What does this research mean for the field?

The Multi-Theory Consciousness framework demonstrates that different consciousness theories interact in measurable ways, affecting assessment scores across the theories when one module is disabled. Novelty: ClaimNovelty.METHODOLOGICAL. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

To develop a unified computational framework that integrates major consciousness theories for assessment and comparison.

March 17, 2026Open Access

Multi-Theory Consciousness Architecture: Integrating GWT, AST, HOT, FEP, IIT, RPT, and BLT in a Unified Computational Framework

Key Points

To develop a unified computational framework that integrates major consciousness theories for assessment and comparison.
Implemented seven major consciousness theories as modules in a Python framework.
Utilized three neural substrates: spiking neural network, liquid state machine, and hierarchical temporal memory.
Created a 20-indicator assessment framework with ablation studies to measure interactions between theories.
Disabling one module affected the assessment scores of other theories, indicating interaction.
Prediction error signals influenced workspace competition and attention strength modulated representation access.

Abstract

We present the Multi-Theory Consciousness (MTC) framework: an open-source Python implementation of seven major consciousness theories operating as interacting modules within a single architecture. The framework implements Global Workspace Theory (Baars, 1988), Attention Schema Theory (Graziano, 2013), Higher-Order Thought Theory (Rosenthal, 2005), the Free Energy Principle (Friston, 2010), Integrated Information Theory (Tononi, 2008), Recurrent Processing Theory (Lamme, 2006), and Beautiful Loop Theory (Laukkonen, Friston attention strength modulates precision weighting; workspace access gates meta-representation. We do not claim the framework is conscious. We claim it is a useful research instrument — a controlled testbed where consciousness theories can be implemented, measured, and compared. The complete codebase (~25,000 lines, 400 tests) is released under the Apache 2.0 license and runs on consumer hardware. Repository: https://github.com/WhiteLotusLA/multi-theory-consciousness

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Calvin Devereaux

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Multi-Theory Consciousness Architecture: Integrating GWT, AST, HOT, FEP, IIT, RPT, and BLT in a Unified Computational Framework

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