The neural substrates of memory suppression: a FMRI exploration of directed forgetting.

Abstract

The directed forgetting paradigm is frequently used to determine the ability to voluntarily suppress information. However, little is known about brain areas associated with information to forget. The present study used functional magnetic resonance imaging to determine brain activity during the encoding and retrieval phases of an item-method directed forgetting recognition task with neutral verbal material in order to apprehend all processing stages that information to forget and to remember undergoes. We hypothesized that regions supporting few selective processes, namely recollection and familiarity memory processes, working memory, inhibitory and selection processes should be differentially activated during the processing of to-be-remembered and to-be-forgotten items. Successful encoding and retrieval of items to remember engaged the entorhinal cortex, the hippocampus, the anterior medial prefrontal cortex, the left inferior parietal cortex, the posterior cingulate cortex and the precuneus; this set of regions is well known to support deep and associative encoding and retrieval processes in episodic memory. For items to forget, encoding was associated with higher activation in the right middle frontal and posterior parietal cortex, regions known to intervene in attentional control. Items to forget but nevertheless correctly recognized at retrieval yielded activation in the dorsomedial thalamus, associated with familiarity-based memory processes and in the posterior intraparietal sulcus and the anterior cingulate cortex, involved in attentional processes.

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Modulation of Brain Activity during a Stroop Inhibitory
Task by the Kind of Cognitive Control Required
Julien Grandjean1,2, Kevin D’Ostilio1,2, Christophe Phillips1,3, Evelyne Balteau1, Christian Degueldre1,
Andre ´ Luxen1, Pierre Maquet1, Eric Salmon1, Fabienne Collette1,2*
1Cyclotron Research Center, University of Lie `ge, Lie `ge, Belgium, 2Department of Psychology: Cognition and Behavior, University of Lie `ge, Lie `ge, Belgium, 3Department
of Electrical Engineering and Computer Science, University of Lie `ge, Lie `ge, Belgium
Abstract
This study used a proportion congruency manipulation in the Stroop task in order to investigate, at the behavioral and brain
substrate levels, the predictions derived from the Dual Mechanisms of Control (DMC) account of two distinct modes of
cognitive control depending on the task context. Three experimental conditions were created that varied the proportion
congruency: mostly incongruent (MI), mostly congruent (MC), and mostly neutral (MN) contexts. A reactive control strategy,
which corresponds to transient interference resolution processes after conflict detection, was expected for the rare
conflicting stimuli in the MC context, and a proactive strategy, characterized by a sustained task-relevant focus prior to the
occurrence of conflict, was expected in the MI context. Results at the behavioral level supported the proactive/reactive
distinction, with the replication of the classic proportion congruent effect (i.e., less interference and facilitation effects in the
MI context). fMRI data only partially supported our predictions. Whereas reactive control for incongruent trials in the MC
context engaged the expected fronto-parietal network including dorsolateral prefrontal cortex (DLPFC) and anterior
cingulate cortex, proactive control in the MI context was not associated with any sustained lateral prefrontal cortex
activations, contrary to our hypothesis. Surprisingly, incongruent trials in the MI context elicited transient activation in
common with incongruent trials in the MC context, especially in DLPFC, superior parietal lobe, and insula. This lack of
sustained activity in MI is discussed in reference to the possible involvement of item-specific rather than list-wide
mechanisms of control in the implementation of a high task-relevant focus.
Citation: Grandjean J, D’Ostilio K, Phillips C, Balteau E, Degueldre C, et al. (2012) Modulation of Brain Activity during a Stroop Inhibitory Task by the Kind of
Cognitive Control Required. PLoS ONE 7(7): e41513. doi:10.1371/journal.pone.0041513
Editor: Friedemann Paul, Charite ´ University Medicine Berlin, Germany
Received March 5, 2012; Accepted June 22, 2012; Published July 24, 2012
Copyright: ? 2012 Grandjean et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The authors are supported by the National Fund for Scientific Research (Belgium; http://www1.frs-fnrs.be/). The funders had no role in study design,
data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: f.collette@ulg.ac.be
Introduction
Cognitive control serves to adjust and flexibly guide people’s
behavior in changing environmental circumstances, especially in
situations where distracting information or a prepotent response
tendency must be ignored in order to successfully act in a goal-
directed manner [1–3]. The notion of ‘‘cognitive control’’ can be
conceived as a global term that encompasses such well-known
concepts in the psychological literature as executive control, goal
maintenance, top-down processing, response selection and re-
sponse inhibition [4].
The Stroop task [5] constitutes one of the most widely used
paradigms in cognitive control studies; in this task, an automatic or
predominant response tendency (i.e., word reading) must be
withheld in favor of a more controlled one [6]. More specifically,
subjects are required to name the ink color of color words as fast
and accurately as possible. Items in the Stroop task can be
congruent, with a match between ink color and color word (e.g.,
‘‘red’’ written in red), incongruent (‘‘red’’ written in green), or
neutral (e.g., a non-word written in red). Reaction times (RTs) are
typically slower for incongruent than for congruent or neutral
trials; this phenomenon is known as the interference effect and is
generally considered to reflect the time needed to overcome the
conflict between the automatic word-reading tendency and the
more controlled color naming response [7,8]. In addition,
a facilitation effect (i.e., faster RTs for congruent than neutral
items), also due to inadvertent word reading, has been reported
[9,10].
The Dual Mechanisms of Control (DMC) Account
Braver et al. [11] developed a general theory of cognitive
control, which states that flexibility in cognitive control strategies,
depending on situational demands or individual differences, may
be achieved through reactive or proactive control [12]. These two
processes are clearly separable in terms of cognitive properties and
brain activity. Proactive control is a sustained form of control that
can be engaged in situations where one can anticipate upcoming
stimuli, allowing one to respond rapidly and efficiently by actively
maintaining all task-relevant information (e.g., task instructions,
identity of previous stimuli, cues for later behavior, etc.). Reactive
control, on the other hand, is engaged in situations in which
anticipating the upcoming stimuli is not possible, and where the
occurrence of a critical event triggers the reactivation of required
information in a transient manner. For example, in the context of
an interference resolution task such as the Stroop task, reactive
control would seek to detect and resolve interference after its onset,
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whereas proactive control would aim at anticipating and
preventing interference before it occurs. Thus, proactive control
is not specific to one type of stimulus and reflects a longer period of
time of active goal maintenance.
As a result, an important factor that can modulate the extent to
which proactive or reactive strategies contribute to task perfor-
mance is the overall task context (i.e., task demands and
characteristics). Indeed, whereas both strategies are equally likely
to lead to correct performance on a specific trial, there are some
situations in which one or the other kind of control would be most
appropriate, with task context encouraging the adoption of one
form of control over the other. For example, the proportion
congruent effect noted in the Stroop literature [13–15] reflects
how task context can influence performance. Classically, the
proportion congruent effect is the observation of less interference
and facilitation in lists of stimuli containing mainly incongruent
items (low-proportion-congruent condition) than in lists containing
mainly congruent trials (high-proportion-congruent condition;
[16,17]).
Expectations are seen as playing a crucial role in the
phenomenon [15,18], and are used by participants as a cue to
adjust the influence of word-reading processes on performance. In
high-proportion-congruent situations, the need to rely exclusively
on color naming processes is not perceived as crucial given that
a majority of trials can be successfully responded to simply by
reading the words. On the contrary, in low-proportion-congruent
situations, color naming would be the main determinant of
response for all the trials within the list, given the high probability
of errors associated with word reading processes. Consequently,
the interference associated with incongruent trials is less pro-
nounced, but this is also true for the facilitation effect, given that
the same processing is applied to all the items. Importantly, this
proportion congruent effect can be explained within the DMC
account and the proactive/reactive control distinction [11]. More
specifically, the low-proportion-congruent condition would be
associated with a proactive control strategy, with sustained high
activation of goal-relevant information (inhibiting word-reading
processes in favor of color naming), whereas the high-proportion-
congruent condition would be associated with the reactive control
strategy, with transient recruitment of attentional control for
critical interfering items only.
Importantly, both mechanisms of control are claimed to be
clearly dissociable at the brain level. Specifically, one of the key
hypotheses within the DMC account is that proactive and reactive
control mechanisms also differ according to the brain regions
subserving them and the temporal pattern of neural activity. Along
these lines, interactions between the lateral prefrontal cortex (PFC)
and anterior cingulate cortex (ACC) constitute a core character-
istic of how cognitive control is implemented within the DMC
model during an interference task [11,12,19]. More specifically,
reactive control is assumed to be associated with transient
activation of the lateral PFC when interference is detected
(reactivation of task goals), and proactive control with sustained
activation of the lateral PFC (active maintenance of task goals). A
wider network of additional brain regions typically associated with
conflict detection and monitoring, especially the ACC, is also
expected to play a crucial role for reactive control in Braver et al’s
account.
The Stroop task has consistently been associated with a large
fronto-parietal network, typically involving the ACC, dorsolateral
prefrontal cortex (DLPFC), inferior frontal gyrus, inferior and
superior parietal cortex and insula [20–22]. Moreover, a series of
studies seems to indicate, as suggested by Braver and colleagues
[11,19], that the ACC and DLPFC play differential roles in
conflict resolution [23]. In addition, greater involvement by the
ACC has been observed for incongruent trials in lists containing
few incongruent trials than in lists composed mostly of incongruent
trials [2,24]. The ACC-DLPFC network is also differentially
involved after probabilistic cueing, with greater conflict effects in
the ACC and DLPFC for incongruent items following highly
congruent-predictive cues by comparison to incongruent items
following highly incongruent-predictive or non-predictive cues
[25]. Finally, Kerns et al. [2] showed that the activity in the ACC
for conflicting trials predicted subsequent PFC activity and
adjustments in behavior. In this context, Botvinick et al. [1,26],
in their conflict monitoring hypothesis, proposed that the ACC is
involved in conflict detection and monitoring and will recruit the
DLPFC when interference occurs in order to resolve conflict in
a top-down manner by means of strategic adjustments in cognitive
control. In order to select the appropriate response, the DLPFC
would bias information processing in posterior brain regions (i.e.,
parietal cortex) to favor the most relevant criteria for performing
the task.
Neuroimaging Studies of Proactive and Reactive Control
Surprisingly, the DMC account has received little attention in
neuroimaging studies of the Stroop task, and most of the studies
used other cognitive control paradigms, such as the AX version of
the Continuous Performance Task (AX-CPT), a task considered to
evaluate goal representation, maintenance, and updating. In this
task, participants are presented with cue-probe pairs, and must
make a target response to an X-probe only when preceded by an
A-cue. Non-target responses must be given for all other trials
(‘‘BX’’, ‘‘AY’’, and ‘‘BY’’ trials). Hence, contextual cues serve as
task goal-relevant information regarding the correct response to
produce following ambiguous probes (for a further description of
this task, see [27]). More specifically, in a series of publication,
Braver and colleagues obtained behavioral and brain data
indicating flexible involvement of proactive and reactive control
depending on task context [28–31]. For example, Locke and
Braver [28] showed a shift from reactive to proactive control (i.e.
active maintenance of cue letter during the delay and increased
sustained activity in a network including the right lateral PFC)
during reward incentive task blocks in comparison to baseline or
penalty blocks. In a further study, Braver et al. [29] showed a shift
from an anticipatory, sustained control (cue-related pattern of
activity in lateral PFC that would represent active maintenance of
goal-relevant information during the cue-probe delay) to a just-in-
time control engaged during task probe occurrence during penalty
blocks. In addition, Paxton et al. [32] also provided neuroimaging
evidence showing a shift from proactive to reactive control with
advancing age. Indeed, they demonstrated an age-related shift in
lateral PFC regions, with reduced cue-related activity and
increased probe-related activity for older than for younger
participants (see also [33], for similar data obtained with a task-
switching paradigm). However, following a period of task-strategy
training, older may shift to a proactive strategy [29].
Regarding the Stroop task, Carter et al. [24], as indicated
previously, showed greater involvement of the ACC for in-
congruent trials in mostly congruent situations than in mostly
incongruent situations. More recently, Floden et al. [34] explored
neural substrates associated with the Stroop effect according to
task context. Three task context manipulations were used:
a blocked context (all trial types were identical within a run), an
unblocked-uncued context (all trials were intermixed and com-
pletely unpredictable), and an unblocked-cued context (intermixed
trials each preceded by a cue signaling the upcoming trial type).
The results showed transient ACC and DLPFC activation mainly
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for incongruent trials in the unblocked and uncued condition,
which supports the hypothesis that these areas are involved in
reactive control processes.
The studies by Carter et al. [24] and Floden et al. [34] were not
expressly designed to evaluate the complete pattern of brain areas
associated with the respective contributions of reactive and
proactive control mechanisms. Indeed, although Carter et al.
focused on the ACC and aimed at better understanding its role in
conflict resolution (i.e., conflict detection vs. strategic process
implementation), Floden et al. did not consider the proactive/
reactive control distinction at all, and aimed at comparing blocked
versus unblocked task contexts rather than low- versus high-
proportion-congruent conditions. Therefore, the present study
investigated whether the general task context (i.e., the proportion
congruency) may influence the mode of cognitive control that
drives performance.
At the behavioral level, we should observe less interference from
incongruent and less facilitation from congruent trials in the
mostly incongruent than in the mostly congruent condition
(proactive control). On the contrary, the greater reliance on word
reading in a mostly congruent context should favor the occurrence
of greater interference and facilitation effects, with reactive control
(reactivation of task goals) occurring only for incongruent stimuli.
At the brain level, we expected incongruent trials of the mostly
congruent conditions to elicit a transient activation of the ACC
and lateral PFC, reflecting reactivation of task goals and
interference resolution (reactive control). On the contrary, we
did not expect any transient activation in the mostly incongruent
context. Rather, we expected a sustained activation (across trials)
in the lateral PFC during this context, reflecting active goal
maintenance for all the items presented (proactive control).
Materials and Methods
Ethics Statement
The study was approved by the Ethics Committee of the Faculty
of Medicine of the University of Lie `ge. In accordance with the
Declaration of Helsinki, all participants gave their written
informed consent prior to their inclusion in the study.
Participants
Twenty-eight right-handed native French-speaking young
adults, with no diagnosed psychological or neurological disorders,
were recruited from the university community. All had normal
color vision. Each participant was also screened for any physical or
medical condition that could prevent an MRI session. Three
participants were excluded from analysis because of incomplete
data or technical problems during scanning that precluded their
inclusion in further analyses. The 25 participants who remained
for the statistical analyses included 12 men and 13 women. Their
ages ranged from 18 to 29 years (mean=21.862.68).
Materials
Four color words presented on a white background were used in
this experiment (Red, Blue, Black, and Green). Proportion
congruency was manipulated using three different contexts of 12
items each (see Figure 1a): the mostly congruent context (MC), the
mostly incongruent context (MI), and the mostly neutral context (MN). Each
MI block was composed of 8 incongruent items (e.g. the word
‘‘red’’ written in ‘‘blue’’), 2 congruent items (e.g. the word ‘‘blue’’
in ‘‘blue’’), and 2 neutral items, which were non-verbal stimuli (i.e.,
strings of five percent signs %%%%%) presented in one of the
four color possibilities. For the MC context, the proportions of
congruent and incongruent items were reversed. Finally, 8 neutral,
2 congruent, and 2 incongruent items were presented during the
MN context. Importantly, the first four items in each block were
representative of the current task context (e.g., four incongruent
trials in the beginning of each MI context) and served to induce
the use of proactive or reactive control processes. The presentation
order of the different blocks was pseudo-randomized, with the use
of three different presentation orders. Each of the three
congruency conditions of 12 items (MI, MC, and MN contexts)
was presented 15 times, for a total of 45 blocks and 540 items.
Procedure
Participants were instructed that their task would be to select the
color in which each item was printed. They were told that the
items would be presented briefly and they were to respond as fast
and accurately as possible. Color words were presented on a screen
that the participants viewed through a mirror located on the
scanner’s head coil. Each trial consisted of the presentation of
a word in the center of the screen, with four response possibilities
(written in brown, a color never used for the items) at the bottom
of the screen (Figure 1a). Participants had thus to press one of the
four response keys on a keyboard, which corresponded to the four
color ink possibilities, always in the same order (blue, black, green,
red, respectively). They used the index and the middle fingers of
their left and right hands for responding. Each item was presented
until the participant responded (with a maximum presentation
time of 2000 ms). If the participant responded before the deadline,
a white screen was presented for the remaining period. If no
response was provided, a white screen appeared after 2000 ms and
an inter-stimulus interval of 500 ms occurred before the next item.
A fixation cross was presented in the center of the screen for 5000
milliseconds after every two or three contexts to provide breaks
during the experiment (Figure 1b).
Prior to the MRI session, participants performed a practice
session outside the scanner in which 40 items were presented in
order to be sure that they understood the task instructions. In the
fMRI scanner, four more examples were presented just before the
test phase began. After the session, participants received a debrief-
ing that explained the main objective of the experiment.
Behavioral Data Analysis
All behavioral data met the criteria of normal distribution and
the sphericity assumption, and were analyzed with a statistical
level set at p,.05. Repeated measures ANOVAs were run on the
mean RTs and accuracy data (errors and no response), with task
context (MC, MI, and MN context) and item type (incongruent,
congruent, and neutral) as repeated measures factors. We also
reported partial eta squared (g2
p) as a measure of effect size. Finally,
post hoc comparisons were performed, also with a p,.05, using
pairwise Tukey’s tests.
MRI Acquisition
Functional MRI time series were acquired on a 3T head-only
scanner (Magnetom Allegra, Siemens Medical Solutions, Erlan-
gen, Germany) operated with the standard transmit-receive
quadrature head coil. Multislice T2*-weighted functional images
were acquired with a gradient-echo echo-planar imaging sequence
using axial slice orientation and covering the whole brain (32
slices, FoV=2206220 mm2, voxel size 3.463.463 mm3, 30%
interslice gap,matrixsize
TE=40 ms, FA=90u). For anatomical reference, a high-resolu-
tion T1-weighted image (3D MDEFT) was acquired for each
subject [35] (TR=7.92 ms, TE=2.4 ms, TI=910 ms, FA=15u,
FoV=25662246176 mm3, 1 mm isotropic spatial resolution).
The first three volumes were discarded to avoid T1 saturation
64664632, TR=2130 ms,
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effects. Head movement was minimized by restraining the
subject’s head using a vacuum cushion. Stimuli were displayed
on a screen positioned at the rear of the scanner, which the
participant could comfortably see through a mirror mounted on
the standard head coil.
fMRI Data Analyses
Data were preprocessed and analyzed using SPM8 (Wellcome
Trust Centre for Neuroimaging, http://www.fil.ion.ucl.ac.uk/
spm) implemented in MATLAB 7.5.0 (Mathworks Inc., Sherborn,
MA). Images of each individual participant were first realigned
(motion corrected). After this realignment, we spatially coregis-
tered the mean EPI image to the anatomical MRI image and
coregistration parameters were applied to the realigned BOLD
time series. Individual anatomical MRIs were spatially normalized
into the MNI space (Montreal Neurological Institute, http://www.
bic.mni.mcgill.ca), and the normalization parameters were sub-
sequently applied to the individually coregistered BOLD times
series, which was then smoothed using an isotropic 8-mm full-
width at half-maximum (FWHM) Gaussian kernel.
For each participant, BOLD responses were modeled at each
voxel, using a general linear model with events convolved with the
canonical hemodynamic response function as regressors. Events
were divided according to the three contexts (MI, MC, or MN
context) and the type of item (incongruent, congruent, or neutral).
These 9 regressors were modeled as event-related responses. Event
durations corresponded to the presentation of the item until the
subject’s response, with a maximum duration of 2 s. Incorrect
trials and no responses were also modeled as separate regressors.
The design matrix also included the realignment parameters to
account for any residual movement-related effect. In addition, the
first four items for each context were modeled separately in the
design matrix. The rationale for excluding these items was that
they did not fully reflect the cognitive control strategy postulated
for the context in question (i.e., in the MI context, the first items
served to establish the subsequent proactive control strategy by
creating expectations associated with this context, and similarly in
the MC context, the first items created a low expectation of
incongruent trials). A high pass filter was implemented using a cut-
off period of 256 s in order to remove the low-frequency drifts
from the time series. Linear contrasts assessed the simple main
effect of each trial type. The resulting set of voxel values
constituted a map of t statistics, SPM[T]. The corresponding
contrast images were smoothed (6-mm FWHM Gaussian kernel)
and entered into a second-level analysis, corresponding to
a random-effect model. All analyses were conducted using
Figure 1. Proportion congruency manipulation. (a) Presentation of the three task contexts (MI, MC, and MN) used in this experiment, with
twelve items constituting each MI (8 incongruent, 2 congruent, and 2 neutral items), MC (2 incongruent, 8 congruent, and 2 neutral items), and MN (2
incongruent, 2 congruent, and 8 neutral items) block, and (b) general procedure for context presentation with a fixation cross presented after every
two or three blocks of stimuli, for a total of 45 blocks.
doi:10.1371/journal.pone.0041513.g001
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a correction for multiple comparisons at the voxel level with
a conservative family-wise error (FWE) threshold p,.05.
A 3 (context)63 (item type) whole-brain voxel-wise repeated
measures ANOVA was performed, which allowed us to examine
the brain regions related to the comparisons of interest (i.e.,
general interference effect in the three contexts, interference effects
in each context separately, comparison of incongruent trials in the
MI and MC contexts with neutral trials in the MN context,
comparison of brain activity across the MI context vs. across MC
or MN contexts). To further investigate similarities and differences
in the activation maps between incongruent trials in the MI and
MC contexts, supplementary conjunction and interaction analyses
were performed between the interference effects in the MC and
MI contexts (respectively assessed here by the comparison between
incongruent and neutral trials in the MC context, and the
comparison between incongruent trials in the MI context and
neutral trials in the MN context). More specifically, the
conjunction analysis using the null hypothesis [36] aimed at
investigating common brain activations in both contrasts. Given
the conservative nature of this conjunction analysis, all activations
Figure 2. Behavioral results. Mean reaction times (ms) in the MI, MC, and MN contexts for incongruent, congruent and neutral items. An
interference effect (incongruent vs. neutral) was observed in each context, and incongruent trials were responded faster in the MI than in the MC and
MN contexts. A facilitation effect (congruent vs. neutral) was only observed in the MC context. Error bars represent standard deviations.
doi:10.1371/journal.pone.0041513.g002
Table 1. Accuracy data (percentage of errors and no
responses) in the MI, MC, and MN contexts for incongruent,
congruent and neutral items.
MI context MC contextMN context
Incongruent5.21 (2.88) 6.53 (5.60)5.14 (5.11)
Congruent 1.67 (2.78)1.88 (2.66)1.53 (2.60)
Neutral 1.11 (2.12)3.89 (4.78) 2.78 (2.72)
Note: Numbers in parentheses correspond to standard deviations.
doi:10.1371/journal.pone.0041513.t001
Table 2. General interference effect (incongruent vs. neutral
in MI, MC, and MN context).
Hemisphere Anatomical region
MNI
coordinates
Z score P value
xyz
L Inferior frontal
242 1426 6.99
, ,.001
L Inferior frontal
254 2034 6.77
, ,.001
L Middle frontal
244 3834 4.77.013
L Superior frontal
224 4 68 5.12.003
L Anterior cingulate
22 18 50 4.60 .027
L Anterior insula
234 202 6.12
, ,.001
R Anterior insula32 224 5.22 .002
R Inferior frontal 30 24
210 4.51.039
L Superior parietal
224 270 42 6.87
, ,.001
L Inferior parietal
232 250 48 5.96
, ,.001
L Precuneus
28
264 62 5.68
, ,.001
R Intraparietal sulcus 30
250 44 4.78.013
L Inferior occipital
244 286 28 6.28
, ,.001
L Fusiform gyrus
248 256 220 6.20
, ,.001
L Inferior occipital
242 268 2105.83
, ,.001
LSuperior temporal
254 246 145.19 .002
R Cerebellum30
264 234 5.15.002
R Cerebellum10
276 2285.14.003
R Cerebellum46
252 2424.93 .007
L/R=left or right; x, y, z: coordinates (mm) in the stereotactic space defined by
the Montreal Neurological Institute (MNI). This analysis was conducted with a p
value ,.05 FWE corrected.
doi:10.1371/journal.pone.0041513.t002
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with a p value ,.001 uncorrected were reported [37,38]. The
interaction analysis aimed at investigating the specific pattern of
activation related to the interference effect in the MC context. As
with the conjunction analysis, we reported all activations with
a p value ,.001 uncorrected.
Results
Behavioral Data
A 3 context (MI, MC, MN)63 item type (incongruent,
congruent, neutral) repeated measures ANOVA was conducted
on the mean RTs (see Figure 2), and revealed a main effect of
context (F(2,48)=11.44; p,.0001; =.32), showing faster RTs in
the MI context; a main effect of item (F(2,48)=126.81; p,.0001;
g2
p=.84), showing longer RTs for incongruent trials; and
a significant context 6 item
p,.0001; g2
p=.32). The analysis of the interaction effect (post
hoc Tukey’s tests) showed an interference effect in all three
contexts (all ps ,.001). However, RTs for incongruent trials were
faster for the MI context than the MC and MN contexts (all ps
,.001), and faster for the MC than the MN context (p=.04). A
facilitation effect (faster RTs for congruent than neutral items) was
present only in the MC context, where congruent trials are very
interaction(F(4,96)=11.05;
frequent (p=.03). Finally, reaction times for congruent items did
not differ between MI and MC contexts (p..05).
A similar repeated measures ANOVA was conducted for the
accuracy data (percentage of errors and no response) for the three
types of items in the three contexts (Table 1). This analysis only
revealed a main effect of item type (F(2,48)=25.27; p,.0001;
g2
p=.51), showing more errors for incongruent trials, indepen-
dently of the context. We failed to show any main effect of context,
although it was very close to significance (F(2,48)=3.13; p=.05;
g2
p=.31; g2
p=.05).
p=.12), or any context 6 item type interaction (F(4,96)=1.20;
fMRI Data
General interference effect.
terference effect (i.e., incongruent vs. neutral items) across the
three contexts revealed a large map of activation corresponding to
the extensive fronto-parietal network typically associated with
interference resolution in the Stroop task (see Table 2). More
specifically, we found strong activation in ACC, DLPFC, inferior
and superior parietal regions, and also the insula and cerebellum
when interfering items were presented.
Transient patterns of brain activation.
neural correlates of the interference effect for the three contexts
First of all, the general in-
We first analyzed
Figure 3. fMRI results for the interference effect in the MC context. This contrast evidenced ACC, DLPFC, and inferior parietal lobe activations
(statistical threshold at p,.001 uncorrected for the present display).
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separately (incongruent vs. neutral). As expected, the interference
effect in the MC context was associated with strong differential
activation between incongruent and neutral trials, especially in
fronto-parietal areas, including the DLPFC and ACC (see Figure 3,
Table 3a). The interference effect in the MI context showed no
differential activation between incongruent and neutral items in
this context (Table 3b). The interference effect in the MN context
elicited activations in the superior parietal lobe, DLPFC, and
insula (Table 3c).
In addition, we also contrasted incongruent trials in the MC and
MI contexts with neutral trials in the MN context. Using these
items as a baseline for comparison is useful, since they are
processed independently of congruency expectations (due to the
MN context) that would modulate the involvement of word-
reading processes. These results did not differ from the previous
contrast for the MC context and confirmed the involvement of the
fronto-parietal network including the DLPFC and ACC (Table 4a).
In addition, they showed an increased activation in the DLPFC for
incongruent trials in the MI context (Table 4b), in a similar area to
that found for incongruent trials in the MC and MN contexts.
To further investigate similarities in the activation maps for
incongruent trials in the MI and MC contexts, we conducted
a conjunction analysis between contrasts assessing the interference
effect in the MI context (incongruent items in the MI context vs.
neutral items in the MN context) and the interference effect in the
MC context (incongruent vs. neutral items in the MC context). As
shown in Figure 4 and Table 5a, incongruent trials in both
contexts elicit, to some extent, activations in a similar brain
network including the DLPFC, superior parietal cortex, and
insula. However, this conjunction analysis did not show common
activation in various frontal, cingulate, and cerebellar regions,
which therefore seem to be specific to incongruent trials in the MC
context. This was confirmed by an interaction analysis between
the same contrasts ((incongruent items in MC - neutral items in
MC) vs. (incongruent items in MI - neutral items in MN)), which
showed that the superior and middle frontal gyrus, anterior
cingulate, and cerebellum (Table 5b) were specifically activated for
incongruent trials in the MC context.
Sustained patterns of brain activation.
dence of proactive control we expected to see was sustained (across
trials) increased activation in the lateral PFC in the MI context,
but not in the MC and MN contexts. Hence, in further analyses,
we directly contrasted the MI context with the MC and MN
contexts. More specifically, brain activity associated with the
processing of the three kinds of items in the MI context was
contrasted with brain activity associated with the processing of
these items, first in the MC context, and next in the MN context.
The results did not confirm our hypothesis. Indeed, no matter
which contrast was considered (MI vs. MC or MI vs. MN), no
significant difference in brain activation emerged.
The main evi-
Discussion
Using a variant of the Stroop task composed of three different
contexts (mostly congruent, mostly incongruent, and neutral), this
study investigated the proposition derived from the Dual
Mechanisms of Control account [11,12] that participants would
adopt a reactive control strategy in mostly congruent condition,
and a proactive control strategy in mostly incongruent condition.
At a behavioral level, our findings globally supported our
predictions when considering reaction times data. Indeed, we
replicated the well-known proportion congruent effect [13–15].
More specifically, whereas interference from incongruent trials
was present in all three contexts, reaction times were slower for
incongruent trials in the MC than in the MI context, which is in
agreement with the hypothesis that participants adopt a reactive
control strategy. Given the rarity of incongruent trials in this
context, they would rely on word-reading processes, since this
strategy gives rise to the fastest and most correct responses for
the majority of trials. However, when interference occurred, the
experienced conflict was even greater since it was unexpected, in
comparison to incongruent trials in the MI context, in which
participants are assumed to focus strongly on task-relevant
information (i.e., not reading the words but focusing on color
naming) given the high expectation of conflict. In addition, we
observed a facilitation effect in the MC but not in the MI
context, which is also in agreement with our hypothesis of
a smaller facilitation effect in MI context due to lower reliance
on word reading. However, one must be cautious in the
interpretation of the facilitation effect. Indeed, the comparison
of performance in the MI and MC contexts with performance in
the MN context brought some surprising findings. First, a larger
interference effect was not observed in the MC by comparison to
the MN context (slower reaction times for incongruent trials in
Table 3. Interference effect (incongruent vs. neutral items) in
MI, MC and MN contexts.
Hemisphere Anatomical region
MNI
coordinates
Z score P value
xyz
a) Interference effect in MC context
L Inferior parietal
248 236 544.82 .011
L Inferior parietal
232 252 504.56 .033
L Superior parietal
232 254 664.71 .017
L Superior parietal
226 268 384.61.027
L Middle frontal
226 210 54 4.77.014
L Inferior frontal
252 16284.18.001a
L Anterior cingulate
26 1846 4.66 .021
L Anterior insula
234 14
26 4.68 .020
R Caudate nucleus 14 106 4.65 .023
L Inferior occipital
248 268 26 4.63 .024
b) Interference effect in MI context
Nil
c) Interference effect in MN context
LInferior frontal
244 14 285.76
, ,.001
L Inferior frontal
256 20 345.37.001
L Anterior insula
232 220 4.75 .015
L Middle frontal
226 46 16 4.53.037
RInferior frontal 606 324.77.014
LSuperior parietal
224 270 42 5.45.001
L Inferior occipital
242 288 210 5.60
, ,.001
L Inferior occipital
240 270 2125.48
, ,.001
L Fusiform gyrus
250 258 2205.48
, ,.001
R Inferior occipital44
284 2104.51.040
R Cerebellum8
276 2304.75 .015
L/R=left or right; x, y, z: coordinates (mm) in the stereotactic space defined by
the Montreal Neurological Institute (MNI). This analysis was conducted with
a p value ,.05 FWE corrected.
aP,.05 FWE corrected with SVC using a 10-mm sphere radius centered on the
DLPFC’s MNI coordinates [248 15 20] [22].
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the MN context). Second, the facilitation effect was not reduced
in the MI context (the facilitation effect was absent in both the
MI and MN contexts). A characteristic of our experimental
design that may have contributed to these unexpected findings is
the use of a row of X’s as baseline. More specifically, it has been
argued [9] that the use of non-words, such as X’s as baseline,
creates a confound between lexicality and congruency (neutrals
items differ both in terms of lexicality and congruency from
congruent and incongruent items, these ones differing only in
terms of congruency). In that line, Brown [9] showed that
reaction times were faster for X’s compared to neutral words,
creating then smaller facilitation and larger interference effects
when a row of X’s was used as baseline. Therefore, it might be
interesting to investigate proactive and reactive control distinc-
tion within a proportion congruency manipulation that controls
for this confound. Finally, contrary to our expectations, error
data analysis did not show any modulation of error rates
according to the context. We only observed a globally higher rate
for incongruent trials compared to congruent and neutral trials.
However, accuracy is usually much less sensitive than reaction
times, since error rates are typically very low, especially for
congruent and neutral trials, and not consistently influenced by
proportion congruency [13,14,16]. This low sensitivity could
explain the absence of congruency effect observed here.
Regarding brain imaging data, the results did not perfectly
match our predictions of a transient reactive mode for the MC
context versus a sustained proactive mode for the MI context. For
reactive control, our analyses supported the postulated neural
network and showed that incongruent trials in the MC context
(contrasted with neutral trials in the MC or MN context) were
associated with a large fronto-parietal pattern of activation,
including the ACC and DLPFC, the two core brain areas
postulated to underlie reactive control, but also the inferior and
superior parietal cortex and anterior insula, which constitute brain
areas frequently reported to be active during conflict processing in
the Stroop literature (for a review, see [21,22]) and in cognitive
control studies in general. The ACC is typically conceived of as
responsible for detecting conflict between incompatible response
tendencies, whereas the subsequent joint involvement of the
DLPFC and parietal cortex is responsible for implementing
strategic adjustments in top-down control in order to select the
appropriate response (through activation of task-relevant in-
formation [1,39]). Interestingly, it has been proposed that the role
of parietal cortex may be to represent the different response
possibilities [40], permitting the DLPFC to focus on task-relevant
information and select the corresponding appropriate response. As
for the anterior insula, this brain area has repeatedly been
associated with a multitude of cognitive tasks (for a review, see
[41]), and is hypothesized to play a major role in identifying salient
stimuli (important environmental stimuli) within the stream of
items [41,42], such as incongruent trials in our MC context. It
would then facilitate the processing of task-relevant information
through transient control signals before the subsequent involve-
ment of the fronto-parietal network, which is responsible for
control implementation.
fMRI analyses for proactive control failed to evidence any
increase in sustained activity of the lateral PFC in the MI context.
With reference to the works of Braver and colleagues, one
important consideration has to be taken into account. Indeed,
most of their studies investigated proactive control using exper-
imental tasks such as the AX-CPT task [28,29], task-switching
paradigms [31], or working memory tasks [30], which used
contextual cues as task goal-relevant information regarding the
correct response to make to the following probes. This kind of
procedure could favor the use of a proactive control strategy, given
that the delay between the cue and the probe constitutes a period
during which relevant information is actively maintained in order
to successfully accomplish the task. In this regard, it could be useful
to investigate the proportion congruent effect in the Stroop task by
providing a cue before each item that would influence the extent to
which participants focus on task-relevant information (i.e., color
naming rather than word reading). In that line, Braver [12]
recently emphasized the importance of strong and reliable
contextual cues in the implementation of a proactive strategy.
Table 4. Comparison of incongruent trials in the MC and MI contexts with neutral trials in the MN context.
Hemisphere Anatomical region
MNI coordinates
Z score P value
xyz
a) Incongruent trials in MC context versus neutral trials in MN context
L Superior parietal
226
26838 5.23 .002
L Inferior parietal
250
236 50 5.20.002
L Inferior parietal
236
240 404.48 .044
L Anterior insula
232 20
22 5.76
, ,.001
L Inferior frontal
24814 285.62
, ,.001
L Anterior cingulate
26 20 44 5.16.002
R Anterior insula34204 4.99 .005
R Inferior frontal 32 24
210 4.72 .017
R Caudate nucleus16 108 4.72 .017
L Inferior occipital
240
288
26 4.69 .019
R Superior temporal 68
24216 4.61 .027
b) Incongruent trials in MI context versus neutral trials in MN context
L Inferior frontal
24214265.06 .004
L/R=left or right; x, y, z: coordinates (mm) in the stereotactic space defined by the Montreal Neurological Institute (MNI). This analysis was conducted with a p value
,.05 FWE corrected.
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In addition, event-related analysis regarding incongruent trials
in the MI context also produced some surprising results. First, we
did not see evidence of any differential pattern of activation
between incongruent and neutral trials within the MI context, in
agreement with one postulated property of proactive control over
similar processing for all items belonging to the MI context (i.e.,
similar inhibition of word reading and task-relevant focus).
Second, we found transient increased activation in the DLPFC
when incongruent trials in the MI context were contrasted with
neutral trials in the MN context. One might wonder why this
comparison evoked DLPFC activation. Indeed, neutral items in
both MI and MN contexts were not expected to differ in terms of
the involvement of word reading. However, the reason for this
suppression of word reading was not the same in the two task
contexts (i.e., dampening of word-reading processes due to high
expectation of interference in MI, but due to the uninformative
nature of the word dimension in the MN context where the
majority of trials were non-words). Therefore the observed
DLPFC activation could reflect the task-relevant focus (i.e., not
reading words) at play when interference occurs in the MI context,
which cannot be observed in the within-context contrast because
of the similar processing strategy applied to all items. Moreover,
conjunction analysis showed a common involvement of this
DLPFC area but also of the superior parietal cortex and insula
for incongruent trials in both MC and MI contexts. This finding
confirmed the conflict sensitivity of this fronto-parietal network,
which was involved every time incongruent trials were encoun-
tered.
However, other components of this conflict resolution network
were only sensitive to the degree of experienced conflict as shown
by the interaction analysis, which found activation in the ACC,
superior, middle, and inferior frontal areas, and cerebellum for
rare conflicting events only (i.e., incongruent trials in the MC
context). This finding is in agreement with the work of Carter et al.
[24], which found the ACC to be sensitive to the global amount of
conflict within a block or list of stimuli, and supports the evaluative
role of the ACC in conflict detection, as well as the subsequent
involvement of the DLPFC in conflict resolution through cognitive
control implementation [26,43]. Strong reliance on word reading
in the MC context would cause ACC activation, whereas strong
task-relevant focus in the MI context would ‘‘skip’’ this step in
conflict processing (i.e., no ACC involvement) and directly engage
top-down areas (e.g., DLPFC) to continue to overcome the
tendency to read words. Regarding the anterior insula, we found
activation of this structure in both the conjunction and interaction
analysis, which can be explained by reference to this structure’s
sensitivity to salient environmental stimuli. Indeed, incongruent
trials can be considered as salient events in both MC and MI
Figure 4. fMRI results for the conjunction analysis. Common activation in the left hemisphere between incongruent trials in the MI versus
neutral trials in the MN context (blue) and incongruent trials in the MC versus neutral trials in the MC context (red) (statistical threshold at p,.001
uncorrected for the present display). Bar graphs illustrate the mean parameter estimates for brain areas that emerged in the conjunction analysis
(DLPFC, insula, and superior parietal cortex), and are displayed for the different item types (incongruent, congruent, and neutral) in the three
contexts. Error bars represent standard errors.
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contexts (insula activation in the conjunction analysis), but
especially salient in the MC context given their unexpected nature
(insula activation in the interaction analysis).
Overall, behavioral and brain findings of the present experi-
ment did not totally match with our predictions. Indeed, whereas
behavioral data replicated the proportion congruent effect and
were in agreement with the proactive/reactive distinction, fMRI
data did not support the sustained nature of the proactive control
mechanism. However, we nevertheless consider that two different
modes of control were effectively at play in MC and MI contexts.
Indeed, in the MI context, the smaller interference effect on
reaction times and the absence of ACC involvement for
incongruent trials indicates that the level of experienced conflict
was reduced. This reduction could originate from a higher
relevant task focus in that context (low reliance on word reading
processes). However, contrary to the proactive mechanism
postulated within the DMC account [11], the strong goal relevant
focus at play here was mainly a transient process, as attested by the
absence of sustained increased activation, and the transient
DLPFC activation for incongruent trials. In fact, this transient
activation and the smaller interference effect at the behavioral
level could indicate item-specific control. More specifically,
a proactive strategy (in the sense of low reliance on word reading
and strong task goal focus) could be engaged at stimulus onset in
the MI context and for incongruent items only, rather than before
Table 5. Common and specific activations between (incongruent trials of MC – neutral trials of MC) and (incongruent trials of MI –
neutral trials of MN) as revealed by conjunction and interaction analyses.
Hemisphere Anatomical region
MNI coordinates
Z scoreP value (uncorrected)
xyz
a) Common activations – conjunction analysis
L Superior parietal
224
270 40 4.19
, ,.001
L Inferior frontal
250 1428 4.01
, ,.001
L Inferior frontal
256 1836 3.65
, ,.001
L Anterior insula
234222 3.87
, ,.001
L Fusiform gyrus
248
256
220 3.78
, ,.001
L Inferior occipital
244
266
2123.63
, ,.001
L Inferior occipital
244
286
24 3.46
, ,.001
b) Specific activations – interaction analysis
L Middle frontal
228
212544.85
, ,.001
L Middle frontal
248
216 604.40
, ,.001
L Middle frontal
236
220 704.28
, ,.001
R Middle frontal 32
28 563.40
, ,.001
R Superior frontal 165018 4.16
, ,.001
R Superior frontal 12 26 583.58
, ,.001
R Superior frontal6 48423.49
, ,.001
R Superior frontal8 40 443.33
, ,.001
R Inferior frontal 4412 163.61
, ,.001
L Anterior cingulate
26 2046 3.37
, ,.001
L Anterior insula
232 16
28 3.58
, ,.001
R Cerebellum10
256
212 4.55
, ,.001
R Cerebellum6
262
28 4.37
, ,.001
R Cerebellum 22
250
2243.93
, ,.001
L Cerebellum
232
248
2504.12
, ,.001
L Cerebellum
214
268
232 3.57
, ,.001
LCerebellum
210
240
250 3.55
, ,.001
L Cerebellum
232
270
224 3.31
, ,.001
RSuperior temporal 68
244103.75
, ,.001
LInferior temporal
246
266
223.35
, ,.001
LMidbrain (colliculus)
28
226
2104.00
, ,.001
L Thalamus
214
230
24 3.88
, ,.001
LThalamus
218
2248 3.80
, ,.001
R Caudate nucleus 1282 3.73
, ,.001
L/R=left or right; x, y, z: coordinates (mm) in the stereotactic space defined by the Montreal Neurological Institute (MNI). Both conjunction and interaction analyses
were conducted with a p value ,.001 uncorrected.
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the item presentation and in a sustained manner as postulated by
Braver et al. [11].
In this context of an item-specific control mechanism, some
authors have recently questioned the validity of accounting for the
proportion congruent effect in terms of variations in control
strategy at the global (i.e., list-wide) level [44–46] and its proposal
that the involvement of word-reading processes is modulated as
a function of general task context and the associated expectations
[15,18]. More specifically, they showed that the proportion
congruency effect might be accounted for by control mechanisms
that operate at the item level, at the time of stimulus onset
(stimulus-driven). These item-specific mechanisms are said to be
implemented transiently on a trial-by-trial basis in response to the
information associated with each particular item, rather than with
the list. In this view, the proactive control mechanism, in the sense
of sustained preparatory attention prior to the occurrence of the
next item, is difficult to defend. However, other recent works by
Bugg and colleagues [47,48] have provided evidence against a pure
item-specific list-wide proportion congruent effect, by clearly
demonstrating the involvement of a list-level control mechanism
minimizing the influence of word-reading processes when item-
specific influences were controlled for (see also Hutchison [49], for
a demonstration of a list-wide congruency effect not confounded
with item-specific effects). Importantly, these authors interpreted
their behavioral findings by referring to the proactive nature of
these list-wide control mechanisms.
In this context, the present experiment does not allow us to
decide about the responsible mechanism at play during the
proportion congruent effect observed. Indeed, even if the in-
volvement of item-specific mechanism is a possibility, our study
was not explicitly designed to separate and evaluate the respective
influences of list-wide and item-specific mechanisms. Indeed, list-
wide proportion congruency was equivalent for each word of the
stimulus set (e.g., in the MC context, the four color words were
presented equally often in a congruent way). Finally, the absence
of differential activation between incongruent and neutral items in
the MI context, which argued in favor of similar processing for all
items in this context, is more compatible with list-level control
rather than an item-specific mechanism. Therefore, further fMRI
studies specifically addressing this issue are needed in order to
respond to the question raised by our study regarding the temporal
dynamics of the proactive control mechanism when investigated
with a list-wide proportion congruency manipulation. In addition,
as mentioned above, the use of non-words as baseline in the
present study might have influenced the magnitude of our
interference and facilitation effects, and thus the engagement of
the associated brain areas.
In conclusion, both behavioral and brain imaging results of the
present experiment confirmed the involvement of two distinct
control strategies according to the task context (i.e., proportion
congruency in a series of trials). However, the brain findings raised
questions about the involvement of a proactive mechanism,
defined as a sustained mechanism throughout a block of stimuli.
Along these lines, we stressed the importance of experimental
design and procedure characteristics that could explain the lack of
sustained activation. In addition, we raised the possibility that high
task-relevant focus, one core property of proactive control, could
originate from item-specific rather than list-wide mechanisms.
Author Contributions
Conceived and designed the experiments: JG KD CP EB CD AL PM ES
FC. Performed the experiments: JG KD FC. Analyzed the data: JG KD
FC. Contributed reagents/materials/analysis tools: JG KD CP EB CD AL
PM ES FC. Wrote the paper: JG KD CP EB CD AL PM ES FC.
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PLoS ONE | www.plosone.org12 July 2012 | Volume 7 | Issue 7 | e41513