The University of Chicago Research Funding

• Principal Investigator: Daniel Margoliash, PhD, Professor, Department of Organismal Biology and Anatomy, Department of Psychology, Committee on Neurobiology, Committee on Computational Neuroscience
• Start Date: July 17, 2009
• Total Award Amount: $188,261

Public Health Relevance

Successful development of this approach would give quantitative neurophysiological insight into complex acoustic object and sequence recognition behavior while developing an approach of general utility to cortical sensory physiology.

Project Description

Auditory neurons are characterized by their receptive field properties, which describe the organization of parameters such as frequency and amplitude of stimuli that the neurons respond to. Receptive fields are relatively better described for neurons at lower levels of the auditory system, but higher-order neurons exhibit complex non-linearities that have resisted systematic quantification. Characterization of higher-order receptive fields, however, is fundamental to understanding normal and abnormal auditory perceptual processes, and also may help optimize performance of prosthetic devices. An attractive model system has been described whereby high-order auditory neurons in starlings become highly selective for acoustic objects ("motifs") embedded in natural signals (songs). Recent results implicate remarkable sequence parsing abilities of starlings that exhibit sensitivity to prototypic grammar-like structures.

In the proposed research, novel statistical techniques will be combined with physiological recordings of "cmHV" neurons of starlings whose song recognition behavior is under operant control. In the first experiment, the statistical methodologies will be developed for learning efficient basis sets for motif structure and for estimating feature-based receptive fields with hierarchical non-linear regression, using Markov random fields of Bayesian inference models and incorporating non-linear temporal dynamics. In the second experiment, operant procedures will be used to identify natural features of motifs and parameters of motif sequences that starlings utilize in song recognition behavior. In the third experiment, cmHV responses will be characterized, with emphasis on analysis of the features identified by behavioral testing, and using the statistical methods for characterization of non-linear properties.

This award is funded under the American Recovery and Reinvestment Act of 2009, NIH Award number: 3R01DC007206-05S1