RESEARCH FIELD

Computational Neuroscience

Computational neuroscience constructs mathematical and computational models of neural circuits and systems to understand how the brain processes information, generates behavior, and learns. At the single-neuron level, conductance-based models capture the biophysics of spike generation; at the network level, attractor dynamics explain working memory and decision-making. Large-scale connectomics projects map the synaptic wiring of entire neural circuits at electron-microscope resolution, providing ground-truth data for model validation. Modern recording technologies capturing thousands of neurons simultaneously are driving a renaissance in understanding distributed computation in the cortex, with implications for brain-computer interfaces and AI architectures.