Universality of neural population coarse-graining exponents
In plain words
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 statement
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.
What would settle it
The same analysis applied to many large recordings and to model networks with known critical and non-critical states, showing which exponents are universal.
Status in the literature
Unverified 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.
Related problems
- Special case of Is the brain poised near a critical point?