308 | VOL.1 NO.1 | 2006 | NATURE PROTOCOLS
The dorsal anterior midcingulate cortex (daMCC), dorsolateral
prefrontal cortex (DLPFC) and superior portions of parietal cor-
tex combine to form part of a cingulo-frontal-parietal cognitive/
attention network (CFP network)1–5. This brain network plays
critical roles in attention and cognitive processing, but group-ave-
raging techniques have generally been required to obtain sig-
nificant activation of these brain regions in functional neuro-
imaging studies—a fact that limits progress. For example, while
the Counting Stroop task has been useful in studying groups of
healthy volunteers and patients6, it has not been robust enough to
produce brain activation in single subjects. Although such group-
averaged tasks contribute greatly to our understanding of normal
human information processing, pathophysiology and drug effects,
they are not effective for use in clinical functional imaging contexts
since they cannot be used to distinguish a patient from a healthy
subject and/or other diagnostic groups. The MSIT was designed to
address these needs.
In developing the MSIT as a task to be used for assessing the
functional integrity of daMCC and DLPFC in neuropsychiatric
disorders7, we attempted to make it conform as closely as possible
to the characteristics of a hypothesized ideal functional neuroim-
aging-based diagnostic test. Specifically, we strove to ensure that it
possessed the following characteristics: (i) It must produce reliable
and robust activation of the cortical region(s) of interest (ROI)
within healthy individuals. (ii) It should be hypothesis driven (i.e.,
pre-existing evidence should support a mechanism explaining
why the task would be expected to recruit the ROI. (iii) It should
include collection of concomitant imaging and performance data
(reaction times and accuracy). (iv) Testing procedures must be
standardized. (v) The task instructions should be easy to learn and
retain so that the task can be performed by subjects with impaired
cognition (e.g., schizophrenia) and by subjects across a wide age
range (to enable developmental studies in children and studies of
elderly subjects). (vi) It should be of short duration, as children
and elderly subjects generally cannot tolerate protracted testing.
(vii) It should not be language specific (to facilitate cross-cultural
studies). (viii) Performance data should vary within a relatively
narrow range in healthy volunteers. (ix) Imaging and performance
data should be related. (x) Imaging and performance data should
show temporal stability (i.e., it should display sufficient test-retest
reliability to permit longitudinal and treatment studies). (xi)
Imaging and performance data should be sensitive to changes with
successful treatment. (xii) Results should be disorder specific.
Seeking first to use existing tasks to study the attention network
in attention-deficit hyperactivity disorder (ADHD) and schizo-
phrenia, we did pilot work using cognitive interference tasks (in
which the processing of one stimulus feature impedes the simul-
taneous processing of a second stimulus attribute). These would
include Stroop and Stroop-like tasks8–20, Eriksen Flanker-type
tasks21–23 and Simon effect task variants18. While full descrip-
tions of these cognitive interference tasks from which the MSIT
was derived are beyond the scope of this protocol, brief descrip-
tions are given here. The essence of the prototypical cognitive
interference task, the Color Stroop9,24, is that subjects take lon-
ger to name the color of the ink that color-words are written in
when the ink color and word are incongruent (e.g., the word ‘red’
written in blue ink) than when they do match (‘blue’ written in
blue ink) or when the word is a non-color word (‘house’ written
in blue ink). In the Eriksen Flanker Task25 subjects take longer to
identify a centrally located target letter (and make more errors)
when the target letter is flanked by incongruent distractor letters
(e.g., DDTDD) than when it is flanked by the same letter (e.g.,
The Multi-Source Interference Task: an fMRI task
that reliably activates the cingulo-frontal-parietal
George Bush1,2 & Lisa M Shin1,3
1Psychiatric Neuroscience Division, Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Massachusetts General Hospital - East CNY-
2614, Building 149, Thirteenth Street, Charlestown, Massachusetts 02129, USA. 2MGH/MIT/HMS Athinoula A. Martinos Center for Functional and Structural Biomedical
Imaging, Massachusetts General Hospital, Massachusetts Institute of Technology & Harvard Medical School, Boston & Cambridge, Building 149, Thirteenth Street,
Charlestown, Massachusetts 02129, USA. 3Department of Psychology, Tufts University, Medford, Massachusetts 02155, USA. Correspondence should be addressed to G.B.
Published online 27 June 2006; doi: 10.1038/nprot.2006.48
In this protocol we describe how to perform the Multi-Source Interference Task (MSIT), a validated functional magnetic resonance
imaging (fMRI) task that reliably and robustly activates the cingulo-frontal-parietal cognitive/attention network (CFP network)
within individual subjects. The MSIT can be used to (i) identify the cognitive/attention network in normal volunteers and (ii)
test its integrity in people with neuropsychiatric disorders. It is simple to perform, can be completed in less than 15 min and
is not language specific, making it appropriate for children, adults and the elderly. Since its validation, over 100 adults have
performed the task. The MSIT produces a robust and temporally stable reaction time interference effect (range 200–350 ms), and
single runs of the MSIT have produced CFP network activation in approximately 95% of tested subjects. The robust, reliable and
temporally stable neuroimaging and performance data make the MSIT a useful task with which to study normal human cognition
and psychiatric pathophysiology.
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NATURE PROTOCOLS | VOL.1 NO.1 | 2006 | 309
TTTTT). The Simon Effect26 denotes the cognitive interference
produced by spatial incongruence between the target and response
(e.g., given a two-button response pad, it takes longer for subjects
to respond using the left button when the target appears on the
right (and vice versa) than when the stimulus and response posi-
tions correspond). Indeed, these tasks have reliably activated the
CFP network in group-averaged functional neuroimaging studies.
This is not surprising, as such tasks place high demands on tar-
get detection, response selection and performance-monitoring
circuits. However, none was robust enough to reliably and signifi-
cantly activate the CFP network within single subjects. By combin-
ing multiple dimensions of cognitive interference (i.e., Stroop24,
Eriksen25 and Simon26) with decision-making and other factors
known to activate daMCC (target detection, novelty detection,
error detection, response selection, stimulus/response competition
and task difficulty)27 all within a single stimulus trial, the MSIT
(see Fig. 1) maximally taxes the CFP network, making it possible
to reliably activate the CFP network within individuals.
Although the MSIT was developed primarily as a clinical func-
tional neuroimaging test, its robust and stable behavioral and imag-
ing effects also make it a powerful task for studying normal cogni-
tion and drug effects and for longitudinal studies. The MSIT has
already been used to study normal volunteers7,28 and patients with
schizophrenia29, and is currently being used in studies of ADHD
pathophysiology, methylphenidate, atomoxetine and placebo,
obsessive-compulsive disorder (OCD), post-traumatic stress disor-
der (PTSD), depression, aging and Tourette’s; we are also using it in
combined fMRI and intracranial recording studies. It has produced
reliable and robust fMRI activation in approximately 95% of over
100 individuals and has generally supplanted the Counting Stroop
in ongoing studies of cognition (but see ref. 6 for special cases in
which the Counting Stroop is useful and preferable).
The main focus of attention of the MSIT’s design was to develop
a task that would maximally activate daMCC and the rest of the
CFP network. Increasing attention, however, has recently been
paid to understanding task-independent deactivation of ‘affective
circuitry’ during cognitive task performance. More specifically,
reciprocal responses have been repeatedly observed in daMCC
and pregenual anterior cingulate cortex (pACC). That is, complex
cognitive tasks increase daMCC activity and decrease pACC activ-
ity, whereas tasks involving emotion conversely produce decreased
daMCC activity and increased pACC activity1,30–34. McKiernan
and colleagues35 reported that as cognitive task difficulty increased,
the magnitude of task-independent deactivations of pACC also
increased. In keeping with these findings, the MSIT’s high difficul-
ty and potent ability to activate the cognitive/attention CFP net-
work also make it a potent deactivator of ‘affective’ brain regions in
single subjects (including pACC, amygdala and posterior cingulate
cortex). Thus, the MSIT might be used to functionally localize and
test these affective areas in individuals and groups.
The MSIT protocol presented here is the recommended for-
mat to follow for block-formatted fMRI, SPECT or PET studies.
However, it can easily be modified for use with event-related fMRI,
ERPs, MEG or for simple offline behavioral studies. The MSIT is
appropriate for use with subjects age 4 or 5 years and above (for
very young children or elderly adults who may not respond via
button press as quickly as typical adults, the rate of presentation
(interstimulus interval) may be adjusted—in these specialized
cases additional pilot testing may be needed to optimize the inter-
stimulus interval). The MSIT’s instructions can be translated into
nearly any language, and should be presented in the subject’s pri-
The MSIT can be used to study healthy volunteers, control sub-
jects, or subjects with neuropsychiatric disorders as appropriate to
study goals. In all cases, documentation should be made of a his-
tory of neurological, major medical, or psychiatric disorder, medi-
cation status or serious head injury.
It should be noted that, based on our pilot data and early experi-
ence with the task, two minor changes were made to the MSIT since
its original report7. First, the distractors were changed from the let-
ter ‘X’ in the original to zero ‘0’ in the revised version. Second, the
targets and distractors are all presented the same size in the revised
version (in the original version, distractors were always smaller
than the target in the control trials and could be larger or smaller
than the target in the interference trials). Preliminary experience
showed that these changes have had no appreciable effect on either
performance or imaging measures, and the changes have been
instituted to facilitate task instructions and improve consistency of
task presentation characteristics.
Formal testing: functional MRI scanning techniques and data
As detailed above, the MSIT was designed to be an fMRI task, and
the following portion of the protocol details the block-formatted
parameters used. However, the MSIT can and has been easily be
converted to an event-related format for use with event-related
fMRI, ERPs, MEG, intracranial recordings or for simple offline
behavioral performance (reaction time (RT)/accuracy).
Whether displayed on a computer screen (for offline studies,
PET, MEG, ERPs) or projected for use during fMRI, individual sets
of numbers should be easily read without strain but should not
take up a large proportion of the visual field. Generally accepted
guidelines would be to display individual numbers that subtend
approximately 1° of visual angle vertically and 3° horizontally, and
to group them together at the screen center without extra spacing.
Issues for studies of clinical populations
The MSIT possesses many of the qualities deemed desirable in a
functional neuroimaging-based diagnostic test. (i) It reliably and
robustly activates daMCC within individuals. (ii) Mechanistically,
it is hypothesis driven. (iii) It permits collection of concomitant
imaging and performance data. (iv) Testing procedures are stan-
dardized. (v) The task instructions are easy to learn and retain so
that the task can be performed by subjects with impaired cogni-
tion and by subjects across a wide age spectrum. (vi) It can be
completed in a short amount of time. (vii) It is not language spe-
cific, which can facilitate cross-cultural studies (i.e., at least across
those cultures that use Arabic numerals). (viii) Performance data
varied within a relatively narrow range. (ix) Imaging and perfor-
mance data were related (i.e., increased RT was associated with
higher fMRI signal). (x) Imaging and performance data showed
temporal stability. Thus, it appears that the MSIT can be a useful
task in studies of neuropsychiatric patients and normal volunteers.
Of course, although we stress the value of the individual study,
group-averaged MSIT data can also be used with the advantages of
greater power, fewer subjects and higher confidence.
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310 | VOL.1 NO.1 | 2006 | NATURE PROTOCOLS
Although the MSIT shows promise as a cognitive task and
potentially as a task that can assist with diagnosis of neuro-
psychiatric disorders, a vast amount of information about
task characteristics remains to be explored. As larger numbers
of subjects are studied, a greater understanding of the effects
of many factors on performance and imaging results will be
attained. For example, task format (block versus event-related),
individual subject characteristics (age, intelligence, education,
handedness, medication effects, disease presence/absence, affec-
tive state), practice effects and scanner strength can all poten-
tially influence results and will need to be better characterized
via future studies to improve task utility. Similarly, although the
development of the MSIT was hypothesis driven, based upon
the presumed single unit qualities of daMCC7,27, future studies
will help refine our understanding of the mechanisms by which
the various components of the cingulo-fronto-parietal network
operate. Our hope is that presentation of this revised version of
the MSIT will assist other groups in implementing the task in a
standardized way, thus facilitating the building of an MSIT data-
base and comparisons of results among laboratories.
The MSIT produces reliable and robust activation of daMCC
and the rest of the cingulo-fronto-parietal attention network in
individuals and this closely matches the group-averaged data.
Coupled with the reliable and robust performance data, the
MSIT displays many of the characteristics desired in a neuroim-
aging-based diagnostic test. As such, it can be expected to serve
as a useful fMRI probe in searching for the neural substrates of
various neuropsychiatric disorders such as attention deficit dis-
order, schizophrenia, obsessive-compulsive disorder, posttrau-
matic stress disorder and depression. Future studies could also
use task manipulations to further elucidate mechanisms of atten-
tion, response selection and cognition.
• Human subjects: Handedness is not crucial, but should be assessed at least by
subject self-report (preferably documented by the Edinburgh Handedness
Inventory36 or other inventory). ▲ CRITICAL Subjects need to have normal or
! CAUTION The study protocol must be approved for use by the appropriate
Human Subjects Committee or Institutional Review Board, and informed
consent must be obtained following the established institutional and national
• MRI scanner. Functional MRI equipment and scanning techniques can
appropriately vary. Our fMRI studies have been performed on Siemens 3.0 tesla
(and 1.5 T) Allegra high-speed echo-planar imaging devices and a GE Signa 1.5
T magnet (modified by Advanced NMR Systems) using a quadrature head coil.
• Magnet-compatible button-press response device (see EQUIPMENT SETUP)
• Padded scanner couch
• Foam ear plugs
• Head stabilizer (e.g., foam padding within a head coil, or a plastic bite bar
molded to each subject’s dentition)
• Stimulus generator. Stimuli can be generated via any number of software/
hardware configurations. Our stimuli have been created/displayed using
MacStim 2.5–3.0 (Dave Darby, WhiteAnt Occasional Publishing, http://www.
brainmapping.org/WhiteAnt) and Presentation (Neurobehavioral Systems,
http://www.neurobs.com), but any suitable stimulus presentation software/
hardware combination that can smoothly display stimuli and record responses
(and RT to millisecond accuracy) can be used (see EQUIPMENT SETUP).
For the button-press response device, only three buttons are needed, although a
four-button setup is typical, in which case the fourth button is ignored. Buttons
should be sized and spaced such that they approximate a typical keyboard input
device (i.e., subjects should be able to comfortably place the index, middle and
ring fingers of the right hand on the keypad).
Whether displayed on a computer screen (for offline studies, PET, MEG, ERPs)
or if projected for use during fMRI, individual sets of numbers should be easily
read without strain but should not take up a large proportion of the visual field.
Generally accepted guidelines would be to display individual numbers that
subtend approximately 1° of the visual angle vertically and 3° horizontally, and
to group them together at screen center without extra spacing.
1| Obtain informed consent from subjects and document handedness and vision.
2| Give subjects the button-press device and instruct them that the keypad buttons represent one, two and three from left to
3| Tell subjects to use the index, middle and ring fingers of the right hand to respond. Depending on individual study
parameters and goals, subjects can theoretically use either hand to respond, but unless there is a special case in question, the
right hand is preferable, as it provides in most cases a more natural digit (number) to digit (finger) mapping, which eliminates
the potential for Simon effect26 interference of spatial incongruity between answer and response selection.
▲ CRITICAL STEP Responses are to be recorded by pressing the selected button. An MSIT variant28 that instructed subjects to
use a very different response method predictably found atypical RT results (i.e., in that study, rather than recording responses
by pressing one of three buttons located immediately beneath the three fingers, trials began with subjects holding down a
central button, and RT was measured as the time it took to release this central button and to initiate a response toward one of
three response buttons that were located 14 cm away—precluding meaningful comparison to standardized existing data).
4| Instruct subjects that sets of three numbers (1, 2, 3 or 0) will appear in the center of the screen every few seconds, and
that one number will always be different from the other two (matching distractor) numbers.
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NATURE PROTOCOLS | VOL.1 NO.1 | 2006 | 311
5| Instruct subjects to report, via button-press, the
identity of the number that is different from the other two
numbers. Inform subjects that during some (control) trials,
the target number (1, 2 or 3) always matches its position
on the button press (e.g., the number ‘1’ would appear in
the first (leftmost) position). Sample trials are, therefore,
100, 020 or 003. Also inform subjects that during other
(interference) trials, in contrast, the target (1, 2 or 3)
never matches its position on the button press, and the
distractors are themselves potential targets (e.g., 233,
correct answer is ‘2’).
Emphasize that subjects are to report what the target number
is regardless of its position (see Fig. 1).
6| Explicitly instruct subjects: (a) that the sets of numbers
will change about every 2 s (actual interstimulus interval for
healthy adults is 1,750 ms), and (b) to “answer as quickly as
possible, but since getting the correct answer is important, do
not sacrifice accuracy for speed.”
7| After instructions are reviewed, and just prior to entering the scanner (or being formally tested), subjects should complete
a 1-min or 5-min computerized practice version of the task (see guidelines below).
▲ CRITICAL STEP Review the responses immediately to ensure that the subject understood the task and can perform correctly,
without giving excessive practice. Ensure that subjects are reporting the target number identity and not its position during
interference trials (an error that occurs in less than 5% of subjects, but if not caught and corrected during practice will
invalidate testing). If subject is found to report position during practice, review results and have them perform practice session
correctly before proceeding.
8| Inform subjects that scans will begin and end with fixation of a white dot for 30 s, and that between these times there
will be two trial types (some with zeros and some without) that will appear in blocks that alternate every 42 s. Block-formatted
fMRI scans start and end with 30 s of fixation on a small dot as it assists in drift correction and between-run assessment by
providing a less biased baseline unrelated to the task.
9| Have subjects lie on a padded scanner couch in a dimly-illuminated room, and have them insert foam ear plugs that
attenuate high-intensity scanner sounds but allow spoken instructions to be heard well.
10| Stabilize the subject’s head via one of the generally used techniques (i.e., foam padding within the head coil, or a plastic
bite bar molded to each subject’s dentition).
11| Have subjects complete two scans each of the MSIT, where four 42-s blocks of the control trials (C) alternate with four
interference (I) blocks, book-ended by 30-s blocks of fixation (F) as described above. Given a fixed interstimulus interval of 1,750
ms, subjects will complete 24 trials during each (neutral/interference) block, 96 trials of each type during a single scan and 192
total trials of each type during the two-scan session (each block type is presented four times for a total scan time of 6 min, 36 s).
Pilot data have confirmed that the order of block presentation does not affect results, so we now present the blocks in fixed
order: FCICICICIF. However, the block order of presentation can be counterbalanced across runs and subjects.
Subject preparation: approximately 20 min
Scanning and testing: approximately 20 min
It is critically important to check the practice task results to ensure that subjects understand how to perform the task. It
should be noted that the blocked format may not be optimal in every situation, and as indicated previously, researchers should
consider using the MSIT stimuli in event-related format as appropriate to imaging modality (e.g., rapid event-related formatting
techniques (see ref. 37) can be used to format for fMRI experiments). Lastly, children, elderly adults and some patient groups
may perform tasks like the MSIT more slowly. These cases may require pilot testing to establish optimal timing parameters for
the subject group in question.
Figure 1 | MSIT trial examples. Subjects are asked to report, via button
press, the identity of the number that differs from the other two numbers.
During control trials (left), the distractors are zeros (0) and target numbers
are always placed congruently with their position on the button box. During
interference trials (right), the distractors are other numbers (either 1, 2
or 3), and target numbers are never placed congruently with their position
on the button box. In both examples, the correct answer would be to press
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312 | VOL.1 NO.1 | 2006 | NATURE PROTOCOLS
Accuracy in healthy adult volunteers should be expected to be
high. The combined mean accuracy for the 25 healthy adults
that have been scanned in our lab to date7,29 was 99.4 ±
1.3% (s.d.) for control trials, and 97.4 ± 2.0% for interference
trials. Both accuracy and RT differences between control and
interference trials were highly significant (P < 0.00001 for
RTs are uniformly greater for interference trials compared
with control trials—this difference score is the cognitive
interference effect (RTinterference – RTcontrol). In the
combined group (n = 25), the mean interference effect
was large (281 ± 65.2 ms, range 154–420 ms). It generally
starts in the 300–400 ms range in adults during the first
5 min and then stabilizes thereafter. The initial validation
study7, designed in part to evaluate early performance
and imaging effects, showed that after the first scan,
both performance and CFP activation tend to decrease
by roughly 30%, but thereafter tend to stay fairly stable
(with the cognitive interference effect (RTinterference) in the
vast (majority of cases remaining above 200 ms despite
extensive practice). Given these findings, our protocols
for single-exposure studies seeking to maximally activate
CFP use only a brief 1-min practice session, whereas longitudinal (test-retest) studies or cross-sectional studies seeking to
minimize early RT and fMRI signal variance now include an extended 5-min practice session.
The MSIT has been validated in healthy adults7,29 and interference minus control trial subtractions can be expected to activate
the CFP network of brain regions involved in attention, response selection, motor planning and motor output, including
daMCC, DLPFC (middle frontal gyri), premotor and primary motor cortex, inferior temporal gyrus and the superior parietal
lobule. A typical example of activated regions within a single subject appears in Figure 2. These structures subserve cognitive
processing in parallel-distributed fashion5,38,39. The daMCC contributes to many cognitive processes1,27,40, DLPFC has often
been reported to be coactivated with daMCC during cognitive tasks2,41–43, premotor cortex is responsible for planning and
execution of non-automatic tasks44,45, and parietal cortex has been shown to be activated during target detection tasks4,46 and
Stroop tasks8,12,14,17,47. Although the precise roles these structures play in such tasks remain to be determined, the convergent
data argue that they interact as a network, and the challenge ahead is to determine the role of the individual components of
these distributed brain circuits. Also, the MSIT typically produces nonspecific ‘deactivation’ effects in affective regions such as
pregenual/subgenual ACC, posterior cingulate cortex and amygdala1,34.
ACKNOWLEDGMENTS Support for this work was provided by the National
Institute of Mental Health (NIMH; Scientist Development Award 01611), the
National Science Foundation, the Mental Illness and Neuroscience Discovery
(MIND) Institute, the National Alliance for Research on Schizophrenia and
Depression (NARSAD) and the Forrest C. Lattner Foundation.
COMPETING INTERESTS STATEMENT The authors declare that they have no
competing financial interests.
Published online at http://www.natureprotocols.com
Reprints and permissions information is available online at http://npg.nature.
1. Bush, G., Luu, P. & Posner, M.I. Cognitive and emotional influences in
anterior cingulate cortex. Trends Cogn. Sci. 4, 215–222 (2000).
2. Duncan, J. & Owen, A. M. Common regions of the human frontal lobe
recruited by diverse cognitive demands. Trends Neurosci. 23, 475–483
3. Corbetta, M. Frontoparietal cortical networks for directing attention and
the eye to visual locations: identical, independent, or overlapping neural
Figure 2 | MSIT typical individual fMRI response. A typical single-scan fMRI
response is shown for an individual subject in the inflated view format (light
gray = gyri, dark gray = sulci). Note the robust bilateral activation (P < 10–4)
in the CFP network (daMCC, DLPFC, and superior parietal cortex). Additional
activity is often seen, as here, in ventrolateral prefrontal cortex (VLPFC).
systems? Proc. Natl. Acad. Sci. USA 95, 831–838 (1998).
4. Corbetta, M., Kincade, J.M., Ollinger, J.M., McAvoy, M.P. & Shulman,
G.L. Voluntary orienting is dissociated from target detection in human
posterior parietal cortex. Nat. Neurosci. 3, 292–297 (2000).
5. Goldman-Rakic, P.S. Topography of cognition: parallel distributed
networks in primate association cortex. Annu. Rev. Neurosci. 11, 137–
6. Bush, G., Whalen, P.J., Shin, L.M. & Rauch, S.L. The counting Stroop: a
cognitive interference task. Nat. Protocols 1, 23-233 (2006).
7. Bush, G., Shin, L.M., Holmes, J., Rosen, B.R. & Vogt, B.A. The multi-
source interference task: validation study with fMRI in individual
subjects. Mol. Psychiatry 8, 60–70 (2003).
8. Banich, M.T. et al. fMRI studies of Stroop tasks reveal unique roles of
anterior and posterior brain systems in attentional selection. J. Cogn.
Neurosci. 12, 988–1,000 (2000).
9. MacLeod, C.M. & MacDonald, P.A. Interdimensional interference in
the Stroop effect: uncovering the cognitive and neural anatomy of
attention. Trends Cogn. Sci. 4, 383–391 (2000).
10. MacDonald, A.W. 3rd, Cohen, J.D., Stenger, V.A. & Carter, C.S.
Dissociating the role of the dorsolateral prefrontal and anterior
© 2006 Nature Publishing Group http://www.nature.com/natureprotocols
NATURE PROTOCOLS | VOL.1 NO.1 | 2006 | 313
cingulate cortex in cognitive control. Science 288, 1835–1838 (2000).
11. Peterson, B.S. et al. An fMRI study of Stroop word-color interference:
evidence for cingulate subregions subserving multiple distributed attentional
systems. Biol. Psychiatry 45, 1237–1258 (1999).
12. Bush, G. et al. Anterior cingulate cortex dysfunction in attention-deficit/
hyperactivity disorder revealed by fMRI and the Counting Stroop. Biol.
Psychiatry 45, 1542–1552 (1999).
13. Derbyshire, S.W., Vogt, B.A. & Jones, A.K. Pain and Stroop interference tasks
activate separate processing modules in anterior cingulate cortex. Exp. Brain
Res. 118, 52–60 (1998).
14. Bush, G. et al. The counting Stroop: an interference task specialized for
functional neuroimaging—validation study with functional MRI. Hum. Brain
Mapp. 6, 270–282 (1998).
15. Taylor, S.F., Kornblum, S., Lauber, E.J., Minoshima, S. & Koeppe, R.A.
Isolation of specific interference processing in the Stroop task: PET
activation studies. Neuroimage 6, 81–92 (1997).
16. Pardo, J.V., Pardo, P.J., Janer, K.W. & Raichle, M.E. The anterior cingulate
cortex mediates processing selection in the Stroop attentional conflict
paradigm. Proc. Natl. Acad. Sci. USA 87, 256–259 (1990).
17. Carter, C.S., Mintun, M. & Cohen, J.D. Interference and facilitation effects
during selective attention: an H215O PET study of Stroop task performance.
Neuroimage 2, 264–272 (1995).
18. Barch, D.M. et al. Anterior cingulate cortex and response conflict: effects of
response modality and processing domain. Cereb. Cortex 11, 837–848 (2001).
19. Ruff, C.C., Woodward, T.S., Laurens, K.R. & Liddle, P.F. The role of the
anterior cingulate cortex in conflict processing: evidence from reverse stroop
interference. Neuroimage 14, 1150–1158 (2001).
20. Leung, H.C., Skudlarski, P., Gatenby, J.C., Peterson, B.S. & Gore, J.C. An
event-related functional MRI study of the stroop color word interference
task. Cereb. Cortex 10, 552–560 (2000).
21. Botvinick, M., Nystrom, L.E., Fissell, K., Carter, C.S. & Cohen, J.D. Conflict
monitoring versus selection-for-action in anterior cingulate cortex. Nature
402, 179–181 (1999).
22. Casey, B.J. et al. Dissociation of response conflict, attentional selection, and
expectancy with functional magnetic resonance imaging. Proc. Natl. Acad.
Sci. USA 97, 8728–8733 (2000).
23. van Veen, V., Cohen, J.D., Botvinick, M.M., Stenger, V.A. & Carter, C.S.
Anterior cingulate cortex, conflict monitoring, and levels of processing.
Neuroimage 14, 1302–1308 (2001).
24. Stroop, J.R. Studies of interference in serial verbal reactions. J. Exp. Psychol.
18, 643–662 (1935).
25. Eriksen, B.A. & Eriksen, C.W. Effects of noise letters upon the identification
of a target letter in a nonsearch task. Percept. Psychophys. 16, 143–149
26. Simon, J.R. & Berbaum, K. Effect of conflicting cues on information
processing: the ‘Stroop effect’ vs. the ‘Simon Effect’. Acta Psychologica 73,
27. Bush, G. et al. Dorsal anterior cingulate cortex: a role in reward-based
decision making. Proc. Natl. Acad. Sci. USA 99, 523–528 (2002).
28. Stins, J.F., van Leeuwen, W.M. & de Geus, E.J. The multi-source interference
task: the effect of randomization. J. Clin. Exp. Neuropsychol. 27, 711–717
29. Heckers, S. et al. Anterior cingulate cortex activation during cognitive
interference in schizophrenia. Am. J. Psychiatry 161, 707–715 (2004).
30. Drevets, W.C. & Raichle, M.E. Reciprocal suppression of regional cerebral blood
flow during emotional versus higher cognitive processes: Implications for
interactions between emotion and cognition. Cognition Emotion 12, 353–385
31. Mayberg, H.S. et al. Reciprocal limbic-cortical function and negative mood:
converging PET findings in depression and normal sadness. Am. J. Psychiatry
156, 675–682 (1999).
32. Gusnard, D.A., Akbudak, E., Shulman, G.L. & Raichle, M.E. Medial prefrontal
cortex and self-referential mental activity: relation to a default mode of brain
function. Proc. Natl. Acad. Sci. USA 98, 4259–4264 (2001).
33. Simpson, J.R. Jr., Snyder, A.Z., Gusnard, D.A. & Raichle, M.E. Emotion-
induced changes in human medial prefrontal cortex: I. During cognitive task
performance. Proc. Natl. Acad. Sci. USA 98, 683–687 (2001).
34. Whalen, P.J. et al. The emotional counting Stroop paradigm: a functional
magnetic resonance imaging probe of the anterior cingulate affective
division. Biol. Psychiatry 44, 1219–1228 (1998).
35. McKiernan, K.A., Kaufman, J.N., Kucera-Thompson, J. & Binder, J.R. A
parametric manipulation of factors affecting task-induced deactivation in
functional neuroimaging. J. Cogn. Neurosci. 15, 394–408 (2003).
36. Oldfield, R.C. The assessment and analysis of handedness: the Edinburgh
Inventory. Neuropsycholgia 9, 97–113 (1971).
37. Burock, M.A., Buckner, R.L., Woldorff, M.G., Rosen, B.R. & Dale, A.M.
Randomized event-related experimental designs allow for extremely rapid
presentation rates using functional MRI. Neuroreport 9, 3735–3739 (1998).
38. Posner, M.I. & Petersen, S.E. The attention system of the human brain. Annu.
Rev. Neurosci. 13, 25–42 (1990).
39. Mesulam, M.M. Large-scale neurocognitive networks and distributed
processing for attention, language, and memory. Ann. Neurol. 28, 597–613
40. Williams, Z.M., Bush, G., Rauch, S.L., Cosgrove, G.R. & Eskandar, E.N. Human
anterior cingulate neurons and the integration of monetary reward with motor
responses. Nat. Neurosci. 7, 1370–1375 (2004).
41. Banich, M.T. et al. Prefrontal regions play a predominant role in imposing
an attentional ‘set’: evidence from fMRI. Brain Res. Cogn. Brain Res. 10, 1–9
42. Badgaiyan, R.D. Executive control, willed actions, and nonconscious
processing. Hum. Brain Mapp. 9, 38–41 (2000).
43. Koski, L. & Paus, T. Functional connectivity of the anterior cingulate cortex
within the human frontal lobe: a brain-mapping meta-analysis. Exp. Brain Res.
133, 55–65 (2000).
44. Schubotz, R.I. & von Cramon, D.Y. Functional organization of the lateral
premotor cortex: fMRI reveals different regions activated by anticipation of
object properties, location and speed. Brain Res. Cogn. Brain Res. 11, 97–112
45. Toni, I., Schluter, N.D., Josephs, O., Friston, K. & Passingham, R.E. Signal-,
set- and movement-related activity in the human brain: an event-related fMRI
study. Cereb. Cortex 9, 35–49 (1999).
46. Rushworth, M.F., Paus, T. & Sipila, P.K. Attention systems and the organization
of the human parietal cortex. J. Neurosci. 21, 5262–5271 (2001).
47. George, M.S. et al. Regional brain activity when selecting a response despite
interference: an H215O PET study of the Stroop and an emotional Stroop.
Hum. Brain Mapp.1, 194–209 (1994).
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