Download physiological plasticity in auditory cortex: rapid induction by learning

Progress in NeurobiologyVol. 29, pp. 1 to 55, 1987
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Copyright © 1987 Pergamon Journals Ltd
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX:
RAPID INDUCTION BY LEARNING
NORMAN M. WEINBERGER and DAVID M. DIAMOND*
Centerfor the Neurobiology of Learning and Memory, and Department of Psychobiology, University of California,
Irvine, &vine, CA 92717, U.S.A.
(Received 2 April 1986)
Contents
Abbreviations
I. Introduction
2. Perspectives on neuroplasticity
3. The study of learning: strategies and caveats
3.1. Background
3.2. Learning and physiological plasticity
3.3. Pupillary conditioning
4. Organization of the thalamocortical auditory system
4.1. Prelude
4.2. Higher order auditory pathways
4.2.1. Background
4.2.2. The lemniscal line
4.2.3. The lemniscal adjunct pathway
4.2.4. The diffuse pathway
4.2.5. Resume
4.3. Approaching physiological plasticity in the auditory system
5. Physiological plasticity in the medial geniculate nucleus
5.1. Effects of learning
5.1.1. Compartmentalization of learning-induced plasticity
5.1.2. Plasticity at the level of single neurons in the magnocellular medial geniculate nucleus
5.2. Long term potentiation in the magnocellular medial geniculate nucleus
6. Physiological plasticity in auditory cortex
6.1. Background
6.2. Primary auditory cortex (A1)
6.2.1. Frequency specific habituation in primary auditory cortex
6.2.2. Associatively-induced plasticity in primary auditory cortex
6.2.2.1. Multiple unit activity
6.2.2.2. Physiological plasticity in primary auditory cortex at the level of single neurons
6.3. Secondary and ventral ectosylvian auditory cortex (AI1/VE)
6.3.1. Associatively-induced plasticity in secondary and ventral ectosylvian auditory cortical fields
6.3.2. Learning effects in different cortical laminae?
6,4. Associatively-induced plasticity of background activity
6.5. A note on auditory cortical plasticity and behavioral responses
6,6. Specificity of learning-induced changes in evoked activity
6.6.1. Background
6.6.2. Learning-induced changes in frequency receptive fields
7. Implications of learning-induced plasticity in auditory cortex
7,1. Introduction
7.2. Implications of physiological plasticity for conceptions of sensory cortical function
7.3. Adaptive functions
7.3.1. Introduction
7.3.2. Stimulus analysis
7.3.3. Response functions
7.3.4. Cognitive functions
7.3.4. I. Perception
7.3.4.2. Selective attention
8. Conclusions
8.1. Summary of findings
8.2. Relationships among physiological plasticity, neocortical function, learning, and sensory information processing
8.2.1. Physiological plasticity and learning
8.2.2. Auditory cortex, plasticity and learning
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* Current Address: University of Colorado Health Sciences Center, Dept. of Pharmacology, Box C-236, 4200
E. Ninth Avenue, Denver, Colorado, 80262.
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N.M. WEINBERGERand D. M. DIAMOND
8.3. Future directions
8.3.1. Introduction
8.3.2. Future cellular studies of physiological plasticity
8.3.3. Generality of sensory cortical plasticity
8.3.4. The basic paradigm of neurobiology
Acknowledgements
References
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Abbreviations
Behavior
CS
CS+
CSCR
UR
US
Conditioned Stimulus
Reinforced Conditioned Stimulus (Discrimination Training)
Unreinforced Conditioned Stimulus (Discrimination Training)
Conditioned Response
Unconditioned Response
Unconditioned Stimulus
Brain Structures
AAF
AI
AII
D
ICc
ICp
ICx
MGN
MGdc/vl
MGm(M)
MGv
NLL
PAF
SAG
VCN
VE
VL
VO
VPAF
Anterior Auditory Cortical Field
Primary Auditory Cortical Field
Secondary Auditory Cortical Field
Dorsal Division of the MGN
Central Nucleus of the Inferior Colliculus
Pericentral Nucleus of the Inferior Colliculus
External Nucleus of the Inferior Colliculus
Medial Geniculate Nucleus
Dorsocaudal and Ventrolateral Subdivisions of the MGN
Magnocellular (or Medial) Subdivision of the MGN
Ventral Subdivision of the MGN
Nucleus of the Lateral Lemiscus
Posterior Auditory Cortical Field
Nucleus Sagulum
Ventral Division of the Cochlear Nucleus
Ventral Ectosylvian Auditory Cortical Field
Pars Lateralis of the ventral MGN
Pars Ovoidea of the ventral MGN
Ventral Posterior Auditory Cortical Field
1. Introduction
F o u r fields in n e u r o b i o l o g y which are o f intense c u r r e n t interest are neuroplasticity,
neocortical function, the n e u r o p h y s i o l o g y o f learning, a n d i n f o r m a t i o n processing in
sensory systems. This c h a p t e r concerns the i n t e g r a t i o n o f these areas in the investigation
o f learning a n d p h y s i o l o g i c a l plasticity in the a u d i t o r y cortex. T h e goals o f this c h a p t e r
are threefold: (1) to p r o v i d e a s u m m a r y o f research which s u p p o r t s a highly d y n a m i c role
for sensory n e o c o r t e x in learning, (2) to call a t t e n t i o n to the close relationships a m o n g the
n e u r o b i o l o g y o f plasticity, cerebral cortex, learning, a n d sensory processing, a n d (3) to
indicate research p a t h s that m a y p r o m o t e their integration.
In the following sections, we discuss p h y s i o l o g i c a l plasticity as it relates to learning,
followed by a brief overview o f the study o f learning as a p p l i e d to c o n d i t i o n i n g studies
in animals. W e p o i n t out the pervasive a n d c o n t i n u a l c h a r a c t e r o f learning, e m p h a s i z i n g
the r a p i d i t y at which a s s o c i a t i o n s between stimuli are formed, in c o n t r a s t to the slower
rate at which specific m o t o r responses are acquired. F o l l o w i n g a s u m m a r y o f r a p i d
learning, as indexed by p u p i l l a r y dilation, findings on p h y s i o l o g i c a l plasticity in the
a u d i t o r y t h a l a m u s a n d especially in a u d i t o r y cortical fields are reviewed. W e focus on the
specificity o f plasticity in cortical processing o f acoustic i n f o r m a t i o n d u r i n g learning. Next,
i m p l i c a t i o n s o f n e u r o p l a s t i c i t y in a u d i t o r y cortex for c o n c e p t i o n s o f cortical o r g a n i z a t i o n
a n d a d a p t i v e b e h a v i o r a l functions are considered. W e c o n c l u d e with suggestions a b o u t
future directions for research in physiological plasticity in neocortex.*
* For expository purposes, we use the following terms interchangeably: physiological plasticity, plasticity, and
neuroplasticity. In this chapter, we do not cover morphological plasticity, including that which is related to
learning (e.g. Greenough, 1984).
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
3
The findings presented herein are taken primarily from our own investigations. Despite
their somewhat novel features, prior acquaintance with the subject matter is not required.
The treatment of both conceptual and empirical issues assumes only a general knowledge
of neurobiology. For several topics, the paper may serve as an introduction to the study
of physiological plasticity and learning. Experts in the relevant areas may find unusual and
possibly controversial material in the chapter. Selected aspects of some issues have been
reviewed elsewhere (Weinberger, 1980, 1982a,b, 1984; Weinberger et al., 1984; Weinberger
and Diamond, in press), and wherever possible, are referenced in the text rather than
repeated here.
2. Perspectives on Neuroplasticity
Neuroplasticity has become a major focus in contemporary neurobiology. It is widely
studied at several levels--subcellular, cellular, neuronal systems, behavioral--and from
various viewpoints--anatomical, biochemical and physiological. The topics most closely
associated with neuroplasticity are (a) neural development, (b) recovery of function
following pathology, (c) functional reorganization following sensory deprivation or
peripheral manipulations, and (d) learning and memory. The first three examples have
often been combined. For example, sensory deprivation is routinely used to study plastic
characteristics of the developing visual system.
Since the term "plasticity" has been introduced into neurobiology at several times, with
various topics, its use has been varied. Therefore, it will be helpful to have a working
definition at the outset. All definitions have in common the idea of change. For example,
as recently defined, plasticity is " . . . a n y persistent change in the functional properties of
single neurons or neuronal aggregates..." (Tsukahara, 1981). A slightly different
definition put forth by Konorski (1967), is that "plasticity" is considered as a capacity or
property of neural tissue, rather than as change, per se. This offers the advantage of
conceptualizing neural substrates that are capable of expressing plasticity (under certain
conditions), even prior to the actual change. Viewed this way, "plasticity" is one of two
fundamental properties of nervous tissue; the other is "reactivity". The latter may be
defined as the " . . . c a p a c i t y to be activated by stimulation, based on properties of
excitability, conductivity and transmittability". "Plasticity" is then seen as the capacity for
nervous tissue t o " . . , change its reactive properties as the result of successive activations."
(Konorski, 1967, p. 7). For purposes of this chapter, we have adopted this "capacity" type
of definition.
It is also important to distinguish between non-associative and associative forms of
plasticity. Habituation, defined as a decrement in response with repeated stimulation, is
an example of the former. It is non-associative because it entails changes in reactivity as
a result of repeating a single stimulus. By contrast, classical conditioning is an example
of associative learning because one stimulus is explicitly paired with a second stimulus (see
also Section 3.2).*
The expression of neuroplasticity during development, following injury, and during
learning has been documented extensively (for reviews see e.g. Lund, 1978; Finger and
Stein, 1982; Tsukahara, 1981, respectively). Not generally recognized is the difference in
time scales involved in these phenomena. Both developmental plasticity and that involved
in recovery of function or reorganization may require months to be fully expressed, even
years in the case of some phenomena in humans (e.g. language development). In contrast,
neuroplasticity expressed during learning develops rapidly. Such changes are measured on
the order of minutes and are often expressed after only one training experience.
Furthermore, even when learning appears to be slow, one can discern behavioral signs of
rapid acquisition of information (Section 3.2). This rapidity with which organisms acquire
and store information indicates that underlying neuroplasticity must develop rapidly
during learning.
* For an introduction to associative and non-associative learning, see Domjan and Burkhard, 1982.
4
N.M. WEINBERGERand D. M. DIAMOND
A second difference between developmental neuroplasticity and recovery of function, on
the one hand, and learning on the other hand, involves their periods of occurrence.
Developmental processes are generally limited to early stages of ontogeny, while recovery
of function is limited to the period following insult to the nervous system. Furthermore,
recovery of function is a response to a singular traumatic event, which rarely occurs
repeatedly during the lifetime of an animal. In contrast, learning is a process in which an
animal is in a continual state of acquiring information from its environment, including
information about the consequences of its own behavior. It is, in fact, extremely difficult
to prevent an animal from learning. Although learning can be prevented by the use of
general anesthesia, under certain circumstances it can still occur even in this depressed state
(Weinberger et al., 1984b). Informal validation of the pervasive and continual character
of learning can be obtained by recalling and listing details of one's own experiences during
the past 24 hr.
While we have pointed out differences between learning and development/recovery of
function, there are also important commonalities. For example, all are essential to
behavioral adaptation. In addition, it is quite possible that the biophysical substrates of
plasticity share common mechanisms. The capacity of nervous tissue to change its
reactivity may be a highly conserved characteristic. As mechanisms of neuroplasticity in
development, recovery of function and learning become understood, this issue will be
resolved.
3. The Study of Learning: Strategies and Caveats
Given that learning involves the continual acquisition of information, how has the
content of a learning experience been addressed empirically, particularly in non-verbal
organisms? In the following section we point out that the study of the acquisition of certain
somato-motor responses has dominated both experimental psychology during the first half
of this century and much of current neurophysiology of learning.
3.1. BACKGROUND
Most contemporary studies of the neurophysiology of learning stress the need to develop
a "model system" approach. The basic notion is to utilize a preparation that allows for
identification of the circuitry underlying learning. In this context, "learning" is taken as
the elaboration of a specific motor response, and the model system encompasses a circuit
analysis of the pathway from the sensory receptors to the motor neurons (e.g. Woody,
1982).
This approach is similar to the well documented stimulus response (S-R) approach
which dominated both theory and experiments in the scientific study of learning in the era
1913-1955. S-R psychology was founded on the well-established reflex of Sherrington
(1906) and others, and the conditioned reflex of Pavlov (1927). A complete account of
attempts to understand learning exclusively in S-R terms, i.e. as the learning of only
behavioral motor responses, cannot be given here. But the attempt was largely abandoned
within experimental psychology by the end of the 1950s. Why was this so? Hindsight, as
always, is perceptive.
The experimental psychology of the late 19th and early 20th centuries took as its subject
matter that which has always been of major interest, the contents of human consciousness.
As its method, it adopted introspection, i.e. the reporting of one's own thoughts and
experiences. Difficulty in cross-observer replication was inevitable with such a subjective
method and attempts to study the contents of mind fell into disfavor (Boring, 1957).
Leading a genuine scientific revolution, John Watson declared that the subject matter of
psychology henceforth would be behavior, not the mind, and the method would be the
observation of behavior (Watson, 1913, 1919).* Although some scientists used behavior
* For an interesting account of the origins and early developmentsof behaviorism, see O'Donnell. 1985.
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
5
to infer mental or cerebral events, the dominant theme was to regard behavior as an end
in itself. Consequently, the study of learning became largely a study of the modification
of reflexes with experience.
Unfortunately, while experimental psychology amassed valuable data and developed
important experimental tools, it forgot that S-R behaviorism was merely a means of
studying that which could be observed easily, i.e. the contractions of striated muscles which
result in overt movements. Furthermore, many findings could not be explained by arguing
that learning consisted only of the acquisition of responses. Undeniable evidence accumulated that much learning consists of learning relationships between events, such as between
two stimuli, i.e. S-S learning. Gradually, the field of experimental psychology accepted that
a behavioral response was not the only product of learning (for reviews see Dickinson,
1980 and Mackintosh, 1983; see also Mackintosh, 1985 and Rescorla, 1985). The scientific
study of animal as well as human behavior is currently "cognitively" oriented. That is, the
learning of information or knowledge is accepted and inferences about the involved
processes and organization of information are made on the basis of behavior.*
3.2. LEARNING AND PHYSIOLOGICALPLASTICITY
Given that learning involves not merely the acquisition of responses, but also the
acquisition of information about relationships between stimuli, it is still necessary to have
a behavioral index of learning. A behavioral response that develops due to the association
of two stimuli permits the inference that neural processes underlying learning have
developed plasticity. Most contemporary studies of physiological plasticity during learning
employ a type of associative training first discovered and elucidated by Pavlov (1927),
called "classical conditioning". In this form of training, a neutral stimulus (the conditioned
stimulus, CS) is paired with a biologically significant event, such as food or a noxious
stimulus (the unconditioned stimulus, US). Presentation of the CS, or US, or both is called
a trial. After several trials of CS-US pairing (the former always preceding the latter), the
CS develops the ability to elicit an acquired response which is usually similar to the
response previously elicited by the US (Mackintosh, 1974). This learned, anticipatory
response is referred to as the conditioned response (CR). Development and performance
of the CR is the operational sign that learning has occurred. A standard example is the
use of an acoustic stimulus as the CS, air puff to the eye as the US, and the development
of an eyeblink as the CR.
The "model systems" approach discussed above concentrates on attempting to trace the
involved circuitry from the CS to the CR. In the example given above, this would involve
circuitry from the auditory system to mechanisms that produce the conditioned eyeblink;
circuitry for the unconditioned response (UR), that is, the eyeblink directly caused by air
puff to the eye, would be different to some degree because the CR is learned while the UR
occurs prior to learning.
While this approach is productive, it fails to account for the fact that "the C R " is
actually only one of several conditioned responses that develop during associative
conditioning (Konorski, 1967; Weinberger, 1982a; Mackintosh, 1985). Thus, rapidly
acquired CRs are evident for many responses, including heart rate, blood pressure,
respiration, general body movement, galvanic skin response, and pupillary dilation. In fact,
these responses are acquired more rapidly than is the eyeblink or leg flexion CR (Table
1). A further difference is that the rapidly acquired CRs develop more or less simultaneously within an animal in classical defensive conditioning situations, regardless of the
particular US employed. In contrast, only one slowly developing CR is obtained, and it
is specific to the US used. Thus, eyeblink CRs develop when air puff is applied as the US,
and flexion CRs are seen only when shock is delivered to a limb, but cardiac conditioned
* Strict S-R behaviorismcontinuesin a narrower arena, mainlyfollowingthe formulationsof B. F. Skinner.
For a literate defenseof behaviorism,see Skinner, 1974. A recentmore technicalanalysis,which favors a greatly
liberalizedbehaviorism,has been providedby Zuriff(1985). Argumentsagainst S-R approachesand for cognitive
interpretations of animal behavior are given in Hulse et al., 1978.
6
N . M . WEINBERGERand D. M. DIAMOND
responses develop in both cases. The slowly acquired CRs may be emphasized because they
can be observed more easily, but the rapidly acquired CRs are earlier and more sensitive
indicators of learning.
The distinction between rapidly and slowly acquired CRs has at least three implications
for the study of physiological plasticity during classical conditioning:
First, associative conditioning appears to be a two stage process. In the initial stage, the
organism learns that the CS predicts the US, as evidenced by rapidly acquired CRs that
are not tied to the particular US. In the second stage, it then learns to make the somatic
response that is specific to the unconditioned stimulus (Weinberger, 1982a).*
Second, this two-stage process implies two alternatives about the physiological plasticity
underlying behavioral plasticity: (i) the rapid development of CRs might involve widespread plasticity in diverse neural systems, followed by additional modifications in the
more restricted circuitry underlying the development of specific somatic CRs; or (ii) the
rapid changes in neural activity may be restricted to certain systems (e.g. sensory systems
processing the CS and the US), with minimal involvement of circuitry underlying the
specific somatic CR, In the latter case, changes in the circuitry of the somatic CR would
develop, d e not,o, very late in the training procedure. If this turns out to be the case, then
analyses limited to neural processes underlying slowly developing CRs may yield the
mistaken conclusion that behavioral and neural plasticity develop only after prolonged
training.
Third, because rapidly developing physiological plasticity precedes the appearance of
slowly acquired CRs, it could contribute to neural changes which underly these specific
somatic conditioned responses.
One way of taking account of the rapid/slow CR dichotomy is to attempt to determine
the neural mechanisms involved in elicitation of a rapidly developing conditioned response,
such as heart rate (e.g. Cohen, 1985). While response-oriented studies are valuable, they
do have limitations. For example, since many rapidly acquired CRs develop more or less
simultaneously, physiological plasticity involved in the production of a CR in one effector
system is not necessarily of greater importance than that which develops in another effector
system. Furthermore, there is no compelling rationale to focus on response systems to the
exclusion of other neural systems, because even rapidly acquired conditioned responses are
still simply behavioral indicators of underlying associatively-induced physiological plasticity (see also Olds e t al., 1972). Rather, any and all neural systems that rapidly develop
physiological plasticity are excellent candidates for investigation of initial events in
learning.
The strategy that we employ is to analyze processing of the conditioned stimulus within
its sensory system during learning; in our case, this is the auditory system. Recording in
auditory pathways during learning has an empirical basis, as there is a substantial literature
describing learning effects in this system (Weinberger e t al., 1984a), particularly in the
auditory cortex (Section 6.1).
There are also conceptual reasons for this line of inquiry. For example, since initial
events in associative learning concern relationships between the CS and the US, plasticity
might develop in the sensory systems which process these stimuli; this could be particularly
true for the conditioned stimulus because its signal value is changed by conditioning. Also,
unlike circuitry involved in specific motor responses, plasticity in the sensory system of the
CS need not be linked to any particular effector action. Therefore, it may be involved in
general processes of associative learning.
3.3. PUPILLARY CONDITIONING
Our studies of physiological plasticity in the auditory system, while not concerned with
the circuitry of any specific learned motor act, nonetheless require a behavioral conditioned
* For a reviewof various two-processtheories of learning, see Rescorla and Solomon, 1967. Konorski (1967)
is responsiblefor the first explicitdistinction between two types of classicallyconditioned responseswhose rates
of acquisition differ. Recently,Thompson et al. (1984)have offereda three-factor hypothesisconsistentwith the
two-process view of Weinberger, 1982.
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
TABLE 1. RATES OF DEVELOPMENT OF VARIOUS CONDITIONED RESPONSES
Conditioned
Response
Rate (Trials)a
Subject
Referencesb,c
Rapidly Developing Conditioned Responses
Galavanic Skin
Response
Pupillary
Dilation
Blood Pressure
Non-Specific
Motor
Respiration
Heart
5-10
5-10
5-12
5-10
2 5
2-10
10-15
10 15
12
2-10
5-10
2-5
24-36
10
5-10
Rat
Cat
Cat
Cat
Cat
Rabbit
Rat
Rat
Rat
Rabbit
Lizard
Fish
Rat
Rabbit
Lizard
Holdstock and Schwartzbaum, 1965
van Twyver and King, 1969
Gerall and Obrist, 1962
Ashe et al., 1976, 1978
Diamond and Weinberger, 1984
Yehle et al., 1967
deToledo and Black, 1966
Parrish, 1967
Rescorla, 1968
Yehle et al., 1967
Davidson and Richardson, 1970
Woodward, 1971
deToledo and Black, 1966
Yehle et al., 1967
Davidson and Richardson, 1970
Slowly Developing Conditioned Responses
Nictitating
Membrane
Eyelid (Airpuff)
Flexion, Leg
70-164
56-64
64-112
160-240
125 300
Flexion, Elbow
Eyelid (Glabella Tap)
600
600-900
Rabbit
Rabbit
Rabbit
Rabbit
Cat
Cat
Cat
Cat
Gormezano et al., 1962
Berger and Thompson, 1978
Berry and Thompson, 1979
Schneiderman et al., 1962
Bruner, 1969
O'Brien and Packham, 1973
Tsukahara et al., 1981d
Woody and Brozek, 1969e
a Earliest consistent CR's. In cases where the authors did not specify the rate of learning, estimates were
obtained from the published data or author's comments.
b Citations are representative and do not constitute an exhaustive list.
c Rapid and slow CR's have been recorded within the same animal. See, e.g. Dykman et al., 1965; Yehle,
1968. See also Black, 1965 and Schneiderman, 1972.
a Stimuli employed were electrical stimulation of the brain.
eThe rate of conditioning can be facilitated by stimulation of the hypothalamus (Kim et al., 1983).
response to p r o v i d e i n d e p e n d e n t evidence o f learning. A s shown p r e v i o u s l y in T a b l e 1,
several c o n d i t i o n e d responses are useful i n d i c a t o r s o f r a p i d associative learning. W e
selected the p u p i l l a r y d i l a t i o n c o n d i t i o n e d response due to its reliability, r o b u s t n e s s a n d
ease o f q u a n t i f i c a t i o n ( C a s s a d y e t al., 1982).
F i g u r e 1 p r o v i d e s e x a m p l e s o f p u p i l l a r y d i l a t i o n responses to an a c o u s t i c stimulus
d u r i n g three p h a s e s o f training:, " s e n s i t i z a t i o n " , " c o n d i t i o n i n g " a n d " e x t i n c t i o n " . D u r i n g
c o n d i t i o n i n g , the CS a n d U S are paired; this is the s t a n d a r d s i t u a t i o n for associative
c o n d i t i o n i n g . In c o n t r a s t , d u r i n g the sensitization phase, the CS a n d U S are n o t p a i r e d ,
b u t p r e s e n t e d m o r e o r less at r a n d o m intervals; h o w e v e r the p r o b a b i l i t y o f the CS a n d U S
are the s a m e (e.g. 2/min) d u r i n g b o t h phases. D u r i n g extinction, the U S is o m i t t e d a n d
the C S is p r e s e n t e d alone.
T h e sensitization p h a s e is n e e d e d to c o n t r o l for n o n - a s s o c i a t i v e factors which m i g h t
p r o d u c e a n a p p a r e n t c o n d i t i o n e d response d u r i n g pairing. F o r e x a m p l e , a n o r g a n i s m m a y
simply give a larger response to a n y stimulus, such as a tone, due to the i n t r o d u c t i o n o f
a s t r o n g stimulus, such as the u n c o n d i t i o n e d stimulus. This effect, t e r m e d " s e n s i t i z a t i o n "
is n o t associative because it d o e s n o t d e p e n d u p o n the p a i r e d r e l a t i o n s h i p between the CS
a n d the US. B o t h b e h a v i o r a l a n d n e u r o p h y s i o l o g i c a l responses to the CS s h o u l d be
m e a s u r e d d u r i n g a sensitization a n d a c o n d i t i o n i n g phase.* Since the o n l y difference
between the two t r a i n i n g phases is in the p a i r e d r e l a t i o n s h i p between the CS a n d US, a n y
differences in n e u r o n a l a n d b e h a v i o r a l responses to the CS d u r i n g the c o n d i t i o n i n g p e r i o d
can be a t t r i b u t e d specifically to the a s s o c i a t i o n o f the CS with the US. A c c o r d i n g l y , we
* Other control procedures are possible, including having different groups of animals undergo sensitization
and conditioning. Further, during sensitization, the CS and the US may be presented randomly or explicitly
unpaired. Related technical details are not covered here; our purpose is to underscore the need for controlling
non-associative factors during conditioning.
8
N.M.
WEINBERGER a n d D. M. DIAMOND
PUPILLARY BEHAVIOR
ISENSITIZATIONI
C5
~
U5
A
C 10 ~.~.......~.
U 10
_ ~
[CONDITIONING~
CS
3
~
CS 12 ~ . ~
CS
4
~
CS 40
[EXTINCTIONI
E4
~A
E 24
-,~-~--.-~
A
FIG. I. Pupillary behavior during training. Sample records are for individual trials during one
training session (dilation is up). Filled triangles indicate the onset of the CS (I sec duration), open
triangles indicate the onset of the US (250 msec duration). The US was presented at the offset of
the CS during conditioning. Whereas the tone alone evokes a low amplitude dilation during
sensitization trials (C5, CI0), the US consistently evokes a large dilation. During conditioning, the
evoked response to the CS is augmented by the fourth trial (CS4), and continues to increase in
magnitude later in conditioning (e.g., CS12, CS40). During extinction, a decrease in the magnitude
of the conditioned response is evident by the fourth trial (E4), and the behavioral response is
virtually abolished by trial 24 (E24).
routinely express responses to the CS during conditioning as differences from responses
to this same stimulus during sensitization,
The extinction procedure is useful to determine if, once established, conditioned
responses still depend upon C S - U S pairing. The systematic reduction of CRs following
removal of the US is evidence of this dependence.
As shown in Fig. l, pupillary dilation is elicited by the CS during sensitization; these
initial orienting responses decrease with repeated trials. In contrast, the response to the
US (electrodermal stimulation, EDS) is larger and maintained throughout the training
period. During conditioning (CS-US pairing) the pupillary CR is evident within a few
trials. It increases in amplitude during continued pairing and is maintained throughout the
conditioning phase. During subsequent extinction, when the CS is removed, the pupillary
conditioned response decreases and finally disappears.
Figure 2 presents group functions for sensitization and conditioning. Note the initial
orienting response during sensitization which decrements, followed by the rapid development of the pupillary C R during conditioning. In fact, the dilation to the CS on trial 2
(the first trial following pairing) shows the initial conditioned response. That is, associative
learning about the C S - U S relationship may develop as rapidly as possible, i.e. after one
trial.
In a series of studies over several years, we found that the pupillary C R exhibits all of
the major characteristics of the more slowly acquired conditioned responses, except that
it develops much more rapidly. For example, when the interval between the onset of the
CS and the onset of the US is systematically increased (e.g. from l to 16 sec), the latency
to peak dilation is also increased (Figs 3 and 4) (Oleson et al., 1973). This function relating
C S - U S interval to CR latency is quantitative evidence that the conditioned stimulus
PHYSIOLOGICAL
P L A S T I C I T Y IN A U D I T O R Y
CORTEX
PUPILLARY BEHAVIOR
400
520
240
I,.l,J
Z
I
i-Z
160
80
-80
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I
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I
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2
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I
4
5
6
I
I
I
7
8
9
SENSITIZATION 1~5 COND.
CONDITIONING
TRIALS
BLOCKS OF FIVE TRIALS
FIG. 2. Pupillary learning curves. Each point represents the mean ( + SE) of 10 subjects. Data points
identified as 1-3 in sensitization and 1-9 in conditioning represent 5 trial averages. Values were
computed as the percentage change in the tone evoked pupillary dilation from the average response
for the last five trials o f sensitization. A significant increase in pupillary response is evident by the
second b]ock of 5 trial averages, and it reached asymptote by the 20th trial. The rapid rate of
acquisition is illustrated in finer detail for the first 5 trials of conditioning.
0
I I i I I I I I I j
, i I I !-J , , t l
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FIG. 3. Pupillar dilation records for single trials at different C S - U S intervals from 2.5 sec. (A) to
16.0 sec. (F). Stimulus markers are solid lines; time marks are I sec. The largest response occurs
in response to presentation of the US at CS offset. Note the conditioned response at the CS onset
with a short interval (A), and the increasing latency of peak o f the CR as C S - U S interval increases;
the peak of the CR occurs at the end o f the C S - U S interval in B-F. (From Oleson et al., 1973.)
10
N . M . WEINBERGER and D. M. DIAMOND
E
16
14
12
Median
Latency
to Peak
Response
10
oD
8
o/
6
4
2
0
d5
;
CS-US
1"1h 1;
;'6
Inlerval
FIG. 4. Median latency (sec) to peak dilation C R as a function of C S - U S interval, for each of five
subjects (A E). Note the increase in latency to m a x i m u m response as CS US interval increases.
(From Oleson et al., 1973.)
becomes an acquired signal which animals use to predict the time of onset of the
unconditioned stimulus.
Additional experiments revealed that animals acquire discriminative pupillary conditioned responses (Ashe et al., 1978a; Ryugo and Weinberger, 1978). That is, the pupillary
CR to a stimulus that is followed by a US (termed a C S + ) , is significantly larger than
dilation to a stimulus that is not followed by a US (termed a C S - ) . This discrimination
between a CS + and a C S - can be established both between modalities (e.g., acoustic and
somatosensory, Weinberger et al., 1973) and also within the auditory modality (white noise
vs pure tone, Oleson et al., 1972, 1975). Discrimination demonstrates that the association
between the CS and the US is specific to the stimulus that signals the US. The pupillary
CR also develops discrimination reversal. This occurs when the CS + (e.g., tone) and C S (e.g. white noise) are reversed such that the tone is no longer followed by the US, and the
white noise is now paired with the US. During discrimination reversal, the pupillary
conditioned response gradually shifts to the new C S + and declines to the new C S (Oleson et al., 1972; 1975). Discrimination reversal is a powerful demonstration that a
discriminative conditioned response is not due to some unknown prior relationship
between a CS and a US, but is attributable only to the stimulus pairing instituted by the
experimenter.
All of these findings show that the pupillary dilation conditioned response is a sensitive
indicator that genuine associative conditioning develops rapidly.
4. Organization of the Thalamocortical Auditory System
4.1. PRELUDE
Later in this paper, we summarize findings which document learning-induced plasticity
in the thalamocortical auditory system. Of note, they reveal differential physiological
plasticity in different components of the higher auditory system. In order to provide a
structure-function framework within which these findings can be considered, it is necessary
to first review the organization of the auditory forebrain.
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
II
4.2. HIGHER ORDER AUDITORY PATHWAYS
4.2.1.
Background
Early descriptions of thalamocortical organization described two basic systems: (1) a
main projection line conveying direct lemniscal information to the primary sensory cortical
receiving area, and (2) intrinsic nuclei of the thalamus and cortical associational areas
which were believed to be independent of direct ascending sensory afferentation (Rose and
Woolsey, 1949). Subsequent findings forced a revision of this view. For example, the
"intrinsic" thalamic nuclei were found to receive ascending input (Jones, 1985; Macchi,
1983; Winer and Morest, 1983). Furthermore, rather than a single sensory projection line
extending to one primary sensory cortical field, there are parallel thalamocortical sensory
pathways which terminate throughout the neocortex (see I. Diamond, 1982; Oliver, 1982;
and Merzenich and Kaas, 1980 for additional discussion of parallel processing).
One of the more important advances in understanding parallel processing in sensory
systems is attributed to Graybiel (1972, 1973) who provided a schema for identifying
functional pathways in the auditory, visual and somatosensory systems, based partially on
their accessibility to primary sensory neocortical areas. Graybiel maintained the wellestablished primary sensory input channels to the cortex, or lemniscal lines, as high fidelity,
modality specific pathways which maintain a strict topographic representation of the
periphery. In addition, she proposed a second class of pathways which ascend in parallel
to the lemniscal lines; Graybiel viewed these as "accessory conduction routes that are
capable of handling input dimensions not conveyed by the precise encoding systems of
lemniscal lines" (p. 242, Graybiel, 1973).
\
I
I
I
I
500 ~rn
FIG. 5. Camera lucida reconstruction of the medial geniculate nucleus through the middle of
the MGN of the adult cat (coronal section, Golgi-Cox). Abbreviations: ventral division, VL,
parlateralis and VO, pars ovoida; magnocellulardivision, M; dorsal division, D. (From Ryugo
and Weinberger, 1978.)
12
N . M . WEINBERGER and D. M. DIAMOND
Taking Graybiel's analysis as the starting point, we have proposed three, rather than
two, parallel pathways in the higher auditory system (Diamond and Weinberger, in
preparation). While maintaining the lemniscal line, we further subdivide Graybiel's
"accessory" route into "lemniscal adjunct" and "diffuse" pathways. Each pathway is
centered on one of the three major subdivisions of the medial geniculate nucleus (Fig. 5)
as described by Morest (1964) with further refinement by Andersen et al. (1980).
4.2.2. The lemniscal line
Our conception of auditory lemniscal line processing is in accord with Graybiel's
classification, and also corresponds to subsequent descriptions of the "core" pathway of
Winer et al. (1977) and I. Diamond (1979), and "central" pathway of Oliver (1982) and
Oliver and Hall (1978a). These authors identify this pathway as composed of auditory
brainstem nuclei (e.g. ventral cochler nucleus, superior olivary complex), central nucleus
of the inferior colliculus, ventral division of the medial geniculate nucleus (MGv) and
primary auditory cortex (AI). Each of these structures is organized topographically, i.e.
contains an orderly representation of the cochlea. Because the cochlea itself has a
systematic frequency organization along the basilar membrane, it projects a functional
"tonotopic" organization upon the auditory lemniscal pathway (e.g. Serkov and Volkov,
1983). These tonotopic structures are populated predominantly by neurons that are
narrowly "tuned", i.e. respond to a narrow range of frequencies (e.g. Aitkin and Webster,
1972; Goldstein et al., 1968; Imig and Morel, 1985a,b; Merzenich et al., 1975; Phillips and
Irvine, 1981; for reviews see Aitkin, 1976; Brugge and Geisler, 1978: Clopton et al., 1974;
Imig and Morel, 1983; Merzenich et al., 1979).
Although the earlier studies restricted the termination of the leminiscal line solely to AI,
recent studies indicate that the cortical projection zone of this pathway extends beyond
AI. Physiological data have revealed that there are at least four tonotopically organized
auditory cortical areas, in addition to the primary field. These are the anterior (AAF),
posterior (PAF), ventral posterior (VPAF) and ventral ectosylvian (VE) auditory fields
(Andersen et al., 1980; Diamond, 1985; Knight, 1977; Phillips and lrvine, 1982; Phillips
and Orman, 1984; Reale and lmig, 1980). As these fields receive projections from the
ventral medial geniculate nucleus (MGv)* (Andersen et al., 1980: hnig and Morel, 1983;
Morel and Imig, 1983; Niimi and Matsuoka, 1979), they are all considered as the cortical
termination zone of the auditory lemniscal line; a similar revision was suggested by
Merzenich et al. (1979). By contrast, secondary auditory cortex (All) receives no input
from the lemniscal line and contains only broadly tuned neurons with no clear frequency
organizationt (Andersen et al., 1980: Imig and Morel, 1983; Rigby et al., 1967; Reale and
Imig, 1980; Schreiner and Cynader, 1984; Watanabe, 1959). The location of"these auditory
cortical fields is presented in Fig. 6.
* Early studies reported narrow tuning and presumably a single tonotopic representation in the ventral division
(MGv). However, recent studies indicate that this gross parcellation can be further subdivided. Presently, four
subdivisions of the auditory thalamus are recognized as containing narrowly tuned cells and tonotopic
organization: pars ovoidea and pars lateralis of the ventral division proper, the deep dorsal subdivision of the
M G N and the lateral division of the posterior nucleus (Calford, 1983; Imig and Morel, 1984a,b). As their
respective projections to auditory cortex are similar, we have retained the MGv distinction as representative of
the region of the medial geniculate nucleus that contains narrowly tuned cells, tonotopic organization and
projects to tonotopically arranged auditory cortical fields.
t It is necessary to clarify the status of the secondary field (AID, because it has changed drastically in recent
years. Originally, AII was believed to be a single field extending from the posterior ectosylvian sulcus to the
anterior ectosylvian gyrus and that it was organized tonotopically. However, anterior AII was found to be a
distinct tonotopic field (the anterior field, AAF), (Knight, 1977). Recent evidence (Niimi and Matsuoka, 1979;
Reale and Imig, 1980) suggested that a tonotopic field exists in posterior AI1. Our recordings of unit activity
in awake cats corroborate tentative descriptions by Reale and Imig (1980) of tonotopy in posterior AII. We refer
to this posterior region as the ventral ectosylvian field (VE). AII as it is presently defined, is bordered by three
tonotopic fields: AI, A A F and VE (Fig. 16). In this newly defined All region, there is no evidence of frequency
organization or narrow tuning.
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
13
FIG. 6. Lateralviewof the auditorycorticalfieldsin the cat. Major sulci are indicatedwith thick
lines and cortical field borders are in dashed lines. Dorsal is up, anterior is left. Abbreviations:
AAF, Anterior AuditoryField; AII, SecondaryAuditoryCortex; AI, Primary AuditoryCortex;
PAF, PosteriorAuditoryField;VPAF,Ventral PosteriorAuditoryField;VE, Ventral Ectosylvian
Auditory Field.
4.2.3, The lemniscal adjunct pathway
The original distinction between the leminiscal line and lemniscal adjunct pathways was
based on auditory response properties and connectivity. These two pathways were seen as
ascending in parallel from the midbrain to cortex. The lemniscal line presumably provides
an accurate representation of the acoustic environment, while the lemniscal adjunct
pathway is less tightly coupled to the physical components of sound. Although we have
retained this "information processing" based distinction between auditory pathways,
recent data indicate that finer distinctions can be made within the lemniscal adjunct
pathway. For example, the magnocellular (MGm) and dorsocaudal/ventrolateral
(MGdc/vl) subdivisions of the medial geniculate nucleus were both considered as
components of the lemniscal adjunct pathway. However, their connectivity and physiological properties indicate that they process acoustic information differently. We briefly
describe physiological and anatomical characteristics of MGdc/vl here, while properties of
the MGm are discussed in the next section.
Neurons in MGdc/vl are broadly tuned and respond to sound at long latencies, e.g.
30-160 msec. There is no evidence of tonotopic organization in either of these subnuclei
of the MGN (Aitkin et al., 1981; Calford, 1983; Calford and Webster, 1981). The lack of
narrow tuning and frequency organization in MGdc/vl is consonant with their afferents
from lower auditory structures; midbrain inputs originate exclusively in non-lemniscal line
structures which contain broadly tuned neurons, e.g. nucleus sagulum, external and
pericentral nuclei of the inferior colliculus (Aitkin et al., 1981; Calford and Aitkin, 1983;
Henkel, 1983).
In contrast to the thalamic lemniscal line (MGv), which terminates solely in tonotopically organized cortical fields, thalamocortical projections of MGdc/vl terminate in
both tonotopic (PAF, VPAF, VE) and non-tonotopic (AII) fields (Fitzpatrick et al., 1977;
Imig and Morel, 1983; Morel and Imig, 1983).
For present purposes, MGdc/vl and all structures directly connected with these
subdivisions are considered to be the "lemniscai adjunct" pathway.
4.2.4. The diffuse pathway
The magnocellular subdivision of the medial geniculate nucleus (MGm) is the only
component of the auditory thalamus that receives convergent ascending input from
midbrain components of both lemniscal line and lemniscal adjunct pathways. Thus, its
afferents include projections from the central nucleus of the inferior colliculus (ICc) and
nuclei of the lateral lemniscus, both of which are tonotopic, and from the external nucleus
of the inferior colliculus (ICx) and the deep layers of the superior colliculus (SCd) which
are not tonotopic (Aitkin et al., 1975, 1978, 1981; Graham, 1977; Henkel, 1983; Kudo and
14
N.M. WEINBERGERand D. M. DIAMOND
CORTEX
THALAMUS
MIDBRAIN
BRAINSTEM
FIG. 7. Schematic diagram of the organization of higher order pathways in the auditory system,
as described in the text. The lemniscal line is striped left, the diffuse pathway is solid and the
lemniscal adjunct in striped right. According to this schema, cortical and midbrain regions may
be components of more than one pathway, e.g. ICc, AAF and AI are connected with both, the
thalamic subdivisions of the lemniscal line (MGv) and diffuse pathway (MGm); ICx and All are
connected with the diffuse and lemniscal adjunct thalamic nuclei; and PAF, VPAF and VE are
terminal fields of all three pathways. See Abbreviation Table for nomenclature.
Niimi, 1980; LeDoux et al., 1985; Takada et al., 1985). Neurons in the M G m are
responsive primarily to a broad range of frequencies and have no tonotopic organization
(Aitkin, 1973; Calford 1983; Phillips and Irvine, 1979; Toros-Morel et al., 1981). That
M G m neurons have the largest extent of dendritic arborization in the medial geniculate
nucleus (Morest, 1964; Oliver, 1982; Winer, 1985; Winer and Morest, 1983), suggests that
they may sample a wide range of afferentation. Therefore, the broad frequency tuning may
result from a convergence of input from ICc cells which are narrowly tuned to different
frequencies. Unlike the MGv, neurons in the M G m also respond to somatosensory stimuli
(Khorevin, 1978; Khorevin, 1980; Love and Scott, 1969; Poggio and Mountcastle, 1960;
Blum et al., 1979; Wepsic, 1966).
The thalamocortical connectivity of M G m is unique in terms of its areal extent and
cortical laminar relations. Unlike all other subdivisions of the M G N , which project to the
middle layers in restricted portions of auditory cortex, M G m projects primarily to the most
superficial layer, lamina I* (Jones and Burton, 1976; Niimi and Naito, 1974; Niimi et al.,
1984; see also Mitani and Shimokouchi, 1985; Mitani et al., 1985). In addition, cortical
projections to M G m originate in layer V, while descending afferents to other subdivisions
originate in layer VI (Diamond, 1982; K a w a m u r a and Diamond, 1978; Kelly and Wong,
1981). Also unique, the M G m projects to every one of the several fields that comprise the
auditory cortex (Andersen et al., 1980; Bentivoglio et al., 1983; Niimi and Matsuoka,
1979).
Because of the widespread convergence of inputs and extensive efferentation, we
designate M G m and all structures to which it is directly connected as the "diffuse"
pathway.
4.2.5. R e s u m e
The organization of higher auditory pathways is represented schematically in Fig. 7. The
lemniscal line is striped left, the diffuse pathway is solid and the lemiscal adjunct pathway
is striped right. In this schema, cortical and midbrain areas can be components of more
than one pathway. For example, the central nucleus of the inferior colliculus (ICc), an
* Projections of MGm to layer I throughout auditory cortex have been found in all species which have been
studied (e.g. rhesus and squirrel monkeys, cat, rat and tree shrew). Certain species such as the tree shrew (Oliver,
1982; Oliver and Hall, 1978) and rat (LeDoux et al.. 1985; Ryugo and Killackey, 1974; Herkenham, 1980) also
have MGm projections to the lower layers as well.
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
15
TABLE 2. COMPLEMENTARY NATURE OF EXPERMENTAL
PARADIGMS OF SENSORY PHYSIOLOGY AND LEARNING
Stimulus Parameters
Sensory Physiology
Learning
Physical
Psychological
Vary
Constant
Constant
Vary
obligatory relay for most ascending auditory information, is tonotopically organized and
projects a topographic representation of the cochlea upon the thalamic lemniscal line
(MGv). In addition, ICc has efferents to the MGm, which has broadly tuned cells and no
apparent frequency organization. In the cortex, the primary field (AI) receives input from
the lemniscal line (MGv) and also the diffuse pathway (MGm). By contrast, the secondary
cortical field is a component of the leminiscal adjunct pathway (MGdc and MGvl) and
diffuse pathways (MGm). The posterior fields (PAF, VPAF and VE) are components of
all three pathways.
4.3. APPROACHING PHYSIOLOGICAL PLASTICITY IN THE AUDITORY SYSTEM
A distinction may be made between two types of stimulus parameters which can affect
the responses of neurons: physical and "psychological" parameters. Physical parameters
are well known; for acoustic stimuli, they include frequency, intensity, and stimulus
duration. Psychological parameters refer to the significance and meaning of stimuli.
Foundational data in sensory physiology are obtained by determining the relationships
between physical parameters and neuronal responses at all levels of the investigated system.
These studies generally utilize anesthetized animals in order to maintain a constant
behavioral state; apparently, anesthesia also eliminates the analysis of stimulus significance
by the nervous system. In contrast, cellular sensitivity to psychological parameters is
determined by recording physiological responses to a stimulus while its significance is
varied and its physical parameters are held constant. (Table 2, see also Weinberger and
Diamond, in press).
The tripartate organization of the thalamocortical auditory system is based on anatomical and sensory physiological criteria. In order to determine if this organizational
schema has functional significance for physiological plasticity, we recorded the discharges
of neurons in various thalamic and cortical regions while the significance of a sound was
changed during classical conditioning; the physical parameters of this conditioned stimulus
were held constant. The change in stimulus meaning was independently verified by
development of the pupillary dilation conditioned response.
To date, we have studied cellular activity in the thalamic components of the lemniscal
line (MGv) and diffuse pathways (MGm), and in auditory cortex, we have studied cellular
activity in the primary (AI), secondary (All) and ventral ectosylvian (VE) fields. Each
cortical field is a component of the diffuse pathway, by virtue of its connection with MGm.
In addition to being components of the diffuse pathway, AI receives lemniscal line input,
All receives lemniscal adjunct input, and VE is innervated by both lemniscal line and
lemniscal adjunct pathways.
5. Physiological Plasticity in the Medial Geniculate Nucleus
5.1. EFFECTS OF LEARNING
5. I. 1. Compartmentalization of learning-induced plasticity
In an initial experiment, we recorded the discharges of unit "clusters" (so-called
multiple-unit recordings)* from microelectrodes chronically-implanted in the MGN.
* Multiple-unit or cluster recordings consist of the discharges of more than one neuron; in most cases, the
number of neurons contributing to the record is not reported or known. Neither is it known whether the same
neurons are contributing to the record over a period of time. This type of data is usually obtained with a
low-impedanceelectrode (< 1 Mohm).
PUPIL
2oo
180 l
i~
120
100
8o
o=
6o
~o
o
20
i
I
I
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2
3
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45
OF F I V E
6
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7
8
J
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2O0
180
160
~-~ 1 4 0
~: 1 2 0
N
'7' 1 0 0
~
°°t
.o!
ao
i
2o+
o /
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- 6 0
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L
1
2
3
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4
5
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i
--4
8
6
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MGm
180
.°°t
160
140
-
100
!
~'
8o "
~
60 T
g
20
40
-
--60
2
1
2
3
BLOCKS
4
5
OF F I V E
6
7
8
TRIALS
FIG. 8. Group functions (n = 6) for pupillary dilation, and multiple unit discharges in the ventral
(MGv) and magnocellular (MGm) medial geniculate nucleus during classical conditioning in
response to an acoustic conditioned stimulus. All values are referenced to the average response
during sensitization (not shown). Negative values at the beginning of conditioning for the pupil
and the M G m reflect the habituation of these responses during the prior sensitization period. Note
the rapid increase in response for the pupil and the M G m and the lack of response plasticity for
the MGv. Each point is the mean _+ SE.
16
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
17
Responses to the acoustic CS were recorded simultaneously from two subdivisions of this
nucleus during pupillary conditioning (Ryugo and Weinberger, 1978). Behavioral associative learning was rapid, as evidenced by development of the pupillary dilation conditioned
response to the conditioned stimulus in an average of 16.3 trials. Of greater importance,
discharge plasticity developed as quickly in the medial geniculate nucleus. Most noteworthy, there was a clear difference in physiological plasticity within the M G N . Neurons
in the lemniscal line (MGv) failed to exhibit any plasticity; that is, they responded to the
acoustic CS without change during learning. In stark contrast, neurons in the diffuse
subsystem (MGm) developed systematic and highly significant increases in response to the
CS during conditioning; no such changes were found during the preceding sensitization
control period (Fig. 8). Furthermore, during subsequent discrimination training between
two acoustic stimuli (one paired with the US, the other unpaired), discriminative neuronal
changes developed only in the magnocellular MGN.*
This compartmentalization of learning in the M G N has also been found for other
species and conditioning paradigms. Gabriel et al. (1975) obtained similar results in rabbits
trained in an instrumental active avoidance task. Also, these findings have been reported
for the rat during appetitive training utilizing a hybrid classical-instrumental conditioning
task (Birt et al., 1979; Birt and Olds, 1981). Thus a functional distinction at the level of
the thalamus between the lemniscal line (ventral M G N ) and diffuse pathway (magnocellular MGN), based on the differential capacity to develop discharge plasticity during
learning, is maintained across species, and is expressed during both appetitive and
defensive learning.#
5.1.2. Plasticity at the level o f single neurons in the magnocellular medial geniculate nucleus
The results obtained with multiple-unit or "cluster" recordings provide an adequate
entry point into the analysis of physiological plasticity. However, they may not provide
a valid basis for inferences about the detailed involvement of single neurons in plasticity because each of the individual neurons may not be affected in the same way by
associative processes. This could not be revealed by recordings in which the discharges
of many neurons are combined. The problem would be resolved by computer-assisted
sorting of unitary waveforms, but this technology is still in the developmental stage
(Schmidt, 1984). Therefore, we recorded activity directly from one neuron throughout each
training session.
In a fine-grain analysis of physiological plasticity in the magnocellular M G N , we
obtained single unit data during pupillary conditioning (Weinberger, 1982a). Most cells
(71%) developed significant changes in response to the acoustic CS during conditioning.
Surprisingly, the directionality of the changes was not consistent with that of the changes
in multiple unit activity. Although there were increases in evoked activity (Fig. 9), 29%
of the plastic neurons developed significant decreases during learning. A commonality
between the multiple and single unit recordings was that changes developed rapidly (10-20
trials) (Fig. 10).
These findings provided the first data on the physiological plasticity of single neurons
in the auditory system during the acquisition of a behavioral conditioned response. In
extending prior multiple unit data, they also revealed heterogeneity of physiological
plasticity. We will return to this important point later (Section 6.2.2.2).
* Neurons in the "'dorsal" divisionof the MGN were also non-plasticduring learning. The recordingsites were
all within, or in the immediatevicinityof the deep dorsal division of the MGN, which has narrowly tuned cells
arranged tonotopically(Calford, 1983).Therefore, recordings in both the dorsal and ventral subdivisions of the
MGN are considered as located in the non-plastic, thalamic lemniscal line.
t This does not imply that the responses of the MGv to the same acoustic stimulus are constant. They may
vary with the state of arousal (Imig et al., 1972;Humphrey and Orman, 1977;Orman and Humphrey, 1981;see
also Ryugo and Weinberger, 1976).However,even when the number of spikes elicited by a stimulus varies, there
is maintained a constancy of the overall pattern of discharges (Imig and Weinberger, 1973). In any event,
associative learning does not alter responses in this nucleus.
JPN 29/1--B
18
N.M. WEINBERGERand D. M. DIAMOND
UI7
SENS
COND
COND
PUPIL
I
COND
FIG. 9. Histograms and pupillary records for a single neuron in the magnocellular medial geniculate
nucleus during sensitization (SENS) and subsequent CS-US pairing (COND). Each histogram is
the sum of discharges of five consecutive trials; bar size = 50 msec. The histograms are complete
data for one training session: 10 trials of sensitization and 50 trials of conditioning. Consecutive
records start at the top of the left column and read downward, ending at the lower right.
Presentation of the CS is indicated by the horizontal bar under each histogram (1 sec). Note the
increased response to the CS during conditioning compared to responses during sensitization. This
associative increase developed within the first 5 trials of CS-US pairing (compare the second SENS
histogram with the first COND histogram) and is maintained or increased (except for the 8th block)
throughout conditioning (compare the lower right histograms with the SENS histograms).
Calibration, 12 spikes per division. Sample pupillary records (right) read from top to bottom:
sensitization, trials 1, 7, 10; conditioning, trials 1, 5, 10, 20, 30, and 45. Note the decrement in
pupillary response during sensitization and the development of the conditioned response during
conditioning. Note also the constant size of the dilation to the US throughout conditioning, and
the growth of the CR relative to this unconditioned response. Stimulus markers, CS = 1 sec,
downward marker = US. (From Weinberger, 1982.)
5.2. LONG TERM POTENTIATION IN THE MAGNOCELLULAR MEDIAL GENICULATE NUCLEUS
The p h y s i o l o g i c a l plasticity that develops r a p i d l y in the m a g n o c e l l u l a r M G N d u r i n g
learning could be s e c o n d a r y to plasticity that develops elsewhere, o r it could d e v e l o p
locally. O n e way o f a p p r o a c h i n g this issue is to d e t e r m i n e if s y n a p t i c plasticity can be
i n d u c e d within this nucleus. A form o f s y n a p t i c plasticity that is o f p a r t i c u l a r relevance
to learning was first described by Bliss a n d L o m o (1973), who f o u n d that brief, high
frequency s t i m u l a t i o n o f the p e r f o r a n t p a t h resulted in a long lasting e n h a n c e m e n t o f
s y n a p t i c t r a n s m i s s i o n in the h i p p o c a m p u s . Subsequently, this " l o n g term p o t e n t i a t i o n "
( L T P ) has been a n a l y z e d extensively (e.g. L y n c h et al., 1982). W e a p p l i e d this technique
to d e t e r m i n e if s y n a p t i c plasticity c o u l d be induced in the M G m ( G e r r e n a n d W e i n b e r g e r ,
1983).
M o n o s y n a p t i c field potentials in the M G m were e v o k e d by single pulse s t i m u l a t i o n o f
a m a j o r a s c e n d i n g input, the b r a c h i u m o f the inferior colliculus (BIC). H i g h frequency
s t i m u l a t i o n i m m e d i a t e l y i n d u c e d LTP: the a m p l i t u d e o f the response increased a n d its
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEx
GROUP
N
=
A
17
.50
,tO
t14
L
30
20
10
O
-10
-20
-30
-40
-50
1
2
BLOCKS
3
FOUR
OF
GROUP
N
=
.4
TRIALS
,5
4
TRIALS
5
[]
10
50
.4.0
i
20
10
F.
~
--10
~
--20
~
-30
-40
-50
1
2
BLOCKS
~.
FOUR
OF
GROUP
N
=
C
7
5C
,,lc
r--
~
2c
N
c
~.~ - - 1 0
N
~
--20
-30
-40
-50
1
2
BLOCKS
OF
3
FOUR
~TRIALS
5
F I G . 10. Group functions for the discharges of single neurons in the magnoce]lular medial
geniculate nucleus during conditioning. Values are the mean percent change (_+ SE) from the
sensitization period (not shown). Data are grouped according to whether neurons developed an
increase (A), no systematic change (B), or decrease (C) in response to the conditioned acoustic
stimulus. Note the significant increases and decreases by the second block of conditioning
(trials 5-8).
19
20
N . M . WEINBERGERand D. M. DIAMOND
c
A
Itcolo
itco,o
i
ORTHO
l
, ~
h iI
i ,/
I
•
,
Ii
PRE
ii
!'/
ji'
ANTI
I
: ;' !y,'
PRE
POST
POST
l>I
J
t
It
"
30'
t
2'
PRE HF
2'
II
30'
60'
POST HF
I
FIG. l l. Long-term potentiation in the magnocellular medial geniculate nucleus. A: Schematic
representation of electrode placements in the magnocellular medial geniculate nucleus (MGm),
brachium of the inferior collicnlus (BIC) and inferior colliculus (IC). B: Representative MGm
responses to single stimuli delivered to the BIC at various times before (PRE) and after (POST)
high frequency (HF) stimulation of the BIC. C: Representative MGm (ORTHOdromic) and IC
(ANTIdromic) responses to BIC stimulation 5 min before (PRE) and 40 min after (POST) HF
stimulation of the BIC. Arrows indicate time of stimulus; triangles indicate pints used for amplitude
and latency measurements. Calibrations: l msec and 100 microvolts. (From Gerren and
Weinberger, 1983.)
latency decreased. Both signs of LTP were maintained for the duration of the recording
session (60-180 min) (Figs 11 and 12). Potentiation of the evoked potential amplitude and
reduction of its onset latency were also observed for input/output functions (Fig. 13). The
enhancement of synaptic efficacy recorded in the magnocellular MGN was not due to a
change in the excitability of the BIC inputs, because it developed in the absence of any
change in the antidromic response within the inferior colliculus (Fig. 13).
Long term potentiation in this nucleus also was obtained at the level of single units.
Following brief high frequency stimulation of the BIC, the following changes developed
immediately: (1) a decrease in spike latency; (2) an increase in the number of evoked
discharges; (3) a decrease in the variability of latency of the first spike; and (4) a
decrease in the variability of interspike discharges within an evoked burst (Weinberger,
1982) (Fig. 14).
These findings demonstrate that synaptic facilitation can develop locally in the
magnocellular MGN. They also indicate that both LTP and learning-induced physiological plasticity can develop rapidly within the thalamic component of the diffuse
auditory pathway. This strengthens the argument for a role of LTP in associative learning,
and underscores the critical position of the magnocellular MGN as a possible contributor
to physiological plasticity in the auditory cortex. That all auditory cortical fields are
innervated by the magnocellular M G N leads to the expectation that cortical cells may be
influenced by the synaptic plasticity which appears to be generated within this nucleus
during learning. In the following sections, we present data on physiological plasticity in
the primary (AI), secondary (AII) and ventral ectosyvian (VE) auditory cortical fields
during learning.
PHYSIOLOGICALPLASTICITY1N AUDITORYCORTEX
21
N=7
130
~
II I
120
Z
ok)
100
N=8
........
B_.
:E
O1.5~
t_J
Z 1.51
.,J
1.4~
I
-I0
I
[
[
I ~
HF
I
i
I
i
i
I0
i
I
i
[
i
i
i
i
i
i
20
30
TIME (rain)
i
i
i
i
i
40
i
t
t
t
I
i
I
i
50
FIG. 12. The effects of high frequency stimulation (HF) on the MGm monsynaptic response to BIC
stimulation. A: Amplitude with respect to the pre-HF mean (dashed line). Each point represents
the mean (+SE) for the 7 of 10 experiments in which amplitude changed. B: Mean (+SE)
latency-to-minimum (maximum negativity) for the 8 of l0 experiments in which latency was
changed following high frequency stimulation. Note the immediate and maintained increase in
amplitude and decrease in latency. (From Gerren and Weinberger, 1983.)
6. Physiological Plasticity in Auditory Cortex
6.1. BACKGROUND
That learning alters physiological indices of sensory cortical function has been known
since the dawn of electroencephalography. The finding was serendipitous. Durup and
Fessard (1935), were studying the blocking of the alpha rhythm by light flash in the visual
cortex of man. They noted that this response of the electroencephalogram actually
occurred prior to the presentation of the flash. They sought and found the source of this
phenomenon. Prior to the presentation of each flash, they activated a camera to film the
oscilloscope record; the shutter made an audible click. The alpha blocking (conditioned
response, CR) was induced by paired presentation of the click (conditioned stimulus, CS)
followed by the flash (unconditioned stimulus, US). The circumstances of this discovery
of electrophysiological classical conditioning indicated the readiness of the brain to
develop plasticity and also inaugurated research on the role of sensory cortex in learning.
Since that first, inadvertent demonstration of neurophysiological conditioning, systematic research has provided abundant additional evidence of learning-induced plasticity in
the visual, somatosensory and auditory cortices; the auditory cortex has received most
attention. (General reviews of early findings have been provided by John, 1961; Morrell,
1961; and Thompson et aL, 1972; more recent examples of learning-induced physiological
plasticity in visual and somatosensory cortex are Morrell et al., 1983; and Voronin et al.,
1975, respectively.) The extensive investigation of the effects of learning on neurophysiological responses in auditory cortex is summarized in Table 3. This information
reveals that learning effects have been reported over the last thirty years, in several
mammals, using various training regimens, recording different types of neurophysiological
activity. The phenomenon appears to be widespread and highly replicable.
22
N.M. WEINBERGERand D. M. DIAMOND
N=7
lOO
N:2 .,--~2---~" 100
.~...~--~---~
//
80
~
80
~
6o
60
~ 40
X
40
._1. a,
:E
MONO
2O
20
.<
c
I
I
i
t
I
I
I
l
i
i
i
E 2.1
Z
~
~E
1.9
t
~
i
i
l
i
N=2
N=8
2.3
I
L
100
x
80
PRE HF
. . . . POST HF
60
2
t..) 1.7
z
40
-~ 1.5
20
B
I
2
3
4
5
6
7
8
STIMULUS LEVEL (V÷lO)
FIG. 13. The effects of high frequency stimulation on input-output curves (I/0 functions) obtained
20 minutes prior to the start of the main experimental series (see Fig. 12) and at least one hour
following high frequency stimulation. A and B: Mean amplitude and latency functions, respectively, for the MGm monosynaptic response to BIC single stimuli as a function of stimulus
intensity. C and D: Amplitude functions for two experiments in which orthodromic (C) and
antidromic (D) responses were recorded simultaneously. Note the orthodromic effect in the absence
of any change in the antidromic response. Solid circles, before HF and open circles, after HF
stimulation. Each point is the mean of the N value (+ SE) presented. The stimulus level corresponds
to current intensities of 0.1-0.8 mA. (From Gerren and Weinberger, 1983.)
T a b l e 3 also p r o v i d e s i n f o r m a t i o n a b o u t the inclusion o f two essential controls: (1) a
c o n t r o l for n o n - a s s o c i a t i v e factors a n d (2) assurance o f stimulus c o n s t a n c y at the cochlea.
T h e f o r m e r has been discussed p r e v i o u s l y (Section 3.3). It need only be recalled here that
in the absence o f an a d e q u a t e control, such as c o m p a r i n g c o n d i t i o n i n g effects with
responses to the same acoustic stimulus d u r i n g a sensitization period, one c a n n o t justifiably
c o n c l u d e t h a t the o b s e r v e d effects are due to associative factors.*
C o n t r o l o f the acoustic stimulus at the cochlea is m o r e difficult to achieve, b u t no less
i m p o r t a n t . Unless stimulus c o n s t a n c y is d e m o n s t r a b l e , it m a y be impossible to d e t e r m i n e
w h e t h e r changes in n e u r o n a l responses are due to intrinsic m e c h a n i s m s o f learning o r to
learning-related changes in effective stimulus intensity. V a r i a b l e s which can p r o d u c e a
spurious o u t c o m e include p o s i t i o n a n d distance o f the h e a d with reference to the s o u n d
source ( M a r s h et al., 1962; Starr, 1964), a n d s o u n d - s h a d o w i n g by the p i n n a e ( W i e n e r et
al., 1966).
Use o f b o t h c o n t r o l p r o c e d u r e s was n o t instituted routinely before the mid-1970s (Table
3). In o u r case, for the d a t a p r e s e n t e d in following sections, we used a sensitization c o n t r o l
p e r i o d preceding CS--US pairing. C o n s t a n c y o f the c o n d i t i o n e d stimulus at the cochlea was
c o n t r o l l e d by m a i n t a i n i n g a fixed relationship between the s p e a k e r a n d the t y m p a n i c
* Discriminative responses in the auditory system which have an extremely short latency (e.g. 4 msec) cannot
be explained by stimulus inconstancy at the periphery (Disterhoft and Stuart, 1976). Such findings, even in the
absence of explicit or verified control of the acoustic stimulus, provide adequate evidence of plasticity due to
central processes.
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
28
23
A. PRE HF: I min
21
14
7
l
28
O3
LLJ
V
i
i
i
i
B. POST HF:2 rain
21
fi-14
O3
281
C. POST HI
52 min
21
14
7
0
10
15
rnse~
FIG. 14. Long term potentiation in the MGm at the level of single neurons. Records are from one
cell at various times. The inset shows superimposition of burst responses to five single stimuli
applied to the brachium of the inferior colliculus one minute preceding and thirty two minutes
following a single train of high frequencies stimulation of the BIC. Note the variability prior to
HF stimulation (top) compared to the lack of variability and also the decrease in latency to the
first spike following HF stimulation (bottom). Calibrations: I msec, 100 microvolts. Histograms
(left) are the sum of responses to 25 single test stimuli before (A), shortly after (B) and 32 minutes
(C) following HF stimulation. Following HF stimulation, notice the decrease in latency to the first
spike, increase in the probability of response to each test stimulus, increase in the number of spikes
per burst, decrease in the variability of interspike intervals, and continuing trend of these change
(compare B and C).
membrane. Verification of acoustic control was obtained by documenting a lack of change
in the cochlear microphonic during conditioning (Ashe et al., 1976).
6.2. PRIMARY AUDITORY CORTEX
(AI)
6.2.1. Frequency specific habituation in primary auditory cortex
Although the major focus of this paper concerns the effects of associative processes on
discharge activity in auditory cortex, it is noteworthy that a form of non-associative
plasticity also develops in this field. We refer here to habituation, which is a systematic
decrement in evoked responses to repeated acoustic stimulation. While such decrements
are attributable to learning per se, rather than to refractory or fatigue processes
(Thompson and Spencer, 1966), they are not associative (see also Section 2). However, a
comprehensive account of physiological plasticity in the auditory cortex must include the
effects of habituation as well as associative learning. It is not yet known whether these two
forms of physiological plasticity are related, particularly at the biophysical level (Hawkins
and Kandel, 1984; Mackintosh, 1985), so it is germane to determine if they both develop
in the same neural structures.
N. M. WEINBERGERand D. M. DIAMOND
24
TABLE 3. NEUROPHYSIOLOGYOF LEARNING IN AUDITORY CORTEX
Authors
Year
Animal
Record '~
Behavior
Galambos et al.
1956
Cat
EP
Jouvet
Beck et al.
Gluck and Rowland
Roitbak et al.
Marsh et al.
Moushegian et al.
Galambos and Sheatz
1956
1958
1959
1960
1961
196t
1962
EP
EEG
EEG
EP
EP
EP
EP
Gerken and Neff
Buchwald et al.
Hall and Mark
Mark and Hall
Popova c
Halas et al.
Popova
Sommer-Smith and Moricutti
Popova
Romanovska
Saunders
Olds et al.
Disterhoft and Olds
Cassady et al.
Majkowski and Sobieszek
Oleson et al.
Disterhoft and Stuart
Dolbakyan
Gasanov and Galashina
Woody et al.
Kitzes et aL
Dumenko and Sachenko
Dumenko and Sachenko
Dolbakyan e
Dumenko and Sachenko
Gasanov and Galashina
Olds et al.
Pukhov and llyushenok
Galashina and Bogdanov
Galashina and Bogdanov
Popova and Uvarov
Kraus and Disterhoft
Weinberger et al.
Diamond and Weinberger
Diamond and Weinberger
1963
1966
1967
1967
1969
1970
1970
1970
1971
1971
1971
1972
1972
1973
1975
1975
1976
1976
1976
1976
1978
1979a
1979b
1980a
1980
1980
1980
1980
1981 a
1981 b
1981
1982
1984
1984
1986
Cat
Cat
Cat
Cat
Cat
Cat
Cat
Monkey
Cat
Cat
Rat
Rat
Dog
Cat
Dog
Cat
Dog
(?at
(?at
Rat
Rat
Dog
('at
('at
Rat
Dog
Cats
Cat
Cat
Cat
Cat
Dog
Cat
Cat
Rat
Cat
Cat
Cat
Dog
Rabbit
Cat
Cat
Cat
Pupil,
"Emotional"
None?
Flexion
None
Head Mov.
None
None
Blink & Head
Mov.
Flexion
Flexion
Freezing
Freezing
Flexion
Flexion
Flexion
Head Mov.
None'?
Eyelid
Mov.
Head Mov.
Head Mov.
Flexion
Press
Pupil
Head Mov.
Flexion
None?
Eyeblink
Pupil
Respir.
Respir.
Flexion
Respir.
None
Head Mov.
None'?
Mov.
Mov.
None?
NM
Pupil
Pupil
Pupil
MU
MU
EP
EP
EP
MU
EP
EP
EP
EP
EP
MU
MU
MU
EP
MU
MU
EP
S"
S
S
S
S
EP
S
Sd
MU
EP
S~
S'~
EP
MU
S
S
S
Control b
Acous. Non-Assoc.
(Y)
N
N?
N?
N
N
N
(Y)
N
N?
N?
Y
N
N
N
N
N
Y
(Y)
(Y)
N?
N?
N
N
N?
N
(Y)
(Y)
(Y)
N
N
N
N
N
N
Y
N
N
N
N
N
Y
Y
Y
N
Y
N
Y/?
Y
Y
N
N
(Y)
Y
Y?
Y?
N
Y?
N
N
Y
N
N
N?
N
Y
Y
Y
?
N
Y
N
Y?
Y?
N
Y?
N?
Y
N
N
N
N
Y
Y
Y
Y
a Denotes type of neurophysiological recording. Abbreviations: EP=evoked potentials; EEG=electroencephalogram; MU = multiple unit discharges; S = single unit spikes.
b Indicates the presence or absence of controls for acoustic constancy ("Acous.") and non-associative factors
("Non-Assoc"). Abbreviations: Y = Yes; N = No; ( ) - P a r t i a l control; ? ~ Uncertain.
c Translation of Popova, 1968.
d Report of several single units separated only by amplitude discrimination, which is not widely accepted as
adequate for demonstration of single unit discharges.
Translation of Dolbakyan, 1980.
H a b i t u a t i o n w a s i n v e s t i g a t e d b y r e c o r d i n g t h e d i s c h a r g e s o f n e u r o n a l c l u s t e r s in p r i m a r y
auditory cortex (AI) during repeated presentation of tone or white noise bursts. Also, we
r e c o r d e d s i m u l t a n e o u s l y t h e r e s p o n s e s o f n e u r o n s in t h e first c e n t r a l a u d i t o r y s t a t i o n , t h e
v e n t r a l c o c h l e a r n u c l e u s , a n d p u p i l l a r y b e h a v i o r ( W e i n b e r g e r e t a l . , 1975). P u p i l l a r y
dilation responses decremented systematically during repeated presentation of acoustic
s t i m u l i (see a l s o C o o p e r e t a l . , 1978). C o n c u r r e n t l y , t h e r e s p o n s e s o f n e u r o n s in p r i m a r y
a u d i t o r y c o r t e x a l s o h a b i t u a t e d . I n c o n t r a s t , t h e r e w a s n o effect in t h e c o c h l e a r n u c l e u s
(see a l s o W e i n b e r g e r e t a l . , 1969). I n c r e a s i n g a r o u s a l , b y t h e a p p l i c a t i o n o f a n o v e l
c u t a n e o u s s t i m u l u s , d i d n o t a l t e r h a b i t u a t i o n (Fig. 15).
T h e s e f i n d i n g s (see a l s o e.g. S i m o n s e t a l . , 1966; a n d W i c k e l g r e n , 1968) i n d i c a t e t h a t
n e u r o n s in t h e p r i m a r y a u d i t o r y c o r t e x a r e a f f e c t e d b y s t i m u l u s m e a n i n g d u r i n g n o n -
25
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
1'50
140
150
i40
COCHLEAR N
AUDITORY CX
N:B
PUPIL
120
120
I00
I00
I'-Z
8O
W~
8O
ac,~
Q,..
40
4O
20
2O
0
-20
,,
5
I0
15
20
I
5
I0
15
20
I
I
,
i
5
t,
,
~
L
I0
h
,
I
t
I~IL
15
i
i
I
20
-20
FIG. 15. Average responses of the pupil (n = 8), primary auditory cortex (n = 8), and lower
auditory system (ventral cochlear nucleus) (n = 6) to repeated presentations of an acoustic stimulus
(white noise burst, approximately 1/min). Open symbols denote background (pre-trial) levels;
dosed symbols denote responses evoked by the acoustic stimulus. Note the decrement of evoked
pupillary dilation and discharges in auditory cortex, in contrast to lack of change in the cochlear
nucleus, during trials 1-15. Background levelsare unchanged during habituation. A novel stimulus
(cutaneous stimulation, arrow) produces general arousal, as indicated by a large increase in
background pupillary size, without any significant effecton habituation of evoked responses of the
pupil and auditory cortex. The abscissa is trials (stimulus presentations) and the ordinate is the
percent of response on the first trial for evoked (left ordinate) and background (right ordinate)
measures. (From Weinberger et al., 1975.)
associative learning (i.e. habituation). In this case, the stimulus meaning is that the sound
is without signal value; this was assayed behaviorally by the systematic decrement in
pupillary dilation to repeated acoustic stimulation. Habituation in AI is not due to
peripheral or lower auditory system processes, in view of the lack of change in the cochlear
nucleus. Furthermore, it is not attributable simply to a decrease in arousal because
habituation is not altered by increasing arousal level.
Although behavioral habituation to tones still occurs following removal of AI, more
complex forms of habituation, such as habituation to an acoustic pattern, require an intact
auditory cortex (Sharpless and Jasper, 1956). This indicates that discharge plasticity in AI
during habituation may reflect higher order analyses of sounds than those occurring more
peripherally.
Habituation might reflect a general decrease in cortical responsivity or it might be
specific to the repeated stimulus. To resolve the issue, we used two tones, only one of which
was used explicitly as a habituating stimulus. (Westenberg et al., 1976; Westenberg and
Weinberger, 1976). First, tones of two different frequencies were presented in an
alternating sequence. Then one of the tones was presented repeatedly for 15 min. During
this time, the evoked potential (EP) in AI systematically decreased in amplitude. Following
this habituation o f the EP, the alternating tones were presented once again (Fig. 16, top).
We compared responses to the alternating tones preceding and following repetition of the
single tone. I f habituation were general, then responses to the non-repeated tone should
be reduced as well as those to the repeated tone. This was not the case; the decrement was
specific to the tone that was presented in isolation (Fig. 16, bottom). This design ruled out
any possible confounding effects of change of behavioral state because the tones were
presented in alternating sequence during the test periods (before and after the repeated
single tone). In a reversal test, the EP habituation was specific to the second tone when
it was the isolated, repeated stimulus (Fig. 16, bottom). This proved that habituation is
specific to the stimulus that is repeated.
These findings demonstrate that physiological plasticity develops within AI for a simple,
non-associative form of learning, i.e. learning that a repeated stimulus has no important
consequences. This was observed both for field potentials and for the discharges of neurons
in response to acoustic stimulation. Furthermore, it is specific to the stimulus that is
repeated, and therefore cannot be attributed to a general loss of responsiveness to acoustic
stimuli or to a general change in the state of excitability of the auditory cortex. Finally,
26
N.M.
WEINBERGER a n d D. M. DIAMOND
the specificity of this phenomenon suggests that plasticity in AI is sensitive to specific
informational aspects of acoustic stimuli. In the case of habituation, this appears to be
concerned with rapidly learning that a potentially important stimulus actually has no
particular significance.
Repetit,ve-pre
i
,
REPETITIVE
Pip
Jr
Series
RepehHve post
H, Hz
LO HZ
Test-pre
Test-post
Test-pre
Test - post
Repetitive-ore
--REPETITIVE
A
Pip
S e r i e s - -
Jr
Repeht,ve- post
Repetitive
B
Tes.__t
f
HI Repehhve
H, Hz
d
" ,o ' e'o " 3o
~o ' 55
.~L.
h
65
C
,5
a5 ' 93 " ,6o
[6
,o
~o
LoHz
30
~o
~0 " ~
7o " 80 ~
,oo
]
13
I
.....7 \
LoHz
.....
,
¸.¸,¸,
I
.... I
II
o " ,0 " 20 " 30 " 4b " 4o ' ~ " rb " e~ " 96 " ,oo ' 6
msec
,O " zO " /~ ' 4b " ~ " 6o
ro
a0
9o " , ~
I mse¢
FIG. 16. F r e q u e n c y specific h a b i t u a t i o n o f e v o k e d p o t e n t i a l s in the p r i m a r y a u d i t o r y cortex. T o p :
d i a g r a m o f the e x p e r i m e n t a l p r o t o c o l . H i g h a n d l o w t o n e pips (100 msec) were first p r e s e n t e d
a l t e r n a t e l y (l/sec) f o l l o w e d b y r e p e t i t i o n o f the h i g h t o n e (900 tones), a n d t h e n b y p r e s e n t a t i o n
o f the initial a l t e r n a t i n g sequence; ( a d d i t i o n a l h i g h t o n e s p r e s e n t e d at 2 H z f o l l o w i n g this w e r e used
f o r a n o t h e r c o n t r o l , n o t d i s c u s s e d here). A v e r a g e e v o k e d p o t e n t i a l s to the s a m e f r e q u e n c y delivered
b e f o r e a n d a f t e r r e p e t i t i o n o f the h i g h t o n e a l o n e w e r e c o m p a r e d . T h i s p a r a d i g m w a s t h e n r e p e a t e d ,
c o u n t e r b a l a n c e d b y u s i n g the l o w t o n e as the r e p e a t e d s t i m u l u s (lower d i a g r a m ) . B o t t o m : a v e r a g e d
e v o k e d p o t e n t i a l s to h i g h (3.2 k H z ) a n d l o w (1.0 k H z ) t o n e s b e f o r e ( " p r e " ) a n d f o l l o w i n g ( " p o s t " )
r e p e a t e d p r e s e n t a t i o n o f o n e t o n e alone. F r e q u e n c y - s p e c i f i c h a b i t u a t i o n is evident in the smaller
c o m p o n e n t s o f " p o s t " e v o k e d p o t e n t i a l s d u r i n g the repetitive c o n d i t i o n . ( F r o m W e s t e n b e r g a n d
W e i n b e r g e r , 1976.)
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
Auditory
27
Cortex
Sens.
Disc.
Day 1
CS+ (WN)
CS- (Tn)
Day 8
CS+ (Tn)
CS- (WN)
FIG. 17. Discrimination and discrimination reversal in primary auditory cortex. Sample histograms
of multiple unit activity in response to white noise (WN) and tone (Tn) during sensitization
(acoustic stimuli and US presented randomly) and discrimination (one sound paired [CS + ], other
sound unpaired [CS-] with the US). Each histogram is the sum of discharges on 10 consecutive
trials. During the first training session, note the large increased response to the CS+ compared
to changes in response to the C S - from sensitization to discrimination training. One week later
(Day 8), training was repeated with the acoustic stimuli reversed. Note the neuronal "memory"
of the original CS + (WN), revealed by the large response to WN at the beginning of Day 8 vs.
response to this stimulus at the beginning of Day 1. Also note, the increased response to the CS +
and decreased response to the C S - during training on Day 8. Horizontal line under each
histogram is the stimulus marker (5 see). Ordinate, 96 spikes per division.
6.2.2. Associatively-induced plasticity in primary auditory cortex
6.2.2.1. Multiple unit activity
H a b i t u a t i o n is p r o t o t y p i c a l o f n o n - a s s o c i a t i v e learning. In further experiments, we
focused on associative effects at the a u d i t o r y cortex. In an early experiment, we r e c o r d e d
m u l t i p l e - u n i t activity o f n e u r o n s in A I (Oleson et al., 1975). M i c r o e l e c t r o d e s were
i m p l a n t e d c h r o n i c a l l y so t h a t recordings f r o m the s a m e cortical sites c o u l d be o b t a i n e d
over days. C o n t r o l s for n o n - a s s o c i a t i v e factors (Section 3.3) included a sensitization
p e r i o d , d i s c r i m i n a t i o n t r a i n i n g between two s o u n d s (tone a n d white noise), a n d s u b s e q u e n t
d i s c r i m i n a t i o n reversal t r a i n i n g one week later.
Behaviorally, the p u p i l l a r y C R d e v e l o p e d quickly, e x h i b i t e d d i s c r i m i n a t i o n between the
C S + a n d C S - , a n d s h o w e d d i s c r i m i n a t i o n reversal when the relation between these
stimuli a n d the U S was reversed. M o r e i m p o r t a n t l y , p h y s i o l o g i c a l plasticity also d e v e l o p e d
r a p i d l y , in less t h a n 20 trials. E v o k e d activity to the C S + d u r i n g c o n d i t i o n i n g was
significantly increased relative to sensitization. M o r e o v e r , there was a clear d i s c r i m i n a t i o n
effect; the C S + e v o k e d significantly m o r e discharges t h a n the C S - . Signs o f long term
s t o r a g e o f this p h y s i o l o g i c a l plasticity were also found: these a c q u i r e d differences were
still present one week later. F i n a l l y , the d i s c r i m i n a t i o n effect reversed d u r i n g s u b s e q u e n t
28
N.M. WEINBERGERand D. M. DIAMOND
reversal training, showing that the response plasticity was due to the associative relationship between the C S + and the US (Fig. 17).
These results demonstrate that stimulus-specific discharge plasticity develops rapidly in
primary auditory cortex during associative learning. Furthermore, the changes were not
transient, but persisted until reversed by discrimination reversal training.
6.2.2.2. Physiological plasticity in primary auditory cortex at the level o f single neurons
As pointed out above (Section 5.2), multiple-unit recordings have both advantages and
limitations. Data from the magnocellular M G N revealed the insensitivity of such
recordings to systematic decreased response to the conditioned stimulus. Multiple unit
recordings in auditory cortex have also consistently reported increased evoked discharges
to the conditioned stimulus (e.g. Disterhoft and Olds, 1972; Disterhoft and Stuart, 1976;
Gabriel et al., 1982; Oleson et al., 1975). Considering the heterogeneity of plasticity in the
magnocellular MGN, it seemed possible that cluster recordings in auditory cortex also
could mask underlying heterogeneity of plasticity of the individual neurons.
In order to address this issue, we recorded the discharges of one neuron in primary
auditory cortex during each training session (Weinberger et al., 1984c). As with earlier
studies, the pupillary CR developed rapidly (6-20 trials). Most neurons (63%) developed
response plasticity to the CS during acquisition of the pupillary CR. Plasticity developed
quickly; it was evident within five trials and attained statistical criterion in an average of
13.2 trials. As in the case of the magnocellular MGN, the directionality of the changes
in evoked activity included increases and decreases. Changes in either direction were of
equal likelihood. Group functions for changes in evoked activity are presented in Fig. 18.
Apparently, as with the magnocellular MGN, significant decreases in evoked activity in
auditory cortex were masked in the earlier multiple unit recordings. In order to evaluate
this proposal, we constructed "multiple unit" histograms by compiling all data from each
single unit record. Figure 19 presents a comparison of evoked activity of all units during
two crucial parts of the training regimen: the last five trials of sensitization (which served
EVOKED ACTIVITY, AI
250 F
i
,
,ooh
t/
I--
50
\
Y
~i
:
]+,
(~-iO0
\
,,, -rodk
rF
I
\
/
,-, % y
/
-200
\
i
\T~
-250
o - - o I N C R E A S E n=6
o-. - o DECREASE n:7
~----A NO CHANGE n=7
-300
-550
I
I
i,
/\
2OO ~
i
L ~
~3
I
I
/
\,!/
l
I
{23~e
SENSITIZATION
~ l
)
i,
i
Bg,o
CONDITIONING
BLOCKS OF FIVE TRIALS
FIG. 18. Group functions for changes in the evoked activity of single neurons in primary auditory
cortex. The data were sorted according to whether the cells attained significant increases or
decreasesin evokedactivityduring conditioning,or failure to developsuch changes ("no change").
Each point is the mean percentage change in evoked activity for blocks of five trials relative to
the last five-trialblock during the sensitization period. Note that the developmentof increased and
decreased evoked discharges is evident during the first block of conditioning (trials 1 5). Vertical
bars denote _+SE.
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
29
AUDITORY CORTEX COMBINED
"I)/I
W
E
U~
mse¢
. . . . . . . . . . .
2.4 1
1.8
W
~tl 1.2
O'3
0.6
0
0
500
lO00
rnsec
FIG. 19. "Pseudo-Multiple Unit" poststimulus histograms constructed by summing the number of
discharges of all 21 neurons from which data were obtained during training. The numbers of spikes
were determined for 500 msec immediatelypreceding presentation of the conditioned stimulus and
for the 1000msec during presentation of the conditioned stimulus. Histograms depicted are for the
last five trials of the sensitization period (SENS) and for a representative five trial block (trials
16-20) during conditioning (COND). Notice the increase in evoked response following onset of
the conditioned stimulus during conditioning relative to sensitization.
as the baseline measure for identifying plasticity during conditioning) and trials 16-20
during conditioning. These conditioning trials were selected because most discharge
plasticity was present during this part of training. Note that there is an apparent increase
in evoked discharges following the onset of the CS during trials 16-20 of conditioning,
relative to the last 5 trials of sensitization. The decreases that were evident in single unit
data are masked when the evoked activity of all neurons are combined into this
pseudo-multiple unit activity record.
Although this histogram record is not identical to standard multiple unit records because
it was obtained from separate experimental sessions, various loci and its individual unit
composition is known, it provides a picture of an increase in evoked activity with learning.
Yet, the histograms of the individual neurons are heterogeneous, including decreases and
no changes, as well as increases during conditioning. Thus, multiple unit records cannot
be considered as representative of the activity of a homogeneous population of neurons
which develop an increase in response. In addition, the single unit data indicate that it
would be incorrect to conclude that the general excitability of auditory cortex simply
increases during learning.
6.3. SECONDARY AND VENTRAL ECTOSYLVIAN AUDITORY CORTEX (AII/VE)
6.3. I. Associatively-induced plasticity in secondary and ventral ectosylvian auditory cortical
fields
Because VE is a recent discovery (see Section 4.2.2), it was not known as a cortical field
distinct from A I I in previous published accounts. Therefore, in our first study of these
30
N . M . WEINBERGERand D. M. DIAMOND
A.
D-IC
B.
T'[-12A
SENSITIZATION
2O
TR 1-15
15
I0
II,
, tUlt
5
I
J
CONDITIONING
20-
~4
61
~l TR.l-15
"rD 1_1~
15IO5-
,
,I
It
t
t
25-] . . . . . .
TR 16-30
2015105-
-lO00 -500
0 500 lOO0
msec
-1000 0 lO00
msec
3000
FIG. 20. Peristimulus histograms of examplesof single unit activity in All during individual training
sessions. A: Cell II-1C developed an increase in both background and evoked activity. B: Cell
II-12A developed an increase in background activity and a decrease in evoked activity. The bar
from 0-1000 msec indicates the duration of the CS, and the second bar (present only during the
conditioning phase) indicates the duration of the US, which was 375 msec. Neuronal activity during
the US is not presented for cell II-IC.
regions (Diamond and Weinberger, 1984), recording sites located in VE were considered
as part of the A I I field. In this paper, we have taken into account the revision of the borders
of AII and consider the recording sites in that study to have been in the AII/VE region.
Considering that AII/VE is reciprocally connected with AI and the magnocellular M G N
(both of which were known to be plastic during learning), it was an appropriate site for
providing comparative data on plasticity in different auditory cortical fields. As with the
AI and M G N studies, we recorded the activity of single AII/VE neurons during the
acquisition of the pupillary dilation CR. Unlike AI and M G N , which are well studied, this
was the first account of physiological recordings in AII/VE in behaving animals.
As reported above, 63% of the neurons recorded in AI developed response plasticity
during learning. In contrast, a significantly greater percentage of cells recorded in AII/VE
(95%) developed learning-induced plasticity (Diamond and .Weinberger, 1984). The
changes were rapid in development, attaining statistical criterion in an average of 17.3
trials. Examples of peristimulus histograms illustrating plasticity of evoked activity are
presented in Fig. 20. Increases and decreases in evoked activity were equally likely (Fig.
21).
The reason for the differences between the incidence of plasticity in AII/VE and AI
cannot be determined at this time, but it may have resulted from the differential input of
the non-plastic lemniscal line to the respective fields. AI is densely innervated by the
thalamic lemniscal line (MGv), while AII receives no input from ventral M G N , and VE
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
31
200
150
-
i11
(.9
Z
it.)
Z
t/J
t.)
Og
,,i
O-
I
.---NCEASE o11
TJ | \
o---oDECREASE n=lO
/T"
J-~"~ T
T
I
6
I
8
I00
50
0
-50
-100
I
1
I
2
I
:5
SENSITIZATION
I
1
I
2
l
5
I
4
I
5
I
7
I
9
CONDITIONING
BLOCKS OF FIVE TRIALS
Fio. 21. Group learning curves of single neurons in AII/VE that developed significant changes in
evoked activity during conditioning. Each point is the mean percentage change in evoked activity
for blocks of five trials relative to the last five-trial block during the sensitization period. Vertical
bars denote +SE.
is only sparsely innervated by the ventral subdivision. Perhaps the greater dependence of
AII/VE on the diffuse pathway (MGm), which is highly plastic during learning (Section
5), enables these cells to be more sensitive to the acquired significance of acoustic stimuli.
6.3.2. Learning effects in different cortical laminae?
One additional finding of single unit activity recorded in AII/VE during learning regards
possible differences in the middle cortical lamina as compared to infra- and supra-granular
layers. That study revealed an extraordinary degree of physiological plasticity during
learning; only one o f 22 neurons recorded in the A I I / V E field was non-plastic. This cell
also was unique in three other physiological indices. Specifically, (1) its background activity
was significantly higher than that o f the rest of the sample (average of 26 sp/sec vs.
2.5 sp/sec), (2) it was the only cell to exhibit a prolonged excitatory response to the CS
(others responded more transiently), and (3) it had a short duration waveform (Fig. 22).*
In other studies of unanesthetized animals, the same distinction between cortical cells
that have a low background activity, phasic sensory responses and long duration
waveforms and those which have a high rate of background activity, sustained evoked
responses and short duration spikes is well documented (e.g., Abeles et al., 1975; De
Ribaupierre et al., 1972; Goldstein and Abeles 1975; Mountcastle et al., 1969; Simons,
1978). After Mountcastle et al. (1969) we refer to the former class as "regular spikes" and
the latter as "thin spikes". These authors have each postulated that thin spike neurons are
likely to be stellate cells while regular spike neurons are pyramidal cells. Recently, this
speculation was substantiated by McCormick et al. (1985) who were able to relate cellular
morphology to electrophysiology in neocortical cells. They demonstrated that thin spikes
are unique to aspiny or sparsely spiny GABAergic stellate neurons, while regular spikes
are recorded only from pyramidal cells.
* Although extracellular recordings of discharge activity cannot unequivocally discern whether the thin spike
was recorded from a thalamocortical fiber or a cortical cell, there is good reason to infer that it was somal in
origin. Others have discounted the possibility that thin spikes are generated by fibers primarily on the basis
of the duration of single unit isolation. According to Mountcastle et at., recordings of single fibers in white
matter yielded a very limited spatial extent of recording such that the action potential could be lost with the
slightest movement of the electrode. That we were able to isolate and maintain stable recordings of the thin spike
for the entire training session (approximately 2 hours) makes it unlikely that the waveform was generated by
a fiber.
32
N.M. WEINBERGERand D. M. DIAMOND
.a,
13
FIG. 22. Photographs of oscilloscope tracings of two types of extracellularly recorded action
potentials in auditory cortex of the cat. A "thin spike" waveform is illustrated at high resolution
in the upper left (A). A typical "regular spike" waveform, recorded during another session, is
illustrated at the same time base in the lower left. Calibration pulses in the lower left = 0.2 msec.
The right side (B) illustrates the background activity of these two neurons. The thin spike cell
(upper) discharged 25-30 spikes/sec, and the regular spike cell (lower), like most long duration
spikes, discharged less than 2 spike/sec in the absence of acoustic stimulation, (calibration
pulses = 0.5 sec in duration). Potentials were filtered at 0.4 kHz high pass and 10 kHz low pass.
In a u d i t o r y cortex, this distinction between two types of cortical cells was systematically
investigated by Abeles e t al. (1975). They reported that thin spikes are most likely to be
e n c o u n t e r e d in the middle cortical layers (III a n d IV), while regular spikes are recorded
t h r o u g h o u t the entire extent of cortex. The same l a m i n a r profile of the two cell classes was
f o u n d by M o u n t c a s t l e e t al. (1969) a n d Simons (1978) in studies o f single unit activity in
s o m a t o s e n s o r y cortex. C o n s i s t e n t with their observations is the well d o c u m e n t e d evidence
that m a j o r lemniscal thalamocortical projections terminate in the zone of high concent r a t i o n of stellate cells in layers III a n d IV. T a k e n together, these findings provide
suggestive evidence that the thin spike recorded in A I I / V E d u r i n g learning was (i) a stellate
cell located in layers II1 or IV; a n d (ii) driven directly by M G N n e u r o n s in the thalamic
c o m p o n e n t o f the leminiscal line (ventral M G N ) . *
A l t h o u g h speculation based on observations of a single n e u r o n is extremely tenuous,
long term recordings from thin spike n e u r o n s are so difficult that there is limited
o p p o r t u n i t y for o b t a i n i n g such data in behavioral studies.t Thus, the recording of thin
* The prolonged short latency evoked response is not typical of cellular activity in the thalamic lemniscal
adjunct (MGdc/MGvl) subdivisions. Their responses tend to be transient onset responses at very long latencies.
In contrast, cells in the thalamic lemniscal line (MGv) respond more similarly to the thin spike in the AII/VE.
Because All receives no input from MGv, the cell was likely to be in layer Ill or IV or VE, which is a component
of the lemniscal line (see Fig. 2).
t Thin spike units consistently yield a small signal to noise ratio and have a limited spatial extent over which
a single unit can be isolated. The difficulty of holding thin spike activity over long durations is also addressed
by Mountcastle et al. (1969) and Simons (1978).
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
33
spike activity during learning appears to have been a rare opportunity to record unit
activity from a cortical neuron being driven directly by the thalamus. That the evoked
activity of this cell was unchanged during learning suggests that the lack of plasticity in
the thalamic lemniscal line may be maintained in the discharge activity of cortical cells
directly receiving this input. A lack of callosal inputs to this class of neuron (CipoUini and
Peters, 1983) suggests that these cells are not only dominated by non-plastic inputs from
the thalamus, but they are also buffered from plasticity which is intrinsic to cortex.
The findings from the AII/VE study suggest that certain stellate cells in the middle layer
of auditory cortex retain the thalamic representation of sound at a purely "sensory" level.*
In contrast, neuronal processing intrinsic to cortex is highly sensitive to the psychological
parameters of acoustic stimulation.
6.4. ASSOCIATIVELY-INDUCEDPLASTICITYOF BACKGROUNDACTIVITY
In addition to changes in tone evoked responses, a second measure of discharge activity
that may be affected by learning is the "spontaneous" or ongoing background activity
occurring between training trials (background activity is quantified as the rate of discharge
activity during the 1.5 sec preceding the onset of each training trial). Notably, each of the
regions of the thalamocortical auditory system that develop plasticity of evoked activity
during learning also developed plasticity in background activity.~" Specifically, background
activity of neurons in the magnocellular MGN, and cortical fields AI and AII/VE changed
during the acquisition of the pupillary dilation CR. The changes in activity cannot be
attributed to non-associative arousal because conditioning effects are compared to the
preceding sensitization control period.
Although the significance of such changes is not known, it is worthwhile to provide some
details of changes in background activity, with restrained speculations regarding function.
One intriguing finding was that most of the cells (77%) recorded in AII/VE developed
decreases in background activity, and the changes occurred at about the same time as the
acquisition of behavioral conditioned responses. This result is noteworthy for the following
reasons. First, as discussed previously (Section 3.1), there is an overemphasis on the
analysis of circuits of motor structures producing what has been considered "the CR".
However, a change in cellular activity between trials is occurring in the absence of any
conditioned response. Hence, plasticity of background activity underscores the need to
view learning as a continuous process occurring at times other than during the presentation
of a stimulus or during a response.
Second, changes in the background activity of cortical neurons appear to occur only
during the initial acquisition phase of learning (e.g. Diamond and Weinberger, 1984;
Disterhoft and Olds, 1972; Disterhoft and Stuart, 1976; Dumenko and Sachenko, 1980;
O'Brien et al., 1973; Weinberger et al., 1984c). In contrast, studies of auditory cortical
activity recorded during the elaboration of a specific somatic conditioned response (Kraus
and Disterhoft, 1982) and during the performance of overlearned responses (Beaton and
Miller, 1975; Benson and Heinz, 1978; Benson et al., 1981; Goldstein et al., 1982) report
that background activity is non-plastic. This indicates that the rapidly acquired conditioned responses involve changes in both background and evoked activity of cells in the
auditory thalamus (MGm) and cortex (AI, AII, VE). Following this initial association
between the CS and US, background activity appears to remain constant, as additional
changes in evoked activity emerge. The later developing plasticity of evoked activity may
relate specifically to somatic conditioned responses that are specific to the US (Section 3).
* Hyvarinenet al. (1980) reported similar results in a study of the effectsof attention on cellular activityin
somatosensorycortex. These authors reported that cellular activityin the middle layer was non-plastic, while
activity in the upper and lower layers was sensitiveto the significanceof cutaneous stimuli.
t Evoked activity was computed as the differencebetween background discharges and discharges during
acoustic stimulation.Hence,plasticityof evokedactivity(discussedpreviously),developedindependentlyof the
changes in backgroundactivity.
J.PN 2 9 / 1 ~ "
34
N.M. WEINBERGERand D. M. D1AMOND
6.5. A NOTE ON AUDITORY CORTICAL PLASTICITY AND BEHAVIORAL RESPONSES
The findings for pupillary behavior and cellular discharges in both the thalamus and
auditory cortex indicate rapid changes during conditioning. Is there a causal link between
the neuronal plasticity and the pupillary conditioned response? This appears to be
extremely unlikely. Although their rates of change are within the same range, a
within-subjects analysis reveals a low, non-significant intercorrelation (e.g. Oleson et al.,
1975; Ryugo and Weinberger, 1978; Weinberger et al., 1984c; Diamond and Weinberger,
1984; see also Birt and Olds, 1981; and Gabriel et al., 1976). The absence of such findings
in the auditory system is not due to limitations of recording techniques or data analysis,
because we have obtained high intercorrelations for nuclei that are closely related to
efferent control of the pupil (Ashe et al., 1978a; see also Ashe et al., 1978b; and Ashe and
Cooper, 1978). Rather, it appears that physiological plasticity in the auditory system
during learning is more closely related to learning about the significance of acoustic stimuli
than it is to response circuitry.
6.6. SPECIFICITY OF LEARNING-INDUCED CHANGES IN EVOKED ACTIVITY
6.6.1. B a c k g r o u n d
Although it is well established that physiological plasticity in auditory cortex is
associative in nature, there has been disagreement regarding interpretation of the learning
effects. One possibility is that learning merely induces a change in the general excitability
of auditory cortical neurons. According to this view, the plasticity is not a reflection of
changed processing of information about the conditioned stimulus, per se. On the other
hand, the cortical plasticity could be highly specific to the conditioned stimulus. For
example, learning-induced changes in evoked activity could reflect a specific "returning"
of neurons to the conditioned stimulus. This type of change would entail the systematic
development of a narrow band enhancement in sensitivity to the physical characteristics
of an important sound.
This issue of specificity was addressed by Hall and Mark (1967) and Kitzes et al. (1978).
Animals were conditioned to either a tone or light CS, paired with a US. The explicit CS
and US were considered to be the only stimuli which provided information to the subjects.
"Neutral" probe stimuli (tones) were also presented at a constant rate throughout training.
Both studies reported that auditory cortical responses to the probe tones presented during
a trial (i.e. immediately following CS onset) were significantly different from responses to
these same tones presented between trials. Because these authors assumed that the probe
tones had no significance whatsover, they interpreted the change to the probes as indicating
a general change in cortical excitability following CS onset. They concluded that
learning-induced plasticity in auditory cortex does not reflect a specific change in the
processing of the conditioned stimulus.
There are two reasons for considering this conclusion unsupported. First, learning effects
were compared with a control phase that had isolated tones, without unpaired reinforcement, rather than a sensitization control phase. As the effects might have been nonassociative, these findings do not demonstrate associatively-induced state effects on
auditory responses.
Second, there was no independent verification that the probe tones were indeed, devoid
of significance. On the contrary, the probe tones presented during trials probably did
provide salient information. On every training trial, the onset of the CS and US were
time-locked to the onset of probe tones. Therefore, the actual conditioned stimulus may
have been a compound stimulus consisting of the CS and a constant number of probe tones
which provided accurate information concerning the timing of US presentation. Such
compound CS and similar temporal conditioning effects are well documented (Pavlov,
1927). In support of this interpretation, Oleson et al. (1975), employing a similar paradigm,
reported that subjects oriented to probe stimuli only when they occurred following CS
PHYSIOLOGICALPLASTICITYIN AUDITORYCORTEX
35
onset. Given these considerations, the studies discussed above leave the issue of general
state effects versus processing specificity unresolved.
6.6.2. Learning-induced changes in frequency receptive fields
In order to resolve the processing specificity issue, we recorded the activity of single
neurons in All and VE during a modified classical conditioning procedure (Diamond and
Weinberger, 1986). In addition to recording evoked activity to the CS during training
trials, we also determined the frequency receptive field (FRF) of each neuron before and
after the acquisition of a behavioral conditioned response. The F R F provided an index
of the sensitivity of AII/VE neurons to a range of different frequencies, only one of which
became significant to the animal during learning.
The crucial advantage of the F R F determination was that the plasticity which developed
during training would be revealed in terms of the frequency specificity of the changes. For
example, if learning-induced discharge plasticity merely reflects a general change in
excitability, then cells should exhibit either an increase or a decrease in their evoked
response across frequencies, without regard to the particular frequency of the CS. On the
other hand, if learning induces a specific change in cortical signal processing, then changes
in evoked activity should be specific to the frequency of the CS.
Upon isolation of discharges from a single neuron, an F R F was obtained by presenting
a sequence of isointensity tones (range across sessions: 20-30 ascending frequencies,
0.1-24.0 kHz, 300 msec duration, 1500 msec inter-tone interval, repeated 10-15 times,
30-80 dB) under computer control via a calibrated delivery system. The CS was a tone
identical in all parameters (e.g. frequency, intensity and duration) to one of the stimuli used
to obtain the FRF. In order to control for non-associative effects, FRFs were determined
immediately before and after sensitization (CS/US unpaired, 20 trials), and then after
conditioning (CS/US paired, US presented 700-2000 msec after CS offset, 20--45 trials) and
extinction (CS alone, 20--40 trials). Stimulus density was maintained constant throughout
the training session at an average of 1 stimulus per 20 sec.
In each of 20 training sessions, the activity of a single neuron was recorded throughout
F R F determinations, sensitization, conditioning, and in some cases, extinction or retention. As with the initial study of AII single unit activity, 95% of the cells rapidly developed
discharge plasticity during training. Most importantly, the FRFs of 80% of the neurons
were changed following conditioning.
To quantify the degree of CS specificity of the changes in FRFs, we calculated a
specificity ratio using two frequency range measures: the range of frequencies above and
below the CS frequency to which the cell developed discharge plasticity, divided by the
total range of frequencies which affected the activity of the cell. Cells with a specificity ratio
of <0.5 were classified as frequency specific. Seventy five percent of the plastic cells met
this criterion.
An example of a cell exhibiting a non-specific associative F R F change is presented in
Fig. 23. The post-conditioning F R F indicates an enhancement of inhibition to most
frequencies. Examples of specific changes in FRFs are presented in Figs 24 and 25. The
FRFs in Fig. 24 illustrate a highly specific increase in evoked activity that developed only
to the frequency of the CS (18 kHz). The conditioning effect was then abolished following
extinction. This reversal occurred for all cells tested with extinction training. Data from
a broadly tuned neuron that developed a specific decrease in evoked activity are presented
in Fig. 25. For this training session, the CS was a triad (10, 11, 12kHz). Following
sensitization, there was an increased response to numerous frequencies (midddle panel).
Despite this increase in evoked activity with sensitization, a highly specific decrease in
evoked response to the CS triad developed after conditioning (lower panel).
The data illustrate the finding that most of the cells recorded in AII/VE during learning
develop highly specific changes in cortical signal processing. In addition, the conditioning
effects were reversed following extinction.
36
N . M . WEINBERGER and D. M. DIAMOND
it
PRE-SENS
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FIG. 23. Frequency receptive fields (FRFs) of a cell that developed a frequency non-specific decrease
in evoked activity with conditioning. The enhancement o f the decrease in evoked response to the
CS (18 kHz) also occurred to almost all other frequencies as well. In all F R F analyses, the rate
of evoked activity is subtracted from background activity. This difference score provides for
quantification of the stimulus evoked inhibition of activity in this figure.
To determine the average range of frequency plasticity, post-conditioning data were
normalized as a positive percent change from the pre-sensitization FRF, and expressed as
the distance, in kHz, from the CS. This analysis revealed that, on the average, the greatest
change in evoked activity for frequency specific neurons was at the CS frequency (71%),
while the change in response to all other frequencies was less than 25% of control values
(Fig. 26). This finding demonstrates that the population of AII/VE neurons developed
significant changes in evoked activity during learning that were highly specific to the CS
frequency.
This normalization analysis was also applied to the post-extinction FRFs. Following
extinction, the enhancement of evoked activity with conditioning was no longer present
6050-
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FXG. 24. FRFs for a frequency specific neuron located in All. Prior to training, it was excited
slightly at frequencies above 8 kHz (pre-cond). Immediately after acquisition of the pupillary
dilation conditioned response to a CS of 18 kHz, an excitatory response was increased significantly
only at the CS frequency (post-cond). Following behavioral extinction, the increased response at
the CS was abolished (post-ext).
37
PHYSIOLOGICAL PLASTICITY IN AUDITORYCORTEX
PRE-SENSITIZATION
A
ILl
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POST-CONDITIONING
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FIG. 25. FRF plasticity of a broadly tuned All neuron that developed frequency specific plasticity
following conditioning. The FRFs of different phases are presented on separate graphs, and the
evoked activity differences from background are shaded solid. In the post-sensitization FRF, the
cell exhibited a general increase in excitability to numerous frequencies in the tone sequence. In
the post-conditioning FRF, there was a highly specific decrease in evoked activity that occurred
only to the three frequency triad (10, 11, 12 kHz) that served as the CS.
(Fig. 27, top). There are two possible explanations for this reversal effect: (a) it is
attributable to experimental extinction itself; (b) the conditioning effects might be
transient, and would have dissipated even in the absence of extinction. A critical test of
the "transiency" hypothesis was performed by obtaining "post-retention" FRFs for some
90 --1
ao-1
70
1
FREQ SPECIFIC
(n=,,12)
FREQ NON-SPECIFIC
(n=,,5)
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50
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o
DISTANCE
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~
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FIG. 26. Normalized group data for cells classified as CS frequency specific and frequency
non-specific in their FRF plasticity. Percent change (associative effect) is given as a percent of
distance (kHz) from the CS frequency. The frequency non-specific cells exhibited increased evoked
activity across a broad range of frequencies, with no selective accentuation at the CS (0 kHz). In
contrast, the frequency specific cells exhibited consistent changes in activity only to the CS
frequency.
38
N.M. WEINBERGERand D. M. DIAMOND
9 0 -]
70
60
50
4O
z
~
POST-COND
(n--7)
I
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POST-EXTINCTION
(n=7)
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FIG. 27. Top: Normalized group data for cells which developed frequency-specificplasticity due
to conditioning, and were further studied following extinction. The specificchange at the CS with
conditioning was no longer present following extinction training. Bottom: Normalized group data
for cells in which a post-retention FRF was obtained. This illustrates that the CS specificchanges
in evoked activity due to conditioning did not dissipate spontaneously.
cells after an interval of silence equal to the maximum period of time for extinction training
(20min). The post-retention F R F summary (Fig. 27, bottom) indicates that frequency
specific plasticity was still present; hence, the reversal effect is attributable to extinction,
p e r se.
The retention test also revealed that learning-induced plasticity persisted for at least
20 min after conditioning was concluded. That the changes outlasted the period of training
suggests that these cells are components of short term memory circuitry. Because the
plasticity was reversed by extinction, the duration of the memory effect is likely to be a
function of the reliability of the CS as a signal for reinforcement.
These findings indicate that learning-induced plasticity of cellular responses to a sound
reflects specific changes in cortical information processing of that sound. Thus, auditory
cortical neurons may function as "adaptive filters" which develop a narrow band change
as stimulus meaning or signal value changes during the acquisition of information.
7. Implications of Learning-Induced Plasticity in Auditory Cortex
7.1. INTRODUCTION
In the foregoing, we have reviewed our research on learning and physiological plasticity
in the auditory system. Although this field is at a relatively early stage of inquiry, it is
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
39
possible to discern some implications of the findings for operation of the neocortex and
adaptive functions of the organism. We will take these up in turn.
7.2. IMPLICATIONS OF PHYSIOLOGICAL PLASTICITY FOR CONCEPTIONS OF SENSORY CORTICAL
FUNCTION
The findings of physiological plasticity, from our laboratory and others, should help to
bring about a revision of traditional views of sensory cortical function. An early distinction
between functional characteristics of sensory and associational cortices was made by
William James (1890), in his analysis of human neurological disorders following brain
damage. The prevailing view at that time was that sensory cortical processing is limited
solely to stimulus detection (sensation), while cognitive processes such as perception,
memory and the capacity to associate meaningful stimuli were assigned to "associational"
regions of the neocortex. This distinction was apparently well accepted when Bishop (1958,
1959) provided comparative anatomical data that were interpreted as supportive of the
classical view. Based on thalamocortical axon diameters and termination zones, this author
viewed primary sensory cortical areas as phylogenetically recent additions to sensory
systems. The primary fields were believed to function in the fine discrimination of sensory
qualities in higher animals. The output of the sensory cortical areas was believed to extend
to phylogenetically older associational cortices, which were thought to integrate sensory
information and perform perceptual functions.
In the last quarter century, numerous workers have questioned the validity of the
traditional view. Diamond and Chow (1962) reviewed neocortical ablation studies in
trained animals and concluded that the detection of stimuli, per se, was largely unaffected
by extensive removal of sensory cortical areas. The deficits that did occur were better
explained by impairment of the ability to learn about complex relations between stimuli.
This interpretation has been supported by the findings of later ablation experiments (for
reviews, see Elliott and Trahiotis, 1972; Neff et al., 1975; Ravizza and Belmore, 1978).
There is an increasing effort to abandon the traditional viewpoint. For example,
following a comprehensive review of physiological and ablation studies of the neocortex,
Masterton and Berkeley (1974) concluded that the concept of "sensory", "motor" and
"associational" cortex has lost most of its original usefulness. They expressed the hope that
"these outmoded terms will not be taken seriously by those outside the field, nor,
especially, by new generations of students" (p. 295). Merzenich and Kaas 0980) and I.
Diamond (1979) proposed similar revisionist views of the utility of the
sensory/motor/association cortex distinction. In addition, Diamond (1979) raised a novel
point regarding the sensory/motor distinction. He pointed out that cells in layer V
throughout the neocortex have direct access to motor effector areas. For example, cells
in auditory cortex project to the basal ganglia (Reale and Imig, 1983), deep layers of the
superior colliculus (Fries, 1984; Kawamura and Konno, 1979) and also pontine motor
nuclei (Andersen et al., 1980; Brodal, 1972; Kawamura and Chiba, 1979). Therefore,
Diamond suggested that layer V throughout the neocortex may be considered as the
"motor" cortex. His analysis illustrates the current state of dissatisfaction with the
standard theory of functional cortical organization.
Initial criticisms of the traditional distinction were based primarily on increased
knowledge of thalamocortical connectivity and the lack of impairment of purely sensory
functions following ablation of sensory cortex. The inadequacy of the traditional view has
been further demonstrated by more recent neurophysiological documentation of plasticity
in sensory cortex during learning. Although the learning data have come mainly from
studies of the auditory cortex, there is also abundent evidence that such plasticity develops
in visual and somatosensory neocortex. Therefore, auditory cortex is not a special case;
rather, theories of function of sensory neocortex in general require revision.*
* Associative effects of learning also develop in the olfactory bulb (Freeman and Schneider, 1982). Therefore,
the need to understand sensory processing from the standpoint of learning appears to include the olfactory system
as well.
40
N.M. WEINBERGERand D. M. DIAMOND
The findings of learning-induced specific changes in frequency tuning of single auditory
cortical neurons, (Section 6.6.2) are particularly difficult to reconcile with views that
sensory neocortex functions merely as a sensory detector, independent of the salience of
stimuli. The plasticity of frequency tuning suggests that auditory cortical cells function as
adaptive filters, the output of which is selectively modified during learning. This is directly
at variance with the classical distinction between the functioning of sensory and association
cortex. New theories of cortical function should not maintain that sensory and association
cortex differ qualitatively in their capacity to participate in learning and perception, but
should seek other grounds.
The dynamic character of auditory, and other sensory, cortex is emphasized by their
development of physiological plasticity during learning. These findings are consonent with
evidence of dynamic sensory cortical operation obtained in very different circumstances.
For example, plasticity of cutaneous receptive fields is evident in somatosensory cortex
following removal of a peripheral source of input (Merzenich et al., 1984; Wall et al., 1986).
Additionally, adult rats placed in "enriched environments" develop structural plasticity in
visual cortex (Rosenzweig et al., 1972; M. Diamond et al., 1985). The latter effects appear
to be a result of increased visual learning, per se (Chang and Greenough, 1982; Vrensen
and Cardozo, 1981).
Despite the extensive and well-established evidence that sensory cortex is highly
dynamic, its function is still generally viewed as static, unaffected by learning. For example,
according to Fuster (1984),
"".. •the participation and purview of primary sensoryareas in memoryis quite differentfrom those
of parasensory or associative areas, such as the inferotemporal area. Indeed, there is reason to
believe that after certain critical events in early ontogeny, primary areas are relativelyset in their
organization. Their cell assemblies are organizedaccording to preprogrammedpatterns of internal
and external connectivity,and, as a result, their analytical function is stably determined.It appears
that the participation of primary areas in the formation of memory is largelydependent on, if not
limited to, their role as the sensory analyzers of what is to have access to memory." (p. 280).
Perhaps this ought not to be surprising, because inadequate scientific conceptions seem
to be discarded, not in the face of contravening evidence, but only when a better theory
is elucidated (Kuhn, 1962). The development of physiological plasticity in sensory cortex
during learning provides additional data directly incompatible with the established view.
However, no contemporary theory of cortical function has yet replaced the traditional
view.
7.3. ADAPTIVE FUNCTIONS
7.3.1. Introduction
Whatever the ultimate development of new theories of neocortex, there are sufficient
data to consider the adaptive functions of learning-induced cortical plasticity. Three major
types of adaptive functions at the level of the organism are usually recognized: (1) stimulus
analysis, (2) response or motor-related functions, and (3) cognitive functions. We will
consider each in turn.
7.3.2. Stimulus analysis
By "stimulus analysis", we refer to processes by which the nervous system accurately
responds exclusively to the physical parameters of stimuli. Although neurons in auditory
cortex can accurately respond to these parameters, their discharges also are affected by
learning, at least in the domain of frequency. Thus, information about both the physical
characteristics and the significance of sound may be reflected in their output. Therefore,
auditory cortex does not function as a pure sensory analyzer.
The distinction between pure sensory analysis and stimulus significance means that
physiological plasticity induced during learning is not involved in analysis of the purely
physical characteristics of sound. This also implies that the subcortical lemniscal auditory
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
41
system, unaffected by learning, is concerned with stimulus analysis, alone. According to
this view, the ventral medial geniculate nucleus is the highest level of the acoustic analysis
system.
7.3.3. Response functions
Birt and Olds (1981) have argued that learning-induced changes in the auditory system
are not directly linked to motor responses, as in a reflex arc. Rather, they hold that this
plasticity is involved in some early stages of information processing in which a particular
acoustic conditioned stimulus will be linked to a particular conditioned response. Although
their argument was based upon physiological plasticity in the region of the magnocellular
M G N , rather than auditory cortex, their argument is relevant also for cortical plasticity.
A very direct role in motor responses can be eliminated because Birt and Olds found
no close relationship between plasticity and conditioned movement in their subjects (rats).
Gabriel et al. (1976) also found a poor relationship between physiological plasticity in the
magnocellular M G N and avoidance responding, in the rabbit. Likewise, we previously
reported a low intra-subject correlation between physiological plasticity in the auditory
system (both the magnocellular M G N and the auditory cortex) and conditioned pupillary
dilation (Section 6.5).
The hypothesis of Birt and Olds that auditory system plasticity represents an early link
of the conditioned stimulus to the conditioned response is unlikely to be correct, as it is
based on a false assumption. The crux of their argument relies on the assumption that
conditioning consists of the acquisition of a single, specific conditioned response. Auditory
system plasticity is alleged to be linked to processes that will culminate in the performance
of this single response. However, several conditioned responses develop during conditioning. Furthermore, the initial learning, indexed by these CRs, seems to be a stimulusstimulus rather than a stimulus-response association (Section 3.2). Once again, the fact
that specific behavioral responses often develop during learning does not mean that
learning is simply the development of specific behavioral responses.*
7.3.4. Cognitive functions
In this section, we suggest how physiological plasticity that is expressed in sensory cortex
during learning may be involved in certain cognitive functions. Specifically, we consider
perceptual functions and selective attention. Although stimulus and response processes are
more familiar, cognitive processes can also be specified objectively and operationally (e.g.
Neisser, 1976), and they are essential to adaptive behavior. An understanding of cortical
function at the level of single neurons should provide a basis for understanding its
functions as accomplished by the organized neuronal ensembles, circuits, and networks
that surely underlie integrated adaptive functions of the entire organism.
7.3.4.1. Perception
Perception is not in one-to-one correspondence with the pattern of stimulation on
receptor epithelia. Rather, it is a conjoint function of the physical and the psychological
parameters of stimuli. The latter include the significance, meaning, and associative links
of environmental events, acquired by experience (Epstein, 1967; Gregory, 1974). The role
of neocortical plasticity in perception is suggested from the fact that the responses of
sensory cortical neurons are affected by both types of stimulus parameters.
* Although plasticity in the auditory thalamus and cortex is clearly not involved in a direct sensory-motor
circuit, there are connectionsfrom the magnocellularMGN and auditory cortex to motor structures such as the
caudate nucleus(LeDouxet al., 1985; Reale and Imig, 1983). However,these connectionsmay be more involved
with sensory gating and mechanisms of attention, rather than the generation of motor patterns, per se. (see
Lidsky, et al., 1985, for discussion of extra-motor functions of the basal ganglia.)
42
N.M. WEINBERGERand D. M. DIAMOND
Learning effects in cortex could subserve perception by providing a basis for stimulus
equivalence.* This refers to the fact that organisms regard the same stimulus emanating
from the same "object" on different occasions as indeed the "same", despite the fact that
the stimuli must be physically different from one time to the next. In the case of the
auditory system, the inevitable sources of stimulus variation at the tympanic membrane
include changes in distance and position between the sound source and the listener,
changes in the position of the head and pinna (external ear) of the listener, and alterations
in sound production at the source. Additionally, there may be stimuli from other sources,
including those with common frequency spectra which could partially "mask" the sound
in question. At the very least, these influences would result in variation in the intensity
of a given sound. In other words, in the natural environment, the "same" stimulus is
almost never exactly the "same", as transduced at the cochlea.
Learning-induced physiological plasticity in auditory cortex could provide a mechanism
for stimulus equivalence for important sounds. Learning alters the frequency receptive field
with respect to the conditioned stimulus (Fig. 25). Therefore, the "same" sound, i.e. an
acoustic stimulus having a particular frequency spectrum, which varies randomly in
intensity from one occasion to the next, will engage cells to a greater degree than otherwise,
The specificity of plasticity would insure that unimportant stimuli would not receive the
same preferential treatment.t
This type of mechanism would not compromise the ability of the auditory system to
discriminate slight changes in stimulus parameters, should the need for attention to the
exact physical characteristics arise, because the subcortical lemniscal system remains
sensitive to such fine detail. Cortical plasticity appears to provide a parallel type of
processing in which features of stimuli are abstracted, and fine details can be ignored unless
of importance. The neurophysiological data upon which this hypothesis is based, as
reviewed above, provide independent support for Whitfield's (1979) conclusion that
sensory neocortex abstracts objects and concepts from primary sensory data.
7.3.4.2. Selective attention
Selective attention refers to the fact that the totality of receptor epithelia of an organism
receive continual bombardment; yet, only a fraction of the transduced stimuli actually
enter into moderate or long term storage, or guide behavior. A major issue in attention
and brain theory is how the processing capacity of the brain is allocated to various stimuli
(Kahneman, 1973; Eysenck, 1982). Learning-induced physiological plasticity may play a
role in such a process.
Learning effectively "recruits" neurons to acoustic conditioned stimuli. This functional
recruitment is evident in the specific effects on frequency receptive fields (Fig. 25). Thus,
when learning causes more neurons to be "allocated" to the processing of important
stimuli, this may signify a literal allocation of processing resources (i.e. neurons) to those
stimuli. The amount of selective attention for a stimulus may then be related to the number
of neurons which are processing that stimulus. One of the effects of learning at the auditory
cortex may then be to provide the basis for the allocation of neurons to the processing
of stimuli which, because of their acquired significance, demand more attention. Thus,
stimuli-to-be attended will find either more cortical neurons responsive or more responsive
cortical neurons.
* Stimulus equivalence depends on "object constancy". Object constancy refers to the fact that organisms
regard their environment as consisting of some set of stable objects which may move or produce different stimuli
(e.g. sounds) at various times, rather than as unique and individual objects whenever they change position or
produce new stimuli. Object constancy is a fundamental abstraction about the nature of the environment and
is so basic to adaptation that it is often assumed to be "built in" at the time of birth. However, object constancy
clearly depends upon experiential factors. Such learning is most clearly seen in developing organisms, such as
young children, and its stages have been well documented (Piaget, 1952).
t Of course, slight variations in stimulus parameters can be discriminated, if they are within the limits of acuity
and if they are important. Nonetheless, they are generally ignored at the gain of dealing with the environment
as reasonably stable.
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
43
8. Conclusions
We conclude by (a) presenting a brief resume of our findings, (b) considering the
relationships among four key topics in neurobiology, and (c) suggesting research avenues
that could yield a more coherent understanding of physiological plasticity, cortical
function, learning and sensory information processing.
8.1.
SUMMARY OF FINDINGS
We view learning fundamentally as the acquisition of information and memory as the
storage of information. Learning and memory can be inferred from overt behavior, but
such effector action is a product of learning rather than the learning itself. Analysis of the
rates at which various effector actions change systematically during associative learning
reveals a bi-modal distribution. Rapidly-appearing behavioral conditioned responses (e.g.
pupillary dilation) develop in all conditioning situations, regardless of the unconditioned
stimulus employed. More slowly-appearing effector actions are specific to the unconditioned stimulus. For example, a puff of air to the eye will lead to an eye blink conditioned
response and shock to a limb will lead to a flexion conditioned response, but not vice-versa.
We interpret these findings to indicate that classical conditioning involves two stages.
During the first stage, animals learn that a neutral stimulus predicts or signals a
biologically significant stimulus; during the second stage, animals learn to perform a
behavioral response that is specific to the unconditioned stimulus. These stages may be
characterized, respectively, as stimulus-stimulus (S-S) learning and stimulus-response
(S-R) learning. We suspect that S-S learning is necessary for later S-R learning, but this
is currently an open question.
Nervous system tissue is specialized, not only for the reception, conduction, and
transmission of information, but also for expressing systematic change in reactivity under
certain circumstances. This physiological plasticity has been studied primarily during
development, recovery of function or readjustment following injury and during learning.
Learning is more or less a continual process seen both on a long time scale, throughout
the lifespan, and on a short time scale, i.e. moment-by-moment acquisition of information.
Physiological plasticity is expressed in auditory cortex during learning. Specifically, the
responses of cortical neurons to acoustic stimuli change when the importance of the
eliciting sound changes. This response plasticity develops rapidly during both nonassociative and associative learning.
In non-associative learning, typified by habituation, an acoustic stimulus is merely
presented repeatedly and the subject learns that it has no particular significance or value
as a signal. Behaviorally, habituation is evident as a systematic decrement in a response
to the repeated sound; in our studies, this behavior is pupillary dilation.
In associative learning, exemplified by classical conditioning, a sound always precedes
a biologically significant stimulus (e.g. food, shock) and the most rapid learning is that
the auditory stimulus signals forthcoming reward or punishment. At the behavioral level,
this is seen as a systematic increase in pupillary dilation to the sound. In both habituation
and classical conditioning, cortical plasticity is specific to the acoustic stimulus; it does not
reflect a general change in excitability of the auditory system.
Associative plasticity in auditory cortex develops in both the primary (AI) and the
secondary/ventral ectosylvian (AII/VE) fields. Within AI, differential plasticity to two
sounds that have different meaning is still present after a one week period, and could then
be reversed when stimulus significance was reversed. In recordings obtained from one cell
throughout a training session, discharge plasticity developed for approximately 60% of
neurons in the primary field and virtually all cells recorded in AII/VE.
In an initial attempt to understand how physiological plasticity during learning is related
to information processing in the auditory cortex, we combined techniques from learning
and auditory physiology to study frequency receptive fields of single neurons in cortical
areas AII/VE. Frequency receptive fields were altered specifically with respect to the tonal
frequency of the conditioned acoustic signal; that is, associative learning can "retune"
44
N.M. WEINBERGERand D. M. DIAMOND
neurons and the maximum change is at the frequency of the conditioned stimulus. This
demonstrates that the informational content of sound is subject to the effects of learning
at the cortical level. Moreover, the change in receptive field did not dissipate spontaneously, but could be reversed quickly by extinction training, in which the acoustic stimulus
no longer signals reward or punishment.
Thus, the responses of auditory cortex are affected by the psychological parameters of
sound (e.g. stimulus significance) as well as by its physical characteristics (e.g. frequency).
At the level of the auditory thalamus, sensitivity to these two types of parameters are
compartmentalized within two distinct parallel auditory pathways. Non-plastic neurons,
which are sensitive to the physical aspects of sound, are in the specific, lemniscal line
pathway, e.g. ventral medial geniculate nucleus. In contrast, cells which rapidly develop
discharge plasticity, but are insensitive to the details of acoustic parameters, are located
in the diffuse auditory pathway, e.g. magnocellular medial geniculate nucleus. Enduring
synaptic facilitation can be induced rapidly in this nucleus, as evidenced by long term
potentiation. Therefore, the magnocellular MGN may contribute to cortical plasticity
during learning. Its diffuse projections to all fields of auditory cortex are consistent with
this possibility.
These findings underscore the dynamic aspects of sensory cortical function (see also
Edelman and Finkel, 1984). They are incompatible with the belief that the auditory cortex
is concerned only with analysis of the physical characteristics of sound. Therefore, the
traditional distinction between sensory cortex and association cortex appears to be
untenable. The adaptive functions of rapid learning-induced physiological plasticity in
auditory cortex are not yet known. However, they appear to be neither pure sensory nor
motor, but rather higher functions concerned with perception and selective attention.
8.2. RELATIONSHIPSAMONG PHYSIOLOGICALPLASTICITY,NEOCORTICALFUNCTION,
LEARNING, AND SENSORY INFORMATIONPROCESSING
The rapid expression of physiological plasticity in the auditory cortex during learning
links all four areas of inquiry. Here, we discuss some of their relationships.
8.2.1. Physiological plasticity and learning
The link between physiological plasticity and learning is secure, both on logical and
empirical grounds. The acquisition of information must have a physiological basis for
change. Thus, physiological plasticity must underly all learning. Thousands of neurophysiological studies have reported the development of physiological plasticity during
learning. So the issue is not "if" there is involvement, but rather the characteristics of the
plasticity which underlies learning. In the present chapter, we have pointed out that one
of these characteristics is stimulus-specific plasticity in the sensory neocortex of the
stimulus whose significance is altered by learning.
The neurobiology of learning necessarily entails physiological plasticity. Is the reverse
true; that is, does all physiological plasticity involve learning? That is currently unknown.
Plasticity will continue to be studied outside of an explicit learning framework, as in
development and recovery of function. Both of these processes do take place within
organisms as they interact with their environments. Therefore, it is possible that the
acquisition of information, i.e. the storage of the effects of stimulation directly from the
environment and also that which results from an organism's behavior itself, interacts with
processes of development and recovery of function. For example, associative learning is
reported to bias the responses of neurons in visual and somatosensory cortices during
development (Spinelli and Jensen, 1979). The need for more data is evident.
8.2.2. Auditory cortex, plasticity and learning
The idea that cerebral cortex is involved in plasticity and learning is not novel. For
example, the traditional view of cortical organization is that association cortex subserves
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
45
learning. But, the development of plasticity in auditory cortex during learning is not part
of the standard view of brain function. Traditionally, sensory cortex has been viewed as
the highest level of sensory analysis. So entrenched is this view that learning induced
physiological plasticity has often been denied (e.g. Miller et al., 1982)* or ignored (e.g.
Fuster, 1984).
Sensory neurobiology has focused on the fundamental relationships between the
physical parameters of stimuli and the responses of neurons within the relevant sensory
system. Of course, the resultant data are absolutely essential to an understanding of the
functioning of sensory systems. These foundational data are in no sense compromised by
the fact that stimulus meaning is also a major factor in the responses of auditory cortical
neurons to sound. Learning-induced plasticity must develop within the basic anatomical
and physiological framework present within an organism.
Physiological plasticity in the auditory cortex reveals dynamic aspects of auditory
function specifically, and sensory cortical function in general. Such dynamic characteristics
of brain physiology need to be incorporated within a broader, more modern schema than
that provided by conceptions limited to rigid stimulus-response formulations.
The anatomical roots of auditory plasticity run at least as deep as the magnocellular
medial geniculate nucleus. There appears to be something rather basic about the dual
functional organization of the auditory thalamus (lemniscal, non-plastic and nonlemniscal, plastic) and its differential projections to the auditory cortex (tonotopic, middle
layers and diffuse, upper layers). The duality of information processing in the auditory
cortex during learning also raises the question of how the visual and somatosensory
systems operate at their cortical levels. In short, sensory neurobiology needs to provide
an adequate account of (a) all of the variables that affect information processing in sensory
systems and (b) how brains construct or reconstruct an accurate representation of the
environment.
8.3. FUTURE DIRECTIONS
8.3.1. Introduction
Investigation of cortical neuroplasticity is still in its early stages. Even so, we believe that
there is reason to be optimistic about future progress. In particular, we advocate
combining two major approaches to information processing in the nervous system, i.e.
learning and sensory physiology. Learning can be used to rapidly induce and control
physiological plasticity. Sensory physiology can provide a foundation for understanding
the functional role of plasticity. Here, we suggest some avenues for future research,
beginning with the analysis of cellular mechanisms.
8.3.2. Future Cellular Studies of Physiological Plasticity
Our findings offer no direct insights into the cellular bases of physiological plasticity,
as they have been limited to determination of the distribution and characteristics of
plasticity in the upper auditory system. However, they have provided sufficient information
to help guide future experiments at a more reductionistic level. For example, more detailed
analysis of physiological plasticity would be facilitated by (a) the ability to control its
occurrence, (b) knowledge of its time course, and (c) information on its locus of origin.
At this stage, we can provide data relevant to each of this points.
Regarding control, plasticity is easily induced by both non-associative (habituation) and
associative (conditioning) learning. The use of associative learning during conditioning is
probably more desirable than the use of habituation because it is possible to compare
physiological processes involved in processing the same acoustic stimulus when that
* Miller et al. (1982) attribute changes in evoked activity to the influenceof arousal or attention, rather than
learning. For a detailed critique of their proposal, see Diamond and Weinberger (1984) and Weinberger and
Diamond, in press.
46
N.M. WEINBERGERand D. M. DIAMOND
stimulus is not involved in plasticity, i.e. during the sensitization control period, and when
it is so involved, i.e. during CS-US pairing. Additionally, plasticity can be reversed easily
by extinction training. Thus, classical conditioning provides a ready means for establishing
and abolishing physiological plasticity in auditory cortex.
With reference to time course, plasticity is expressed very quickly during CS-US pairing.
It does not dissipate spontaneously, but appears to remain until reversed by extinction.
The rapid development of plasticity renders it amenable to intracellular investigations.
A major question is whether cortical physiological plasticity is local or reflects
subcortical plasticity which is projected to the cortex. This traditionial dichotomy does not
quite fit into the learning data, because there is evidence that both subcortical and cortical
mechanisms are involved. Furthermore, the subcortical effects do not fully account for the
characteristics of cortical plasticity; rather, the latter takes on a new form within the cortex.
Let us consider each of these points.
The thalamic component of the temniscal line (ventral MGN) does not develop
physiological plasticity during conditioning (Section 5.1.1 .). This implies that information
about the specific physical parameters of sound reaches auditory cortex unaltered by
learning. Therefore, learning induced physiological plasticity in auditory cortex cannot be
attributed to the subcortical lemniscal line. In contrast, the thalamic component of the
diffuse auditory pathway (magnocellular MGN) does develop discharge plasticity rapidly
during learning (Sections 5.I.1.). Furthermore, long term potentiation develops in the
magnocellular M G N (Section 5.2.), indicating that cells in this nucleus can serve as an
origin of plasticity. Notably, the magnocellular M G N projections to auditory cortex are
different from those of the thalamic component of the lemniscal line pathway. The diffuse
pathway terminates heavily in the upper layer of all auditory cortical fields, while the
lemniscal line projects exclusively to the middle layers (Section 4).
These findings suggest that learning-induced physiological plasticity in auditory cortex
depends upon the confluence of detailed, non-plastic, lemniscal information and plastic,
non-lemniscal influences. Biophysical and molecular approaches to cortical physiological
plasticity could take into account this framework. For example, the cortical synapses of
the magnocellular M G N projection would be an obvious subject of interest. It has
previously been determined that these synapses are located on the spines of layer I
dendrites, and are likely to be excitatory (Maiskii and Genis, 1972).
The fact that the MGv is not plastic is of potential importance because mechanisms of
plasticity should not be found in this nucleus. Moreover, the lack of plasticity in the
thalamic lemniscal line may be retained by certain neurons in auditory cortex which are
directly innervated by MGv (Section 6.3.2). Thus, the MGv and the MGm, as well as their
cortical termination zones, could serve as neural substrates for analysis of cellular and
subcellular mechanisms of plasticity; commonalities between the two could be discounted
as being non-critical for physiological plasticity.
In summary, there now appear to be sufficient basic data on the control, time course,
and locus to provide for the study of mechanisms of learning-induced physiological
plasticity in auditory cortex.
8.3.3. Generality of sensor), cortical plasticity
The findings of highly specific effects of learning on frequency receptive fields in AII/VE
present a new domain of inquiry for sensory cortex. Just as foundational studies of sensory
neurobiology have delineated sensory cortical fields, parallel studies are needed to
characterize the involvement of stimulus significance in the responses of sensory cortical
neurons. Only by comparative analysis with the visual and somatosensory cortices will it
be possible to determine how general or restricted is this cortical plasticity. Within each
modality, various fields also need to be compared. For example, it is possible that the
multiple sensory fields within each modality differ not only in their responses to the
physical parameters of stimuli but also in their sensitivity to the psychological aspects of
stimuli. This is the case for AI vs AII/VE (Diamond and Weinberger, 1984). Within each
PHYSIOLOGICAL PLASTICITY IN AUDITORY CORTEX
47
modality, various stimulus parameters need to be studied during learning. In the auditory
system, in addition to frequency, location of the sound source would be particularly
appropriate, given the sensitivity of auditory cortical cells to binaural cues (e.g. Kitzes et
al., 1980).
8.3.4. The basic paradigm of neurobiology
The basic paradigm of contemporary neurobiology can be traced rather directly to the
sensory-motor foundations of this science in the 18th and 19th centuries (Boring, 1957;
Liddell, 1960; Fearing, 1964; Young, 1970). Although experimental neurobiology based on
this paradigm has expanded in a systematic and productive manner, there are too many
aspects of brain function which cannot be encompassed therein. While we cannot recount
the contrary findings here, we have at least pointed out how traditional conceptions of
sensory cortex are incompatible with a growing body of anatomical and physiological data.
The new theme is the dynamic character of sensory cortex. Our findings emphasize the fact
that this dynamism is evident on a moment-by-moment time scale.
It would be premature and presumptuous to attempt to formulate a new paradigm for
brain organization at this time. We do urge that a great deal more research be devoted
to neuroplasticity, in order to achieve a comprehensive characterization of how this
property is distributed throughout the brain, the circumstances under which it is expressed,
and its biophysical and molecular bases. One avenue is to explicitly control the expression
of plasticity using learning. The techniques for instituting and controlling learning are
neither mysterious nor forbidding. They could, with profit, be included routinely in the
gamut of techniques that are part of normative neurobiology. Further, since plasticity is
expressed whenever information is acquired, and since information acquisition is a
pervasive process, it is important to recognize that learning-induced plasticity may be
instituted even when an experimenter has no intentions of so doing, This hightened
awareness should help focus attention on the dynamic aspects of brain function.
Acknowledgements
This work has been supported by research grants MH 11250, 22712 BNS 81924, NS
16108, ONR N-00014-84-K-0391, fellowships MH 05424, 05440, 11095, and 51342,
training grants MH 11095 and 14599, an unrestricted grant from the Monsanto Company,
and the University of California Irvine Focused Research Program in Cooperative Brain
Function. DD was supported in part by a UC Irvine Dissertation Fellowship and
Chancellor's Patent Fund Award. We wish to thank Drs. J. Michael Cassady and Herman
Birch for writing computer programs and Jacquie Weinberger for invaluable secretarial
services.
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