Since the last decade or so, the methodology of functional magnetic resonance imaging (fMRI) is becoming mature day by day. This non-invasive technique has been widely used in the studies of human cognition and brain function, and is becoming the research hotspot in these fields. With the aid of novel analysis methods in the field of information science, researchers can process and analyze the fMRI data to obtain the new knowledge which can't be abstracted by traditional methods. In that way, they explore the neural correlates of brain function, and uncover the neural mechanisms of human brain. Nowadays, one of research hotspots in the field of cognitive neuroscience is the study of neural mechanisms underlying face perception. Face perception plays an important role in the social communication. The cross-race effect is a common phenomenon in face perception, and attracts broad attention from psychologists in more than half century. The current study provides some valuable evidence for uncovering the cognitive mechanism of the cross-race effect at the neural level. Furthermore, it sheds some light on the neural mechanism underlying the face perception, and can help to address the problem whether there is a neural mechanism which is specific for face processing. Additionally, as another important application of machine learning, neuroimaging analysis attracts more and more attention in the last decades. The amount of papers on analysis of fMRI data using machine learning methods is rising each year. The prosperity of machine learning provides some powerful tools for the cognitive neuroscience. However, the amount of papers on studies of cross-race effect using machine learning methods is limited. This article describes my fMRI-based studies on the cross-race effect. Main work can be divided into three parts: (1) A standard-resolution fMRI study about the other-race categorization advantage was carried out. The special psychological experimental software and MRI equipment were used respectively to record the behavioral reactions and neural activities when Chinese adults processed faces of different races. Then, the statistical parametric mapping (SPM) was used to process fMRI data at the whole-brain level, and psychophysiology interaction was used to compute the effective connectivity between active brain regions. In that way, from both the single-brain-region level and brain-network level, I explored both the difference and correlate of neural activ...
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