Neuroscience Model

Neuroscience models aim to replicate brain function and learning mechanisms using computational approaches, primarily to understand the brain's workings and develop more efficient AI. Current research focuses on improving model training efficiency and stability, exploring architectures like predictive coding networks and spiking neural networks, and incorporating biologically plausible features such as neuromodulation and astrocytic self-repair. These advancements are leading to more accurate and robust models for analyzing neuroimaging data, quantifying behavior in psychiatric research, and potentially informing the design of novel, brain-inspired computing systems.