Central Auditory Processing and Neural Modeling

283 Pages·1998·9.115 MB·English

by  Josef Syka, Jiri Popelář, Eugen Kvašňák (auth.), Paul W. F. Poon, John F. Brugge (eds.)

Central Auditory Processing
and Neural Modeling
Central Auditory Processing
and Neural Modeling
Edited by
PaulW.F.Poon
National Cheng Kung University
Tainan, Taiwan
and
John F. Brugge
University of Wisconsin
Madison, Wisconsin
Springer Science+Business Media, LLC
Library of Congress Cataloging-in-Publication Data
On file
Proceedings of an International Workshop on Central Auditory Processing and Neural Modeling,
held January 26-29,1997, in Kaohsiung, Taiwan
ISBN 978-1-4613-7441-1 ISBN 978-1-4615-5351-9 (eBook)
DOI 10.1007/978-1-4615-5351-9
© 1998 Springer Science+Business Media New York
Originally published by PleDIUll Press, New York in 1998
Softcover reprint of the hardcover 1s t edition 1998
http://www.plenum.com
10987654321
AII rights reserved
No part ofthis book may be reproduced, stored in a retrieval system, or transmitted in any form or by any
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permission from the Publisher
ORGANIZERS
*
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Department of Physiology, Medical College, NCKU (~ iL.!&. 7-lJ 1-JX *~ ~
Ministry of Education (~ 11 .g~ )
National Science Council (H JltPit ~ ~H* t-~ -t)
CO-ORGANIZERS
NCKU Alumni Foundation for Culture and Education, Kaohsiung (~.$!&.7-lJ *-*~
-t ~~*1t-t)
Tainan City Government (f; ~ -;p JliJit)
NCKU Alumni Association, Malaysia (,~ *-iffIli!&'7-lJ *-*;ft~ xtt*:t--t)
Kaohsiung City Government (it;.$ -;p JltJit)
Kaohsiung Hsien Government ( iii.$ ~ JltJit )
Cheng Shing Medical Foundation (!&. ~ X tt.* :t--t)
Bureau of Health, Kaohsiung City Government (it;.$ -;p JltJit ftf 1-1l] )
Council of Labor Affairs (H JlUit of t--t)
Department of Health (H JlUitftj 1-:i)
People to People International Tainan Chapter R.O,C ('f"* ~ III ~ ~;~ 3t W, -t f;
~ ~J".)
Office of Research and Developement, N*CK U (~iL.!&.7-lJ *-o:f~1t1t~*1t-t)
Kaohsiung Polytechnic Institute (~tft.x.. f;t)
Wen Tzao Ursuline Junior College of Modern Languages (x~"t! xt-fto!t;ft)
The Chinese Physiological Society ('f ~ 1-JX o!t -t)
Taiwan Neurological Association (f; J,hff4'.Ho!to!t-t)
Kaohsiung Medical College (~t1t"''' Pit)
SPONSORS
Lin Trading Co. Ltd. (If,j 1+ 1f ~ n~ 17)-t F!t ~ .;J)
Eva Air (-k ~Ait 1: ~.;J)
Gin Yuan Hotel (1t III *-1&.~)
ENDORSED BY
*
Association for Research in Otolaryngology (~ I'!f.It iJ -t)
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vi
PREFACE
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. The approach of combining experiment and theory has borne much fruit in other
systems of the brain, and it was felt that auditory researchers had much to learn from those us
ing it. It was also recognized that research on the central auditory system has a great deal to of
fer those seeking to understand fundamental mechanisms of sensory processing in the brain.
Thus, it seemed that this was the right time to bring together, in the form of a work
shop, experimentalists and theoreticians studying the central auditory system and other sen
sory systems with the hope and expectation that such a gathering would serve to nurture
deeper insight into the fundamental problems before us and to generate new ideas on how fu
ture research might accelerate the understanding of auditory cerebral function. We were not
disappointed, though only time will tell the degree to which the workshop was a success. This
volume is one result of that workshop.
We are grateful to Moshe Abeles, Tsutomu Kamada, Gerald Langner, Petr Lansky,
and JosefSyka for serving as an advisory group in putting together the workshop program, to
Pi-Hsueh Shirley Li, Mei-Ling Tsai, Shun-Sheng Chen, Ling-Ru Lee, Jih-Ing Chuang, and
Bu-Miin Huang for serving as the local organizing committee, and to Patrick Heinritz for his
valuable editorial assistance in preparing this book.
Paul Poon
John 8rugge
vii
CONTENTS
Processing of Vocalization Signals in Neurons of the Inferior Colliculus and Medial
Geniculate Body ................................................... .
Josef Syka. Jiri Popelat. Eugen K vasiHik. and Daniel Suta
Coding of FM and AM Sounds at the Auditory Midbrain. . . . . . . . . . . . . . . . . . . . . . .. 13
Paul w.F. Poon. T.w. Chiu. and Xinde Sun
Inhibition and Inhibitory Plasticity in the Mammalian Auditory Midbrain .......... 23
Mike B. Cal ford and Yuri Saalmann
Neuronal Periodicity Coding and Pitch Effects ... . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 31
Gerald Langner
Specializations of the Auditory System for the Analysis of Natural Sounds ......... 43
Israel Nelken. Varon Rotman. and Orner Bar Yosef
The Processing of Species-Specific Complex Sounds by the Ascending and
Descending Auditory Systems ......................................... 55
Nobuo Suga. Jun Van. and Yunfeng Zhang
Speech Recognition System Using Dynamic Programming of Bayesian Neural
Networks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 71
Chaug-Ching Huang. Jhing-Fa Wang, Chung-Hsien Wu, and Jau-Yien Lee
A Computational Model of Birdsong Learning by Auditory Experience and
Auditory Feedback .................................................. 77
Kenji Doya and Terrence 1. Sejnowski
On Recent Results in Modeling of Sensory Neurons. . . . . . . . . . . . . . . . . . . . . . . . . . .. 89
Petr Lansky
Interneurons Which Shape Response Properties in Dorsal Cochlear Nucleus ........ 101
Eric D. Young and Israel Nelken
Behavioral and Physiological Studies of Sound Localization in the Cat. . . . . . . . . . . .. 117
Tom c.T. Yin and Luis C. Populin
The Processing of Auditory Stimuli for Eye Movements in the Posterior Parietal
Cortex of Monkeys ..... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. 129
Richard A. Andersen, Alexander Grunewald, and Jennifer F. Linden
IX
Location Coding by Auditory Cortical Neurons ............................... 139
John C. Middlebrooks
Spatial Receptive Field Properties of Primary Auditory Cortical Neurons ........... 149
Richard A. Reale, John F. Brugge, and Joseph E. Hind
Models of Direction Estimation with Spherical-Function Approximated Cortical
Receptive Fields .................................................... 161
Rick L. Jenison
Medical Image Data Compression Using Cubic Convolution Spline Interpolation .... 175
T. K. Truong and Lung-Jen Wang
Independent Component Analysis of Electroencephalographic and Event-Related
Potential Data ...................................................... 189
Tzyy-Ping Jung, Scott Makeig, Anthony 1. Bell, and Terrence 1. Sejnowski
Time Structure of Cortical Activity 199
Yifat Prut and Moshe Abeles
Organization and Perturbation of Neuronal Assemblies ......................... 211
George L. Gerstein, Marc J. Bloom, and Pedro E. Maldonado
Neural Principles of Visual Cortical Processing: Scene Segmentation Investigated
with Microelectrodes and Models ...................................... 225
Reinhard Eckhom
Dynamic Mechanisms of Perception Exhibited by Bat Biosonar .................. 247
James A. Simmons, Michael 1. Ferragamo, Tim Haresign, Steven P. Dear, and
Mark 1. Sanderson
Poster Abstracts of the Workshop on Central Auditory Processing and Neural
Modeling .............................................................. 261
Participants' Photographs ................................................. 276
Index ................................................................. 279
x
PROCESSING OF VOCALIZATION SIGNALS IN NEURONS OF THE INFERIOR
COLLICULUS AND MEDIAL GENICULATE BODY
Josef Syka, Jiri PopehU', Eugen Kvasfuik and Daniel Suta
Institute of Experimental Medicine
Academy of Sciences of the Czech Republic
Prague 4, Czech Republic
INTRODUCTION
Animals vocalize for different reasons: to express their feeling and mood, to emit warning
signals, to communicate with individuals of the same species. Vocalization plays a specific
role in bats and other echo-locating animals where it serves for the scanning of space. Of the
vertebrates, birds in particular are known for their repertoire of vocalizations or singing.
Vocalization also plays an important role in the behavior of primates. Undoubtedly an
unprecedented and yet unknown process of the perfection and refinement of vocalization in
primates resulted in the emergence of a unique feature of the human brain -speech. Although
a great deal of knowledge has been accumulated about the production of animal calls and
their acoustical features, an understanding of the mechanisms which subserve the processing
of these signals in the brain of animals still remains to be elucidated. In the first studies, which
were mostly performed in the auditory cortex of awake monkeys in the seventies (Wollberg
and Newman, 1972; Winter and Funkenstein, 1973; Newman and Wollberg, 1973; Manley
and Muller-Preuss, 1978; Newman, 1978; Newman and Symmes, 1974), the authors expected
that they would find neurons utilizing a feature extraction like the neurons in the visual cortex.
The existence of specific cells which function as "call detectors" was not confirmed in these
studies, and the authors later came to the conclusion that the pattern discrimination of a complex
sound can be accomplished by a functional ensemble of neurons (Pelleg-Toiba and Wollberg,
1991). Muller-Preuss and Ploog (1981) demonstrated that many cells in the auditory cortex
of the squirrel monkey were inhibited during self-produced vocalizations. New interest in the
investigation of the perception of species-specific vocalizations has recently emerged.
Rauschecker et al. (1995) studied the responses of neurons in the superior temporal gyrus of
anaesthetized rhesus monkeys to complex acoustic stimuli. They found a preference in these
neurons for increasingly complex stimuli and suggested that the lateral areas of the monkey
auditory cortex may form an important stage in the preprocessing of communication sounds.
Wang et al. (1995) found a representation of behaviorally important and spectrotemporally
Central Auditory Processing and Neural Modeling
Edited by Poon and Brugge, Plenum Press, New York, 1998
complex species-specific vocalizations in the primary auditory cortex of anaesthetized common
marmoset and suggested that the representation is carried by dispersed and synchronized
cortical cell assemblies that correspond to each individual's vocalization in a specific and
abstracted way.
In contrast to the large amount of studies which have investigated the role of individual
cortical areas in the processing of animal vocalizations, the subcortical nuclei have attracted
less attention from this point of view. Creutzfeldt et aI. (1980) studied in unanaesthetized
guinea pigs the thalamocortical transformation of responses to complex auditory stimuli. The
results of their experiments demonstrated that the responses of medial geniculate body (MGB)
cells represent more components of a call than cortical cells, even if the two cells are synaptically
connected. Responses ofMGB neurons to species-specific vocalizations were also the subject
of a study by Tanaka and Taniguchi (1991), performed in guinea pigs. These authors observed
low responsiveness ofMGB neurons to vocalizations; however, the responses to vocalizations
displayed discharge patterns which were not possible to predict from the properties of their
responses to pure tones. In contrast to this, Buchwald et al. (1988) found that approximately
30% of the units in the caudal part of the cat MGB responded only to species-specific calls,
while relatively few responded to a tone or click. Only a few studies were designed to investigate
the responses of neurons of the inferior colliculus to vocal stimuli (Aitkin et aI., 1994; Poon
and Chiu, 1997). The aim of the study by Aitkin et aI. (1994), performed in anaesthetized cats,
was to gain information about the differential coding properties of neurons in three major
subdivisions of the inferior colliculus: the central (CNIC) and external (EN) nuclei and dorsal
cortex (DC). Feline vocal stimuli were found to be more effective in terms of higher firing
rates than white noise or pure tone stimuli at the characteristic frequency (CF) in 27% of the
units in the CNIC, 82% in EN and 72% in DC. There were no units that responded exclusively
to one vocal stimulus, but a high proportion of units in EN responded strongly to broad band
stimuli, and some of these showed clear preferences for one vocal stimulus over another.
The aim of the present study was to find out how single cells in the inferior colliculus
and in the medial geniculate body of the guinea pig respond to four main types of calls of this
species. In addition, we asked the question to what extent could the responses to animal calls
be predicted from the responses of the same unit to pure tones at the characteristic frequency
(CF) and to white noise. In several animals, we also investigated the responses of two or
more neurons recorded in the medial geniculate body with one rnicroelectrode and their
interaction with the aid of crosscorrelation technique.
METHODS
The extracellular responses of IC and MGB neurons to pure tones, white noise and four
typical species-specific vocalizations (purr, chutter, chirp and whistle) were recorded in guinea
pigs. These calls were selected from a large repertoire of guinea pig calls as the most frequently
used. Spontaneous vocalizations were recorded in female pigmented guinea pigs (age 2-24
months) placed in a sound-attenuated room. Recorded calls were analyzed with a high resolution
signal analyser B&K 2033 and with aCED 1401plus interface connected to a PC 486 (CED
program for frequency analysis Waterfall). Purr is a special call which consists of a bout of
regular acoustical impulses with a very small variability of frequency and time parameters.
The fundamental frequency of the purr is around 300 Hz. Animals express purr in conjunction
with mating behavior and when they seek contact. General exploratory activity is accompanied
by a frequently occurring call chutt or chutter, which lasts for 200-300 ms and may appear in
a series with variable intercall intervals. The chutter or its parts can sometimes be aperiodic;
its fundamental frequency is between 800 and 1500 Hz. The calming of an animal in
2