Psychology, Sabanci University, Istanbul, Turkey.
Electronics Engineering, Sabanci University, Istanbul, Turkey.
Sci Rep. 2022 Jan 7;12(1):118. doi: 10.1038/s41598-021-02808-9.
Integrating the spatiotemporal information acquired from the highly dynamic world around us is essential to navigate, reason, and decide properly. Although this is particularly important in a face-to-face conversation, very little research to date has specifically examined the neural correlates of temporal integration in dynamic face perception. Here we present statistically robust observations regarding the brain activations measured via electroencephalography (EEG) that are specific to the temporal integration. To that end, we generate videos of neutral faces of individuals and non-face objects, modulate the contrast of the even and odd frames at two specific frequencies ([Formula: see text] and [Formula: see text]) in an interlaced manner, and measure the steady-state visual evoked potential as participants view the videos. Then, we analyze the intermodulation components (IMs: ([Formula: see text]), a linear combination of the fundamentals with integer multipliers) that consequently reflect the nonlinear processing and indicate temporal integration by design. We show that electrodes around the medial temporal, inferior, and medial frontal areas respond strongly and selectively when viewing dynamic faces, which manifests the essential processes underlying our ability to perceive and understand our social world. The generation of IMs is only possible if even and odd frames are processed in succession and integrated temporally, therefore, the strong IMs in our frequency spectrum analysis show that the time between frames (1/60 s) is sufficient for temporal integration.
整合我们从周围高度动态的世界中获取的时空信息对于正确导航、推理和决策至关重要。尽管这在面对面的对话中尤为重要，但迄今为止，很少有研究专门研究动态人脸感知中时间整合的神经相关性。在这里，我们提出了关于通过脑电图 (EEG) 测量的大脑激活的具有统计学意义的观察结果，这些结果是特定于时间整合的。为此，我们生成了个体中性面孔和非面孔物体的视频，以交错方式以两个特定频率 ([Formula: see text] 和 [Formula: see text]) 调制偶数和奇数帧的对比度，并测量参与者观看视频时的稳态视觉诱发电位。然后，我们分析了互调分量 (IM：([Formula: see text])，是具有整数乘数的基频的线性组合)，这些分量随后反映了非线性处理并按设计指示时间整合。我们表明，当观看动态面孔时，中颞、下和中额区域周围的电极会强烈且选择性地做出反应，这表明了我们感知和理解社交世界的基本过程。只有偶数和奇数帧依次处理并进行时间整合，才能产生 IM，因此，我们的频谱分析中的强 IM 表明帧与帧之间的时间（1/60 秒）足以进行时间整合。
