| A Brain-Inspired Model of Theory of Mind | |
| Zeng, Yi1,2,3,4; Zhao, Yuxuan2; Zhang, Tielin2; Zhao, Dongcheng2,4; Zhao, Feifei2; Lu, Enmeng2 | |
| 刊名 | FRONTIERS IN NEUROROBOTICS
 |
| 2020-08-28 | |
| 卷号 | 14页码:17 |
| 关键词 | theory of mind false-belief task brain inspired model self-experience connection maturation inhibitory control |
| ISSN号 | 1662-5218 |
| DOI | 10.3389/fnbot.2020.00060 |
| 通讯作者 | Zeng, Yi(yi.zeng@ia.ac.cn) |
| 英文摘要 | Theory of mind (ToM) is the ability to attribute mental states to oneself and others, and to understand that others have beliefs that are different from one's own. Although functional neuroimaging techniques have been widely used to establish the neural correlates implicated in ToM, the specific mechanisms are still not clear. We make our efforts to integrate and adopt existing biological findings of ToM, bridging the gap through computational modeling, to build a brain-inspired computational model for ToM. We propose a Brain-inspired Model of Theory of Mind (Brain-ToM model), and the model is applied to a humanoid robot to challenge the false belief tasks, two classical tasks designed to understand the mechanisms of ToM from Cognitive Psychology. With this model, the robot can learn to understand object permanence and visual access from self-experience, then uses these learned experience to reason about other's belief. We computationally validated that the self-experience, maturation of correlate brain areas (e.g., calculation capability) and their connections (e.g., inhibitory control) are essential for ToM, and they have shown their influences on the performance of the participant robot in false-belief task. The theoretic modeling and experimental validations indicate that the model is biologically plausible, and computationally feasible as a foundation for robot theory of mind. |
| 资助项目 | Strategic Priority Research Program of Chinese Academy of Sciences[XDB32070100] ; Beijing Municipality of Science and Technology[Z181100001518006] ; CETC Joint Fund[6141B08010103] ; Major Research Program of Shandong Province[2018CXGC1503] ; Key Research Program of Frontier Sciences of Chinese Academy of Sciences[ZDBS-LY-JSC013] |
| WOS关键词 | SELF-PERSPECTIVE INHIBITION ; TEMPORO-PARIETAL JUNCTION ; FALSE-BELIEF TASK ; NEURAL BASIS ; OTHERS ; METAANALYSIS ; PERCEPTION ; UNDERSTAND ; COGNITION ; AUTISM |
| WOS研究方向 | Computer Science ; Robotics ; Neurosciences & Neurology |
| 语种 | 英语 |
| 出版者 | FRONTIERS MEDIA SA |
| WOS记录号 | WOS:000570490100001 |
| 资助机构 | Strategic Priority Research Program of Chinese Academy of Sciences ; Beijing Municipality of Science and Technology ; CETC Joint Fund ; Major Research Program of Shandong Province ; Key Research Program of Frontier Sciences of Chinese Academy of Sciences |
| 内容类型 | 期刊论文 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/41976]  |
| 专题 | 类脑智能研究中心_类脑认知计算 |
| 通讯作者 | Zeng, Yi |
| 作者单位 | 1.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Automat, Res Ctr Brain Inspired Intelligence, Beijing, Peoples R China 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China 4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zeng, Yi,Zhao, Yuxuan,Zhang, Tielin,et al. A Brain-Inspired Model of Theory of Mind[J]. FRONTIERS IN NEUROROBOTICS,2020,14:17. |
| APA | Zeng, Yi,Zhao, Yuxuan,Zhang, Tielin,Zhao, Dongcheng,Zhao, Feifei,&Lu, Enmeng.(2020).A Brain-Inspired Model of Theory of Mind.FRONTIERS IN NEUROROBOTICS,14,17. |
| MLA | Zeng, Yi,et al."A Brain-Inspired Model of Theory of Mind".FRONTIERS IN NEUROROBOTICS 14(2020):17. |
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