| Abstract |
Accumulating evidence indicates that single neurons in the primate brain specifically encode sensorimotor experience about the self or others. Although the self-other distinction has been a major focus of social neuroscience research, little is known about the underlying mechanisms that enable the recognition of bodily self. Here, we review the literature demonstrating that pre-reflective bodily self-recognition can be achieved through the spatiotemporally contingent integration of visual, somatosensory, and motor signals arising from sensorimotor experience. We propose a self-other inference model as a neural computation for self-other distinction, in which the likelihood of being oneself is updated constantly based on Bayesian causal inference using appearance, contingency, and perspective cues. The results of simulation incorporating a state-space point-process model revealed that our self-other inference model successfully captures the latent state representation about the self-other distinction from synthetic neural activity. We hypothesize that the self-other inference model is implemented by distinct brain areas that process individual cues and their integrative hubs. This hypothesis is experimentally testable using cutting-edge technologies such as area-specific or pathway-selective silencing.
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