The Studies Of Neural Specificity Of Face Perception And The Neural Substrate Of Top-down Face Processing Based On Functional Neuroimaging

Faces are one of the upmost important visual stimuli in the human's social lives; the means of communication among people rely heavily on processing the information contained in the faces, and humans are exceptionally skilled at face perception. How the face processing is performed in the brain has been the research focus in numerous disciplines. With the development of neuroscience, many achievements on this question have been gained. However, it is still unclear what the neural mechanisms of face processing are. Therefore, the goal of this article is to study a number of cognitive issues of face processing based on fMRI, hoping to promote this research progress.In recent years, converging evidences, which come from the studies of activation patterns in face processing using a variety of functional imaging technologies, have provided a very consistent finding, which is that faces always lead strong activation in the fusiform gyrus when compared to other visual stimuli. This area is defined as the fusiform face area (FFA). At present, there are two distinct different explanations on the function of this region: one theory interprets that this area is just specialized for face processing, but the other one considers that this area is responsible for faces as human are the experts in face processing. In our first study, we find that the control stimuli used in the previous studies are not matched with the faces. Thus, we improve the experimental control stimuli of face to study the neural specificity of face perception. For literate Chinese adults, the characters should be the ideal contrast condition for face stimuli, because it is similar to the face in multi-dimensions. Hence, in the first study, characters are chosen as the comparison stimuli of faces. The results in this study indicate that the activation patterns of bilateral fusiform gyrus induced by faces and characters are very similar and strong correlative,which is attributed to the similar multi-dimensions between the faces and characters. However, it is found that the right fusiform gyrus is strongly activated when faces relative to characters. On the opposite, bilateral fusiform gyrus is not active when characters comparing to faces. Those results convincingly support the hypothesis that the neurons specified for face processing exist in this region.Face processing can be achieved through two means: bottom-up and top-down. For the experimental approach of bottom-up face processing is easily to be implemented and controlled, most of previous studies of face processing have focused on this means of face processing. In the study of top-down face processing, as the information coming from the bottom-up face processing easily interferes to extract the brain activation patterns of top-down face processing, it is the first key step to design a logical and effective paradigm to obtain the signal flow of top-down face processing. In the second study, a novel experimental paradigm is designed to study the neural substrate of top-down face processing. Subjects are trained to perceive illusory faces from the pure noise images. Since the physical properties of all noise images are identical and illusory face processing carried by subjects is formed entirely under the top-down approach.Based on the experimental paradigm, the traditional Pearson correlation analysis of time series and improved Psychophysiological Interactions analysis are used to obtain the distributed neural network of top-down face processing. This network not only contains the regions of core system in the distributed face processing network defined by previous studies, but also the brain regions involved in the processing of low-frequency information of visual stimuli, making decision, as well as in working memory and attention regulation. Further researches use the method of dynamic causal model (DCM) analysis to infer the effective connectivity network of the regions of the fusiform face area (FFA), the occipital face area (OFA), the inferior parietal lobule (IPL) and the orbitofrontal cortex(OFC), which are contained in the top-down face processing network. The four regions are considered to play a crucial role in the face processing or top-down processing manner. The optimal network model indicates that the OFC and IPL play crucial roles in the top-down face processing by regulating the activities of the OFA. The OFC can offer OFA the low-frequency information of faces and OFA can search the pure noise images for face-like features under directing top-down visual attention exerted by IPL. After the initial processing by OFA, the face-like featured information is transmitted to FFA for further holistic face processing.The neural substrate of face processing is always the hot field in many disciplines, and many significant results have been achieved in relative research fields. Nevertheless, this issue is still not well understood. It could take advantage of the interdisciplinary efforts to promote the progress of neural mechanisms study of face perceptions, to provide the proper treatment ways for face processing diseases, and also to provide new methods and ideas to solve the bottleneck problems of face identification in pattern recognition field. In the third study of this article, those most influential functional cognitive models and neural distributed network models of face processing are primarily presented. Then recent findings using novel methods and advanced technologies to study the neural mechanism of face processing are accumulated to investigate spatiotemporal relation among the neural regions involved in face processing, hoping to provide new ideas for our further studies of face processing after this review.