Revisiting Brain Circuits Subserving Self-Consciousness: A Cognitive Computational Perspective

A theoretical framework proposes that self-consciousness arises not from specialized brain regions but from domain-general areas dynamically deployed to meet two core computational demands: self-distinctiveness and self-renewal. Integration is a fundamental principle that unifies self-experience. Two hierarchically structured subsystems, aligned with the Action-Mode Network and Default Mode Network, underpin self-related processing. These are regulated by the insula-centered body-based self-schema and the mPFC-centered knowledge-based self-schema, supporting bodily and mental interactions with the external environment. The framework outlines open questions for future research.

Study at a glance

Abstract

The neural basis of self-consciousness has been intensively investigated for decades, with numerous studies characterizing distributed brain areas engaged in self-related processing. Despite systematic descriptions of core brain regions and functional architectures in previous reviews, a unified theoretical framework explaining the mechanisms of self-consciousness has yet to be established. From a cognitive computational perspective, I synthesize the brain circuits subserving self-consciousness-related processing and argue that the unique neural responses linked to self-consciousness stem neither from specialized brain regions nor stimulus selectivity. Instead, domain-general brain regions are dynamically deployed to address the main cognitive computational requirements, i.e., self-distinctiveness and self-renewal, across bodily and mental domains. I further recognize integration as a fundamental computational principle that gives rise to cohesive, unified self-experience. Moreover, hierarchically structured dual subsystems aligned with the Action-Mode Network and Default Mode Network underpin self-related processing. Regulated respectively by the insula-centered body-based self-schema and mPFC-centered knowledge-based self-schema, these two subsystems support bodily and mental interactions between the self and the external environment. Finally, I elaborate on the theoretical implications of this computational framework and outline major open questions for future research.