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The Journal of Neuroscience, April 1, 1998, 18(7):2613-2625
Neuronal Signals in the Monkey Ventral Striatum Related to
Progress through a Predictable Series of Trials
Munetaka
Shidara1, 2,
Thomas G.
Aigner1, and
Barry J.
Richmond1
1 National Institute of Mental Health, Bethesda,
Maryland 20892, and 2 Neuroscience Section,
Electrotechnical Laboratory, Tsukuba-shi, Ibaraki 305, Japan
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ABSTRACT |
Single neurons in the ventral striatum of primates carry signals
that are related to reward and motivation. When monkeys performed a
task requiring one to three bar release trials to be completed successfully before a reward was given, they seemed more motivated as
the rewarded trials approached; they responded more quickly and
accurately. When the monkeys were cued as to the progress of the
schedule, 89 out of 150 ventral striatal neurons responded in at least
one part of the task: (1) at the onset of the visual cue, (2) near the
time of bar release, and/or (3) near the time of reward delivery. When
the cue signaled progress through the schedule, the neuronal activity
was related to the progress through the schedule. For example, one
large group of these neurons responded in the first trial of every
schedule, another large group responded in trials other than the first
of a schedule, and a third large group responded in the first trial of
schedules longer than one. Thus, these neurons coded the state of the
cue, i.e., the neurons carried the information about how the monkey was
progressing through the task. The differential activity disappeared on
the first trial after randomizing the relation of the cue to the
schedule. Considering the anatomical loop structure that includes
ventral striatum and prefrontal cortex, we suggest that the ventral
striatum might be part of a circuit that supports keeping track of
progress through learned behavioral sequences that, when successfully
completed, lead to reward.
Key words:
ventral striatum; motivation; schedule length; reward; visual cue; information analysis; macaque monkey; neurophysiology
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INTRODUCTION |
The ventral striatum seems to play
an important role in motivation and reward-related behavior (Schultz et
al., 1995 ). It is part of a circuit that includes the anterior
cingulate cortex, globus pallidus, ventral pallidum, substantia nigra,
and mediodorsal nucleus of thalamus (Alexander et al., 1986). It also
receives connections from orbitofrontal cortex (Haber et al., 1996),
parts of the temporal lobe cortex (VanHoesen et al., 1981), and the amygdala (Russchen et al., 1985), which suggest that it could play a
role in planning future behavior and providing emotional content to
it.
Single neurons in the ventral striatum of trained primates carry
signals that are strongly related to reward and motivation. Two types
of neural activity have been reported thus far in trained monkeys, (1)
responses to the delivery of the primary reward (Apicella et al., 1991;
Bowman et al., 1996) and (2) responses that anticipate certain task
events, especially in rewarded trials (Schultz et al., 1992).
Before Bowman et al. (1996), the tasks used to study ventral striatal
neuronal responses had several events but single trials. By contrast,
Bowman et al. (1996) used a task in which the monkey was required to
complete several successful trials before a reward was given. They
reported that approximately one-third of the ventral striatal neurons
showed reward-related neural activity. The monkeys behaved differently
and ventral striatal neurons responded differently during trials in
which a cue indicated there would be a reward relative to those trials
in which the cue indicated there would be no reward. Behaviorally, the
monkeys seemed more motivated in the rewarded trials. Bowman et al.
(1996) concentrated on the reward-related activity of the neurons
during this task. However, they pointed out that some neurons responded
in other phases of the task. To investigate the relations among these
neurons with other events in this task more thoroughly, we compared the
responses when the monkey was cued as to whether or not it would
receive a reward (i.e., cues predicted proximity of reward) with the
responses when the monkey received the same cues but a random
reinforcement schedule (i.e., cues did not predict proximity of
reward). When the cue was meaningful, the neural activity coded the
state of the cue, i.e., the neurons carried the information needed to
know how the monkey was progressing through the task. These effects disappeared immediately (for these very experienced monkeys) when the
meaning of the cue was removed, showing that the effects are the result
of the monkey associating the meaning of the cue with the task. We
suggest that the ventral striatum might be part of a circuit that
supports keeping track of progress through learned behavioral sequences
that, when successfully completed, lead to reward.
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MATERIALS AND METHODS |
Animal preparation. Behavioral and single-unit data
were collected from two young adult (5-9 kg) monkeys (Macaca
mulatta). Both monkeys were initially trained to fixate a small
target spot to obtain a fluid reward (Wurtz, 1969). After this
training, a cylinder for microelectrode recording and a head holder
were fixed to the skull during an aseptic surgical procedure performed
under isoflurane anesthesia. The head holder allowed the head to be fixed in the standard stereotaxic position during the experiments. Scleral magnetic search coils for measuring eye movements were implanted (Robinson, 1963; Judge et al., 1980). Electrophysiological recording sessions generally began a week after surgery.
Behavioral paradigms and visual stimuli. The behavioral
paradigms and visual stimuli used in the present study are similar to
those of Bowman et al. (1996) (Fig. 1).
Visual stimuli were presented on a computer video monitor subtending
10.5° of visual angle in front of the animal. In each trial, a white
cue, which will be described below, was present at the top of the
computer video screen, and a small white fixation spot (0.07°)
appeared in the center of the screen. Then, after the monkey touched
the bar in the chair and fixated the fixation point and after at least 400 msec, a red Wait signal (0.2°) appeared around the fixation point. After a randomly selected Wait time (400, 600, 800, 1000, or
1200 msec), the red Wait signal changed to become the green Go signal,
indicating that the monkey could release the bar to earn a liquid
reward. If the monkey responded within 1 sec, the target turned blue
(OK signal), signaling the monkey that the trial had been completed
correctly. The target then disappeared. If the monkey responded in
<200 msec after the Go signal, we counted this as an anticipatory
error. The target disappeared, and the trial was terminated
immediately. If the monkey did not respond within 1 sec after the onset
of the Go signal, we counted this trial as a late error.
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Figure 1.
The task. A, In each trial, a
fixation target (small white circle) appeared. After the
monkey touched a bar mounted on the chair and after at least 400 msec,
a red target (indicated by a square with
vertical lines), the Wait signal,
appeared. After a randomly chosen delay of between 400 and 1200 msec,
the target became green (indicated by a
square with horizontal lines), the Go signal. If the monkey released the bar within 1 sec,
the target turned blue (indicated by a
square with diagonal lines), the
OK signal, indicating to the monkey that the trial had
been completed correctly. Then the target disappeared.
B, The complete task was composed of one to three simple
bar release trials. In each trial, a white cue, the
schedule fraction cue, was present at the top of the
monitor. The monkey had to complete one, two, or three trials correctly to earn a reward. The schedules were randomly interleaved. The brightness of the cue was proportional
to the schedule fraction (see Materials and Methods). The schedule
fraction was the measure that indicated the progress toward the
rewarded trial. For example, if the required number of trials to
receive the reward was three, the schedule fraction could be 1/3, 2/3, and finally 3/3, which was the rewarded trial and had the
brightest cue (brightening paradigm). We also randomized
the cue sequence so that the cue lost its meaning (random
paradigm).
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Initially, each correct trial was rewarded by delivering a drop of
juice at a randomly chosen time beginning 250-350 msec after the
target turned blue. When the monkeys completed >80% of the trials
correctly, a cued multiple-ratio reinforcement schedule was introduced.
The monkeys were required to complete randomly interleaved ratio
schedules of one, two, or three correct trials to obtain a reward. The
brightness of the rectangular cue (10.5 × 0.26°) at the top of
the screen varied from black to white in direct proportion to the
schedule fraction. The schedule fraction, schedule fraction = (trial number)/(schedule length), quantified the progress toward the
rewarded trial, that is, 1/3, 2/3, 3/3, 1/2, 2/2, and 1/1. The
brightness of the schedule fraction cue was changed at the onset of the
intertrial interval so that the monkeys could interpret the meaning of
the cue before responding to the target in the forthcoming trial. We
call this the brightening paradigm, because the brightness of the cue
increased along with the progress of the schedule. The luminance of the
brightest cue and black level were 9.8 and 0.8 cd/m2, respectively, when using a 19 inch monitor,
and 65 and 0.05 cd/m2, respectively, when using a 14 inch monitor.
The monkeys had to complete each schedule before beginning a new one,
no matter how many errors they made. On correct trials in which no
reward was delivered, the reward apparatus was activated with the
delivery valve turned off (sham reward) so that the auditory stimulation was the same as in the rewarded trials.
In the session for each day, after recording the single-unit activity
in a block of trials with the trial sequence tied to the cue brightness
and if the neuron was still electrically well-isolated, the neural
activity was recorded in a block of trials in which the cue brightness
was not related to the trial sequence (randomized). The monkeys behaved
differently in the two blocks (Bowman et al., 1996; see Results).
In these behavioral tasks, the items that changed across trials are the
schedule fraction cue and whether a reward is delivered. All of the
other sensory conditions and all of the motor conditions are the same
in every trial. Using this design, we can study how the schedule
fraction cue is associated with the neural responses.
Recording technique. Single units were recorded while the
monkeys performed the task. A hydraulic microdrive was mounted on the
recording cylinder, and tungsten microelectrodes with an impedance of
0.8-1.3 M (MicroProbe, Clarksburg, MD) were used through a stainless steel guide tube. Experimental control and data collection were performed by a Hewlett-Packard Vectra 486/33, using a real-time data acquisition program (Hayes et al., 1982) adapted for the QNX
operating system. Single units were discriminated according to spike
shape and amplitude by calculating principal components using an IBM
personal computer-compatible microcomputer (Abeles and Goldstein, 1977;
Gawne and Richmond, 1993).
All of the experimental procedures described here were approved by the
Animal Care and Use Committee of the National Institute of Mental
Health and were in accordance with the National Institutes of
Health Guide for the Care and Use of Laboratory Animals.
Statistical analysis. The mean reaction time (onset of Go
signal to bar release) and correct rates were calculated for each combination of the schedule fraction and the cue brightness in the
brightening and random paradigms. The single-unit activity was
displayed as raster plots and spike density functions (Richmond and
Optican, 1987). A spike density function, which is an estimate of spike
probability over time, was constructed for each individual response by
replacing each spike with a Gaussian pulse,  = 5 msec (convolving
the spike train with a Gaussian pulse). These were averaged at each
millisecond.
To quantify the neural responses, we measured the firing frequencies
during selected time periods. To select the time period for the phasic
response, we found the schedule fraction with the peak average response
in the brightening paradigm (Fig. 2). We then looked for the minimum firing frequency in the period between 200 msec before the appearance of the cue and the peak and in the period
between the peak and 1000 msec after the appearance of the cue. This
defined the time period over which to quantify the neuronal activity
(Fig. 2). Then we compared the firing frequency between the phasic
responses and the spontaneous firing frequency that was measured during
200 msec before the onset of the cue. For many neurons, we also
measured the firing frequency in the random paradigm and compared
it with the firing frequency in the schedule fraction that had the same
cue brightness in the brightening paradigm. For the bar release-related
neurons, the search ranged between 200 msec before and 500 msec after
the bar release, and for the reward-related neurons, the search ranged
between 200 msec before and 750 msec after the activation of the reward
apparatus.
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Figure 2.
Identification of phasic response. In these plots,
the average spike densities are aligned at the time of the cue onset.
The schedule fraction is shown at the top. The phasic
response was identified automatically by finding the peak average
firing across all of the schedule fractions, shown here by a
solid vertical line in the panel
representing the response in the 2/2 schedule. The beginning was
defined as the minimum between 200 msec before the cue onset and the
peak for this response, and the end of the responses was defined as the
minimum between the peak and 1000 msec after the peak. These are shown
by the dashed vertical lines in the panel
labeled 2/2. This time period was then applied to the responses in all
of the schedule fractions (dashed vertical lines). The
asterisk indicates that the peak response occurred for
the indicated schedule, here 2/2. The same algorithm was used for bar
release-related neurons and reward-related neurons, with the search
periods being 200 msec before to 500 msec after bar release and 200 msec before to 750 msec after reward delivery, respectively.
Ordinate: sp/s, spikes per second.
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For bar release-related neurons, the response did not disappear even in
the random paradigm (see Results). Therefore, we quantified the
modulation strength by first averaging the responses across all
schedule fractions and then calculating the ratio of the response in
each cue condition to this average, i.e.:
where Mj is the relative activity
measure for schedule fraction j,
Aj is the activity for schedule fraction
j, and the summation is over all of the schedule fractions,
i = 1 ... 6.
Information analysis. We wished to determine whether the
neuronal responses could be decoded to identify the experimental conditions. In the past we have used an information theoretical analysis to make similar assessments (Kjaer et al., 1994; Bowman et
al., 1996). In this approach, each neuron is considered as a
transmission channel carrying information about the experimental conditions via their event-related responses in the task. Transmitted information quantifies the discriminability of the experimental conditions based on the responses. This discriminability is in turn a
function of the means and variabilities of the responses across
different experimental conditions. Intuitively, the less the
distributions of the responses elicited by different experimental conditions overlap, the greater the transmitted information. The amount
of information regarding the condition is the entropy:
The transmitted information is the entropy before receiving a
message, H(C), minus the residual entropy
(or uncertainty) after receiving a message,
H(C|R), that is, the conditional
entropy or the entropy given the response. This can be rewritten
as:
where I(C;R) is the
information transmitted about the conditions c given in the
responses R. C is the average over each
condition, and c is the condition related to response
r. P(c|r) is the
probability of c given r, i.e., the conditional
probability of the condition being selected on the basis of the
response. P(c) is the a priori probability of the
condition, which is known in the experiment. P(c|r)log2[P(c|r)/P(c)]
is the expected or average information about condition c
over all of the responses r. Obtaining an accurate estimate
of the transmitted information,
I(C;R), requires an accurate estimate of P(c|r). We have done
this using a neural network to perform a nominal regression of the
experimental condition on the neural response. The analysis performed
by the neural network is similar to logistic regression (Kjaer et al.,
1994). Here, the spike count was used as the response representation.
The spike counts from one or more neurons were used as inputs to the
neural network, and the conditions of the six task states were used as target outputs in the analyses, in which for each trial one schedule fraction was set to one and the others were zero. Getting an unbiased value for P(c|r) when the data set
has a limited number of responses r for each condition
c can be problematical. Recent work shows that the neural
network method accurately estimates the conditional probabilities
(Golomb et al., 1997).
In the extreme, if the network could perfectly categorize each schedule
fraction using the neuronal response, i.e., if there were no noise and
all responses were distinct, the amount of information transmitted in
the spike train would be equal to the amount required to encode the
experimental conditions. Estimates of transmitted information always
depend on the stimulus set and the response representation and cannot
be taken to be absolute. However, for the conditions under study at any
time, transmitted information provides a quantitative assessment of the
use of a response for estimating the experimental condition. The amount
of transmitted information is usually expressed in bits. Because there
were almost equal numbers of trials, the maximum amount of information
that could have been transmitted about the task state (1/3, 2/3, 3/3, 1/2, 2/2, and 3/3), that is, the entropy, is log2 6 or 2.58 bits. The spike count was used as the neuronal code r.
Histology. During the last few recording sessions with the
first monkey, small electrolytic lesions were made at a few recording sites by passing 5 µA of current for 30 sec. At the end of the experiments, this monkey was given a lethal dose of pentobarbital (75 mg/kg) and was transcardially perfused with saline followed by 10%
formalin. Fifty micrometer frozen sections were cut, mounted on
microscope slides, and stained for histology. Comparing the recording
tracks, penetration records, and electrolytic marking lesions confirmed
that all of the units described in this paper were located in the
ventral striatum. Figure 3 shows guide
tube tracks at the top of all three sections, indicating
that guide tubes were placed at those locations. The middle
section shows a small electrolytic marking lesion at a location where
responsive units were recorded during the task.
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Figure 3.
Histological sections from one monkey that
showed the recording area in the ventral striatum. Frontal sections at
A23, A20, and A18 from top to bottom,
which span the recording area along the rostrocaudal direction, are
shown. The thick line in the A20 photograph indicates
the approximate area where we recorded single-unit responses. The
inset shows a magnified view of an electrolytic lesion
marking a recording site in the outlined area of the A20 histological section. A, anterior.
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We used magnetic resonance (MR) imaging to confirm that our recordings
were taken from the same region in the other monkey (Saunders et
al., 1990). The MR sections from the second monkey were matched to the
histological sections from the first monkey. The depths of recording
sites were calculated from the lengths of the guide tubes and
electrodes. The recording depths were confirmed further by calculating
backward from the depth at which the electrode struck the dura at the
bottom of some penetrations. The sampling of neurons in both monkeys
was approximately uniform across the anterior-posterior range
represented by the sections in Figure 3.
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RESULTS |
Behavioral results
As reported previously (Bowman et al., 1996), the mean reaction
time to bar release decreased as the brightness of the cue approached
the level that signaled a forthcoming reward in the brightening
paradigm (Fig. 4A),
suggesting that the monkeys were more motivated. When we randomized the
schedule fraction cue (random paradigm) with respect to the reward, the
reaction time was short and relatively constant in all trials (Fig.
4A). It has long been known that when animals perform
tasks using variable-ratio reward schedules, the rate of responding
becomes nearly constant (Mackintosh, 1983). Thus, the results we see
here in the random paradigm suggest that the monkey treats the random
paradigm as a task with a variable-ratio reward schedule.
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Figure 4.
Relation between mean reaction time and schedule
fractions. A, Mean reaction times in brightening
(circle) and random (square) paradigms
sorted by the schedule fraction. B, Mean reaction times in brightening (circle) and random
(square) paradigms sorted by the brightness of the
schedule fraction cue. Error bars indicating SEs are smaller than are
the squares and circles used to mark data points.
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When the data are sorted by the cue brightness rather than by the
schedule fraction in the random paradigm, we see that the monkeys
responded a little faster when the cue was brighter. This effect is
significantly smaller (p < 0.01; t
test) than the effect of the cue when it is meaningful (Fig.
4B).
The percentage of correct trials increased as the monkey progressed
through the schedule toward the rewarded trial in the brightening
paradigm (Fig. 5A). In the
random paradigm, the percentage of correct trials was high and
relatively constant in all trials (Fig. 5A). Although there
seems to be a slight trend toward better performance when the cue was
brighter, the effect does not reach significance (Fig.
5B).
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Figure 5.
Relation between correct rate and schedule
fractions. A, Correct rate in brightening
(circle) and random (square) paradigms sorted by the schedule fraction. B, Correct rate in
brightening (circle) and random (square)
paradigms sorted by the brightness of the schedule fraction cue.
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These changes in reaction time and percentage correct behavioral
responses across paradigms indicate that the schedule fraction cue has
meaning for the monkeys in the brightening paradigm. Thus, the results
might be interpreted as an indication of the level of effort or
motivation of the monkeys.
Neural response
We recorded from 150 neurons in the ventral striatum of two
monkeys. There were 89 neurons that responded to one or more phases of
this task. Some neurons responded to the appearance of the schedule
fraction cue, some responded to the bar release or Go signal, and
others responded to the OK signal or reward dispensing (Fig.
6). There were some neurons that showed
phasic responses in relation to more than one task event.
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Figure 6.
Distribution of the neurons that responded in
three task phases shown in Venn diagram. Eighty-nine out of 150 neurons
were responsive to one or more of the three task phases, which are the
onset of the schedule fraction cue, the time of bar release, and reward
dispensing.
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Figure 7 shows the neural responses of
one neuron that responded to all three task phases. Although we only
found two neurons responding in all three phases, the responses are
typical for the response seen at each phase, i.e., cue-related, bar
release-related, and reward-related. On the time scale used here, all
of the response types had clear phasic components. The cue-related
responses, seen in this example for the 2/3, 3/3, and 2/2 schedule
fractions, ended before any other event, including the appearance of
the red Wait signal (Fig. 7A). The bar release-related
responses began just before bar release occurred, as seen in this
example (Fig. 7B), or otherwise started after bar release
(see below). The reward-related responses also frequently started
before the reward was delivered, as shown here (Fig. 7C).
Both the bar release- and reward-related responses were clearly largest
in the 3/3, 2/2, and 1/1 conditions for this neuron, i.e., in trials
when a reward was forthcoming. There was also some response to bar
release in the other conditions, a frequently seen result (see
below).
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Figure 7.
Rasters and spike density plots of the activity of
one neuron that showed cue-related, bar release-related, and
reward-related responses. Although only two neurons responding to all
three task events were encountered, the responses illustrated here in
relation to these events are typical of the types of phasic responses
that were observed across the population of responsive neurons.
A-C, Each section contains two rows,
with the upper showing raster dot diagrams indicating
the times of action potentials in all trials and the
lower showing spike density diagrams averaged from the
spike density plots made for each trial. The gray area
around each spike density represents the SEM at that time.
A, Data aligned at the time of cue onset. There are
significant phasic responses just after the cue appears in the 2/3,
3/3, and 2/2 schedule fractions. B, The same data shown
in A but now aligned at the time of bar release. There
are significant responses in all schedule fractions, but the responses
are much larger in the schedules in which a reward is forthcoming, 3/3,
2/2, and 1/1. C, The same data shown in A
and B but now aligned at the time of reward delivery.
There are significant responses in the 3/3, 2/2, and 1/1 schedule
fractions. Both the bar release-related and the reward-related
responses begin before the task event.
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Cue-related neurons
Forty-seven out of the 150 neurons showed phasic responses when
the schedule fraction cue appeared in some schedule fractions and not
in others. A phasic response was considered significant when the mean
response in the time period selected, as described in Materials and
Methods and shown in Figure 2, was different from the background
activity taken from the intertrial interval (p < 0.05; t test). The phasic response related to the cue
lasted <1 sec, averaging 927 ± 30 msec (± SE; n = 44). This phasic component always ended before the bar release
occurred. The neuron shown in Figure
8A responded to the
appearance of the cue when the schedule fraction was 2/3, 3/3, and 2/2
in the brightening paradigm. Thus, this neuron responded in trials
other than the first one in a schedule and failed to respond when the
cue appeared in the random paradigm (Fig. 8B).
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Figure 8.
Rasters and spike density plots of the activity of
one neuron that responded to the appearance of the schedule fraction
cue. A, B, Vertical lines
(y-axis) indicate the onset of the appearance of
the cue. Upper rows indicate the rasters, and
lower rows indicate the spike density plots. The
responses are aligned to the onset of the cue. A,
Neuronal response in brightening paradigm sorted by the schedule
fraction. The neuron responded in 2/3, 3/3, and 2/2 conditions.
B, The responses of the same neuron in random paradigm
sorted by the cue brightness. The plots compare the schedule fraction
with the corresponding brightness in the brightening paradigm
(connected by the heavy arrows). The neuronal responses, which had been large in the 2/3, 3/3, and 2/2 conditions of the brightening paradigm, disappeared at the corresponding cue brightness in the random paradigm.
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The responses illustrated in Figure 8A ended rather
abruptly, raising the question of whether the responses ended in
relation to one of the other task events, especially the appearance of the red Wait signal. For 36 out of 47 cue-related neurons, the response
ended before the onset of the Wait signal (average time from cue onset
to Wait signal was 1270 msec). Of the remaining 10 neurons, four had
responses that returned to the spontaneous firing level within 200 msec
after the Wait signal, and six had responses that gradually declined,
lasting >300 msec before returning to the spontaneous firing level.
Thus, most of the cue-related neurons had phasic responses that ended
before other task events occurred.
The cue-related neurons fell into five main groups (Table
1) of neurons that responded (1) in the
middle of or at the end of the multiple trial schedules
(n = 16) (Fig.
9A); (2) in the first trials
of all schedules (n = 13) (Fig. 9B); (3) in
only the first trials of multiple trial schedules (n = 6) (Fig. 9C); (4) in all of the rewarded trials
(n = 3); and (5) only in the last trial of the multiple
trial schedules (n = 3). Two neurons responded in all
schedule fractions except 1/1; one neuron responded in 1/3, 1/2, 2/3,
and 3/3; one neuron responded in 1/3, 2/3, and 3/3; one neuron
responded in 1/3 and 2/3; and one neuron responded only in 2/2.
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Figure 9.
Spike density plots of the activity of three
neurons that responded to the appearance of the schedule fraction cue.
A-C, Vertical lines
(y-axis) indicate the onset of the appearance of
the cue. 1, Plots that indicate the neuronal responses
in the brightening paradigm sorted by the schedule fraction.
2, Plots that indicate the neuronal responses in the
random paradigm sorted by the cue brightness. A, An
example of a neuron from group 1 that responded in 2/3, 3/3, and 2/2 in
the brightening paradigm. B, An example of a neuron from
group 2 that responded in 1/3, 1/2, and 1/1 in the brightening
paradigm. C, An example of a neuron from group 3 that
responded in 1/3 and 1/2 in the brightening paradigm.
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For 23 of the cue-related neurons, we also recorded while the monkey
performed in the random paradigm, i.e., when the cue had no predictive
value. During the random paradigm, none of these neurons showed
activity that was significantly different (Kruskall-Wallis, p = 0.07) than the background activity during the 200 msec before the trial onset. Thus, the responses that were seen in the
brightening paradigm disappeared in the random paradigm, showing the
associative nature of the relation between the cue and the neural
response.
We identified significant responses during the brightening paradigm by
comparing the responses to the background activity during the
brightening paradigm. However, as described above, the phasic
cue-related responses seen in the brightening paradigm disappeared,
even at the same cue brightness in the random paradigm. We calculated
how much larger the phasic responses were by forming a ratio:
(significant response in the brightening paradigm)/(response to the cue
of same brightness in the random paradigm). The ratios for the 1/3,
1/2, 2/3, 3/3, 2/2, and 1/1 cues were 2.0 ± 0.39 (mean ± SE; n = 11), 1.8 ± 0.28 (n = 11),
3.5 ± 1.1 (n = 8), 3.1 ± 0.76 (n = 13), 3.7 ± 1.0 (n = 13), and
1.6 ± 0.37 (n = 9), respectively. These ratios
show that the cue-related phasic responses were especially large during
the 2/3, 3/3, and 2/2 schedule fractions in the brightening paradigm,
showing that the responses are largest after the first trial of a
schedule.
Neurons responding at the time of bar release
There were 41 neurons that showed phasic responses at the time of
bar release or the Go signal. Figure 10
shows the neural responses of one of these neurons, aligned at the time
of bar release. This neuron responded in all of the schedule fractions, and the response onset preceded the onset of the bar release. The
response was largest in the first trial of multiple trial schedules,
i.e., 1/3 and 1/2 (Fig. 10A). When we randomized the cue sequence, these large responses decreased (Fig.
10B) but did not disappear. The overall activity also
fell for this neuron in the random paradigm.
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Figure 10.
Rasters and spike density plots of the activity
of the neuron that responded at the time of bar release in the
brightening paradigm. This neuron also responded at the time of the
activation of the reward apparatus, which corresponds to the second
rise of spike density in the plots (see Fig. 11). A,
B, Vertical lines (y-axis) indicate the time of bar release.
A, Neuronal responses in the brightening paradigm sorted
by the schedule fraction. The large responses occurred in the 1/3 and
1/2 conditions. B, Neuronal responses in the random
paradigm sorted by the cue brightness. In the random paradigm, all of
the responses became smaller and the differences in the responses
across brightnesses disappeared.
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There were also five main response groups for these neurons. However,
two of them were different than those seen for the cue-related neurons
(Table 2 vs Table 1). The differences are
that there were no neurons for the previous groups 2 and 5; two new
groups, one containing neurons that showed large responses in all of
the nonrewarded trials (1/3, 1/2, and 2/3) and another containing neurons that showed large responses in all of the trials, were found;
and the largest group, group 4, which contained neurons that showed
large responses in all of the rewarded trials, was 15 of 41 neurons.
Figure 7B shows an example from a group 4 neuron.
Unlike the cue-related neurons, the bar release-related neurons showed
activity in both the brightening and random paradigms. The difference
in activity between the brightening and random paradigms was that the
activity in the brightening paradigm was larger in some schedule
fractions and smaller in others, whereas the activity in the random
paradigm was almost the same for all cue brightnesses. To quantify the
differential activity seen in the brightening paradigm, we formed a
relative measure: (activity in one schedule fraction)/(average activity
across all schedule fractions). This measure gives the activity
relative to the mean across all conditions (see Materials and Methods).
When the activity went up, the ratios were 1.14 ± 0.06 (mean ± SE; n = 21), 1.15 ± 0.08 (n = 21), 1.20 ± 0.06 (n = 22), 1.17 ± 0.04 (n = 28), 1.10 ± 0.04 (n = 28),
and 1.20 ± 0.07 (n = 25) for 1/3, 1/2, 2/3, 3/3, 2/2, and 1/1 conditions, respectively. When the activity went down, the
ratios were 0.76 ± 0.07 (n = 17), 0.79 ± 0.06 (n = 17), 0.80 ± 0.05 (n = 16), 0.64 ± 0.06 (n = 10), 0.59 ± 0.06 (n = 10), and 0.69 ± 0.06 (n = 13), for the same schedule fractions, respectively. For the random
paradigm, these same ratios were 0.95 ± 0.03 (n = 19), 1.04 ± 0.04 (n = 19), 1.02 ± 0.02 (n = 19), and 0.97 ± 0.05 (n = 19) for the 1/3, 1/2, 2/3, and 1/1 cue brightnesses, respectively.
Thus, in the brightening paradigm, the responses were substantially
different from the expected value, whereas in the random paradigm, the
ratios were basically equal to 1, showing that there was no
modulation.
Neurons responding at the time of activation of the
reward apparatus
There were 24 neurons that responded at the time of activation of
the reward apparatus. Figure
11A shows one of the
neural responses of these neurons in the brightening paradigm. The
response is aligned to the onset of the activation of the reward
apparatus. This neuron showed large neural responses at the time the
reward was dispensed in the rewarded trials, 3/3, 2/2, and 1/1; the
response preceded the onset of activation of the reward apparatus. In
the random paradigm, the responses increased in the nonrewarded trials, indicating that these neurons were closely related to the behavior of
the monkey; they responded as if a reward was expected on every trial
(Fig. 11B).
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Figure 11.
Rasters and spike density plots of the activity
of a neuron responding at the time of reward apparatus activation.
A, B, Vertical lines
(y-axis) indicate the onsets of activation of the
reward apparatus. A, Neuronal responses in the
brightening paradigm sorted by the schedule fraction. The neuron
responded significantly more strongly in 3/3, 2/2, and 1/1 conditions.
B, Neuronal responses in the random paradigm sorted by
the cue brightness. The neuronal responses to the brightest cue
condition was now no bigger than the response to the other cue
brightnesses.
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For 15 neurons, the response preceded the onset of activation of the
reward apparatus. For nine neurons, the response began at the time of
or after activation of the reward apparatus.
The response types are summarized in Table
3 using the same group classification
given in Tables 1 and 2. Fourteen out of the 24 neurons responded in
the rewarded trial, group 4. There were no neurons responding for
groups 1, 2, 3, and 5. One neuron responded in all schedule fractions
except 1/1, and one neuron responded in 1/2 and 2/3. These
reward-related neurons responding at the time of activation of the
reward apparatus are probably similar to those reported by others
(Apicella et al., 1991; Schultz et al., 1992; Bowman et al., 1996).
On average, the reward-related responses that showed a significant
increase were 1.6 ± 0.07 (mean ± SE; n = 8), 1.6 ± 0.42 (n = 8), 1.6 ± 0.36 (n = 8), 2.5 ± 0.61 (n = 18),
2.6 ± 0.59 (n = 18), and 2.5 ± 0.48 (n = 18) times larger than the responses in the random
condition for the 1/3, 1/2, 2/3, 3/3, 2/2, and 1/1 schedule fractions,
respectively. Here, the responses were greatest in the trials when a
reward was forthcoming, as compared with the cue-related responses,
which tended to be largest in any trial except the first in a
series.
The relation between change in reaction time and
neural response
The differences between the results in the brightening and random
paradigms show that the relation of the response to the cue is
associatively formed. We investigated how quickly the association is
gated.
When the behavioral paradigm changed, the monkeys had no explicit cues.
Thus, the monkeys would work until they discovered that the cue was no
longer related to the schedule. By the time we began the unit
recording, the monkeys had many weeks of experience with the task
change, and they almost never made more than the one unavoidable
error.
We compared how quickly the behavior and neural activity changed after
the shift from the brightening to the random paradigms. For the
behavior, we compared the reaction times in the last trial of the
brightening paradigm in the 1/3 condition, the condition in which the
monkey had the longest reaction time, with the second trial in the
random paradigm. This test tends to underestimate the difference
slightly because, occasionally, when the brightest cue appears with a
reward by chance in the first trial after the switch to the random
paradigm, this first trial in the random condition still seems to be
valid. The reaction times before the switch (median, 413 msec) were
significantly longer than were the latter ones (median, 343 msec)
(Wilcoxon signed-rank test; p < 0.01). For the neural
activity, the spike counts during 800 msec from the onset of the cue in
the last trial of the brightening paradigm in the neurons that were
responsive to the task states (median, six spikes) were significantly
larger than were those in the second trial of the random paradigm
(median, two spikes) (Wilcoxon signed-rank test; p < 0.05). These results show that the change in neuronal responses
paralleled the change in the behavioral state. We cannot conclude that
these neuronal responses at the onset of the cue directly drive the
motor activity. It seems more likely that these signals influence
subsequent processing that is closer to the motor output.
The information of the responses of cue-related neurons about the
schedule fraction
It is clear that the cue-related neurons encode information about
the schedule. We wanted to know whether the monkey could unambiguously
determine what the schedule fraction is by using only these neurons. To
study this issue, we performed an information theoretical analysis. The
states 3/3, 2/2, and 1/1 all correspond to the schedule fraction of 1. However, we treat them independently because there were cue-related
neurons that responded in only some of these three states. We
calculated the information about all six task states (1/3, 1/2, 2/3,
3/3, 2/2, and 1/1) using the spike count during the 100-800 msec epoch
after the onset of the cue as the response code. The information was
0.267 ± 0.183 bits (mean ± SD; n = 47)
(Fig. 12). This calculation is for the
current state, regardless of its predictability given previous states, i.e., given the response without its history.
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Figure 12.
Distribution of information about six task states
transmitted in the cue-related neuronal responses. The spike count
during the 100-800 msec epoch after the onset of the cue was used as the response code. The mean information was 0.267 ± 0.183 bits (± SD).
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In information theory, information from independent channels adds.
Because there are six task states, the a priori uncertainty is 2.58 bits (see Materials and Methods). Therefore only 10 independent neurons
(10 × 0.267 bits) would be required to differentiate among the
six task states. However, from inspection, it is not clear how
independent these groups of cue-related neurons are. Therefore, we also
calculated the information using the spike count of one or two neuron
in each group (total, 5 or 10 neurons) taken together, even though they
were not recorded at the same time. When we chose the neurons carrying
the largest amount of information in each group, the information
carried by the five neurons was 1.21 ± 0.20 bits, somewhat less
than the 1.34 bits that would be found if these were completely
independent. When we chose the neurons carrying the smallest amount of
information in each group, the information carried by the five neurons
was 0.62 ± 0.09 bits. When we chose the two neurons with the
largest and second largest amount of information in each group (total,
10 neurons), the information carried by the 10 neurons was 1.35 ± 0.33 bits. Thus, using more neurons from each of the groups does not
help much. Because adding more neurons from each group does not
increase the transmitted information substantially, the result of this
information theoretical analysis indicates that the neurons we assigned
to the groups via inspection are very similar in their information
processing, thus supporting our categorization. Although the
information calculation showed that this discrimination among the
states could be done with as few as 10 independent neurons, the neurons
we have recorded, when considered together, do not seem to reach the
level of signal independence needed to reach the a priori uncertainty
of 2.58 bits. It is possible that neurons in as yet undiscovered other classes or in other brain areas are used to solve this problem.
| |
DISCUSSION |
The new finding reported here is that a majority of the neurons in
the monkey ventral striatum respond to different parts of a task in
which one or more scheduled trials must be completed before a reward is
delivered. The neurons carry signals that show which schedule is in
effect and where the current trial is in the schedule. A large
proportion of the neurons respond in schedules requiring more than one
trial. Each neuron can also be placed in one or more of three
categories: (1) neurons that respond at the onset of the cue, (2)
neurons that respond near the time of bar release, and (3) neurons that
respond near the time that the reward is dispensed. These are similar
to categories seen by others in ventral and dorsal striatum (Hikosaka
et al., 1989; Apicella et al., 1991; Schultz et al., 1992). Here we
concentrate on the effects related to the number of scheduled
trials.
Relation to other studies
The reward-related neurons are easiest to compare to other
studies. In our study, the majority of reward-related neurons responded in every rewarded trial (compare Table 3). A smaller but significant number of reward-related neurons responded in correct, but
nonjuice-rewarded, trials. Some neurons responded in every successfully
completed trial whether or not a reward was delivered. These three
groups are similar to reward-related neurons seen by others in dorsal and ventral striatum (Hikosaka et al., 1989; Apicella et al., 1991;
Schultz et al., 1992; Bowman et al., 1996).
It is more difficult to compare the other two categories, bar
release-related and cue-related neurons, to other studies. The striking
aspect of the results here is the relation to schedule. Some neurons
responded in schedules having only one trial. These can be interpreted
as predicting the reward and seem most similar to the neurons reported
in other studies. Many neurons responded in schedules with more than
one trial. Presumably neurons such as these would not have been
activated in previous studies using single-trial schedules. The higher
percentage of responsive neurons seen in the population here [>50%
vs ~30% for Hikosaka et al. (1989) in dorsal striatum and 7% for
Apicella et al. (1991) and 14% for Schultz et al. (1992) in ventral
striatum] seems to be related to the schedule cuing used here.
Ventral and dorsal striatal neurons respond when predictable events
will occur in the future (Hikosaka et al., 1989; Schultz et al., 1992,
1995). These neurons only respond when the reward is predictable; the
same was true here. Thus, all of these researchers conclude that these
neurons carry predictive signals. Here, we extend the idea about
predictive signals. In our task, a large number of neurons were
recruited by longer schedules (length more than one). Thus, these
neurons show specific activity about the parts of the schedule, not
about the reward itself.
Relation to scheduling
The cue-related neurons are not directly related to reward
expectation. If we assume the response types are related only to the
reward expectation, the responses should occur in the trials in which
the reward is forthcoming (fourth line in Table 1 or the fourth and
seventh lines in Tables 2, 3). However, these cue-related neurons code
the meaning of the cue more finely. The largest group responds in
trials other than the first of a schedule-a "keep going" signal
(compare Table 1, group 1). The second most common category responds in
the first trial of all of the schedules (compare Table 1, group 2), and
the third most common category responds in the first trial of schedules
longer than one (compare Table 1, group 3). Thus, they robustly code
for situations in which the schedule must continue for more than one
trial, thus not directly predicting reward.
What can the animal know using these cue-related neurons? The amount of
information available about the cue from the best two neurons in each
category was only approximately one-half (1.35 bits) of the amount
needed (2.58 bits) to decode unambiguously the meaning of the cue. If,
instead, we consider the task as start, continue, and reward,
examination of Table 1 shows that these neurons can solve the problem
completely.
Clearly, the cue-related neurons can provide effective signals about
progress through a schedule. It would take only a small generalization
for these neurons to signal progress through any sequence of epochs in
which intermediate goals and rewards can be identified. In addition,
the ventral striatal neurons may also be viewed as encoding
motivational and emotional states associated with the cues, a
possibility that is not incompatible with the first. Both possibilities
are consistent with our findings in the brightening versus random
paradigms. The activities of the cue-related neurons disappeared in the
random paradigm, showing that their responses arise from associative
learning of the meaning of the cue. Also, when we compared the change
in reaction time to bar release with the neural responses of
cue-related neurons from the brightening and random paradigms, the
change in neuronal responses paralleled the change in behavioral
responses. Although this could be considered as a code for the motor
command, it seems more likely that these neurons are in the circuit
that codes the meaning of the schedule fraction cue and provides the
information about the progress of the schedule for neurons that are
related to motivation and motor output.
Brown and Bowman (1995) and Bowman and Brown (1996) have conducted
ablation experiments in rats using similar tasks. In one study, they
cued the animal about the size of the reward (Brown and Bowman, 1995).
Normal animals had shorter reaction times when the cue indicated a
bigger reward. Bilateral ablations of the nucleus accumbens did not
affect reaction-time performance or learning in this task. In a
preliminary report of a subsequent study, they showed that normal
animals stopped lever pressing late in a testing session in a
progressive-ratio schedule. Animals with bilateral nucleus accumbens
lesions continued to respond far longer than did control animals
(Bowman and Brown, 1996). This latter result shows that the normal
animals must have an internal signal in the ventral striatum that codes
the schedule length and affects the motivation of the animal. The
cue-related neurons in the ventral striatum could carry the needed
signal and are part of a neural circuit that is related to
motivation.
Relation to behavioral response
Some neurons responded near the time of the bar release movement,
the most frequently found ones being those responding at approximately
the time of the bar release movement in rewarded trials and the next
most frequently found ones being those responding at approximately the
time of bar release in all trials. These are similar to the neurons
reported by Hikosaka et al. (1989) in the dorsal striatum and Schultz
et al. (1992) in the ventral striatum. A significant number also
responded in all nonrewarded trials or in any but the first trial when
the schedule was longer than one. These neurons do not carry a simple
motor or premotor signal because the response became significantly
smaller when the brightness of the cue was randomized with respect to
the schedule.
Models of ventral striatal function
The finding that many cue-related and bar-related neurons
differentiate among the states in the brightening paradigm is quite striking. How does this relate to the role of the striatum in behavior?
The ventral striatum is thought to be within a processing loop that
includes the anterior cingulate cortex, the internal segment of the
globus pallidus, the ventral pallidum, rostrodorsal substantia nigra,
and posterior medial portions of the medial dorsal nucleus of the
thalamus (Alexander et al., 1986). The orbital prefrontal cortex, the
amygdala, and other parts of the medial temporal lobe also project to
the ventral striatum (VanHoesen et al., 1981; Russchen et al.,
1985; Haber et al., 1995). Thus, the ventral striatum is well-placed to
take part in planning and maintaining behavior in response to
emotionally significant stimuli. By having signals that keep track of
progress through sequences of behavior, the ventral striatum seems to
have signals useful for measuring progress through a previously set
plan. The results presented here show that the population of ventral
striatal neurons keep an internal model by coding the place in the
schedule for long sequences of behavior that ultimately lead to
reward.
Using behavioral data, Everitt et al. (1991) and Everitt and Robbins
(1992) concluded that the ventral striatum is important for linking
cues with their reinforcement value. The cue-related neurons seem to be
involved in a stage that is before the translation of a motivational
signal and related only to keeping track of the sequence. The
behavioral results (Bowman and Brown, 1996) taken with our single-unit
studies suggest that the ventral striatum is involved in the normal
pacing of activity, which may include delaying behavior when the reward
value is not large enough to provide the drive for sequenced, and
perhaps costly, behavior. We wonder whether the ventral striatum is
important for the planning and persistence that it takes to keep
working when reward can only be achieved via stepwise progression.
| |
FOOTNOTES |
Received Aug. 13, 1997; revised Dec. 2, 1997; accepted Jan. 7, 1998.
This work was supported by the National Institute of Mental Health
Intramural Research Program and by Agency of Industrial Science and
Technology, Ministry of International Trade and Industry, Japan. We
thank Dr. Mortimer Mishkin for his encouragement and support. We thank
Drs. Kenji Kawano and Elizabeth Murray for their reading and discussion
of this manuscript and Dr. Takao Oishi for the photograph of the
histological section. B.J.R. and T.G.A. express warm appreciation to
Dr. Steven Paul (Eli Lilly Company), who, as scientific director of the
National Institute of Mental Health, provided support and encouragement
for developing this line of work.
Correspondence should be addressed to Dr. B. J. Richmond, National
Institute of Mental Health, Building 49, Room 1B80, Bethesda, MD
20892-4415.
Dr. Aigner's present address: National Institute on Drug Abuse,
Division of Basic Research, Parklawn Building 10A19, 5600 Fischers
Lane, Rockville, MD 20857.
| |
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Top
Abstract
Introduction
