During natural listening conditions we effortlessly attend to a single speaker despite high levels of superfluous background clutter. Humans and mammals easily filter important biological signal such as speech and vocalizations amongst high levels of noise; yet artificial speech recognition systems using computer technologies fail miserably at this seemingly simple computational task. The brains of mammals have evolved elaborate neuronal coding strategies for dealing with computational problems that are relevant behaviorally, and we are interested in identifying such strategies. How does the brain consolidate sound information from the environment into a single perceptual and cognitive experience? We study this question at the single neuron and cellular network level by employing a variety of electrophysiological, optical imaging, and systems theoretic approaches in the mammalian auditory system. Aside from helping us develop a general theory for the “neuronal code”, such an understanding could significantly benefit the design of optimal speech recognition systems and could improve preprocessing strategies for assistive hearing devices (e.g., hearing aids and cochlear implants).
●Neuronal mechanisms underlying sound analysis, detection, and recognition
●Topographic organization of receptive field preferences in the Inferior Colliculus and Auditory Cortex
●Optical imaging of auditory cortex
●Neuronal mechanisms involved in impaired auditory cortical processing
●Anatomical organization in the inferior colliculus and auditory cortex
●Neuronal modeling and Information Processing of single neurons
