Learning Path

Linear Algebra Fundamentals → Network Dynamics and Stability

This learning path guides computational neuroscience students through the essential concepts and models of neural networks, from foundational mathematics to advanced recurrent and attractor networks. It covers feedforward networks, recurrent dynamics, and learning rules, providing a systematic understanding of how neural computations emerge from network architectures.