Abstract
At the core of bodily self-consciousness is the perception of the ownership of one's body. Recent efforts to gain a deeper understanding of the mechanisms behind the brain's encoding of the self-body have led to various attempts to develop a unified theoretical framework to explain related behavioral and neurophysiological phenomena. A central question to be explained is how body illusions such as the rubber hand illusion actually occur. Despite the conceptual descriptions of the mechanisms of bodily self-consciousness and the possible relevant brain areas, the existing theoretical models still lack an explanation of the computational mechanisms by which the brain encodes the perception of one's body and how our subjectively perceived body illusions can be generated by neural networks. Here we integrate the biological findings of bodily self-consciousness to propose a Brain-inspired bodily self-perception model, by which perceptions of bodily self can be autonomously constructed without any supervision signals. We successfully validated our computational model with six rubber hand illusion experiments on platforms including a iCub humanoid robot and simulated environments. The experimental results show that our model can not only well replicate the behavioral and neural data of monkeys in biological experiments, but also reasonably explain the causes and results of the rubber hand illusion from the neuronal level due to advantages in biological interpretability, thus contributing to the revealing of the computational and neural mechanisms underlying the occurrence of the rubber hand illusion.
Abstract (translated)
在身体自我感知的核心,感知自己身体所有权的意识感知是主要的。最近,为了更深入地理解大脑自我身体编码的机制,人们尝试了各种方法,以期建立一个统一的理论框架来解释相关的行为和神经生理现象。一个关键问题是如何产生像橡皮手幻觉这样的身体错觉的。尽管对身体自我感知机制和可能相关的大脑区域进行了概念描述,但现有的理论模型仍然缺乏解释大脑中计算机制如何编码感知自己身体以及我们的主观感知身体错觉如何由神经网络产生。在这里,我们综合了身体自我感知的生理研究成果,提出了一个基于大脑的身体自我感知模型,该模型可以使自主地构建身体自我感知信号,而无需监督信号。我们成功验证我们的计算模型,在包括一个iCub机器人和模拟环境的平台上进行六次橡皮手幻觉实验,实验结果表明,我们的模型不仅可以在生物实验中复制猴子的行为和神经数据,而且由于生物解释性的优势,可以合理地解释橡皮手幻觉的产生原因和结果,从而为揭示产生橡皮手幻觉的计算和神经机制提供了贡献。
URL
https://arxiv.org/abs/2303.12259