Using steady-state visual evoked potentials (SSVEP) to measure brain responses to faces and objects

本研究采用稳态视觉诱发电位（SSVEP）研究人脸和物体感知的神经相关性。 已经表明，人类视觉系统的重复刺激在脑电图（EEG）中产生振荡，其模仿重复刺激的频率-SSVEP（Regan 2009）。 所提出的实验将采用适应范例，其中具有相同身份的适应面孔（例如，“Joe”）以周期性的呈现速率（4 Hz）在屏幕上反复闪烁。基于先前的研究（Rossion & Boremanse，2011），相同面部身份的连续呈现产生神经信号的减少（即，重复抑制效应）。 在测试阶段，不同身份的面孔（例如，“Fred”、“Bob”、“Bill”等）以用于适应的刺激速率示出。 不同面孔的呈现导致EEG信号的突然增加，表明SSVEP对个体面孔的身份变化敏感。与传统的事件相关电位（ERP）相比，SSVEP技术的优势在于，该方法产生高信噪比，需要的实验次数少得多，并且是高水平视觉中感知辨别力的可靠测量。然而，目前还不知道SSVEP是否对感知经验和学习的影响有反应。 这些问题在当前的提案中通过测试真实的世界和实验室培训的专家来解决。 在第一个系列的实验中，将研究对鸟类有丰富经验的真实的世界鸟类专家和对自己有丰富经验的单一种族的人，而不是其他种族的面孔。我们假设鸟类专家和本族面孔专家将对专业领域的刺激表现出更大的SSVEP（即，鸟类为鸟类专家，本族面孔为本族专家）而不是新手。此外，SSVEP差异将与来自专业领域的物体和面部识别的差异相关。 第二，我们将在实验室培训研究中调查知觉专业知识的获得。 我们预测，这是一种，而不是数量的知觉经验，决定知觉的专业知识和调制强度的SSVEP信号。 在最后一组实验中，我们将检查SSVEP的幅度是否区分了面部识别的个体差异以及神经典型人群和具有已知面部识别缺陷的人群之间的组间差异（即，自闭症患者）。 总之，拟议的研究计划填补了我们对指导高级视觉过程的机制的理解的关键空白，将观察者的感知经验和能力与大脑活动的差异联系起来。

The proposed research investigates the neural correlates of human face and object perception using steady-state visual-evoked potentials (SSVEP). It has been shown that repetitive stimulation of the human visual system produces oscillations in the electroencephalogram (EEG) that mimics the frequency of the repeating stimulus - the SSVEP (Regan 2009). The proposed experiments will employ an adaptation paradigm in which an adapting face of the same identity (e.g., "Joe") is repeatedly flashed on the screen at a periodic rate of presentation (4 Hz). Based on a previous study (Rossion & Boremanse, 2011), the continuous presentation of the same face identity produces a reduction in the neural signal (i.e., repetition suppression effect). In the test phase, faces of different identities (e.g., "Fred", "Bob", "Bill", etc.) are shown at the rate of stimulation used for adaptation. The presentation of different faces cause an abrupt increase in the EEG signal indicating that the SSVEP is sensitive to the changing identities of individual faces. The advantages of the SSVEP technique over traditional event-related potentials (ERPs) are that the method yields a high signal-to-noise ratio, requires substantially fewer experimental trials and is a robust measure of perceptual discrimination in high-level vision.**However, it is not known if the SSVEP is responsive to the effects of perceptual experience and learning. These questions are addressed in the current proposal by testing real world and laboratory-trained experts. In the first series of experiments, real world bird experts who have extensive experience to birds and mono-racial people who have extensive experience to own-, but not other-race faces will be studied. We hypothesize that bird experts and own-race face experts will exhibit a greater SSVEP to stimuli in the domain of expertise (i.e., birds for bird experts, own-race faces for own-race experts) than novices. Moreover, SSVEP differences will be correlated with differences in recognition of objects and faces from the domain of expertise. Second, we will investigate the acquisition of perceptual expertise in a laboratory training studies. We predict that it is the kind, not the amount of perceptual experience that determines perceptual expertise and modulates the strength of the SSVEP signal. In the final set of experiments, we will examine whether the magnitude of the SSVEP distinguishes individual differences in face recognition and inter-group differences between neurotypical people and a population with known face recognition deficits (i.e., people on the autism spectrum). In summary, the proposed program of research fills a critical gap in our understanding of mechanisms that guide the processes of high-level vision, linking the observer's perceptual experience and abilities with differences in brain activity.