Natural Sounds and Neural Coding
Principal Investigator : Kamal Sen
How do neurons in the brain encode complex natural sounds? What are the neural substrates of selectivity and discrimination of different categories of natural sounds? How are these substrates shaped by learning?
The Natural Sounds and Neural Coding Laboratory investigates these questions 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.