Brain Simulation

Brain simulation aims to create computational models that accurately replicate the structure and function of the brain, from individual neurons to entire brain regions, ultimately seeking to understand biological intelligence and build more sophisticated AI. Current research focuses on developing differentiable simulators, enabling efficient optimization and training of biologically realistic spiking neural networks (SNNs) using advanced algorithms and parallel computing techniques. These efforts leverage diverse data sources, including electrophysiological recordings, anatomical connectivity maps, and behavioral observations, to build multi-scale models and assess their performance on cognitive tasks. The resulting simulations are valuable tools for neuroscience research, informing our understanding of brain function and dysfunction, and also for advancing brain-inspired artificial intelligence.