Integrated World Modeling Theory (IWMT) Implemented: Towards Reverse Engineering Consciousness with the Free Energy Principle and Active Inference
International Workshop on Affective Interactions August 28, 2020 preprint DOI: 10.31234/osf.io/paz5j (opens in new tab) via Semantic Scholar
Summary
AI-generated from the abstractIntegrated World Modeling Theory (IWMT) proposes a unified account of consciousness by combining the Free Energy Principle, Integrated Information Theory (IIT), and Global Neuronal Workspace Theory (GNWT). It suggests that the brain's predictive processing can be modeled as variational autoencoders, where beliefs are updated through self-organizing harmonic modes (SOHMs) that form synchronous complexes. Alpha-synchronized SOHMs across posterior cortices may constitute the maximal complexes described by IIT, enabling phenomenal consciousness as mid-level perceptual inference. When these posterior SOHMs couple with frontal complexes, conscious access and higher-order cognition emerge, as described by GNWT. The entorhinal/hippocampal system organizes intermediate-level beliefs into spatiotemporal trajectories, affording episodic memory, counterfactual thinking, and planning.
Study at a glance
| Characteristics | Theoretical or philosophical paper |
|---|---|
| Keywords | Computer science Philosophy |
| Key finding | Proposes that alpha-synchronized self-organizing harmonic modes across posterior cortices may constitute the maximal complexes described by Integrated Information Theory, enabling phenomenal consciousness as mid-level perceptual inference, and that coupling with frontal complexes enables conscious access and higher-order cognition as described by Global Neuronal Workspace Theory. |
Abstract
Integrated World Modeling Theory (IWMT) is a synthetic model that attempts to unify theories of consciousness within the Free Energy Principle and Active Inference framework, with particular emphasis on Integrated Information Theory (IIT) and Global Neuronal Workspace Theory (GNWT). IWMT further suggests predictive processing in sensory hierarchies may be well-modeled as (folded, sparse, partially disentangled) variational autoencoders, with beliefs discretely-updated via the formation of synchronous complexes—as self-organizing harmonic modes (SOHMs)—potentially entailing maximal a posteriori (MAP) estimation via turbo coding. In this account, alpha-synchronized SOHMs across posterior cortices may constitute the kinds of maximal complexes described by IIT, as well as samples (or MAP estimates) from multimodal shared latent space, organized according to egocentric reference frames, entailing phenomenal consciousness as mid-level perceptual inference. When these posterior SOHMs couple with frontal complexes, this may enable various forms of conscious access as a kind of mental act(ive inference), affording higher order cognition/control, including the kinds of attentional/intentional processing and reportability described by GNWT. Across this autoencoding heterarchy, intermediate-level beliefs may be organized into spatiotemporal trajectories by the entorhinal/hippocampal system, so affording episodic memory, counterfactual imaginings, and planning.