Abstract
The excellence of the brain is its robustness under various types of noise and its flexibility under various environments. However, how the brain works is still a mystery. The critical brain hypothesis proposes a possible mechanism and states that criticality plays an important role in the healthy brain. Herein, using an electroencephalography dataset obtained from patients with psychotic disorders (PDs), ultra-high risk (UHR) individuals and healthy controls (HCs), and its dynamical network analysis, we show that the brain of HCs remains around a critical state, whereas that of patients with PD falls into more stable states. Meanwhile, the brain of UHR individuals is similar to that of PD in terms of entropy but is analogous to that of HCs in causality patterns. These results not only provide evidence for the criticality of the normal brain but also highlight the practicability of using an analytic biophysical tool to study the dynamical properties of mental diseases.
Highlights
Studying the human brain is a large project, which involves investigating its organization, structure, function, and association with behavior
By analyzing the dynamical properties of the DNM group of the neural network in the brain, we found that brains of healthy controls (HCs) were at a critical state, whereas those of patients with psychotic disorders (PDs) were stuck in more stable less-critical states
Using the DNMIndex, we found the brain of HC is in a significantly more critical state than those of patients with PD and ultra-high risk (UHR) individuals in both duration deviant (dD) and frequency deviant (fD) cases (Figures 1E–F)
Summary
Studying the human brain is a large project, which involves investigating its organization, structure, function, and association with behavior. The brain should be well-structured to process information appropriately. Self-organized criticality (Cocchi et al, 2017; Lee et al, 2019) is one argument of the critical brain hypothesis, which has been supported by the neuronal avalanche phenomenon experimentally (Beggs and Plenz, 2003; Petermann et al, 2009): the size of the cortical activities exhibits power laws. Studies have found a possibility that this critical mechanism in the brain could ensure maximized capacity and transmission of information (Haldeman and Beggs, 2005; Shew et al, 2009; Shew et al, 2011). Neuronal avalanches and power laws provide important statistical descriptions of the critical brain, an intrinsic dynamical interpretation is still missing
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