The Natural Sounds and Neural Coding Laboratory investigates how neurons in the brain encode complex natural sounds, the neural substrates of selectivity and discrimination of different categories of natural sounds, and how these substrates are shaped by learning, in the model system of the songbird. Electrophysiological techniques are used to record neural responses from hierarchical stages of auditory processing. Theoretical methods from areas such as statistical signal processing, systems theory, probability theory, information theory and pattern recognition are applied to characterize how neurons in the brain encode natural sounds. Computational models are constructed to understand the processing of natural sounds both at the single neuron and the network level, to model neural selectivity and discrimination, and to explore the role of learning in shaping the neural code.
Director Kamal Sen