虚幻面孔加工有效连通网络的非线性DCM分析

doi:10.3969/j.issn.1001-2400.2011.03.012

Abstract

Abstract:

In order to extract the activation patterns of top-down face processing, the present study uses an experimental paradigm in which participants detect illusory faces in pure noise images. The nonlinear dynamic causal models (DCM) analysis, which has a perfect neural theory foundation, is used to investigate the effective connectivity of the illusory face detection network under the top-down processing mechanism. The optimal network model indicates that the occipital face area (OFA) serves as a key generator of illusory face detection. Under directing top-down visual attention exerted by the inferior parietal lobule (IPL), OFA searches for the pure noise images for face-like features, and then provides those face-like feature information to the fusiform face area(FFA) for further holistic face processing.

Key words: nonlinear analysis, dynamic causal model (DCM), neural network, top-down, effective connectivity

LI Jun；ZHAO Jizheng；FENG Lu；SHI Guangming；LIANG Jimin. Investigation of effective connectivity of the illusory face detection network based on nonlinear dynamic causal models analysis[J].J4, 2011, 38(3): 69-75.

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Investigation of effective connectivity of the illusory face detection network based on nonlinear dynamic causal models analysis

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