Meditation boosts brain's signal-to-noise ratio, new theory suggests

A new paper from Ruben Laukkonen (arXiv:2606.29698) proposes that meditation's diverse cognitive benefits can be traced to a single measurable construct: functional signal-to-noise ratio (f-SNR). In this framework, 'signal' refers to neural variance tracking goal-relevant sensory input, while 'noise' includes irrelevant endogenous fluctuations like self-referential thoughts. Meditation increases f-SNR through two operations: selectively amplifying relevant signals and 'decluttering' noise. Deeper practice also reduces self-referential filtering and shifts the brain toward a critical regime—a thermodynamically efficient state that maximizes information transmission and dynamic range.

The theory has strong implications for emerging technology. By sharpening neural signals, meditation may make brain-computer interfaces (BCIs) easier to read, potentially improving accuracy for thought-controlled devices. It also offers a transdiagnostic explanation for meditation's efficacy across conditions like anxiety and depression, which are characterized by low-SNR brain states. The framework is readily falsifiable using metrics such as neural variability quenching, mutual information, and multivariate decoding, grounding ancient practice in modern computational neuroscience.