An implementation of integrated information theory in resting-state fMRI.

ABSTRACT: Integrated Information Theory was developed to explain and quantify consciousness, arguing that conscious systems consist of elements that are integrated through their causal properties. This study presents an implementation of Integrated Information Theory 3.0, the latest version of this framework, to functional MRI data. Data were acquired from 17 healthy subjects who underwent sedation with propofol, a short-acting anaesthetic. Using the PyPhi software package, we systematically analyze how Φ^max, a measure of integrated information, is modulated by the sedative in different resting-state networks. We compare Φ^max to other proposed measures of conscious level, including the previous version of integrated information, Granger causality, and correlation-based function

SUBMITTER: Nemirovsky IE 

PROVIDER: S-EPMC10322831 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature