Author: Thomas F Varley1,2,3, Michael Craig1,2, Ram Adapa1, Paola Finoia1, Guy Williams4, Judith Allanson5, John Pickard4,6, David K Menon1,4, Emmanuel A Stamatakis1,2
1 Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridgeshire, England, United Kingdom.
2 Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridgeshire, England, United Kingdom.
3 Department of Psychological & Brain Sciences, Indiana University, Bloomington, Indiana, United States of America.
4 Wolfson Brain Imaging Center, University of Cambridge, Cambridgeshire, England, United Kingdom.
5 Department of Neurorehabilitation, Addenbrooke's Hospital, Cambridgeshire, England, United Kingdom.
6 Division of Neurosurgery, School of Clinical Medicine, University of Cambridge, Cambridgeshire, England, United Kingdom.
Conference/Journal: PLoS One
Date published: 2020 Feb 13
Other: Volume ID: 15 , Issue ID: 2 , Pages: e0223812 , Special Notes: doi: 10.1371/journal.pone.0223812. , Word Count: 282
Recent evidence suggests that the quantity and quality of conscious experience may be a function of the complexity of activity in the brain and that consciousness emerges in a critical zone between low and high-entropy states. We propose fractal shapes as a measure of proximity to this critical point, as fractal dimension encodes information about complexity beyond simple entropy or randomness, and fractal structures are known to emerge in systems nearing a critical point. To validate this, we tested several measures of fractal dimension on the brain activity from healthy volunteers and patients with disorders of consciousness of varying severity. We used a Compact Box Burning algorithm to compute the fractal dimension of cortical functional connectivity networks as well as computing the fractal dimension of the associated adjacency matrices using a 2D box-counting algorithm. To test whether brain activity is fractal in time as well as space, we used the Higuchi temporal fractal dimension on BOLD time-series. We found significant decreases in the fractal dimension between healthy volunteers (n = 15), patients in a minimally conscious state (n = 10), and patients in a vegetative state (n = 8), regardless of the mechanism of injury. We also found significant decreases in adjacency matrix fractal dimension and Higuchi temporal fractal dimension, which correlated with decreasing level of consciousness. These results suggest that cortical functional connectivity networks display fractal character and that this is associated with level of consciousness in a clinically relevant population, with higher fractal dimensions (i.e. more complex) networks being associated with higher levels of consciousness. This supports the hypothesis that level of consciousness and system complexity are positively associated, and is consistent with previous EEG, MEG, and fMRI studies.
PMID: 32053587 PMCID: PMC7017993 DOI: 10.1371/journal.pone.0223812