CAREER: Cortical Mechanisms of Sound Localization

University Of California-Riverside, Riverside CA

Investigators

Abstract

The cerebral cortex contains maps that represent various features of the sensory world. For example, the visual cortex contains a map of an animal's visual space and the auditory cortex contains a map of the animal's frequency hearing range. In addition to these basic brain maps, there are also maps of features that are behaviorally important to the animal. Typically these brain maps arise through complex integrations performed by neurons, but the mechanisms of these computations are not understood. Through the experiments described here, the investigator will provide fundamental insights into the construction and modulation of such computational maps and will determine how neural connections in the brain shape computational maps. The specific focus of this project is to determine how maps that underlie an animal's ability to localize a sound are formed in the auditory cortex. The investigator and his students will use electrophysiological methods to record from neurons to determine 2-D spatial sensitivity. The input/output connections of these neurons will be identified using neuro-anatomical tracing. The neurotransmitters involved in shaping responses will be determined using pharmacology. Finally, the behavioral role of these computations will be examined with behavioral testing. This research will provide insights on how cortical maps are shaped in normal brains and how brain computations may be disrupted in mental disorders. The broader impacts of this project will include training of undergraduate and graduate students, including underrepresented minorities. The research training will be integrated with undergraduate education at the University of California, Riverside and community outreach will occur through collaborations with the California Science Center (serving inner city schools in Los Angeles) and a desert research station (educating federal and state park employees). In addition, novel neural computations discovered here will guide construction of new electronic devices with potentially wide applications.