A multi-scale extension of the Fisher information metric, derived from coarse-graining contraction rules, exactly captures the structure of mutual information in neural population codes and can be estimated via diffusion models.
Mutual information and minimum mean- square error in gaussian channels.IEEE Transactions on Information Theory, 51(4):1261–1282
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A multi-scale information geometry reveals the structure of mutual information in neural populations
A multi-scale extension of the Fisher information metric, derived from coarse-graining contraction rules, exactly captures the structure of mutual information in neural population codes and can be estimated via diffusion models.