Neural System

Neural systems research aims to understand how biological brains process information and learn, often using artificial neural networks (ANNs) as models. Current research focuses on developing biologically plausible learning algorithms (e.g., counter-current learning), addressing challenges like catastrophic forgetting in lifelong learning (e.g., using DriftNet), and exploring the role of spatiotemporal dynamics in computation. This work has implications for improving the robustness, efficiency, and interpretability of AI systems, while simultaneously deepening our understanding of biological neural mechanisms and potentially leading to more efficient and adaptable AI architectures.