Multi-Theory Consciousness Architecture: Integrating GWT, AST, HOT, FEP, IIT, RPT, and BLT in a Unified Computational Framework
Zenodo (CERN European Organization for Nuclear Research) March 15, 2026 Calvin Devereaux
A new open-source Python framework, Multi-Theory Consciousness (MTC), implements seven major consciousness theories as interacting modules within a single architecture, using three neural substrates (spiking neural network, liquid state machine, hierarchical temporal memory). The framework includes a 20-indicator assessment to measure architectural function across theories. Disabling one module measurably changes assessment scores for other theories, demonstrating cross-theory interactions: prediction error signals shape workspace competition, attention strength modulates precision weighting, and workspace access gates meta-representation. The authors do not claim the framework is conscious but present it as a controlled testbed for implementing, measuring, and comparing consciousness theories. The codebase (~25,000 lines, 400 tests) runs on consumer hardware.