式人脸网络中,与静态人脸相比,动态人脸会引起多个区域的激活增强,这些区域与之前通过 fMRI 确定的区域在空间上是一致的。此外,我们的结果表明,感知逼真的动态面部刺激会在不同的时间点激活一个分布式神经网络,这是由 alpha 和 beta 频段(8-30Hz)内低频功率的调制所促进的。自然动态人脸刺激可能为在现实世界中更有效地表现感知面部表情的复杂性质提供了更好的手段,而神经振荡活动可以为相关神经过程提供更多的见解。