Mapping Motor Inhibition: Conjunctive Brain Activations across Different
Versions of Go/No-Go and Stop Tasks
Katya Rubia,1Tamara Russell, Stephan Overmeyer, Michael J . Brammer, Edward T. Bullmore,*
Tonmoy Sharma, Andrew Simmons, Steve C. R. Williams, Vincent Giampietro,
Chris M. Andrew, and Eric Taylor
Institute of Psychiatry, King’s College, London; and *Department of Psychiatry, Addenbrooke’s Hospital, Cambridge, United Kingdom
Received March 17, 2000; published online December 21, 2000
Conjunction analysis methods were used in func-
tional magnetic resonance imaging to investigate
brain regions commonly activated in subjects per-
forming different versions of go/no-go and stop tasks,
differing in probability of inhibitory signals and/or
contrast conditions. Generic brain activation maps
highlighted brain regions commonly activated in (a)
two different go/no-go task versions, (b) three differ-
ent stop task versions, and (c) all 5 inhibition task
versions. Comparison between the generic activation
maps of stop and go/no-go task versions revealed in-
hibitory mechanisms specific to go/no-go or stop task
performance in 15 healthy, right-handed, male adults.
In the go/no-go task a motor response had to be selec-
tively executed or inhibited in either 50% or 30% of
trials. In the stop task, the motor response to a go-
stimulus had to be retracted on either 50 or 30% of
trials, indicated by a stop signal, shortly (250 ms) fol-
lowing the go-stimulus. T he shared “inhibitory” neu-
rocognitive network by all inhibition tasks comprised
mesial, medial, and inferior frontal and parietal corti-
ces. Generic activation of the go/no-go task versions
identified bilateral, but more predominantly left hemi-
spheric mesial, medial, and inferior frontal and pari-
etal cortices. Common activation to all stop task ver-
anterior cingulate, supplementary motor area, infe-
rior prefrontal, and parietal cortices. On direct com-
parison between generic stop and go/no-go activation
maps increased BOL D signal was observed in left
hemispheric dorsolateral prefrontal, medial, and pari-
etal cortices during the go/no-go task, presumably
reflecting a left frontoparietal specialization for re-
Key Words: fMR I; neuroimaging; motor response in-
hibition; response selection; motor preparation; motor
attention; conjunction analysis.
© 2001 Academic Press
Control of behavior and impulse is a higher-order
function that evolves late, phylogenetically as well as
ontogenetically, and has been suggested to be sub-
served by the frontal lobes (Fuster, 1989). Every be-
havioral, cognitive, or motor act requires a finely tuned
balance between initiatory and inhibitory processes to
provide appropriate preparation, initiation, on-line
control, and timely inhibition of this act. Inhibitory
control is therefore an essential regulatory function. It
develops progressively from childhood to adulthood
(Williams et al., 1999) and is therefore susceptible to
impairment in neurodevelopmental disorders such as
attention deficit hyperactivity disorder (Rubia et al.,
1999, 2000b), conduct disorder, antisocial personality
disorder, obsessivecompulsivedisorder, and Tourette’s
syndrome (Bradshaw, 2000).
Different types of motor acts are likely to be regu-
lated by different inhibitory processes, which may be
mediated by different cortical areas. The parts of the
frontal lobes specifically involved in inhibitory control
may therefore depend on the type of inhibitory process
and the kind of action which needs to be inhibited.
Concordant with this multiple domain model, different
parts of the frontal lobes have been found tobe respon-
sible for different aspects of inhibitory control. Lesions
in orbitofrontal cortex can lead to behavioural and
socioemotional dyscontrol (Fuster, 1989), mesial and
dorsolateral prefrontal brain areas have been related
toreflex inhibition in the antisaccade task (Gaymard et
al., 1998; O’Driscoll et al., 1995; Pierrot-Deseilligny et
al., 1991), the supplementary motor cortex has shown
to be involved in both initiation and suppression of
voluntary movements (Dinner and Lueders, 1995; Ka-
washima et al., 1996; Peterson et al., 1999), dorsolat-
eral, inferior prefrontal, and anterior cingulate cortices
are activated during the more cognitive/attentional
forms of “inhibiting interference” during the Stroop
task (Pardoet al., 1990; Bench et al., 1993; Taylor et al.,
1To whom correspondence and reprint requests should be ad-
dressed. Fax: ?44-0207-7085800; E-mail: email@example.com.
NeuroImage 13, 250–261 (2001)
doi:10.1006/nimg.2000.0685, available online at http://www.idealibrary.com on
Copyright © 2001 by Academic Press
All rights of reproduction in any form reserved.
1997) and during the suppression of previously learned
stimulus–response associations in switching tasks
(Nagahama et al., 1998, 1999; Konishi et al., 1998b,
1999; Dove et al., 2000). Inhibition of a motor response
is the most direct expression of inhibitory control, as it
involves (compared to the more cognitive forms of in-
hibitory control such as interference control) all-or-
none decisions about action or non-action. Several
brain areas have been related to inhibition of a motor
response in stop and go/no-go tasks, including orbital,
inferior, dorsolateral and mesial frontal, temporal and
parietal cortices, as well as cerebellum and basal gan-
glia (Garavan et al., 1999; Rubia et al., 1997, 1999,
2000a,b,c; Konishi et al., 1998a, 1999; Humberstone et
al., 1997; Casey et al., 1997; Kawashima et al., 1996;
Godefroy et al., 1996).
The goal of this study was tofurther investigate and
compare the neurocognitive networks related to two
different forms of motor response inhibition, namely
those required by performing go/no-go and stop tasks,
by use of generic brain image analysis methods similar
to cognitive conjunction (Price and Friston, 1997; Fris-
ton et al., 1999). Such analyses allow exploration of
commonalities in activations of subject groups per-
forming different tasks in relation to functions which
are common to the tasks. In this study, these generic
analysis methods enable the identification of brain re-
gions generically activated during different versions of
go/no-go and stop tasks independent of the specific
effects of the particular task versions (versions differ-
ing in probability of inhibitory signals or in contrast
conditions). Furthermore, the analysis of generic acti-
vation across all stop and go/no-gotask versions allows
the identification of brain regions related to shared
inhibitory control mechanisms involved in both tasks,
independent of the task-specific effects (go/no-go or
stop task performance).
The go/no-go paradigm requires a response selection
process between either executing or inhibiting a motor
response, triggered by a go- or a no-go-stimulus. The
task demands high-level cognitive functions of deci-
sion-making, response selection, and response inhibi-
tion. The stop task requires withholding a motor re-
sponse, which is triggered by a stop signal shortly
following the go signal, thereby converting the go-sig-
nal aposteriori to a no-go signal. It contains a higher
load on response inhibition processes compared to the
go/no-go task in that it involves the retraction of a
response that has already been triggered by a go sig-
nal. Go/no-go tasks have a higher load on response
selection, due to the apriori knowledge about whether
or not to respond, provided by the categorical stimuli.
The common and distinct neural substrates of motor
response inhibition in these two tasks has not previ-
ously been identified. Evidence from lesion studies
points towards the involvement of the mesial frontal
lobes in go/no-go tasks, especially the SMA and ante-
rior cingulate(Drewe, 1975; Leimkuhler and Mesulam,
1985; Verfaellie and Heilman, 1987), but alsodorsolat-
eral, medial prefrontal cortex, and caudate(Godefroy et
al., 1996). Recent modern brain imaging studies using
fMRI have revealed mesial, dorsolateral, and inferior
frontal and parietal involvement in this selective re-
sponse inhibition process (Rubia et al., 2000c; Garavan
et al., 1999; Humberstone et al., 1997). Event related
fMRI has shown that focused activation of predomi-
nantly right inferior frontal cortex correlated with
no-go activity (Konishi et al., 1998a, 1999), as well as
pre-SMA (Humberstone et al., 1997), but also inferior,
mesial, and middle frontal, insular, parietal and tem-
poral lobes (Garavan et al., 1999). The motor response
inhibition process involved in stop tasks has been
shown to elicit predominantly right mesial and infero-
medial prefrontal cortex activation in adults (Rubia et
al., 1997, 2000a,c) and additional caudate activation in
adolescents (Rubia et al., 1999, 2000a).
The goal of this paper was to investigate and com-
pare the neurocognitive networks mediating the two
types of motor inhibitory control required by go/no-go
and stop tasks, independent of the specific contexts of
the task variants as well as to explore shared neuro-
cognitive processes underlying performance on both
Fifteen healthy right-handed male adults, aged 26 to
58 (mean age ? 36 years; standard deviation (SD) ? 7
years), and of average intelligence as measured by a
nonverbal intelligence measure (Raven, 1960) partici-
pated in the study (mean intelligence quotient ? 104 ?
(SD) ? 16). Subjects were divided in subgroups per-
forming different task versions. Groups of performers
did not differ in IQ or task performance (Mean perfor-
mance data. Go/no-gotask1: mean reaction time (MRT
in ms) ? 352 ? 82, mean probability of inhibition (P(I)
in percentage ? 95 ? 8): go/no-gotask2: MRT ? 304 ?
87, P(I) ? 89 ? 9; stop task1: MRT ? 664 ? 66, P(I) ?
93 ? 7; stop task2: MRT ? 624 ? 149, P(I) ? 93 ? 7;
stop task3: MRT ? 576 ? 111, P(I) ? 93 ? 5). All
subjects provided written informed consent. The study
was approved by the Bethlem Royal and Maudsley
NHS Trust Ethics (Research) Committee.
Each paradigm consisted of two main conditions
(control and activation condition), lasting 27 s each,
preceded by a short visual warning cue (lasting 3 s).
Control and activation condition epochs were periodi-
cally alternated five times in the course of a single
experiment lasting 5 min. The control condition was
MAPPING MOTOR INHIBITION WITH fMRI
presented first for each task. Throughout acquisition of
the MR images, subjects responded to the stimuli by
pressing a button with their right thumb, which was
recorded by means of an MR compatible interface to a
Go/no-go task 1.The go/no-go task requires selec-
tion of either a response, indicated by a go signal, or a
“no-response,” indicated by a no-go signal. Interstimu-
lus-interval (ISI) was 1000 ms, including a stimulus
duration of 200 ms followed by a blank screen for 800
ms (27 stimuli per epoch). Go signals (airplanes) and
no-go signals (bombs) alternated with 50% probability
each. Subjects had to respond to airplanes, but not to
bombs. In thecontrol condition airplanes and zeppelins
alternated with a probability of 50% and subjects were
instructed to press a button in response to either stim-
uli. This task controlled for the amount of sensory
stimulation but only partially for the number of motor
responses, which was higher in the control condition
(by 12 responses). Five of the subjects performed go/
no-go task 1.
Go/no-go task 2.This task differed from the first
go/no-go task in that the no-go signals and its control
signals in the control condition appeared in 30% of
trials only, while the go signals appeared in 70% of
trials, in both conditions. A second difference was that
the ISI of the control task was 1300 ms compared to
1000 ms for the activation task, in order to control for
the number of motor responses, but only partially for
the number of visual stimuli, which was higher in the
activation condition (by six stimuli). This task was
performed by seven subjects.
Stop task 1.The stop task requires a motor re-
sponse in response to the go signal, only when the go
signal is not followed by a stop signal. In the activation
condition (stop condition), airplanes appeared on the
screen for 1000 ms, followed by a blank screen for 650
ms (18 stimuli per epoch). On 50% of trials theairplane
was followed by a bomb, which appeared 250 ms after
onset of the airplane, replacing it for 300 ms, and was
then then followed by a blank screen for 1100 ms. The
subject was required to press a button if the airplane
alone appeared, but not if the airplane was followed by
a bomb. The control condition was identical, except
that a zeppelin instead of the bomb appeared on 50% of
trials, and subjects were instructed topress the button
always, whether or not the airplane was followed by a
zeppelin. This task controls for the number of visual
stimuli, but only partially the number of motor re-
sponses which was higher in the control condition (by
eight responses). This task was performed by eight
Stop task 2.A second version of the stop task was
identical to stop task 1, except that the stop stimuli
and its control stimuli in the control conditions ap-
peared with a frequency of 30% of trials instead of 50%
of trials. The conditions were matched for visual stim-
ulation, but only partially for number of motor re-
sponses, which was higher in the activation condition
(by 4 responses). Go-signals appeared in 70% of trials.
This task was performed by seven subjects.
Stop task 3.This stop task was identical to stop
task 2, where stop stimuli and its control stimuli ap-
peared with a frequency of 30%, except that the ISI in
the control condition was 2200 ms compared to the ISI
for 1650 ms of the activation condition. This task con-
trols for the number of motor responses, but only par-
tially for the number of visual stimuli, which was
higher (by 4 stimuli) in the activation condition. This
task was performed by the same seven subjects who
performed stop task 2 (see Table 1).
Gradient-echo echoplanar MR images were acquired
using a 1.5 Tesla GE Signa System (General Electric,
Milwaukee, WI) fitted with Advanced NMR hardware
and software (ANMR, Wolburn MA) at the Maudsley
Hospital, London. A quadrature birdcage head coil was
used for RF transmission and reception. Data were
collected from 15 axial planes parallel to the anterior
that thelowermost slicelay below theinferior border of
the frontal lobe. 100 T*
BOLD contrast (Ogawa et al., 1990) wereacquired with
TE ? 40 ms, TR ? 3300 ms, in-plane resolution ? 3.1
mm, slice thickness ? 5 mm, and slice gap ? 0.5 mm.
Head movement was limited by foam padding within
the head coil and a restraining band across the fore-
head. At the same session, a 43 slice, high resolution
echoplanar image of the whole brain was acquired with
TE ? 40 ms, TI ? 180 ms, TR ? 16 s, in-plane resolu-
tion ? 1.5 mm, slice-thickness ? 3 mm, slice gap ? 0.3
mm for subsequent registration of the fMRI data in
2-weighted MR images depicting
T ABL E 1
Overview of Inhibition Task Versions Performed by the 15 Subjects
Go/no-go 1Go/no-go 2Stop 1 Stop 2Stop 3
Percentage of inhibition
Number of subjects
50% 30%50% 30% 30%
RUBIA ET AL.
standard stereotactic space (Talairach and Tournoux,
Analysis of individual
three-dimensional correction for movement during im-
ageacquisition using standard algorithms (Bullmoreet
al., 1999a), analysis of the individual subject data by
sinusoidal regression yielded estimates for the ampli-
tudes of thesineand cosinecomponents of theresponse
at the frequency of alternation between the activation
and control conditions of each task. These estimates
(gamma and delta) wereused tocomputethestandard-
ised power (fundamental power quotient or FPQ) and
phase of the response at each voxel (Bullmore et al.,
1996). Gamma and delta were then reestimated 10
times at each voxel following random permutation of
the time-series data. This facilitated construction of a
distribution of FPQs under the null hypothesis of no
experimentally determined response at the experimen-
tal design frequency. Tests for activation of any voxel
could then be performed by obtaining the appropriate
critical value from the distribution of “randomized”
FPQs and accepting as activated any voxel whose FPQ
exceeded this threshold (normally set at P ? 0.003) in
the current series of experiments.
Generic analyses. The data were first normalised
for each subject on an inversion recovery echoplanar
imageobtained at twicetheresolution of thefMRI data
in x, y, and z. In a second stage, these were then
transformed into a Talairach template (Talairach and
Tournoux, 1988), constructed by manual transforma-
tion of the structural inversion recovery image from 10
subjects (5 male, 5 female) using the AFNI software
(Cox, 1995) and spatially smoothed by application of a
2-D Gaussian filter (SD ? 3 mm). The transformation
at both stages was done by minimizing the sum of
absolute image differences between the image to be
transformed and the template image using an affine
transformation and at the second stage by a quadratic
warp algorithm. The procedure is described in detail in
Brammer et al. (1997).
The data from the different experiments were com-
bined and several generic analyses with non-paramet-
ric inference at a voxel-wise probability of type I error
P ? 0.0007 were performed on the motion-corrected
fMRI time series at each voxel to explore commonly
activated brain regions (a) in the twodifferent versions
of thego/no-gotask (b) in thethreedifferent versions of
the stop task, and (c) across all five task versions.
Approximate Brodmann areas were assigned to the
voxel with maximum FPQ in each generically activated
2-D cluster by an automated cortical parcellation
scheme described in detail by Wright et al. (1999).
Generic activations (of a, b, and c) were analyzed using
a linear model todetect effects that were dependent on
and independent of the nature of the particular task/
The following regression model can be expressed as
FPQijk ? ?0i ? ?1i Task version ? ?ijk, where FPQijk
denotes the standard power of response to the jth task
(i.e., across the different experiments of (a, b, and c)) in
the kth individual at the ith voxel; ?0i ? ?1i are the
parameters estimated from the model; and ?ij is the
residual error at each voxel. The effect of task version
membership (Task version is the classification param-
eter) is parameterized by ?1iat the ith voxel and the
task version-independent (overall mean) effect by ?0i.
This model was fitted to the Talairach transformed
FPQ data obtained by random permutation of the time
series (see above) as well as the FPQ data obtained by
analysis of the observed time series. Fitting to the
randomized FPQ data permitted construction of distri-
butions of a1i and ?0i under the null hypothesis that
there was no experimentally determined response to
periodic alternation of the different activation and con-
trol conditions of each task. Thenull distributions of ?1i
and a0iwere then used to determine critical values of
the two parameters for statistical significance at the
level of probability P ? 0.0007, allowing for 10 error
voxels. As the main goal of the analysis was toidentify
voxels showing significant responses related to shared
inhibitory processes involved in task performance
across all task conditions, regardless of the particular
task version, we were primarily interested in estimat-
ing and testing experiment-independent effects (a0i).
But since the overall mean can be inflated by a partic-
ularly salient response to one of several experiments,
we included the ?1i term in the model to allow such
responses to be identified and removed from generic
activation maps. Following this conservativecorrection
of the data, significant generic effects across task ver-
sions in (a, b, and c) were then displayed on a morpho-
logical template. The median value of gamma, indicat-
ing the phase of periodic signal change with respect to
the input function, was computed for each generically
activated voxel. Voxels with gamma ? 0 had maximum
signal during the first (control) condition, voxels with
gamma ? 0 had maximum signal value during the
second (activation) condition. Generic brain activation
maps were constructed to represent FPQ and gamma
at each voxel of generic activation in (a) (go/no-go), (b)
(stop), or (c) (stop and go/no-go tasks). Only voxels
activated in phase with the activation condition were
superimposed on a grey-scale template image toform a
generic activation map depicting significant effects in-
dependent from the different task versions.
Task comparison.To estimate the difference be-
tween generic brain activation across all go/no-go task
versions and generic activation across all stop task
versions, data from all experiments werecombined and
fitted to the following analysis of variance (ANOVA)
MAPPING MOTOR INHIBITION WITH fMRI
model at the ith voxel generically activated by the
activation condition in one or both of the tasks (refer-
ring to generic gonogo and generic stop task activa-
F PQi,j? ?i? ? Taskj? ?i,j
Here, FPQi,j denotes the standardized power of re-
sponse by the jth individual at the ith voxel; ?iis the
overall mean power at the ith voxel; and ?i,j is the
residual term for the same individual. Task denotes a
factor coding the main effect of task (generic go/no-go
task activation or generic stop task activations), and
?i? ?Taskjdenotes the mean power of response in the
jth Task. The null hypothesis of zero between-task
difference in mean FPQ was tested by comparing the
observed coefficient ?1tocritical values of its nonpara-
metrically ascertained null distribution. Todothis, the
elements of Task are randomly permuted 10 times at
each voxel; ?1 is estimated at each voxel after each
permutation; and these estimates are pooled over all
intracerebral voxels in standard space to sample the
permutation distribution of ?1. Critical values for a
two-tailed test of size a ? 0.01 are the 100*(?/2)th and
100*(1 ? ?/2)th percentiles of this distribution (Bull-
more et al., 1999b). Note that this uncorrected proba-
bility threshold was used to identify differentially ac-
tivated voxels only within the restricted search volume
of voxels generically activated in the activation condi-
tions of the different stop task and go/no-go task ver-
Voxel clusters containing less than 4 voxels are not
considered in any of the analyses and are not shown in
Generic Activation of Go/No-Go Task Versions
Common activation foci (P ? 0.0007) in the different
versions of the go/no-go task were in bilateral but pre-
dominantly left hemispheric middle (BA 9) and inferior
frontal gyri at the border to the frontal operculum (BA
44/45), left and right mesial frontal cortex, including
anterior cingulate and pre-SMA (BA 8/32/6), left infe-
rior parietal lobe (BA 40), left precuneus (BA 7), and
bilateral extrastriate cortices (BA 18/19) (see Fig. 1,
Generic Activation of Stop Task Versions
Common activation foci across thedifferent stop task
versions (P ? 0.0007) were noted in bilateral, but pre-
dominantly right hemispheric inferior prefrontal/oper-
cular cortex (BA 45), right inferior parietal lobe (BA
40), pre-SMA (BA 6), and anterior cingulate (BA 32)
(see Fig. 1, Table 2b).
Shared Activation in All Inhibition Task Versions
Common foci of activation across all fivego/no-goand
stop task versions (P ? 0.0007) were observed in left
and right inferior (BA 47/44), right middle frontal gy-
rus (BA 9/6), anterior cingulate (BA 8/32), pre-SMA
(BA 6), right inferior parietal lobe (BA 40), and pre-
dominantly left middle temporal cortex (BA 21) (see
Fig. 2, Table 2c).
Differences between Generic Go/No-Go Task
Activation and Generic Stop Task Activation
The search volume for the differences between the
generic go/no-go and generic stop task activations was
limited to the generic activations found in each of the
two conjunctive analyses. The search volume in these
regions of conjunctive activations in either go/no-go or
stop tasks or both of them was 514 voxels and the
voxel-wise probability of false positive test was P ?
0.01. At this size of test we expect five false-positive
tests. In fact we observed significant differences at 77
voxels. The differences were in left middle prefrontal
gyrus (BA 9), in left inferior parietal lobe (BA 40), and
in left medial frontal cortex (BA 32/6). In each region
there was increased BOLD response during the go/
no-go task compared to the stop task (see Fig. 3,
Concerted activation of mesial, middle, and inferior
frontal and inferior parietal lobes appear to mediate
performance on tasks requiring the inhibition of a mo-
tor response. While selective inhibition in a go/no-go
task activates a bilateral, but more left hemispheric
withholding a planned motor response in a stop task
elicits a predominantly right hemispheric homologue
Our observation of a neural network of anterior cin-
gulate, pre-SMA, dorsolateral, and inferior frontal and
inferior parietal cortices during go/no-go task perfor-
mance confirms previous findings. The middle and in-
ferior frontal foci of activation of our study are in close
proximity to the middle and inferior activation foci in
the event related fMRI study of Garavan et al. (1999)
and Konishi et al. (1999) (in inferior frontal lobe), with
the difference that the foci in middle and inferior fron-
tal gyri were more prominent in the right hemisphere
in those studies as opposed to the left hemisphere
predominance in our study (inferior lobe Talairach co-
ordinates (mm); Garavan et al., 42, 40, ?2; Konishi et
al., 41, 16, 19; this study, ?49, 11, 9; middle frontal
gyrus, Garavan et al., 36, 23, 33; this study, ?35, 19,
37). Bilateral foci in anterior cingulate as well as infe-
rior parietal lobes were also found by Garavan et al.
RUBIA ET AL.
(1999), again more prominently right hemispheric
compared to our left hemisphere predominance (Gara-
van et al., 1999). Studies using block designed go/no-go
tasks have observed activation in bilateral anterior
cingulate, middle prefrontal and inferior frontal corti-
ces (Casey et al., 1997; Kawashima et al., 1996; Krams
et al., 1999). Differences between studies in go/no-go
task designs and contrast conditions may explain the
differences in laterality or precise localization. Despite
these differences, however, common areas of activation
have been identified, especially in medial, middorsolat-
eral, and inferior frontal lobes. From these, the most
consistent activation found across studies is in inferior
frontal lobes. Right and left inferior frontal cortices are
involved in a wide range of high level cognitive func-
tions, including language processing, working memory
and attention. Many of these executive functions in-
volve aspects of inhibitory control, such as inhibition of
interference in attention or working memory tasks.
The inhibitory role of inferior frontal cortex therefore
seems not to be limited to the motor domain. Inferior,
and also occasionally middorsolateral prefrontal corti-
ces, have been found to be activated during working
memory conditions with high inhibitory demand
T ABL E 2
Main Brain Regions Generically Activated (Omnibus P ? 0.0003) in (a) Go/No-Go Task, (b) Stop Task, (c) Go/No-Go and
Stop Task, and (d) Differences between Generic Activations in Go/No-Go and Stop Tasks (Using Region of Interest Analysis
Approach at P ? 0.01)
Cerebral regionBASidex, y, zPN
(a) Generic Go/no-go
?35, 19, 37
46, 22, 31
?49, 11, 9
40, 3, 31
3, 31, 42
?3, 0, 42
3, 14, 48
?52, 28, 37
49, ?50, 37
?38, ?75, ?2
17, ?69, 42
?12, ?64, 48
6L ? R
(b) Generic stop task
49, 3, 4/40, 17, 9
?40, 11, 4
49, ?42, 37
3, 3, 53
6, 25, 37
common to all go/
no-go and stop
?49, 11, 4
49, 3, 4
43, 3, 37
3, 31, 37/3, 14, 42
3, 11, 48
46, ?42, 37
?49, ?44, 9
61, ?28, 4
go/no-go and stop
?32, 6, 37
?52, ?28, 37
?6, 0, 42
Note. BA, approximate Brodmann area; P, probability of maximum regional difference in fundamental power quotient (FPQ); N, number
of voxels; x, y, z refer to Talairach coordinates (mm).
MAPPING MOTOR INHIBITION WITH fMRI
(Smith and J onides, 1996; J onides et al., 1998), during
control of distraction (Chao and Knight, 1995), during
inhibition of habitual responses in Stroop tasks (Pardo
et al., 1990; Bench et al., 1993; Taylor et al., 1997;
Carter et al., 1999a), and during inhibition of previ-
F IG. 1.
corresponds to the left side of the image. The voxel-wise probability of Type I error is P ? 0.0007.
Generic activation of the different task/contrast conditions of (a) go/no-go and (b) stop tasks. The right side of the brain
F IG. 2.Generic activation across all 5 go/no-go and stop task versions. P ? 0.0007.
RUBIA ET AL.
switching tasks (Konishi et al., 1998a, 1999; Naga-
hama et al., 1998, 1999; Dove et al., 2000).
Lesion studies have traditionally implicated the ad-
jacent orbito-frontal lobes in behavioral and emotional
inhibition in animals (Fuster, 1989; Brutkowski et al.,
1964; Iverson and Mishkin, 1970) and in humans (Fus-
ter, 1989; Stuss and Benson, 1986; Rolls et al., 1994;
Malloy et al., 1993). Susceptibility effects at the air–
tissue interface in the perinasal sinuses can make it
difficult to observe orbitofrontal activation in fMRI;
while it is conceivable that orbitofrontal cortex is more
prominently related to behavioral and emotional
rather than motor inhibition, we can, however, not
exclude a potential role of orbitofrontal cortex in inhib-
itory motor control based on fMRI data.
The middorsolateral prefrontal focus could be re-
lated to other noninhibitory functions, which were not
optimally controlled for by the executive control condi-
tions, such as selective attention, conflict monitoring,
motor preparation, and response selection. Dorsolat-
eral prefrontal cortex has been attributed a role in
selective attention and response selection (Decary and
Richter, 1995; Sakai et al., 2000; Passingham, 1993;
Deiber et al., 1996; J ueptner et al., 1997; Rubia et al.,
1998). The implication of dorsolateral prefrontal cortex
in response selection is supported by the fact that the
main dorsolateral prefrontal focus was during the go/
no-go task, which has a higher load on response selec-
tion compared to the stop task.
Pre-SMA and the proximal, closely connected rostral
anterior cingulate have reciprocal anatomical connec-
tions with lateral prefrontal and parietal brain regions
(Bates and Goldman-Rakic, 1993; Picard and Strick,
1996). As stated above, these medial frontal brain ar-
eas have been shown by several studies to be involved
in situations where motor responses need to be inhib-
ited, based on modern neuroimaging (see above), elec-
trophysiological (Brandeis et al., 1998; Naito and Mat-
Leimkuhler and Mesulam, 1985; Verfaellie and Hei-
lman, 1987). It is conceivable, however, that the role of
medial frontal cortex during inhibition task perfor-
mance is not restricted to the process of inhibition
itself. Evidence exists for a more general, metamotor,
attentional control function of medial frontal cortex,
required for, but not specific to complex motor inhibi-
tion task situations. Neuroimaging studies haveattrib-
uted a wide range of executive supervisory and atten-
tionalcontrolfunctions to pre-SMA
anterior cingulate, such as attention for action, re-
data (Drewe, 1975;
F IG. 3.
volume was restricted to generically activated voxels in the 2 go/no-go or the 3 stop tasks (ANOVA map). The voxel-wise probability of Type
I error is P ? 0.01.
Areas of significant increased power of BOLD signal response during go/no-go compared to stop task performance. The search
MAPPING MOTOR INHIBITION WITH fMRI
sponse monitoring and motor preparation; while the
more caudal parts of anterior cingulate and SMA have
been found to be involved in motor execution itself (for
overview see Picard and Strick, 1996; Passingham,
1996; Posner and Digirolamo, 1997). Both areas have
thus been found to be activated in complex and novel
versus simple and learned performance (Paus et al.,
1993; J enkins et al., 1994), in motor preparation and
initiation (J enkins et al., 2000; Warburton et al., 1998;
Abdullaev and Posner, 1998; D’Eposito et al., 1995;
Deiber et al., 1996, 1999), in responseselection (Paus et
al., 1993; Devinsky et al., 1995; Elliott and Dolan,
1998; Peterson et al., 1999) and in motor timing (Raoet
al., 1997; Rubia et al., 1998). Most recently, anterior
cingulate has been attributed a role in the high-level
cognitive functions of task switching (Nagahama et al.,
1999) and monitoring response competition (Carter et
al., 1999b; Botvinick et al., 1999), both of which are
required by go/no-go and stop tasks. A more general
meta-motor control function of medial frontal cortex is
also supported by findings of studies using inhibition
tasks. We have observed a biphasic response of ante-
rior cingulate during delay and stop tasks in the acti-
vation and their fMRI contrast conditions (Rubia et al.,
1998, 1999). Anterior cingulateactivation disappears if
a go/no-go task is subtracted from a response selection
task (Kawashima et al., 1996) and is equally engaged
in the processes of response inhibition, response selec-
tion and target detection in different modifications of
go/no-go-like tasks (Braver et al., 2000). In the Stroop
task, anterior cingulate activation has been shown to
be related toresponse selection and selective attention
processes rather than tointerferenceinhibition (Taylor
et al., 1997). Pre-SMA has found tobe activated during
both “go” and “no-go” trials in go/no-gotasks (Humber-
stone et al., 1997). Thus, medial prefrontal activation
during inhibition tasks may not necessarily reflect an
inhibitory function, but a multipurpose and metamotor
attentional control function in a multifunctional net-
work necessary for performance of inhibition tasks,
involving selective attention, conflict monitoring, re-
sponse selection and ultimately response inhibition.
Alternatively, it is alsoconceivable that particular sub-
regions in pre-SMA and in anterior cingulate are re-
sponsible for inhibition of motor responses, while other
parts are mediating response execution (Dinner and
Lueders, 1995; Peterson et al., 1999).
The stop task has rarely been used in functional
imaging. The predominantly right hemispheric net-
work of medial and inferior prefrontal cortex found
here is strikingly similar to the network we observed
previously in healthy adults (Rubia et al., 1997, 2000c)
and adolescents (Rubia et al., 1999, 2000a,b), with the
exception of an additional caudate activation found in
adolescents, possibly reflecting a reliance on subcorti-
cal structures in younger subjects. The medial prefron-
tal focus is in line with electrophysiological activity
found over frontocentral brain areas during stop task
performance, assumed to lie close to the SMA (DeJ ong
et al., 1990, 1995; Naito and Matsamura, 1996; Bran-
deis et al., 1998).
Left inferior parietal activation in our go/no-go task
and theright parietal homologuein thestop task arein
close proximity tothe bilateral inferior parietal activa-
tions in Garavan’s study (Garavan et al., 1999). Pari-
etal activation is also unlikely to be related to motor
inhibition per se, but rather to movement-related
visuospatial attentional demands which might have
been higher in the inhibition tasks compared to their
executive control conditions. Although visual stimula-
tion was controlled for, the conflict situation of either
execution or inhibition, depending on the signal con-
text, may have produced the activation in inferior pa-
rietal brain regions. The anterior part of inferior pari-
etal cortex, closely connected to the other areas
activated in this study, has been related to motor at-
tention/motor control (Rushworth et al., 1997) and to
preparation for movements (Decety et al., 1992; Deiber
et al., 1991, 1996), especially in situations where visual
cues need to be integrated into movement preparation
and selection (Grafton et al., 1992). Stop and go/no-go
task performance may thus produce a high load on this
“sensorimotor interface” role of the inferior parietal
cortex (Mattingley et al., 1998).
The left hemispheric medial, dorsolateral and pari-
etal activation specific to go/no-go task performance
may be related to the role of these left-hemispheric
regions in higher level motor planning and response
selection (Kimura, 1993; Rushworth et al., 1997, 1998),
which is in greater demand in thego/no-gocompared to
the stop task. Specifically left anterior cingulate (El-
liott and Dolan, 1998; Badgaiyan and Posner, 1998),
left pre-SMA (Stephan et al., 1995; Rubia et al., 1998),
and left dorsolateral prefrontal cortex (Stephan et al.,
1995; Thompson-Schill et al., 1997; Desmond et al.,
1998; Rushworth et al., 1998; Rubia et al., 1998) have
been found to be involved in response selection; left
inferior parietal lobe has been shown to play a role in
movement preparation and fine-motor control (Rush-
worth et al., 1997).
In conclusion, using a range of conjunctive brain
activation and ANOVA analysis methods we have
shown that theneurocognitivenetwork subserving mo-
tor response inhibition involves bilateral middle and
inferior frontal gyri, anterior cingulate, pre-SMA, and
inferior parietal cortex. Inferior frontal cortex may be
specifically related to motor response inhibition, while
dorsolateral, medial prefrontal, and parietal cortices
are possibly mediating more general metamotor exec-
utive control functions such as motor attention, conflict
monitoring, and response selection, necessary for inhi-
bition task performance. While activations during stop
task performance were more right-hemispheric, the
go/no-go task with lower load on inhibition elicited
RUBIA ET AL.
specific left hemispheric dorsolateral, medial prefron-
tal, and parietal activations, presumably responsible
for response selection.
S.O. and K.R. were supported by European Fellowships from the
European Union Programme for the Training and Mobility of Re-
searchers. E.B. was supported by the Wellcome Trust.
Abdullaev, Y. G., and Posner, M. I. 1998. Event-related brain poten-
tial imaging of semantic encoding during processing of single
words. NeuroImage 7: 1–13.
Badgaiyan, R. D., and Posner, M. 1998. Mapping thecingulatecortex
in response selection and monitoring. NeuroImage 7: 255–260.
Bates, J . F., and Goldman-Rakic, P. S. 1993. Prefrontal connections
of medial motor areas in therhesus monkey. J . Comp. Neurol. 336:
Bench, C. J ., Frith, C. D., Friston, K. J ., Frackowiak, R. S., and
Dolan, R. J . 1993. Investigations of the functional anatomy of
attention using the Stroop test. Neuropsychologia 31(9): 907–922.
Botvinick, M., Nystrom, L. E., Fissell, K., Carter, C. S., and Cohen,
J . D. 1999. Conflict monitoring versus selection-for-action in ante-
rior cingulate cortex. Nature 402: 179–181.
Bradshaw, J . L. 2000. Neurodevelopmental Fronto-Striatal Disor-
ders. Psychology Press, London.
Brammer, M. J ., Bullmore, E. T., Simmons, A., Williams, S. C. R.,
Grasby, P. M., Howard, R. J ., Woodruff, P. W. R., and Rabe-
Hesketh, S. R. 1997. Generic brain activation mapping in func-
tional magnetic resonance imaging: A nonparametric approach.
Magn. Reson. Imag. 15(7): 763–770.
Brandeis, D., Leeuwen, T. H., Rubia, K., Vitacco, D., Steger, J .,
Borntraeger, E., and Steinhausen, H. C. 1998. Neuroelectric pre-
cursors of stop failures in children with attention problems. Behav.
Brain Res. 94(1): 111–125.
Braver, T., Barch, D., Molfese, D., and Ollinger, J . 2000. Anterior
cingulate activation is sensitive to response probability but not
response inhibition. NeuroImage 11(5), S55.
Brutkowski, S. 1964. Prefrontal cortex and drive inhibition. In The
Frontal Granular Cortex and Behaviour (J . Warren and K. Akert,
Eds.), pp. 242–270. McGraw-Hill, New York.
Bullmore, E. T., Brammer, M. J ., Williams, S. C. R., Rabe-Herketh,
S., J anot, N., David, A. S., Mellers, J . D. C., Howard, R., and Sham,
P. 1996. Statistical methods of estimation and inference for func-
tional MR image analysis. Magn. Reson. Med. 35: 261–277.
Bullmore, E. T., Brammer, M. J ., Rabe-Herketh, S., Curtis, V., Mor-
ris, R. G., Williams, S. C. R., Sharma, T., and McGuire, P. K.
1999a. Methods for diagnosis and treatment of stimulus-correlated
motion in generic brain activation studies using fMRI. Hum. Brain
Map. 7: 38–48.
Bullmore, E. T., Suckling, J ., Overmeyer, S., Rabe-Hersketh, S.,
Taylor, E., and Brammer, M. 1999b. Global, voxel, and cluster
tests, by theory and permutation, for a difference between two
groups of structural MR images of the brain. IEEE Trans. Med.
Imag. 18: 32–42.
Carter, C. S., Botvinick, M. M., and Cohen, J . D. 1999b. The contri-
bution of the anterior cingulate cortex to executive processes in
cognition. Rev. Neurosci. 10(1): 49–57.
Carter, C. S., Mintun, M., and Cohen, J . D. 1999a. Interference and
facilitation effects during selective attention: An H215O PET
study of Stroop task performance. Neuroimage 2(4): 264–272.
Casey, B. J ., Trainor, R., Orendi, J . L., Schubert, A. B., Nystrom,
L. E., Giedd, J . N., Castellanos, F. X., Haxby, J . V., Noll, D. C.,
Cohen, J . D., Forman, S. D., Dahl, R. E., and Rapoport, J . L. 1997.
A developmental functional MRI study of prefrontal activation
during performance of a go/no-go task. J . Cogn. Neurosci. 9: 835–
Chao, L. L., and Knight, R. T. 1995. Human prefrontal lesions
increase distractibility to irrelevant sensory inputs. NeuroReport
Cox, R. W. 1995. Analysis and visualisation of 3D fMRI data. Proc.
Third Scientific Meeting. Soc. Magn. Res. 2: 834.
Decary, A., and Richer, F. 1995. Response selection deficits in frontal
excisions. Neuropsychologia 33: 1243–1253.
Decety, J ., Kawashima, R., Gulyoas, B., and Roland, P. E. 1992.
Preparation for reaching: A PET study of the participating struc-
tures in the human brain. Neuroreport 3: 761–764.
deJ ong, R., Coles, M. G. H., Logan, G. D., and Gratton, G. 1990. In
search of the point of noreturn: The control of response processes.
J . Exp. Psychol. Hum. Percept. Perform. 16: 164–182.
deJ ong, R., Coles, M. G. H., and Logan, G. D. 1995. Strategies and
mechanisms in nonselective and selective inhibitory motor control.
J . Exp. Psychol. Hum. Percept. Perform. 21(3): 498–511.
Deiber, M. P., Passingham, R. E., Colebatch, J . G., Friston, K. J .,
Nixon, P. D., and Frackowiak, R. S. 1991. Cortical areas and the
selection of movement, A study with positron emission tomogra-
phy. Exp. Brain Res. 84: 393–402.
Deiber, M. P., Ibanez, V., Sadato, N., and Hallett, M. 1996. Cerebral
structures participating in motor preparation in humans: A
positron emission tomography study. J . Neurophysiol. 75: 233–
Deiber, M. P., Honda, M., Ibanez, V., Sadato, N., and Hallett, M.
1999. Mesial motor areas in self-initiated versus externally trig-
gered movements examined with fMRI: Effect of movement type
and rate. J . Neurophysiol. 81: 3065–3077.
D’Eposito, M., Detre, J . A., Alsorp, D. C., Shin, R. K., Atlas, S., and
Grossman, M. 1995. The neural basis of the central executive
system of working memory. Nature 378: 279–281.
Desmond, J . E., Gabrieli, J . D., and Glover, G. H. 1998. Dissociation
of frontal and cerebellar activity in a cognitive task: Evidence for a
distinction between selection and search. Neuroimage 7(4): 368–
Devinsky, O., Morrell, M. J ., and Vogt, B. A. 1995. Contributions of
the anterior cingulate cortex to behaviour. Brain 118: 279–306.
Dinner, D. S., and Lueders, H. O. 1995. Human Supplementary
Motor Area- Electrical stimulation and movement-related poten-
tial studies. In Epilepsy and theFunctional Anatomy of theFrontal
Lobe (H. H. J asper, S. Riggio, and Goldman-Rakic, Eds.) Raven
Press, New York.
Dove, A., Schubert, T., Pollman, S., Norris, D., and v.Cramon, D. Y.
2000. Prefrontal cortex activation in task switching. Cogn. Brain
Res. 9: 103–109.
Drewe, E. A. 1975. Go/no-go learning after frontal lobe lesions in
humans. Cortex 11: 8–16.
O’Driscoll, G. A., Alpert, N. M., Matthysse, S. W., Levy, D. L., Rauch,
S. L., and Holzman, P. S. 1995. Functional neuroanatomy of anti-
saccade eye movements investigated with positron emission to-
mography. Proc. Natl. Acad. Sci. USA 92: 925–929.
Elliott, R., and Dolan, R. J . 1998. Activation of different anterior
cingulate foci in association with hypothesis testing and response
selection. NeuroImage 8(1): 17–29.
Friston, K. J ., Holmes, A. P., Price, C. J ., Buechel, C., and Worsley,
K. J . 1999. Multisubject fMRI studies and conjunction analyses.
NeuroImage 10: 385–396.
MAPPING MOTOR INHIBITION WITH fMRI
Fuster, J . M. 1989. The Prefrontal Cortex: Anatomy, Physiology and
Neuropsychology of the Frontal Lobe. Raven, New York.
Garavan, H., Ross, T. J ., and Stein, E. A. 1999. Right hemispheric
dominance of inhibitory control: An event-related functional MRI
study. Proc. Nat. Acad. Sci. USA 96(14): 8301–8306.
Gaymard, B., Ploner, C. J ., Rivaud, S., Vermersch, A. I., and Pierrot-
Deseilligny, C. 1998. Cortical control of saccades. Exp. Brain Res.
Godefroy, O., Lhullier, C., and Rousseaux, M. 1996. Non-spatial
attention disorder in patients with frontal or posterior brain dam-
age. Brain 119: 191–202.
Grafton, S. T., Mazziotta, J . C., Presty, S., Friston, K. J ., Frackowiak,
R. S., and Phelps, M. E. 1992. Functional anatomy of human
procedural learning determined with regional cerebral blood flow
and PET. J . Neurosci. 12(7): 2542–2548.
Humberstone, M., Sawle, G. V., Clare, S., Hykin, J ., Coxon, R.,
Bowtell, R., Macdonald, I. A., and Morris, P. G. 1997. Functional
magnetic resonance imaging of single motor events reveals human
presupplementary motor area. Ann. Neurol. 42(4): 632–637.
Iverson, S. D., and Mishkin, M. 1970. Perseverative interference in
monkeys following selective lesions of the inferior prefrontal con-
vexity. Exp. Brain Res. 11: 376–386.
J enkins, I. H., Brooks, D. J ., Nixon, P. D., Frackowiak, R. S., and
Passingham, R. E. 1994. Motor sequence learning: A study with
positron emission tomography. J . Neurosci. 14(6): 3775–3790.
J enkins, H., J ahanshahi, M., J ueptner, M., Passingham, R. E., and
Brooks, D. J . 2000. Self-initiated versus externally triggered move-
ments. Brain 123(6): 1216–1228.
J onides, J ., Smith, E. E., Marshuetz, C., Koeppe, R. A., and Reuter-
Lorenz, P. A. 1998. Inhibition in verbal working memory revealed
by brain activation. Proc. Nat. Acad. Sci. USA 95(14): 8410–8413.
J ueptner, M., Stephan, K. M., Frith, C. D., Brooks, D. J ., Frackow-
iak, R. S., and Passingham, R. E. 1997. Anatomy of motor learning.
I. Frontal cortex and attention to action. J . Neurophysiol. 77(3):
Kawashima, R., Satoh, K., Itoh, H., Ono, S., Furumoto, S., Gotoh, R.,
Koyama, M., Yoshioka, S., Takahashi, T., Takahashi, K., Yanagi-
sawa, T., and Fukuda, H. 1996. Functional anatomy of GO/NO-GO
discrimination and response selection-a PET study in man. Brain
Res. 728(1): 79–89.
Kimura, D. 1993. Left hemisphere control of oral and brachial move-
ments and their relation to communication. Phil. Transact. Royal
Soc. London: Biol. Sci. 298: 135–149.
Konishi, S., Nakajima, K., Uchida, I., Kikyo, H., Kameyama, M., and
Miyashita, Y. 1999. Common inhibitory mechanism in human
inferior prefrontal cortex revealed by event-related functional
MRI. Brain 122: 981–991.
Konishi, S., Nakajima, K., Uchida, I., Sekihara, K., and Miyashita, Y.
1998a. No-godominant brain activity in human inferior prefrontal
cortex revealed by functional magnetic resonance imaging. Eur.
J . Neurosci. 10(3): 1209–1213.
Konishi, S., Nakajima, K., Uchida, I., Kameyama, M., Nakahara, K.,
Sekihara, K., and Miyashita, Y. 1998b. Transient activation of
inferior prefrontal cortex during cognitive set shifting. Nature
Neurosci. 1(1): 80–84.
Krams, M., Rushworth, M. F., Deiber, M. P., Frackowiak, R. S., and
Passingham, R. E. 1998. The preparation, execution and suppres-
sion of copied movements in the human brain. Exp. Brain Res.
Leimkuhler, M. E., and Mesulam, M. M. 1985. Reversible go/no-go
deficits in a case of frontal lobe tumor. Ann. Neurol. 18: 617–619.
Malloy, P. F., Bihrle, A., Duffy, J ., Cimino, C. 1993. The orbitomedial
frontal syndrome. Arch. Clin. Neuropsychol. 7: 88–95.
Mattingley, J . B., Husain, M., Rorden, C., Kennard, C., and Driver,
J . 1998. Motor role of human inferior parietal lobe revealed in
unilateral neglect patients. Nature 392(6672): 179–182.
Nagahama, Y., Okada, T., Katsumi, Y., Hayashi, T., Yamauchi, H.,
Sawamoto, N., Toma, K., Nakamura, K., Hanakawa, T., Konishi,
J ., Fukuyama, H., and Shibasaki, H. 1999. Transient neural ac-
tivity in the medial superior frontal gyrus and precuneus time
locked with attention shift between object features. Neuroimage
Nagahama, Y., Sadato, N., Yamauchi, H., Katsumi, Y., Hayashi, T.,
Fukuyama, H., Kimura, J ., Shibasaki, H., and Yonekura, Y. 1998.
Neural activity during attention shifts between object features.
Neuroreport 9(11): 2633–2638.
Naito, E., and Matsamura, M. 1996. Movement-related potentials
associated with motor inhibition under different preparatory
states during performance of two visual stop signal paradigms in
humans. Neuropsychologica 34: 565–573.
Ogawa, S., Lee, T. M., Kay, A. R., and Tank, D. W. 1990. Brain
magnetic resonance imaging with contrast dependent on blood
oxygenation. Proc. Nat. Acad. Sci. USA 3: 9868–9872.
Pardo, J . V., Pardo, P. J ., J aner, K. W., and Raichle, M. E. 1990. The
anterior cingulate cortex mediates processing selection in the
Stroop attentional conflict paradigm. Proc. Natl. Acad. Sci. USA
Passingham, R. E. 1993. The Frontal Lobes and Voluntary Action.
Oxford Univ. Press, Oxford.
Passingham, R. E. 1996. Functional specialisation of the supplemen-
tary motor area in monkeys and humans. In Advances in Neurol-
ogy, Vol. 70: Supplementary Motor Area (H. O. Luders, Eds.), pp.
105–116. Lippingcott-Raven, Philadelphia.
Paus, T., Petrides, M., Evans, A. C., and Meyer, E. 1993. Role of the
human cingulate cortex in the control of oculomotor, manual, and
speech responses: A positron emission tomography study. J . Neu-
rophysiol. 70(2): 453–469.
Peterson, B. S., Skudlarski, P. J ., Gatenby, J . G., Zhang, H., Ander-
son, A. W., and Gore, J . C. 1999. An fMRI study of Stroop word-
color interference: Evidence for cingulate subregions subserving
multiple distributed attentional systems. Biol. Psych. 45: 1237–
Picard, N., and Strick, P. L. 1996. Motor areas of the medial wall: A
review of their location and functional activation. Cerebral Cortex
Pierrot-Deseilligny, C., Rivaud, S., Gaymard, B., and Agid, Y. 1991.
Cortical control of reflexive visually-guided saccades. Brain 114:
Posner, M. I., and DiGirolamo, G. J . 1997. Conflict, target detection
and cognitive control. In The Attentive Brain (R. Parasuraman,
Ed.) MIT Press, Cambridge, MA.
Price, C. J ., and Friston, K. J . 1997. Cognitive conjunction: A new
approach tobrain activation experiments. Neuroimage5: 261–270.
Rao, S. M., Harrington, D. L., Haaland, K. Y., Bobholz, J . A., Cox,
R. W., and Binder, J . R. 1997. Distributed neural systems under-
lying the timing of movements. J . Neurosci. 17(14): 5528–5535.
Raven, J . C. 1960. Guide to the Standard Progressive Matrices. HK
Rolls, E. T., Hornak, J ., Wade, D., and McGrath, J . 1994. Emotion-
related learning in patients with social and emotional changes
associated with frontal lobe damage. J . Neurol. Neurosurg. Psy-
chiatr. 57: 1518–1524.
Rubia, K., Overmeyer, S., Taylor, E., Bullmore, E. T., Brammer, M.,
Williams, S. C. R., Simmons, A., and Andrew, C. 1997. Neuronal
substrate of inhibitory control: A fMRI study. NeuroImage5: S113.
Rubia, K., Overmeyer, S. O., Taylor, E., Brammer, M., Williams, S.,
Simmons, A., Andrew, C., and Bullmore, E. T. 1998. Prefrontal
RUBIA ET AL.
involvement in temporal bridging and timing movement: An fMRI
study. Neuropsychologia 36: 1283–1293.
Rubia, K., Overmeyer, S. O., Taylor, E., Brammer, M., Williams, S.,
Simmons, A., Andrew, C., and Bullmore, E. T. 1999. Hypofrontal-
ity in Attention Deficit Hyperactivity Disorder during higher order
motor control: A study with fMRI. Am. J . Psych. 156(6): 891–896.
Rubia, K., Overmeyer, S. O., Taylor, E., Brammer, M., Williams, S.,
Simmons, A., Andrew, C., and Bullmore, E. T. 2000a. Frontalisa-
tion with age: Mapping neurodevelopmental trajectories with
fMRI. Neurosci. Biobehav. Rev. 24: 13–19.
Rubia, K., Taylor, E., Smith, A., Oksanen, H., Overmeyer, S., Bull-
more, E. T., and Newman, S. 2000b. Neuropsychological analyses
of impulsiveness in childhood hyperactivity. Br. J . Psychiatry, in
Rubia, K., Russell, T. A., Taylor, E., Bullmore, E. T., Brammer, M.,
Williams, S. C. R., Simmons, A., Andrew, C., and Sharma, T.
2000c. An fMRI study of reduced left prefrontal activation in
schizophrenia during normal inhibitory function. Schizophrenia
Res., in press.
Rushworth, M. F., Nixon, P. D., Wade, D. T., Renowden, S., and
Passingham, R. E. 1998. The left hemisphere and the selection of
learned actions. Neuropsychologia 36(1): 11–24.
Rushworth, M. F., Nixon, P. D., Renowden, S., Wade, D. T., and
Passingham, R. E. 1997. The left parietal cortex and motor atten-
tion. Neuropsychologia 35(9): 1261–1273.
Sakai, K., Hikosaka, O., Takino, R., Miyauchi, S., Nielsen, M., and
Tamada, T. 2000. What and when: Parallel and convergent pro-
cessing in motor control. J . Neurosci. 20(7): 2691–2700.
Smith, E. E., and J onides, J . 1998. Neuroimaging analyses of human
working memory. Proc. Natl. Acad. Sci. USA 95: 12061–12068.
Stephan, K. M., Fink, G. R., Passingham, R. E., Sibersweig, D.,
Ceballos-Baumann, A. O., Frith, C. D., and Frackowiak, R. S. J .
1995. Functional anatomy of the mental representation of upper
extremity movements in healthy subjects. J . Neurophysiol. 73:
Stuss, D. T., and Benson, D. F. 1986. TheFrontal Lobes. Raven, New
Talairach, J ., and Tournoux, P. 1988. A Co-Planar Stereotactic Atlas
of the Human Brain. Thieme Medical, New York.
Taylor, S. F., Kornblum, S., Lauber, E. J ., Minoshima, S., and Ko-
eppe, R. A. 1997. Isolation of specific interference processing in the
Stroop task: PET activation studies. Neuroimage 6(2): 81–92.
Thompson-Schill, S. L., D’Esposito, M., Aguirre, G. K., and Farah,
M. J . 1997. Role of left inferior prefrontal cortex in retrieval of
semantic knowledge: A reevaluation. Proc. Natl. Acad. Sci. USA
Verfaellie, M., and Heilman, K. M. 1987. Response preparation and
response inhibition after lesions of the medial frontal lobe. Arch.
Neurol. 44(12): 1265–1271.
Warburton, E., Wise, R. J . S., Price, C., Weiller, C., Hadar, U.,
Ramsay, S., and Frackowiak, R. S. J . 1996. Noun and verb re-
trieval by normal subjects. Studies with PET. Brain 119: 159–179.
Williams, B. R., Ponesse, J . S., Schachar, R. J ., Logan, G. D., and
Tannock, R. 1999. Development of inhibitory control across the life
span. Dev. Psychol. 35(1): 205–213.
Wright, I. C., Sharma, T., Ellison, Z. R., McGuire, P. K., Friston,
K. J ., Brammer, M. J ., Murray, R. M., and Bullmore, E. T. 1999.
Supra-regional brain systems and the neuropathology of schizo-
phrenia. Cereb. Cortex. 9(4): 366–378.
MAPPING MOTOR INHIBITION WITH fMRI