Modeling the auditory functions in the primary cortex

Neurons in the primary auditory cortex exhibit distinctive selectivities in responses to various acoustic features. Recent physiological studies suggest three spatial dimensions along which the neural response patterns can be systematically organized: the tuning frequencies of the neurons are logarithmically mapped on the tonotopic axis, and the shapes of the tuning curves, in terms of symmetry and bandwidth, vary gradually along two other spatial dimensions. In this report, it is shown that these variations can be effectively modeled by a complex wavelet transform. With such a tie, one can employ well- established wavelet theories into analyzing and understanding how acoustic signals are processed in the auditory system, and thereby design novel engineering applications that are perceptually oriented.

[1]  C E Schreiner,et al.  Functional topography of cat primary auditory cortex: distribution of integrated excitation. , 1990, Journal of neurophysiology.

[2]  S. A. Shamma The Auditory Processing of Speech. , 1986 .

[3]  Biing-Hwang Juang,et al.  On the use of bandpass liftering in speech recognition , 1987, IEEE Trans. Acoust. Speech Signal Process..

[4]  Shihab A. Shamma,et al.  A Functional Model of Primary Auditory Cortex: Spectral Orientation Columns , 1990 .

[5]  Deepen Sinha,et al.  On the optimal choice of a wavelet for signal representation , 1992, IEEE Trans. Inf. Theory.

[6]  Shihab A. Shamma,et al.  Hearing As Seeing Space and Time in Auditory Processing , 1992 .

[7]  Kuansan Wang,et al.  Self-normalization and noise-robustness in early auditory representations , 1994, IEEE Trans. Speech Audio Process..

[8]  Stéphane Mallat,et al.  Matching pursuits with time-frequency dictionaries , 1993, IEEE Trans. Signal Process..

[9]  S. A. Shamma,et al.  Representation of Spectral Profiles in the Auditory Systems , 1992 .

[10]  Stéphane Mallat,et al.  Characterization of Signals from Multiscale Edges , 2011, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Rama Chellappa,et al.  A unified approach to boundary perception: edges, textures, and illusory contours , 1993, IEEE Trans. Neural Networks.

[12]  Ingrid Daubechies,et al.  The wavelet transform, time-frequency localization and signal analysis , 1990, IEEE Trans. Inf. Theory.

[13]  Stéphane Mallat,et al.  Multifrequency channel decompositions of images and wavelet models , 1989, IEEE Trans. Acoust. Speech Signal Process..

[14]  K. Wang Neural Networks That Recognize Phonemes by Their Acoustic Features , 1991 .

[15]  S. Shamma,et al.  Organization of response areas in ferret primary auditory cortex. , 1993, Journal of neurophysiology.

[16]  J. Flanagan Speech Analysis, Synthesis and Perception , 1971 .

[17]  C E Schreiner,et al.  Topography of excitatory bandwidth in cat primary auditory cortex: single-neuron versus multiple-neuron recordings. , 1992, Journal of neurophysiology.

[18]  M. Goldstein,et al.  Single-unit activity in the primary auditory cortex of unanesthetized cats. , 1968, The Journal of the Acoustical Society of America.

[19]  Olivier Rioul,et al.  Fast algorithms for discrete and continuous wavelet transforms , 1992, IEEE Trans. Inf. Theory.

[20]  Kuansan Wang,et al.  Modeling the spectral transition selectivity in the primary auditory cortex , 1993, Neural Networks for Signal Processing III - Proceedings of the 1993 IEEE-SP Workshop.