Jun-nosuke Teramae

This study shows that high-dimensional neural activity self-organizes in dissociated cultures without sensory input, exhibiting power-law decay and spatial patterns linked to self-organized criticality.

This paper proposes a biologically plausible learning algorithm based on dual stochasticity in the cortex, showing it accounts for efficient power-law coding and overcomes limitations of conventional neural network learning.