The human brain is unique in the animal kingdom and capable of complex thinking, learning, and adaptation. Part of this ability comes from the "criticality" of neural networks within our brains. The concept of criticality refers to a balanced state between stability and flexibility. This balance allows brain networks to adapt to new information while maintaining a steady state. While criticality is widely accepted, its complexities are yet to be fully explored.

In this Research Topic, our goal is to understand further the effect of criticality on the brain's activity and its role in processing information. Specifically, we intend to develop new computational models, drawing inspiration from the theory of self-organized criticality and intermittent criticality, explaining how critical states influence the brain's normal and pathological dynamics. By doing this, we expect to gain a more comprehensive understanding of the brain's processing properties and apply these insights to design brain-machine interfaces.

We welcome Original Research, Reviews, and Perspective pieces addressing the concept of criticality in neural systems and its role in shaping brain activity. Topics can range from the basic neural principles of criticality and mathematical and computational models to understanding brain dynamics influenced by critical states to the applications of these insights in technological fields. We encourage novelty in concepts, methodology, and interdisciplinary approaches, and we also highly value detailed yet accessible explanations suitable for a broad audience.

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Exploring the Role of Criticality in Neural Systems