Clear Mind: Meditation and the Brain's Signal-to-Noise Ratio
Abstract
Meditation is quintessentially associated with a clear mind. This paper proposes that diverse findings in the science of meditation can be mapped onto a single, empirically tractable construct: functional signal-to-noise ratio in the brain, or f-SNR. Signal denotes neural variance that tracks the goal-relevant causes of sensory input, while noise denotes residual activity, including irrelevant endogenous fluctuations. Mechanistically, meditation increases f-SNR through two primary operations: se...
Description / Details
Meditation is quintessentially associated with a clear mind. This paper proposes that diverse findings in the science of meditation can be mapped onto a single, empirically tractable construct: functional signal-to-noise ratio in the brain, or f-SNR. Signal denotes neural variance that tracks the goal-relevant causes of sensory input, while noise denotes residual activity, including irrelevant endogenous fluctuations. Mechanistically, meditation increases f-SNR through two primary operations: selectively enhancing signal and "decluttering" noise. Deepening practice is further proposed to increase f-SNR by reducing self-referential filtering and shifting global neural activity toward a critical regime, a thermodynamically efficient state that maximizes information transmission and dynamic range. This framework has a strong existing evidence base and is readily falsifiable using metrics such as neural variability quenching, mutual information, and multivariate decoding. The f-SNR account also offers a transdiagnostic explanation for the efficacy of meditation across a range of psychopathologies associated with low-SNR states. The theory also has implications for emerging technology: meditation may improve brain-computer interfaces, or BCIs, by making brain activity easier to read.
Source: arXiv:2606.29698v1 - http://arxiv.org/abs/2606.29698v1 PDF: https://arxiv.org/pdf/2606.29698v1 Original Link: http://arxiv.org/abs/2606.29698v1
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Jun 30, 2026
Neuroscience
Neuroscience
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