22The brain is possibly the most complex system known to mankind, and its complexity has 23 been called upon to explain the emergence of consciousness. However, complexity can take 24 many forms: here, we investigate measures of algorithmic and process complexity in both the 25 temporal and topological dimension, testing them on functional MRI data obtained from indi-26 viduals undergoing various levels of sedation with the anaesthetic agent propofol, in two separate 27 datasets. We demonstrate that the various measures are differently able to discriminate between 28 levels of sedation, with temporal measures showing higher sensitivity. Further, we show that 29 all measures are strongly related to a single underlying construct explaining most of the vari-30 ance, as assessed by Principal Component Analysis, which we interpret as a measure of overall 31 complexity of our data. This overall complexity was also able to discriminate between levels of 32 sedation, supporting the hypothesis that consciousness is related to complexity -independent 33 of how the latter is measured. 34 1 Introduction 35 The science of complex systems has gained increasing prominence in the 21st century. It combines 36 the reductionist ideal of science, with the notion of emergence, whereby high-level phenomena can 37 result from the interactions of simple constituent parts, confirming Aristotle's saying that the whole 38 is more than the sum of its parts [1]. However, complexity science is also a discipline still in its 39 infancy. In particular, due to its appealing and apparently intuitive nature, the notion of complex-40 ity has remained relatively ill-defined. The interdisciplinary nature of this science has resulted in 41 different fields applying the term complexity to multiple quantities, variously measured. ity is perhaps best understood as the negation of simplicity. A system exhibits complex behaviour 43 when it is not uniform, stereotyped, or predictable. However, there is a key assumption that this 44 is not sufficient: complexity must emerge from the underlying orderly interactions of a system's 45 components, about which its behaviour must provide information in other words, its unpredictabil-46 ity must be more than mere randomness, but rather the result of interesting behaviours emerging. 47 a crystal and complete disorder, as exhibited for instance by the random motion of molecules of 49 2 a gas. Complexity can be identified in more than one dimension of the same system, too. It may 50 be due to the structure of the interactions between components, such as the connections in a social 51 or biological network. Or it may only become apparent over time, as when it is applied to signals 52 and temporal patterns. Furthermore, there are different ways in which something can be said to be 53 complex, reflected in the different ways that have been developed to estimate complexity. On the 54 one hand, methods from algorithmic information theory such as Shannon entropy and Lempel-Ziv 55 compressibility [2, 3] emphasise unpre...
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 on the axes of order/randomness and integration/differentiation. 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 the 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 predictive of level of consciousness in a clinically relevant population, with more fractal (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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.