Is criticality a unified set-point of brain function?

Brains face selective pressure to optimize computation, broadly defined. This optimization is achieved by myriad mechanisms and processes that influence the brain’s computational state. These include development, plasticity, homeostasis, and more. Despite enormous variability over time and between individuals, do these diverse mechanisms converge on the same set-point? Is there a universal computational optimum around which the healthy brain tunes itself? The criticality hypothesis posits such a unified computational set-point. Criticality is a special dynamical brain state, defined by internally-generated multi-scale, marginally-stable dynamics which maximize many features of information processing. The first experimental support for this hypothesis emerged two decades ago, and evidence has accumulated at an accelerating pace, despite a contentious history. Here, we lay out the logic of criticality as a general computational end-point and systematically review experimental evidence for the hypothesis. We perform a meta-analysis of 143 datasets from manuscripts published between 2003 and 2024. To our surprise, we find that a long-standing controversy in the field is the product of a simple methodological choice that has no bearing on underlying dynamics. Our results suggest that a new generation of research can leverage the concept of criticality—as a unifying principle of brain function–to accelerate our understanding of behavior, cognition, and disease.