An implementation of integrated information theory in resting-state fMRI

• Published in: Communications biology Vol. 6; no. 1; pp. 692 - 14
• Main Authors: Nemirovsky, Idan E., Popiel, Nicholas J. M., Rudas, Jorge, Caius, Matthew, Naci, Lorina, Schiff, Nicholas D., Owen, Adrian M., Soddu, Andrea
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 05.07.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 59/36; 59/57; 631/378/116/1925; 631/378/2649/1398; Anesthesia; Biology; Biomedical and Life Sciences; Cognitive ability; Functional magnetic resonance imaging; Information theory; Life Sciences; Neural networks; Neuroimaging; Propofol; Sleep and wakefulness
• ISSN: 2399-3642; 2399-3642
• DOI: 10.1038/s42003-023-05063-y

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 functional connectivity. Our results indicate that Φ max presents a variety of sedative-induced behaviours for different networks. Notably, changes to Φ max closely reflect changes to subjects’ conscious level in the frontoparietal and dorsal attention networks, which are responsible for higher-order cognitive functions. In conclusion, our findings present important insight into different measures of conscious level that will be useful in future implementations to functional MRI and other forms of neuroimaging. Resting-state fMRI data in conditions of wakefulness and anaesthesia was analyzed using integrated information theory and its key measure, Φmax, which presents a variety of sedative-induced behaviours across different cortical networks.