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The Me-File: An Event-Coding Approach to Self-Representation.

Bernhard Hommel

Frontiers in psychology January 1, 2021 DOI: 10.3389/fpsyg.2021.698778 via PubMed

Summary

AI-generated from the abstract

People represent themselves using the same basic cognitive mechanisms they use to represent other individuals, events, and objects. This self-representation works by binding sensory codes that result from one's own actions into a 'Me-File'—an integrated event file. This view aligns with a Humean bundle-self theory, where the self is not a unified entity but a collection of perceptions. Recent extensions of the Theory of Event Coding provide the necessary mechanistic ingredients for this account. The Me-File concept offers a foundation for more targeted experimentation and for building artificial agents with human-like selves.

Study at a glance

Characteristics Theoretical or philosophical paper Peer reviewed
Keywords Agency Body ownership Minimal self Self representation
Citations 7
Key finding People represent themselves by binding sensory consequences of their own actions into a Me-File, consistent with a Humean bundle-self theory.

Abstract

Numerous authors have taken it for granted that people represent themselves or even have something like "a self", but the underlying mechanisms remain a mystery. How do people represent themselves? Here I propose that they do so not any differently from how they represent other individuals, events, and objects: by binding codes representing the sensory consequences of being oneself into a Me-File, that is, into an event file integrating all the codes resulting from the behaving me. This amounts to a Humean bundle-self theory of selfhood, and I will explain how recent extensions of the Theory of Event Coding, a general theory of human perception and action control, provide all the necessary ingredients for specifying the mechanisms underlying such a theory. The Me-File concept is likely to provide a useful mechanistic basis for more specific and more theoretically productive experimentation, as well as for the construction of artificial agents with human-like selves.

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