Functional Models of Mouse Visual Cortex

We develop machine learning methods to decipher the neural code that links perception with the firing of neurons in the cerebral cortex. We deploy Bayesian graphical models for holistic neuron data analysis to provide a framework for understanding the neural circuitry, which is unattainable with current single neuron methods. The proposed models are data-driven and capture the probabilistic conditional dependencies between the neural activity and the visual stimuli.