| Title: |
An implementation of integrated information theory in resting-state fMRI. |
| Authors: |
Nemirovsky, Idan E; Popiel, Nicholas JM; Rudas, Jorge; Caius, Matthew; Naci, Lorina; Schiff, Nicholas D; Owen, Adrian M; Soddu, Andrea |
| Publisher Information: |
Springer Nature; //doi.org/10.1038/s42003-023-05063-y |
| Publication Year: |
2023 |
| Collection: |
Apollo - University of Cambridge Repository |
| Subject Terms: |
Humans; Magnetic Resonance Imaging; Information Theory; Consciousness; Propofol; Hypnotics and Sedatives |
| Description: |
Acknowledgements: This work was supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) discovery grant to A.S. Funding was provided through the NSERC Canada Graduate Scholarship - Master’s Program (CGS-M) to I.E.N., as well as the Canada Excellence Research Chair (CERN) to A.M.O. ; Funder: Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada (Conseil de Recherches en Sciences Naturelles et en Génie du Canada); doi: https://doi.org/10.13039/501100000038 ; 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 Φmax, a measure of integrated information, is modulated by the sedative in different resting-state networks. We compare Φmax 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 Φmax presents a variety of sedative-induced behaviours for different networks. Notably, changes to Φmax 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. |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/zip; application/pdf; text/xml |
| Language: |
English |
| Relation: |
5063; https://www.repository.cam.ac.uk/handle/1810/354916 |
| Availability: |
https://www.repository.cam.ac.uk/handle/1810/354916 |
| Accession Number: |
edsbas.63120EB5 |
| Database: |
BASE |