Explores the learning dynamics of deep neural networks using linear networks for analysis, covering two-layer and multi-layer networks, self-supervised learning, and benefits of decoupled initialization.
Covers spontaneous brain network activity, neural simulation, and validation, emphasizing the importance of in-vitro and in-vivo conditions for accurate network modeling.
