Download Rapid enhancement of visual cortical response

Rapid enhancement of visual cortical response
discriminability by microstimulation of the
frontal eye field
Katherine M. Armstrong* and Tirin Moore
Department of Neurobiology, Stanford University School of Medicine, Stanford, CA 94305
Communicated by Charles G. Gross, Princeton University, Princeton, NJ, February 8, 2007 (received for review November 19, 2006)
cognition 兩 gain control 兩 oculomotor 兩 prefrontal cortex 兩 visual perception
C
overt visual attention selectively enhances relevant signals
from among the flood of information that enters the eye.
Perception of attended stimuli is enhanced in a variety of ways
(1–3), but in general discrimination of attended stimuli is
improved (4). Neurophysiological studies in monkeys and functional imaging studies in humans have demonstrated neural
correlates of these perceptual improvements in visual cortex
during attention (5–7). Recent work has implicated saccaderelated circuits in driving modulations of visual processing
during spatial attention. Specifically, subthreshold microstimulation of the frontal eye field (FEF), an area involved in the
control of voluntary saccadic eye movements (8, 9), improves
performance on an attention task (10, 11) and transiently
enhances visual responses in extrastriate area V4 (12, 13). It is
known that voluntary attention improves the discriminability of
V4 neuronal responses (14, 15) and that the enhanced discriminability results from selective changes in the magnitude of visual
responses but not in their reliability (16). Although the effects of
FEF microstimulation on V4 responses mirror those of voluntary
attention in some respects (12, 13), how FEF microstimulation
affects response discriminability and reliability is not known.
We studied the influence of FEF microstimulation on the
ability of V4 neurons to discriminate receptive field (RF) stimuli.
We used receiver-operating characteristic (ROC) analysis (17),
applied to each neuron’s response (18), to quantify how well V4
www.pnas.org兾cgi兾doi兾10.1073兾pnas.0701104104
responses could discriminate two stimuli, and we used this metric
to examine how visual-response discriminability in the population of V4 neurons was affected by FEF microstimulation.
Several hundred ms after visual stimulus onset, response adaptation had markedly reduced the discriminability of V4 responses
to different RF stimuli. However, FEF microstimulation transiently restored response discriminability. Furthermore, the enhancement in discriminability resulted from stimulation-driven
changes in response magnitude but not in response reliability.
Both effects have been observed in V4 neurons during voluntary
attention (16). The enhancement was restricted to responses to
RF stimuli appearing at locations that were aligned with the end
point of the saccade that could be evoked at the stimulation site.
Importantly, enhanced discriminability was apparent immediately after FEF microstimulation, suggesting that the effect of
stimulation on visual representations is direct. These results
suggest that neural circuits involved in voluntary saccade production also modulate representations in the visual cortex during
covert attention.
Results
Visual Response Discriminability. We studied the responses of
single V4 neurons to different RF stimuli in monkeys performing
a passive fixation task. Fig. 1A shows the response of an example
neuron when one of two differently oriented bars was presented
to its RF. Shortly after visual stimulus onset (90–290 ms), this
neuron responded differently to the two test stimuli (paired t test,
P ⬍ 0.01). The ROC curve computed from the onset response
quantifies the extent to which the response discriminates between the two stimuli tested (Fig. 1B). The area under the ROC
curve (AROC), in this case 0.76, is the performance (76%)
expected of an ideal observer if she were to make her decision
about the RF stimulus orientation based solely on the neuron’s
response (17), and it is used here as an index of visual-response
discriminability (18). For the population of 78 neurons, the mean
onset response discriminability varied widely, with a mean 〈ROC
of 0.68. We focused our analyses on the subset of neurons that
individually showed selective responses to the two RF stimuli
(paired t test, P ⬍ 0.05; n ⫽ 37/78, 47%) (Fig. 1C). For this subset
of neurons, response discriminability decayed throughout the
trial and had decreased significantly by 500 ms after visual
stimulus onset (⌬AROC ⫽ ⫺0.23, permutation test, P ⬍ 10⫺12)
(Fig. 1D), despite the fact that the RF stimulus remained stable
throughout the trial. This degradation in discriminability may
reflect the response adaptation often observed in the responses
of V4 neurons to stable RF stimuli (19–21).
Author contributions: K.M.A. and T.M. designed research, performed research, analyzed
data, and wrote the paper.
The authors declare no conflict of interest.
Abbreviations: AROC, area under the receiver-operating characteristic curve; FEF, frontal
eye field; RF, receptive field; ROC, receiver-operating characteristic; SC, superior colliculus.
*To whom correspondence should be addressed. E-mail: [email protected].
© 2007 by The National Academy of Sciences of the USA
PNAS 兩 May 29, 2007 兩 vol. 104 兩 no. 22 兩 9499 –9504
NEUROSCIENCE
Visual attention provides a means of selecting among the barrage
of information reaching the retina and of enhancing the perceptual
discriminability of relevant stimuli. Neurophysiological studies in
monkeys and functional imaging studies in humans have demonstrated neural correlates of these perceptual improvements in
visual cortex during attention. Importantly, voluntary attention
improves the discriminability of visual cortical responses to relevant stimuli. Recent work aimed at identifying sources of attentional modulation has implicated the frontal eye field (FEF) in
driving spatial attention. Subthreshold microstimulation of the FEF
enhances the responses of area V4 neurons to spatially corresponding stimuli. However, it is not known whether these enhancements
include improved visual-response discriminability, a hallmark of
voluntary attention. We used receiver-operator characteristic analysis to quantify how well V4 responses discriminated visual stimuli
and examined how discriminability was affected by FEF microstimulation. Discriminability of responses to stable visual stimuli
decayed over time but was transiently restored after microstimulation of the FEF. As observed during voluntary attention, the
enhancement resulted only from changes in the magnitude of V4
responses and not in the relationship between response magnitude and variance. Enhanced response discriminability was apparent immediately after microstimulation and was reliable within 40
ms of microstimulation onset, indicating a direct influence of FEF
stimulation on visual representations. These results contribute to
the mounting evidence that saccade-related signals are a source of
spatial attentive selection.
P(Hit)
B
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# Neurons
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Time from visual onset (ms)
n=79
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Late Discriminability
Response (sp/s)
A
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A ROC = 0.76
0
0 0.2 0.4 0.6 0.8 1
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shown to depend on the spatial alignment of the visual stimulus
and the activated saccade representation within the RF (13). A
subset of neurons (n ⫽ 49) were tested with RF stimuli that were
either spatially aligned or misaligned with the saccade vector that
could be evoked at the stimulation site (Fig. 3). As expected, for
neurons displaying significant tuning for visual stimuli appearing
at the aligned RF position (n ⫽ 18), microstimulation enhanced
neuronal response discriminability during aligned conditions
(AROCcont ⫽ 0.59, AROCstim ⫽ 0.66, ⌬AROC ⫽ 0.07; permutation
test, P ⬍ 0.02) (Fig. 3A). By contrast, during misaligned conditions, microstimulation did not affect the response discriminability of neurons tuned at the misaligned position (AROCcont ⫽ 0.59,
AROCstim ⫽ 0.58, ⌬AROC ⫽ ⫺0.01; permutation test, P ⬎ 0.7; n ⫽
25) (Fig. 3B).
Response Reliability. The ability of V4 neurons to discriminate
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Early Discriminability
Fig. 1. Visual-response discriminability of V4 neurons. (A) Histograms show
the average response of an example V4 neuron to the onset of a 45° (thick line)
or 135° (thin line) bar presented inside its RF. Rasters (black and gray for 45°
and 135° bars, respectively) show action potentials recorded on individual
trials. The horizontal line above the rasters indicates the analysis window used
to characterize the onset response. (B) ROC curve computed from the onset
responses to the two stimuli. The area underneath the curve yields a measurement of how well the V4 neuron’s response discriminates between the 45°
and 135° bars. This neuron’s response reliably discriminated the two stimuli,
yielding an ROC area of 0.76. (C) Discriminability values (ROC areas) computed
for the population of V4 neurons. Black shading indicates neurons with
significant stimulus tuning during the onset analysis window. (D) Comparison
of discriminability values computed during early (90 ms after visual onset)
versus late (⬎ 500 ms after stimulus onset) analysis windows. The late discriminability values shown here were computed from responses during control
trials only.
We examined the impact of 20–50 ms of subthreshold FEF
stimulation on the visual-response discriminability of simultaneously recorded V4 neurons (Fig. 2). During each experiment,
we selected FEF sites with saccade vectors that corresponded
spatially with the V4 RF. For the example neuron, microstimulation applied 500 ms after visual onset enhanced responses to
the preferred stimulus (paired t test, P ⬍ 0.02) but did not
reliably affect responses to the nonpreferred stimulus (paired t
test, P ⬎ 0.5) (Fig. 2 A). This stimulus-selective response enhancement produced significant stimulus tuning during microstimulation trials (paired t test, P ⬍ 0.02), whereas the responses
during control trials could not differentiate the two oriented-bar
stimuli (paired t test, P ⬎ 0.8). This enhanced discriminability is
reflected in the ROC curves generated from stimulation and
control trials (AROCstim ⫽ 0.86, AROCcont ⫽ 0.55, respectively)
(Fig. 2B).
Microstimulation reliably enhanced response discriminability
for the entire population (⌬AROC ⫽ 0.05; permutation test, P ⬍
0.003; n ⫽ 78) as well as for the neurons that exhibited reliable
tuning at visual onset (⌬AROC ⫽ 0.05; permutation test, P ⬍ 0.02;
n ⫽ 37) (Fig. 2C). Microstimulation could therefore recover
⬇22% of the response discriminability lost during the first half
of the trial. For the tuned neurons, the effect of microstimulation
on response discriminability was correlated with the drop in
discriminability during the trial (Pearson’s correlation, r ⫽ 0.39,
P ⬍ 0.02) (Fig. 2D). Thus, FEF microstimulation appeared to
compensate for the decay in discriminability observed with
stable visual stimuli.
The effect of FEF microstimulation on V4 responses has been
9500 兩 www.pnas.org兾cgi兾doi兾10.1073兾pnas.0701104104
visual stimuli depends on the overall difference in mean responses to different stimuli as well as on response reliability.
Stimulation-driven enhancement of discriminability could reflect an increase in the response difference between different
stimuli and/or a reduction in variability. To determine whether
FEF microstimulation affects response reliability, we examined
the relationship between mean response magnitude (spike
count) and variance across trials (Fig. 4A). Response magnitude
and variance data for the population of tuned neurons (n ⫽ 37)
was pooled and fit with a power function (16, 22) for stimulation
and control conditions. Stimulation and control functions did not
differ in their power terms (powerstimulation ⫽ 1.15, powercontrol ⫽
1.03; paired t test, P ⬎ 0.5) or coefficients (coeffstimulation ⫽ 1.07,
coeffcontrol ⫽ 1.29; paired t test, P ⬎ 0.1). However, stimulation
did significantly increase the mean response to preferred stimuli
(normalized response: stim ⫽ 0.91, cont ⫽ 0.75; paired t test, P ⬍
0.0005), whereas the mean response to nonpreferred stimuli
remained unchanged (stim ⫽ 0.61, cont ⫽ 0.57; paired t test, P ⬎
0.3) (Fig. 4B). These changes in response magnitude increased
the difference between preferred and nonpreferred responses
(normalized response difference: stim ⫽ 0.29, cont ⫽ 0.18;
paired t test, P ⬍ 0.02). Thus, like voluntary attention, FEF
microstimulation improved response discriminability in V4 neurons by selectively enhancing responses to preferred stimuli
without altering response reliability.
Timing. To assess how quickly microstimulation altered V4 re-
sponse discriminability, we examined the subset of experiments
in which very brief trains of microstimulation (20 ms; n ⫽ 16)
were delivered to the FEF site. For these neurons, we compared
the response to an effective visual stimulus with the response to
a blank RF to maximize the sensitivity of the ROC analysis. We
computed a moving 20-ms window average of ROC areas
surrounding the time of FEF microstimulation. Because of the
stimulation artifact, response discriminability during microstimulation was transiently disrupted. However, an increase in
ROC areas was evident immediately after the offset of the
microstimulation train. Already in the first poststimulation time
bin, ROC areas were significantly increased above control
(⌬AROC ⫽ 0.06; permutation test, P ⬍ 0.04) (Fig. 5A). Therefore,
the discriminability enhancement began within 40 ms of the first
FEF microstimulation pulse.
For comparison with the effect of FEF microstimulation, we
examined the influence of a simulated phosphene on response
discriminability in a small number of V4 neurons (n ⫽ 11). The
simulated phosphene, depicted in Fig. 5B, consisted of a translucent Gaussian blob (23) transiently superimposed on the stable
RF stimulus (or the background) late in the trial. As with the
neurons tested with short microstimulation trains, we computed
ROC areas from responses to an effective visual stimulus
compared with responses to a blank RF. In contrast to the effect
of FEF microstimulation, presentation of the simulated phosArmstrong and Moore
A
B
Cont A ROC = 0.55
Stim A ROC = 0.86
RF
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r = 0.39
p < 0.02
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∆ Discriminability
(Onset - Late Cont)
phene disrupted response discriminability. This disruption began
70 ms after the onset of the simulated phosphene, approximating
the visual latency of V4 neurons (24), and persisted for ⬎150 ms.
This finding is consistent with the prediction that the simulated
phosphene should temporarily mask the stable RF stimulus
when presented simultaneously (11, 25) and is consistent with a
previous observation that visual cues can interfere with neuronal
responses to subsequently presented RF targets (26). By comparison, for the longer (50-ms) FEF stimulation trains, discriminability of an effective stimulus from a blank RF was increased
for the duration of the 70-ms analysis window (permutation test,
P ⬍ 0.03; n ⫽ 61).
Discussion
We found that FEF microstimulation increases the ability of V4
neurons to discriminate RF stimuli. V4 response discrimination
decays during the presentation of a stable RF stimulus but is
transiently restored by FEF microstimulation. The increase in
discriminability is restricted to responses to visual stimuli appearing at RF locations aligned with the saccade vector that
could be evoked from the FEF site, whereas discriminability of
stimuli appearing at misaligned locations remains unchanged.
Discriminability enhancement results from changes in response
magnitude but not from changes in response reliability. These
results, along with previous studies using FEF microstimulation
(12, 13), demonstrate that this manipulation modulates visual
Armstrong and Moore
responses in a manner remarkably similar to the well characterized effects of voluntary attention.
We found that stimulation-driven enhancement of response
discriminability is present as soon as it can be measured. By using
very brief trains of stimulation pulses, discriminability enhancement is apparent immediately after the offset of FEF microstimulation. Within the relatively small subset of cells tested with
20-ms trains, the enhancement was reliable in the first time bin
after microstimulation offset. Thus, the restorative influence of
microstimulation on response discriminability takes effect within
40 ms of the first current pulse delivered to the FEF. This finding
addresses an important caveat to recent studies reporting attentional benefits from microstimulation of saccade representations
during psychophysical tasks. The concern is that the observed
effects could be due to an indirect effect of microstimulation (11,
23, 27, 28). Specifically, microstimulation could perhaps induce
a spatially localized experience that could subsequently orient
attention to the veridical stimulus. Although the possibility of
inducing a visual experience, or phosphene, is considered most
often (11, 23, 27, 28), microstimulation could conceivably induce
a variety of experiences, including highly complex or ‘‘psychical’’
ones (29, 30). However, the rapid enhancement in discriminability implies that rather than producing an experience that subsequently attracts attention, FEF microstimulation activates a
neural circuit responsible for modulating visual responses. Moreover, activation of this circuit might underlie the behavioral
PNAS 兩 May 29, 2007 兩 vol. 104 兩 no. 22 兩 9501
NEUROSCIENCE
Fig. 2. Subthreshold FEF microstimulation enhances V4 response discriminability. (A) Twenty-millisecond trains of microstimulation were applied to the FEF
while visual responses were recorded in an example V4 neuron. FEF and V4 electrodes were positioned so that the saccade that could be evoked at the
microstimulation site (red arrow) moved the monkey’s gaze to the RF (dotted circle) of the V4 neuron. Histograms and rasters show the response of the V4 neuron
to a 45° (Left) and 135° (Right) oriented-bar stimulus for stimulation (red) and control (black) trials (10 repetitions). Histograms and rasters are aligned to the
offset of the 20-ms train of subthreshold FEF microstimulation, which was applied 500 ms after visual onset, and to the corresponding period during control trials.
The gray bar above the rasters indicates the 70-ms analysis window used to study the effect of microstimulation on neuronal responses. (B) ROC curves computed
for the neuron shown in A during the late-analysis window for stimulation (red) and control (black) trials. (C) Discriminability for stimulation (red) and control
(black) conditions for the population of stimulus-selective V4 neurons studied. Bar graphs show the distribution of ROC areas (Left ordinate), and colored lines
show the corresponding cumulative distribution functions (Right ordinate). Arrows indicate mean ROC area. (D) The effect of subthreshold FEF microstimulation
on response discriminability was correlated with the change in discriminability that occurred between the visual-onset and the late-trial analysis periods. Dots
show discriminability values for individual neurons, and the line shows the linear best fit.
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Fig. 3. Effect of subthreshold FEF microstimulation on response discriminability for aligned and misaligned visual stimulus conditions. (A) (Left)
During aligned stimulus conditions, the visual stimulus was positioned within
the RF (dotted circle) at the end point of the saccade that could be evoked from
the stimulation site (red arrow). (Right) Late-period discriminability is shown
for stimulation (red) and control (black) conditions for the population of
neurons exhibiting reliable tuning for aligned stimuli. Conventions are as
described in Fig. 2C. (B) (Left) During misaligned stimulus conditions, the visual
stimulus was positioned within the RF (dotted circle) at a location that was
spatially offset from the end point of the saccade that could be evoked from
the stimulation site (red arrow). (Right) Late-period discriminability values for
stimulation (red) and control (black) conditions for the population of neurons
exhibiting reliable tuning for misaligned stimuli. Conventions are as described
in Fig. 2C.
∆ AROC (stim - cont)
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microstim
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improvements observed after FEF microstimulation in animals
performing an attention task (10, 11). In addition, our failure to
produce enhancements of response discriminability with a simulated phosphene is consistent with findings that substitution of
microstimulation with simulated phosphenes does not lead to
improved attentional performance (23, 28). Therefore, unless
No
n-
Mean Spike Count
Fig. 4. Effect of subthreshold FEF microstimulation on response magnitude
and reliability. (A) Relationship between response variance (computed across
trials) and average response (spike count) during the late-analysis window for
stimulation (red) and control (black) trials. Individual dots show the values for
each tuned neuron’s response to preferred and nonpreferred stimuli. Power
functions were fit to the data for stimulation (red line) and control (black line)
conditions. Best-fit equations are shown. (B) Normalized population responses during the late-analysis window for stimulation (red) and control
(black) trials. Error bars indicate the SEM.
9502 兩 www.pnas.org兾cgi兾doi兾10.1073兾pnas.0701104104
Fig. 5. Timing of stimulation-driven effects on discriminability and comparison with the effect of a simulated phosphene. (A) A subset of neurons was
tested with 20-ms trains of microstimulation (four current pulses at 200 Hz).
The average difference in response discriminability (⌬AROC, stimulation minus
control) of preferred (p) and blank (background) stimuli in the RF (dotted
circle) is shown around the time of FEF microstimulation. Shading indicates
SEM. The decrease in discriminability seen during microstimulation is caused
by the stimulation artifact. (B) The effect of a simulated phosphene (Gaussian
brightness patch superimposed on a RF stimulus; Upper) on response discriminability of preferred and blank stimuli was examined in a population of V4
neurons (n ⫽ 11). The difference in ROC area (phosphene minus control) is
shown around the time of the simulated phosphene presentation. Shading
indicates SEM.
our observations were due primarily to antidromic activation of
neurons outside the FEF, e.g., in the lateral intraparietal area
(LIP), our results imply that FEF neurons, perhaps by way of
other structures activated orthodromically, enhance representations in visual cortex during spatial attention. Indeed, the FEF
projects to the superior colliculus (SC) and area LIP, two areas
known to be involved in both saccade control and visual attention (23, 27, 28, 31, 32). Thus, there are several pathways by
which FEF stimulation could act on visual responses.
The conclusion that saccadic representations drive attention is
supported by a number of recent studies. One study that
recorded neuronal activity in the FEF while monkeys performed
covert visual search tasks found that both visual and visuomovement neurons had elevated responses to the search target, a
popout stimulus, although no saccades were made to the target
(33). By contrast, responses of neurons with purely movementrelated activity were suppressed, suggesting that some neurons
participate selectively in saccade production and others participate in covert visual selection. Similarly, another study that
recorded neuronal activity in the SC while monkeys performed
a visual discrimination task found that visuomovement neurons
Armstrong and Moore
Methods
General and Surgical Procedures. Four male monkeys (two Macaca
mulatta and two Macaca fascicularis, 4–10 kg) were used in these
experiments. All experimental procedures were in accordance
with National Institutes of Health Guide for the Care and Use
of Laboratory Animals, the Society for Neuroscience Guidelines
and Policies, and Stanford University Administrative Panel on
Laboratory Animal Care. General experimental and surgical
procedures have been described previously (45). Each animal
was surgically implanted with a head post, a scleral eye coil, and
two recording chambers. Surgery was conducted by using aseptic
techniques under general anesthesia (isoflurane), and analgesics
were provided during postsurgical recovery. Two craniotomies
were performed on each animal, allowing access to dorsal V4, on
the prelunate gyrus, and FEF, on the anterior bank of the
arcuate sulcus.
Visual Stimuli and Behavioral Task. Monkeys were trained to fixate
within a 2–3° diameter error window surrounding a central spot;
250–500 ms after fixation, oriented-bar stimuli (1–4° ⫻ 0.25–
1.0°) were presented for 1–2 s at locations both inside and outside
the RF of the V4 neuron under study. On 50% of experimental
trials, subthreshold microstimulation of an FEF site (20–50-ms
train) was applied 200–500 ms after visual stimulus presentation.
Monkeys were required to maintain fixation throughout the
course of visual stimulus presentation, and only correctly completed trials were included in the analyses. Throughout all
experiments, eye position was monitored with a scleral search
coil and digitized at 200 Hz. All visual stimulus and microstimulation conditions were randomly interleaved and were controlled
by the CORTEX system for data acquisition and behavioral
control.
Responses to two oriented bar stimuli (0°, 45°, 90°, or 135°)
were examined during each experiment, and on each trial visual
stimuli were presented to the RF individually. In a subset of
experiments, stimuli were presented at one of two positions
within the RF: either at the end point of the saccade that could
be evoked with suprathreshold FEF stimulation (the aligned
position) or at another position (the misaligned position). The
misaligned position was chosen to maximize the separation
between the aligned and misaligned positions while still evoking
a reliable response from the V4 neuron. In all experiments, a
Armstrong and Moore
second visual stimulus was also presented outside the RF at the
mirror-image location in either the ipsilateral or upper hemifield
on every trial because the effects of FEF stimulation have been
shown to be greatest in the presence of ‘‘distracter’’ stimuli (12).
Visual stimuli were most often two grayscale bars of orthogonal
orientation (0.5–0.9 Michaelson contrast) but occasionally consisted of two bars of the same orientation but different colors.
The experimenter attempted to select two test stimuli that varied
in their ability to evoke V4 responses, but stimulus tuning was not
characterized before carrying out an experiment. The simulated
phosphene stimulus was a two-dimensional Gaussian brightness
modulation superimposed on the RF stimulus (either the oriented bar stimulus or the background). Simulated phosphenes
were presented for 66 ms at 500 ms after RF stimulus onset, the
time when FEF stimulation would have occurred, although no
microstimulation was ever applied during the simulated phosphene experiments. Visual stimuli were displayed on LCD
(52-cm vertical ⫻ 87-cm horizontal, 60 Hz) and CRT (30-cm
vertical ⫻ 40-cm horizontal, 60 Hz) monitors, positioned 57 cm
in front of the monkey, with photopic background illumination.
Single-Neuron Recording in V4. Single-neuron recordings in awake
monkeys were made through surgically implanted cylindrical
stainless steel or titanium chambers (20-mm diameter) overlying
the prelunate gyrus. Electrodes were lowered into the cortex by
using a hydraulic microdrive (Narishige, Tokyo, Japan). Activity
was recorded extracellularly with varnish-coated tungsten microelectrodes (FHC, Bowdoinham, ME) of 0.2- to 1.0-M⍀
impedance (measured at 1 kHz). Extracellular waveforms were
classified as single neurons by using both template-matching and
window-discrimination techniques (FHC, Bowdoinham, ME)
and Plexon (Dallas, TX). V4 neuron RFs were mapped in a
separate behavioral paradigm in which oriented bars were swept
across the display while the monkey fixated a central spot. The
RFs of V4 neurons studied were in the lower contralateral field
with eccentricities between 5° and 16°.
Electrical Microstimulation of the FEF. Electrical microstimulation
consisted of a 20- to 50-ms train of biphasic current pulses
(0.2–0.25 ms, 200 Hz) delivered with a Grass stimulator (S88)
and two Grass stimulation isolation units (PSIU-6). Current
amplitude was measured by the voltage drop across a 1-k⍀
resistor in series with the return lead of the current source. All
stimulation was delivered by varnish-coated tungsten microelectrodes of 0.2- to 1.0-M⍀ impedance (measured at 1 kHz). In each
monkey, the FEF was first localized on the basis of its surrounding physiological and anatomical landmarks and the ability to
evoke fixed-vector, saccadic eye movements with stimulation at
currents of ⬍50 ␮A (9). During each experimental session, we
mapped the saccade vector elicited at the cortical site under
study with the use of a separate behavioral paradigm (10). The
stimulating electrode was advanced until sites were localized
from which saccades could be evoked into the RF of the V4
neuron under study, and the current threshold for evoking
saccades was measured for this site. Experimental currents were
set at 50% of the FEF site’s saccadic threshold (10–13).
Analyses. Onset responses were characterized by analyzing neural
activity during a 90- to 190-ms window, relative to the presentation of visual stimuli. Stimulation and control trials were
collapsed in all analyses of visual-onset activity. Analyses of the
effects of FEF stimulation on V4 responses were conducted
during a 70-ms time window beginning after the offset of
microstimulation, adjusted for any stimulation artifact, and
during the corresponding period of control trials. This window
was chosen to avoid any indirect effects of disturbances in
fixation after microstimulation on visual responses (13). For the
subset of neurons tested with 20-ms trains of stimulation, a
PNAS 兩 May 29, 2007 兩 vol. 104 兩 no. 22 兩 9503
NEUROSCIENCE
were active during covert shifts of attention (31). Thus, both the
FEF and SC contain neurons that signal the locus of attention.
Moreover, these results suggest that visuomovement neurons
have a dual role in both covert visual selection and saccade
production. These findings are complemented by experiments
that test whether neuronal signaling in the FEF and SC is
necessary for attention by inactivating these areas. Reversible
inactivation of FEF neurons not only impairs saccade production
(34, 35) but has also been shown to increase reaction time in a
covert visual search task that did not require eye movement
responses (36). In addition, reversible inactivation of the SC
produces deficits in target selection that cannot be attributed to
a purely visual or motor impairment (37). Consistent with
neurophysiological studies in monkeys, transcranial magnetic
stimulation experiments provide causal evidence that the attentional role of the FEF is conserved in humans (38–43). Finally,
studies in the barn owl have found that microstimulation of
gaze-control circuits homologous with primate FEF produces
space-specific modulation of auditory responses (44). Thus,
evidence from a diverse set of experimental approaches, species,
and modalities, has accrued to indicate that saccade-related
mechanisms drive spatial attention in the absence of overt
orienting. The improved ability of V4 neurons to discriminate
RF stimuli after FEF microstimulation might account for at least
some of the perceptual benefits of attention.
moving 20-ms analysis window was used to examine the effect of
stimulation.
Stimulus tuning was determined by performing a paired t test
on the responses observed to the two different visual stimuli.
ROC areas were used as an index of stimulus tuning and were
calculated as in a previous study (18) during both the onset- and
late-analysis windows. Specifically, for each trial we computed
the average firing rate during the relevant analysis window (early
or late) for the two visual stimulus conditions. We then computed the probability that the firing rate in preferred and
nonpreferred stimulus conditions exceeded a criterion, P (Hit)
and P (False Alarm), respectively. The criterion was incremented from 0 to the maximum firing rate, and the probability
of exceeding each criterion was computed. Thus, a single point
on the ROC curve is produced for each increment in the
criterion, and the entire ROC curve is generated from all of
the criteria. The area under the ROC curve is a measure of the
separation between the two distributions and provides a measure
of how well the neuronal response discriminates the two visual
stimuli. Differences in ROC areas, at the population level, were
assessed by way of a permutation test on paired samples (46).
The permutation test was carried out by randomly assigning a
coefficient of ⫹1 or ⫺1 to each difference in ROC area (e.g.,
stimulation minus control) and computing the mean difference
across the population. After generating 1,000 of these random
differences, the mean observed difference was compared with
the randomly generated distribution to determine whether it fell
outside of the 95th percentile.
Population response-variance functions were computed and
analyzed as in previous studies (16, 22). Specifically, for all
neurons the variance in spike count (across trials) versus the
average spike count within the analysis window was plotted, and
the data were fit with a power function. Fits were computed for
both stimulation and control conditions, and the resulting power
and coefficient terms were compared with paired t tests. For the
analysis of the effect of microstimulation on response magnitude
in the population, each neuron’s activity was normalized by its
largest average response during all visual stimulus conditions,
and a paired t test was performed. All analyses were performed
on the combined population of neurons from the four monkeys.
Posner MI (1980) Q J Exp Psychol 32:3–25.
Cameron EL, Tai JC, Carrasco M (2002) Vision Res 42:949–967.
Carrasco M, Williams PE, Yeshurun Y (2002) J Vis 2:467–479.
Lee DK, Koch C, Braun J (1997) Vision Res 37:2409–2418.
Moran J, Desimone R (1985) Science 229:782–784.
Kastner S, De Weerd P, Desimone R, Ungerleider LG (1998) Science 282:108–
111.
Reynolds JH, Pasternak T, Desimone R (2000) Neuron 26:703–714.
Bruce CJ, Goldberg ME (1985) J Neurophysiol 53:603–635.
Bruce CJ, Goldberg ME, Bushnell MC, Stanton GB (1985) J Neurophysiol
54:714–734.
Moore T, Fallah M (2001) Proc Natl Acad Sci USA 98:1273–1276.
Moore T, Fallah M (2004) J Neurophysiol 91:152–162.
Moore T, Armstrong KM (2003) Nature 421:370–373.
Armstrong KM, Fitzgerald JK, Moore T (2006) Neuron 50:791–798.
Spitzer H, Desimone R, Moran J (1988) Science 240:338–340.
McAdams CJ, Maunsell JH (1999) J Neurosci 19:431–441.
McAdams CJ, Maunsell JH (1999) Neuron 23:765–773.
Green D, Swets DJ (1966) Signal Detection Theory and Psychophysics (Wiley,
New York).
Britten KH, Shadlen MN, Newsome WT, Movshon JA (1992) J Neurosci
12:4745–4765.
Mountcastle VB, Motter BC, Steinmetz MA, Sestokas AK (1987) J Neurosci
7:2239–2255.
Motter BC (1993) J Neurophysiol 70:909–919.
Moore T (1999) Science 285:1914–1917.
Bichot NP, Thompson KG, Chenchal Rao S, Schall JD (2001) J Neurosci
21:713–725.
Muller JR, Philiastides MG, Newsome WT (2005) Proc Natl Acad Sci USA
102:524–529.
24. Nowak L, Bullier J (1997) The Timing of Information Transfer in the Visual
System (Plenum, New York), pp 205–241.
25. Breitmeyer B (1990) Visual Masking: An Integrative Approach (Oxford Univ
Press, New York).
26. Robinson DL, Kertzman C (1995) J Neurophysiol 74:713–721.
27. Cavanaugh J, Wurtz RH (2004) J Neurosci 24:11236–11243.
28. Cavanaugh J, Alvarez BD, Wurtz RH (2006) J Neurosci 26:11347–11358.
29. Penfield W, Rasmussen T (1950) The Cerebral Cortex of Man: A Clinical Study
of Localization of Function (Macmillan, New York).
30. Blanke O, Landis T, Seeck M (2000) Epilepsy Behav 1:356–361.
31. Ignashchenkova A, Dicke PW, Haarmeier T, Thier P (2004) Nat Neurosci
7:56–64.
32. Bisley JW, Goldberg ME (2003) Science 299:81–86.
33. Thompson KG, Biscoe KL, Sato TR (2005) J Neurosci 25:9479–9487.
34. Dias EC, Kiesau M, Segraves MA (1995) J Neurophysiol 74:2744–2748.
35. Sommer MA, Tehovnik EJ (1997) Exp Brain Res 116:229–249.
36. Wardak C, Ibos G, Duhamel JR, Olivier E (2006) J Neurosci 26:4228–4235.
37. McPeek RM, Keller EL (2004) Nat Neurosci 7:757–763.
38. Grosbras MH, Paus T (2002) J Cogn Neurosci 14:1109–1120.
39. Grosbras MH, Paus T (2003) Eur J Neurosci 18:3121–3126.
40. Smith DT, Jackson SR, Rorden C (2005) Neuropsychologia 43:1288–1296.
41. Ruff CC, Blankenburg F, Bjoertomt O, Bestmann S, Freeman E, Haynes JD,
Rees G, Josephs O, Deichmann R, Driver J (2006) Curr Biol 16:1479–1488.
42. Silvanto J, Lavie N, Walsh V (2006) J Neurophysiol 96:941–945.
43. Taylor PC, Nobre AC, Rushworth MF (2007) Cereb Cortex (2007) 17:391–399.
44. Winkowski DE, Knudsen EI (2006) Nature 439:336–339.
45. Graziano MS, Hu XT, Gross CG (1997) J Neurophysiol 77:2268–2292.
46. Efron B, Tibshirani RJ (1998) An Introduction to the Bootstrap (Chapman and
Hall/CRC, Washington, DC), Ed 2, pp 202–219.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
9504 兩 www.pnas.org兾cgi兾doi兾10.1073兾pnas.0701104104
We thank D. S. Aldrich for technical assistance and J. K. Fitzgerald for
helpful comments on this paper. This work was supported by National
Institutes of Health Grant EY14924, the Pew Charitable Trust, the Sloan
Foundation (to T.M.), and a Howard Hughes Medical Institute Predoctoral Fellowship (to K.M.A.).
Armstrong and Moore