Download Physiological Plasticity of Single Neurons in Auditory Cortex of the

Behavioral Neuroscience
1984. Vol. 98. No 2, 189-210
Copyright 1984 by the
American Psychological Association. Inc
Physiological Plasticity of Single Neurons
in Auditory Cortex of the Cat During Acquisition
of the Pupillary Conditioned Response:
II. Secondary Field (All)
David M. Diamond and Norman M. Weinberger
Center for the Neurobiology of Learning and Memory
and Department of Psychobiology
University of California, Irvine
The discharges of 22 single neurons were recorded in the secondary auditory
cortical field (All) during acquisition of the pupillary dilation conditioned
defensive response in chronically prepared cats. All 22 neurons developed
discharge plasticity in background activity, and 21/22 cells developed plasticity
in their responses to the acoustic conditioned stimulus (CS). Nonassociative
factors were ruled out by the use of a sensitization phase (CS and US
[unconditioned stimulus] unpaired) preceding the conditioning phase and by
ensuring stimulus constancy at the periphery by neuromuscular paralysis.
Changes in background neuronal activity were related to measures of behavioral learning or to changes in the level of arousal. Specifically, decreases in
background activity (17/22 cells) developed at the time that subjects began to
display conditioned responses. Increases in background activity (5/22) developed in animals that became more tonically aroused during conditioning.
However, both increases (11/22) and decreases (10/22) in evoked activity
developed independently of the rate of pupillary learning, tonic arousal level,
or changes in background activity. These findings indicate that changes in
background activity are closely related to behavioral processes of learning and
arousal whereas stimulus-evoked discharge plasticity develops solely as a
consequence of stimulus pairing. A comparative analysis of the effects of
conditioning on secondary and primary (AI) auditory cortex indicates that
both regions develop neuronal discharge plasticity early in the conditioning
phase and that increases in background activity in primary auditory cortex
are also associated with elevated levels of tonic arousal. In addition, the overall
incidence of single neurons developing learning-related discharge plasticity is
significantly greater in All than in AI. The relevance of these findings is
discussed in terms of parallel processing in sensory systems and multiple
sensory cortical fields.
This article forms the second part of an
investigation of single-unit discharges in
auditory cortex of the cat during learning,
The first part described the effects of classical conditioning on the primary auditory
cortical field (AI; Weinberger, Hopkins, &
is
Neurological and Communicative Disorders and Cemed With the secondary auditory
Stroke Grant NS16108 and National Science Foun- (All). The two fields differ in their physdation Grant BNS76-81924 to N. M. Weinberger.
iological organization, response properties
The authors gratefuUy acknowledge Cathy Bennett to a c o u s t i c stimulation, thalamOCOrtical
and Thomas Mckenna for helpful discussion during
..
,
.
... ,
AT .
the preparation of the manuscript, Herman Birch for connections, and cytoarchltectoniCS. AI IS
writing the computer programs, William Hopkins for tonotopically organized, and its neurons
technical assistance, and Lisa Weinberger for secre- have narrow tuning curves. Its major thatarial assistance.
l a m i c 8 O u r C e of input is the ventral medial
Requests for reprints should be sent to Norman M. , ~ n j c u i f l t e n u c l p , , s (MGv) which is also
Weinberger, Center for the Neurobiology of Learning geniCUJate nucleus IML.V;, wnicn IS aiSO
and Memory, University of California, Irvine, Califor- tonotopically Organized and comprises part
nia 92717.
of the lemniscal auditory system (Aitkin &
189
190
DAVID M. DIAMOND AND NORMAN M. WEINBERGER
Webster, 1972). All is not tonotopically
organized, and its neurons have very broad
tuning curves. Its major source of input is
the dorsocaudal division of the medial geniculate (MGdc), the cells of which also
have broad tuning curves (Aitkin, 1973;
Calford & Webster, 1981). The major commonality of these two thalamocortical subsystems is the magnocellular division of the
medial geniculate nucleus (MGm). This nucleus projects to layer I of both AI and All,
and to all other cortical auditory fields as
well (Niimi & Naito, 1974; Wilson & Cragg,
1969). The neurons in the MGm are
broadly tuned (Aitkin, 1973) and receive
convergent input from the somatosensory
system (Poggio & Mountcastle, 1960; Wepsic, 1966).
Functional aspects of parallel thalamocortical auditory pathways have been revealed at the thalamic level in learning
tasks in which acoustic stimuli serve as cues
predicting reward or punishment. Neurons
in the lemniscal MGv respond in an unchanging fashion to acoustic stimuli during
learning irrespective of their behavioral relevance. In contrast, neurons in the nonlemniscal MGm develop discharge plasticity in
a rapid and pronounced manner during
learning. These results have been found in
three orders of mammals in three different
tasks: in the cat during classical defensive
(pupillary) conditioning for both multipleunit (Ryugo & Weinberger, 1976,1978) and
single-unit activity (Weinberger, 1982), in
the rabbit during instrumental avoidance
conditioning (Gabriel, Miller, & Saltwick,
1976), and in the rat during a hybrid instrumental-classical appetitive task (Birt,
Nienhuis, & Olds, 1979; Birt & Olds, 1981).
The discharge plasticity in the magnocellular medial geniculate develops in the absence of proprioceptive feedback or changes
in the effective stimulus intensity at the
tympanic membrane (Ashe, Cassady, &
Weinberger, 1976). Thus, at the level of the
thalamus, there is a fundamental dichotomy with respect to the ability of a region
of the medial geniculate nucleus to convey
either an accurate representation of the
acoustic environment (MGv) or respond
differentially to sounds that acquire greater
salience as a function of learning (MGm).
At the cortical level, the accompanying
investigation of primary auditory cortex
(Weinberger et al., 1984) demonstrated
that single neurons developed learning-related discharge plasticity rapidly, for both
background and evoked discharges. In that
report, we suggested that such plasticity
may result, in part, from the regulatory
influence of the MGm to layer I of the
primary auditory cortex. The present study
of the secondary auditory cortex provides
both a characterization of single neurons
in AH during learning and the first comparative data of neuronal activity in different sensory cortical subfields during learning.
A preliminary report of some of these
results has been presented (Diamond &
Weinberger, 1982).
Method
The surgical and training procedures were identical
to those described in the companion investigation of
the primary auditory cortex (Weinberger et al., 1984),
with one exception as noted below. Briefly, the subjects were 12 adult cats (3-5 kg) in good health.
Pedestals were affixed to the skull under general anesthesia (Nembutal, 40 mg/kg, ip) to provide for atraumatic fixation of the head during subsequent recording
sessions. Subjects recovered from the anesthesia in an
incubator, and recordings began 1-2 weeks later. On
the day of recording, paralysis was induced with gallarnine triethiodide (10 mg/kg, ip). The trachea was
intubated, and the animal was artifically respired. The
corneas were protected from drying with an application of ophthalmic ointment. Pupillary diameter was
monitored with an infrared pupillometer. Epoxyhtecoated tungsten electrodes were lowered through a
burr hole into All in a ventromedial direction at an
angle of 25°-30° to the vertical. Histological verification of the recording sites indicated that the electrode
typically entered the brain near the AI-AII border and
then passed at least 3 mm into All. Consequently, the
final position of the electrode was in the infragranular
layers (V and VI) during all recordings. Single-unit
activity was recorded on magnetic tape and led to an
LSI 11/03 computer for on- and off-line analysis.
The conditioned stimuli (CS) were white noise or
tones (70-80 dB) 1 s in duration, presented to the ear
contralateral to the recording site. The unconditioned
stimulus (US) was electrodermal stimulation (EDS;
375 ms) presented to the forelimb contralateral to the
recording site. Training consisted of 15 trials of sensitization (unpaired CS and US, 15 each) followed by
conditioning (CS paired with US at CS offset) up to
60 trials.
The only differences in procedure between this
study and the companion investigation of primary
auditory cortex was that several sessions at the start
of this study involved the extensive presentation of
191
PLASTICITY OF SINGLE All NEURONS DURING LEARNING
white noise or tones as search stimuli preceding training.
At the conclusion of the experiment, the animal
was deeply anesthetized and perfused through the
carotids with normal saline and 10% formalin. Recording sites were verified on the basis of cytoarchitectonic distinctions (Rose, 1949).
Results
26- 51- 76- 101- 151- >300
50 75 100 150 300
LATENCY TO ONSET (ms)
8-1 D-12B
9ms/bm
D-2B1
2ms/bm
20-
i
is-
General Response Characteristics of
Neurons in AH
Data were obtained from 22 cells in 21
recording sessions.1 The recording sites
were histologically verified in layers V and
VI of auditory field AH. The best stimuli
for evoking activity were complex sounds
such as keys jangling, squeaky sounds, and
the experimenter's voice. White noise was
more effective than tones in evoking responses. Consequently, white noise was
used as the CS in 18 sessions and a 2-kHz
tone in the other three sessions. The background firing rates of 21 of the 22 cells were
less than 7 spikes/s, averaging 2.5/s (SE =
0.56). One cell was unique in that its background activity was very high (26 sp/s), and
it was the only cell to exhibit a sustained
excitatory response to acoustic stimuli.
Virtually all cells (21/22) responded to
acoustic stimuli with an increased rate of
activity over background, but this proportion may not be representative of the All
population as a whole because inhibition
was difficult to detect due to the extremely
low background firing rates. The typical
evoked pattern was an onset response consisting of single or multiple discharges. The
mean latency to onset was 147 ms, the
median was 80 ms, and the range was from
22 to 500 ms (Figure 1). Long-latency responses might have resulted from an initial
period of inhibition followed by rebound
excitation, but the low background rates
precluded an analysis of this possibility.
les'
-50 0
52-
100
D-9B
9ms/bm
200 1000
500
15-
n-9c
J
6 ms /bin
12-
|
9-
1
"llJ 1 l 1 II
63-
963-
0
500
1000
1000
JBVI
0
L
L i
^ M I M • I 1 MM I I I ! II
500
10
Figure J. Upper right: Locations of the recording
sites that were histologically verified in layers V and
VI of cortical field AIL Upper left: Distribution of the
neuronal onset latencies following the presentation of
the acoustic stimulus. (Of the 22 cells, 21 displayed
excitatory responses.) Lower Peristimulus time histograms illustrating examples of cellular responses to
the acoustic stimulus. (Each histogram is a composite
of 50 stimulus presentations. The filled circle indicates
the determination of the onset latency. The horizontal
line denotes the duration of the stimulus presentation.)
phase, dilation responses were reduced in
both amplitude and duration. Electrodermal stimulation (US) produced consistently large dilation responses throughout
the experimental session. Acoustically
evoked dilations increased in amplitude
during the conditioning phase, as has been
reported (Ashe et al., 1976; Oleson, Vododnick, & Weinberger, 1973; Oleson, Westenberg, & Weinberger, 1972; Ryugo & Weinberger, 1978; Weinberger, Oleson, & Haste,
1973).
Pupillary Behavior and Conditioning
The rate of acquisition of the pupillary
Pupillary data were recorded during 20 dilation conditioned response was meaof the 21 recording sessions. Early in the sured relative to the averaged evoked dilasensitization phase, the acoustic stimulus
1
(CS) generally elicited a small amplitude
Two cells were recorded from one electrode during
dilation. By the end of the sensitization one session.
192
DAVID M. DIAMOND AND NORMAN M. WEINBERGER
tions on the last 5 trials of the sensitization
phase. The criterion of learning was five
consecutive dilation responses to the CS
greater than the sensitization reference
level; the fifth consecutive trial was noted
as the trial(s) to criterion. This criterion
was met in 17 of the 19 sessions in which
acoustically evoked dilations were recorded. During the 20th session, the pupil
dilated to a maximum level early in the
conditioning phase and remained there.
Consequently, the development of conditioned responses (CRs) could not be
measured for this session. For the 19 sessions in which conditioned responses were
recorded, the mean trials to criterion was
26.6. However, it became evident that the
trials to criterion were distributed bimodally; pupillary conditioned responses developed either rapidly (in less than 20 trials,
n — 10) or slowly (greater than 20 trials, n
= 9).2 The rapid learners attained criterion
in an average of 11.9 trials, and slow learners required 42.5 trials. The difference between the two groups is significant (t test,
p < .05; Figure 2). It is likely that the
disparity in learning rate is due to latent
inhibition as a result of the extensive use
of tones and white noise as search stimuli
in the earlier recording sessions (see
Method). In later recording sessions, we did
not use these stimuli to locate cells.
Squeaky sounds and jangling keys served
as effective stimuli for evoking neuronal
activity, and the retardation of learning
during these sessions was not evident. To
examine the latent inhibition hypothesis,
we compared the rate of pupillary learning
in sessions that involved the extensive use
of tones and white noise as search stimuli
with the rate in sessions in which complex
ambient sounds were used. For the sessions
that involved the extensive use of tonal
search stimuli, the criterion was met in an
average of 42.0 trials. Subjects conditioned
in sessions without such search stimuli
learned significantly more rapidly, in a
mean of 15.1 trials (p < .005, U test).
Therefore the rate of conditioning appears
to have been influenced by the amount of
prior exposure to tones and white noise.
Of the 12 animals, 10 were trained more
than once: 5 received three conditioning
1
2
3 ' 2 345|
4
5
6
SENSITIZATION SECOND
CONDITIONING
TRIALS
BLOCKS OF FIVE TRIALS
7
Figure 2 Pupillary learning curves. (Each point represents the mean (±1 SE. Values are computed as
percentage change in the acoustically evoked pupillary
dilation from the average response for each of the last
5 trials of sensitization. The animals are divided into
two groups on the basis of the rate of acquisition of
conditioned responses. For the slow learners, the magnitude of the dilation response remains at the sensitization level for the first 20 trials of conditioning.
Rapid learners display conditioned responses within
the first 10 trials of the conditioning phase and reach
asymptote by the 20th trial. The rate of acquisition is
illustrated in finer detail for the first 5 trials of conditioning. The N totals 19 because the evoked pupillary dilations were not monitored during 2 of the 21
recording sessions. In some cases, recording was terminated after the sixth block of conditioning [Trial
30] due to deterioration of isolation of discharges from
single units; the numbers of subjects for Blocks 7-9
were 12, 8, and 7.)
sessions and 5 received two sessions, at
intervals of 7-30 days. In order to assess
the cumulative effect of earlier training sessions on later ones, each animal was assigned a "savings score" based on whether
conditioned responses developed more rapidly in the later sessions than they did in
the first session. Thus an animal would be
assigned a positive savings score if the
number of all possible session comparisons
for which there was a reduction in the
trials-to-criterion measure was greater
2
Two subjects in the slow category failed to exhibit
five consecutive CRs. However, they developed significantly greater CS-evoked pupillary dilation responses
late in conditioning compared with the sensitization
phase (U test, p < .05). Consequently, they were
included in the slow-learning category, with their total
number of conditioning trials used as their trials to
criterion (34 and 50).
193
PLASTICITY OF SINGLE All NEURONS DURING LEARNING
than the number of comparisons that
yielded an increase in this measure. In this
manner, it was then determined that 4 of
10 animals had a positive savings score and
6 had negative savings. Hence there was
little evidence of savings when the subjects
were trained more than once.
Neuronal Data
To facilitate comparison of pupillary and
neuronal data, we used a criterion to classify neuronal plasticity in the same manner
as pupillary learning was classified. However, to accommodate decreases as well as
increases in neuronal activity, the criterion
for neuronal plasticity was five consecutive
trials, all of which had either greater or
fewer discharges than the mean of the last
five trials of the sensitization phase. We
would have excluded any neurons that, although meeting the criterion, were simply
continuing a trend existent during sensitization (Weinberger et al., 1984); however,
no such trends were found.
Background Activity
Background activity was measured for
the 1.5 s immediately preceding the initiation of a trial. All 22 units satisfied the
criterion of plasticity for background activity (Table 1). A significant majority of the
neurons (17/22) developed a decrease in
background activity during conditioning
(binomial test, p < .02). The mean number
of trials to criterion between increases and
decreases did not differ significantly (increases, n = 5, M = 14.0; decreases, n — 17,
M = 18.9; p < .05 (Figure 3A). Poststimulus
histograms of the development of decreases
in background activity during single sessions are presented in Figure 4 and of increases in Figure 5.
The fact that animals learned at different
rates led to an analysis of the relation between behavioral learning and the development of neuronal plasticity. The most
salient finding was that the development of
decreases in background activity was correlated with the acquisition of pupillary
conditioned responses. Subjects classified
as rapid learners displayed a rapid decrease
Table 1
Background Activity and Pupillary
Responses
Cell
no.
Conditioned
Trials to criterion
Pupil
Background discharges
Increases
II-2A
II-3B
II-9B
II-12A
II-12D
n
M
SD
43
51
•
9
16
21
6
23
7
13
4
5
29.8
17.7
14.0
7.0
Decreases
m
II-1C
II-2B1
II-2B1
II-2D
II-10B
II-9C
II-11B
II-llD
II-12B
II-4E1
II-4A2
II-A21A
II-A21D
II-4E2
II-4B
II-5C
II-10A
16b
16"
53
13
30
25
13
38
14
6
6
38
16
10
50
59
n
M
SD
15
17
25.8
17.2
18.9
14.3
6
21
11
33
20
61
27
6
8
6
6
23
23
6
37
14
14
Totals
19
22
n
M
26.6
17.8
SD
17.4
13.1
* Pupillary behavior was not monitored during these
sessions. b Cells II-2B1 and II-2B1' were recorded
simultaneously from the same electrode during one
session; therefore, this value applies once to both cells.
in background activity during stimulus
pairing. Slow learners did not reach the
behavioral criterion until considerably later
in the conditioning session, and the development of changes in background activity
was also retarded. The relation of decline
in background activity to acquisition of the
pupillary conditioned response is presented
in Figure 6. The difference in background
activity between the respective groups is
DAVID M. DIAMOND AND NORMAN M. WEINBERGER
194
270 _
A BACKGROUND
A
INCREASE
n-2D
B.
n-iiB
SENSITIZATION
T
42-
TR 1-15
180 -
90
TR 1-15
35-
12-
28-
9-
21-
6-
14-
3-
7i..|
: -90
_|.
i.
i
•~t*
—™
r
f J.
»""V
*
IlLllUlB
—i—i—i—i—
i—
CONDITIONING
21-
TR 1-15
147CO
LU
a.
CO
2
3
SENSITIZATION
4
5
6
CONDITIONING
BLOCKS OF FIVE TRIALS
Figure 3 Learning curves for (A) background activity (measured for the 1.5 s immediately before each
trial) and (B) evoked activity, of single neurons that
satisfied the plasticity criteria. (Values are relative to
the average level of neuronal activity during the last
5 trials of sensitization Conditioning stimulus was
white noise or pure tone, 1 s in duration. Number of
cells for each block in A during conditioning: increases,
5,5,5,5,5,4,4,3,2; decreases, 17,17,17,17,17,16,11,8,8.
Number of cells in each block in B during conditioning: increases, 11,11,11,11,11,10,5,5,4; decreases,
10,10,10,10,10,10,9,5,5. All 22 cells developed plasticity
in background activity, and 21/22 cells developed plasticity in evoked activity.)
21-
TR 16-30
147314-
TR 31-45
7TR 46-60
14-
TR 46-60
7-2000
^2000 4000
500 1000
ms
statistically significant during the first 20
trials of conditioning (U test, p < .02).
Later in conditioning, background activity
stabilized at about the same level for both
groups (Figure 6).
Increases in background activity during
conditioning (n = 5) developed rapidly even
when animals learned slowly. However,
these neuronal changes were related to
other measures of pupillary behavior and
are evaluated in detail in a later section
which examines the relation between behavioral measures of tonic arousal and neuronal activity.
Figure 4 Peristimulus histograms of examples of
single-unit activity in All during individual conditioning sessions. (Here and Figure 5, each histogram is the
sum of 15 consecutive trials for sensitization and
conditioning. A: Cell II-2D developed a decrease in
both background and evoked activity. B: Cell II-11B
developed a decrease in background activity as evoked
activity increased. The bar from 0 to 1,000 ms indicates the conditioned stimulus duration, and the second bar [present only during conditioning] indicates
the duration of the unconditioned stimulus [US],
which was 375 ms Neuronal activity during the US is
not presented for cell II-llB.)
Evoked Activity
Evoked activity was computed as the difference between background and evoked
195
PLASTICITY OF SINGLE AH NEURONS DURING LEARNING
n-IC
B
320
H-12A
SENSITIZATION
60
160
>
J 20
3
a
•
- A.
/
804
/
\
0 g
0
3
I
CONDITIONING
20-r
a:
o
g-20
-
i1 -40
-
-
/
•
TR I 15
-
JO
"
£
K \°\\ 7
i \
/ \
•
-160 S
AD BACKGROUND
•
I S U n.7
O—-OFost n.9
-60
-80
v
\
o j^**
80
-240
PUPILLARY CR
A—ASlow n • 7
6—Gfost n-8
1
1
2
3
1
SENSITIZATION
2
3
4
5
6
CONDITIONING
7
BLOCKS OF FIVE TRIALS
Figure 6 Illustration of the relation between the
development of decreases in background activity and
the rate of pupillary conditioning. (Each point is the
mean value for a block of five trials and is expressed
as percentage change from the mean value of the last
-1000 -500 0
3000
five trials of sensitization. Fast learners [open triannra
gles] displayed conditioned responses within the first
five trials of conditioning, whereas slow learners [solid
Figure 5. Peristimulus histograms of examples of
triangles] did not begin to display conditioned resingle-unit activity in All during individual conditionsponses until after the 20th trial of conditioning.
ing sessions. (A: Cell II-lC developed an increase in
Rapid learners developed decreases in background acboth background and evoked activity. B: Cell II-12A
tivity [open circles] within the first five trials of condeveloped an increase in background activity and a
ditioning. Background activity for the slow learners
decrease in evoked activity. The bar from 0 to 1,000
[solid circles] did not decrease until the fifth block of
ras indicates the duration of the conditioned stimulus, conditioning trials, at which time the slow learners
and the second bar [only present during the conditionbegan to exhibit conditioned responses and the backing phase] indicates the duration of the unconditioned
ground activity abruptly decreased. The n for fast
stimulus [US], which was 375 ms. Neuronal activity
pupillary learners equals 8, and the neural data conduring the US is not presented for cell II-lC.)
tains 9 cells because two units were recorded from one
electrode during one session. In Figure 3, the n for
decreases in background activity equals 17 because it
represents the activity of all cells that developed
changes in activity during conditioning. One of the
discharges. This method eliminated appar- cells could not be included in this analysis [n = 16]
ent changes in evoked activity that merely because pupillary behavior was not monitored during
reflected a general change in the back- a session in which a decrease in background activity
ground excitability of a cell, rather than a was recorded.)
specific effect that occurred during acoustic
stimulation. Of the 22 neurons, 21 developed stimulus-evoked plsticity during conditioning (Table 2). Eleven developed increases (Af = 21.7 trials to criterion), and
10 developed decreases (M = 12.5 trials to
criterion; Figure 3B). Decreases in evoked
activity were significantly more rapid than
increases (U test, p < .01). Poststimulus
histograms of the development of increases
in evoked activity during single sessions are
presented in Figures 4B and 5A; decreases
are presented in Figures 4A and 5B. There
were no significant relations between the
development of changes in evoked activity
and pupillary learning.
This is in contrast to the direct relation
found for decreases in background activity
and the acquisition of pupillary conditioned
responses, discussed above. However, one
consistent aspect of evoked plasticity was
that decreases always developed rapidly,
even when pupillary learning occurred
much later in the conditioning session. Decreases in evoked activity satisfied the plasticity criterion in 10.8 conditioning trials
196
DAVID M. DIAMOND AND NORMAN M. WEINBERGER
Table 2
Evoked Activity and Pupillary Conditioned
Responses
Trials to criterion
Cell no.
II-1C
II-2A
I1-2B1
II-3B
II-9B
II-10A
II-10B
II-11B
II-A21A
II-4E2
II-4E1
Pupil
Evoked discharges
Increases
°
10
43
26
16
51
0
59
13
25
6
16
14
11
30
19
26
26
25
35
6
25
terion for background and evoked discharges were 17.9 and 17.3, respectively.
However, the directions of change (increase
or decrease) within a training session were
independent, x 2 (l, N = 21) = 0.153, p >
.05; for example, increases in background
activity were accompanied by the development of increases or decreases in evoked
activity. These findings are summarized in
Table 3.
Relation Between Tonic Arousal and
Neuronal Discharge Plasticity
The pupillomotor system provides sensitive indexes of the general state of excitability or arousal of a subject, in addition
11
n
9
to yielding prime data on the acquisition of
M
27.0
21.7
an associative relation between a CS and a
8.7
SD
18.0
US, that is, a conditioned response. As an
Decreases
index of tonic arousal, we measured the
53
II-2D
8
baseline level of pupillary dilation through30
8
II-9C
out each recording session. Pupillary base13
II-11D
42
line was measured immediately preceding
9
7
II-12A
presentation of each acoustic stimulus. The
II-12B
38
6
average of the last 5 CS trials of sensitiza16
II-12D
8
6
6
II-4A2
tion served as the reference level, and
34
9
II-A21D
changes in the baseline of pupillary dilation
50
II-5C
23
were measured as a percentage change from
10
IIp4B
8
this reference value. The tonic level of dilation increased by about 30% early in the
n
10
10
M
25.9
12.5
sensitization phase, reaching asymptote beSD
16.6
10.9
tween the 5th and 10th sensitization trials
(see Figures 7A and 7B). Decreases in neuTotal
ronal background activity (n = 17) always
19
21
n
occurred when the tonic level of dilation
M
26 4
17.3
SD
17.3
10.8
remained at about the same relative level
during the conditioning phase as it was
Note Cell II-2B' did not develop evoked plasticity.
* Pupillary behavior was not monitored during these during the last 10 trials of sensitization. In
sessions.
contrast, the 5 sessions in which neuronal
background activity increased were unique
in that the pupillary baseline also increased
for slow learners and 14.3 trials for fast
learners. The difference was not significant
(U test, p > .1). In contrast, increases in Table 3
evoked plasticity were just as likely to occur Effects of Conditioning on Background and
before as after the development of pupillary Evoked Activity
conditioned responses.
Background discharges
Relation of Evoked to Background Activity
The rates of change for background and
evoked discharges were not significantly
different; the overall average trials to cri-
Evoked discharges Increase Decrease No change
3
8
Increase
8
2
Decrease
1
0
No change
2
Note x (1, N = 22) = 0.153, p > .05.
PLASTICITY OF SINGLE AH NEURONS DURING LEARNING
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COND
BLOCKS OF FIVE TRIALS
8
9
Figure 7. Tonic level of arousal presented as a function of the direction of changes in neuronal activity.
(Arousal level is indexed by the baseline level of pupillary dilation measured immediately before the presentation of a trial. A: Tonic arousal level increased for
animals that developed an increase in background
discharge activity [n = 5] but was unchanged for
animals that developed decreases in background discharge activity [n = 15]. B: Tonic arousal level did
not differ between subjects that developed increases
(n = 10) or decreases (n = 11) in evoked discharge
activity. The n value equals 20 rather than 21 because
pupillary behavior was not monitored during one session.)
significantly during the conditioning phase
([/test, p < .001). This indicates that increases in neuronal background activity
were accompanied by increases in tonic
arousal during conditioning but that decreases in background activity were not
accompanied by decreases in tonic arousal
(Figure 7A).
In a related issue, recall that decreases in
background activity developed early in conditioning for rapid learners and after the
20th trial for slow learners. The relation
between arousal and background activity
led to an analysis of the possibility that the
differential rate of decline may have resulted from a difference in generalized
197
arousal between the two groups. In order to
investigate this possibility, the baseline levels of the pupil during the first 20 trials of
conditioning were compared for the rapid
and slow learners. The tonic levels of dilation of rapid and slow learners were not
different during the first 20 trials of conditioning (Mann-Whitney U test, p > .1).
Therefore, the differential rate of decrease
in background activity during conditioning
for the rapid and slow learners was not due
to a difference in their levels of tonic
arousal.
In contrast to background activity, plasticity of evoked activity to the CS did not
bear any relation to the baseline level of
the pupil (Mann-Whitney U test, p > .1;
Figure 7B).
Relation Between Phasic Arousal and
Neuronal Discharges in AH
Phasic increases in pupillary dilation (25 s) were reliably evoked by electrodermal
stimulation. This unconditioned response
may be considered a reliable index of phasic
increases in general behavioral excitability
or arousal. In order to examine the possible
effects of phasic arousal on cellular activity,
neuronal discharge rate was measured for
the 1.5 s immediately preceding and immediately following each EDS during the
sensitization phase. For each animal, the
numbers of discharges during the pre- and
post-EDS periods for each trial were evaluated across the 15 sensitization EDS trials
by the Mann-Whitney Utest (Siegel, 1956).
Of the 22 neurons, 17 exhibited significant
responses to EDS (p < .05); the rates of
discharges were increased for 6 cells and
decreased for 11 neurons.
This outcome is in contrast with evidence
that increases in tonic arousal were always
accompanied by increases in background
activity, as discussed above. Moreover, of
the five cells that developed increases in
background activity along with elevated
levels of tonic arousal, four exhibited a
suppression of ongoing activity during
phasic increases in arousal.
As further evidence that tonic and phasic
changes in arousal level have different effects on neurons in All, we may consider
198
DAVID M. DIAMOND AND NORMAN M. WEINBERGER
A.
B.
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4000
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Figure 8 Peristimulus histograms of single-unit activity in AH during 15 presentations of the
unconditioned stimulus (EDS) for two cells. (They illustrate the finding that All cells respond
differently to tonic and phasic changes in arousal level. Cell II-2A developed an increase in background
activity which was correlated with an increasing tonic level of behavioral arousal. However, following
EDS discharge activity decreased. Cell II-3B developed a decrease in background activity as the tonic
level of arousal remained relatively constant during conditioning. A phasic increase in arousal evoked
a substantial increase in discharge activity. The stippled bar indicates the duration of the unconditioned stimulus, which was 375 ms.)
data from cells II-3B and II-2A, illustrated
in Figure 8. Subject II-3B developed an
increase in pupillary baseline during the
conditioning phase, and its neuronal background activity also increased. However,
EDS caused suppression of its discharges
(Figure 8). On the other hand, subject II2A was more typical in that it did not
develop an increase in pupillary baseline
during conditioning and its background activity decreased during the conditioning
phase. Nonetheless, increases in phasic
arousal elicited an increase in firing rate
(Figure 8).
Comparison of Primary (AI) and
Secondary (All) Cortical Auditory Fields
At this juncture, it is possible to compare
the effects of training on the discharges of
single neurons in All with those reported
in the companion article for AI (Weinberger et al., 1984).
The probabilities of the development of
discharge plasticity during conditioning
were compared in 2 X 2 contingency tables.
These analyses indicated that neurons in
All had a significantly higher proportion of
discharge plasticity than did neurons in AI,
both for evoked, x 2 (l, N = 41) = 4.87, p <
.05 (Table 4), and background, x'(l, N =
41) = 8.98, p < .01, activity (Table 5). The
direction of change for background and
evoked activity was evaluated in the same
manner. There was no significant difference between AI and All for evoked activity, x 2 d, N = 33) = 0.05, p > .05. For
background activity, All developed predominant decreases in contrast to AI, but
the differences did not reach statistical significance, x 2 (l, N = 33) = 3.68, p < .10.
The effects of phasic arousal on singleunit discharges were also evaluated. It
should be recalled that the effects of phasic
arousal were measured as the responses, or
lack thereof, to EDS during presentation of
the US in the sensitization phase of the
experiment. Only 6/19 neurons in AI
showed a significant response to EDS, in
contrast to 17/22 cells in All. This difference was statistically significant, x 2 (l. N =
41) = 6.89,p<.01.
Comparison of the rates of development
of discharge plasticity was complicated by
the fact that in the present study of All,
acquisition was retarded in several cases
due to latent inhibition that was caused by
the extensive use of acoustic search stimuli
Table 4
Comparison of Effects of Conditioning on
Evoked Discharges for Primary (AI) and
Secondary (AH) Auditory Fields
Training outcome
AI
Plastic
12
Nonplastic
7
Note x2 (1, N = 41) = 4.87, p < .05.
AH
21
1
PLASTICITY OF SINGLE All NEURONS DURING LEARNING
Table 5
Comparison of Effects of Conditioning on
Background Discharges of Primary (AI) and
Secondary (AH) Cortical Auditory Fields
Training outcome
AI
Plastic
11
Nonplastic
8
Note. x2(l,N=
41) = 8.98, p < .01
All
22
0
preceding training, as discussed above.
Therefore, this comparison was restricted
to those neurons in All that were recorded
during sessions that had training conditions identical to those used in the study of
AI, that is, no extensive use of acoustic
search stimuli.
In the case of evoked activity, this comparison yielded data from 10 neurons from
All, compared with 12 cells in AI in which
conditioning resulted in significant changes
in evoked activity. There was no significant
difference between the rates of change for
AI and All (AI M = 13.17 trials to criterion;
All M = 14.50; Mann-Whitney U test, p >
.05). In the case of background activity,
there were 11 neurons in All and also 11 in
AI that attained the criterion of change.
The AI neurons had a mean of 22.91 trials
to criterion, and the mean for All was 14.63.
This difference approached but did not attain statistical significance (Mann-Whit-
ney
Utest,p<A0).
Summary of Results
All 22 cells recorded in All developed
physiological plasticity in either background or evoked activity during the conditioning phase, and 21 of the 22 cells were
plastic in both measures. Furthermore,
changes in background activity were related
to behavioral measures of arousal and
learning rate. Increases in background activity occurred in animals that became
more tonically aroused during conditioning
than in the sensitization phase. Decreases
in background activity developed in subjects that remained at the same relative
tonic level of arousal during the conditioning and sensitization phases. The decrease
in background activity developed along
with the acquisition of pupillary condi-
199
tioned responses. Increases in phasic
arousal also affected the activity of most
neurons, but the effects of phasic and tonic
arousal were not necessarily concordant.
The rates at which neurons in AI and
All developed discharge plasticity for
evoked and background activity were not
significantly different. However, the proportion of cells that developed discharge
plasticity was significantly greater in All
than AI both for evoked and for background
activity. Finally, phasic arousal had greater
effects on cells in All than in AI.
Discussion
Changes in sensory system activity during learning may reflect mechanisms that
underlie alterations in the processing of
information. However, central auditory activity can be affected by changes in the
effective intensity of a stimulus at the receptors during postural adjustments and
middle ear muscle contractions (Imig &
Weinberger, 1970; Marsh, Worden, &
Hicks, 1962; Starr, 1964; Wiener, Pfeiffer,
& Backus, 1966). In this investigation, the
subjects developed pupillary conditioned
responses while they were maintained under neuromuscular blockade. Consequently, the changes recorded in secondary
auditory cortex during learning cannot be
attributed to proprioceptive feedback or to
a change in the physical parameters of the
stimulus at the tympanic membrane.
Given that the stimulus remained constant throughout the conditioning session,
it is extraordinary that every cell recorded
in All developed physiological plasticity
during learning. The only comparable degree of learning-related changes, of which
we are aware, is that of the magnocellular
medial geniculate nucleus (MGm) of the
thalamus. It has been reported that all neurons in this nucleus exhibit discharge plasticity for either or both background and
evoked activity during pupillary conditioning (Weinberger, 1980, 1982). The possible
role of MGm plasticity in that of All is
considered in a later section.
In addition to the detection of neuronal
plasticity during conditioning, changes in
All single-unit activity covaried with be-
200
DAVID M. DIAMOND AND NORMAN M. WEINBERGER
havioral measures of learning rate and level
of arousal. However, before further discussing relations between neuronal activity and
behavioral measures, it will be helpful to
provide a general description of the discharge characteristics of the cells that were
encountered in this region.
General Characteristics of Neuronal
Activity in AH
The cells recorded in this study typically
responded best to squeaky sounds and
other complex acoustic stimuli. Onset latencies ranged from 22 to 500 ms; the average was 147 ms, and the median was 80
ms. These values are similar to previous
recordings of single cells in All in anesthetized preparations. Katsuki, Watanabe,
and Maruyama (1959) noted that most cells
in All responded with latencies greater
than 100 ms whereas AI units had considerably shorter onset latencies. Others extended their analysis of AI to note the
broadness of tuning curves in AH and its
lack of tonotopic organization (Merzenich,
Knight, & Roth, 1975; Middlebrooks &
Zook, 1983; Reale & Imig, 1980).
Background activity for most cells was
very low, rarely exceeding 5 spikes/s. It was
common to find cells that fired only 5-10
spikes/min. An example of this class of unit
is presented in Figure 4A. Its evoked response consisted of one or two discharges
at a latency of about 30-50 ms after stimulus onset, followed infrequently by further
firing. This particular unit had a background firing rate of 8 spikes/min during
the sensitization phase, which declined to
an almost complete cessation of background activity during conditioning. This
essentially led to a circumstance such that
the stimulus-evoked discharges were the
only times the cell fired for periods as long
as 10-15 min.
One cell was unique in that its background firing rate was considerably higher
than the rest of our sample (27 spikes/s),
and it was the only unit to exhibit a sustained excitatory response to acoustic stimulation. The discharge characteristics of
this cell were similar to a class of cells
recorded by De Ribaupierre, Goldstein, and
Yeni-Komshian (1972) in AI of the cat.
(See also Mountcastle, Talbot, Sakata, and
Hyvarinen, 1969, for similar data in somatosensory cortex.) Others have also detected a low incidence of auditory cortical
units that have high background firing
rates (Goldstein & Abeles, 1975). The major features that this unit had in common
with the AI cells in De Ribaupierre's study
were its high rate of background activity
and sustained excitatory response to acoustic stimulation. It is unlikely that the highrate units of De Ribaupierre were axons
because extensive intracellular recordings
were obtained from many cells in this category. In the present study, the unique behavior of this cell cannot be attributed to
peculiarities in the recording site or a result
of an instability in the preparation because
a second cell was recorded from the same
electrode and it responded in a more typical
fashion, that is, it had a very low rate of
background activity (5 spikes/min) and
rarely discharged more than one action potential to the acoustic stimulus.
Mountcastle et al. (1969) and De Ribaupierre et al. (1972) postulated that cells that
received predominantly excitatory input
and lacked inhibitory postsynaptic potentials at the soma were stellate cells whereas
units with lower background rates and
transient evoked responses were pyramidal
cells. These points are noteworthy because
the high-rate cell in this study was the only
one that failed to develop evoked plasticity
during conditioning. Although the sample
size is too small to speculate extensively on
the nature of this finding, it is suggestive
of a fundamental difference between plastic
changes in cortical projection cells and interneurons during learning.
Relation Between AH Neuronal Activity
and Learning
AH unit activity was profoundly influenced by the conditioning procedure. All 22
units displayed plasticity in their background activity, and 21 of the 22 developed
evoked plasticity. The probability of obtaining increases and decreases in evoked
activity was approximately equal; 11 units
increased and 10 decreased evoked activity
PLASTICITY OF SINGLE AN NEURONS DURING LEARNING
201
during conditioning relative to the sensiti- that decreases in auditory cortical backzation phase. Decreases in background ac- ground activity predominated during activity predominated; 17 units decreased, quisition of a tone-signaled, appetitive clasand only 5 developed increases. The direc- sically conditioned response in rats. As in
tion and rate of change in background ac- the present study, the decreases began with
tivity were not related in any obvious man- the first evidence of conditioned responses.
ner to evoked changes.
Our findings are also in agreement with the
Given that there was such a large'degree aforementioned study with regard to the
of plasticity, we investigated the relation differential nature of evoked and backbetween alterations in firing rates as a ground changes. In rat auditory cortex,
function of the rate of learning. A serendip- evoked plasticity developed later than did
itous finding aided such an investigation. background changes and the early signs of
The subjects acquired the pupillary condi- behavioral learning. The fact that we found
tioned response either rapidly (range, 6-16 changes in evoked activity both before and
trials) or slowly (range, 25-59 trials). It is after learning is likely to be a function of
likely that this was the result of two differ- the differences in the sampling of neuronal
ent procedures that were employed while populations. Disterhoft and Stuart researching for cells. The low background corded from more than one cell simultanerates encountered in All made it difficult ously, whereas the present study characterto locate units in the absence of acoustic ized the activity of single neurons.
stimulation. In earlier recordings, tones
Changes in evoked and background acand white noise stimuli were extensively tivity are likely to involve different mechused as search stimuli. However, the devel- anisms for the following reasons. Evoked
opment of conditioned responses was de- plasticity developed gradually and reached
layed in these sessions. In later recording asymptote after 20-35 conditioning trials
sessions, it was discovered that the best (see Figure 4A). Further, the development
stimuli for evoking All activity were com- of changes in evoked activity did not coinplex sounds such as squeaks and shaking cide with the acquisition of pupillary conkeys. By using these stimuli, we were able ditioned responses. Thus, stimulus-evoked
to obviate the problem of locating cells with plasticity develops solely as a consequence
low background firing rates without induc- of stimulus pairing and maintains a gradual
ing a latent inhibitory effect on condition- increase in plasticity beginning early in the
ing. The subjects that learned slowly al- conditioning phase. In contrast, decreases
lowed for the investigation of the temporal in background activity developed abruptly,
relation between the development of neu- along with the first signs of associative
ronal plasticity and the acquisition of con- learning (see Figure 6). When the subjects
ditioned responses.
developed pupillary conditioned responses
The rate at which evoked plasticity de- rapidly (fewer than 10 trials), the decrease
veloped was not related to the rate of pu- occurred abruptly, within the first 5 trials
pillary conditioning during individual re- of conditioning, and stabilized at depressed
cording sessions. In contrast, changes in levels of activity for the duration of the
background activity were correlated with recording session. The subjects that exhiblearning rate. Specifically, for units that ited slower learning began to develop condeveloped decreases in background activity ditioned responses after the 20th trial. Noduring conditioning, the rate of decrement tice in Figure 6 that background activity of
was directly related to the rate of develop- cells in the slower learners remained at the
ment of the pupillary conditioned response. sensitization level for the first 20 trials of
Rapid learners displayed a rapid decrease conditioning and then abruptly decreased
in background activity, whereas the decre- and stabilized.
ment was not evident in slower learners
The relation between learning rate and
until they began to associate the acoustic neuronal plasticity held for decreases in
stimulus with paw shock (see Figure 6). background activity only. The five units
Disterhoft and Stuart (1976) also reported that showed increases in background activ-
202
DAVID M. DIAMOND AND NORMAN M. WEINBERGER
ity during conditioning did so at a rate that
was independent of the rate of learning.
However, increases in background activity
were related to other measures of behavior,
and these are discussed in the next section.
Relation Between Neural Activity and
Tonic Arousal
related to the rate of learning, were not
associated with the tonic level of arousal;
decreases in background activity occurred
in training sessions that involved no significant changes in tonic arousal level.
With further respect to changes in background activity, we previously noted that
decreases in background activity during
conditioning develop at a rate that is correlated with the rate of learning; rapid
learners develop decreases rapidly, and
slow learners develop decreases more
slowly. Perhaps the reason why there was
a differential rate of decline of background
activity was a difference in the tonic level
of arousal between rapid and slow learners;
for example, if the slow learners were temporarily in a state of increased tonic arousal
early in conditioning, their background activity could have been elevated and thus
retarded the rate of decrease of background
activity. If this was the case, then one would
expect the pupillary baseline of the slower
learners to be greater than that of the rapid
learners in the early stage of conditioning.
However, an analysis of this possibility revealed that the baseline level of pupillary
dilation did not differ between the two
groups early in the conditioning session.
Therefore, the differential development of
the decrement in background activity is not
a function of differences in generalized
arousal. Rather, it appears to reflect associative processes, the exact nature of which
remains to be determined.
In addition to providing an index of
learning, pupillary dynamics serve as an
indicator of the behavioral state of the animal. In humans, the relation between
arousal level and pupillary dilation is well
documented (Nunnally, Knott, Duchnowski, & Parker, 1967). By using the relative levels of pupillary dilation during a
recording session as an indicator of the
state of the subject, the relation between
neuronal activity and arousal level could be
quantified. The analyses focused on the
tonic or baseline level across the entire
recording session and phasic increases in
arousal following EDS. In this section, we
take up the former; in the next section, the
latter.
The tonic level of arousal in awake animals has not been investigated widely in
previous neurophysiological studies of
learning. Generally, it has been assumed
that whereas distinctions among states of
waking, drowsiness, and sleep are important, finer distinctions need not be addressed. Perhaps this is so because animals
are clearly awake during conditioning
training and sensitive measures of tonic
It is important to point out that animals
arousal are not generally employed. How- can still learn rapidly even with increases
ever, we were able to analyze the tonic level in pupillary baseline level and background
of arousal in awake animals because we neuronal activity. Therefore, the decrease
recorded the diameter of the pupil during in background activity related to behavioral
the intertrial intervals as well as during the learning should be considered to be a compresentation of the conditioning stimuli.
ponent of acquisition during a relatively
As noted above, increases in background stable state of tonic arousal, but it is not a
activity were unrelated to the rate of pupil- necessary component of learning per se.
lary conditioning. However, they proved to
The overall picture presented with rebe related to tonic arousal; animals that spect to background activity, tonic arousal,
became more tonically aroused also devel- and conditioning is as follows. Decreases in
oped increases in background activity (Fig- background activity are correlated with the
ure 8). This relation holds for the 5 neurons rate of acquisition of the conditioned rethat developed increased background activ- sponse; further, they are themselves assoity but not for the 17 neurons that exhibited ciative in nature. This is the usual state of
decreased background discharges. Thus, affairs, as revealed to the experimenter
decreases in background activity, although when the level of tonic arousal does not
PLASTICITY OF SINGLE All NEURONS DURING LEARNING
change much during training; in the present experiment, such effects occurred in 17/
22 cases. However, when, for reasons unknown, subjects develop increases in their
level of tonic arousal, background activity
increases in a correlated manner, and such
increases override or "mask" processes that
generate the usual decrease in background
activity. The tonic level of arousal need not
change in order for associative behavioral
and neuronal events to develop, as such
events are obtained in the absence of
changes in tonic arousal in most cases.
Thus, changes in tonic arousal should be
viewed as performance rather than as associative factors. They are nonetheless important because they can mask or prevent
the appearance of neuronal changes that
are associative (i.e., decreases in background activity) and are neurophysiological
correlates of acquired responses (e.g., conditioned pupillary dilation responses). One
implication of these findings is that caution
should be exercised in the interpretation of
the absence of a neurophysiological correlate of learning in a given experiment unless there has been a concurrent analysis of
performance variables that could obscure a
brain-behavior relation, such as the level
of tonic arousal.
Relation Between Neuronal Activity and
Unconditioned Phasic Arousal
Phasic (transient) arousal is evidenced
by pupillary dilations that are evoked by
sensory stimulation and have a relatively
brief duration (e.g., 2-5 s). Strictly speaking, conditioned dilations to acoustic stimulation are instances of phasic arousal.
However, for purposes of discourse, we distinguish between these learned effects,
which have been discussed previously, and
unconditioned arousal, such as that which
occurs in response to presentation of the
unconditioned stimulus. To assess the possible relations between phasic arousal and
neuronal discharges, we analyzed the effects of EDS during the sensitization phase.
As noted in Results, 17 of the 22 cells
responded to EDS: 6 exhibited increases,
and 11 exhibited decreases in activity, relative to pretrial discharge activity. It is
203
important to note that for a given neuron,
the effects of phasic arousal were not necessarily the same as the effects of tonic
arousal. Of the 5 neurons that had increases
in background activity, along with increasing tonic levels of arousal, 4 displayed a
decrease in activity during phasic arousal.
Hence, increases in tonic arousal were always accompanied by increases in background cellular discharge activity, whereas
increasing phasic arousal caused either increases or decreases in neuronal activity.
Such evidence indicates that tonic and
phasic changes in arousal level represent
distinct physiological processes: the latter
is apparently not merely a brief episode of
the former.
The present findings on arousal-related
processes in sensory cortex are somewhat
similar to the effects of stimulation of the
reticular formation on cortical cellular
function, which also may be either facilitatory or inhibitory (Feeney & Orem, 1972;
Inubishi, Kobayashi, Oshima, & Torii,
1978; Singer, Tretter, & Cynader, 1976;
Spehlmann & Downes, 1974). However, it
is not yet possible to draw conclusions regarding the extent to which the normative
function of the reticular formation is responsible for the increases and decreases in
cellular discharge reported here for tonic
and phasic arousal, for several reasons.
First, the phasic arousal effects herein reported were elicited by sensory stimulation,
and it has not been determined whether a
given cortical cell responds in the same
manner for peripherally and centrally induced arousal. Second, the previous studies
did not measure the changes in pupillary
diameter that undoubtedly occur following
reticular stimulation (Loewy, Arajo, &
Kerr, 1973), so that one cannot yet infer
that the two sources of arousal yield the
same behavioral results. Third, there is as
yet insufficient understanding of the presumptive different mechanisms underlying
phasic and tonic arousal (Jasper, 1960).
However, at least the first two issues may
be approached directly by concurrent use
of reticular and sensory stimulation while
records are obtained from single cortical
neurons. Such studies should also shed
light on the extent to which phasic arousal
204
DAVID M. DIAMOND AND NORMAN M. WEINBERGER
induced by EDS is similar to phasic conditioned arousal induced by a conditioned
acoustic stimulus.
Arousal, Attention, and Learning
berger, & Westenberg, 1972; Orman &
Humphrey, 1981), but learning studies have
consistently failed to obtain discharge plasticity in this nucleus (Birt et al., 1979;
Gabriel et al., 1976; Ryugo & Weinberger,
1976, 1978). Hence, arousal and learning
effects are clearly separable. These data
indicate that processes of attention and
arousal may affect widespread regions of
the brain but that the capacity to develop
discharge plasticity as a function of associative learning may involve more restricted populations of cells. In order to
determine such a capacity, recordings must
be obtained during the acquisition phase of
learning rather than during the performance of an overlearned task.
Miller, Pfingst, and Ryan (1982) reviewed studies of single-unit activity in the
auditory system of primates during the performance of various tasks and concluded
that changes in neuronal activity are
largely a consequence of shifts in arousal
and attention, rather than learning. Although this line of research has been fruitful in identifying neuronal correlates of attention, the designs employed do not allow
one to distinguish between the effects of
learning and the effects of arousal or attention. The subjects had been trained in complex instrumental tasks for many months Relation to Previous Studies of Acquisition
before recordings were initiated. Miller and of Conditioned Responses
associates found that auditory system neuThere are two previous studies that inronal activity was significantly altered dur- vestigated neural recordings in nonprimary
ing trials when the subject was attending auditory cortical fields during learning.
to acoustic cues, compared with nonattend- Kraus and Disterhoft (1982) reported on
ing trials. The fact that neuronal activity single units in auditory association cortex
in a sensory system is different while a of the rabbit during acquisition of the nicsubject is attending to environmental stim- titating membrane response,3 and Gabriel,
uli is consistent with the view that sensory Orona, Foster, and Lambert (1982) recortex plays an active role in the processing ported on multiple-unit activity in a secof information, rather than only providing ondary auditory cortical field of rabbits
an accurate representation of the physical during active avoidance conditioning. The
parameters of the stimuli. However, the results of our study contrast with those
findings in this study and in the investiga- reported in the two investigations of neution of AI (Weinberger et al., 1984) indicate ronal plasticity in terms of the incidence of
that nonspecific processes of arousal and plasticity and the time course of such
attention can be separated from associative changes. Kraus and Disterhoft detected sigprocesses for the following reasons. First, nificant changes in background and evoked
recordings were obtained during a sensiti- activity in only 50% of their recordings,
zation as well as a conditioning phase. Dur- and the changes that did occur developed
ing sensitization, the subjects were aroused late in conditioning. Gabriel et al. (1982)
by the EDS, yet there was little evidence of did not find any changes in neuronal activchanges in acoustically evoked activity (see ity related to learning. An assessment of
Figure 3). Second, during the conditioning the anatomical, procedural, and methodophase, evoked plasticity developed at a rate logical differences between the paradigms
that was independent of the rate of pupillary learning, which is a sensitive behavioral index of arousal. Third, previous
3
Kraus and Disterhoft reported using the same
neural recordings in the ventral division of
method
processing neurophysiological data as that
the medial geniculate nucleus indicated used by ofOlds
(1973). They stated that "cells with
that the activity of these cells changes as a similar waveforms were sometimes combined by this
function of the arousal level of the animal technique and were not further discriminated" (p.
(Humphrey & Orman, 1977; Imig, Wein- 206). Therefore, the extent to which their data actually
reflect the discharges of single neurons is unclear.
PLASTICITY OF SINGLE All NEURONS DURING LEARNING
is necessary in order to properly evaluate
the disparity in experimental findings.
The anatomy of the auditory system has
been most thoroughly investigated in the
cat. The feline auditory cortex is comprised
of at least four tonotopically organized subfields surrounding All, which is not tonotopic (Merzenich & Kaas, 1980; Merzenich
et al., 1975; Reale & Imig, 1980). Kraus and
Disterhoft (1982) recorded in an auditory
cortical field they described as "auditory
association cortex." However, it is likely
that this area is homologous to one of the
tonotopically organized fields that have
been described in the cat because their cells
had distinct best frequencies. Recent electrophysiological evidence indicates that the
rabbit contains at least two tonotopically
organized auditory cortical fields (McMullen & Glaser, 1982). The location of
these fields coincides with the recording
sites in the Kraus and Disterhoft study and
supports the view that AH of the cat is not
the homologue of auditory associational
cortex of the rabbit.
Although the two fields are not homologous, there is still the issue of substantial
differences in the time course of the development of neuronal plasticity between the
present study and that of Kraus and Disterhoft. Changes in activity in All developed soon after stimulus pairing began and
tended to stabilize by the 20th conditioning
trial for animals that did not exhibit latent
inhibition. Kraus and Disterhoft found that
plasticity developed about 100 trials after
stimulus pairing began, which was after the
somatic conditioned response appeared.
However, their training sessions did not
include a sensitization phase, which could
serve as a reference for which to compare
changes in activity during conditioning.
Animals were either sensitized or conditioned. They reasoned that because somatic
conditioned responses were not evident
early in the conditioning phase, these trials
could serve as a reference point for learning-related plasticity. However, we have
shown in this study and in the investigation
of AI (Weinberger et al., 1984) that auditory cortex is in a dynamic rather than
static state early in the conditioning phase.
Therefore, even though somatic condi-
205
tioned responses were not evident early in
their conditioning sessions, rapid associative neuronal changes may have still developed but were not detected.
It has been argued that classical defensive conditioning is a two-stage process
(Weinberger, 1982). The initial stage consists of a rapidly conditioned process in
which the conditioned stimulus elicits conditioned arousal or conditioned fear. This
is followed by a slowly acquired process
involving the acquisition of a conditioned
somatic response which is specific to the
nature of the US. The present study and
that of Kraus and Disterhoft (1982) indicate that both stages involve changes in the
discharge characteristics of auditory cortical neurons. However, we detected changes
in neuronal activity involving both background and evoked activity. Kraus and Disterhoft noted that all of their changes involved stimulus-evoked activity whereas
background activity remained relatively
constant. A lack of change in background
activity is also a common finding during
the performance of tasks involving animals
that are highly overtrained (Beaton &
Miller, 1975; Benson & Hienz, 1978; Goldstein, Benson, & Hienz, 1982; Pfingst,
O'Connor, & Miller, 1977). Perhaps the
initial recognition of stimulus contingencies involves a widespread damping of ongoing neuronal activity and an accentuation of the activity of neurons that are
specifically involved in the processing of
salient cues. Once such a process takes
place and contextual cues remain constant,
all further changes may procede on a relatively constant level of background activity.
The elaboration of conditioned somatic responses as well as the performance of
overlearned tasks may involve a fine tuning
of neural processing that is more likely to
be expressed during stimulus-evoked activity than during interstimulus periods of
background activity. Resolution of this issue will have to await studies in which
continuous recordings are maintained from
single neurons throughout the course of
acquisition of conditioned fear and conditioned specific somatic responses.
Gabriel et al. (1982) recorded neural activity in AH of the rabbit during condi-
206
DAVID M. DIAMOND AND NORMAN M. WEINBERGER
tioned avoidance. As noted above, they Sources of Plasticity in Secondary
failed to find learning-related changes. Auditory Cortex
However, owing to the lack of data on the
AH receives input from two auditory recomparative anatomy between the rabbit
gions
that display learning-related changes
and cat, it is not known if their recording
sites were in a cortical field that is homol- in neuronal activity, AI and the magnocelogous to All of the cat. In addition to the lular division of the medial geniculate
issue of homologous recording sites, there (MGm). Of these two regions, the cells in
was a crucial difference in the manner in MGm exhibit a greater probability of plaswhich neuronal activity was recorded and ticity than those in AI. It is possible that
analyzed. In our study, single neurons were the plasticity that develops in All is demonitored during an entire conditioning pendent in part upon the plasticity that
session. Gabriel et al. recorded neural activ- develops in AI or MGm. However, the most
ity which was composed of an indetermi- prominent All afferent is the dorsocaudal
nate number of neurons over the course of division of the medial geniculate (MGdc;
many days. All of the multiple-unit record- Anderson, Knight, & Merzenich, 1980). Alings from different animals were pooled though there are no published studies of
into one cumulative record, which was single-unit recordings in MGdc in behaving
found to be nonplastic. This technique is animals, Calford and Webster (1981) charnot likely to be fruitful when attempting to acterized the activity of cells in this region
detect learning-related changes in neocor- in anesthetized cats. The majority of the
tical activity for a number of reasons. Sin- units were broadly tuned, responded to
gle-unit recordings in many different cor- acoustic stimuli at long latencies (greater
tical fields indicate that most cells have than 40 ms), and habituated rapidly to revery low background firing rates and re- petitive stimulation. These findings suggest
spond transiently to sensory stimuli. A that MGdc may play a role in the processsmall population of cortical cells has high ing of acoustic information with respect to
rates of neuronal activity and respond in a its behavioral relevance. In addition, the
sustained manner to sensory stimulation. long onset latencies recorded in this study
Recall that one of the cells recorded in this may have resulted, in part, from input from
study had firing characteristics that sug- MGdc. The extent to which the plasticity
gested that it belonged within this class of found in All is conferred upon it by MGdc
cells. This was also the only cell that did remains to be investigated.
not develop evoked plasticity during learning. Such activity, if present in multipleunit recordings, would mask the plasticity Comparison of AI and AH
of other types of neurons. Evidence of
Previous analyses of AI and All distinmasking in multiple-unit recordings was
presented in Weinberger et al.'s (1984) ar- guished these cortical fields on the basis of
ticle on primary auditory cortex. Further, cytoarchitectonics (Rose, 1949), thalamothe present study has shown that changes cortical connections (Anderson et al.,
in evoked activity are equally likely to be 1980), and sensory response characteristics
increases and decreases. These differences (Katsuki et al., 1959; Merzenich et al., 1975;
would tend to average to no change in a Phillips & Irvine, 1981). AI is tonotopically
multiple-unit record containing both types organized, with narrowly tuned cells. It is
of data. This very effect has been demon- the major projection site of the primary
strated by multiple-unit recordings (Ryugo lemniscal pathway of the auditory system.
& Weinberger, 1978) and single-unit re- Subcortical nuclei that comprise this pathcordings (Weinberger, 1982) in the mag- way are tonotopically organized, with narnocellular division of the medial geniculate rowly tuned cells. In contrast, All does not
nucleus. Thus, negative findings obtained contain a tonotopic organization and has
from multiple-unit recordings are subject broadly tuned cells. It is the cortical projection field of the so-called "diffuse" or "lemto incorrect conclusions.
niscal-adjunct" auditory pathway entailing
PLASTICITY OF SINGLE All NEURONS DURING LEARNING
subcortical nuclei that are not tonotopically
organized (Aitkin, 1973; Aitkin, Webster,
Veale, & Crosby, 1975; Graybiel, 1972).
Cells in these regions are more broadly
tuned than those in the lemniscal pathway.
By recording neuronal activity in AI and
All during learning, we are attempting to
uncover evidence of general principles governing the functional organization of primary and secondary cortical fields and gain
a greater understanding of the nature of
parallel pathways in sensory systems.
The cells that were recorded in these two
regions were in layers V and VI. Therefore,
this analysis is concerned with the discharge characteristics of neurons that convey information from each field toward
other cortical and subcortical regions (Beyerl, 1978; Imig & Brugge, 1978; Kelly &
Wong, 1981).
Three aspects of differences in neuronal
activity of AI and All are discussed next:
the rate of development of discharge plasticity during the course of the conditioning
phase, the relation between changes in neuronal activity and arousal level, and the
relative incidence of single cells developing
learning-related discharge plasticity.
In both cortical fields, evoked and background neuronal activity changed rapidly
once the acoustic stimulus was paired with
EDS (see Figures 2 and 5 of Weinberger et
al., 1984, and Figure 3 of the present study).
As the changes developed at about the same
rate in both regions, it is unlikely that the
plasticity developed first in one of the fields
which then conferred its plasticity upon the
other field. Further, as the magnocellular
division of the medial geniculate (MGm)
projects to the upper layers of both fields
(Niimi & Naito, 1974; Wilson & Cragg,
1969), and it also develops discharge plasticity early in conditioning (Weinberger,
1982), aspects of the plasticity may have
resulted, in part, from the modulatory influence of MGm in concert with processes
intrinsic to each field.
In terms of the relation between discharge activity and arousal level, one interesting finding was that both fields were
similar with respect to changes in background neuronal activity and the tonic level
of behavioral arousal. In AI and All, in-
207
creases in background activity developed in
subjects that became more tonically
aroused during the conditioning phase than
during sensitization. In addition, the increase in cellular excitability was not expressed as an increase in evoked discharge
rate. In fact, the direction of change of
evoked activity in All was completely unrelated to the tonic level of arousal, that is,
the incidence of increases or decreases in
evoked plasticity was not a correlate of the
behavioral state of the subject. The only
correlation between evoked activity in AI
and arousal level was that cells failed to
develop evoked plasticity when the subjects
were in a state of elevated tonic arousal (see
Figure 6 of Weinberger et al., 1984). In
contrast, cells in All developed evoked
plasticity even when subjects were in an
increased state of arousal during conditioning. Perhaps the information that is processed in this field is qualitatively less specific in nature than that in AI and may be
less susceptible to interference by elevated
states of arousal during learning.
In another analysis of the relation between arousal and discharge activity, cells
in All were more likely to display altered
firing rates following EDS than were cells
in AI (77% in All vs. 32% in AI). EDS
consistently evoked large transient pupillary dilations lasting from 2 to 5 s. The
observation that more cells in All were
responsive to the EDS alone may reflect a
greater involvement of this region with
nonspecific processes governing rapid
changes in arousal level. It is also possible
that the cells were responding to somatosensory input which may reach All via the
posterior nucleus of the thalamus (J. Winer, Diamond, & Raczkowski, 1977). In any
case, the capacity of cells in All to respond
to the US as well as the CS may have
increased the likelihood that discharge
plasticity developed during conditioning.
Related findings were reported by Cohen,
Gibbs, Siegelman, Gamlin, and Broyles in
the lateral geniculate of the pigeon (1982),
Yoshii and Ogura in the reticular formation
(1960), and O'Brien and Fox in motor cortex (1969).
Although there is the potential for a sampling bias, the difference in the incidence
208
DAVID M. DIAMOND AND NORMAN M. WEINBERGER
of cells that developed learning-related tion of change of activity could also be
plasticity in AI and All provides evidence correlated with behavioral measures. Defor a functional distinction. All 22 cells in creases in background activity occurred in
All were plastic in either background or conjunction with the development of pupilevoked activity, and 95% (21/22) were plas- lary conditioned responses. Increases in
tic in both measures. In AI, 79% (15/19) background activity were recorded when
were plastic in either measure, and only subjects became more tonically aroused
42% (8/19) developed changes in both during conditioning. In contrast, CSbackground and evoked activity during evoked plasticity was not correlated with
conditioning. Constraints on the degree of either the rate of pupillary learning or the
discharge plasticity that develops in AI may tonic level of arousal during the conditionresult from the necessity of this region to ing phase. Thus, single-unit activity in secalso perform aspects of an analysis of the ondary auditory cortex reflects components
physical properties of sound. AI may be of behavioral processes, namely, changes in
necessary for such complex processes as arousal level and associative learning.
integrating the acoustic environment into
a coherent framework (see Whitfield,
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Received August 17,1983
Revision received November 29, 1983