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Accepted · first revision · record

Title: Universality of neural population coarse-graining exponents
Plain: Grouping correlated neurons step by step, as physicists do near phase transitions, gives scaling exponents in mouse brain recordings. Whether these numbers are the same across brain regions and animals, as a true fixed point would require, is open.
Precise: Apply phenomenological renormalization-group coarse-graining (iteratively merging maximally correlated neurons; Meshulam and co-workers, 2019) to recordings of $N \ge 10^{3}$ neurons and measure the variance-scaling exponent, the covariance-eigenvalue exponent and the dynamic exponent. Determine whether they are universal across regions, species and behavioral states, and identify the model class whose fixed point produces them.
Settled by: The same analysis applied to many large recordings and to model networks with known critical and non-critical states, showing which exponents are universal.
Kind: well-posed
Answer type: classification
References: (empty)
Literature status: partially-resolved
Status note: Studies in 2024 to 2026 report similar exponents in other regions and in human brain imaging; whether they indicate a fixed point is unresolved.
Posed since: 2019