Distinct frontal systems for response inhibition,
attentional capture, and error processing
D. J. Sharpa,b,1, V. Bonnellea,b, X. De Boissezonc,d,e, C. F. Beckmanna,f, S. G. Jamesg, M. C. Patelh, and M. A. Mehtab,i
aDivision of Experimental Medicine, Imperial College London, London, W12 0NN, United Kingdom;bMedical Research Council Clinical Sciences Centre,
Imperial College London W12 0NN, United Kingdom;cINSERM–Imagerie cérébrale et handicaps neurologiques UMR 825, F-31059 Toulouse, France;
dUniversite de Toulouse, UPS, Imagerie cerebrale et handicaps neurologiques UMR 825, CHU Purpan, Place du Dr Baylac, F-31059 Toulouse Cedex , France;
eCentre Hospitalier Universitaire de Toulouse, Pole Neurosciences, CHU Purpan, F-31059 Toulouse Cedex 9 ,France;fFunctional Magnetic Resonance Imaging
of the Brain Centre, University of Oxford, Oxford OX3 9DU, United Kingdom;gSchool of Human and Life Sciences, University of Surrey, London SW15 5PU,
United Kingdom;hNeuroradiology Department, Charing Cross Hospital, Imperial College Academic Health Sciences Centre, London W6 8RF, United Kingdom;
andiCentre for Neuroimaging Sciences, Institute of Psychiatry, King’s College London, London SE5 8AF United Kingdom
Edited by Edward E. Smith, Columbia University, New York, NY, and approved February 5, 2010 (received for review November 11, 2009)
Stopping an action in response to an unexpected event requires
both that the event is attended to, and that the action is inhibited.
Previous neuroimaging investigations of stopping have failed to
adequately separate these cognitive elements. Here we used a
version of the widely used Stop Signal Task that controls for the
attentional capture of stop signals. This allowed us to fractionate
the contributions of frontal regions, including the right inferior
frontal gyrus and medial frontal cortex, to attentional capture,
response inhibition, and errorprocessing. A ventral attentional sys-
tem, including the right inferior frontal gyrus, has been shown to
respond to unexpected stimuli. In line with this evidence, we rea-
soned that lateral frontal regions support attentional capture,
whereas medial frontal regions, including the presupplementary
motor area (pre-SMA), actually inhibit the ongoing action. We
with the presentation of unexpected stimuli against those associ-
ated with outright stopping. Functional MRI images were obtained
in 26 healthy volunteers. Successful stopping was associated with
However, only activation of the pre-SMA differentiated stopping
from a high-level baseline that controlled for attentional capture.
As expected, unsuccessful attempts at stopping activated the ante-
rior cingulate cortex. In keeping with work in nonhuman primates
these findings demonstrate that successful motor inhibition is spe-
cifically associated with pre-SMA activation.
attention|functional MRI|presupplementary motor area|stop signal
task provides evidence that both medial frontal regions, including
the presupplementary motor area (pre-SMA), and more lateral
regions, including the right inferior frontal gyrus (IFG; rIFG) and
insula (Ins), are involved in stopping. However, the specific con-
tributions of these regions to motor control are unresolved (2–4).
Many functional imaging studies have demonstrated activation of
differences in response inhibition correlate with the magnitude of
the IFG/Ins activation during the SST (5). Activation of medial
prefrontal regions are also observed during stopping (2, 5). Pre-
SMA activation is correlated with the efficiency of inhibitory pro-
cessing(2), andworkinnonhumanprimatessupports a role forthe
medial prefrontal regions in behavioral inhibition (9, 10). Neuro-
psychological studies provide discrepant results, with correlations
between the extent of damage and impairments of inhibitory
function reported for both the right lateral and medial frontal
regions (3, 4).
A limitation of much of the previous neuroimaging literature is
that “stop trials” conflate processing associated with attentional
capture of the perceptual cue and response inhibition. Stopping in
response to a stop signal requires a subject to attend to a cue,
appreciate its significance, and engage response inhibition (2, 11,
12). This is important because the attentional processing of an
unexpected perceptual event is associated with significant brain
activation, without necessarily signifying the presence of inhibitory
the frontal cortex (13) and a right lateralized ventral attentional
system that includes the right IFG/Ins has been described, which is
thought to support the attentional capture of salient stimuli (14).
We propose that much of the network that is activated during
stopping, including the right IFG/Ins, is the result of attentionally
processing the stop signal. In contrast, we predict that the pre-
SMA is critically involved in response inhibition. We test this
hypothesis by manipulating the standard version of the SST to
separate attentional processing of the cue to stop, from response
inhibition that actually stops an initiated response. This is ach-
ieved by adding a high-level control condition that involves the
presentation of an unexpected continue signal (Fig. 1). This cue
is attentionally processed as an unexpected event, but requires
no change in behavior. In addition, to limit the strategic slowing
of task performance that can occur during performance of the
SST (12), we provided negative feedback for response trials with
slow reaction times. Crucially the comparison of stop and con-
tinue trials allows the separation of brain regions involved in
attentional capture from those involved in response inhibition.
Behavior. Performance for both the original and controlled ver-
sions of the SST was similar to that observed in previous studies
(7, 8, 15). The average accuracy for all runs was close to 50%
(see SI Results for further information on individual perform-
ance). The addition of continue trials to the controlled SST had
no significant effect on mean go reaction time (RT), median go
RT, or stop signal reaction time (SSRT), i.e., these measures
were similar in the original and controlled versions of the task.
This suggests that adding the continue trials did not lead to a
major strategic change in task performance. Go trial RT during
the SST was significantly longer than the mean go RT for the
simple choice reaction time (CRT) task [T(25) > 2.74, P < 0.05
for all four SST runs]. Error rates for continue and go trials were
less than 4%. Across all subjects, RT for continue trials was
Author contributions: D.J.S., X.D.B., and M.A.M. designed research; D.J.S., V.B., X.D.B.,
S.G.J., and M.C.P. performed research; D.J.S., V.B., C.F.B., and M.A.M. analyzed data; and
D.J.S., V.B., X.D.B., C.F.B., and M.A.M. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
Freely available online through the PNAS open access option.
1To whom correspondence should be addressed. E-mail: firstname.lastname@example.org.
This article contains supporting information online at www.pnas.org/cgi/content/full/
| March 30, 2010
| vol. 107
| no. 13www.pnas.org/cgi/doi/10.1073/pnas.1000175107
approximately 40 ms slower than RT for go trials in the con-
trolled version of the SST [T(25) = 10.43, P < 0.001; Table 1].
Neuroimaging Results. Overall network for stopping is consistent with
the previous literature. The stop network can be defined by con-
trasting trials wherein a stop signal occurred and a response was
successfully inhibited with a go trial (i.e., stop vs. go). This net-
work includes brain regions involved in the attentional process-
ing of a perceptual cue, as well as those involved in response
inhibition. In our main analyses of the original and controlled
versions of the SST, we combined both runs of each version in
two separate mixed effects analyses. In both versions of the task,
we observed a stopping network that was similar to that pre-
viously reported, e.g., in refs. 6 and 7. Correcting for multiple
comparisons, activation was observed within the right anterior
insular cortex and middle frontal gyrus, as well as bilaterally
within the inferior, middle, and superior frontal gyri. Activation
was also observed within the right supramarginal gyrus, the left
intraparietal sulcus and the lateral occipital cortices (Table S1
and Fig. 2A illustrating the controlled SST). We found no sig-
nificant difference between the stop activation (i.e., stop vs. go
trials) in the two versions of the SST, indicating that activation in
the stop networkwas unaffected
Continuing activates a similar brain network to stopping. In the con-
trolled version of the SST, we added a trial type consisting of
unpredictable but behaviorally irrelevant stimuli (continue trials).
but required no change to the initiated motor response. The
contrast between correctly continuing after an unexpected event
occurred (go trials) showed activation within the IFG/Ins, the
frontal pole, and the middle frontal gyri, as well as within the lat-
eral occipital lobes (Table S2 and Fig. 2B). Extensive activation
was observed within bilateral IFG, including both the pars oper-
cularis and pars triangularis. Activation also extended into the
right anterior cingulate and paracingulate cortices, and a small
amount of activation was observed within the superior frontal
gyrus (pre-SMA). In posterior brain regions, activation was pres-
ent in the fusiform gyrus and the parietal lobes bilaterally, as well
Pre-SMA is specifically activated during response inhibition. Brain
regions specifically activated by the outright stopping of a motor
response were identified by the contrast of correct stop with
correct continue trials. Critically, the latter trial type provides a
high-level baseline that controls for the attentional capture of an
unexpected event, and so allows the isolation of brain regions
that support response inhibition. This contrast demonstrated
medial frontal activation, with peaks of activation within medial
and lateral parts of the pre-SMA and the paracingulate cortex
Fixation Go-signa l
cross was presented initially for 350 ms followed by the go stimulus for 1,400
ms (a right- or left-pointing arrow). For both the original and controlled
versions of the SST, 20% of the trials involve an unpredictable stop signal
(red dot) presented at a variable delay following the go signal (the stop
signal delay). See SI Materials and Methods for more information about the
staircase procedure. During the controlled version of the SST, a further 20%
of trials involve a continue signal (green dot) presented with the same stop
signal delay as the previous stop signal.
Stop signal paradigm. Interstimulus interval was 1,750 ms. A fixation
Table 1. Behavioral results for the CRT task and SST (original and controlled)
SST original SST controlled
Run 1Run 2Run 1Run 2
Median Go RT (ms)
SD Go RT (within subjects)
Median Continue RT (ms)
Accuracy on Go trials, %
Accuracy on Continue trials, %
Accuracy on Stop trials, %
411 ± 16
69 ± 8
97.7 ± 0.4
447 ± 14
87 ± 5
98.3 ± 0.4
48.3 ± 0.7
231 ± 11
448 ± 14
83 ± 5
98.7 ± 0.4
50.1 ± 0.7
227 ± 11
462 ± 17
100 ± 8
502 ± 17
98.2 ± 0.5
97.0 ± 0.9
50.9 ± 0.7
222 ± 13
453 ± 13
90 ± 9
486 ± 17
98.5 ± 0.3
98.2 ± 0.6
50.9 ± 0.7
220 ± 11
Average of the median speed of response to Go trials (Go RT), median speed of response to continue trials
(Continue RT), SSRT, and accuracy on Go, Continue, and Stop trials are reported (±SEM). Percentage accuracy is
estimated by dividing the number of correct trials (Go, Continue, or Stop) by the total number of each trial type.
The within-subject SD is also reported for Go RT. SSRT was calculated for each subject and each run by subtract-
ing the critical SSD from the median Go RT. NA, not applicable.
Z Score 2.3 4.6
show brain regions activated in the controlled SST for (A) correct stop (StC)
more than correct go trials (StC > Go); (B) correct continue trials more than
go trials (Co > Go); and (C) correct stop trials more than continue trials (StC >
Co). Results are superimposed on the MNI 152 T1 2 mm brain template. For
the whole-brain analysis, a Z-statistic threshold of 2.3 was employed, com-
bined with a corrected cluster significance threshold probability of P < 0.05.
Frontal activation during response inhibition. Rendered images
Sharp et al. PNAS
| March 30, 2010
| vol. 107
| no. 13
(Table S3 and Fig. 2C). Activation also extended from the pre-
SMA laterally into the right middle frontal gyrus. No significant
activation of the right IFG/Ins was observed, suggesting that this
region was not specifically supporting response inhibition.
Distinct medial frontal regions for error processing, response conflict, and
response inhibition. Failure to inhibit a response after a stop signal
results in an erroneous button press. In keeping with previous
reports of midline frontal activation for errors on the task (2, 6),
incorrect stop trials in both the original and controlled versions
of the SST were associated with greater ACC activation than
successfully inhibited stop trials. This activation was not related
to the appearance of an unexpected stimulus, as in the controlled
SST a similar activation in the ACC was observed when continue
trials were used as a baseline. This error-related activation was
distinct from the lateral/caudal pre-SMA activation seen when
responses were successfully inhibited. More medially within the
pre-SMA, the patterns of activation for successfully and unsuc-
cessfully inhibiting a motor response overlapped, with similar
peaks of activation for the contrasts of both correct and incorrect
stop with continue trials (Table S4 and Fig. 3).
Pre-SMA supports response slowing as well as stopping. On average
subjects slowed their responses slightly on continue trials
(approximately 40 ms). This raised the possibility that incomplete
response inhibition may have occurred, without the response
actually being stopped. “Horse race” models of SST performance
by the go signal and inhibitory processes triggered by the stop
from inhibitory processing triggered by the appearance of an
unexpected event. In most situations this would be insufficient to
the pre-SMA influences response slowing as well as outright
pre-SMA activation would be observed when continue trials
showed high slowing. This relationship might then explain the
small amount of pre-SMA activation observed for the overall
continue versus go contrast.
To investigate this hypothesis, we compared subjects in whom
the continue trials showed a high degree of slowing against those
the difference between median RT for continue and go trials. As
we had two runs per subject, run-to-run variability in continue
slowing could be examined. Comparing the first and second runs,
changed from low to high slowing (see SI Results for further
second runs separately. For the first run, a whole-brain analysis
and the lateral occipital cortex. In contrast, activation of the pre-
SMA was observed for only the high slowing group. In addition, a
more extensive network of activation was observed for the high-
the left IFG, as well as bilaterally within the middle frontal gyrus,
supramarginal gyrus, and fusiform gyri (Fig. 4A). Similar results
were observed for the second run of the controlled SST.
To test specifically whether the same region of the pre-SMA
supports response slowing and outright stopping we used a region
on the coordinates of the peak of activation from the stopping
contrast, along with another ROI from the rIFG (see SI Materials
and Methods for further details of ROI definition). By using the
contrast of stop against continue trials to generate the ROI, we
way, as the region was defined on the basis of increased activation
during stopping relative to continuing overall. For the first run of
the controlled SST, correcting for multiple comparisons, high
did not activate the pre-SMA. Directly comparing high and low
slowing confirmed that the pre-SMA was more active when sub-
jects slowed their responses [Run1: T(24) = −3.067, P = 0.02]. In
contrast, there was no difference in right IFG activation for con-
tinue trials with high and low slowing (Fig. 4B). The same pattern
wasobserved inthesecondrunofthecontrolled SST:significantly
0.04], but no difference in rIFG activation. There was no evidence
low slowing on continue trials were performing the task, as there
were no group differences on other behavioral variables (SI
Z Score 2.3 - 4.6
and error processing. Regions showing greater activation during the con-
for correct stop trials (StC) compared with correct continue trials(Co). Overlap
between these contrasts is shown in green. Activations are superimposed on
axial sections from z = 16 to z = 62. Thresholding and overlay are as in Fig. 2.
Distinct medial frontal activations for successful response inhibition
High Co slowing
Z Score 2.3 4.6
Low Co slowing
% signal change
the contrast Co > Go when subjects slow their response to the Continue signal
(high Co slowing) or respond as quickly as in Go trials (low Co slowing). Thresh-
olding and overlay as in Fig. 2. (B) Percentage signal change within the right
caudal/lateral pre-SMA and right inferior frontal gyrus (RIFG) for the two con-
trasts stop correct (StC) > go and continue correct (Co) against go (±SEM). *P <
0.05 in activation between the two groups in pre-SMA activation for continue
versus go trials.
Increased pre-SMA activation during response slowing. (A) Rendered
| www.pnas.org/cgi/doi/10.1073/pnas.1000175107 Sharp et al.
Results). In addition, the specificity of the slowing result for the
continue trials is supported by fact the there was no group dif-
ference in the network activated by stop versus go trials, as dem-
onstrated by whole-brain analysis of subjects with high and
Relationship Between Brain Activation and SSRT. We also examined
the relationship between SSRT and neural activity within the pre-
SMA and right IFG using predefined ROIs. Discrepant results
have been reported previously for this relationship (2, 5). Mean
SSRT values were calculated first across the two runs of the con-
region was observed between groups with high or low SSRT (P >
0.2). There was also no significant correlation between neural
activation and SSRT in these regions (P > 0.2).
In this study we have successfully delineated the relative con-
tributions of nodes within the frontal cortex that contribute to
stopping an initiated motor action. We have achieved this by the
in work with clinical populations. However, previous neuro-
imaging studies have failed to separate the distinct cognitive pro-
cesses that are involved in stopping, such as response inhibition
itself, the attentional capture of an unexpected event, and error
processing when stopping fails. We resolve this issue by exper-
SST, and separately modeling correct and incorrect responses. In
line with our hypotheses, the pre-SMA, but not the right IFG,
showed a profile of activation in keeping with response inhibition.
Similar activation was observed during both stopping and “con-
tinuing” within the rIFG. Errors on the task, i.e., failures of
inhibition, were associated with activation of the medial frontal
lobe, including the rostral ACC, which was distinct from the cau-
dal/lateral part of the pre-SMA we observed to be specifically
involved in response inhibition.
Our controlled version of the SST involved the presentation of
an unexpected but behaviorally irrelevant event, with the same
timing and frequency as the stop signal. These continue trials
controlled for the attentional capture of an unexpected event,
providing a high-level baseline with which to contrast stop trials.
Caudal/lateral pre-SMA was robustly activated in the critical
comparison of stop and continue trials, providing evidence for a
specific role for this region in response inhibition. The intro-
duction of continue trials did not notably alter task performance
significantly as behavioral performance and brain activation
patterns were similar for the preserved aspects of the new con-
trolled and original versions of the task. The comparison of
continue trials with go trials demonstrated brain regions engaged
with processing an unexpected but behaviorally irrelevant cue.
This revealed an extensive network that largely overlapped with
that activated by stopping. In contrast to the selective activation
of the pre-SMA, similar activation was observed within the right
IFG/Ins region for both continuing and stopping. This profile is
more in keeping with a role in attentional processing of unex-
pected events, regardless of whether the event signals a need to
change task performance, and argues against a specific role for
the right IFG/Ins in response inhibition.
The introduction of continue trials also allowed us to demon-
the new continue trials were, on average, approximately 40 ms
longer than the go trials. This is in keeping with the unexpected
continue cue triggering a degree of inhibitory processing. Activa-
tion of the pre-SMA was significantly greater when continue trials
were slow, a result that was replicated across both runs of the
controlled SST. This differential activation was not observed for
the rIFG. This result suggests that inhibitory processing supported
by the pre-SMA may result in outright stopping, if it is sufficient to
overcome excitatory motor processing, or may slow a produced
response by interacting with ongoing excitatory processing.
Our results are consistent with previous studies demonstrating
In monkeys, microstimulation of the supplementary eye field
within the medial prefrontal cortex improved performance on an
oculomotor version of the SST by delaying saccade inhibition (9),
and stimulation of the pre-SMA inhibited automatic unwanted
actions while facilitating a desired alternative (10). In humans,
direct cortical microstimulation of the medial PFC can produce
motor inhibition (16, 17), and lesions in the medial frontal lobe
impair inhibitory processing on the SST (4). Paired-pulse trans-
cutaneous magnetic stimulation has demonstrated that the pre-
SMA provides rapid context dependent modulation of motor
cortical activity (18), and transcutaneous magnetic stimulation
applied to the pre-SMA impairs inhibitory control during the SST
(19). In addition, tasks involving either response selection or the
inhibition of certain elements of a movement activate the SMA/
pre-SMA (20, 21). Taken together this work delineates a role for
the pre-SMA in the rapid selection of motor responses, including
choosing to withhold a response and delaying a response.
Our observed pre-SMA activation is not likely to be a result of
error processing, as the critical contrast of stop and continue
trials involved only successful trials. In keeping with previous
results (2, 6), unsuccessful stop trials were associated with mid-
line activation within the rostral ACC. This activation is unlikely
to be the result of incomplete inhibitory processing or non-
specific attentional factors, as similar activation was observed
irrespective of whether successful stop or continue trials were
used as a baseline. This rostral ACC activation is consistent with
performance monitoring processes engaged following errors and
is thought to arise from the ACC (22, 23). Previous functional
MRI and PET studies (24, 25) show that activation of the ACC is
associated with error processing and that selective damage to the
rostral ACC impairs error processing (26).
We also observed an area of overlapping activation within the
rostral pre-SMA for successful and unsuccessful inhibition. This
during successful inhibition and superior to the ACC seen during
failed stops (Fig. 3). Therefore, this result cannot be explained by
may relate to response conflict generated during both successful
and unsuccessful stop trials from the temporal juxtaposition of go
within rostral pre-SMA for conflict trials that required the direc-
tion of eye movements to be switched compared with trials in
which a preplanned eye movement was continued (27). Together
these results suggest a specific role for the rostral pre-SMA in
processing motor conflict that generalizes across motor outputs
introduction of response inhibition.
frontal region is important for cancelling or restraining a motor
response, and that lesions to this area are associated with
clear whether this region is critically involved in response inhib-
ition during the SST (29). An alternative possibility is that acti-
vation within the right IFG/Ins is secondary to engagement of the
ventral attentional system following the appearance of the stop
signal (30). This right lateralized system includes the tempor-
oparietal junction and right IFG/Ins, and it is engaged by the
detection of unexpected stimuli. In our study, both stop and con-
of a stimulus that has varying behavioral significance. Similar
Sharp et al. PNAS
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| vol. 107
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activation within the right IFG/Ins is observed for both trial types,
subsequent decision-making associated with the cues.
Alternatively, it is possible that subregions within the right
inferior frontal region may support distinct cognitive processes
during behavioral inhibition. A recent study using a go/no-go task
provides some evidence for this (28). In this study two types of go
trials were used, with infrequent go stimuli controlling for the
additional attentional demands of the unexpected no-go stimuli.
Two ROIs were defined based on the contrast of no-go trials and
frequent go trials. A region within the posterior inferior frontal
gyrus showed greater response on no-go trials relative to infre-
quent go trials, in keeping with a specific role in response inhib-
ition, whereas part of the right inferior frontal junction showed a
profile in keeping with attentional capture. In contrast, our own
the right IFG/Ins on the SST, as we observed extensive activation
of the right IFG/Ins for both stopping and continuing.
Differences between the go/no-go task and SST could be
responsible for the discrepancy between our results and those of
Chikazoe and colleagues (31, 32). Although the go/no-gotask and
SST are often thought of as interchangeable ways of assessing
behavioral inhibition, they probe distinct aspects of action
“restraint” and “cancellation” (32). In the go/no-go task, subjects
decide whether to go before the initiation of the motor response,
thus selecting a response strategy at the start of each trial (31). In
contrast, the original form of the SST is specifically designed to
minimize any decision-making, as the cancellation of an already
initiated motor response occurs after the response strategy has
inhibition may thus depend on both attentional capture and the
initiation of a response strategy. This could explain the extensive
activation weobserved within this region duringcontinue trials, as
the introduction of an additional cue increases decision-making
demands relative to the original version of the SST.
Along similar lines, distinct involvement of the pre-SMA and
in task performance on the SST are known to affect inhibitory
processing (12, 33, 34). For example, if subjects slow down on go
trials in an attempt to improve “accuracy,” performance on stop
trials maybechanged,assubjects delay theinitiation ofa response
strategy. In a similar way to a previous study (4), we counteracted
this tendency by providing performance feedback about response
speed adaptively during the experiment. Both studies reduced the
medial PFC is critical for rapid motor inhibition.
Our findings support the results of Li and colleagues (2), who
demonstrated that individuals with better motor inhibition as
measured by the SSRT showed greater activation in the region of
the pre-SMA. However, this is not a consistent finding in the liter-
ature (5), and the use ofthistype ofindividualdifference approach
separate individuals is an accurate and reliable measure of the
underlying cognitive process and that there is significant individual
variability. Our study extends this previous work by experimentally
controlling for attentional confounds in the baseline task and by
limiting strategic changes in task performance to allow a more
precise analysis of the motor inhibition, emphasizing the role of
Successful behavioral inhibition involves the interaction
betweenthe rightIFG/Ins andthe pre-SMA,aswellassubcortical
regions. Recent work has begun to investigate structural and
functional connections within this network. White matter tracts
directly connect the right IFG to both the pre-SMA and the sub-
thalamic nucleus, providing a putative circuit for their interaction
during motor control (5). Functional connectivity has been shown
to increase between the right IFG/Ins and the pre-SMA during
successful stopping, and Grainger causality analysis of the SST
provides evidence that the right IFG/Ins influences motor
response through its interaction with the pre-SMA (29). Thus,
damage to the IFG/Ins could be expected to impair stopping sec-
of neurons directly coding response inhibition.
engaged differentially during attempts to stop an action that has
already been initiated. The attentional capture of low-frequency
is engaged as part of the ventral attentional system. Recognition of
the stop signal creates response conflict, which engages the rostral
pre-SMA regardless of the outcome of inhibitory processing. The
engages an error processing system within the rostral ACC. In
contrast, both successful inhibition and the slowing of an already
initiated response are dependent on the caudal/lateral pre-SMA, a
region able to rapidly influence motor cortical activity.
Materials and Methods
Participants. Twenty-six right-handed healthy adult volunteers (nine women)
were recruited, with a mean age of 34y (range, 23–59 y). All participants gave
written consent. The experiment was approved by the Hammersmith and
Queen Charlotte’s and Chelsea Research ethics committee. Subjects had
normal or corrected-to-normal vision and had no neurological, major med-
ical, or psychiatric disorders.
SST. The SST is a two-choice CRT task in which participants are required to
respond to one or more go stimuli. At irregular intervals and unpredictably
for the participants, a stop signal is presented (1). Following this stop signal,
participants are required to attempt to inhibit their response to the go
signal. We used two versions of the SST. The first (original SST) was similar to
previous versions of the task used in neuroimaging studies. A second version
(controlled SST) was designed to control for the attentional confound
inherent in the original version. In both versions, subjects were presented
with an initial fixation cross for 350 ms. This was followed by a go signal
lasting 1,400 ms in the form of a left- or right-pointing arrow in the direction
of the required response (Fig. 1). Finger presses were made with the index
finger of each hand. Unpredictably, on 20% of the trials, a red circle (the
stop signal) appeared above the location of the go stimulus. This stop signal
indicated the need to attempt to inhibit the button press. The delay
between the presentation of the go and stop signals is termed the stop
signal delay (SSD). The ability to stop a response is a function of the length
of the SSD. The longer the SSD, the more difficult it is to stop. The SSD was
varied from trial to trial using a staircase procedure that converged subjects
toward an overall performance of 50% for each run (see SI Materials and
Methods for further details). In our controlled version of the SST, we
introduced a continue signal in the form of a green circle presented below
the go signal (Fig. 1). Subjects were instructed that, on some trials, this
continue signal would appear unpredictably, but this should not alter their
response, i.e., the initiated response to the go signal should be completed.
The continue signal occurred on the same number of trials (20%) as the stop
signal and with the same timing as the previous stop signal. The duration of
both stop and continue cues was 1,400 msec minus the current SSD. Con-
tinue trials thus provide a control condition for the attentional processing
associated with the presentation of an unexpected perceptual event in a
context in which response inhibition is not required. We also introduced a
further modification of the SST to limit any strategic slowing on the task by
providing negative feedback when subjects slowed on the task (see SI
Materials and Methods for a justification and further details).
MR Scanning Procedure. Participants performed two runs of the original and
controlled SST, each with 184 trials and an interstimulus interval of 1.75 s. The
order of the runs was counterbalanced across subjects. The original SST
consisted of 20% stop and 70% go trials, with 10% randomly interspersed
“rest” trials consisting of a visual fixation cross. The controlled SST consisted
of 20% stop, 20% continue, 50% go, and 10% rest trials. Stimulus order was
randomized within a run (see SI Materials and Methods for more informa-
tion). Before the SST, subjects performed a simple CRT task. This was iden-
tical to the original SST except that only go trials were presented. MRI data
were obtained using a Philips Intera 3.0-T MRI scanner (see SI Materials and
Methods for further information).
| www.pnas.org/cgi/doi/10.1073/pnas.1000175107Sharp et al.
Functional MRI Analysis. Imaging analysis was performed using FEAT (FMRI Download full-text
Expert Analysis Tool) version 5.98, a part of FSL version 4.1.2 [FMRIB Software
Library (35)]. Image preprocessing involved realignment of EPI images to
remove the effects of motion between scans, spatial smoothing using a
8-mm full-width half-maximum Gaussian kernel, prewhitening using FILM,
and temporal high-pass filtering using a cutoff frequency of 1/50 Hz to
correct for baseline drifts in the signal. The FMRIB Linear Image Registration
Tool was used to register echoplanar imaging functional datasets into
standard Montreal Neurological Institute space using the participant’s indi-
vidual high resolution anatomical images (36). Functional MRI data were
analyzed using voxel-wise time series analysis within the framework of the
General Linear model (see SI Materials and Methods for further informa-
tion). Mixed-effects analysis of session and group effects was carried out by
using the FMRIB Local Analysis of Mixed Effects. Final statistical images were
thresholded using Gaussian random field–based cluster inference with a
height threshold of Z > 2.3 and a cluster significance threshold of P < 0.05.
ACKNOWLEDGMENTS. This work was supported by The Medical Research
Council (United Kingdom) and The Hammersmith Hospitals Trustees’
1. Logan GD, Cowan WB, Davis KA (1984) On the ability to inhibit simple and choice
reaction time responses: a model and a method. J Exp Psychol Hum Percept Perform
2. Li CS, Huang C, Constable RT, Sinha R (2006) Imaging response inhibition in a stop-
signal task: neural correlates independent of signal monitoring and post-response
processing. J Neurosci 26:186–192.
3. Aron AR, Fletcher PC, Bullmore ET, Sahakian BJ, Robbins TW (2003) Stop-signal
inhibition disrupted by damage to right inferior frontal gyrus in humans. Nat
4. Floden D, Stuss DT (2006) Inhibitory control is slowed in patients with right superior
medial frontal damage. J Cogn Neurosci 18:1843–1849.
5. Aron AR, Behrens TE, Smith S, Frank MJ, Poldrack RA (2007) Triangulating a cognitive
control network using diffusion-weighted magnetic resonance imaging (MRI) and
functional MRI. J Neurosci 27:3743–3752.
6. Rubia K, Smith AB, Brammer MJ, Taylor E (2003) Right inferior prefrontal cortex
mediates response inhibition while mesial prefrontal cortex is responsible for error
detection. Neuroimage 20:351–358.
7. Aron AR, Poldrack RA (2006) Cortical and subcortical contributions to Stop signal
response inhibition: role of the subthalamic nucleus. J Neurosci 26:2424–2433.
8. Chevrier AD, Noseworthy MD, Schachar R (2007) Dissociation of response inhibition
and performance monitoring in the stop signal task using event-related fMRI. Hum
Brain Mapp 28:1347–1358.
9. Stuphorn V, Schall JD (2006) Executive control of countermanding saccades by the
supplementary eye field. Nat Neurosci 9:925–931.
10. Isoda M, Hikosaka O (2007) Switching from automatic to controlled action by monkey
medial frontal cortex. Nat Neurosci 10:240–248.
11. Logan GD (1994) On the ability to inhibit thought or action: a user’s guide to the stop
signal paradigm. Inhibitory processes in attention, memory, and language, eds
Dagenbach D, Carr TH (San Diego, Academic Press), pp 189–239.
12. Liddle EB, et al. (2009) Looking before you leap: a theory of motivated control of
action. Cognition 112:141–158.
13. de Fockert J, Rees G, Frith C, Lavie N (2004) Neural correlates of attentional capture in
visual search. J Cogn Neurosci 16:751–759.
14. Corbetta M, Kincade JM, Shulman GL (2002) Neural systems for visual orienting and
their relationships to spatial working memory. J Cogn Neurosci 14:508–523.
15. Li CS, et al. (2008) Neural correlates of post-error slowing during a stop signal task: a
functional magnetic resonance imaging study. J Cogn Neurosci 20:1021–1029.
16. Fried I, et al. (1991) Functional organization of human supplementary motor cortex
studied by electrical stimulation. J Neurosci 11:3656–3666.
17. Luders H, et al. (1988) Localization of cortical function: new information from
extraoperative monitoring of patients with epilepsy. Epilepsia 29 (suppl 2):S56–S65.
18. Mars RB, et al. (2009) Short-latency influence of medial frontal cortex on primary
motor cortex during action selection under conflict. J Neurosci 29:6926–6931.
19. Chen CY, Muggleton NG, Tzeng OJ, Hung DL, Juan CH (2008) Control of prepotent
responses by the superior medial frontal cortex. Neuroimage 44:537–545.
20. Mostofsky SH, Simmonds DJ (2008) Response inhibition and response selection: two
sides of the same coin. J Cogn Neurosci 20:751–761.
21. Coxon JP, Stinear CM, Byblow WD (2009) Stop and go: the neural basis of selective
movement prevention. J Cogn Neurosci 21:1193–1203.
22. Gehring W, Goss B, Coles M (1993) A neural system for error detection and
compensation. Psychol Sci 4:385–390.
23. Falkenstein M, Hoormann J, Christ S, Hohnsbein J (2000) ERP components on reaction
errors and their functional significance: a tutorial. Biol Psychiatry 51:87–107.
24. Sharp DJ, Scott SK, Mehta MA, Wise RJ (2006) The neural correlates of declining
performance with age: evidence for age-related changes in cognitive control. Cereb
25. Debener S, et al. (2005) Trial-by-trial coupling of concurrent electroencephalogram
and functional magnetic resonance imaging identifies the dynamics of performance
monitoring. J Neurosci 25:11730–11737.
26. Swick D, Turken AU (2002) Dissociation between conflict detection and error
monitoring in the human anterior cingulate cortex. Proc Natl Acad Sci USA 99:
27. Nachev P, Rees G, Parton A, Kennard C, Husain M (2005) Volition and conflict in
human medial frontal cortex. Curr Biol 15:122–128.
28. Chikazoe J, et al. (2009) Functional dissociation in right inferior frontal cortex during
performance of go/no-go task. Cereb Cortex 19:146–152.
29. Duann JR, Ide JS, Luo X, Li CS (2009) Functional connectivity delineates distinct roles of
the inferior frontal cortex and presupplementary motor area in stop signal inhibition.
J Neurosci 29:10171–10179.
30. Corbetta M, Shulman GL (2002) Control of goal-directed and stimulus-driven
attention in the brain. Nat Rev Neurosci 3:201–215.
31. Eagle DM, Bari A, Robbins TW (2008) The neuropsychopharmacology of action
Psychopharmacology (Berl) 199:439–456.
32. Schachar R, et al. (2007) Restraint and cancellation: multiple inhibition deficits in
attention deficit hyperactivity disorder. J Abnorm Child Psychol 35:229–238.
33. Alderson RM, Rapport MD, Sarver DE, Kofler MJ (2008) ADHD and behavioral
inhibition: a re-examination of the stop-signal task. J Abnorm Child Psychol 36:
34. de Zeeuw P, et al. (2008) Inhibitory performance, response speed, intraindividual
variability, and response accuracy in ADHD. J Am Acad Child Adolesc Psychiatry 47:
35. Smith SM, et al. (2004) Advances in functional and structural MR image analysis and
implementation as FSL. Neuroimage 23:S208–S219.
36. Jenkinson M, Bannister P, Brady M, Smith S (2002) Improved optimization for the
robust and accurate linear registration and motion correction of brain images.
Sharp et al.PNAS
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| vol. 107
| no. 13