1Center for Neuroscience and Section of Neurobiology, Physiology and Behavior, University of California at Davis, Davis, California 95616; and 2Laboratory of Sensorimotor Research, National Eye Institute, National Institutes of Health, Bethesda, Maryland 20892
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ABSTRACT |
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Recanzone, Gregg H. and Robert H. Wurtz. Effects of Attention on MT and MST Neuronal Activity During Pursuit Initiation. J. Neurophysiol. 83: 777-790, 2000. The responses of neurons in monkey extrastriate areas MT (middle temporal) and MST (medial superior temporal), and the initial metrics of saccadic and pursuit eye movements, have previously been shown to be better predicted by vector averaging or winner-take-all models depending on the stimulus conditions. To investigate the potential influences of attention on the neuronal activity, we measured the responses of single MT and MST neurons under identical stimulus conditions when one of two moving stimuli was the target for a pursuit eye movement. We found the greatest attentional modulation across neurons when two stimuli moved through the receptive field (RF) of the neuron and the stimulus motion was initiated at least 450 ms before reaching the center of the RF. These conditions were the same as those in which a winner-take-all model better predicted both the eye movements and the underlying neuronal activity. The modulation was almost always an increase of activity, and it was about equally frequent in MT and MST. A modulation of >50% was observed in ~41% of MT neurons and 27% of MST neurons. Responses to all directions of motion were modulated so that the direction tuning curves in the attended and unattended conditions were similar. Changes in the background activity with target selection were small and unlikely to account for the observed attentional modulation. In contrast, there was little change in the neuronal response with attention when the stimulus reached the RF center 150 ms after motion onset, which was also the condition in which the vector average model better predicted the initial eye movements and the activity of the neurons. These results are consistent with a competition model of attention in which top-down attention acts on the activity of one of two competing populations of neurons activated by the bottom-up input from peripheral stimuli. They suggest that there is a minimal separation of the populations necessary before attention can act on one population, similar to that required to produce a winner-take-all mode of behavior in pursuit initiation. The present experiments also suggest that it takes several hundred milliseconds to develop this top-down attention effect.
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INTRODUCTION |
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The direction and speed of moving visual stimuli
are encoded in extrastriate cortical areas MT (middle temporal area)
and MST (medial superior temporal area) (Allman et al.
1985; Desimone and Ungerleider 1986
;
Maunsell and Van Essen 1983
; Tanaka et al. 1989
; Van Essen et al. 1981
). These cortical
areas are also instrumental in the generation of smooth pursuit eye
movements, based on both the activity of the neurons during this
behavior and deficits following ablation (Dursteler et al.
1987
; Groh et al. 1997
; Komatsu and Wurtz
1988
, 1989
; Newsome et al. 1985
;
Schiller and Lee 1994
; Thier and Erickson
1992
; Yamasaki and Wurtz 1990
). The results of
our previous experiments indicated that during a task in which the
monkey was required to pursue one of two stimuli, the responses of MT
and MST neurons could be better represented by one of two models
depending on the stimulus conditions (Recanzone et al. 1997
; Recanzone and Wurtz 1999
). The model that
better described the metrics of the initial eye movements and the
activity of the MT and MST neurons was a vector average when both the
time between the onset of target motion and pursuit initiation (150 ms)
and the distance over which the target moved was short. A
winner-take-all model was the better description when the time (450 ms)
and distance was longer (Recanzone and Wurtz 1999
). This
difference was interpreted as a reflection of the interactions of
subpopulations of neurons within MT and MST that have receptive fields
and best directions of motion aligned along the stimulus trajectory.
In these previous experiments, we used the motion of single stimuli in
the receptive field (RF) to predict the response when two stimuli moved
through the RF simultaneously. On all trials two different stimuli
moved through the visual field, and the monkey presumably directed its
attention to the target stimulus but not to the other stimulus. In the
present experiments we have specifically investigated the contribution
of attention to the responses of MT and MST neurons by comparing their
responses on trials when we required the monkey to attend to one
stimulus with the responses on trials when we required the monkey to
attend to the other stimulus. We did this attention shift by requiring the monkey to use one stimulus or the other as the target for a pursuit
eye movement. We compared the neuronal responses on long and
short-duration trials that led to winner-take-all and vector average
interpretations of the behavior and the underlying neuronal activity,
and also when two stimuli moved through the RF of the neuron and when
the two stimuli moved through different visual hemifields. In an
additional set of experiments, we changed the cue for attention from
the usual shape of the fixation stimulus to one of the locations in the
visual field. We found only limited attentional modulation under
conditions that were better predicted by the vector average model, and
the largest attentional modulation under conditions that were better
predicted by the winner-take-all model, even for the same neurons
tested on interleaved trials. These attentional effects were
intermediate in magnitude compared with two recent reports of attention
effects in these visual motion processing areas (Seidemann and
Newsome 1999; Treue and Maunsell 1999
). In the
present experiments we were able to show attentional effects that were
restricted to certain conditions on randomly interleaved trials, and we
believe the results offer a few clues to the conditions under which
attention effects are most prominent.
A brief report of this study has appeared previously (Recanzone
et al. 1993).
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METHODS |
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The general procedures in these experiments were identical to
those described in detail in Recanzone and Wurtz (1999),
and here we will provide those methods that are critical for
understanding the current attention experiments. All procedures were
approved by the Institute Animal Care and Use Committee and complied
with Public Health Service policy on the humane care and use of
laboratory animals.
Target selection task
Two adult male rhesus monkeys (Macaca mulatta) were used in this study (monkeys N and P). Each monkey was trained to perform several versions of two pursuit eye movement tasks, and these tasks are illustrated in Fig. 1. In all versions of the task, there were three steps that are shown in the three columns in Fig. 1. First, the monkey was required to fixate a central stimulus (middle square in left panels of Fig. 1) to within ±2° for a random period of 100-500 ms. Second, two stimuli were presented in motion (Fig. 1, middle panels), but the monkeys were required to maintain fixation for 150 or 450 ms. Third, the fixation stimulus was extinguished (Fig. 1, right panels), and the monkey had to make a saccade to the location of the target and then match the eye movement to the target motion with smooth pursuit to receive a liquid reward. The stimulus conditions were set so that at least one of these two stimuli always moved through the RF of the neuron under study (dashed box in Fig. 1) and so that this stimulus was at the geometric center of the RF when the monkey was released from fixation.
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The cue used in the first set of experiments was the shape of the fixation stimulus. In this shape-cue task, the monkey was instructed which stimulus was to be the target on that trial by the shape of the fixation stimulus that matched the shape of one of the forthcoming targets. For example, in Fig. 1A the square fixation stimulus matched the upward moving target so that correct pursuit was to that target. On other trials the fixation stimulus was a circle, and the monkey was thereby instructed to pursue the downward moving target.
The timing and location of the onset of the stimulus motion was varied. On the short-duration trials shown in Fig. 1A, the stimulus crossed the RF in 150 ms after the start of motion. On the long-duration trials the moving stimuli were displaced in space at the onset of the trial and therefore had a longer trajectory to the center of the RF, but moved at the same velocity. These stimuli reached the center of the RF 450 ms after moving stimulus onset. We term these trial types as "long duration" and "short duration," although it must be emphasized that both the time of motion and the space over which the motion occurred varied between the two stimulus conditions.
The location of the two stimuli was also varied, although one always
moved through the RF of the neuron under study. On half the trials the
other stimulus moved in the same visual hemifield as the RF stimulus
and the two stimuli intersected at the RF center. We refer to these as
"crossed" trials, and they are illustrated in Fig. 1, A
and B (the same convention as used in the previous paper,
Recanzone and Wurtz 1999). On the other half of the
trials, the second stimulus moved in the opposite visual hemifield and did not cross the path of the RF stimulus, and we refer to trials with
this stimulus configuration as "uncrossed" trials, as shown in Fig.
1C. Both short-duration and long-duration trial types were
included in both the crossed and uncrossed trials.
Finally, we used trials with a different cue condition, a location cue. On these trials the monkey was cued as to which visual hemifield the target stimulus would be presented in (Fig. 1D). On this task, all visual stimuli including the fixation stimulus were the same shape, and the moving stimuli were always in different visual hemifields. Short-duration and long-duration trial types were included in the location cue task as well, and of course all of these trials were of the uncrossed type.
We will operationally define the "attended" trials as those in which the monkey selected and made an eye movement to a stimulus passing through the RF and the "unattended" trials as those in which the eye movement was made to the other stimulus. On all trials there were two moving stimuli, and the stimuli in the RF were physically identical between attended and unattended trials. For the uncrossed trials, those in which the stimuli moving through the RF were the targets for the eye movements are termed the attended trials, whereas those in which the identical stimuli passed through the RF but the targets were the stimuli in the opposite visual field are termed the unattended trials. For the crossed trials, the two stimuli always moved through the RF, one in the best direction and one in a nonbest direction. Trials in which the targets moved in the best direction are termed the attended trials, whereas trials in which the target stimuli moved in a nonbest direction while the other stimulus moved in the best direction are termed the unattended trials.
Thus the present analysis compared the neuronal responses to the same
stimulus on the attended and unattended trials. In contrast, the
previous experiments (Recanzone and Wurtz 1999) compared
the neuronal response with one stimulus in the RF on uncrossed trials to the case with two stimuli in the RF on crossed trials to determine whether the integration was better described by an average or a
winner-take-all model. In that previous analysis, the attention to the
stimuli was the same on all the analyzed trials.
Stimuli moved in eight different directions (0, 45, 90, 135, 180, 225, 270, and 315°). For shape cue and location cue uncrossed trials, the
stimulus that was the target moved in any of the eight directions on
any trial, as could the stimulus in the other visual hemifield. For the
shape-cue crossed trials, one stimulus always moved in the best
direction, and the other stimulus moved in one of the seven other
nonbest directions. On these trials, either stimulus could be the
target for the eye movement. In a given session, only location cue
trials or shape cue trials were presented, but within these sessions
all of the stimulus conditions (crossed trials and uncrossed trials,
different target directions) were presented on randomly interleaved
trials, and when long-duration trials were used, they also were
introduced with the other trial types in randomly interleaved order. A
complete data set consisted of at least eight correct trials for each
stimulus type, although most of the data of this report are from 10-15
correct trials for each stimulus type. The majority of neurons were
recorded in both the shape-cue and location-cue types of sessions,
although these could be initiated up to 90 min apart in time. In some
instances, the neuron was lost before a complete data set could be
recorded under both experimental conditions. The results of the
behavioral measures (saccadic and pursuit eye movements) and the
behavioral performance have been reported previously (Recanzone
and Wurtz 1999).
For the shape-cue task, monkey N completed 80 sessions and monkey P completed 65 sessions with short-duration stimuli in which both crossed and uncrossed trials were presented (Fig. 1, A-C). For the location-cue task, monkey N completed 92 sessions and monkey P completed 55 sessions. For the long-duration stimuli, monkey N completed 60 sessions for the shape-cue task and 72 sessions for the location-cue task, but monkey P frequently was unable to reliably suppress the initial saccade for a sufficient period to complete at least 8 trials under all conditions for the long-duration trials (only 13 and 7 sessions with only 3-7 successful trials per stimulus per session for the location-cue and shape-cue task, respectively). Although we found that these limited data were consistent with those obtained in monkey N, this data set is not sufficiently extensive to report in detail in results.
Experimental procedures
Visual stimuli were back-projected onto a tangent screen placed 57.4 cm from the monkey using a video projector (Electrochrome, SVGA, 1,024 × 768 pixel resolution). Each pixel subtended a visual angle of 0.13° horizontally and 0.12° vertically. Images were created by a PC and were presented at a frame rate of 72 Hz. Stimulus objects were brighter (1.8 cd/m2) than the background (0.2 cd/m2). Two of five different objects (circle, square, diamond, plus sign, and triangle) were used in each behavioral session, with each object of equal luminance and size (same number of pixels/object) subtending a maximum visual angle of 1.8°. Objects were moved across the screen by displacing each illuminated pixel by 1 or 2 pixels each frame in either the horizontal, vertical, or both directions. Three stimulus speeds were produced by pixel shifts of 1, 1.5, or 2 pixels/frame corresponding to ~9, 13.5, or 18°/s along the horizontal and vertical directions, and 12, 18.5, or 25°/s along the obliques. For speeds using 1.5 pixels/frame, all stimulus pixels were displaced by 1 and 2 pixels on alternate frames. These stimulus motions were perceived by human observers as continuous, smooth motion.
Monkeys underwent magnetic resonance imaging (MRI) scans in the frontal
and sagittal planes (1.5 T magnet, 3 mm slices) before implantation of
a restraining head post and scleral search coils in each eye. The MRI
images allowed us to direct electrode penetrations into the region of
the superior temporal sulcus just medial to the opening of the sulcus
into a floor. Following initial training, a recording cylinder was
implanted directly over areas MT and MST in the stereotaxic vertical
plane (see Recanzone and Wurtz 1999). Single neuron
activity was recorded in cortical areas MT and MST, whereas horizontal
and vertical eye position was recorded using the magnetic search coil
technique (Fuchs and Robinson 1966
; Judge et al.
1980
). Both eye position and unit activity were monitored on-line as well as stored for off-line analysis. Neurons recorded in
this study met the same three criteria described previously (Recanzone et al. 1997
; Recanzone and Wurtz
1999
): 1) the activity of the neuron was altered by
the presence of visual stimuli (but not necessarily moving stimuli),
2) isolation was sufficient to be confident that only a
single neuron was being recorded, and 3) the center of the
RF was between 5 and 25° of eccentricity. This last requirement was
necessary because the monkeys had difficulty in maintaining fixation if
a stimulus moved through the fixation stimulus before the fixation
stimulus offset and reliably making the visual shape discrimination at
eccentricities >25°.
RFs were defined using hand-held bars, spots, and patterns of light. RF
edges were defined as locations where the neuron no longer responded to
moving, flashed, or stationary visual stimuli. We categorized each
neuron as being located within cortical area MT or MST based on the
location and depth of the electrode within the recording cylinder
relative to the MRI images, and the characteristics of the visual
stimuli required to maximally activate the neuron (Desimone and
Ungerleider 1986; Maunsell and Van Essen 1983
;
Van Essen et al. 1981
). We only rarely encountered
neurons with very large RFs that responded best to large patterned
stimulation similar to those described in the dorsal region of MST
(MSTd) (Komatsu and Wurtz 1988
; Tanaka and Saito
1989
; Tanaka et al. 1986
, 1989
, 1993
), and the vast majority of our sample of MST
neurons were characteristic of those located in the lateral region
(MSTl). However, it is possible that some of the neurons in this study were located within MSTd. Histological sections through the superior temporal sulcus obtained at the end of the experiments showed that the
electrode tracks were consistent with our categorization of neurons
into MT or MST, as described previously (Recanzone et al.
1997
).
The stimulus speed and shape used in a particular behavioral session
was based on the best response of the recorded neuron during
preliminary characterization of the cell's tuning and RF properties
and was adjusted so that the stimulus would traverse as much of the RF
as possible before reaching the center on the short-duration trials. RF
sizes ranged from diameters of 5-24° for neurons recorded in MT, and
5-35° for neurons recorded in MST, and increased in diameter with
increasing eccentricity, as described previously (e.g., Desimone
and Ungerleider 1986; Komatsu and Wurtz 1988
).
Stimulus parameters used were tailored to each neuron under study such
that the onset of the motion stimulus occurred near the edge of the RF.
We noted no differences in the response properties of these neurons
under the different stimulus conditions when the stimulus onset was
slightly within, at, or slightly outside the edge of the RF, and thus
all data were pooled.
Data analysis
For the responses of individual MT and MST neurons reported here, the firing rate was measured during the period from the onset of the moving visual stimuli to the onset of the initial saccade for all correct trials. The firing rate before the onset of the moving stimulus was also calculated (spontaneous activity) and subtracted from the driven activity. For each neuron, the best direction was defined as the stimulus direction that gave the largest response during the uncrossed trials. The null direction was defined as the direction 180° from the best direction. Given the low occurrence of incorrect trials, we were not able to directly compare the responses of correct and incorrect trials.
We used an attention index that was a contrast ratio calculated
following the procedures of Treue and Maunsell (1996).
The attention index was defined as the difference in the average
response between attended and unattended trials divided by the sum of
the response. This value varies from
1.0 (no attended response) to +1.0 (no unattended response), with zero where there is no difference between the responses under the two conditions.
The effect of attention on the response to different directions of motion was defined by the vector strength. For the uncrossed trials, a vector was defined for each direction of motion with the vector direction equal to the direction of the target motion and the amplitude of the vector as the neural response (mean spikes/trial). These vectors were then summed and divided by the total number of spikes. This metric varies from zero (no directional tuning) to one (all responses for only one direction). For the crossed trial condition, because one stimulus always moved in the best direction of the neuron, only seven directions of motion could be used in calculating the vector strength. For this analysis, the attended vector strength was calculated from trials in which the target moved in the best direction, and the other stimulus moved in each of the seven nonbest directions. The unattended vector strength was calculated from trials where the nontarget stimulus moved in the best direction and the target stimulus moved in one of seven nonbest directions. To quantify differences between the vector strengths on the attended and unattended trials we used a contrast ratio with the same calculation as for the attention index described above.
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RESULTS |
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Attentional modulation during the shape-cue task
We determined the effect of attending to one of two stimuli moving across the RF on a total of 107 MT neurons and 105 MST neurons in the two monkeys. Figure 2 shows the rasters and peristimulus time histograms from a typical MT neuron during trials in which the two stimuli both crossed the RF and in which the stimulus attended to was indicated by the shape of the fixation stimulus (shape-cue task with crossed stimuli; Fig. 1, A and B). In the left column of Fig. 2 are the attended trials in which the target for the eye movement was moving across the RF of the neuron in its best direction (leftward moving stimulus, indicated to the monkey by the target being a square like the fixation stimulus). In the right column are the unattended trials in which the target for the eye movement moved in the null direction of the neuron (rightward moving stimulus, the fixation stimulus was a circle on these trials). Note that on both the attended and unattended trials the stimuli crossing the RF of the neuron were identical: the only difference in the visual stimulus was the shape of the fixation point, and the only difference to the monkey was which stimulus was the target for the eye movement on a given trial. The response of this MT neuron showed very little difference between the attended and unattended trials when there was only a short temporal and spatial interval between the stimulus motion onset and the time that the stimulus intersected at the RF center (150 ms; short-duration trials, Fig. 2A), and this difference was not statistically significant (2-tailed, unpaired t-test; P > 0.05). In contrast, by separating the two stimuli in time and space between the time of stimulus motion onset and crossing the RF (450 ms; long-duration trials, Fig. 2B), there was clearly a stronger response when the stimulus moving in the best direction was attended (left panel) than when it was not (right panel). There was a statistically significant difference in the response between these two trial types (P < 0.05).
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Across the population of MT neurons, 12/72 (17%) showed statistically significant differences in activity as a function of attention on the short-duration crossed trials (2-tailed unpaired t-test; P < 0.05). These neurons were equally divided between those that showed statistically significant increases (6 neurons) and decreases (6 neurons). In MST, there were 14/73 (19%) neurons showing statistically significant modulation, with 11% showing increases and 8% showing decreases. For the long-duration trials, however, there were 14/27 neurons (52%) in MT that showed statistically significant differences, with only one neuron showing a decrease in activity as a function of attention and the remaining 13 all showing increases. Similarly, 12/33 (36%) of MST neurons had statistically significant modulation, and all neurons showed increases with attention. The median increase in the response on the long-duration trials was 11% for MT neurons and 16% for MST neurons.
To quantify the size of the effect of attention on each neuron, we used
a contrast ratio calculated as the difference between the attended and
unattended trials divided by their sum. Positive values of this index
indicate an increased response with attention, negative values indicate
a reduced response, and zero indicates no change. Figure
3 shows the distribution of attention
indexes. In both MT and MST (Fig. 3A), for the
short-duration trials of the shape-cue task there were approximately
equal numbers of positive and negative values, and the distribution of
attention indexes across the sample was not significantly different
from a population with a mean of zero (P > 0.05).
Comparison between MT and MST similarly showed no statistically
significant difference (2-tailed, unpaired t-test;
P > 0.05). In contrast, for the long-duration trials
(Fig. 3B), in both MT and MST the sample mean was
significantly greater than zero (P < 0.05) between
these trial types, with a mean of 0.17 for MT neurons and 0.15 for MST
neurons. Comparison between MT and MST again showed no statistically
significant difference (P > 0.05). Although the
changes on the long-duration trials were significant, they were
generally small. A doubling of the response (100% increase), which was
approximately the median for these two areas in a previous report (86 and 113% for MT and MST, respectively) (Treue and Maunsell
1996) was only observed in 19% (5/27) of MT neurons and 6%
(4/33) of MST neurons. A 50% increase in the response was observed in
41% (11/27) of MT neurons and 27% (9/33) MST neurons.
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Given that we studied the responses of the same neurons on
long-duration trials as well as short-duration trials in monkey N, we were able to directly compare the modulation due to
attention in these same neurons. Because the attention index is a
highly nonlinear transformation of the responses, to make this
comparison we calculated the difference in the firing rate between the
attended and unattended trials on the short- and long-duration trials
for the same neurons shown in Fig. 3. Figure
4 plots this difference in activity for
the short-duration trials (x-axis) against the long-duration
trials (y-axis) for neurons recorded in MT () and MST
(
). The thin line shows perfect correlation between these two
measures, whereas the heavy line shows the best-fit regression line for
the data pooled between both cortical areas. Most points fell above the
line of unity slope, indicating that the majority of neurons showed a
greater difference in the activity on the long-duration trials as
compared with the short-duration trials. This analysis shows that the
difference in the population distributions of Fig. 3 reflect a
consistent difference in the change in activity on a neuron-by-neuron
basis depending on the trial conditions.
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In summary, these results showed that there were significant differences in neuronal responses between the attended and unattended stimuli in our paradigm only when we used the long spatial/temporal stimulus configuration. We did not find substantial differences in the effect of attention between MT and MST.
Attentional effects on directional tuning
So far we have only considered the effect of attention on the response of the neuron to motion in the best direction, but we also determined the effect of attention on the relative strength of the response in the seven other nonbest directions tested. For this analysis we calculated the vector strength on the attended and unattended trials and compared these vector strengths using a contrast ratio (see METHODS). The results of this analysis for the same neurons described in Fig. 3 are shown in Fig. 5. For the short-duration trials (Fig. 5A) in both MT and MST the population distribution was not statistically significantly different from a population with a mean of zero, which was expected due to the lack of any attention effect for the vast majority of these neurons. For the long-duration trials, in which an effect of attention was observed, the population distribution again was not statistically significantly different from a population with a mean of zero. This indicates that the effect of attention under these experimental conditions is an elevation of the response for all directions of motion, and is not selective for the best direction of motion.
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Paradigm parameters alter the modulation
A number of previous experiments, beginning with those in
extrastriate area V4 (Moran and Desimone 1985), have
found that the influence of attention is best observed when two stimuli
are presented in the RF of the neuron at the same time, as in our crossed trials. To address this issue in the present pursuit-based experiments, we compared the neuronal response on attended and unattended trials when one stimulus passed through the RF and the other
was in the opposite hemifield. These uncrossed trials (Fig.
1C) were interleaved with the crossed trials considered above so that the analysis could be performed on the same neurons. Figure 6 shows the response on uncrossed
trials for the same neuron shown in Fig. 2. For both the short-duration
trials (Fig. 6A) and the long-duration trials (Fig.
6B), there was very little apparent difference in the
activity of the neuron whether the stimulus moving through the RF of
the neuron was attended to or not. As expected, there was no
statistically significant difference in the responses between the
attended and unattended trials for either duration stimulus (unpaired
t-test; P > 0.05 for both short- and
long-duration trials). Across the population of studied neurons, in
area MT there were 10/72 neurons (14%) with statistically significant differences in activity, with 7 showing decreases and 3 showing increases with attention on the short-duration trials. For
long-duration trials, 5/27 neurons (19%) showed a difference, with 4 neurons having increased activity and 1 neuron having decreased
activity with attention. For MST neurons, on the short-duration trials 7/73 neurons (9%) showed a statistically significant difference, with
4 showing increases and 3 decreases in activity with attention. On the
long-duration trials, only 3/33 (10%) showed any difference in
activity, and these neurons all showed increases with attention. Figure
7 shows the attention index for both
areas MT and MST. None of these sample distributions were significantly
different from a population with a mean of zero (t-test;
P > 0.05), and these distributions were also not
statistically significantly different from each other
(P > 0.05). Thus the greatest effect of attention that
we observed in the shape-cue task occurred when the selection was
between two stimuli crossing the RF of the neuron, and there was a
relatively long spatial/temporal interval before the stimuli cross the
RF. The effect was equal in MT and MST.
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In this analysis of the uncrossed trials (Fig. 7) as well as that for
the crossed trials (Fig. 3) we compared the total activity during the
period from the onset of stimulus motion to the start of the eye
movement. If these neurons had a consistent attentional effect with a
long latency, there should be a divergence of the two plots following
that latency (e.g., see Motter 1994a; Seidemann and Newsome 1999
). Alternatively, if the attentional effect was only in the early phase of the response, the two plots should initially
be distinct, and then become similar after the period of the
attentional effect was over. To determine whether there was a
consistent change in the level of activity throughout the trial, we
pooled the responses of the population of neurons. Such a pooling
procedure is shown in Fig. 8 for all MT
neurons that showed a statistically significant modulation. For the
short-duration crossed trials (Fig. 8A), the population
activity was essentially identical throughout both the attended and
unattended trials. In contrast, for the long-duration crossed trials
there was an elevation of activity that began close to the beginning of
the response, reached a plateau, and then decreased throughout the rest
of the trial, largely in parallel with the response to the unattended
stimulus. For the uncrossed trials (Fig. 8B), both the
short-duration and long-duration conditions showed virtually identical
responses for the attended and unattended stimuli. Importantly, there
was no clear difference in the responses as a function of time from the
onset of the stimulus, indicating that the differences in the activity
of these neurons were modulated consistently across the entire stimulus
period. Similar analysis of MST neurons showed the same result. Pooling
the responses across neurons that did not show a statistically
significant effect did not show a difference in the response at any
period during the trial under any stimulus conditions. We also analyzed
these responses using 50- and 100-ms windows throughout the response
period and found essentially the same result (data not shown).
Therefore we did not observe an increased response limited to one
period of the visual response, but rather an increased response on
attended trials that followed the same time course as that on the
unattended trials.
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Any movement of the eyes to the target would not have affected the response in these experiments because we terminated the period in which the visual response was analyzed before the onset of the saccade. We also considered the possibility that the difference in activity could be due to small differences in the eye position before the saccade, which would result in a different retinal image depending on which stimulus was the target. These monkeys were required to maintain fixation throughout the data collection period; however, the eye position criteria was set at ±2° due to the large size of the fixation stimulus. We therefore compared the eye position measured at the start of the trial (time 0 ms of Fig. 1) and the eye position measured before the saccade on the attended and unattended trials. We restricted this analysis to those trials in which the target moved in either the best or null direction, because these opposite directions should yield the greatest difference if the monkey initiated an eye movement before the saccade. We found no statistically significant difference between attended and unattended trials for either time period when measured across the population, or when restricted to only those neurons that showed a statistically significant effect of attention (t-test, P > 0.05). This finding, coupled with the time course analysis of Fig. 8 indicates that small eye movements during the fixation period cannot account for the attentional effect we observed.
Another variable in our experiment is the type of cue used to indicate
which stimulus was to be the target for the eye movement and when it
was given. In the shape-cue task, the monkey was cued which target
shape was to be used on that trial but not where that target was to be
in the visual field. In a separate set of experiments, we used a
location cue rather than a shape cue. The location cue task (Fig.
1D) addressed the possibility that shifting attention to the
appropriate region of visual space before the onset of the moving
stimuli would generate a difference in the neuronal response. In this
task the monkey was cued which hemifield the target stimulus would
appear in, similar to other recent experiments (Seidemann and
Newsome 1999; Treue and Maunsell 1996
,
1999
). We were only able to use uncrossed trials in this
paradigm, because the direction of motion of the target stimulus was
not cued, only the hemifield location. Figure
9 shows the responses of the same MT
neuron illustrated in Figs. 2 and 6 during the location cue task in
which the cue was extinguished once the monkey fixated, and the moving
stimuli then appeared after a 300- to 600-ms fixation period. The
neuronal responses shown in Fig. 9 indicate that there was very little
difference in the response of this neuron even when the attention was
directed to the RF location by an earlier location cue (2-tailed
unpaired t-test; P > 0.05 for both short- and long-duration trials). This lack of attentional modulation was
consistently seen across the sample of both MT and MST neurons in both
monkeys, as well as for both the short-duration and long-duration versions of this task. For MT neurons, only 6/75 neurons (8%) showed
any modulation on the short-duration trials (5 increases and 1 decrease) and only 3/47 (6%) on the long-duration trials (2 increases
and 1 decrease). In MST, only 5/72 neurons (7%) showed modulation on
the short-duration trials (2 increases and 3 decreases) and only 4/45
(9%) showed modulation on the long-duration trials (2 increases and 2 decreases). The frequency distribution of the attention index
emphasizes this result, and under these stimulus conditions the
population of MT or MST neurons was not statistically significantly
different from zero (Fig. 10). Vector
strength analysis as described above for the short- and long-duration
shape-cue task again showed that the population of MT and MST neurons
was not statistically significantly different from a population with a
mean of zero (P > 0.05). Finally, analysis of the
differences in activity as a function of time from stimulus onset
showed the same result as for the uncrossed trials of the shape-cue
task, namely, the lack of any consistent difference in the responses throughout the stimulus period.
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In summary, these results indicate that attending to the visual field location corresponding to the RF of the neuron under study before the onset of the stimulus motion did not significantly effect the firing rate of the vast majority of neurons and indicates that the modulation observed on the long-duration crossed trials of the shape-cue task cannot be simply explained by a shift of attention to the visual field containing the target stimulus. The results support the hypothesis that the long spatial/temporal delay for the stimulus to reach the RF is not in itself sufficient to produce the observed modulation but that it probably must be paired with multiple stimuli in the RF.
Contribution of changes in spontaneous activity
Experiments on the effects of attention in area V4 and inferior
temporal cortex (Luck et al. 1997) have indicated that
attention to the stimuli can alter the spontaneous activity of the
neurons, and have suggested that this change in activity is indicative of a change in the excitability of the neurons during the attention task. We also saw such changes in spontaneous activity during some
experiments, and we therefore compared the spontaneous activity just
before the onset of the visual stimuli when attention was directed
toward and away from the RF location across our sample of neurons. We
compared the firing rate over the 150 ms before the onset of the moving
stimuli on attended trials to the same period before unattended trials.
For the shape cue task, only trials with a 300- to 500-ms fixation
period were used, which was the fixation period used during the
location-cue task, and inspection of the postcue period before the
onset of the moving stimulus showed no indication of an offset or other
stimulus-related response during this 150-ms period. We found no
difference in spontaneous activity for either the short- or
long-duration trials during the shape-cue task, which is reassuring
given that the monkey had no knowledge of the hemifield in which the
target stimulus would later appear. In contrast, for the location cue
trials, we found a small but statistically significant increase in the spontaneous activity on trials in which the monkey was cued that the
target would move through the RF of the neuron under study. This
increase varied between neurons, and the number of trials provided a
strong statistical sample (256-320 trials/neuron), but in the vast
majority of cases this increase in activity was quite small. For MT
neurons, the population average went from 3.47 ± 2.97 (SD) spikes to 4.45 ± 3.75 spikes, with 37/75 individual neurons showing significant differences (all increases) during trials
in which the target was to appear in the RF of the neuron (1-tailed
unpaired t-test, P < 0.05). There
was a similar finding for MST neurons, where the population average
increased from 2.78 ± 1.91 spikes to 3.55 ± 2.61 spikes,
with 34/72 individual neurons showing a statistically significant
difference (again, all increases) during trials in with the target was
to appear in the RF of the neuron.
To show these differences across our sample of neurons, we used the same attention index for the 150-ms prestimulus period for both MT and MST neurons. As expected, the population of neurons did show an average attention index greater than zero (Fig. 11). For area MT neurons, the population average was 0.14 ± 0.22 and 0.07 ± 0.14 for monkeys N and P, respectively. For area MST neurons, the population average was 0.05 ± 0.24 and 0.19 ± 0.27 for monkeys N and P, respectively. Overall, however, these differences in spontaneous activity were small and were not statistically significantly correlated with the difference in the driven activity when measured across neurons in our sample (r = 0.03; P > 0.05).
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DISCUSSION |
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We observed attentional modulation of the responses of MT and MST
neurons to stimulus motion, but only on trials in which the two stimuli
both moved through the RF of the neuron, and only when these stimuli
moved for a longer time and distance before the pursuit initiation.
Attention acted on all directions of motion so that the directional
tuning curve remained the same. The modulation was substantially the
same in MT and MST. We will first consider the relationship between the
current study and our previous study (Recanzone and Wurtz
1999), and then how our observations relate to models of
competitive interactions by attention, consider why our attentional
effects were relatively small, and finally compare a few of our salient
observations with those in previous attentional experiments in
extrastriate cortex.
Relationship to our previous study of the population models
The present experiments continue the analysis of the activity of
MT and MST neurons during pursuit initiation begun in the previous
report (Recanzone and Wurtz 1999). In those experiments, we found that both the monkey's pursuit behavior and the correlated neuronal activity could be described by either a vector average of the
two directions of motion or a winner-take-all in which the response to
one direction prevailed depending on the stimulus conditions. The
winner-take-all model (for both behavior and neuronal modulation) was
the better predictor on trials with a longer spatial/temporal interval
before the two stimuli crossed the RF of the neuron, whereas the vector
average model was the better predictor for the shorter spatial/temporal
interval trials. One concern raised by those experiments was that an
attention effect could account for the results, and indeed recent
studies have shown striking modulation of MT and MST neurons as a
function of attention (Treue and Maunsell 1996
,
1999
), although other studies have shown limited modulation (e.g., Ferrera and Lisberger 1997
;
Newsome et al. 1988
; Seidemann and Newsome
1999
). In the present experiments we addressed the issue of
attention directly by analyzing the MT and MST neuronal responses when
the monkey did and did not attend to a moving stimulus. The effect of
attention is best addressed by comparing the results of our previous
experiments with the effect of attention in the present experiments as
measured by the attention index.
The relationship between the vector average prediction and the
attention index is relatively straightforward, because the vector
average model predicts the same response under both the attended and
unattended conditions. The attention index we used (the difference in
the average response between the attended and unattended trials divided
by the sum of the 2 responses) gives values varying from 1.0 (no
attended response) to +1.0 (no unattended response), with zero being no
difference in the response between the two conditions. When the vector
average model better predicted the neuronal response (the
short-duration crossed trials), the responses should have an attention
index near zero, which is what we observed.
The only time we saw modulations that could be related to the monkey's
attention to a stimulus was when the winner-take-all model better
predicted the behavior and neuronal activity. The relationship between
the winner-take-all prediction and the attention index, however, is
less straightforward because the attention index is a nonlinear
transformation of the data. An attention index of 1.0 will only occur
when there is no response during the unattended trials, which was not
observed in either our uncrossed or our crossed stimulus condition. For
example, even for neurons that respond with 100 spikes for stimuli
moving in the best direction, and 10 spikes for stimuli moving in the
null direction, a winner-take-all model predicts a response of 100 spikes with an attention index of only 0.82 (90/110). Therefore the
winner-take-all model still predicts some response during the
unattended trials, and given the relatively high firing rates for the
crossed trial stimuli (e.g., Fig. 2) (Recanzone and
Wurtz 1999) an attention index greater than zero, but
still <1, is entirely consistent with the winner-take-all model. It is
also difficult to compare directly across our two studies because the
previous study used the uncrossed trials to predict the
responses on the crossed trials, whereas in the present study we compared the responses of the neurons with the identical visual stimulus moving through the receptive field, so that in the two
studies different trial types were compared. Nonetheless, the results
of the present experiment are consistent with those using uncrossed
trials to predict the response of the crossed trials. For the
long-duration crossed trials, 48 and 36% of the MT and MST neurons,
respectively, showed statistically significant differences in activity
consistent with a winner-take-all model. For neurons tested under both
the short- and long-duration conditions, there was a consistently
greater difference in activity on the crossed long-duration attended
trials compared with the short-duration trials, indicating that this
difference in the attentional effect was consistent across neurons.
Taken together, these results show that the trial conditions (long-duration crossed trials) in which there is the strongest tendency for the winner-take-all model to better describe the activity of MT and MST neurons are the same conditions under which the effect of attention is most prominent. It is clear that an attentional mechanism alone cannot account for these results given the lack of attentional modulation observed under other trial conditions: the short-duration trials with the fixation stimulus as the cue, the long-duration trials in which only one stimulus moved through the receptive field of the neuron, or the location-cue trials in which the monkey's attention was to the region of visual space corresponding to the RF of the neuron. The attention effect may be necessary for the shift from an average to a winner-take-all mode, but it is not sufficient. On the other hand, it seems clear that the modulation of neuronal activity, which we have related to attention, is not related to the preparation to move the eye because the modulation varied across conditions even though the eye movement always occurred.
Probably the simplest way to view the results of the present and the previous experiments is in their contribution to the winner take all response mode. In the previous experiments, the longer time of motion before pursuit was enough to allow one stimulus to produce a stronger response in the neuron under study. In the present experiments, the effect of attention to one stimulus was to strengthen the neuronal response to that stimulus. Thus both effects acted to strengthen the response to the one stimulus thereby contributing to the winner take all mode of the response, and the underlying mechanisms are likely to be similar in both cases.
Competitive models of attention
The effects of attention in MT and MST in our experiments are
consistent with neuronal competition models of attention and possibly
also place limits on these models. In the biased competition model of
Desimone and Duncan (1995), when two stimuli appear, they activate two populations of neurons that compete with each other.
Which neurons are active is determined by the effectiveness of the
stimuli activating them (a bottom-up effect). The effect of attention
is to bias this competition toward one population or the other (a
top-down effect). These two populations must be close together for
lateral excitatory or inhibitory interactions to be effective, and this
aspect of the hypothesis arises from the observation that for the
attention to be most effective on the responses of cortical neurons,
the two stimuli must both fall within the RF of the neurons [such as
in the original V4 and IT observations of Moran and Desimone
(1985)
]. In our experiments, we found the greatest effect of
attention when both the attended stimulus and the other stimulus fell
in the RF of the neuron (the crossed trial condition). Our results are
also consistent with a series of experiments showing larger attention
effects with two stimuli in the RF in other extrastriate areas
(Luck et al. 1997
; Moran and Desimone
1985
; Motter 1994a
,b
; Reynolds et al. 1999
; Treue and Martinez Trujillo 1999
;
Treue and Maunsell 1996
, 1999
) but not
those of Seidemann and Newsome (1999)
.
We think our experiments also add a constraint on the characteristics
of the competing neuronal populations: just as the competing populations cannot be too far separated, they also cannot be too close
together. The results of the present study show that when the two
populations are initially very close together in both stimulus space
and time, in our case with similar receptive field locations but
different best directions, attention is much less effective in acting
on one population. We saw the largest attention effect when we also saw
a winner-take-all mode indicating that the neuronal activity of two
subpopulations of activity could be separated, but when the two
populations were so close together that the output was simply an
average, attention was not effective in acting on a subpopulation. The
populations must therefore have some degree of separation that allows
competition between them and then attention can introduce a bias.
Although we have seen this effect in the motion processing neurons in
MT and MST, a similar principle of separation of subpopulations in
order for attention to act might be present in the other extrastriate
areas where attention for stimulus form has been identified and in
other areas more closely related to saccade generation such as
posterior parietal cortex (e.g., Bushnell et al. 1981;
Lynch et al. 1977
; Robinson et al. 1995
;
Steinmetz et al. 1994
) and superior colliculus (Goldberg and Wurtz 1972
; Kustov and Robinson
1996
).
Thus the populations on which the competition acts must be close enough
to be in one RF but not so close that the two populations are
indistinguishable. We previously interpreted the winner-take-all behavior to reflect hypothetical excitatory intracortical connections between columns of neurons with the same best direction and with RFs
along the trajectory of the stimulus, and the vector average behavior
to reflect the interactions between neurons with similar RF locations
but different best directions (see Recanzone and Wurtz
1999, Fig. 13). This organization would be part of the
bottom-up processing within MT and MST on which the top-down influences of attention would act.
Attentional modulation in MT and MST
Our current study was as striking for the number of conditions in
which we did not see modulation as those in which we did, and even when
we did see modulation, the effects were small compared with those
observed in MT and MST for a speed change detection task (Treue
and Maunsell 1996). In our experiments, the median increase in
response in the long-duration crossed trials was 11% for MT and 16%
for MST, whereas for the best case in the Treue and Maunsell
experiments the median modulation was 86% for MT and 113% for MST.
For a direction of motion discrimination task in MT, Seidemann
and Newsome (1999)
found even less modulation than we did, a
median of 8.7%. The magnitude of attentional modulation is clearly
dependent on the conditions under which it is invoked and, although it
is difficult to compare across very different experimental paradigms,
it is worth noting the similarities and differences that we think are
important along with a few that we think probably are not.
Comparing recent results of attentional effects in visual motion
processing areas indicates that at least two factors appear to be
critical for producing attentional modulation in MT and MST. One factor
is the nature of the cue, which in our experiments was either the shape
of the fixation stimulus or the location in the visual field that the
target would appear in, but in neither case was the direction of the
target motion indicated before the trial began. We observed the largest
attentional effect on the long-duration crossed trials of the shape-cue
task, where the monkey presumably identified the target and its
direction of motion before it entering the RF of the recorded neuron.
The larger attention effects in the Treue and Maunsell
(1996, 1999
) experiments were observed under
cueing conditions that provided both the location and the impending
direction of motion of the target. In their task, the stationary cue
was offset from the center of the RF and began its motion to the
nearest edge of the RF before reversing direction, and given the
unvarying trajectory of the stimuli throughout each experimental
session, the monkey likely predicted both the starting direction of
motion and when the target stimulus was about to change direction. The
small effects in the direction discrimination task of Seidemann
and Newsome (1999)
were observed when only cueing the location
of the stimulus to be discriminated. Thus a key difference is that the
Treue and Maunsell design would allow an attentional mechanism to
engage the specific population of neurons that would provide the most
salient information about the stimulus (those with the appropriate best
direction) before the start of the trial, whereas in our experiments
which neurons would be providing this information remained unknown
until after the shape discrimination was made. Furthermore, if it takes
time for the top-down attention effect to develop, our experiments would have minimized the period over which this attention could act.
This is further supported by recent experiments by Treue and
Martinez Trujillo (1999)
, who similarly used a location cue task and saw significant modulation of most of the MT neurons encountered, but they analyzed the responses in a period of 200-1,200 ms after the onset of target motion. Other studies that found little
modulation in MT also indicated the stimulus to be attended for only a
short time before the movement or discrimination was required
(Ferrera and Lisberger 1995
, 1997
;
Newsome et al. 1988
). At least in these motion-based
tasks, a location cue alone might be an inadequate one because it does
not specify the population of neurons related to the relevant stimulus
parameter, in this case the direction of motion.
The other factor is whether both stimuli were in the RF of the neuron.
In our experiments we only saw a modulation when both stimuli passed
through the RF, and in the Treue and Maunsell (1996, 1999
) experiments the effect was substantially stronger
when two stimuli were within the RF. These findings support the
competition model of attention described above, in that there must be
two competing populations of neurons activated by the stimuli before these top-down influences can be observed. This is confounded somewhat
by the relatively small modulations seen with both one and two stimuli
in the RF of the neuron observed by Seidemann and Newsome
(1999)
. The interactions of the type of cue (in this case the
direction of the target vs. the target location) and the stimulus
configurations may account for these differences, although clearly more
experiments are necessary to resolve this issue.
A final consideration of why the effects we observed were smaller than
those of Treue and Maunsell (1996, 1999
)
might be the extent to which attention was concentrated on one
stimulus. In the task that we used most, the shape-cue task, the monkey
had to quickly perform a shape discrimination of two moving visual stimuli, and was cued to initiate pursuit by the offset of the fixation
stimulus. These circumstances are thus quite different from those in
which the monkey was required to attend to only a particular visual
stimulus, and make a lever press response (Treue and Maunsell
1996
). Our monkeys had to attend to the moving stimuli as well
as the fixation stimulus, and this division of attention may have
contributed to the more limited modulation we saw.
Finally there are two issues that we do not think are critical in
producing the attentional modulation. The first is whether our use of a
movement rather than a discrimination could account for our
observations of relatively limited modulation. We consider this very
unlikely because all of our tasks required a movement, but attentional
modulation was associated with only a few conditions. It is also worth
noting that because a number of our paradigms produce little
attentional modulation, whereas all of them produced pursuit movements,
preparation to move seems to be a less likely correlate of the change
in activity than does the effect of attention. In addition, both the
Treue and Maunsell (1996) and Seidemann and
Newsome (1999)
experiments required discriminations rather than
motion-guided movement, but one produced much stronger and the other
weaker modulation than we observed.
The second issue is related to the difficulty of the task: if the task were easy, no attention might be required. In our experiments the monkeys were required not just to detect some change in the visual motion signal but to exactly match its eye speed and direction to that motion. This is arguably a more demanding task than just detecting a change in the motion, and the effect of attention ought to be commensurate with this demand. This is clearly not a determining factor because the tasks in which we observed an attention effect were nearly identical in difficulty to those in which we did not, although difficulty might influence the strength of the attention effect.
In summary, we think that the effectiveness of the cue in engaging
attention, combined with a competitive model of attention, can account
for the results of this and the preceding experiment (Recanzone
and Wurtz 1999). On the long-duration trials the attentional effect was most prominent and the winner-take-all model was a better
predictor of the response because attention had an opportunity to be
engaged. In contrast, we saw little effect of attention and neuronal
responses better predicted by the vector average model on the
short-duration trials. On the uncrossed trials, we saw no attentional
effect (using either the shape or location cue) presumably because the
two competing populations were too far apart for attention to influence
one population over the other. If our reasoning is correct, cueing the
monkeys with both the location and direction of motion of the target
before the onset of the trial should result in a greater attention
effect and both neuronal responses and eye movement metrics that are
even more closely predicted by the winner-take-all model than were
described under the present experimental conditions (Recanzone
and Wurtz 1999
).
Comparison to other studies of attention in extrastriate cortex
Attentional modulation has been observed throughout visual cortex
in the ventral pathway (V1, V2, V4, and IT) (e.g., Haenny and
Schiller 1988; Luck et al. 1997
; McAdams
and Maunsell 1999
; Moran and Desimone 1985
;
Motter 1993
, 1994a
,b
; Reynolds et al. 1999
; Richmond and Sato 1987
), and the
dorsal pathway (MT and MST) (e.g., Ferrera and Lisberger
1997
; Newsome et al. 1988
; Seidemann and
Newsome 1999
; Treue and Maunsell 1996
) including
the parietal cortex (Bushnell et al. 1981
; Lynch
et al. 1977
; Robinson et al. 1995
;
Steinmetz et al. 1994
). Several observations in the
present experiments are worth noting with respect to these other
attention studies in extrastriate cortex.
The first is the specificity of the attention effect. Studies of
attention in area V4 have shown that attention alters not just the
response to stimuli with the best orientation for the neuron, but the
response to the nonbest orientations as well (McAdams and
Maunsell 1999; see also Motter 1993
). The
comparable measure for the neurons sensitive to motion in MT and MST
would be the direction tuning curve, and we found that attention had
little influence on the directional tuning of both MT and MST neurons. This result is in agreement with Treue and Martinez Trujillo
(1999)
, who tested MT neurons using random dot patterns as the
visual stimulus. Thus for both orientation and for direction, attention altered the activity not of just the best stimulus but the range of
stimuli to which the neuron responded and thus did not change the
tuning of the neuron studied. In both cases attention acts to enhance
the information carried by the neuron, not to alter its content.
The second is the relation of changes in the background activity of the
neuron to the magnitude of the attention effect. Luck et al.
(1997) found that larger attention effects in area V4 were accompanied by increases of background activity, and they interpreted these changes as an indicator of the changes in the underlying excitability of the neurons. We also found a significant change in the
background discharge rate but found that the changes were small and
unlikely to be sufficient to explain the attentional modulation. Our
results would suggest that these are parallel events rather than one
being an indicator of the other. But it is also possible that weaker
attention effects that we observed in MT and MST are accompanied by a
lower level of background activity.
Perhaps the most striking finding, and one that we have
considered above, is the inference that attention takes time to
develop. The clearest case of this is the minor attentional effect in
the short-duration shape-cue task when only 150 ms intervened between the identification of the object of attention and the movement and the
more robust attentional effect in the long-duration shape-cue task when
the intervening time was 450 ms. On the short-duration trials, there
was no modulation 300 ms after stimulus motion onset, and by that time
the stimuli were leaving the RF. Such a latency for the attention
effect to develop was also clearly observed by Seidemann and
Newsome (1999), who saw the modulation at ~300 ms after
stimulus onset, similar to observations in V4 (Motter 1994a
,b
).
The latency of the attention effect could also interact with the size
of the RF of the neurons when motion stimuli are used. This factor
could potentially account for the roughly equivalent modulation of MT
and MST neurons in contrast to the larger effect on MST than on MT
neurons described by Treue and Maunsell (1996) and the
lack of modulation in MT seen by Newsome et al. (1988)
. This would occur if attentional effects in MST had a similar time course to those in MT but the stimuli started at the edge of the RF in
both areas; the stimuli would be out of the RF for those neurons with
small RFs sooner than those with larger RFs. If we had allowed a longer
time between target identification and movement initiation, we might
have seen more substantial attentional modulation in MST than in MT
because the added time would have allowed further motion within the RF.
Thus we think that a significant factor in the strength of attentional
modulation is the time taken for the top-down attention effect to
develop, and that this time should be measured not just from stimulus
onset but from the cue for attention.
Thus it seems reasonable to conclude that just as the bottom-up activity has a visual latency that is dependent on the stimulus conditions, the top-down attention modulation also has a latency that is dependent on task conditions. The attention latency may usually be longer than the visual latency, but can be engaged before the appearance of a visual stimulus if the salient features of the target can be predicted. The attention latency must be measured from the onset of the cue rather than the onset of the stimulus, and the nature of that cue undoubtedly alters the attentional latency.
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ACKNOWLEDGMENTS |
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We thank our colleagues at the Center for Neuroscience (particularly K. H. Britten, H. Heuer, and S. Elfar) and at the Laboratory of Sensorimotor Research for suggestions on previous versions of the manuscript, U. Schwarz for support during the collection of data for these experiments, and the National Institutes of Health Laboratory of Diagnostic Radiology Research for providing the MRIs of the monkeys.
Funding was provided by the National Eye Institute (R. H. Wurtz and G. H. Recanzone) and the National Research Council, National Institute on Deafness and Other Communication Disorders Grant DC-02371, The Klingenstein Fund, and the Sloan Foundation (G. H. Recanzone).
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FOOTNOTES |
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Address for reprint requests: R. H. Wurtz, Laboratory of Sensorimotor Research, Bldg. 49, Rm. 2A50, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD 20892-4435.
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Received 21 June 1999; accepted in final form 8 October 1999.
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REFERENCES |
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