a r t ic l e s

Responses of pulvinar neurons reflect a subject’s
confidence in visual categorizationnpg© 2013 Nature America, Inc. All rights reserved.

Yutaka Komura1,2, Akihiko Nikkuni1, Noriko Hirashima1, Teppei Uetake1 & Aki Miyamoto1
When we recognize a sensory event, we experience a confident feeling that we certainly know the perceived world ‘here andnow’. However, it is unknown how and where the brain generates such ‘perceptual confidence’. Here we found neural correlatesof confidence in the primate pulvinar, a visual thalamic nucleus that has been expanding markedly through evolution. During
a categorization task, the majority of pulvinar responses did not correlate with any ‘perceptual content’. During an opt-out
task, pulvinar responses decreased when monkeys chose ‘escape’ options, suggesting less confidence in their perceptual
categorization. Functional silencing of the pulvinar increased monkeys’ escape choices in the opt-out task without affecting
categorization performance; this effect was specific to the contralateral visual target. These data were supported by a theoreticalmodel of confidence, indicating that pulvinar activities encode a subject’s certainty of visual categorization and contribute toperceptual confidence.
When we are aware of a sensory event, our subjective experiencehas two aspects1–6: one involves perceptual content (for example,
an upward-moving red ball) and the other refers to perceptual
confidence (for example, a confident feeling that we have actuallyperceived it). Studies over last few decades have suggested that
sensory awareness emerges from the thalamocortical complex7–10,
and the study we describe here is focused on the visual thalamus.
The primate visual thalamus has two regions 11–14: the lateralgeniculate nucleus (LGN; the relay from the retina to the primaryvisual cortex) and the pulvinar, the largest thalamic area, which
has expanded during primate evolution and connects with multiple
visual cortices. Based on anatomical connectivity, we hypothesizedthat these two regions of the visual thalamus have different roles inthe two aspects of a subject’s visual experience. To examine theirfunctional roles, we first recorded the single-unit activities whilemonkeys performed the two tasks: a perceptual categorization task,
which we used to evaluate perceptually experienced content, and an
opt-out task15–17, which we used to explore the subjects’ confidence
levels. To test whether the LGN and pulvinar are functionally linked
to perceptual content and confidence, we pharmacologically inactivated these regions.
In a recent study, a theoretical model of confidence wasdescribed, in which a confidence value is calculated by measuring
the distance between the perceived stimulus value and the categoryboundary18. That model produces a close fit to neural responses ofthe orbitofrontal cortex during a categorization task 18,19. We foundthat this model also accounted for the pulvinar responses observedin our experiments and the monkeys’ psychometric function during an opt-out task. Furthermore, the trial-by-trial firing rates ofpulvinar neurons predicted the monkeys’ upcoming behaviors.
These neural and behavioral data together with the ­computationalmodeling indicated that the pulvinar responses likely reflectedconfidence in perceptual categorization. In addition, inactivationof the pulvinar confirmed that the representation of confidence inthe pulvinar was behaviorally used while the monkeys performed
the opt-out task.
RESULTS
Behavioral task and performance
In the perceptual categorization task (Fig. 1a), the color of the first
fixation point (either red or green) indicated which colored cloud of
dots would be the target (target color). After a delay, the random-dots
stimulus (RDS) appeared for 500 ms. Each dot had a color (red or
green) and moving direction (upward or downward). After anotherdelay, the monkey was required to report the direction of the moving cloud of dots of the ‘target color’, either downward or upward by
touching either the left or right bar, respectively. Difficulty of the task
was manipulated by a stimulus matrix in which the ratio of colormotion pairings changed while the ratio of each individual color or
motion remained constant (Fig. 1b). When the proportion of red dots
moving downward (‘red-down pairing ratio’) approached 50%, thestimulus ambiguity increased. In Figure 1c we show the behavioral
result from the initial assessment of two monkeys (for each monkey’s
performance, see Supplementary Fig. 1). The monkey selected a bar
to touch according to its decision about the perceived content fromthe four categories (that is, red-down, red-up, green-down and greenup). For example, in the leftmost stimulus shown in Figure 1b, themonkey made a decision about the motion direction (up or down)in the red or green task–relevant trials, respectively (Fig. 1c). The
proportion of the monkey’s bar choice varied as a function of thestimulus matrix, indicating that the monkey’s visual categorization
fluctuated in relation to the stimulus ambiguity.

1Systems Neuroscience, Human Technology Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, Japan. 2Precursory Research

for Embryonic Science and Technology, Japan Science and Technology Agency, Saitama, Japan. Correspondence should be addressed to Y.K. (komura-y@aist.go.jp).
Received 26 December 2012; accepted 5 April 2013; published online 12 May 2013; doi:10.1038/nn.3393

nature NEUROSCIENCE

VOLUME 16 | NUMBER 6 | JUNE 2013749

Figure 1 Perceptual categorization task.
(a) Sequence of visual events in a trial. At the
beginning of each trial, the color of the fixation
point indicated which colored dots the monkey was
to judge: red (R) or green (G). After the monkeys
fixated, the RDS was presented on the screen.
After another delay, the fixation point dimmed,
signaling the monkey to report the perceived
category by touching the left or right bar when
the dots of task-relevant color moved downward
or upward, respectively. Hues have been modified
for presentation purposes. (b) A stimulus matrix
determined the RDS characteristics, by changing
only color-motion pairing ratios, holding thesum ratios (100%) of individual visual features
constant. Note that the number of the red (orgreen) dots is always the same, and the number ofthe upward (or downward) moving dots is the sameas well. The values surrounded by the dotted circles
in the stimulus matrices are the percentage of red
dots moving downward (‘red-down pairing ratio’).
(c) Proportion of right bar choice (mean ± s.d.) by
two monkeys as a function of the red-down pairingratio (X value surrounded by the dotted circle in b)
for red and green (target color) task–relevant trials.

aTarget color cuea

600 ms300–600 ms

R

Delay 2Go

400–900 ms

Motion

100

Down

Up

Red

X

100 – X

100 – X

X

30

70

50

50

70

30

100

0

70

30

50

50

30

70

0

100

R

G

R

G

R

G

R

G

R

G

45

–1

500

Early phase

50

55

0
500
0
500
Time from the RDS onset (ms)

40

40

30

30

20

20

Solid lines (ratio <50%)
Dotted lines (ratio >50%)

10

10
0

0
0

20

40

60

80 10020

Target color cue
Red

40

Green

20

0

20

40

60

80

100

pairing ratios were negative and positive, respectively (P < 0.001).
We recorded 618 single neurons with visual responses (83 LGN
neurons and 535 pulvinar neurons) and found that the response
magnitude of 163 neurons exhibited V-shaped modulations likethose shown in Figure 2b (for characterization of the responsesof LGN and pulvinar neurons, see Online Methods). Notably, allof the neurons with V-shaped response modulations were locatedin the pulvinar. We averaged the ­instantaneous regression slopes
across the 163 neurons (Fig. 2c) to visualize the time course of thedevelopment of the regression slopes at the population level. We
then estimated the onset of the response modulation by finding
the earliest time of ten consecutive 1-ms bins for which the regression slopes were significantly different from the baseline (Wilcoxon
signed rank test, P < 0.05). In the red task–relevant trials, onsets
of response modulation were 191 ms and
178 ms for the lower and higher ratios of
red-down pairing, respectively. In the green
70
100
task–relevant trials, onsets of response
modulation were 207 ms and 164 ms

500

0

500

0.6
0.4
0.2
0
–0.2
–0.4
–0.6

0

Red-down pairing ratio (%)

750

0

c

Late phase50

60Red-down pairing ratio (%)

Regression slope(normalized)

b

0

80

0

0
500

0

100

60

0

Right

100

Right bar (Up) choice (%)

0

Left

c

Green

Color

b

–1

Firing rate (spikes s )30

Moving dots

G

500 msRed-down pairing ratio (%)
0

Delay 1

N=

Pulvinar responses during a categorization task
The response examples of one pulvinar neuron are shown in Figure 2a.
The neuron exhibited early transient and late sustained responses
during the perceptual categorization task. The late responses
decreased in a graded manner as stimulus ambiguity increased. To
quantify the relationship between the neural responses and stimulus
parameters, we calculated two linear regressions for firing rates
versus the lower and higher ratios (0%, 30%, 45% and 55%, 70%
and 100%) of red-down pairing, separately (Fig. 2b; equation (1) in
Online Methods). The early responses (average firing rates 50–150 ms
after onset of the stimulus) were not affected by changes in the
red-down pairing ratios (permutation test, P > 0.51), whereas
the regression slopes of the late responses (average firing rates of
400–500 ms after the onset of stimulus) on the lower and higher

Firing rate (spikes s )npg© 2013 Nature America, Inc. All rights reserved.

a r t ic l e s

4060

80 1000500Time (ms)Figure 2 Graded modulation of pulvinar responses
with stimulus ambiguity. (a) A representative
response of a pulvinar neuron during theperceptual categorization task. Rastergrams
and spike-density functions show the neuronal
response to each RDS. Red and gray indicate
data in the red and green task–relevant trials,
respectively. The thick horizontal bar indicates theperiod during which the RDS was presented.
(b) Regression slopes for the early and late
responses of a pulvinar neuron (a) versus the lower
ratio (<50%) and higher ratio (>50%) ratios of
red-down pairing (error bars, s.e.m.; n = 211
trials). (c) Time course of the average regression
slope for normalized visual response (normalized
to maximal response magnitude for each neuron)versus the lower (solid line) and higher (dottedline) ratios of red-down pairing, calculated fromthe population data (n = 163 neurons).

VOLUME 16 | NUMBER 6 | JUNE 2013

nature NEUROSCIENCE

a r t ic l e s
a

b
Risky
Error

Home
Right

Left

Behavioral choices

Correct
Right

Left

Correct
Error
Escape

1.0
0.8
0.6
0.4
0.2
0

Escape

Safe
Low

c

30 and 70

0 and 100

0

20
40
60
80
100
Red-down pairing ratio (%)

Low

45 and 55

dNormalized activity

Firing rate (spikes s–1)

60

0.8

0.4
0.2
0

0
0

500

(n = 72)

0.6

0

20
40
60
80 100Red-down pairing ratio (%)

Time from the RDS onset (ms)for the lower and higher ratios, respectively. The results indicatethat the response modulations with stimulus ambiguity appeared
gradually after the onset of RDS.
Pulvinar responses during an opt-out task
Next, we examined whether the V-shaped response modulations
merely reflected physical ambiguity in the stimulus or reflected
perceptual ambiguity in the subject. Using the opt-out task15–17, wereevaluated the pulvinar activities (Fig. 3). In this task, we gave themonkeys the option of abandoning the perceptual discriminationand choosing instead a third bar, touching which always resulted ina small reward (Fig. 3a). We hypothesized that the monkeys would
accept the discrimination (risky option with a big reward only forcorrect trials) when they were confident in their perceptual categorization but would avoid the discrimination and choose a third bar(safe ‘escape’ option with a small reward in all trials) when they wereless confident. The behavioral performance of the monkeys was consistent with the hypothesis because they chose the third bar more
frequently as the stimulus ambiguity increased (Fig. 3b). We theninvestigated the relationship between the pulvinar activities and themonkey’s choice in each trial (Fig. 3c and Supplementary Fig. 2).
The magnitude of the pulvinar post-stimulus activities in the later
epoch decreased (Kruskal-Wallis test, H = 890.4, P < 0.001; with posthoc Steel-Dwass test, P < 0.001) in the order of correct risky choices,
erroneous risky choices and safe escape choices. For all of the testeda> b = categorizations>

S1

nature NEUROSCIENCE

VOLUME 16 | NUMBER 6 | JUNE 2013

Down

Up

b

c 1.0

Correct

0.8
0.6
0.4
0.2
0

Threshold

S2

s

b 1.0

|s – b| = confidence (d)Confidence (d)Figure 4 A model of categorization and confidence. (a) Schematicof the calculation of categorization and confidence during a motioncategorization task with an opt-out option. Each RDS was encoded as a
distribution of values (S1 or S2). In each trial, a stimulus (s) was drawn
from the respective distribution of the values. A categorical choicedepended on comparing the stimulus value and a boundary (s > b ors < b), and a confidence value (d) was determined by calculating the
distance between the two (|s – b|). A risky or escape choice was definedby a confidence value above or below a threshold value, respectively.
(b) Model choices as a function of stimulus parameter, with proportions ofcorrect, error and escape choices plotted. (c) Average confidence values incorrect, error, and escape trials as a function of stimulus parameter.

neurons (n = 72, Fig. 3d), the activity modulation as a function of the red-down pairing ratio displayed V-shaped and inverted
V–shaped patterns for correct (permutation
test, P < 0.001) and erroneous risky choices(P < 0.001), respectively, but was not apparent when the monkey chose the safe escapeoption (P > 0.28).

Computational basis of the pulvinar responses
To assess the response patterns of pulvinar neurons, we used a theoretical model of confidence that has been established in a previous
study18 of a binary categorization task. In the model (Fig. 4a), a binary
choice was determined by comparing the stimulus value and a category boundary (s < b or s > b), and a confidence value was calculated from the distance between the stimulus value and the categoryboundary (|s – b|). In the opt-out task, the subject chose the escape orrisky response when the confidence value was smaller or larger thana threshold value, respectively. This algorithm generated a psychometric function in the model, which replicated the V-shaped pattern
for correct risky choices and the inverted V–shaped patterns for both
erroneous risky choices and safe escape choices (Fig. 4b). Based on
this algorithm, the confidence values (d) as a function of stimulus typeexhibited a V-shaped pattern for correct risky choices, an inverted
V–shaped pattern for erroneous risky choices and a flat pattern forsafe escape choices (Fig. 4c). The modeling results closely matched
the characteristic patterns of the pulvinar activities (Fig. 3d) and suggest that pulvinar responses reflect a subject’s confidence derived froma categorical decision process.

Model choices

npg© 2013 Nature America, Inc. All rights reserved.

1.0

Figure 3 Relationships between opt-out task
performances and pulvinar activities. (a) Outlineof an opt-out task. The reward size was larger incorrect risky trials than in safe trials. A ‘beep’sound signaled when the outcome was an error.
(b,c) Opt-out task performance (b) and pulvinar
activities (c) as a function of stimulus parameter(n = 298 trials). In c, six red-down pairing ratios(0%, 30%, 45%, 55%, 70% and 100%) werecombined into three groups (0% and 100%, 30%
and 70%, and 45% and 55%) based on stimulus
ambiguity. (d) Normalized firing rate (normalized
to maximal response magnitude for each neuron;mean ± s.d.) as a function of stimulus parameterand the monkeys’ choices for all of the tested
neurons (n = 72 neurons).

Error
0

Escape2040
60
80 100Red-down pairing ratio (%)

d

d

Risky

EscapeCorrect

0.8
0.6
0.4

Error

0.2

Escape

0

0

20
40
60
80 100Red-down pairing ratio (%)

751

a r t ic l e sab
Escape choice

1.0
Accuracy

Figure 5 Pulvinar activity predicts the monkeys’ behaviors in the opt-out
task. (a,b) Proportion (mean ± s.d.) of accurate (a) and escape (b) choices
as a function of the normalized firing rates (binned in five ranges) for all
neurons tested during the opt-out task (n = 72 neurons). Note that theaccuracy rates (a) were significantly above chance (0.5, dotted line; onesample sign test, P < 0.01), except that for the bin with the lowest firing
rate (P = 0.61). (c,d) Proportion (mean ± s.d.) of accurate (c) and escape(d) choices as a function of the stimulus parameter, conditioned of highor low firing rates (n = 72 neurons). Note that the accuracy (c) under
any conditions of firing rates and stimulus types was significantly above
chance (0.5, dotted line; one-sample sign test, P < 0.01).

0.5bInactivation

npg

Categorization task
(left visual field)

Categorization
versustask(binary)

Opt-outtask(escape)Correct choice (%)

Pulvinar
100
80
60
40

c
Opt-out task
(left visual field)

Escape choice (%)

60
40

Muscimol
Saline

*

20

* *
*

0

0

20
40
60
80 100Red-down pairing ratio (%)

Opt-out task(right visual field)

60

Muscimol
Saline

40
20
0

0

752

Muscimol
Salined

Escape choice (%)© 2013 Nature America, Inc. All rights reserved.

a

20
40
60
80 100Red-down pairing ratio (%)

0

20
40
60
80 100Red-down pairing ratio (%)

0.8
0.6
0.4
0.2
0

0

c

0.2
0.4
0.6
0.8
Normalized firing rate0

1.0High firing rate
Low firing ratedAccuracy

Escape choice

1.0

Predicting the monkeys’ behaviors from pulvinar activities
We also analyzed whether the pulvinar responses predicted the monkeys’ upcoming behaviors. In Figure 5a,b we plotted the accuracy(proportion of correct choices among risky choices) or likelihoodof escape choices as a function of the firing rates for all the neurons(n = 72, results from individual neurons are available in Supplementary
Fig. 3). When the neurons fired at higher rates, the accuracy increased(Fig. 5a, Kruskal Wallis test, H = 235.3, P < 0.001; with post-hoc
Scheffe test, P < 0.001), whereas the monkeys more frequently chosethe escape options when the neurons fired at lower rates (Fig. 5b,Friedman test, χ2 = 271.6, d.f. = 4, P < 0.001; with post-hoc Scheffe
test, P < 0.001). We then divided the trials into two groups characterized by high or low firing rates based on values that were higher orlower than the median spike count. We plotted accuracy (Fig. 5c)and escape (Fig. 5d) rates as a function of stimulus type for trials
characterized by high or low firing rates. For any stimulus types, theaccuracy and escape rates increased and decreased, respectively, when
the neurons fired at high compared to low rates (Wilcoxon signedrank test, P < 0.01). The results demonstrate that knowing whether
firing rates were high or low improved the predictions of the monkeys’
accurate and escape choices across any stimulus conditions. Such predictability also indicates that the trial-by-trial fluctuations in pulvinar
responses correlated with changes in the subject’s confidence.

1.0

0.5

1.0

0.2
0.4
0.6
0.8
Normalized firing rate

1.0High firing rate
Low firing rate

0.8
0.6
0.4
0.2
0

0
20 40 60 80 100
Red-down pairing ratio (%)

0
20 40 60 80 100
Red-down pairing ratio (%)

Functional silencing effect of the visual thalamus
Next, we examined whether the neural responses in the pulvinar and
LGN were functionally linked to the behaviors in the categorizationand opt-out tasks (Fig. 6a and Fig. 7a, see Supplementary Figs. 4
and 5 for each monkey’s performance). We inactivated the unilateral visual thalamus (the right side) by injecting the GABA receptor agonist muscimol and compared the behavioral data with thoseobtained after saline injections. Inactivation of the pulvinar did not
significantly affect the monkeys’ binary choices in the catgorization
task (Fig. 6b and Supplementary Fig. 6a; Wilcoxon signed-rank
test corrected by Holm-Bonferroni method, P > 0.34) but increased
the monkeys’ choice of the escape option in the opt-out task (Fig. 6c;
P < 0.017). We observed the effects of pulvinar inactivation when
the RDS was presented to the monkey in the visual field that wascontralateral (left side) to the injection site but not when the RDS
was presented in the ipsilateral visual field (right side; Fig. 6d;
P > 0.77). In contrast, inactivation of the LGN impaired performanceon the categorization task (Fig. 7b; P < 0.039; but see Supplementary
Fig. 6b for the RDS presented in the right hemifield, P > 0.57) andincreased the frequency of the escape choice in the opt-out task
(Fig. 7c; P < 0.002). These results indicate that the pulvinar is crucial
for perceptual confidence but is not necessary for perceptual categorization, whereas the LGN underpins both perceptual categorizationand confidence.
Functional topography of the pulvinar
Finally, we investigated the functional map of the pulvinar (Fig. 8).
Based on the anatomical scheme in some previous studies20–22,
we divided the pulvinar into dorsal and ventral parts, which wereseparated at the level of the brachium of the superior colliculus(Supplementary Fig. 7). We reconstructed the recording sites using
Figure 6 Selective effects of inactivating the pulvinar on the tasks.
(a) Reversible inactivation of the right pulvinar (n = 22 sites, twomonkeys) during the perceptual categorization task and the opt-out task.
(b–d) Behavioral performance (mean ± s.e.m.) as a function of stimulus
ambiguity with muscimol versus saline injections. Images show where
RDS was presented on the monitor. Inactivation effects on binary choicesin the categorization task did not appear regardless of whether RDS
was presented on the left side (b) or right side. Significant effects ofinactivation (*P < 0.05, Wilcoxon signed-rank test) on escape choices in
the opt-out task were observed when RDS was presented in the left visual
field (c) but not when RDS was presented in the right visual field (d).

VOLUME 16 | NUMBER 6 | JUNE 2013

nature NEUROSCIENCE

a r t ic l e s

DISCUSSION
Using a combination of psychophysics, neural recordings and theoretical modeling, we identified the neural correlates of confidence inthe primate pulvinar. Previous studies have shown that the pulvinar

a

b

A8

A8

dPUL

BSC
vPUL
A7

A7

dPUL

BSC

npg

© 2013 Nature America, Inc. All rights reserved.

vPUL
A6

A6

dPUL

BSC

Categorization
versustask(binary)

Opt-outtask(escape)

LGN

b

c

Categorization task
(left visual field)

Opt-out task
(left visual field)
60

100
80
60

*

*

* *

*

*

Escape choice (%)

MRI (magnetic resonance imaging) scans (Fig. 8a) and locatedthe 247 neurons (164 in the dorsal pulvinar and 83 in the ventral
pulvinar) with the types of response modulation identified during
the categorization task. The majority of dorsal pulvinar neurons(n = 141 neurons, 86.0%) exhibited V-shaped response modulations,whereas we observed this type of response modulation less frequently
for ventral pulvinar neurons (n = 22, 26.5%). Moreover, all muscimoltreated sites that resulted in increasing escape rates during the opt-out
task were located in the dorsal pulvinar (Fig. 8b).

a Inactivation

Correct choice (%)

Figure 7 Effects of inactivating the LGN on the task performance.
(a) Reversible inactivation of the right LGN (n = 16 sites, two monkeys)
during the two types of task when RDS was presented in the left
hemifield. (b,c) Proportion (mean ± s.e.m.) of correct choices in the binary
categorization task (b) and that of escape choices in the opt-out task (c)as a function of stimulus ambiguity. Significant effects of inactivation(*P < 0.05, Wilcoxon signed-rank test) were observed in both tasks.

*

*

* *

*

*

40
Muscimol
Saline

20
0

40
0

20
40
60
80 100Red-down pairing ratio (%)

0

20
40
60
80 100Red-down pairing ratio (%)

is involved in visual attention23–28. These studies raise a possibility
that our experimental data may be explained solely by an ‘attention
factor’. First, difficulty of the task owing to the stimulus could changedemands on attention, which potentially caused V-shaped modulations of the pulvinar responses in correct trials. Second, lapses in attention could decrease the firing rate and increase the escape rates in the
opt-out task. The attention factor by itself, however, cannot accountfor the peculiar tuning curves of the pulvinar responses showing theV-shaped and inverted V–shaped modulations in correct and error
trials, respectively (Fig. 3d). Other studies have shown that the pulvinar responses are modulated by eye position29–31, although changes
in eye position do not explain the pulvinar responses described in thecurrent study: pulvinar responses markedly changed as a function of
the stimulus and the monkey’s choice, whereas eye position during thetask was not significantly affected by the different stimuli and monkeys’ choices (Kruskal-Wallis test, P > 0.35; Supplementary Fig. 8).
In contrast, all the patterns of response modulations during correct,
error and escape trials were systematically explained by a confidence
model (Figs. 3d and 4a,c). Additionally, the monkeys’ psychometric function in the opt-out task was also reproduced by this model(Fig. 4b). Finally, the pulvinar activities were predictive of the monkeys’ performances beyond the stimulus information (Fig. 5). These
results led us to conclude that the observed response modulations of
the pulvinar neurons most likely reflect the subject’s confidence.
The experiment of pharmacological inactivation revealed a specificrole of the pulvinar in the tasks: pulvinar inactivation affected optout choices but not visual categorization (Fig. 6). In contrast, inactivation of the LGN affected both categorization and opt-out choices(Fig. 7). From a modeling perspective, we considered inactivation of
the pulvinar to represent conditions in which the distance between the

vPUL
A5

A5

dPUL

BSC
vPUL
V-shaped (–, +)(+, –)(+, +)(–, –)
Neural response

nature NEUROSCIENCE

5 mm

EffectNo effects
Muscimol injection

VOLUME 16 | NUMBER 6 | JUNE 2013

Figure 8 Functional topography of the pulvinar. (a) Locations of neurons
showing the four types of response modulation during the categorization
task are plotted on representative coronal sections of the right thalamus.
Blue and yellow dots indicate neurons with negative-positive (V-shaped)
and positive-negative slopes for the response modulations, respectively.
Red and gray dots indicate neurons with positive-positive and negativenegative slopes, respectively. (b) Sites of muscimol injection in thepulvinar. Circles indicate sites that, when inactivated by muscimol,
affected the behavioral results of the opt-out task. Crosses indicate
sites that did not affect the results of the task after muscimol injection.
The dorsal pulvinar (dPUL) and pulvinar ventral (vPUL) were defined as
pulvinar regions dorsal and ventral to the brachium of superior colliculus(BSC), respectively. The value above each section indicates the anterior
distance from ear bar zero.

753

npg

© 2013 Nature America, Inc. All rights reserved.

a r t ic l e s
stimulus and boundary (the confidence value) was underestimated(Supplementary Fig. 9). Although we could make similar predictions by elevating the threshold for opt-out choices without changing
confidence values, the model of reduced confidence provided a moreplausible explanation for the inactivation results (Fig. 6c), particularly
because the majority of pulvinar neurons showed visual responses
that were modulated by confidence levels (Figs. 2 and 3). In contrast,
inactivation of the LGN was thought to devastate the stimulus value
itself. These behavioral and modeling results of inactivation support
the view on perceptual process13,14,32,33 that the LGN (first-ordervisual thalamus) acts upstream of perceptual categorization whereas
the pulvinar (higher-order visual thalamus) acts downstream of visual
categorization and has an essential role in the subject’s confidence
about the visual categorization.
Neurons with V-shaped response modulation were located primarily in the dorsal pulvinar rather than the ventral pulvinar (Fig. 8a).
The dorsal region corresponds to the classically defined medial pulvinar and dorsal portion of the lateral pulvinar12,21,34–36. This region
receives input from multiple cortical areas, including the frontal andparietal cortices12–14,33–36, which have been shown to contain neural correlates of confidence in previous studies18,19,37. The response
profiles of the cortical neurons, however, differed from those of thepulvinar neurons. The frontal cortical neurons18,19 represented uncertainty (the opposite of confidence) more frequently than confidence
and were activated during the outcome-anticipation period (mainly
between the behavioral choice and reward delivery). The parietal
cortical neurons37 represented the decision about where to directa saccade, and their responses showed monotonic modulations inrelation to confidence levels. Thus, it is unlikely that the pulvinar
responses passively reflected these cortical responses. The pulvinar
neurons exhibited undifferentiated early responses and differentiated later responses, with V-shaped modulation during presentationof the visual stimulus. Based on anatomical connectivity, we presume
that the early responses likely reflect bottom-up sensory inputs via
visual cortical areas, whereas the late responses reflect recurrent activity arising from interactions with multiple cortical areas. Additional
experiments, such as simultaneous neural recordings from the different brain areas during the same task, are necessary to study the neuralcircuits that generate these responses.
Our results can offer a new perspective on previous studies of thepulvinar. First, our findings do not deny a hypothesis about the pulvinar contributing to attention, which has been suggested in many
­studies23–28. Rather, a possible interpretation is that confidencerelated signals in the pulvinar can be used to regulate attention,
because recent studies indicated that estimates of uncertainty or confidence influence how a subject will explore the world and allocate
attention resources19,38–41. Second, clinical studies in humans5,42,43
have shown that pulvinar damage results in hemineglect, that is, failure to notice a stimulus that is present in one hemifield. A study ofmonkey neurophysiology also has suggested that pulvinar responses
correlate with the visibility of a stimulus22. Visibility has been often
measured by rating the confidence in whether the stimulus can beperceived and is intimately tied to stimulus awareness6,7,44–46. In thisstudy, the pulvinar neurons representing confidence were activatedonly during visual events (Figs. 2 and 3) and effects of pulvinar
inactivation during the opt-out task were specific to contralateralvisual targets (Fig. 6). These observations are consistent with theview that confidence signals in the pulvinar are closely related tothe extent of perceptual visibility in the corresponding visual field.
Taken together with these previous results, our data indicate thatthe pulvinar houses a confidence map of the visual world, which
754

potentially serves for a subject’s visual awareness ‘here and now’and explorations of the environment.
Methods
Methods and any associated references are available in the online
version of the paper.
Note: Supplementary information is available in the online version of the paper.
Acknowledgments
We thank K. Kawano, S. Dehaene, R. Kanai and S. Phillips for valuable comments
and critical discussions; R. Tamura and K. Numata for continuous encouragement;
T. Mega and A. Muramatsu for technical help and animal care. This work was
supported in part by Precursory Research for Embryonic Science and Technology
program from Japan Science and Technology Agency, Grant-in-Aids for Young
Scientists (A) and Scientific Research on Innovative Areas from Ministry of
Education, Culture, Sports, Science and Technology, Japan (to Y.K.).
AUTHOR CONTRIBUTIONS
Y.K. and N.H. designed the experiment. Y.K., A.N., N.H. and A.M. collected data.
Y.K., A.N., T.U. and N.H. contributed to data analysis. All authors discussed theresults and wrote the manuscript.
COMPETING FINANCIAL INTERESTS
The authors declare no competing financial interests.
Reprints and permissions information is available online at http://www.nature.com/
reprints/index.html.
1. Peirce, C.S. & Jastrow, J. On small differences of sensation. Mem. Nat. Acad. Sci.
3, 73–83 (1884).
2. Seth, A.K., Baars, B.J. & Edelman, D.B. Criteria for consciousness in humans andother mammals. Conscious. Cogn. 14, 119–139 (2005).
3. Frith, C., Perry, R. & Lumer, E. The neural correlates of conscious experience: anexperimental framework. Trends Cogn. Sci. 3, 105–114 (1999).
4. Sahraie, A., Weiskrantz, L. & Barbur, J.L. Awareness and confidence ratings inmotion perception without geniculo-striate projection. Behav. Brain Res. 96, 71–77(1998).
5. Driver, J. & Vuilleumier, P. Perceptual awareness and its loss in unilateral neglect
and extinction. Cognition 79, 39–88 (2001).
6. Lau, H.C. A higher order Bayesian decision theory of consciousness. Prog. Brain
Res. 168, 35–48 (2008).
7. Dehaene, S. & Changeux, J.P. Experimental and theoretical approaches to conscious
processing. Neuron 70, 200–227 (2011).
8. Haynes, J.D., Deichmann, R. & Rees, G. Eye-specific effects of binocular rivalry inthe human lateral geniculate nucleus. Nature 438, 496–499 (2005).
9. Tononi, G. An information integration theory of consciousness. BMC Neurosci. 5,
42 (2004).
10. Crick, F. & Koch, C. Constraints on cortical and thalamic projections: the no-strongloops hypothesis. Nature 391, 245–250 (1998).
11. Berman, R.A. & Wurtz, R.H. Exploring the pulvinar path to visual cortex. Prog.
Brain Res. 171, 467–473 (2008).
12. Kaas, J.H. & Lyon, D.C. Pulvinar contributions to the dorsal and ventral streams ofvisual processing in primates. Brain Res. Rev. 55, 285–296 (2007).
13. Guillery, R.W. & Sherman, S.M. Thalamic relay functions and their role incorticocortical communication: generalizations from the visual system. Neuron 33,
163–175 (2002).
14. Casanova, C. The visual functions of pulvinar. in The Visual Neurosciences (eds.
Chalupa, L.M. & Werner, J.S.) 592–608 (MIT Press, 2003).
15. Shields, W.E., Smith, J.D., Guttmannova, K. & Washburn, D.A. Confidence judgments
by humans and rhesus monkeys. J. Gen. Psychol. 132, 165–186 (2005).
16. Kornell, N., Son, L.K. & Terrace, H. Transfer of metacognitive skills and hint seeking
in monkeys. Psychol. Sci. 18, 64–71 (2007).
17. Persaud, N., McLeod, P. & Cowey, A. Post-decision wagering objectively measuresawareness. Nat. Neurosci. 10, 257–261 (2007).
18. Kepecs, A., Uchida, N., Zariwala, H.A. & Mainen, Z.F. Neural correlates,computation and behavioural impact of decision confidence. Nature 455, 227–231(2008).
19. Kepecs, A. & Mainen, Z.F. A computational framework for the study of confidence
in humans and animals. Phil. Trans. R. Soc. Lond. B 367, 1322–1337 (2012).
20. Olszewski, J. The Thalamus of the Macaca Mulatta, An Atlas for Use with theStereotaxic Instrument (Karger Press, Basel, 1952).
21. Gutierrez, C., Cola, M.G., Seltzer, B. & Cusick, C. Neurochemical and connectionalorganization of the dorsal pulvinar complex in monkeys. J. Comp. Neurol. 419,
61–86 (2000).
22. Wilke, M., Mueller, K.M. & Leopold, D.A. Neural activity in the visual thalamus
reflects perceptual suppression. Proc. Natl. Acad. Sci. USA 106, 9465–9470(2009).

VOLUME 16 | NUMBER 6 | JUNE 2013

nature NEUROSCIENCE

a r t ic l e s
34. Bender, D.B. & Youakim, M. Effects of attentive fixation in macaque thalamus andcortex. J. Neurophysiol. 85, 219–234 (2001).
35. Imura, K. & Rockland, K.S. Long-range interneurons within the medial pulvinar
nucleus of macaque monkeys. J. Comp. Neurol. 498, 649–666 (2006).
36. Romanski, L.M., Giguere, M., Bates, J.F. & Goldman-Rakic, P.S. Topographicorganization of medial pulvinar connections with the prefrontal cortex in the rhesus
monkey. J. Comp. Neurol. 379, 313–332 (1997).
37. Kiani, R. & Shadlen, M.N. Representation of confidence associated with a decisionby neurons in the parietal cortex. Science 324, 759–764 (2009).
38. Yu, A.J. & Dayan, P. Uncertainty, neuromodulation, and attention. Neuron 46,
681–692 (2005).
39. Luck, S.J., Hillyard, S.A., Mouloua, M. & Hawkins, H.L. Mechanisms of visualspatial attention: resource allocation or uncertainty reduction? J. Exp. Psychol. Hum.
Percept. Perform. 22, 725–737 (1996).
40. Itti, L. & Baldi, P. Bayesian surprise attracts human attention. Vision Res. 49,
1295–1306 (2009).
41. Dayan, P., Kakade, S. & Montague, R.P. Learning and selective attention. Nat.
Neurosci. 3 (suppl.), 1218–1223 (2000).
42. Karnath, H.O., Himmelbach, M. & Rorden, C. The subcortical anatomy of human spatial
neglect: putamen, caudate nucleus and pulvinar. Brain 125, 350–360 (2002).
43. Zihl, J. & von Cramon, D. The contribution of the ‘second’ visual system to directedvisual attention in man. Brain 102, 835–856 (1979).
44. Kunimoto, C., Miller, J. & Pashler, H. Confidence and accuracy of near-thresholddiscrimination responses. Conscious. Cogn. 10, 294–340 (2001).
45. Koch, C. & Preuschoff, K. Betting the house on consciousness. Nat. Neurosci. 10,
140–141 (2007).
46. Kolb, F.C. & Braun, J. Blindsight in normal observers. Nature 377, 336–338 (1995).

npg© 2013 Nature America, Inc. All rights reserved.

23. Petersen, S.E., Robinson, D.L. & Morris, J.D. Contributions of the pulvinar to visual
spatial attention. Neuropsychologia 25, 97–105 (1987).
24. Rafal, R.D. & Posner, M.I. Deficits in human visual spatial attention following
thalamic lesions. Proc. Natl. Acad. Sci. USA 84, 7349–7353 (1987).
25. Kastner, S. & Pinsk, M.A. Visual attention as a multilevel selection process. Cogn.
Affect. Behav. Neurosci. 4, 483–500 (2004).
26. LaBerge, D. & Buchsbaum, M.S. Positron emission tomographic measurements ofpulvinar activity during an attention task. J. Neurosci. 10, 613–619 (1990).
27. Saalmann, Y.B., Pinsk, M.A., Wang, L., Li, X. & Kastner, S. The pulvinar regulates
information transmission between cortical areas based on attention demands.
Science 337, 753–756 (2012).
28. Desimone, R., Wessinger, M., Thomas, L. & Schneider, W. Attentional control ofvisual perception: cortical and subcortical mechanisms. Cold Spring Harb. Symp.
Quant. Biol. 55, 963–971 (1990).
29. Petersen, S.E., Robinson, D.L. & Keys, W. Pulvinar nuclei of the behaving rhesus
monkey: visual responses and their modulation. J. Neurophysiol. 54, 867–886(1985).
30. Benevento, L.A. & Port, J.D. Single neurons with both form/color differential
responses and saccade-related responses in the nonretinotopic pulvinar of the
behaving macaque monkey. Vis. Neurosci. 12, 523–544 (1995).
31. Robinson, D.L., McClurkin, J.W. & Kertzman, C. Orbital position and eye movement
influences on visual responses in the pulvinar nuclei of the behaving macaque.
Exp. Brain Res. 82, 235–246 (1990).
32. Malpeli, J.G. & Baker, F.H. The representation of the visual field in the lateralgeniculate nucleus of Macaca mulatta. J. Comp. Neurol. 161, 569–594 (1975).
33. Purushothaman, G., Marion, R., Li, K. & Casagrande, V.A. Gating and control ofprimary visual cortex by pulvinar. Nat. Neurosci. 15, 905–912 (2012).

nature NEUROSCIENCE

VOLUME 16 | NUMBER 6 | JUNE 2013755

ONLINE METHODS

npg© 2013 Nature America, Inc. All rights reserved.

Experiments with monkeys. All surgical and experimental procedures wereapproved by the Animal Care and Use Committee of the National Instituteof Advanced Industrial Science and Technology (AIST, Japan), and performedin accordance with the Guidelines for the Care and Use of Animals of AIST.
Details of procedures used in the present study are similar to those previously described47–49. Two male macaque monkeys (Macaca fuscata, weighing
5−9 kg, 3–8 years of age) participated in the experiments. We minimized thenumber of monkeys used by considering the ethics and data similarity. Eachmonkey had his own cage with environmental enrichment. The housing area wasmaintained on a 12-h light–12-h dark cycle. The experiments were conductedduring the light cycle. We used the naive monkeys without a history of any otherexperiments. For this study, a head holder, recording chamber and search coils were
implanted into the monkeys under anaesthesia and sterile surgical conditions. The
head holder, the recording chamber and the eye coil connectors were all embedded
in dental acrylic that covered the top of the skull and were connected to the skull
using titanium screws. The search coils were surgically placed under the conjunctiva of the eyes for recording of eye movements. The recording chamber was placed
over the parietal cortex, tilted laterally by 20° and aimed at the visual thalamus.
Visual stimulus. Visual stimuli were generated using VSG 2/5 (Cambridge
Research Systems). A CRT color display (Sony, GDM-F500) was placed 57 cm
in front of the monkey. The display subtended a visual angle of 40° × 30° with aresolution of 688 × 516 pixels, and refreshed at 100 Hz. Random dots (0.165° indiameter each) were drawn with densities of 16.8 per degree2 inside circle apertures with diameters of 4.7°–8.8° and moved at the speed of 15.8 degrees s−1. In
the task, the random-dots stimulus covered the neuron’s receptive field, mapped
initially with a moving bar. The dot color was red (CIE chromaticity, x = 0.623,
y = 0.34) or green (x = 0.288, y = 0.6) at the same luminance (10 cd m−2). Apartfrom the color cue, the fixation point (0.33°) was 10 cd m−2 white (x = 0.255,
y = 0.219), then dimmed to 2 cd m−2 white.
Behavioral tasks. The behavioral task was controlled by REX, a QNX-based realtime experimentation data-acquisition system. All trials started with the presentation of a fixation point at the center of the display to attract the focus of themonkey. In the perceptual categorization task, the color of the fixation point (redor green) indicated which colored dots the monkey should judge (Fig. 1a). If themonkey gazed at it for 600 ms, the color of the fixation point turned white. Afterthe monkey fixated on it for 300–600 ms, the RDS appeared for 500 ms. Between
400 ms and 900 ms after the RDS was turned off, the fixation point dimmed,
signaling that the monkey could release the home bar and was required to touchthe left or right bar within 1 s. Correct responses were rewarded with a drop ofwater or juice. The two cue colors were randomly interleaved from trial to trial.
In any tasks, the monkey was required to maintain fixation within a 1.4-degreesquare window throughout all the visual events. The eye position was monitoredwith a search coil system (Datel) and stored at 1 kHz. Based on the psychophysicalassessment (Fig. 1c), we selected RDSs with six kinds of the pairing ratios (0%,30%, 45%, 55%, 70% and 100%) in the electrophysiological experiments. EachRDS was presented randomly from trial to trial at nearly equal frequency.
Electrophysiology. Single units were recorded with flexible tungsten microelectrodes (Microprobe). The recording chambers were implanted in accordance withcoordinates determined by MRI. Before the start of the recording experiments, wefirst searched for auditory neural responses by clapping and thereby localized themargins of the medial geniculate body, serving as a physiological landmark. We
then determined the posterior pole of the lateral geniculate nucleus (LGN), which
demarcated the anterior border of the pulvinar. Based on the coordinates derived
from these structural and physiological localizing procedures, the microelectrodewas then inserted stereotaxically stepwise with a micromanipulator (MO-97A,
Narishige) into various parts of the visual thalamus. At the beginning of eachrecording session, visual receptive-field mapping was done while the monkey
looked at the central fixation spot. All the LGN neurons showed the visual
responses with the contralateral small receptive fields. Although some pulvinar
neurons had large response fields extending into the ipsilateral hemifields, mostpulvinar neurons also had the contralateral receptive fields. Thus we selected
the neurons whose receptive fields were restricted in the contralateral hemifield.
Spiking data were collected with a MAP recording system (Plexon).

nature NEUROSCIENCE

Recording sites. To position the electrode at the target site, we advanced it
through a guide tube that placed in a Crist grid and transversed the dura matterof the monkey. The Crist grid with holes separated by 1 mm was attached tothe inside of the recording chamber50. During the recording experiments, we
visualized electrode tracks in MRI scans eight times in total. After each scan,we confirmed by comparing the MRI image to coronal sections in a histologicalatlas51 of M. fuscata that the tip of the electrode was located in the LGN or pulvinar (Supplementary Fig. 7). These procedures enabled us to reconstruct therecording sites: locations of the recorded neurons were plotted onto monkey brain
atlas, based on MRI images, electrode positions in the chamber and recording
depth (Fig. 8a). In the present study, we divided the pulvinar into the dorsal andventral parts, separated at the level of the brachium of superior colliculus; similar
approaches have been used in previous studies20–22. The dorsal pulvinar contains
sites previously referred to as the dorsal portion of the lateral pulvinar and medial
pulvinar regions, whereas the ventral pulvinar contains sites previously referred
to as the ventral portion of the lateral pulvinar and inferior pulvinar.
Data analysis. We analyzed behavioral and spiking data using custom software
written in Matlab (Mathworks). Spike trains were smoothed by convolution with aGaussian kernel (σ = 10 ms) to obtain spike-density functions. The early responseof the pulvinar neurons was defined as the number of spikes in the first 100 ms
from 50 ms to 150 ms after the onset of RDS. The early response of the LGN
neurons was defined as the number of spikes in the first 100 ms after the onset of
RDS because the response latencies of the LGN neurons were shorter than thoseof the pulvinar neurons. The late response was defined as the number of spikes
from 400 ms to 500 ms after the onset of RDS. A neuron was classified as ‘visual
responsive’ if the early or late response differed from the number of spikes in
the 100-ms control period just before the onset of RDS (Wilcoxon signed-rank
test, P < 0.01).
To statistically assess how the visual responses of the single neurons wererelated to the red-down pairing ratios, we first performed the following linear
regression analysis, in which the firing rate of the neurons was given by(0 ≤ x < 50) f1 + k1x
f =
(
50
f
+
k
x
< x ≤ 100)
2
 2

(1)

where x is the ratio of red-down pairing, and k1 and k2 indicate the regression
coefficient (slope) in the lower and higher ratios of red-down pairing, respectively,
and f1 and f2 indicate the intercept in the lower and higher ratios of red-down
pairing, respectively. We evaluated the statistical significance of the coefficient
using a permutation test by randomly reassigning each firing rate to the reddown pairing ratio. This was repeated 1,000 times to calculate P value for eachcoefficient. If P < 0.01 in both k1 and k2, neural activity was defined as modulated by the RDS of different red-down pairing ratios. Second, for cells satisfying
this criterion, the response modulations were classified into four types, depending on whether the value of k1 or k2 was positive or negative: in other words,(k1, k2) was (positive, positive), (negative, positive), (negative, positive) or (positive, negative). If (k1, k2) was (negative, positive), the response modulation wasclassified as V-shaped.
To normalize the firing rates across neurons, we first averaged neural responses
to the RDS with any color-motion pairings for different tasks and then used the
maximum among these as a reference value for each neuron. Next, we divided the
response of each neuron to the different condition with respect to the reference
value, and this quotient was defined as a normalized activity in each condition.
To track the time course of V-shaped response modulations at the populationlevel (Fig. 2c), we calculated the slope of the linear regression of the normalized
firing rates in the 50-ms sliding windows with 1-ms moving steps on the lowerand higher pairing ratios.
Each statistical test was performed, following checks on normality and equalvariances of the samples by the Kolmogorov-Smirnov test and Levene test, respectively. Throughout this study, two-sided tests were used when we compared thedata between the two groups. We used the Holm-Bonfferoni method to adjust for
multiple comparisons, if necessary (Figs. 6 and 7 and Supplementary Figs. 4–6).
The data were analyzed by the persons with and without knowing relations
between the experimental procedures and data. These blinded and unblended
analyses had no effects on the results. We found similar tendencies in behavioral
performances across the different monkeys (Supplementary Figs. 1, 4 and 5) anddoi:10.1038/nn.3393

npg© 2013 Nature America, Inc. All rights reserved.

in the neural responses across the different cells (Figs. 2 and 3 and SupplementaryFigs. 2 and 3), which indicated the biological replicates.
Characterizing neural responses. We encountered 618 neurons showing visual responses to the RDS during the categorization task. Of these neurons, 247
showed response modulations during the perceptual categorization task. The
response modulations of the neurons were classified into four types: negativepositive (n = 163 neurons), positive-positive (n = 28), negative-negative (n = 25)
and positive-negative (n = 31) slopes in the lower-higher pairing ratio, respectively. These neurons were located in the pulvinar. The responses of all the LGN
neurons were not modulated during the categorization task, like the neuron forwhich data are shown in Supplementary Figure 10. The LGN neurons exhibitedthe early transient responses to the onset of RDS, but, unlike the pulvinar neurons,
did not show the vigorous responses during the later phase of the RDS presentation period. To understand the major role of the visual thalamus during our task,
we focused on the vast proportion of the neurons that produced negative-­positive
slopes (n = 163, 66% of 247 neurons, chi-squared test, P < 0.01), resulting inV-shaped response modulations like those shown in Figure 2b.
We recorded 133 neurons during the opt-out task. Out of the 163 neurons with
V-shaped response modulation during the categorization task, we consecutively
tested 38 in the opt-out task. Ninety-five cells were recorded only during the
opt-out task. Among these 95 neurons, 34 showed V-shaped response modulation in correct trials. Thus, we analyzed 72 neurons in total for the opt-out task.
Of these, 65 neurons and 7 neurons were recorded from the dorsal and ventral
pulvinar, respectively.
Modeling. We used a confidence model in a previous study18. Our task can bethought of as a binary motion-categorization task (up or down) after the target
color is determined. In the model, each stimulus (s) with the red-down pairingratio (x) was encoded as a distribution with Gaussian noise (n):s = m (x − 50)/ 50 + n, n ∈ N (0, s ),where σ2 was the noise variance, and m determined mean values of the extreme
distributions for stimulus type with 0-100 pairing ratio. In a given trial, a stimulus
sample was drawn from the respective distribution.
The categorical choice was determined by comparing stimulus and boundary:Categorization = {up | s > b; down | s < b}.
The confidence value (d) was calculated from the distance between stimulus
and boundary (|s – b|). In the opt-out task, a risky or escape decision was determined by comparing the confidence value and a threshold value (c):Decision = {risky | d > c; escape | d < c}.
For fitting the model, m, σ and c were adjusted using the least-square method.
The yielded confidence values as a function of stimulus type were normalized tothe maximum value of 1. The qualitative patterns of the simulated data for correct, error and escape trials were robust to different parameters, which affected

doi:10.1038/nn.3393

the slope and level of each function. In the present model, we did not calibrate
the confidence value. For simplicity, the category boundary (b = 0) and threshold(c) were fixed without variance.
Reversible inactivation. After the recording experiment, the inactivation experiments were conducted. A small amount of a GABA agonist (muscimol hydrobromide; 5 µg µl−1 in saline; volume = 1.0 µl) was pressure-injected at a rate ofabout 0.1 µl per 30 s using a 32-gauge injection needle that was connected to a
microsyringe and was penetrated through a 23-gauge guide tube. Site and depthof injection were adjusted by using an x-y stage attached on top of the cylinderand a micromanipulator that was also used for the unit recording experiments.
We injected muscimol in the pulvinar (n = 34 sites) and LGN (n = 16 sites).
Sites of inactivation in the pulvinar were within the area containing neurons
showing V-shaped response modulations during the categorization task. To
rule out confounds from physical effects resulting from needle penetration, theeffect of inactivation for each site was assessed across any stimulus types bycomparing behavioral data obtained after injection with muscimol and saline(volume = 1.0 µl). If there were any differences in the proportions of correct orescape choices between the two injection conditions (two-sample proportion
test, P < 0.05), the sites were classified as effective. All the LGN sites with muscimol injection significantly affected the performances during the categorizationand opt-out tasks (Fig. 7). Among the 34 muscimol-treated sites in the pulvinar(Fig. 8b), 22 affected the opt-out task performances whereas the other 12 sites
did not exhibit any effects on the task performance. In Figure 6, the population data based on muscimol injections into these effective sites of the pulvinar
is shown. The muscimol or saline injection was conducted from day to day inrandom order.
We did not measure the spread of muscimol directly. However, a previous
study52 showed using glucose autoradiography that muscimol spread ~1.7 mmfrom the injection site when 1.0 µl of muscimol solution was injected during a
4-min period. In the presesnt study, we injected 1.0 µl of muscimol solution
during a 5-min period. The minimum distances between the injection sites in
the pulvinar and the LGN were more than 3.0 mm, which was beyond the rangethat muscimol would spread. Thus, it is unlikely that the injected muscimol inactivated both of the two regions of the visual thalamus. The effect of inactivation
persisted for the period of the experiments but disappeared the next day.

47. Inaba, N., Shinomoto, S., Yamane, S., Takemura, A. & Kawano, K. MST neurons
code for visual motion in space independent of pursuit eye movements.
J. Neurophysiol. 97, 3473–3483 (2007).
48. Komura, Y. et al. Retrospective and prospective coding for predicted reward in thesensory thalamus. Nature 412, 546–549 (2001).
49. Komura, Y. et al. Auditory thalamus integrates visual inputs into behavioral gains.
Nat. Neurosci. 8, 1203–1209 (2005).
50. Crist, C.F., Yamasaki, D.S., Komatsu, H. & Wurtz, R.H. A grid system and a
microsyringe for single cell recording. J. Neurosci. Methods 26, 117–122 (1988).
51. Kusama, T. & Mabuchi, M. Stereotaxic atlas of the brain of macaca fuscata(University of Tokyo Press, Tokyo; University Park Press, 1970).
52. Martin, J.H. Autoradiographic estimation of the extent of reversible inactivation
produced by microinjection of lidocaine and muscimol in the rat. Neurosci. Lett.
127, 160–164 (1991).

nature NEUROSCIENCE