Quantifying Spacetime Integration across a Partition with Synergy
For researchers in consciousness and complex systems, this provides improved mathematical tools for quantifying integration, though the results are preliminary and domain-specific.
The paper introduces four measures of integration based on partial information decomposition for the Information Integration Theory of Consciousness (IIT), showing that synergy-based measures outperform current IIT practice in simple deterministic networks.
In service to the mathematical underpinnings of the Information Integration Theory of Consciousness (IIT), we introduce four measures of integration based on the partial information decomposition framework. We compare our measures to current IIT practice in simple deterministic networks. We find synergy-based measures more suitable for IIT's use-case than current practice. Outside IIT, these measures could also be useful as non-IIT-related measures of complexity within discrete dynamical systems.