The Emergence of Integrated Information, Complexity, and 'Consciousness' at Criticality.
Nicholas J M Popiel, Sina Khajehabdollahi, Pubuditha M. Abeyasinghe, Francesco Riganello, Emily S Nichols, Adrian M. Owen, Andrea Soddu
Entropy (Basel, Switzerland) March 16, 2020 DOI: 10.3390/e22030339 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Simulation study Peer reviewed |
|---|---|
| Sample size | 159 |
| Population | Normalized, random, positively weighted five-node excitatory neural network motifs simulated as generalized Ising models |
| Keywords | Ising model Criticality Integrated information |
| Key points | Integrated information, as an order parameter, undergoes a phase transition at the critical point in the generalized Ising model, where it is maximally receptive and responsive to perturbations. |
Abstract
Integrated Information Theory (IIT) posits that integrated information ( Φ ) represents the quantity of a conscious experience. Here, the generalized Ising model was used to calculate Φ as a function of temperature in toy models of fully connected neural networks. A Monte-Carlo simulation was run on 159 normalized, random, positively weighted networks analogous to small five-node excitatory neural network motifs. Integrated information generated by this sample of small Ising models was measured across model parameter spaces. It was observed that integrated information, as an order parameter, underwent a phase transition at the critical point in the model. This critical point was demarcated by the peak of the generalized susceptibility (or variance in configuration due to temperature) of integrated information. At this critical point, integrated information was maximally receptive and responsive to perturbations of its own states. The results of this study provide evidence that Φ can capture integrated information in an empirical dataset, and display critical behavior acting as an order parameter from the generalized Ising model.