Abstract
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.
Highlights
Research into the neural origins of conscious experience has suggested that consciousness may be associated with the “complexity” of information processing in the brain [1, 2]
In Lempel-Ziv compressibility (LZC) analyses a maximally random signal would be indicated as having the highest “complexity.” This is, a somewhat counterintuitive understanding of what we mean when we talk about the “complexity” of brain activity: the brain is complex not because it is highly random, but because it combines an incredible degree of order with a high degree of unpredictability
In this study we found that the complexity of functional connectivity networks, as measured by the fractal dimension, was significantly associated with level of consciousness in healthy volunteers and patients with DOC of varying severity
Summary
Research into the neural origins of conscious experience has suggested that consciousness may be associated with the “complexity” of information processing in the brain [1, 2]. Is the brain both structured and unpredictable, it shows one of the hallmarks of complex systems writ large: emergent dynamics over multiple scales. With this in mind, we strongly feel that consciousness science requires further discussion and refinement of what “complexity” means in the context of the brain. We propose that complexity should be understood as a fundamentally multi-scale phenomena, emerging in systems that display both a high degree of emergent structure and organization as well incompressible and unpredictable features
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