Abstract
Brains face selective pressure to optimize computation, broadly defined. This is achieved by mechanisms including development, plasticity, and homeostasis. Is there a universal optimum around which the healthy brain tunes itself, across time and individuals? The criticality hypothesis posits such a setpoint. Criticality is a state imbued with internally generated, multiscale, marginally stable dynamics that maximize the features of information processing. Experimental support emerged two decades ago and has accumulated at an accelerating pace despite disagreement. Here, we lay out the logic of criticality as a general computational endpoint and review experimental evidence. We perform a meta-analysis of 140 datasets published between 2003 and 2024. We find that a long-standing controversy is the product of a methodological choice with no bearing on underlying dynamics. Our results suggest that a new generation of research can leverage criticality-as a unifying principle of brain function-to accelerate understanding of behavior, cognition, and disease.