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The statistical physics of psychological networks: Zero matters
Han L J van der Maas1, Denny Borsboom1, Lourens Waldorp1
1Department of Psychology, University of Amsterdam.
Psychological Review
|February 17, 2026
Summary
Psychological network models are enhanced using ternary spin models, moving beyond binary limitations. This allows for more nuanced representations of psychological data, improving the analysis of attitudes, mood disorders, and knowledge acquisition.
Area of Science:
- Psychology
- Statistical Physics
- Computational Neuroscience
Background:
- Psychological network theories offer an alternative to traditional common cause models.
- Ising models are commonly used but limited by binary node states.
- Psychological data often includes neutral or uncertain responses not captured by binary models.
Purpose of the Study:
- To introduce ternary spin models for psychological networks, overcoming limitations of binary Ising-type models.
- To enable more nuanced representations of psychological data by incorporating a third, neutral node state.
- To demonstrate the application of ternary models in attitude research, mood disorder analysis, and knowledge acquisition.
Main Methods:
- Formalization of psychological networks using ternary spin models, specifically the Blume-Capel model.
- Extension of the Ising attitude model to a ternary framework.
- Development of a unified ternary network model for bipolar and major depressive disorders.
- Application of ternary network models to study knowledge acquisition.
Main Results:
- Ternary spin models successfully incorporate neutral or uncertain responses, enhancing scale representation.
- The proposed models exhibit more complex dynamics, offering novel insights into psychological constructs.
- Demonstrated utility in modeling attitudes, unifying bipolar and major depressive disorder frameworks, and analyzing knowledge acquisition.
Conclusions:
- Ternary spin models provide a more flexible and nuanced approach to psychological network analysis.
- These models advance our understanding of complex psychological phenomena by accommodating diverse response types.
- The framework offers new avenues for research across various psychological subdisciplines.
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