350 citations · 693 across the 14 of their papers we have counts for
16 papers
Space versus Context: Competition for limited neural resources determines engram cell allocation in the hippocampus
Kensuke Chiba, Jun-nosuke Teramae
Engram cells in hippocampal CA1 represent contextual information associated with events experienced by animals and constitute a cellular substrate of episodic memory. Recent experi…
Learning reshapes power-law anisotropy in internal representations
Asahi Nakamuta, Jun-nosuke Teramae
Power-law anisotropy in internal representations has been observed across a wide range of biological and artificial neural systems, from state-of-the-art language models to the mou…
The Impact of Anisotropic Covariance Structure on the Training Dynamics and Generalization Error of Linear Networks
Taishi Watanabe, Ryo Karakida, Jun-nosuke Teramae
The success of deep neural networks largely depends on the statistical structure of the training data. While learning dynamics and generalization on isotropic data are well-establi…
Spectral density of correlated random matrices and nonmonotonic stability in hetero-associative memory networks
Arata Tomoto, Jun-nosuke Teramae
Random matrix theory, which characterizes spectral distributions of infinitely large matrices, plays a central role across diverse fields, including high-dimensional data analysis,…
Dynamical mean-field theory for a highly heterogeneous neural population
Futa Tomita, Jun-nosuke Teramae
Large-scale systems with inherent heterogeneity often exhibit complex dynamics that are crucial for their functional properties. However, understanding how such heterogeneity shape…
Energy-information trade-off makes the cortical critical power law the optimal coding
Tsuyoshi Tatsukawa, Jun-nosuke Teramae
Stimulus responses of cortical neurons exhibit the critical power law, where the covariance eigenspectrum follows the power law with the exponent just at the edge of differentiabil…