Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Cambridgeshire, England, United Kingdom.
Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridgeshire, England, United Kingdom.
PLoS One. 2020 Feb 13;15(2):e0223812. doi: 10.1371/journal.pone.0223812. eCollection 2020.
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.
最近的证据表明，意识体验的数量和质量可能是大脑活动复杂性的函数，意识出现在低熵和高熵状态之间的临界点。我们提出分形形状作为接近这个临界点的度量，因为分形维数编码了关于复杂性的信息，超越了简单的熵或随机性，并且已知分形结构出现在接近临界点的系统中。为了验证这一点，我们在来自健康志愿者和不同严重程度意识障碍患者的大脑活动上测试了几种分形维数的测量方法。我们使用紧凑型盒燃烧算法计算皮质功能连接网络的分形维数，以及使用二维盒计数算法计算相关邻接矩阵的分形维数。为了测试大脑活动在时间和空间上是否具有分形性质，我们使用了基于 BOLD 时间序列的 Higuchi 时间分形维数。我们发现，无论损伤机制如何，健康志愿者（n = 15）、处于最小意识状态的患者（n = 10）和处于植物状态的患者（n = 8）之间的分形维数都显著降低。我们还发现邻接矩阵分形维数和 Higuchi 时间分形维数显著降低，这与意识水平的降低相关。这些结果表明，皮质功能连接网络显示出分形特征，并且这与具有临床意义的人群中的意识水平相关，具有较高分形维数（即更复杂）的网络与较高的意识水平相关。这支持了意识水平和系统复杂性呈正相关的假设，并且与之前的 EEG、MEG 和 fMRI 研究一致。
