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The Journal of Neuroscience, June 15, 2002, 22(12):5081-5090
Visual and Anticipatory Bias in Three Cortical Eye Fields of the
Monkey during an Adaptive Decision-Making Task
Brian
Coe,
Kazuya
Tomihara,
Masako
Matsuzawa, and
Okihide
Hikosaka
Department of Physiology, School of Medicine, Juntendo University,
2-1-1 Hongo, Bunkyo-Ku, Tokyo 113, Japan
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ABSTRACT |
To examine the role of three cortical eye fields during internally
guided decision-making processes, we recorded neuronal activities in
the frontal eye field (FEF), supplementary eye field (SEF), and lateral
intraparietal cortex (LIP) using a free-choice delayed saccade
task with two synchronized targets. Although the monkeys must perform
the task in a time-locked manner, they were free to choose either the
receptive field (RF) target or the nonreceptive field (nRF) target to
receive reward. In all three areas we found neurons with stronger
activation during trials when the monkey was going to make a saccade to
the RF target (RF trials) than to the nRF target (nRF trials).
Modulation occurred not only during target presentation (visual bias)
but also before target presentation (anticipatory bias). The visual
bias was evident as an attenuated visual response to the RF stimulus in
nRF trials. The anticipatory bias, however, was seen as an enhancement
of pretarget activity in the RF trials. We analyzed the activity during
the 500 msec before target presentation and found that 22.5% of FEF
and 31.3% of LIP neurons and 49.1% of SEF neurons showed higher
activity during the RF trials. To more accurately determine when each
neuron started to show preferential activity, we used a new inverse
interspike interval analysis procedure. Our results suggest that
although all three cortical eye fields reflect attentional and
intentional aspects of sensorimotor processing, SEF plays an earlier
and perhaps more cognitive role in internally guided decision-making
processes for saccades.
Key words:
frontal eye fields; supplementary eye fields; lateral
intraparietal cortex; single-cell activity; attention; intention; decision making; free-choice task; saccade
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INTRODUCTION |
Many areas of the primate brain
contribute to the generation and control of saccadic eye movements. At
least three areas in the monkey cerebral cortex are thought to
participate actively in saccade initiation: the frontal eye field (FEF)
(Bruce and Goldberg, 1985 ), the supplementary eye field (SEF) (Schlag
and Schlag-Rey, 1987), and the lateral intraparietal cortex (LIP) (Andersen and Gnadt, 1989). Neurons in these areas are not only active
before and during saccades but also respond to visual targets (Mohler
et al., 1973; Goldberg and Bushnell, 1981; Schall, 1991b; Colby et al.,
1996). All three of these cortical eye fields also project to the
superior colliculus (SC) where saccadic or gaze commands are generated
(Segraves and Goldberg, 1987; Shook et al., 1990; Paré and Wurtz,
1997; Sommer and Wurtz, 2000). These studies suggest that the cortical
mechanism for visually guided saccade initiation is distributed among
at least three cortical eye fields. Such a distributed and presumably
parallel network seems to be a general feature of neuronal mechanisms
underlying complex behaviors. However, this raises two important
questions: Why are there three cortical eye fields, and how do they
cooperate or compete to make a saccade?
In most experimental situations to date, the subject's decision when
and where to make a saccade was dictated explicitly by instruction and
reward; therefore, the subject's performance was exogenously
controlled and highly predictable. In our daily life, however, we can
easily choose between competing objects or locations to select as a
target for a saccade without explicit instruction, often relying
on internal bias. For brevity, we refer to these two kinds of
decision-making processes as "externally guided" and "internally
guided" decisions, understanding that these are over-simplified
terms. Externally guided decision, or discrimination, tasks have been
well studied (Schall, 1995, 2001; Kim and Shadlen, 1999).
We speculated that clear differences between the neuronal activity of
the three areas might become apparent when investigating internally
guided decision-making processes using the same task. To test this
hypothesis, we needed to create a paradigm that did not blatantly
dictate behavior and discouraged purely random selection. We devised a
task where two identical stimuli were displayed and subjects were free
to make a saccade to either one of them to obtain reward. A key feature
of our paradigm is that the amount of reward waxed and waned gradually.
This reward schedule encouraged but did not instruct the monkeys to
choose one target for several consecutive trials and then switch to the
other target. In this way, the subject was still free to select either
target, because it would always receive reward, but could ascertain,
after investigation and observation, which target it preferred. This
complex decision-making task we feel is best described by the oxymoron
"free-choice (FC) task." Using this task, we found neurons in the
three cortical eye fields, especially the SEF, with anticipatory
activity before target presentation that predicted the monkey's
saccadic behavior. Some of the findings presented have been published
previously in abstract form (Coe et al., 1998, 2001).
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MATERIALS AND METHODS |
General
We used five male Japanese monkeys (Macaca fuscata;
subjects H, K, P, L, and C). The monkeys were kept in individual
primate cages in an air-conditioned room with food available ad
libitum. At the beginning of each experimental session, they were
moved to the experimental room in a primate chair. The monkeys were given restricted amounts of fluid during periods of training and recording. Their body weight and appetite were checked daily. Supplementary water and fruit were provided daily. The experiments were
performed while the monkey's head was fixed and its eye
movements were recorded. For this purpose, we implanted a head holder,
a chamber for unit recording, and an eye coil under general anesthesia (Nakamura et al., 1998). All surgical and experimental protocols were
approved by the Juntendo University Animal Care and Use Committee and
are in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals.
Experimental procedures
During the training and recording sessions, each monkey was
seated in a primate chair and placed in a sound-attenuated and dimly
lit room with its head fixed. Visual stimuli consisted of small red
spots of light (diameter, 0.4°) and were back-projected, using
light-emitting diode projectors, onto a tangent screen 25 cm in
front of the monkey's face. Eye movements were recorded using the
search coil method (Robinson, 1963). Each monkey's performance was
reinforced after each successful trial by drops of water. Water was
dispensed through a "double barrel" tube arrangement, where one
tube led to the pipe supplying the water and the other was left open,
preventing the monkeys from sucking excess water.
Before single-unit recording began, we obtained magnetic resonance (MR)
images (0.3 T; Airis; Hitachi, Tokyo, Japan) perpendicular to
each recording chamber. Based on multitiered surface MR images, we
could readily determine the locations of the three cortical eye fields:
(1) FEF (monkeys P, H, and K), in and around the anterior bank of the
arcuate sulcus (Bruce et al., 1985); (2) SEF (monkeys P, C, and L), in
the dorsomedial convexity, 2-5 mm from the midline, slightly anterior
to the level of FEF (Shook et al., 1990); and (3) LIP (monkey P), in
the lateral bank of the intraparietal sulcus (Barash et al.,
1991b).
Single-unit recording was then performed using tungsten electrodes
(diameter, 0.25 mm; 1-5 M ; measured at 1 kHz; Frederick Haer, Bowdoinham, ME). A hydraulic microdrive (MO95-S; Narishige, Tokyo, Japan) was used to advance electrodes into the brain. The locations of the cortical eye fields were reconfirmed by the presence of visually responsive cells and, for the FEF and SEF, electrically evoked saccades with thresholds of <50 µA (Bruce et al., 1985; Schlag and Schlag-Rey, 1987).
The receptive fields (RFs) of visually responsive neurons were
elucidated using a memory-guided task (Hikosaka and Wurtz, 1983). Once
neurons were properly isolated using a BAK dual-window discriminator
(model DDIS-1; BAK Electronics, Germantown, MD), single-unit recording
was performed during ~100 trials of the FC task and 60 trials of a
similar control task.
Task procedures
FC task
The FC task is shown in Figure 1
(left). Each trial started with the appearance of a central
spot of light on which the monkey had to fixate (Fig.
1A). After 1200 msec, two spots appeared
simultaneously, one in the RF of the cell (RF target) and the other
outside the RF [nonreceptive field (nRF) target] (Fig.
1B). During this time, the monkey had to maintain
fixation for another 800 msec. This period is referred to as the
"visual period," because both targets were visible but the monkey
had to maintain fixation. The nRF target was placed diametrically
opposed to the RF target with respect to the fixation point (Fig. 1,
left). After the visual period of 800 msec, the central
fixation point was turned off, signaling the monkey to make a saccade
(Fig. 1C). The monkey could then make a saccade to either of
the two targets to obtain reward. Reward consisted of water (released
by a solenoid) for a maximum of 150 msec duration and a tone pulse. The
duration of the tone pulse was fixed at 75 msec so that the only clue
as to the duration of the reward was the amount of water dispensed.
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Figure 1.
A schematic of the tasks. Left, The
FC task. A, Fixation period. The subject must maintain
fixation for 1200 msec. The gray ring indicates the RF
of the cell. B, Visual period. Two targets come on but
the subject must maintain fixation for another 800 msec.
C, Saccade period. The fixation offset is the cue for
the subject to make a saccade to the target inside the RF (RF target)
or to the target outside the RF (nRF target). Successful trials in the
FC task are categorized as RF trials and nRF trials based on the
monkey's behavior. Right, The control task.
A, Fixation period (same as the FC task).
B, Visual period. Only one target is presented, and the
subject must still maintain fixation for another 800 msec.
C, Saccade period. The fixation offset is the cue for
the subject to make a saccade to the target presented. Successful
trials in the control task are referred to as RFc trials and nRFc
trials based on the target presented. The white dots
represent the visual stimuli and are the only items visible to the
subject. Large arrows indicate correct trial progression.
Small arrows indicate saccades made. Sunbursts
indicate fixation offset.
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To encourage the monkey to participate more actively in the task, the
computer program adjusted the amount of reward after most trials using
several guidelines, as shown below. However complex these
"policies" may appear, the monkey was always free to choose either
one of the targets to receive reward. The reward scheme was designed to
react to, not instruct, the monkey.
Independence policy. Each target had its own independent
reward amount. The reward amount for either target would only change if
it had been chosen (but see Bonus policy, below).
Initialization policy. At the start of each block of trials,
the reward amount for both targets is set to 30% of maximum. A saccade
to either target would be rewarded by the release of the current amount
of reward for the target chosen and then the reward amount for the
chosen target would increase by 10% for the next trial. The first
target to be chosen three times would be designated the incrementing
target and the other target would be designated the decrementing
target. This nomenclature was set regardless of the spatial attributes
of each target and was based solely on the monkey's behavior.
Main policy. Once the initialization was complete, a saccade
to the incrementing target would dispense the current amount of reward
for that target and then increase the amount of reward for that target
by 10% for the next trial until it reached 100% (150 msec). A saccade
to the decrementing target would dispense the current amount of reward
and then decrease the reward amount for that target by 10% for the
next trial until it reached 20% (30 msec).
Exchange policy. The reward amount for the incrementing
target would remain at 100% for four to seven trials, randomly, to assure that the monkey would not know when the reward was going to
start to decrease. At that point the designations would switch so that
the previous incrementing target was now the decrementing target and
vice versa.
Bonus policy. After an exchange, if the reward amount
for the incrementing target was low ( 40%), a small bonus of 20%
would be added to it.
Control task
The control task is shown in Figure 1 (right). The
time schedule of the control task was the same as the FC task, but only one target was presented for each trial and reward was always 50% of
maximum (75 msec). The stimuli were identical to the ones used for the
FC task but were presented in alternation. We avoided a random
presentation schedule for the control task to prevent confounds that
may have taken place by comparing the very predictable FC task with a
nonpredictable control task.
Data analysis
Our initial interest for this study was in the modulation of
visual responses in the three cortical areas, so purely saccadic cells
or pause cells were not included in this data analysis.
Context dependency
For the data obtained from each neuron, we investigated the
response of each cell in four conditions (Fig. 1): trials in the control task were classified into RF control (RFc) trials
(saccades to the RF target) and nRF control (nRFc) trials
(saccades to the nRF target); trials in the FC task were classified
into RF trials (saccades to the RF target) and nRF trials (saccades to
the nRF target). The RFc trials were used to set a standard for the
response of the cell to a single target in its RF to which the monkey
will make a saccade. The nRFc trials were used to set a standard for the response of the cell to a single saccade target diametrically opposed to the RF of the cell. The RF trials were used to gauge the
response of the cell to having a second target outside the RF of the
cell but still making a saccade to the RF target. The nRF trials were
used to see how the cell would react when there was a target in its RF
but the monkey had chosen to saccade to the nRF target instead.
Operationally we defined two kinds of context-dependent influences: (1)
externally guided (the difference between the RFc and RF trials in
which the saccade was to the same location but the visual display was
different) and (2) internally guided (the difference between the RF and
nRF trials in which the visual display was identical but the saccade
was made to different targets). Although the external influences have
been the main focus of many previous studies, the main focus of the
rest of this paper will be on the modulation of visual and anticipatory
responses within the internally guided context situation.
Individual neuronal analysis
Wilcoxon-Mann-Whitney (WMW) tests (Siegel and Castellan, 1988)
were performed on RF versus nRF spike counts for each neuron for both
the pretarget period ( 500 to 0 msec; WMW-pre) and the post-target
period (50-550 msec; WMW-post) in the FC task. Z scores above 2.58 (RF > nRF) or below 2.58 (nRF > RF) are
significant (p < 0.01) (see Fig. 8).
Normalized differential activity
To characterize the response properties of individual neurons
across cortical areas, normalized differential activity scores were
obtained for both the pretarget period and the post-target period in
the FC task using the formula (RF nRF)/(RF + nRF), where each
term indicates the number of action potentials during a given time
window for the indicated condition.
Inverse interspike interval procedure
Figure 2 shows the inverse
interspike interval procedure (1/ISI), which was used for each trial.
Basically, for any two consecutive spikes the value of interspike
interval (ISI) was assigned to the time period of the first spike and
to every time period between the two spikes. The spike times were
measured at the millisecond level so that interval functions with 1 msec bins were created. For each trial, ISI plots were created that
overlapped the preceding and following trials and truncated to a fixed
time range of 2200 msec before target onset to 2800 msec after target
onset. We took the inverse of each ISI (1/ISI) to create
spike-frequency functions (Fig. 2B,C, gray
lines). In this way, each trial had an activity score at every 1 msec interval with values of >0 and 1 kHz. To reduce noise, the
1/ISI of each trial was condensed into 5 msec bins by taking the mean
of five 1 msec bins of the 1/ISI at nonoverlapping 5 msec intervals
(Fig. 2B,C, black circles). We avoided
smoothing and waveform convoluting to preserve independence of measures within each trial, across time. These types of data fit quite well with
the assumptions of the nonparametric WMW test (Siegel and Castellan,
1988).
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Figure 2.
Explanation of the 1/ISI procedure and the Running
Mann comparison. Sample data were taken from the cell in Figure
4C. A, Rasters for 10 RF and 10 nRF
trials. Ticks indicate neuronal spikes.
B, 1/ISI data for individual RF trials from the raster
above are superimposed. The 5 msec condensing process is shown at two
sample time points. Each circle indicates the mean value
for the 1/ISI data for each trial within the 5 msec time window.
This was done at nonoverlapping 5 msec intervals for every trial in
each block. C, The same as B but
for the nRF trials from the raster above. D, The
Z scores from the running WMW tests between the two
groups of condensed 1/ISI data from all of the RF and nRF trials
(~100 trials). The arrow indicates the onset of the
differentiation of neuronal activity, which was defined as the first of
at least 10 consecutive Z scores of >2.33
(p < 0.01). E, The 5 msec
condensed data for all of the RF and nRF trials were then averaged
across trials to form mean spike-frequency functions
(black and gray solid lines,
respectively). For comparison, the 10 msec bin peristimulus time
histograms of the same data are plotted with dotted
lines. The vertical dotted line indicates the
onset of the differentiation of neuronal activity. See Materials and
Methods for details.
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Onset of modulation
To determine when the activity of each neuron started to
differentiate between RF and nRF trials, the WMW test was performed on
the condensed 1/ISI spike-frequency functions. For each 5 msec epoch,
1/ISI values from the RF trials and nRF trials were ranked and compared
using the WMW test. This "Running Mann" comparison would return a
Z score for each 5 msec epoch (Fig. 2D).
The first of 10 consecutive Z scores (i.e., 50 msec
duration) to be >2.33 (p < 0.01) was chosen as
the onset of preferential modulation (Fig. 2E,
vertical dotted line).
Mean spike-frequency function
The mean spike-frequency function was obtained to visualize the
mean changes in spike frequency by simply averaging the condensed 1/ISIs for all trials in one condition (Fig. 2E). We
used this method (hereafter called "1/ISI plot") to present the
activities of individual neurons (Figs.
3-5 ) and of a population of neurons (Fig. 6). This is basically equivalent to the
peristimulus time-binned histogram that
has been widely used (shown in Fig.
2E for comparison). The 1/ISI plot is smoother and
has better temporal resolution than the
10 msec binned histograms used in the past, while still maintaining
independence of measures across time.
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Figure 3.
Visual and motor responses of a typical cell in
the right FEF during the FC task (top) and the control
task (bottom). Plots are arranged by task and
destination of saccade. For both tasks, the activities are shown
separately for both kinds of trials where a saccade was made either to
the target in the RF (RF target; left-down, 30°) or to the target
outside the RF (nRF target; right-up, 30°). Rasters are in
chronological order from top to bottom.
Black ticks indicate neuronal spikes, and green
bars indicate saccade onset and duration. One millisecond 1/ISI
functions are directly above the rasters they represent and are color
coded to match the target plots for each task. The 5 msec condensed
1/ISI, or 1/ISI plots, for each are overlaid in black.
The shaded area in each plot indicates the visual period
(0-800 msec), and the green line represents the mean
saccade onset. The horizontal bar plots next to each
raster indicate the percentage of reward for each trial. Colored
sections represent the percentage of reward given for a saccade
to the corresponding target. For the FC task, dark gray
bars indicate amount of reward the monkey voluntarily skipped,
and white bars indicate error trials in both
tasks.
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Figure 4.
Strong modulation of visual response in three
cortical eye fields. For a representative cell in each area, the 1/ISI
plot is shown for the RF trials (black) and the nRF
trials (gray) in the FC task. The difference in
cell activity between the RF trials and the nRF trials is clearest
during the visual period (shaded area).
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Figure 5.
Strong modulation of anticipatory activity in
three cortical eye fields. For a representative cell in each area, the
1/ISI plot is shown for the RF trials (black) and the
nRF trials (gray) in the FC task. The difference
in cell activity between the RF trials and the nRF trials is clear in
the fixation period, before the onset of the targets. The dotted
line in each 1/ISI plot indicates the time when the activities
for the RF trials and for the nRF trials first displayed a significant
difference according to the Running Mann comparison (see Materials and
Methods). The shaded area indicates the visual period.
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Figure 6.
Population plots for three cortical eye fields.
For the three populations of cells, the mean 1/ISI plots are shown for
the RF trials (solid black lines) and the nRF trials
(solid gray lines) of the FC task and, for comparison,
the RFc trials (dotted black lines) and the nRFc trials
(dotted gray lines) of the control task. The population
data are based on 55 cells in the SEF, 111 cells in FEF, and 32 cells
in LIP from five monkeys. The shaded area indicates the
visual period.
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RESULTS |
In the FC task, the monkeys switched between the two targets after
several trials, displaying the behavioral pattern we were hoping for.
As illustrated in Figure 3, the monkeys tended to choose a target for
consecutive trials while the amount of reward increased, peaked, and
began to decrease. Eventually the monkeys would switch to the other
target, apparently seeking the more rewarding target. However, this
behavior was not invariable, because the monkeys often switched between
the targets after only a few trials, leaving the target with a higher
percentage of reward in favor of the less rewarding target. The
important point here is that the monkeys chose a target based on their
own internal decision-making process and not based solely on the actual
amount of reward. How the monkeys decided to which target they would saccade is an important behavioral issue that we will examine in future
studies. Our main interest in this study was the modulation of visual
and anticipatory activity relating to the selection of a target.
Specifically, if the subject has already decided to select a given
target in the FC task, attention may be allocated to that location even
before the onset of the target. Accordingly, the magnitude of the early
visual response and even pretarget anticipatory activity in many cells
was strongly correlated with the monkey's subsequent selection. The
question then becomes "when does the neural activity start to predict
the behavior?"
The activity of a typical FEF cell is shown in Figure 3. In the control
task, the target was presented in the lower-left or upper-right field
in alternation. The FEF cell exhibited a visual and motor response to
the target in the lower-left field (Fig. 3, yellow plot) but
not to the target in the upper-right field (Fig. 3, gray
plot). Thus, the target in the lower-left target was in the RF of
the cell (RF target), whereas the target in the upper-right target was
outside the RF of the cell (nRF target). These task trials were
designated as the RFc and nRFc trials, respectively.
In the FC task (Fig. 3, left), the two targets were
presented simultaneously and the monkey could choose either one to
receive reward. The visual response of the cell was weaker (WMW-post; p < 0.01) when the monkey was going to make a saccade
to the nRF target (Fig. 3, blue plot) than when the monkey
was going to make a saccade to the RF target (Fig. 3, red
plot). These task trials were designated as the RF and nRF trials,
respectively. The difference in activity between the RF and nRF trials
was entirely dependent on the monkey's decision, because the
presentation of stimuli was identical throughout the block of trials
and both targets were associated with the full range of reward amounts.
When we compare between the tasks, we can see that the neural
activities during the RF trials and RFc trials were quite similar
(WMW-post; p > 0.10). Thus the difference within the
FC task would be caused by an attenuated visual response during
the nRF trials.
Figure 4 shows examples of strong modulation of visual response during
the FC task in cells from the SEF, FEF, and LIP. All three cells showed
a striking difference in the visual response between the RF trials and
the nRF trials (WMW-post; p < 0.01), although the
visual display was identical. In the SEF and FEF examples, the
inhibition in the nRF trials was strong enough to block out almost the
entire visual response.
With closer inspection of Figure 4, the examples from SEF and FEF also
seem to show anticipatory modulation even before the visual response of
each cell. In Figure 5 we show three different cells from the SEF, FEF,
and LIP with robustly enhanced anticipatory activity during the RF
trials (WMW-pre; p < 0.01). All three of these cells
showed a striking increase of activity during the pretarget fixation
period of the RF trials, although the visual targets had not yet
appeared. Note that whether a given trial would be an RF trial or an
nRF trial solely depended on the monkey's behavior. Thus, the
anticipatory modulation of the activity of the cells reflects the
monkey's decision to choose the RF target well in advance of the
arrival of the visual target that it will use to execute its selection.
A comparison of the cells shown in Figures 4 and 5 suggests that the
monkey's decision is represented more robustly in the SEF and FEF than
in the LIP.
This impression was supported by the population data (Fig. 6), which
indicate that one of the clearest differences between the three
cortical areas was before the onset of the targets (white portion on
the left of each plot). Cells in the SEF showed the strongest
modulation of anticipatory activity during the pretarget period. The
difference in anticipatory activity was less clear for the FEF and was
slight for the LIP. The activity is higher in the RF trials than in the
nRF trials in the FC task as well as both conditions of the control
task (RFc and nRFc trials). This suggests that the stronger
anticipatory activity in the RF trials was attributable to an
enhancement of the default anticipatory activity. Because the timing of
all target onsets was fixed and the targets in the control task were
presented in alternation, the monkeys could, in principle, anticipate
the onset of each target; however, we found no indication in the data
to suggest that the monkeys anticipated a specific target in the
control task.
To determine whether the activity of each neuron during the RF trials
was statistically different from the nRF trials, WMW tests were
performed on the spike count during 500 msec of the pretarget and
post-target periods (Fig. 7). During the
post-target period, 67.3% (37 of 55) of SEF neurons, 43.2% (48 of
111) of FEF neurons, and 56.3% (18 of 32) of LIP neurons displayed
significantly stronger activity during the RF trials than during the
nRF trials. During the pretarget period, 49.1% (27 of 55) of SEF
neurons, 22.5% (25 of 111) of FEF neurons, and 31.3% (10 of 32) of
LIP neurons displayed significantly stronger activity during the RF trials than during the nRF trials. During both time windows, a remarkable percentage of cells from all areas, especially in the SEF,
seemed to reflect the monkey's intention (i.e., as to which target it
had decided to select). However, the difference between the SEF and the
other two eye fields seems greater during the pretarget period than
during the post-target period.
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Figure 7.
Distribution of Z scores for
pretarget and post-target activity. The spike counts for the RF trials
and the nRF trials were compared using the WMW test for two separate
time windows. Histograms of the results indicate how many cells showed
significantly different activity. Black bars indicate
cells with Z scores above 2.58 (RF > nRF) or below
2.58 (nRF > RF; p < 0.01). Gray
bars indicate cells with nonsignificant Z
scores. Left, Pretarget time window: 49.1% (27 of 55)
of SEF cells, 22.5% (25 of 111) of FEF cells, and 31.3% (10 of 32) of
LIP cells show greater activity during the RF trials than during the
nRF trials. Right, Post-target window: 67.3% (37 of 55)
of SEF, 43.2% (48 of 111) of FEF, and 56.3% (18 of 32) of LIP cells
show greater activity during the RF trials than during the nRF
trials.
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To characterize the response properties of the individual neurons for
each area, pretarget and post-target normalized differential activity
scores were calculated for each neuron (Fig.
8). Scores could vary from 1 to 1 and a
positive score indicates that the neuron showed stronger activity
during the RF trials than during the nRF trials. We used this
methodology to help visualize the variation within groups and for
statistical analysis between groups. During the post-target period, SEF
neurons had significantly higher scores than FEF neurons
(p < 0.01; t test) and showed a
strong tendency for higher scores than LIP neurons
(p = 0.052; t test). Neurons from the
FEF and LIP had scores that were quite similar. During the pretarget
period, SEF neurons had significantly higher scores than both FEF and
LIP neurons (p < 0.01; t test) and
again, neurons from the FEF and LIP had scores that were quite similar. In Figure 8, we show the pretarget scores plotted against the post-target scores to demonstrate correlations. The SEF shows stronger
Pearson correlation coefficients between pretarget and post-target
normalized differential activity scores than do the FEF and LIP (SEF,
r = 0.483, p < 0.01; FEF,
r = 0.395, p < 0.01; LIP,
r = 0.399, p < 0.05). The small and
large ellipses show the first and second SD for the bivariate normal
approximation, respectively. Thus, despite the variation in
activity, visually responsive cells in the SEF encode the intention of
the subject to select the RF target earlier than visually responsive
cells in either the FEF or LIP, and modulation in the post-target
period is more often preceded by modulation in the pretarget period of
visually responsive cells in the SEF than visually responsive cells in
either the FEF or LIP.
View larger version (26K):
[in this window]
[in a new window]
|
Figure 8.
Normalized differential activity plots for three
cortical eye fields of all five monkeys (left) and
monkey P (right). Positive values indicate greater
activity during the RF trials than during the nRF trials. Each
circle represents a single neuron. In each plot,
horizontal dotted lines represent the mean score for the
post-target time window, and vertical dotted lines
represent the mean score for the pretarget time window. The
small and large ellipses indicate the
first and second SD of the bivariate normal distribution.
|
|
Finally, we compared the normalized differential activity
scores for both time windows from the FEF and SEF of monkey P, from whom we collected data from all three areas, with scores from the FEF
and SEF of the other four monkeys to check for reliability across
subjects. t tests revealed no significant differences.
To further test the hypothesis that the monkey's decision
is represented differently and at different times in the three cortical areas, we attempted to measure when the activity of a cell started to
indicate the monkey's decision (i.e., make a saccade to the RF
target). For this purpose we performed a running WMW test on the
inverse interspike intervals (see Materials and Methods). The results
from this Running Mann comparison on the individual examples shown in
Figure 5 indicate that the onset of decision-related modulation was 855 msec before the onset of the targets for both the SEF cell and the FEF
cell and 580 msec for the LIP cell. In this way, we determined the
onset of decision-related modulation for every cell. The results for
all cells are plotted in Figure 9 as a
cumulative histogram for each cortical area. The onset of
decision-related modulation was clearly earlier for the SEF population
than for the FEF or LIP populations (WMW test; p < 0.01); there was no significant difference between the FEF and LIP. In
the SEF, 58.2% of the cells started reflecting the monkey's decision
before the target onset period, whereas only 27% of the cells in the
FEF and 34.4% of the cells in the LIP did so. A few cells in the SEF
(5.5%) had a higher resting level, reflecting the monkey's decision
even before the trial started. This was not found in the FEF or
LIP.
View larger version (26K):
[in this window]
[in a new window]
|
Figure 9.
The onset of modulation predicting the monkey's
decision to choose the RF target in three cortical eye fields.
Cumulative histograms for each cortical area indicate when individual
cells started showing preferential activity for the RF trials over the
nRF trials as determined by the Running Mann comparison. The
shaded area indicates the visual period and the
vertical line indicates fixation onset. The majority of
visually responsive cells from all three areas showed modulation before
the offset of the fixation point (800 msec). Although some cells in the
FEF and LIP (~30%) showed modulation before fixation onset, this
type of modulation was more prevalent in cells in the SEF (58.2%).
Three cells in the SEF showed predictive differentiated activation
throughout the intertrial interval (indicated by the initial
elevation). All three areas had some cells that never showed
preferential activity for the RF trials in the FC task even after
making a saccade (indicated by the final elevation on the
right). Tgts, Targets.
|
|
| |
DISCUSSION |
Mechanisms of internally guided decision making for saccades
An important conclusion of this study is that the SEF rather than
the FEF or LIP plays a leading role in the internally guided decision-making mechanisms for saccade generation. In the FC task, the
subject generally chose the same target for several trials in a row and
most likely had already decided the direction in which the subject was
going to make a saccade well before the targets appeared.
Accordingly, we found many neurons in the cortical eye fields that
started to change their firing rate depending on the monkey's decision
even before target presentation (Figs. 5 and 6). This anticipatory bias
reflects an internal decision-making process. What was striking in our
findings was that the anticipatory bias occurred earlier and was more
common in the SEF than in the FEF or LIP. The results suggest that
anticipatory bias is generated either in the SEF or in a region more
directly linked to the SEF than the FEF or LIP. The bias signals in the
SEF might then be transmitted to the FEF and LIP through their well
known connections (Huerta and Kaas, 1990; Tian and Lynch, 1996).
Neurons from these three cortical eye fields have been shown to have
similar visual or saccadic motor properties (Barash et al., 1991a;
Schall, 1991a; Russo and Bruce, 2000). However, other studies suggest
that the SEF has some unique, more cognitive properties: object-centered coding of visual stimuli (Olson and Gettner, 1995; Olson and Tremblay, 2000), saccades evoked by microstimulation that
vary with eye position (Schall, 1991b), saccades evoked in the SEF that
can be goal-directed (Fujii et al., 1995), learning of arbitrary
visuomotor associations (Chen and Wise, 1995a,b, 1996), enhanced
activities in conflict situations (Schlag-Rey et al., 1997),
reward-related activities (Amador et al., 2000), performance monitoring
(Stuphorn et al., 2000), and coding of learned visuomotor sequences (Lu
et al., 2002). These results suggest that aspects of previous sensory
signals are first stored in the SEF and later used for movement
initiation; this would be a key feature of internally guided decision making.
The hypothesized function of the SEF in internally guided decision
making might be related to its location in the dorsomedial frontal
cortex. It has been reported that patients with lesions in the
supplementary motor area (SMA) may show a loss of spontaneous motor
activity (Laplane et al., 1977). Clinical findings led to the
suggestion that the SMA plays a role in decision making based on
internal drives (Goldberg, 1985). This hypothesis appears to be
supported by subsequent experimental studies showing that memory for
which target button was rewarded was more important for success than
the visual aspects of the task (Kurata and Wise, 1988). In addition,
SMA neurons may be related to a long-lasting process leading to
initiation of self-paced movement (Okano and Tanji, 1987; Tanji and
Shima, 1994) and, in conjunction with the basal ganglia, part of a
distributed neuronal system for movement initiation (Romo and Schultz,
1987; Hikosaka et al., 2000). The anterior part of the SMA, which is
now called the pre-SMA, may also be related to decision making. Pre-SMA
neurons may become active when the monkey changes its behavior in
response to a sensory signal (Shima et al., 1996) or starts learning a
new procedure (Nakamura et al., 1998). Imaging studies in humans have
also indicated a role for the pre-SMA in the internal selection of
movement (Deiber et al., 1996; Jenkins et al., 2000). Particularly
remarkable are findings in the anterior cingulate cortex, which is just
ventral to the SMA (for review, see Paus, 2001). Many anterior
cingulate neurons became active when the monkey changed its behavior in response to a large reduction of the amount of reward (Shima and Tanji,
1998) or when the monkey found a correct answer by inference (Procyk et
al., 2000). Anatomical studies also indicate that these structures are
interconnected (Huerta and Kaas, 1990). Together, these results suggest
that the medial frontal cortex, including the anterior cingulate
cortex, pre-SMA, and SEF, may form a functional network that uses
contextual clues and internal biases to select appropriate actions.
Relationship between decision making and voluntary attention
In our FC task, we found that the phasic and sustained visual
responses of many neurons were stronger when the monkey was going to
make a saccade to the RF target (RF trials) than to the nRF target (nRF
trials) (Figs. 4 and 6). Because the target presentation was identical
in both situations, the modulation of neuronal activity was solely
attributable to the monkey's intention to select the RF target.
Similar results have been described using an interesting paradigm where
the monkeys freely scanned still images. Some FEF neurons showed a
stronger visual response before saccades to a location within the RF of
the neuron than before saccades to a location outside the RF of the
neuron (Burman and Segraves, 1994). The authors argue that the
activity of FEF neurons seemed to depend on the monkey's level of
arousal or engagement of attention. The modulation of visual response
may include two kinds of processes: voluntary attention (Bushnell et
al., 1981; Kodaka et al., 1997; Luck et al., 1997) and motor
preparation (Goldberg and Bushnell, 1981). For the FEF and SEF cells in
Figure 4, this visual modulation, or bias, was sometimes so strong that
the response to the RF stimulus was eliminated when the monkey was
going to choose the nRF stimulus. In this situation, top-down
inhibitory modulation completely countermanded the bottom-up visual
response of the neuron.
In the FC task, the monkeys had already decided the direction in which
they were going to saccade by the time the targets appeared and could
allocate attention to a specific location in space. This biased the
neural response even before the onset of the targets. For many SEF
cells, this anticipatory bias was correlated with visual modulation.
Similar findings have been discussed for V4 neurons, for which the
modulation appeared before the target onset. However, this modulation
took place after a visual response to the onset of two location-marking
frames (Luck et al., 1997).
One possibility for the origin of the visual bias is that the strong
anticipatory bias in the SEF (Fig. 6) might be transmitted to the FEF
and LIP (Huerta and Kaas, 1990), which, together with visual inputs,
would initiate the visual biases in the FEF and LIP. This initial
visual bias might then be enhanced and maintained if the visual signals
are circulated through the three cortical eye fields (Stanton et al.,
1993, 1995; Tian and Lynch, 1996; Chafee and Goldman-Rakic, 2000).
Relationship between externally guided and internally guided
decision making
There have been many studies on the neural mechanisms of
externally guided decision making (Shadlen et al., 1996; Thompson et
al., 1996; Schall and Bichot, 1998; Thompson and Schall, 1999). In
these studies, the subject would make a perceptual decision by
detecting the presence of or a characteristic of a single stimulus or
by discriminating between stimuli presented; the subject would then
perform a fixed behavioral response. The subject's decision is then
directly linked to, or the result of, immediate sensory evaluation. In
a typical case, the physical features of the sensory stimulus, or a
cueing stimulus, determine the subject's behavior, because the subject
has been taught as such. This type of selection behavior may be
predicted mathematically from neuronal activity (Gold and Shadlen,
2001).
However, primates are thought to behave based on some internal factors
in addition to external factors. These internal factors are ill defined
and can include expectation, inference, preference, mood, habits,
fatigue, and guessing. For this reason, even the most basic
discrimination task must still involve some internal factors. Likewise,
no task could be exclusively internally driven, because external
factors such as visual display, auditory events, and timing instruct
the subject what needs to be done and when. In this paper, the terms
internal and external are used for instructional purposes as labels for
situations where the majority of influences would be biased in one
manner or the other. By introducing small and imprecise alterations in
water release during our task, we hoped to significantly enhance the
role of dynamic internal factors in a task where the rest of the
external factors remained constant. In this way we gave the subject the
freedom to choose the target that it expected, inferred, felt, or
guessed was in some way preferable while still maintaining a controlled
environment. A similar paradigm, based on a match-to-sample format, has
been used on humans. In that case, the experimenter simply asked the
subjects which one of three stimuli they "like the best" and
compared the results with previous blocks for which the subjects
were asked to select the most similar or most different (Goldberg and
Podell, 2000). Using their cognitive bias task, they found
perseverance-type deficits in prefrontal lobe patients that the
Wisconsin card-sorting task did not elucidate, arguing that to truly
investigate decision making and the frontal lobes, one needs to use
more dynamic preference-based tasks.
Strong manipulation of reward has induced modulations of neuronal
activities in cortical areas (Watanabe, 1996; Tremblay and Schultz,
2000) including the FEF (Kobayashi et al., 2002), area 46 but not the
FEF (Leon and Shadlen, 1999), the LIP (Platt and Glimcher, 1999), the
supplementary motor cortex (Kurata and Wise, 1988), and basal ganglia
nuclei (Bowman et al., 1996; Kawagoe et al., 1998; Schultz, 1998; Shimo
and Hikosaka, 2001). However, most of the reward-related modulations
occurred after presentation of targets or instructional cues that
explicitly instructed the subject. Notable exceptions have been found
recently in the caudate (Lauwereyns et al., 2002; Takikawa et al.,
2002), the substantia nigra pars reticulata (Sato and Hikosaka,
2000), and the SC (Ikeda et al., 2001), all of which showed pretarget
activity that depended on the context of an asymmetric reward schedule
that remained fixed throughout each block.
These data suggest that different neural networks are involved in
different aspects of decision making. We believe that by directly
comparing three cortical eye fields, the present results provide an
important development in the study of neural mechanisms for both
internally guided and externally guided decision-making mechanisms.
| |
FOOTNOTES |
Received Dec. 20, 2001; revised Feb. 28, 2002; accepted March 25, 2002.
This work was supported by a grant-in-aid for Scientific Research on
Priority Areas (C) from the Ministry of Education, Culture, Sports,
Science, and Technology, by Core Research for Evolutional Science and
Technology of Japan Science and Technology Corporation, and by Japan
Society for the Promotion of Science Research for the Future program.
We thank Johan Lauwereyns, Shunsuke Kobayashi, Hiro Nakahara, and
Makoto Sato for helpful comments, Makoto Kato for aid in designing the
online computer program, and Masashi Koizumi for technical support.
Correspondence should be addressed to Okihide Hikosaka, Laboratory of
Sensorimotor Research, National Eye Institute, National Institutes of
Health, Building 49, Room 2A50, Bethesda, MD 20892. E-mail:
oh{at}lsr.nei.nih.gov.
K. Tomihara's present address: Department of Psychology, Faculty of
Law, Economics, and Humanities, Kagoshima University, 1-21-30 Korimoto,
Kagoshima 890-0065, Japan.
M. Matsuzawa's present address: Department of Psychology, Faculty of
Letters, Showa Woman's University, 1-7 Taishido, Setagaya-Ku, Tokyo
154-8533, Japan.
| |
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ABSTRACT
INTRODUCTION
