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Neural systems for the extraction of socially-relevant information from faces

Neural systems for the extraction of socially-relevant information from faces
用于从面部提取社会相关信息的神经系统
批准号:
0446801
负责人:
James Haxby
金额:
$45.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-08-01 至 2008-06-30

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中文摘要
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英文摘要
Appropriate and effective social interaction requires ready access to representations of the personal traits, intentions, goals, opinions, and mental states of others. With funding from the National Science Foundation, James V. Haxby is investigating the functional organization of neural systems that extract such person knowledge from the perception of faces and gestures. The proposed experiments use functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and other measures to investigate the roles played by neural systems for face perception, action perception and imitation (mirror neuron, MN), and theory of mind (ToM) in obtaining social information from faces. This information can be transient mental states, such as direction of attention, emotional state, and level of interest, or more enduring attributes, such as personal traits, goals, attitudes, and beliefs. Perception of facial and social gesture, on the one hand, and recognition of familiar faces, on the other, are hypothesized to be mediated by distinct parts of the neural systems for face and action perception. By contrast, a common neural system for the representation of person knowledge is hypothesized to mediate the representations of transient mental states and enduring personal attributes of others that are activated during face perception. The system for these representations is hypothesized to be the same system that has been associated with ToM, the ability to represent the mental states of others. The first objective of the experiments is to characterize the functional organization of the mirror neuron system, its role in the perception of facial expressions, social gestures, and eye gaze, and its role in the activation and updating of representations of transient mental states in the ToM system. The hypothesis is being tested that perception of facial movements and gestures activate mirror neuron networks (superior temporal sulcus, intraparietal sulcus, and premotor regions, namely Broca's area and the frontal eye fields)' that both perception and imitation evoke this activity; and that movements that convey socially-relevant information also will evoke activity in the ToM system. The second objective is to investigate which of the regions that are activated during the recognition of familiar faces are associated with the spontaneous retrieval of representations of the enduring personal attributes associated with familiar individuals. The hypothesis is being tested that this process is mediated by cortical areas in the ToM system (anterior paracingulate cortex, posterior superior temporal sulcus), and these areas can be distinguished from areas associated with emotional responses (amygdala) and the retrieval of autobiographical episodic memories (posterior cingulate/precuneus, anterior temporal cortex). Automaticity of retrieval of person knowledge associated with familiar faces by manipulating awareness of the faces will also be investigated.Face perception is a highly developed and efficient skill that plays a central role in social communication. In particular, face perception may play a more critical role than language in conveying information about the intentions, attitudes, emotions, level of interest, and other transient mental states of others. Better understanding of the functional architecture of the human neural systems that mediate this skill can help to inform computational approaches to face perception, with possible applications to improved human-computer interfaces. Such understanding can also help in the development of diagnostic procedures and therapies for psychiatric disorders characterized by impaired social communication and face perception, such as social phobia, autism, and schizophrenia. Undergraduate and graduate students at Princeton University will be involved in the research.
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