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Reduced emergent character of neural dynamics in patients with a disrupted connectome

Andrea I. Luppi, Pedro A.M. Mediano, Fernando E. Rosas, Judith Allanson, John D. Pickard, Guy B. Williams, Michael M. Craig, Paola Finoia, Alexander R.D. Peattie, Peter Coppola, David K. Menon, Daniel Bor, Emmanuel A. Stamatakis

NeuroImage February 11, 2023 DOI: 10.1016/j.neuroimage.2023.119926 via DOAJ

Summary

AI-generated from the abstract

High-level brain functions are thought to arise from coordinated activity across neural systems, but this has been hard to test empirically. Using a framework called Integrated Information Decomposition, which quantifies emergence in dynamical systems, the authors analyzed functional MRI data and found that emergent and hierarchical neural dynamics are significantly reduced in chronically unresponsive patients with severe brain injury. Emergence capacity was positively correlated with hierarchical organization in brain activity. Combining network control theory and whole-brain modeling, the authors show that reduced emergent and hierarchical dynamics in these patients can be explained by disruptions in the structural connectome. The results suggest that chronic unresponsiveness after severe brain injury may stem from structural damage to neural infrastructure needed for emergent brain dynamics.

Study at a glance

Characteristics Observational cohort Peer reviewed
Population Chronically unresponsive patients suffering from severe brain injury
Keywords Whole-brain modelling Network control theory Hierarchy Emergence Information decomposition
Key finding Emergent and hierarchical neural dynamics are significantly diminished in chronically unresponsive patients with severe brain injury, and this reduction is mechanistically linked to disruptions in the structural connectome.

Abstract

High-level brain functions are widely believed to emerge from the orchestrated activity of multiple neural systems. However, lacking a formal definition and practical quantification of emergence for experimental data, neuroscientists have been unable to empirically test this long-standing conjecture. Here we investigate this fundamental question by leveraging a recently proposed framework known as “Integrated Information Decomposition,” which establishes a principled information-theoretic approach to operationalise and quantify emergence in dynamical systems — including the human brain. By analysing functional MRI data, our results show that the emergent and hierarchical character of neural dynamics is significantly diminished in chronically unresponsive patients suffering from severe brain injury. At a functional level, we demonstrate that emergence capacity is positively correlated with the extent of hierarchical organisation in brain activity. Furthermore, by combining computational approaches from network control theory and whole-brain biophysical modelling, we show that the reduced capacity for emergent and hierarchical dynamics in severely brain-injured patients can be mechanistically explained by disruptions in the patients’ structural connectome. Overall, our results suggest that chronic unresponsiveness resulting from severe brain injury may be related to structural impairment of the fundamental neural infrastructures required for brain dynamics to support emergence.

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