Central Auditory Processing and Neural Modeling

1. Front Matter

   Pages i-x

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2. Processing of Vocalization Signals in Neurons of the Inferior Colliculus and Medial Geniculate Body

   • Josef Syka, Jiri Popelář, Eugen Kvašňák, Daniel Šuta

   Pages 1-11

3. Coding of FM and AM Sounds at the Auditory Midbrain

   • Paul W. F. Poon, T. W. Chiu, Xinde Sun

   Pages 13-22

4. Inhibition and Inhibitory Plasticity in the Mammalian Auditory Midbrain

   • Mike B. Calford, Yuri Saalmann

   Pages 23-30

5. Neuronal Periodicity Coding and Pitch Effects

   • Gerald Langner

   Pages 31-41

6. Specializations of the Auditory System for the Analysis of Natural Sounds

   • Israel Nelken, Yaron Rotman, Omer Bar Yosef

   Pages 43-53

7. The Processing of Species-Specific Complex Sounds by the Ascending and Descending Auditory Systems

   • Nobuo Suga, Jun Yan, Yunfeng Zhang

   Pages 55-70

8. Speech Recognition Using Dynamic Programming of Bayesian Neural Networks

   • Chaug-Ching Huang, Jhing-Fa Wang, Chung-Hsien Wu, Jau-Yien Lee

   Pages 71-76

9. A Computational Model of Birdsong Learning by Auditory Experience and Auditory Feedback

   • Kenji Doya, Terrence J. Sejnowski

   Pages 77-88

10. On Recent Results in Modeling of Sensory Neurons

    • Petr Lánský

    Pages 89-99

11. Interneurons Which Shape Response Properties in Dorsal Cochlear Nucleus

    • Eric D. Young, Israel Nelken

    Pages 101-115

12. Behavioral and Physiological Studies of Sound Localization in the Cat

    • Tom C. T. Yin, Luis C. Populin

    Pages 117-127

13. The Processing of Auditory Stimuli for Eye Movements in the Posterior Parietal Cortex of Monkeys

    • Richard A. Andersen, Alexander Grunewald, Jennifer F. Linden

    Pages 129-138

14. Location Coding by Auditory Cortical Neurons

    • John C. Middlebrooks

    Pages 139-148

15. Spatial Receptive Field Properties of Primary Auditory Cortical Neurons

    • Richard A. Reale, John F. Brugge, Joseph E. Hind

    Pages 149-160

16. Models of Direction Estimation with Spherical-Function Approximated Cortical Receptive Fields

    • Rick L. Jenison

    Pages 161-174

17. Medical Image Data Compression Using Cubic Convolution Spline Interpolation

    • T. K. Truong, Lung-Jen Wang

    Pages 175-188

18. Independent Component Analysis of Electroencephalographic and Event-Related Potential Data

    • Tzyy-Ping Jung, Scott Makeig, Anthony J. Bell, Terrence J. Sejnowski

    Pages 189-197

19. Time Structure of Cortical Activity

    • Yifat Prut, Moshe Abeles

    Pages 199-210

20. Organization and Perturbation of NeuronalAssemblies

    • George L. Gerstein, Marc J. Bloom, Pedro E. Maldonado

    Pages 211-224

The full power of combining experiment and theory has yet to be unleashed on studies of the neural mechanisms in the brain involved in acoustic information processing. In recent years, enormous amounts of physiological data have been generated in many laboratories around the world, characterizing electrical responses of neurons to a wide array of acoustic stimuli at all levels of the auditory neuroaxis. Modern approaches of cellular and molecular biology are leading to new understandings of synaptic transmission of acoustic information, while application of modern neuro-anatomical methods is giving us a fairly comprehensive view ofthe bewildering complexity of neural circuitry within and between the major nuclei of the central auditory pathways. Although there is still the need to gather more data at all levels of organization, a ma­ jor challenge in auditory neuroscience is to develop new frameworks within which existing and future data can be incorporated and unified, and which will guide future laboratory ex­ perimentation. Here the field can benefit greatly from neural modeling, which in the central auditory system is still in its infancy. Indeed, such an approach is essential if we are to address questions related to perception of complex sounds including human speech, to the many di­ mensions of spatial hearing, and to the mechanisms that underlie complex acoustico-motor behaviors.

• brain
• cognition
• cortex
• information processing
• neural mechanisms
• neural modeling
• neural networks
• neurons
• neuroscience
• perception

• National Cheng Kung University, Tainan, Taiwan

  Paul W. F. Poon

• University of Wisconsin, Madison, USA

  John F. Brugge

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