Using as a starting point the postulate that sensory systems have evolved to perform optimal transformations on behaviorally relevant or natural stimuli, we will use systems analysis methods and information theoretic principles to develop a theory of auditory processing. The goals of our theory will be to predict the stimulus-response transformations that are found at different stages of auditory processing. First, we will obtain theoretical predictions for the distribution of linear receptive fields by jointly maximizing signal to noise ratio and entropy in the output of the ensemble of filters when presented with natural sounds. Second, we will derive non-linear stimulus-response transformations that can be obtained with biologically plausible networks and that will minimize the mutual information across neurons. These neural networks will perform a form of independent component analysis, in which the resulting operation is to extract independent acoustical features in natural sounds. We will also develop novel methods to estimate the information transmitted by single neurons and ensembles of neurons in songbirds. The goodness of fit of the theoretical models will be assessed in two steps. First we will compare the theoretical stimulus-response functions with the functions of the same order that will be obtained directly from the neural data. Second, we will evaluate how well the stimulus-response functions describe the actual neural transformation by comparing predicted responses and predicted information rates with actual responses and measured information rates. Our analysis will give us insight on how complex natural sounds are processed in the auditory system of animals and humans. Understanding how biological systems process natural sounds will be instrumental in the development of novel algorithms in engineering applications for sound compression, speech recognition and sound pre-processing for hearing aids and auditory prosthetics.

Agency
National Institute of Health (NIH)
Institute
National Institute on Deafness and Other Communication Disorders (NIDCD)
Type
Research Project (R01)
Project #
5R01DC007293-03
Application #
7076972
Study Section
Special Emphasis Panel (ZRG1-MDCN-G (50))
Program Officer
Platt, Christopher
Project Start
2004-07-01
Project End
2008-06-30
Budget Start
2006-07-01
Budget End
2008-06-30
Support Year
3
Fiscal Year
2006
Total Cost
$209,291
Indirect Cost
Name
University of California Berkeley
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
124726725
City
Berkeley
State
CA
Country
United States
Zip Code
94704
Elie, Julie E; Theunissen, Frédéric E (2015) Meaning in the avian auditory cortex: neural representation of communication calls. Eur J Neurosci 41:546-67
Perez, Emilie C; Elie, Julie E; Boucaud, Ingrid C A et al. (2015) Physiological resonance between mates through calls as possible evidence of empathic processes in songbirds. Horm Behav 75:130-41
Mouterde, Solveig C; Theunissen, Frédéric E; Elie, Julie E et al. (2014) Acoustic communication and sound degradation: how do the individual signatures of male and female zebra finch calls transmit over distance? PLoS One 9:e102842
Mouterde, Solveig C; Elie, Julie E; Theunissen, Frédéric E et al. (2014) Learning to cope with degraded sounds: female zebra finches can improve their expertise in discriminating between male voices at long distances. J Exp Biol 217:3169-77
Theunissen, Frederic E; Elie, Julie E (2013) Population code, noise correlations, and memory. Neuron 78:209-10
Elliott, Taffeta M; Hamilton, Liberty S; Theunissen, Frédéric E (2013) Acoustic structure of the five perceptual dimensions of timbre in orchestral instrument tones. J Acoust Soc Am 133:389-404
Gastpar, Michael C; Gill, Patrick R; Huth, Alexander G et al. (2010) Anthropic Correction of Information Estimates and Its Application to Neural Coding. IEEE Trans Inf Theory 56:890-900
Woolley, Sarah M N; Hauber, Mark E; Theunissen, Frederic E (2010) Developmental experience alters information coding in auditory midbrain and forebrain neurons. Dev Neurobiol 70:235-52
Vu, Vincent Q; Yu, Bin; Kass, Robert E (2009) Information in the nonstationary case. Neural Comput 21:688-703
Woolley, Sarah M N; Gill, Patrick R; Fremouw, Thane et al. (2009) Functional groups in the avian auditory system. J Neurosci 29:2780-93

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