Cerebrum: A New Framework for Simulating Brain Networks
A groundbreaking new framework, Cerebrum, combines biologically-inspired Hodgkin-Huxley neuron models with graph neural networks to simulate and infer synaptic connectivity in large-scale brain networks. Trained and evaluated on three canonical network topologies (Erdős-Rényi, small-world, and scale-free), Cerebrum demonstrated more accurate and robust connectivity inference with scale-free networks. Integrating empirical synaptic data from C. elegans and simulating disease effects (e.g., Parkinson's, epilepsy), Cerebrum is released as an open-source toolkit to foster collaboration and accelerate progress in computational neuroscience. This advancement promises to improve our understanding of brain networks and drive innovation in neuroscience and clinical practice.