The overall goal of research is to gain an understanding of the neural mechanisms underlying sound pattern recognition. Experiments proposed in this application are designed to study how the spectral and temporal attributes of a sound (i.e., signal) in free-field are represented in the central auditory system when the signal is embedded in noise (or interfering sound) originating from a spatially segregated source. It is well known that the ability of the auditory system to extract a sound in the presence of another is constrained by masking. Thus the specific goal of the proposed physiological experiments is to validate several hypotheses pertaining to how masking by noise is released by the angular separation of the signal and noise sources, whereby the signal can be extracted by the nervous system. The experimental design has elements in common with hearing in a """"""""cocktail party"""""""" involving coherent perception of the location and patterns of a sound in the presence of other competing sounds. The proposed study will be conducted from the torus semicircularis (or inferior colliculus, IC) of the green treefrog for which the ability to perceive coherently is vital for reproductive success. The research plan will make use of different probe stimuli (both simple as well as complex sounds). Furthermore, the effects of simultaneous and forward making will be evaluated and compared. Finally, the role of binaural inhibition in spatially-mediated release from masking will be assessed in order to gain insight into the cellular underpinning of the underlying neural processes. Response of a single IC unit to a probe stimulus (presented within the unit's best spatial receptive field) plus a masker originating from a different azimuth and the unit's response to the masker alone will be analyzed and compared. Results deriving from this research will be interpreted, insomuch as possible, within the context of behavioral framework (i.e., signal detection). We expect the outcome to generate insight into the neural computational algorithm for extracting desired signals in the presence of interfering sounds. This is important basic knowledge, but the knowledge gained can also shed light on practical applications, e.g., on design of intelligent hearing aid devices.
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