ISSN 1671-3710
CN 11-4766/R

Advances in Psychological Science ›› 2021, Vol. 29 ›› Issue (10): 1783-1795.doi: 10.3724/SP.J.1042.2021.01783

• Meta-Analysis • Previous Articles     Next Articles

The neural mechanism of self-face recognition: An ALE meta-analysis of fMRI studies

NA Yuting, ZHAO Yuwen, GUAN Lili()   

  1. School of Psychology, Northeast Normal University, Changchun 130024, China
  • Received:2020-11-14 Online:2021-10-15 Published:2021-08-23
  • Contact: GUAN Lili


Self-face recognition reflects the process whereby someone can recognize their own face by distinguishing it from the other. Generally, people recognize self-faces faster than they do other faces, and self-face recognition can elicit enhanced brain activity compared with that of other face recognitions. Researching self-face recognition is valuable because of its close relationship with self-awareness. Recently, many studies used functional magnetic resonance imaging (fMRI) to investigate the neural basis of self-face recognition. However, there are no consistent results regarding the key brain regions involved in self-face recognition. Therefore, in the current study, a quantitative meta-analysis of fMRI studies, using activation likelihood estimation (ALE), was performed to localize the neural structures engaged in recognizing self-face.

Twenty-seven studies involving 635 participants met the inclusion criteria. The meta-analysis was conducted in the standard Montreal Neurological Institute (MNI) space, and we translated results reported using Talairach coordinates into MNI coordinates. The statistical analysis of the transformed foci was validated using the Monte Carlo Simulation (1,000 permutations) with a cluster-forming voxel-level threshold at uncorrected p < 0.001 combined with cluster-size correction using family-wise error at p < 0.05. We used Mango software to project the activation coordinates onto a brain template to provide a visual representation of activation distributions.

Results showed that the contrast of self-face versus other-face displayed increased activations of the right superior parietal lobule/precuneus/middle occipital gyrus, middle frontal gyrus, inferior frontal gyrus, fusiform gyrus, postcentral gyrus, insula, and left precuneus. There was no active region in the contrast of other-face versus self-face. Based on the meta-analysis results and on previous event-related potential (ERP) studies, self-face recognition may involve two levels of processing, perceptual integration processing and the accompanying process of evaluation and emotional response. In the process of recognizing self-face, the occipital gyrus, fusiform gyrus, and precuneus are involved in the perceptual integration process. The occipital cortices may be involved in the processing of self-related facial features in the early stages of face recognition. The fusiform gyrus is involved in low-level sensory processing, and it is also sensitive to the categorization of faces in terms of self versus nonself. The precuneus is recruited in the perceptual integration of self-related information. The superior parietal lobule, middle frontal gyrus, inferior frontal gyrus, and insula are mainly recruited in the evaluation and the emotional response at the middle and late stages of recognizing self-face. The superior parietal lobule and middle frontal gyrus have been shown to play an important role in the processing of evaluating self-face. Moreover, their activations reflect the influence of social and cultural factors on self-face recognition. The inferior frontal gyrus and insula are also involved in the processing of evaluating self-face. Furthermore, they play a direct role in the subjective emotional experience of viewing or evaluating self-face.

In sum, the current meta-analysis reveals the neural basis of self-face recognition and suggests two levels of processing of self-face recognition (perceptual integration processing and the accompanying process of evaluation and emotional response). The current study provides support for investigating the neural mechanism of self-face recognition and, based on the limitations of previous studies, makes suggestions for future research. Future studies could use magnetoencephalography (MEG) or simultaneous EEG-fMRI to combine brain location and time course, thereby revealing the cognitive and neural mechanisms of self-face recognition. Close attention should be paid to the structural and functional connectivity of brain areas and brain networks and to the neural correlates of interoception and self-face recognition. Clinical studies should investigate abnormal neural activity in patients with self-processing impairment and explore the influence of threatening information on self-face recognition.

Key words: self-face recognition, neural mechanism, fMRI, ALE meta-analysis

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