Abstract

Social cognition has received much attention in fields such as neuroscience, psychology, cognitive science, and philosophy. Theory-theory (TT) and simulation theory (ST) provide the dominant theoretical frameworks for research on social cognition. However, neither theory addresses the matter of how the concepts of “self” and “other” are acquired through the development of human and nonhuman agents. Here, we show that the internal representations of “self” and “other” can be developed in an artificial agent only through the simple predictive learning achieved by deep neural networks with the superposition mechanism we herein propose. That is, social cognition can be achieved without a pre-given (or innate) framework of self and other; this is not assumed (or is at least unclear) in TT and ST. We demonstrate that the agent with the proposed model can acquire basic abilities of social cognition such as shared spatial representations of self and other, perspective-taking, and mirror-neuron-like activities of the agent’s neural network. The result indicates that the superposition mechanism we propose is a necessary condition for the development of the concepts of “self” and “other” and, hence, for the development of social cognition in general.

Highlights

  • Mutual development c Differentiation of self and other through learning self and other from the beginning of its existence; rather, they are acquired through the process of learning by gradually being contrasted against and related to each other

  • The given sensation is processed through multiple paths, and the results are processed by a single circuit (Fig. 2b)

  • Inside agent-1, we identified the neural activation patterns that correspond to the actual places and visual perspectives of agent-1

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Summary

Introduction

Mutual development c Differentiation of self and other through learning self and other from the beginning of its existence; rather, they are acquired through the process of learning by gradually being contrasted against and related to each other. It is more natural to assume that each agent has only one circuit that models any agent (including the self) In this case, the given sensation is processed through multiple paths, and the results are processed by a single circuit (Fig. 2b). We can assume that social agents obtain a single concept of agent while distinguishing self and others at the same time This assumption allows us to consider that self and others can be equated to each other at a certain level without abolishing their differences. Based on these ideas, we propose a novel neural mechanism that can build a single internal model that is applicable to “anyone,” which we call the “superposition mechanism.”. By this process of duplication and superposition, Scientific Reports | (2022) 12:2859 |

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