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Wired for coherence: a network theory of self
Arshiya Aggarwal1, Brent L Hughes1
1Department of Psychology, University of California, Riverside, 900 University Avenue, Riverside, CA 92521, USA.
Trends in Cognitive Sciences
|July 21, 2026
Summary
The self is a dynamic causal network of interconnected self-aspects. This network maintains stability through belief-guided coherence, adapting to change by reorganizing connections to preserve identity.
Area of Science:
- Psychology
- Cognitive Science
- Social Psychology
Background:
- Human identity shows remarkable stability despite daily changes and life transitions.
- Understanding the mechanisms behind self-stability is crucial for explaining psychological continuity.
- Existing models inadequately capture the dynamic interplay of self-aspects.
Purpose of the Study:
- To propose a novel framework for understanding the stability of the self.
- To explain how different aspects of the self (identities, traits, values, memories) interact and maintain coherence.
- To differentiate this dynamic network model from existing associative, categorical, or hierarchical accounts.
Main Methods:
- Conceptual modeling of the self as a dynamic causal network.
- Analysis of belief systems linking self-aspects and their directional dependencies.
- Examination of coherence restoration through activation shifts and structural reorganization.
Main Results:
- The self is conceptualized as a network of self-aspects with directional causal beliefs.
- Network coherence is maintained when self-aspects align with beliefs and context.
- Disruptions trigger adaptive shifts in activation or structural network reorganization.
Conclusions:
- The dynamic causal network model offers a nuanced explanation for self-stability and change.
- Directional dependencies within the network constrain psychological transformations.
- Modifying network connections can enhance self-coherence and psychological well-being.
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