focus of spatial attention. Here, we investigated the influence of saccade selection on sensory interactions within single response fields
when two stimuli appeared at different locations within a single RF, SC neuronal activity was reduced compared with when a single
stimulus appeared in isolation within the center of the RF in both the Go-Go and Go/No-Go tasks. In both tasks, a subsequent cue
indicating one stimulus as a saccade target reduced the influence of the second stimulus located within the RF. We found that the time
course of the suppression resulting from the two stimuli was ?130 ms, a time close to that seen in cortex. Finally, we found that the
influence of two stimuli within single RFs of SC neurons changed over time in both the Go-Go and the Go/No-Go tasks. Initially, the
generation and the preceding events such as visual target selec-
tion for saccades (Basso and Wurtz, 1998; Port and Wurtz, 2003;
2002; Carello and Krauzlis, 2004), saccade selection (Glimcher
ing the focus of spatial attention (Goldberg and Wurtz, 1971,
Muller et al., 2005), and perceptual decision making (Horwitz
strate a strong coupling between saccades and shifts of spatial
attention (Kowler, 1990; Kowler and Blaser, 1995; Kowler et al.,
suggesting that physiological mechanisms underlying selection
for attention and selection for action are shared. How this is
implemented within the SC is unknown and is the focus of the
A conceptual model of attention developed from studies in
visual areas V4 and inferotemporal cortex IT is called the biased
competition model (Desimone and Duncan, 1995; Reynolds et
stimuli appear in a single response field (RF), they will compete.
If a single stimulus produces a strong response in a neuron, the
addition of a second, weaker stimulus will reduce the response.
Second, when attention is directed to one of the two stimuli, the
to that stimulus when it is presented in isolation. Thus, attention
appears to modulate sensory responses in cortex (Luck et al.,
1997; Reynolds et al., 1999, 2000). Recent experiments in SC and
frontal eye field (FEF) using multiple stimuli with large spatial
separations demonstrate that neuronal responses are reduced
compared with when a single stimulus appears in isolation
(Schall, 1991, 1995; Schall et al., 1995; Basso and Wurtz, 1998;
striate cortex (Motter, 1993, 1994b; Treue and Maunsell, 1996;
Luck et al., 1997; Recanzone et al., 1997). In SC, when a periph-
eral cue indicates which stimulus will be a saccade target, neuro-
nal activity increases to levels measured in single stimulus trials
(Basso and Wurtz, 1998), suggesting that a cue to shift gaze can
influence sensory interactions arising from the surrounding
Here, we test predictions of the biased competition model
(Desimone and Duncan, 1995; Reynolds et al., 1999) in individ-
ual SC neurons. For SC, the relevant stimulus dimension is loca-
to visually guided saccade tasks to determine whether the biased
competition model could be generalized to spatial location
within the RF of SC neurons. The results demonstrate stimulus
stein Fund. We are grateful to Dr. John H. Reynolds and our colleagues in the laboratory for providing critical
W. McClurkin for analysis software support. We also thank Joshua Smith for expert technical assistance and the
Correspondence should be addressed to Dr. Michele A. Basso, Department of Physiology, University of Wis-
consin, Madison Medical School, 1300 University Avenue, Room 127 SM1, Madison, WI 53706. E-mail:
TheJournalofNeuroscience,December7,2005 • 25(49):11357–11373 • 11357
interactions influencing individual SC
neurons. The interactions were modified
by cues to shift gaze. Our observations are
shift gaze, like attention, modulate the in-
fluence of sensory interactions, providing
attention and saccade selection.
For electrophysiological recording of single
neurons and monitoring eye movements, cyl-
sus monkeys (Macaca mulatta) using standard
procedures as described previously (Basso and
Wurtz, 2002). Anesthesia was induced initially
with an intramuscular injection of ketamine
(5.0–15.0 mg/kg). Atropine (0.5 mg/kg) was
provided to minimize salivation. Monkeys
plastic head holder for restraint and a cylinder
for subsequent microelectrode recording were
mounted on the top of the exposed skull and
secured with titanium screws and dental
acrylic. Plastic hardware allowed subsequent
minimal artifact. For access to the SC, the re-
cording cylinder was placed stereotaxically on
the midline and angled 38° back so that the
electrode penetrations were directed caudo-
rostrally, toward the SC. An antibiotic (Ce-
fadroxil, 25 mg/kg) was given 1 d before the
operation and every day for a minimum of 4 d after the operation. Anal-
gesia was provided by the administration of buprenorphine (0.01–0.03
mg/kg) and Flunixin (1–2 mg/kg) for 48 h postsurgically as needed.
Monkeys recovered for 1–2 weeks before behavioral and physiological
University of Wisconsin–Madison Institutional Animal Care and Use
Committee and complied with or exceeded standards set by the Public
Health Service policy on the humane care and use of laboratory animals.
General behavioral procedures
We used a real-time experimental data acquisition and visual stimulus
generation system (Tempo and VideoSync; Reflective Computing, St.
Louis, MO) to create the behavioral paradigms and acquire eye position
and single neuron data. Monkeys were trained to sit in a custom-
designed primate chair with head fixed during the experimental session
51 cm distance using a digital light projector (DLP) (LP335; Infocus,
60 Hz. The background luminance was 0.28 cd/m2. The visual stimulus
ing) running on a dedicated personal computer (PC) with a 1024 ? 768
VGA video controller (Computer Boards). The PC was a slave device to
is an inherent time limitation in DLPs (both the vertical refresh rate and
the vertical synch pulse), a photocell was placed on the tangent screen,
which sent a signal [a transistor-transistor logic (TTL) pulse] to the
experimental PC providing an accurate measure of stimulus onset.
Control task. Because we used different shapes (triangle and square) in
this task to ensure that SC neurons were not shape selective. The same
number of white pixels made up each isoluminant stimulus (2.17 cd/
m2). The size of the stimuli was scaled with the distance from the fovea,
either 0.6° for distances ?15° or 0.9° for distances ?15°. Initially, mon-
keys looked at a centrally located fixation spot for 800–1500 ms. Then,
either a triangle or a square was displayed on the screen. The target was
placed in the optimal location of the RF of the neuron under study (see
below for RF mapping). At the end of this second delay (800–1000 ms),
the fixation point was removed, and this cued the monkeys to make a
2° square electronic window (if the target was farther than 10°, the win-
and triangle trials were randomized. In this task, before training on the
visual-tonic neurons. A visual (0–200 ms from target onset), a delay
(300–800 ms after target onset), and a saccade (100 ms before to 100 ms
after the onset of a saccade) interval were measured to compare the
neuronal activity in the two conditions. No SC neuron showed any sig-
nificant differences in these two conditions in any of the intervals mea-
sured (t test, p ? 0.05; data not shown). Thus, not surprisingly, we
concluded that our stimuli were neutral to SC neurons before any train-
ing in the tasks.
Go-Go task. After the onset of a centrally located fixation spot for a
random time of 1000–1500 ms, either one or two shapes were presented
The fixation point remained illuminated along with the peripheral stim-
uli for a random delay of 800–1000 ms, and then the fixation point
changed shape to either a triangle or a square (Fig. 1a). After another
800–1000 ms delay, the fixation point turned back to its original spot,
and this was the cue for the monkey to make a saccade to the cued
at that location for 400–600 ms, a liquid reward was provided. The
accuracy criterion was 2° square around the target (if the target was
farther than 10°, the criterion was increased to 3–4° square around the
target). The smallest distance between two stimuli was ?2°, whereas the
largest was ?25°. Importantly the separation between the two stimuli
11358 • J.Neurosci.,December7,2005 • 25(49):11357–11373LiandBasso•CompetitionandSuperiorColliculus
exceeded the size of the windows to discourage averaging saccades and
encourage precise saccades.
Each experimental session consisted of four trial types presented in
(“blocked”) and randomly in a second condition (“interleaved”). One
trial type was a triangle presented in the RF with a triangle cue presented
at the fovea (1T). A second type was a square presented in the RF with a
square cue presented at the fovea (1S). A third type presented both the
and a square cue was at the fovea (2S). We collected, on average, 20–50
trials for each type.
the triangle served as a cue for the Go condition, whereas a square indi-
cated the No-Go condition (Fig. 1b). The square cue indicated that the
monkey had to remain fixating at the central spot for 400–600 ms to
windows nonoverlapping. Thus, averaging saccades were discouraged.
Response field mapping
A stimulus was moved around to assess qualitatively the boundary and
the center of the visual RF of SC neurons. We then placed the triangle
stimulus in the approximate center of the RF and a second stimulus
(square) at any location around the center but, importantly, within the
boundaries of the RF. The placement of the second stimulus was deter-
mined empirically by listening and watching the neuronal discharge on-
line. Because we were interested in accessing stimulus interactions, we
placed the second stimulus within a region of the RF that was likely to
produce suppression, if it existed. However, during data analysis, we
discovered that, in some cases, the two stimuli resulted in enhanced
responses in the averaged discharge (these neurons can be identified on
the population plots in Results). The separation between the two stimuli
was scaled by the diameter of the visual RF. For example, if the diameter
of the field was ?5°, the two stimuli would be located ?2° apart; if the
also placed the two stimuli approximately equidistant from the fixation
point to keep the amplitude of the vector constant. We did not use
neurons with RFs that included the fovea. For some neurons with large
We classified neurons as either buildup or visual-tonic in the single tar-
get, visually guided saccade task using the following statistical criteria.
We computed a baseline measure of activity (200 ms before the onset of
the visual target), a delay period activity (400 ms before a cue), and a
icantly greater activity in the delay period compared with the baseline
(t test, p ? 0.05) and a significantly greater activity in the saccade period
response and had a significantly greater level of activity in the delay
period than the baseline (t test, p ? 0.05) but had no significant differ-
ence between the saccade period and the delay period, we classified the
neuron as a visual-tonic neuron. Examples of each type are shown in
Data acquisition and analysis
Using the magnetic search coil technique (Fuchs and Robinson, 1966)
to horizontal and vertical components of eye position were filtered
(eight-pole Bessel, ?3 dB, 180 Hz), digitized at 16-bit resolution, and
sampled at 1 kHz (CIO-DAS1602/16; Measurement Computing,
Middleboro, MA). The data were saved for off-line analysis using an
interactive computer program designed to display and measure eye po-
sition and calculate eye velocity. We used an automated procedure to
define saccadic eye movements by applying velocity and acceleration
was verified on a trial-by-trial basis by the experimenter. Single neurons
at 1 kHz. Electrodes were aimed at the SC through stainless steel guide
tubes held in place by a plastic grid secured to the cylinder (Crist et al.,
1988). Action potential waveforms were identified with a window dis-
criminator (Bak Electronics, Germantown, MD) that returned a TTL
pulse for each waveform that met voltage and time criteria. The TTL
pulses were sent to a digital counter (PC-TIO-10; National Instruments,
Austin, TX) and were stored with a 1 ms resolution.
Works, Natick, MA). Standard parametric descriptive and inferential
(ANOVA, t tests with modified Bonferroni corrections) statistics were
used (Keppel, 1991). If the data failed to pass normality tests, nonpara-
metric statistics were used. Wilcoxon’s signed-rank test was used for
sample data analyses. To compare the time course of neuronal activity
changes in the different stimulus conditions, we computed receiver op-
erating characteristic (ROC) curves based on signal detection theory
LiandBasso•CompetitionandSuperiorColliculus J.Neurosci.,December7,2005 • 25(49):11357–11373 • 11359
each trial, we divided individual spike trains recorded in the two condi-
tions into 5 ms bins and averaged the discharge rate within the bin. We
then computed the probability that the discharge rate exceeded a crite-
rion. The criterion was incremented from 0 to the maximum discharge
rate for each 5 ms bin, and a probability value was computed for each
criterion. Therefore, a single point on the ROC curve is produced for
each increment in the criterion, and the entire ROC curve is generated
separation between the two distributions, and the area value provides a
measure of the probability that the two curves could be distinguished.
However, whether this value is statistically significant is ambiguous.
Therefore, we performed a permutation test (Efron and Tibshirani,
1998) to determine whether the areas we measured were statistically
reliable. For each 5 ms bin and each neuron, we randomly sampled the
discharge rate 1000 times and generated an ROC curve for each permu-
tation. This resulted in a distribution of ROC areas for every 5 ms time
we determined that the difference between the two curves at that time
point was statistically reliable. We then computed a mean separation
time from all of the significant times across the sample of neurons.
(see Materials and Methods) each as buildup (106) or visual-
rons dorsally in the SC (mean ? SD, 1.1 ? 0.7 mm from the
surface) and buildup neurons below visual-tonic neurons
(mean ? SD, 1.6 ? 0.6 mm from the surface). Subsets of these
neurons were recorded in different tasks (control, Go-Go and
Go/No-Go). In two monkeys, we recorded neurons only during
performance of the Go/No-Go task, and, in two monkeys, we
recorded during both tasks. Of the two that learned both tasks,
the Go/No-Go task. Table 1 shows the breakdown of how many
indicates the number of neurons recorded in both tasks. Note
that the monkeys did not always complete all of the trial types in
all tasks, so particularly in the interleaved conditions, there are
often fewer neurons. Also note that the neurons recorded in the
control task (n ? 15) are excluded from the table.
In most models of competition, neurons with similar properties
ties are mutually inhibitory (Desimone and Duncan, 1995). In
to the activation of two overlapping populations of neurons
(McIlwain, 1975, 1986) reflecting close (generally within 5°) but
reduced level of activity in SC neurons in the two stimulus con-
performed this task in blocked and interleaved trial conditions.
To display the results, we constructed mean spike density
functions for all of the neurons except those showing statistically
significant effects that were opposite our predictions in at least
one interval (for description of intervals, see below or Materials
and Methods). To assess the variability, the results for the indi-
vidual neurons across the entire sample are shown in plots, gen-
24 buildup neurons in interleaved conditions of the Go-Go task,
construct the mean spike density function shown in Figure 3a.
Across this sample of buildup neurons, when a single stimulus
was presented in the center of the RF, we observed a robust dis-
charge of action potentials (Fig. 3a, left panel, red traces 1T).
During the delay period, action potentials were maintained at a
lower level (Fig. 3a, middle panel, red traces 1T). When the fixa-
tion point changed shape, indicating the target for an upcoming
saccade, the activity of buildup neurons increased further (Fig.
3a, middle panel, red traces 1T). Finally, when the fixation point
changed back to its original shape, providing a cue to initiate a
saccade to the target, we observed a robust discharge of action
potentials (Fig. 3a, right panel, red traces 1T). Because the stim-
ulus located at the edge of the RF was also excitatory for the
neurons, a qualitatively similar profile of activity was observed
of buildup neurons was reduced (Fig. 3a, left panel, green traces
neuronal activity seen in buildup neurons showed two possible
profiles. If the stimulus located in the center of the field was
indicated, the activity increased (Fig. 3a, middle panel, green
traces 2T). If the edge stimulus was indicated as the target of the
saccade, the activity increased slightly or remained essentially
unchanged (Fig. 3a, middle panel, yellow traces 2S). Note, how-
ever, that the pair activity was still higher when the cue indicated
the center stimulus compared with when the cue indicated the
edge stimulus. By the time of saccade initiation, the neuronal
activity measured in these two conditions was clearly separate
(Fig. 3a, right panel, green traces 2T, yellow traces 2S). When the
saccade was made to the center of the field, the activity was sta-
across the sample of neurons (Fig. 3a, right panel, red traces 1T,
was made to the edge stimulus, although the saccade-related dis-
charge was less robust (Fig. 3a, blue traces 1S, yellow traces 2S).
Compared with the interleaved target trial conditions, the
neuronal modulations were more robust when the trial condi-
tions were blocked. The results obtained in the blocked target
trial condition for a single buildup neuron are shown in Figure
these were also recorded in the interleaved condition) (Table 1).
the single neuron as well as the sample data, the separation be-
response (Fig. 3b,c, green and yellow traces). This was evident
because the monkeys knew in advance which saccade would be
required (Basso and Wurtz, 1997). Because of the clarity of the
11360 • J.Neurosci.,December7,2005 • 25(49):11357–11373LiandBasso•CompetitionandSuperiorColliculus
trate most of the rest of the results.
Buildup neuron activity across the sample: two
Two excitatory stimuli located within a single RF of SC buildup
neurons resulted in a suppression of neuronal activity compared
To quantify the activity across all of the neurons in our sample
measured the mean neuronal discharge rate in these intervals.
The first 200 ms interval began at the time the stimuli appeared
(visual interval). The second interval (delay 1) was defined as the
400 ms of activity before the onset of the cue. The third interval
began at the time the cue indicated the target and continued for
600 ms (delay 2). The saccade interval was defined as 100 ms
before to 100 ms after saccade onset (for saccade detecting algo-
rithm, see Materials and Methods).
In the blocked condition, 29 of 39 (74%) buildup neurons
showed significantly lower responses in the 2T condition com-
pared with the 1T condition during the visual interval (Fig. 4a,
filled blue circles, points below the unity line), whereas 13 of 24
(54%) showed this in the interleaved condition (Fig. 4a, filled
of 39 (44%) buildup neurons in blocked trials showed signifi-
cantly reduced activity for the 2T condition compared with the
4 of 24 (17%) showed this pattern in interleaved trials (Fig. 4b,
filled green triangles) (t test, Bonferroni corrected, p ? 0.05).
During delay 2, 17 of 39 (44%) showed significantly reduced
activity in blocked trials (Fig. 4c, filled red circles), and 6 of 24
(25%) buildup neurons had significantly reduced activity (Fig.
4b, filled red triangles) in interleaved trials (t test, Bonferroni
corrected, p ? 0.05). Despite the fact that the same saccade was
made in the 2T and 1T conditions, 8 of 39 (21%) neurons had
significantly lower activity during the saccade interval for the 2T
the sample, the differences were significantly different for all in-
tervals except the saccade interval (Wilcoxon’s signed-rank test;
this pattern was more evident when the trial conditions were
presented in blocks.
Buildup neuron activity across the sample: a central cue affects
stimulus interactions in the Go-Go task
When the cue located at the center of the screen appeared, mon-
keys were required to select one of the two stimuli as the saccade
target. Consistent with a biased competition, when the target in
the center location was selected (2T), we expected the level of
neuronal activity to closely match the triangle-alone condition
(1T). Similarly, when the square was indicated as the saccade
target (2S), we expected the neuronal activity to closely match
tical comparisons, and filled rectangles indicate statistically significant differences across all
15 ms) averaged over 32 buildup neurons are shown for each of the four trial types in the
correctly performed trials. Red traces are from 1T trials, blue traces are from 1S trials, green
LiandBasso•CompetitionandSuperiorColliculusJ.Neurosci.,December7,2005 • 25(49):11357–11373 • 11361
that measured during the square-alone condition (1S). This pat-
tern was seen in many buildup neurons (Fig. 3, middle and right
panels). To determine whether this was consistent across our
sample of neurons, we plotted the neuronal activity from the 2T
trials against the neuronal activity in the 2S trials for the visual,
delay 1 and delay 2 measurement intervals (Fig. 4e–g). In the
blocked target trials, we found that 14 of 39 (36%) buildup neu-
rons had significantly (t test, Bonferroni corrected, p ? 0.05)
higher visual responses for the 2T condition compared with the
2S condition (Fig. 4e, filled blue circles, points above the unity
line) in the visual interval. Fourteen of 39 (36%) showed signifi-
cantly higher activity measured during delay 1 (Fig. 4f, filled
green circles), and 24 of 39 (62%) buildup neurons had signifi-
cantly greater activity for 2T compared with 2S during delay 2
Because the monkeys could not know which stimulus would be
identified as a saccade target in the interleaved conditions, we
found few neurons with these differences before the saccade cue
was provided. One of 24 and 2 of 24 showed significant differ-
ences during the visual and delay 1 intervals (Fig. 4e, filled blue
triangles, f, filled green triangles), whereas 7 of 24 (29%) showed
significant differences during the delay 2 interval (Fig. 4g, filled
red triangles) (t test, Bonferroni corrected, p ? 0.05). Consistent
with a biased competition, when a cue indicated a saccade to a
strong stimulus, suppressive stimulus interactions decreased.
the RF), the reduction in stimulus interactions was less obvious.
Across all neurons in the sample, the differences were significant
for the three intervals (Wilcoxon’s signed-rank test; p ? 0.046;
p ? 0.012; p ? 0.001).
We recorded from 17 visual-tonic neurons in the blocked trials,
and nine of these were also recorded in the interleaved trials. We
found that visual-tonic neurons behaved similarly to buildup
neurons. Figure 5 shows the average neuronal activity profile
recorded from 12 visual-tonic neurons (recall that we plotted
spike density functions for all neurons excluding those showing
opposite effects in at least one interval of the task). The initial
200 ms after stimulus onset), green circles and triangles are delay 1 (400 ms before the cue
symbols indicate that the differences between the conditions were statistically significant
same as in a. Each symbol is taken from a single neuron and is an average of 20–50 trials.
ted as averaged, spike density functions (? ? 15 ms) for each of the four trial types. The
the vertical dashed lines and the arrowheads at the bottom of each panel. Filled rectangles
along the bottom of the panels indicate significant differences across the four conditions
Visual-tonic neurons show reduced activity with two stimuli in the RF, and a
11362 • J.Neurosci.,December7,2005 • 25(49):11357–11373LiandBasso•CompetitionandSuperiorColliculus
two stimuli were present in the RF (Fig. 5, red, green, and yellow
Visual-tonic activity across the sample: two stimulus interactions
In blocked trials, 6 of 17, 6 of 17, and 7 of 17 of visual-tonic
neurons had significantly (t test, p ? 0.05, Bonferroni corrected)
lower activity in 2T compared with 1T target trials in all three
measurement intervals (Fig. 6a–c, filled blue, green, and red cir-
cles). In interleaved trials, three of nine (33%) neurons had a
significantly lower level of activity in the 2T condition compared
with the 1T condition in the visual interval (Fig. 6a, filled blue
triangles) (t test, Bonferroni corrected, p ? 0.05). Five of nine
condition during delay 1 (Fig. 7b, filled green triangles), and one
filled red triangles) (t test, Bonferroni corrected, p ? 0.05).
Across all neurons in the sample, the differences were significant
for the visual and delay 1 intervals but not the delay 2 interval
(Wilcoxon’s signed-rank test; p ? 0.001; p ? 0.005; p ? 0.096).
Visual-tonic activity across the sample: a central cue affects
stimulus interactions in the Go-Go task
As we had done for buildup neurons, we plotted visual-tonic
2S condition for each measurement interval (Fig. 6d–f). We
found that, in blocked trials, 7 of 17 (41%) visual-tonic neurons
showed significantly higher visual activity when monkeys knew
they should select a saccade target located in the center of the RF
compared with when they knew they
edge of the RF (Fig. 6d, filled blue circles,
blocked; filled blue triangles, interleaved)
(t test, Bonferroni corrected, p ? 0.05).
This was also evident for delay 1 intervals
(Fig. 6e, filled green circles, blocked; filled
green triangles, interleaved) and delay 2
filled red triangles, interleaved) (t test,
neurons in the sample, the differences
coxon’s signed-rank test; p ? 0.046; p ?
0.010; p ? 0.001).
In extrastriate cortex, sensory interactions
and the ability of attention to bias these
interactions were tested by comparing at-
dissociate stimulus interactions from pro-
cesses related to events preceding eye
movement initiation. Therefore, we re-
corded from buildup and visual-tonic
neurons while monkeys performed the
Go/No-Go task. In our Go/No-Go task,
triangle would be required. When the fix-
indicated that the monkey should hold its
ine stimulus interactions while the monkeys remained fixating
and presumably did not engage in processes leading up to a sac-
cade. We assumed this was analogous to the unattended condi-
tion in previous experiments. We measured neuronal activity in
two variations of this scheme. In one, the triangle was located in
the center of the RF and was always associated with the produc-
of a weak stimulus. Therefore, using this visual stimulus config-
uration, we could assess the influence of cueing a gaze shift to a
strong stimulus on the stimulus interactions. In the second vari-
was still excitatory for the neuron, but it drove the neuron less
well. The square was now located at the center of the RF and
drove the neuron maximally. In this arrangement, we could as-
sess the influence of a cue to shift gaze to a weak (edge) stimulus
on the stimulus interactions.
First, we describe the results from buildup neurons in the
experiments in which the influence of a strong stimulus was as-
sessed (Figs. 7, 8), and we describe results from buildup neurons
in the experiments in which the influence of a weak stimulus was
assessed (Fig. 9). Second, we describe the results from visual-
tonic neurons in the same two stimulus configurations (Figs. 10,
Forty-four neurons were recorded with the trial conditions ran-
domly interleaved, and 47 neurons were recorded with the trial
LiandBasso•CompetitionandSuperiorColliculus J.Neurosci.,December7,2005 • 25(49):11357–11373 • 11363
conditions blocked. Thirty-one of these neurons were recorded
in both the interleaved and blocked conditions (Table 1).
Influence of cueing a strong stimulus in buildup neurons
In Figure 7, we show a single neuron example (Fig. 7a) and an
average of 42 buildup neurons (Fig. 7b) recorded in the blocked
version of the Go/No-Go task. We found three differences in the
neuronal activity in this task compared with the Go-Go task
(Figs. 3c, 7b). First, immediately before the saccade interval, the
the 1T condition more closely in the Go-Go task than in the
Go/No-Go task (Figs. 3c, 7b, right panels, green and red traces).
Second, immediately before the saccade interval, the neuronal
activity in the 2S condition matched the neuronal activity in
the 1S condition more closely in the Go-Go task than in the
Third, and expectedly, there was no saccade-related burst in the
related burst in the 2S condition of the Go-Go task because a
As we observed for the Go-Go task, in the Go/No-Go task,
when two stimuli were presented in the same RF of buildup neu-
rons, the activity was lower than when a single stimulus was pre-
blue, green, and red circles, blocked; blue, green, and red trian-
is a schematic of eye position. The panel on the left is aligned on the onset of the stimuli
Cueing a strong stimulus influences buildup neuron activity. The temporal ar-
Cueing a strong stimulus influences most buildup neurons. Neuronal activity in
11364 • J.Neurosci.,December7,2005 • 25(49):11357–11373 LiandBasso•CompetitionandSuperiorColliculus
gles, interleaved) (t test, Bonferroni corrected, p ? 0.05). At the
time the cue was provided, indicating that a saccade should be
changed. For the sample of 47 neurons recorded in the blocked
condition, 23 of 47 (49%) had a significantly (t test, p ? 0.05,
Bonferroni corrected) higher level of activity in the 2T condition
compared with the 2S condition during the visual interval (Fig.
8e, blue circles, blocked; blue triangles, interleaved). Twenty-
Bonferroni corrected, p ? 0.05). Thirty-six of 47 (77%) showed
the enhancement during the delay 2 interval (Fig. 8g, red circles,
blocked; red triangles, interleaved) (t test, Bonferroni corrected,
p ? 0.05). Thus, a cue indicating a shift of gaze to a strong stim-
ulus reduced the influence of a weak stimulus on SC buildup
from 2T trials, and yellow traces are from 2S trials. Note that, in this version of the task, the
b–d, The neuronal activity measured in the 2T condition was plotted against the neuronal
Cueing a weak stimulus influences buildup neuron activity. a, The temporal ar-
indicate the alignment time. The left panel is aligned on stimuli onset, the middle panel is
2T condition was plotted against the neuronal activity measured in the 2S condition. Each
differences between the conditions were statistically significant ( p ? 0.05). Open symbols
LiandBasso•CompetitionandSuperiorColliculusJ.Neurosci.,December7,2005 • 25(49):11357–11373 • 11365
Fig. 8d; p ? 0.001, Fig. 8e; p ? 0.001, Fig. 8f; p ? 0.001, Fig. 8g).
Influence of cueing a weak stimulus in buildup neurons
In these experiments, the target associated with a saccade (trian-
gle) was presented at the edge of the RF. The No-Go target
stimulus for the neuron. Accordingly, the biased competition
model applied to the SC predicts that a cue to shift gaze to the
ulus located in the center of the RF. Therefore, the activity levels
observed in Figure 7.
Figure 9 shows the average response profile of the 33 buildup
neurons recorded in this version of the task. The same neurons
were recorded in the previous configuration. During all three
intervals, the neuronal activity in the 2T and 2S trial types were
much closer than that seen in the 2T and 2S condition with the
condition, we are interested in the values that were not signifi-
cantly different or were lower in the 2T compared with the 2S
condition. In the blocked condition, 31 of 33 (94%) buildup
neurons had the same or lower activity in the 2T condition com-
pared with the 2S condition during the visual interval (Fig. 9b,
open and filled blue circles, blocked; open and filled blue trian-
gles, interleaved). Twenty-three of 33 (67%) showed the same or
lower activity during the delay 1 interval (Fig. 9c, open and filled
green circles, blocked; open and filled green triangles, inter-
leaved). In the delay 2 interval, 20 of 33 (61%) buildup neurons
2S trials (Fig. 9d, open and filled red circles, blocked; open and
filled red triangles, interleaved). Note also that the 1S condition
was high at the time of the cue because there continued to be a
stimulus in the center of the RF. Thus, cueing a weak stimulus,
did not produce the same enhancement as seen when a strong
stimulus was cued. We will explore this phenomenon more
thoroughly in the section below (see Direct comparison with the
biased competition model).
(Fig. 10). Thirteen were recorded in interleaved trials, and 18
were recorded in blocked trials. Eleven were recorded in both
types (Table 1). The results were qualitatively identical to those
seen in buildup neurons.
Influence of cueing a strong stimulus in visual-tonic neurons
Again, in this condition, we predicted that, if a cue to shift gaze
locations, then 2T activity should be higher than 2S activity.
Across our sample of visual-tonic neurons, respectively, 13 of 18
2T condition during the visual and delay 1 intervals in the
blocked condition (Fig. 10b,c, filled blue and green circles,
blocked; filled blue and green triangles, interleaved) (t test, Bon-
ferroni corrected, p ? 0.05). When monkeys were provided with
filled red circles, blocked; filled red triangles, interleaved) had a
significantly (t test, Bonferroni corrected, p ? 0.05) higher activ-
ity for 2T compared with 2S. Across the sample, significant dif-
ferences were found in all three intervals (Wilcoxon’s signed-
rank test; p ? 0.003; p ? 0.001; p ? 0.002).
labeled “eye” is a schematic of eye position. The alignment of each panel is indicated by the
trials, green traces are from 2T trials, and yellow traces are from 2S trials. Note that, in this
version of the task, the triangle stimulus was placed at the edge of the RF, and the square
2T condition was plotted against the neuronal activity measured in the 2S condition for the
from interleaved target trials. The filled symbols indicate that the differences between the
conditions were statistically significant ( p ? 0.05). Open symbols indicate that differences
were not statistically significant. Blue circles and triangles are data from visual interval
(400 ms before cue onset), and red circles and triangles are data from the delay 2 interval
11366 • J.Neurosci.,December7,2005 • 25(49):11357–11373LiandBasso•CompetitionandSuperiorColliculus
Influence of cueing a weak stimulus in visual-tonic neurons
Recall that, in this condition, we predicted that, if a cue to shift
biased the competition between locations, then 2T activity
should be the same or lower than 2S activity. We recorded from
12 neurons were also recorded in the opposite configuration.
Many visual-tonic neurons showed no significant difference for
2T compared with the 1T condition (Fig. 11b–d, open blue,
green, and red circles, blocked; open blue, green, and red trian-
gles, interleaved). Across the sample, only delay 1 showed signif-
icant differences (Wilcoxon’s signed-rank test; p ? 0.147; p ?
0.036; p ? 0.260).
To provide an explicit test of whether the biased competition
model explained the results we obtained in SC, we adopted an
analysis that was used to assess V2 and V4 neurons (Reynolds et
al., 1999). A selectivity index was compared with a sensory inter-
action index. The values of both indices ranged from ?1 to 1. In
probe stimuli. If a neuron had a negative selectivity index, the
neuron had a smaller response to a probe stimulus compared
with a reference stimulus. If a neuron had a positive selectivity
index, the neuron had a larger response to the probe than to the
reference. The sensory interaction index determined how the
neurons behaved in the presence of the two stimuli together. A
negative interaction index indicated that the neuronal response
to the pair was dominated by the neuronal response to reference
response was dominated by the probe stimulus. The slope of the
line relating the sensory interaction and selectivity indices indi-
attention experiments (Reynolds et al., 1999), comparing the
slope of these two variables with and without attention provided
a way to assess the influence of attention. When attention was
directed to the probe stimulus, the response of the probe domi-
nated the pair response and the slope increased. When attention
was directed to the reference stimulus, the probe had a reduced
influence on the pair response and the slope was reduced. Thus,
et al., 1999, their Figs. 4, 10, 11).
stimulus interactions within the SC, we computed a sensory in-
teraction index and plotted this against a selectivity index (Fig.
12). We used 32 neurons (25 buildup and 7 visual-tonic) re-
corded in both configurations of the task in the interleaved trial
types. We measured the neuronal activity for the neurons when
both stimuli were present (pair) and when only a single stimulus
the sum of these two activities. The ratio of the pair ? reference
activity to the pair ? reference activities was our measure of the
sensory interaction. Negative values indicate that the response of
the neuron is suppressed in the pair condition. Positive values
indicate that the response of the neuron is enhanced in the pair
ing the interval before the presentation of the centrally located
two visual stimulus configurations of the Go/No-Go task. The
configuration in which the triangle (Go cue) was located at
the edge of the RF is shown in Figure 12, a and b. The configura-
RF is shown in Figure 12, c and d. In both cases, the center stim-
was defined as the probe. During delay 1 when the square was
located in the center of the RF and the triangle was located at the
edge of the RF, the slope of the sensory interaction versus the
selectivity index was 0.13 (Fig. 12a). This indicated that the pair
response was little influenced by the probe (the triangle on the
edge of the RF). However, during delay 2, when the triangle was
cued for a saccade to the edge of the RF, the slope increased to
toward a sensory interaction value that favored the probe stimu-
lus response (the points fell more negative, resulting in an in-
difference between these slopes was significant ( p ? 0.05).
In the Go/No-Go task in which the triangle was located in the
center of the RF (reference) and the square was at the edge
1, the slope of the line was positive (0.54) (Fig. 12c). This was
because the reference term in the sensory interaction index was
the triangle would be cued for a saccade. After the cue to make a
saccade to the reference stimulus, during delay 2, the slope de-
displayed in all four panels. For the sensory interaction measure, the mean discharge rate of
neurons during the presentation of two stimuli in a single RF was measured (pair), and the
mean discharge rate of the same neurons when only a single stimulus was presented at the
mean discharge rate of the same neurons when a single stimulus was located at the edge
was divided by the sum of these two quantities. a, Sensory interaction plotted against the
selectivity index for delay 1 using the trials in which the center (reference) stimulus was the
Cue to shift gaze influences sensory interactions in SC neurons. The sensory
LiandBasso•CompetitionandSuperiorColliculusJ.Neurosci.,December7,2005 • 25(49):11357–11373 • 11367
that the cue to the reference stimulus
changed the sensory interaction. The neu-
ronal response became dominated by the
reference stimulus (the points became less
negative, resulting in a decrease in the
slope). The difference in slopes in delay 1
and delay 2 were statistically significant
( p ? 0.05). Thus, we conclude that a cue
to shift gaze, like attention in extrastriate
cortex, influences stimulus interactions in
By presenting two stimuli within single
plained the influence of multiple stimuli
pare the behavior of SC neurons with the
known behavior of neurons within the vi-
sual cortex (Ferrera and Lisberger, 1995,
1997; Treue and Maunsell, 1996; Recan-
zone et al., 1997; Britten and Heuer, 1999;
Reynolds et al., 1999). For the summation
model, we measured the discharge rate of
neurons in the single stimulus cases sepa-
rately (1T and 1S) and summed these two
activities. We then measured the actual
discharge rates in the 2T condition and
constructed plots of the predicted dis-
charge rate against the actual discharge
rate. This computation was performed
we also could explore the dynamics (Fig. 13a–d). We performed
the averaging model, we computed the predicted discharge rates
by summing the neuronal activity for the 1S and 1T conditions
and dividing by 2. We then measured the actual discharge rates
observed in the 2T condition and plotted the predicted rate
In the plots of predicted against actual discharge rates, if the
model explained the data well, we expected to see the points fall
In the visual interval, the summation model did not explain the
observations in SC buildup neurons for either the Go-Go task or
the Go/No-Go task (Fig. 13a, ? and ? symbols). Indeed, the
summation model was a poor predictor of the neuronal activity
for all of the intervals in both task conditions (Fig. 13a–d, red ?
and blue ? symbols). The averaging model, in contrast, was
much better (Fig. 13e–h). For the visual, delay 1, and delay 2
intervals, the neuronal activity in the two stimulus condition, in
both the Go-Go and the Go/No-Go task, was very well explained
by the average of the neuronal discharge seen in the single stim-
ulus conditions (Fig. 13e–g, red ? and blue ? symbols). During
the saccade interval, however, the pattern changed. Few of the
points fell along the averaging line; rather, most fell below the
line, indicating that the neuronal activity during this time was
the two single stimulus condition responses (Fig. 13h, red ? and
blue ? symbols). Indeed, the activity measured in the 2T condi-
tion was most similar to that seen in the 1T condition during the
saccade interval for both the Go-Go task (Fig. 4d) and the Go/
No-Go task (Fig. 8d). This is consistent with a winner-take-all
more apparent for the neuronal activity measured in the Go/
No-Go task than the Go-Go task (Fig. 13h, red ? and blue ?
In visual-tonic neurons, the pattern was similar. For neither
the Go-Go task nor the Go/No-Go task was the summation
model satisfactory to explain the data (Fig. 13a–c, red ? and
blue ? symbols). In contrast, the averaging model was better in
all three intervals, visual, delay 1, and delay 2 (Fig. 14c–e, red ?
task, particularly during the visual interval (Fig. 14a, red ?).
Because the stimuli in our task were very close to one another,
between the 1T and 2T conditions indicated changes in saccade
parameters, such as accuracy, precision, or velocity. To test this,
we measured the endpoint and velocity of saccades in the 1T and
and SD of the endpoints and velocities from 16 experiments in
which the neuronal activity in the 1T condition was significantly
greater than in the 2T condition during the saccade interval (Fig.
8d, filled black circle). We compared the vertical and horizontal
2T condition if they summed the discharge rates from the 1T and 1S conditions is plotted against the actual discharge rates
using an averaging model. For this, the mean discharge rate was computed by summing the discharge rates in the 1T and 1S
11368 • J.Neurosci.,December7,2005 • 25(49):11357–11373 LiandBasso•CompetitionandSuperiorColliculus
eye position for the 1T and the 2T conditions and found that the
conditions (t test, p ? NS; data not shown). As a measure of
saccade precision, we computed the SD of the endpoints for the
1T and 2T conditions. We found here also that the SDs were
statistically indistinguishable in the two conditions (t test, p ?
in saccade velocity between the two conditions (t test, p ? NS;
data not shown). We drew two conclusions from these results.
ual targets in the different conditions. Second, variations in sac-
modulations we observed in the SC neuronal activity.
An important, unresolved question is whether the modulations
seen in the SC arise from mechanisms within the SC itself or
whether they are reflections of processing occurring elsewhere
and are simply passed on to the SC. We reasoned that we could
explore this by comparing the time course of neuronal activity
changes in the different conditions of our task. Moreover, we
could compare the timing of neuronal activity changes in visual-
tonic neurons to the changes in buildup neurons to determine
whether the times differed for these two neuronal classes.
To address this, first we compared the time that neuronal
conditions. Second, we measured the time when the 2T and 2S
activities separated after the cue in the Go/No-Go task. Finally,
we compared the statistically significant times (as determined by
a permutation test) measured in visual-tonic neurons to those
measured in buildup neurons.
We applied ROC analysis to measure time courses. Consider-
ing that top-down modulations may influence stimulus interac-
tions in the blocked condition, we used only the data from the
interleaved condition that were significantly different in the 1T
and the 2T conditions during the visual interval (Fig. 8a, filled
for buildup (n ? 16) and visual-tonic (n ? 5) neurons recorded
we found that the neuronal activity measured in the two condi-
tions separated at a mean time of 132 ms (Fig. 15a, top, dashed
and solid lines) ( p ? 0.05). Visual-tonic neurons had separable
curves at a mean time of 146 ms (Fig. 15a, bottom, dashed and
solid lines) ( p ? 0.05). We next compared the time course of
separation between the 2T and 2S trials for the neurons that had
a significant difference in the 2T and 2S conditions (buildup, 25;
visual-tonic, 8). We found that buildup neurons had a mean
separation time of 127 ms (Fig. 15b, top, dashed and solid lines)
( p ? 0.05). Visual-tonic neurons reached significance at 152 ms
(Fig. 15b, bottom, dashed and solid lines) ( p ? 0.05).
We recorded from buildup and visual-tonic neurons within the
(BassoandWurtz,1998;Pare ´ andWurtz,2001)intwoimportant
ways. First, the stimuli were presented within single RFs of SC
neurons. Second, the cue to make or withhold a saccade to a
target was presented at the fixation point rather than in the pe-
riphery. This required a shape to location transformation.
of saccade selection on SC neuronal activity is similar to the in-
fluence of attention on sensory interactions seen in extrastriate
of a visual stimulus to a saccade, the activity of SC neurons is
dynamic. The readout for saccade generation is initially a vector
average and only later becomes winner-take-all. Each of these
conclusions will be addressed below.
Placing two stimuli within a single RF of a V4, V2 (Moran and
Desimone, 1985; Motter, 1994a,b; Luck et al., 1997; Reynolds et
al., 1999), or middle temporal area MT neuron (Treue and
Maunsell, 1996; Recanzone et al., 1997; Seidemann and New-
neuron compared with the presentation of a single stimulus
alone. When cued to attend to one of two stimuli, the neuronal
activity moves toward the response of the neuron when the at-
tended stimulus is presented in isolation. These results led to the
hypothesis that attention acts to change the sensory responsive-
ness of neurons to stimuli that are not relevant for behavior, the
biased competition model of attention (Desimone and Duncan,
1995; Reynolds et al., 1999).
We wanted to determine whether similar stimulus interac-
would bias the activity of SC neurons in a manner similar to that
seen in cortex. Rationale for these ideas comes primarily from
three sources. First, an influential hypothesis, called the “motor
theory of attention” (Rizzolatti, 1983; Sheliga et al., 1994, 1995;
Kustov and Robinson, 1996), posits that commands to shift gaze
dividing by 2. The solid lines in all panels are the lines of unity. Points falling along this line
indicate that the actual discharge rate was predicted accurately from the modeled discharge
Dynamics of multistimulus integration in visual-tonic neurons. The predicted
LiandBasso•CompetitionandSuperiorColliculusJ.Neurosci.,December7,2005 • 25(49):11357–11373 • 11369
on a large body of psychophysical data (Kowler, 1990; Kowler et
al., 1995; Deubel and Schneider, 1996; Schneider and Deubel,
tion of the FEF (Moore and Fallah, 2001, 2004) and SC (Ca-
vanaugh and Wurtz, 2004; Muller et al., 2005) reveals that intro-
ducing artificial signals in regions of the brain controlling gaze
shifts can enhance sensory processing.
competitive interactions influencing SC neurons (Basso and
Wurtz, 1998; McPeek and Keller, 2002). Electrophysiological
studies in cats (Meredith and Ramoa, 1998) and monkeys (Mu-
noz and Istvan, 1998) reveal long-range competitive interactions
in SC (but see O¨zen et al., 2004). Psychophysical experiments
suggest that there is competition between saccades and fixation
to be mediated by mutual inhibition between the rostral and
caudal SC (Munoz and Wurtz, 1993a,b).
Third, short-range inhibitory mechanisms are likely to exist
within the SC (Lee et al., 1997, 2001). Presenting two stimuli in
succession, within single RFs of superficial layer SC neurons, re-
is presented alone (Rizzolatti et al., 1973, 1974; Wurtz et al.,
1980). Anatomical evidence reveals GABA neurons distributed
uniformly throughout the SC (Mize, 1992; Behan et al., 2002).
The present results demonstrate short-range competitive inter-
actions influencing SC neurons. One hypothesis is that these are
the interactions occur in cortex and are transmitted through the
direct connections to the SC (Graham et al., 1979; Fries, 1984;
Harting et al., 1992). The time course we measured between the
1T and 2T conditions is consistent with the hypothesis that in-
hibitory interactions occur simultaneously in SC and cortex
[?100–150 ms for V4 (Reynolds et al., 1999); ?128–140 ms for
FEF (Thompson et al., 1996)]. A similar conclusion was drawn
either make or withhold a saccade, or, to make a saccade to dif-
ferently shaped targets. Consistent with a biased competition,
when a strong stimulus (defined by the preferred location) was
cued, neuronal activity increased. When a weak stimulus was
cued, the activity also increased, although not as much as when
the strong stimulus was cued (Figs. 7, 9, 10, 11). We found an
with the selectivity index measured for SC neurons before and
after a cue to make a saccade (Fig. 12). When two stimuli were in
the RF of SC neurons, the interaction depended on the task de-
mands. If monkeys chose a saccade target that by itself produced
a weak response (located on the edge of the RF: probe), the sup-
was greater after the cue compared with before the cue (Fig.
12a,b). If monkeys chose a saccade target that alone produced a
strong response (located at the center of the RF: reference), SC
neurons showed less suppression to the pair of stimuli after the
of the phenomenon in extrastriate cortex in which sensory inter-
actions are modified by attention (Reynolds and Desimone,
1999, their Figs. 10, 11). We conclude, therefore, that saccade
actions on SC neurons. These results are consistent with the
neurons in attentional processing (Kustov and Robinson, 1996;
et al., 2005).
visual-tonic neurons. We cannot determine unequivocally the
location of visual-tonic neurons but, because of the general find-
ing that they were located more dorsal to the buildup neurons
and because of the similarity between these neurons and those
recorded by McPeek and Keller (2002), we suspect that these are
the neurons originally described by Sparks and Mays (1980), as
quasi visual neurons. Our results suggest that visual information
reaches buildup neurons before visual-tonic neurons. Because of
(? ? 15) is plotted against time for the 1T (solid lines) and 2T (dashed lines) conditions for
discharge rate of each neuron was normalized to its own maximum rate during the delay 2
interval of the 2T condition. n ? 19 buildup neurons; n ? 7 visual-tonic neurons. Dashed
11370 • J.Neurosci.,December7,2005 • 25(49):11357–11373LiandBasso•CompetitionandSuperiorColliculus
the small number of neurons contributing to the results, addi-
tional experiments are required to determine this conclusively.
Models of the SC in saccade generation have been developed
primarily using single-point visual stimulation (Lee et al., 1988;
1993a,b, 1994; Van Opstal and Kappen, 1993; Das et al., 1996;
large population of active SC neurons (Schiller and Koerner,
1971; Wurtz and Goldberg, 1972; Sparks et al., 1976; Sparks and
Mays, 1980; Munoz and Wurtz, 1995) and that there are excita-
tory connections linking large regions of the SC (McIlwain,
1982), the models fall into the general class of distributed coding
models (Lee et al., 1988; McIlwain, 1991; Quaia et al., 1998,
SC map was summed linearly (Ottes et al., 1986). These models
failed to replicate the well known behavior of saccade averaging
(Findlay, 1982, 1992; Ottes et al., 1984, 1987). When subjects are
asked to look toward one of two stimuli, they are frequently in-
accurate, as if making a movement to an illusory target located
between the two stimuli. To produce more realistic saccade be-
havior, nearby excitation and remote, lateral inhibitory mecha-
1987; Van Opstal and Van Gisbergen, 1989).
Two issues arise. First, is the divisive inhibition required to
produce averaging (Carandini et al., 1997; Britten and Heuer,
1999; Groh, 2001) performed within or downstream of the SC?
Second, is the readout of SC activity dynamic? With time or ad-
ditionalinformation(Coe ¨ffe ´ andO’Regan,1987;HeandKowler,
stimuli was an average of the response of SC neurons to a single
stimulus presented alone, consistent with normalization occur-
ring within the SC at least for the visual and the delay-period
stimulus does not change neuronal activity in SC (Cynader and
Berman, 1972; Goldberg and Wurtz, 1972a), our result also sug-
gests that SC neurons interpret a single large stimulus differently
from two individual stimuli.
We also found that the pattern of normalization changed as
the trial progressed. Initially, the pattern was characteristic of
matched that seen with a single target. This is consistent with the
readout of SC activity changing from a vector average to a
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