Brain Circuit for Cognitive Control Is Shared
by Task and Language Switching

Wouter De Baene1,2,3, Wouter Duyck1, Marcel Brass1, and Manuel Carreiras2,4

Astratto

■ Controlling multiple languages during speech production is
believed to rely on functional mechanisms that are (almeno
partly) shared with domain-general cognitive control in early,
highly proficient bilinguals. Recent neuroimaging results have
indeed suggested a certain degree of neural overlap between
language control and nonverbal cognitive control in bilinguals.
Tuttavia, this evidence is only indirect. Direct evidence for
neural overlap between language control and nonverbal cogni-
tive control can only be provided if two prerequisites are met:
Language control and nonverbal cognitive control should be

compared within the same participants, and the task require-
ments of both conditions should be closely matched. To pro-
vide such direct evidence for the first time, we used fMRI to
examine the overlap in brain activation between switch-specific
activity in a linguistic switching task and a closely matched non-
linguistic switching task, within participants, in early, highly
proficient Spanish–Basque bilinguals. The current findings pro-
vide direct evidence that, in these bilinguals, highly similar
brain circuits are involved in language control and domain-
general cognitive control. ■

INTRODUCTION

A key question in bilingual language production is how
bilingual speakers are able to control their two languages
during speech processing and why they are so efficient
in avoiding language conflicts or unintended nontarget
language intrusions. The nature of the cognitive pro-
cesses underlying this bilingual language control is still
a matter of debate and has generated a substantial body
of research during the last decade. Several language
control mechanisms have been proposed, such as inhibi-
tion of the unintended language (Verde, 1998).

One of the most frequently used paradigms to study
the cognitive mechanisms underlying bilingual and multi-
lingual language control in language production has been
the language-switching paradigm (Abutalebi et al., 2008,
2013; Gollan & Ferreira, 2009; Verhoef, Roelofs, & Chwilla,
2009; Costa, Santesteban, & Ivanova, 2006; Costa &
Santesteban, 2004; Jackson, Swainson, Cunnington, &
Jackson, 2001; Hernandez, Martinez, & Kohnert, 2000;
Meuter & Allport, 1999). Recent neuroimaging research
has suggested that brain areas involved in language switch-
ing are similar to those implicated in nonverbal cognitive
controllo, as measured for instance with (nonverbal) task-
switching paradigms (per esempio., Garbin et al., 2010, 2011; Guo,
Liu, Misra, & Kroll, 2011; Abutalebi & Verde, 2008; Wang,
Xue, Chen, Xue, & Dong, 2007; Crinion et al., 2006;

1Ghent University, 2Basque Center on Cognition, Brain and
Language, Donostia-San Sebastián, Spain, 3Tilburg University,
4Basque Foundation for Science, Bilbao, Spain

© 2015 Istituto di Tecnologia del Massachussetts

Hernandez, Dapretto, Mazziotta, & Bookheimer, 2001;
Hernandez et al., 2000). The language control network
involves lateral and medial prefrontal areas, parietal areas,
and the caudate nucleus (see Abutalebi & Verde, 2008, for
a review). D'altra parte, in task switching, a fronto-
parietal network is generally observed, including lateral
and medial prefrontal, premotor, and anterior and pos-
terior parietal regions as well as the BG (De Baene, Albers,
& Brass, 2012; De Baene & Brass, 2011; Shi, Zhou, Müller, &
Schubert, 2010; Crone, Wendelken, Donohue, & Bunge,
2006; Yeung, Nystrom, Aronson, & Cohen, 2006; Barber
& Carter, 2005; Ruge et al., 2005; Braver, Reynolds, &
Donaldson, 2003; Brass & von Cramon, 2002; Dreher &
Berman, 2002; Dreher, Koechlin, Ali, & Grafman, 2002;
Rushworth, Hadland, Paus, & Sipila, 2002; Rushworth,
Paus, & Sipila, 2001; Dove, Pollmann, Schubert, Wiggins, &
Yves von Cramon, 2000; Kimberg, Aguirre, & D’Esposito,
2000; Sohn, Ursu, Anderson, Stenger, & Carter, 2000).

È interessante notare, up to now there is only indirect evidence
that the neural regions supporting language control are
the same as those supporting cognitive control in non-
verbal domains. Only a few studies have directly exam-
ined the neural regions involved in a nonverbal cognitive
control task in bilinguals (Garbin et al., 2010; Luk, Anderson,
Craik, Grady, & Bialystok, 2010; Bialystok et al., 2005).
Garbin et al. (2010), for instance, compared the brain
regions involved in a non-linguistic switching task between
bilinguals and monolinguals and reported fundamental
differences in the brain network engaged in task switching
between both groups. Whereas monolinguals activated the
right inferior frontal gyrus, ACC, and left inferior parietal

Journal of Cognitive Neuroscience 27:9, pag. 1752–1765
doi:10.1162/jocn_a_00817

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lobule, bilinguals only displayed switch-specific activity in
the left inferior frontal gyrus and the left striatum. Given
that the left inferior frontal gyrus and the left striatum have
been consistently related to bilingual language control
(per esempio., Abutalebi & Verde, 2007), according to Garbin
et al. (2010), these results suggest a certain degree of
neural overlap between language control and nonverbal
cognitive control in bilinguals.

Tuttavia, to directly examine the link between the
regions involved in control of language conflict and
those involved in general cognitive control, we need to
examine the regions involved in both domains, within
the same participants. Until now, only Abutalebi et al.
(2012) followed this rationale. They examined within
the same participants whether language control and the
cognitive control processes involved in the flanker task
have a common neural substrate. The dorsal ACC was
found to be common to language switching and conflict
monitoring in the flanker task. Tuttavia, comparing
a language-switching task with a conflict task confounds
a number of cognitive control processes that are not
related to the specific requirements of language switch-
ing. In particular, language switching relies mainly on
the executive function of mental shifting (Miyake et al.,
2000), whereas the flanker task is more strongly asso-
ciated with inhibition of distractors or responses. Although
these executive functions (together with updating of
working memory) are moderately correlated (see also
Friedman et al., 2006), they are clearly distinct, separable
functions. Accordingly, these functions seem to rely on a
partly shared–partly selective neural circuit. There are
several brain areas involved commonly in different execu-
tive processes, whereas other brain areas are involved
only in specific executive processes (per esempio., only for shift-
ing; Hedden & Gabrieli, 2010). To capture those specific
processes that relate language control with nonverbal
controllo, one needs to compare language switching with
a closely matched nonlinguistic switching paradigm.
Therefore, we examined the neural overlap between
two closely matched linguistic and nonlinguistic switch-
ing paradigms within the same participants.

Importantly, the occurrence and manifestation of lan-
guage conflict might depend on the proficiency of the
bilinguals (Van Heuven, Schriefers, Dijkstra, & Hagoort,
2008). Infatti, the precise nature of the language conflict
(Abutalebi & Verde, 2007) and the associated control
meccanismo (Costa et al., 2006; Costa & Santesteban,
2004) might even alter qualitatively with proficiency. A
the neural level, the activation of the regions involved in
language control or the specific network involved might
also be modulated by language proficiency (Abutalebi
et al., 2013; Garbin et al., 2011). Consequently, one
might assume that also the overlap between the regions
involved in language control and the regions involved in
cognitive control might vary as a function of language
proficiency. In this study, we only considered early profi-
cient bilinguals who switch frequently between languages.

This choice was motivated by the fact that several stud-
ies have claimed that bilinguals outperform mono-
linguals on a range of cognitive control tasks (per esempio., Prior
& Gollan, 2011; Prior & MacWhinney, 2010; Bialystok &
Viswanathan, 2009; Bialystok, Craik, & Luk, 2008; Costa,
Hernández, & Sebastián-Gallés, 2008; but see Antón
et al., 2014; Duñabeitia et al., 2014; Hernández, Martin,
Barceló, & Costa, 2013; Paap & Greenberg, 2013). How-
ever, this bilingual advantage might be more salient and
might spread across a wider range of attention-demanding
compiti (Bialystok, Craik, & Ryan, 2006) for those bilinguals
who constantly exercise language control functions on a
daily basis (Verreyt, Woumans, Vandelanotte, Szmalec, &
Duyck, 2015).

In summary, in the current study, we wanted to examine
the overlap in brain activation between a language-
switching paradigm and a nonverbal task-switching
paradigm with a closely matched procedure, using a
within-subject paradigm with early proficient bilinguals.
This approach allows us to directly relate brain acti-
vation in a linguistic switching task to brain activation
in a nonlinguistic switching task, providing the strongest
test possible of the generalizability of the language con-
trol system developed by early proficient bilinguals to
the cognitive control domain.

In this study, we opted for a paradigm with three tasks
or three languages. This was motivated by the fact that
two-task or two-language experiments might be a special
case, because switching away from one task or language
automatically involves switching back to the only other
task or language (Ruthruff, Remington, & Johnston,
2001). With three tasks or languages, a switch requires
that participants choose which of the remaining tasks
or languages to perform, which might be more repre-
sentative of natural language processing. Because early,
proficient bilinguals seem to apply the same language-
switching mechanism not only to the most proficient lan-
guages but also to weaker (L3) languages (Costa et al.,
2006; Costa & Santesteban, 2004), including a weaker
third language here should not imply qualitatively dif-
ferent language switches.

METHODS

Participants

Thirty-six healthy right-handed college students partici-
pated in this study for monetary reimbursement. Four
participants were excluded from the analyses because
of excessive movement during scanning. All remaining
participants (13 men; mean age = 22.4 years, range =
18–33 years) had Spanish as their L1, Basque as their L2
and had a good knowledge of English (L3). All participants
were early, highly proficient bilinguals: They acquired L2
at an early age (on average before the age of 3 years; one
participant at the age of 8 years) and were regularly (SU
average 4.3 days/week, range = 1–7 days/week)

De Baene et al.

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confronted with contexts in which (inter- and intrasen-
tential) code switching between their L1 and L2 occurred.
The participants acquired L3 on average after the age of
6 years (range = 4–12 years) and were rarely confronted
with contexts in which code switching between their L1
and L3 or between their L2 and L3 occurred.

All participants had normal or corrected-to-normal
vision. None of them used medication or had a history
of drug abuse, head trauma, or neurological or psychiat-
ric illness. All participants gave informed consent before
testing. The study was approved by the institutional
ethical committee.

Materials

Language proficiency has many different dimensions
(word processing, syntactic processing, eccetera.), making it
a complex concept to measure. Although, optimally,
proficiency should be defined using different tasks that
measure proficiency at different representational levels
of the language, only single word processing tasks were
included here given that the focus of this study is on
switching at the word level. Next to the self-reported
proficiency measures, language proficiencies in Spanish,
Basque, and English were therefore measured with the
Rapid Automatized Naming (RAN) test and the Boston
Naming Test (BNT; Vedi la tabella 1 for results on these tests).

RAN Test

Both a digits RAN test and a color RAN test were admin-
istered in Spanish, Basque, and English in all participants.
The order of the language to be used was counter-
balanced across participants. The RAN test (Denckla &
Rudel, 1974) is assumed to measure the ability to access
and retrieve phonological representations from long-term
memory (per esempio., Torgesen, Wagner, Rashotte, Burgess, &
Hecht, 1997; Wagner & Torgesen, 1987) as well as the
ability to form orthographic representations (Bowers,
Sunseth, & Golden, 1999; Bowers, Golden, Kennedy, &
Young, 1994).

In each rapid naming test, participants were asked to
name, as quickly as possible, six visual stimuli displayed
on the screen, in a random order in four rows of nine
stimuli each. Before each test, all stimuli were shown

once to the participant to verify that he or she was able
to name them in the languages to be used.

The stimuli for the digits RAN test were 1, 2, 3, 5, 7,
E 8, each presented six times. The stimuli of the color
RAN test were red, black, green, brown, blue, and yellow
piazze, also presented six times each. Naming times
were measured. The digits RAN test was always adminis-
tered before the color RAN test.

As a proficiency measure, the ratio between the
average naming times across the digits and color RAN
tests in L2 and L1 was calculated. Perfectly balanced par-
ticipants have a RAN ratio of 1, whereas larger RAN
ratios indicate a larger proficiency difference between
L1 and L2.

BNT

The BNT was administered in Spanish, Basque, and English
to all participants. The order of the language to be used
was counterbalanced across participants. The BNT is
assumed to measure word retrieval abilities (Kaplan,
Goodglass, & Weintraub, 1983).

The BNT contains 60 pictures presented one by one in
order of word frequency and grade of difficulty (from
common, high frequent, [per esempio., “bed”] to less familiar,
low frequent, [per esempio., “abacus”]). Participants were asked
to name them in the appropriate language. The scoring
was done according to standard instructions.

Language-switching Task

For the language-switching task, eight pictures (size =
3.27 × 3.27 visual degrees) of common objects with
noncognate names in Spanish, Basque, and English were
selected from the Snodgrass and Vanderwart pictures set
(Rossion & Pourtois, 2004). The stimuli were selected
based on the following matching criteria across the three
languages: frequency, number of letters, number of
phonemes, number of orthographic neighbors, age of
acquisition, and concreteness. For Spanish and Basque,
information was extracted from the BaSp database
(Duñabeitia et al., in preparation). For English, infor-
mation was provided by the N-Watch program (Davis,
2005).

Tavolo 1. Overview of Language Proficiency Scores

Self-ratings

Naming times (colors), sec

Naming times (numbers), sec

BNT

Spanish

9.56 (0.62)

21.59 (2.75)

14.04 (2.79)

50.72 (3.79)

Basque

8.13 (1.29)

25.65 (4.22)

17.30 (4.80)

39.97 (8.71)

English

6.59 (1.16)

26.70 (6.61)

19.06 (2.95)

24.72 (7.41)

1754

Journal of Cognitive Neuroscience

Volume 27, Numero 9

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Figura 1. Design of the
experiment. The language-
switching condition is
presented on the left. IL
task-switching condition is
presented on the right. A trial
started with the presentation
of a cue for 300 msec, Quale
instructed the participants
which language to use (Spanish,
Basque, or English) or which
task to perform (motion, colore,
or gender task). The cue was
followed by the stimulus that
was presented for 500 msec.
The participants were instructed
to respond as fast as possible,
without sacrificing accuracy. After the response (or maximally after 1500 msec, whichever came first), a variable response–cue interval started (mean =
2625 msec; range = 1000–5250 msec, in steps of 250 msec, distribution with pseudologarithmic density). In the language-switching condition,
verbal responses were used whereas responses via button presses were used in the task-switching condition.

Participants were instructed to name the picture aloud
in Spanish, Basque, or English according to the shape cue
presented before the picture. Per participant, three cues
were selected out of six available cues (a circle, diamond,
triangle, square, star, or pentagon). The remaining three
cues were used in the task-switching task. The cue-to-
response language assignments were counterbalanced
across participants.

Each experimental trial had the following structure
(Figura 1): After the presentation of a cue for 300 msec,
a picture was presented on a black background at the
center of the screen (60 Hz frame rate, positioned 250 cm
from the participants) for 500 msec, after which the
participants had to respond as fast as possible, without
sacrificing accuracy. After a jittered response–cue interval
(mean = 2625 msec; range = 1000–5250 msec, in steps
Di 250 msec, distribution with pseudologarithmic density),
the next trial started.

Before scanning, all participants completed a training
phase. Primo, participants were familiarized with the
names of the pictures in the three languages. To this
end, each stimulus was presented centered on the screen
with its name presented below it in Spanish, Basque, E
English. Participants had to press a button to go to the
next stimulus. After this familiarization phase, partici-
pants worked through one practice block for each lan-
guage separately (16 trials each). The order of the
language to be used in the practice blocks was counter-
balanced across participants. Afterwards, participants
worked through a practice block (48 trials) in which the
three languages were randomly intermixed. In the scan-
ner, participants went through nine blocks of 72 trials,
each of which were equally distributed across the three
languages and the eight stimuli. The sequence of trials
was also controlled for an equal number of language
transitions (per esempio., L1–L1 vs. L1–L2) and language sequences
(per esempio., L1–L2–L1 vs. L3–L2–L1). Each block started with
an instruction screen reminding the participants of the

cue-to-language assignments. Speech onset of the vocal
responses was recorded with a voice key. Errors were
coded offline by the experimenter in a subject file.

Task-switching Task

In the task-switching task, three different tasks were
used. In the motion task, participants judged the motion
direction of the stimulus (up and down vs. left and right).
In the color task, participants judged the color (red vs.
blue) of the colored pixels of the stimulus. In the gender
task, participants judged the gender (male vs. female) Di
the face. Participants used their index finger of their right
and left hand to answer. The stimulus–response assign-
ments for each task were counterbalanced across par-
ticipants. On each trial, the task to perform was indicated
by the shape cue presented before the stimulus. Per par-
ticipant, three cues were selected out of six available cues
(see previous section). The cue-to-task assignments were
counterbalanced across participants.

All stimuli were stored as 320 × 400 pixel image
sequences and presented for 500 msec as a continuous
movie of frame sequences at a frame rate of 60 Hz on
a black background on a screen positioned 250 cm from
the participant. The stimuli (size = 3.49 × 4.36 visual
degrees) were pictures of a man or a woman filled with
a random texture pattern (50% colored and 50% black
pixels) moving at a standard speed of 1.3 degrees/sec.
The colored pixels were either red or blue and were
matched for luminance. The pixels moved up and down
(250 msec each in intervals of 125 msec) or left and right
(250 msec each in intervals of 125 msec). The structure
of the experimental trials was identical to the language-
switching trial structure (Figura 1): After the presentation
of a cue for 300 msec, a stimulus was presented for
500 msec after which the participants had to respond
as fast as possible, without sacrificing accuracy. Dopo
a jittered response–cue interval (mean = 2625 msec;

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range = 1000–5250 msec, in steps of 250 msec, distribu-
tion with pseudologarithmic density), the next trial started.
Before scanning, all participants went through a train-
ing phase. Primo, participants worked through one practice
block for each task separately (16 trials each). The order
of the tasks in the practice blocks was counterbalanced
across participants. Afterwards, participants worked
through a practice block (48 trials) in which the three
tasks were randomly intermixed. In the scanner, partici-
pants went through nine blocks of 72 trials, each of which
were equally distributed across the three tasks. IL
sequence of trials was also controlled for an equal number
of task transitions (per esempio., repeat vs. switch) and task
sequences (per esempio., color–motion–color vs. gender–motion–
colore). Each block started with an instruction screen
reminding the participants of the cue-to-task and stimulus–
response assignments.

Procedure

Given the amount of tasks and the duration of these
compiti, participants went through two separate sessions,
each lasting for about 2.5 hr, with a mean intersession
time of 6.26 days (SD = 2.78 days).

One session contained the language-switching task.
For half of the participants, the different RAN tests were
also ran in this session, whereas the different BNT tests
were ran in this session for the other half of the partici-
pants. The other session contained the task-switching
task. Additionally, the different BNT tests were ran in this
session for half of the participants, whereas the different
RAN tests were added in the other half of the partici-
pants. The order of the two sessions was counter-
balanced across participants.

fMRI Data Acquisition and Analysis

Participants were positioned head first and supine in the
magnetic bore. Images were collected with a 3T Magnetom
Trio MRI scanner system (Siemens Medical Systems,
Erlangen, Germany), using a standard 32-channel radio-
frequency head coil. Participants were instructed not to
move their heads to avoid motion artifacts.

Each session started with a high-resolution 3-D struc-
tural scan, using a T1-weighted 3-D MPRAGE sequence
(repetition time = 2530 msec, echo time = 2.97 msec,
inversion time = 1100 msec, acquisition matrix = 256 ×
256 × 176, field of view = 256 mm, flip angle = 7°, slice
thickness = 1 mm, slice gap = 0.5 mm). Whole-brain func-
tional images were collected using a T2*-weighted EPI
sequence, sensitive to BOLD contrast (repetition time =
2000 msec, echo time = 28 msec, image matrix = 64 × 64,
field of view = 192 mm, flip angle = 20°, slice thickness =
3 mm, distance factor = 20%, voxels resized to 3 × 3 ×
3 mm3, 33 axial slices). A varying number of images were
acquired per run because of the self-paced initiation of
trials.

fMRI Data Preprocessing

Data processing and analyses were performed using
the SPM8 software (Wellcome Department of Cognitive
Neurology, London, UK). The first four scans of all EPI
series were excluded from the analysis to minimize T1
relaxation artifacts. Data processing started with slice
time correction and realignment of the EPI datasets. UN
mean image for all EPI volumes was created, to which
individual volumes were spatially realigned by rigid body
transformation. The high-resolution structural image was
coregistered with the mean image of the EPI series. IL
structural image was normalized to the Montreal Neuro-
logical Institute template. The normalization parameters
were then applied to the EPI images to ensure an ana-
tomically informed normalization. Motion parameters
were estimated for each session separately. A commonly
applied filter of 8-mm FWHM was used. The time series
data at each voxel were processed using a high-pass filter
with a cutoff of 128 sec to remove low-frequency drifts.
Separately for the language-switching and task-switching
parts, statistical analyses were performed on individual
participants’ data using the general linear model (GLM)
in SPM8. The fMRI time series data were modeled by two
different vectors reflecting the transition status (switch vs.
repeat) of the trial. Erroneous trials and trials following
errors were modeled together as a regressor of no inter-
est and were excluded from the analyses.

All these vectors were convolved with the canonical
hemodynamic response function, as well as with the tem-
poral derivative and entered into the regression model
(the design matrix). Inoltre, residual effects of head
motion were corrected by including the six motion param-
eters estimated during the SPM8 realignment procedure
for each participant as regressors of no interest in the
design matrix. The statistical parameter estimates were
computed separately for each voxel for all columns in
the design matrix.

Whole-brain Analyses

For the group analyses, the contrast images from the
single participant analyses were submitted to a random-
effects full factorial design with condition (lingua
switching vs. task switching) as factor. Group map sig-
nificance was defined using a threshold of p < .0001 at voxel level and a cluster level corrected for the whole brain at p < .05. In a conjunction analysis, we compared the contrast images of both switching conditions to identify brain regions showing switch-specific activity common to both language switching and task switching. In this analysis, we tested for a rejection of the conjunction null hypoth- esis (i.e., only those voxels were reported as active which proved to be significant for the switch vs. repeat contrast in both switch conditions). Additionally, we used the contrast images of the language-switching and 1756 Journal of Cognitive Neuroscience Volume 27, Number 9 D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 7 / 9 2 7 1 / 7 9 5 / 2 1 1 7 9 5 4 2 9 / 8 1 1 7 0 8 o 3 c 5 n 5 _ 3 a / _ j 0 o 0 c 8 n 1 7 _ a p _ d 0 0 b 8 y 1 g 7 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j t f / . u s e r o n 1 7 M a y 2 0 2 1 task-switching conditions for a disjunction analysis to identify areas showing switch-specific activity in language switching ( p < .0001) but not in task switching ( p > .10)
as well as vice versa.

ROI Analyses

To get a more fine-grained look at the pattern of brain
activation across conditions in the areas observed with
the above-mentioned analyses, we performed an ROI
analysis for each of these areas. Data for the different
conditions (switch and repeat conditions for both the
language-switching and task-switching parts) for each
ROI were extracted from a 6-mm-radius sphere around
the peak voxel identified for each of these areas.

For each ROI and participant, we also measured the
voxelwise pattern of selectivity of the switch condition
compared to the repeat condition. This was done by
extracting a t value for the contrast switch versus repeat
at each voxel within the ROI (see also Peelen, Wiggett, &
Downing, 2006). A correlation between two switch selec-
tivity patterns (cioè., in language switching and task switch-
ing) for each participant was calculated as follows. Primo,
we computed a t value for each voxel in the ROI reflect-
ing language switch selectivity. Secondo, we computed a
t value for each voxel in the same ROI reflecting task
switch selectivity. These two sets of t values were then
represented as two 1-D vectors. Finalmente, a correlation
was computed between these two vectors. The average
correlation across participants constitutes the voxelwise
correlation between language switch and task switch
selectivity. We would expect a positive voxelwise cor-
relation between language switch selectivity and task
switch selectivity in an ROI if the variation in selectivity
across voxels is stable and reflects variations in the pro-
portions of neurons exhibiting different kinds of selec-
attività (for a similar argument, see Peelen & Downing,
2005). In summary, the assumption is that a positive cor-
relation indicates that similar voxels are recruited during
both switching conditions. As such, a positive voxelwise
correlation within an area might provide additional
evidence that this area is similarly involved in language
control and in nonverbal cognitive control.

RESULTS

Behavioral Results

For the language production task, a GLM repeated-measures
ANOVA was run on the accuracy data with Language (L1, L2,
or L3) and Transition status (switch vs. repeat) as within-
subject variables. Only the main effect of Transition status
reached significance, F(1, 31) = 23.08, P < .001. There was a switch cost with less accurate switch trials than language repeat trials (93.20% vs. 96.06%, respectively). This switch cost was equally large across languages (Inter- action language × Transition status: F < 1). Such a symmetric switch cost is generally found in balanced bilinguals, and switching between the early acquired languages also generalizes to a third, late acquired language (e.g., see previous findings in a different, Spanish–Catalan bilingual community; Costa et al., 2006). The main effect of Lan- guage was not significant, F(2, 30) = 1.96, p = .16. RT data for the language task were not available because the scanner noise yields technical difficulties for extracting the voice onset times. For the task-switching task, a GLM repeated-measures ANOVA was run on both the accuracy and the RT data with Transition status (switch vs. repeat) as the within- subject variable. A substantial switch cost was again observed: Participants were significantly less accurate (89.03% vs. 93.39%, F(1, 31) = 29.37, p < .001) and slower (808.1 msec vs. 653.0 msec, F(1, 31) = 119.19, p < .001) for switch trials than for repeat trials. fMRI Results Conjunction Analysis We first tried to identify brain regions showing switch- specific activity common to both language switching and task switching. To do so, we ran a conjunction anal- ysis of both the language-switching and task-switching conditions. This analysis (Figure 2; Table 2) revealed switch-specific activity in both conditions within the pre- cuneus (extending into bilateral superior parietal lobule and left inferior parietal lobule), posterior cingulate cor- tex, left fusiform gyrus (extending into the cerebellum), pre-SMA, left inferior frontal junction (IFJ; extending into the inferior frontal gyrus), and left and medial calcerine fissure. For each of these areas, an ROI analysis was performed to get a more fine-grained look at the pattern of brain activation across conditions. A GLM repeated-measures ANOVA for each of these areas with Activity as a depen- dent variable and Transition (switch vs. repeat) and condition (language switching vs. task switching) as independent variables showed a higher activity in switch trials than in repeat trials across conditions (main effect Transition, all ps < .001) in all these areas. Additionally, the precuneus, posterior cingulate cortex, left IFJ, and pre-SMA also showed a significant interaction between Transition and Condition ( p < .05 for posterior cingulate cortex; all other ps < .001; for areas showing no inter- action: all ps > .36). In these four areas, this interaction
was driven by a higher switch-specific activity in task
switching compared to language switching.

For each area, we also determined the voxel-by-voxel
correlations between language switch selectivity and task
switch selectivity. Voxel by voxel, language switch selec-
tivity was significantly correlated with task switch selec-
tivity in all ROIs: precuneus (r = .46; t31 = 6.03, P < .001), posterior cingulate cortex (r = .61; t31 = 11.04, p < .001), left fusiform gyrus (r = .40; t31 = 6.33, p < .001), pre-SMA De Baene et al. 1757 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 7 / 9 2 7 1 / 7 9 5 / 2 1 1 7 9 5 4 2 9 / 8 1 1 7 0 8 o 3 c 5 n 5 _ 3 a / _ j 0 o 0 c 8 n 1 7 _ a p _ d 0 0 b 8 y 1 g 7 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j f / . t u s e r o n 1 7 M a y 2 0 2 1 Figure 2. Activation map for areas involved both in language switching and task switching averaged across 32 participants ( p < .0001 uncorrected, corrected at cluster level) mapped onto a standard Colin brain template. D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 7 / 9 2 7 1 / 7 9 5 / 2 1 1 7 9 5 4 2 9 / 8 1 1 7 0 8 o 3 c 5 n 5 _ 3 a / _ j 0 o 0 c 8 n 1 7 _ a p _ d 0 0 b 8 y 1 g 7 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j . t f / u s e r o n 1 7 M a y 2 0 2 1 (r = .56; t31 = 7.54, p < .001), left IFJ (r = .62; t31 = 10.79, p < .001), left calcarine fissure (r = .40; t31 = 6.26, p < .001), and medial calcarine fissure (r = .23; t31 = 2.95, p < .01). This suggests that in all these areas, similar sub- populations of neurons are recruited during both language switching and task switching. Disjunction Analyses To identify areas showing switch-specific activity specifi- cally in language switching, we performed a disjunction analysis between language switching and task switching (Figure 3; Table 3). Switch-specific activity in right Sylvian fissure, pre-SMA, right precentral gyrus, and left pre- central gyrus was only observed in language switching Table 2. Areas Common to Language Switching and Task Switching Peak Coordinates z Score Extent Area Precuneus Posterior cingulum −6 −76 52 0 −34 31 Fusiform gyrus −45 −67 −17 Pre-SMA IFJ Calcarine fissure Calcarine fissure 0 14 52 −48 8 31 −12 −76 10 0 −91 −11 6.92 6.50 6.10 6.06 5.99 4.61 4.54 1041 67 218 211 267 40 69 1758 Journal of Cognitive Neuroscience Volume 27, Number 9 Figure 3. Activation map for areas specifically involved in language switching. D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 7 / 9 2 7 1 / 7 9 5 / 2 1 1 7 9 5 4 2 9 / 8 1 1 7 0 8 o 3 c 5 n 5 _ 3 a / _ j 0 o 0 c 8 n 1 7 _ a p _ d 0 0 b 8 y 1 g 7 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j . / f t u s e r o n 1 7 M a y 2 0 2 1 but not in task switching. To exclude the possibility that this result is merely the consequence of subthreshold activation in the task-switching condition in these areas and to provide additional support for the fact that these areas do show specific effects for language switching, ROI Table 3. Areas Specifically Involved in Language Switching Area Peak Coordinates z Score Extent Sylvian fissure Pre-SMA Precentral gyrus 54 17 −5 3 20 67 51 −10 40 Postcentral gyrus −45 −16 40 5.95 5.23 4.84 4.57 31 27 48 38 analyses in these areas were performed using a GLM repeated-measures ANOVA with Activity as a dependent variable and Transition (switch vs. repeat) and Condition (language switching vs. task switching) as independent variables. All areas showed a higher activity in switch trials compared with repeat trials across conditions (main effect Transition; p < .05 for left postcentral gyrus, p < .01 for right precentral gyrus, and p < .001 for right Sylvian fis- sure and pre-SMA). However, all these areas also showed a significant interaction between Condition and Transition (all ps < .001). This interaction was driven by a significant language switch cost (all ps < .001) in combination with no task switch cost (all ps > .15).

To identify areas showing switch-specific activity spe-
cifically in task switching, we performed a disjunction
analysis between task switching and language switching

De Baene et al.

1759

Figura 4. Activation map for
areas specifically involved in
task switching.

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Tavolo 4. Areas Specifically Involved in Task Switching

Area

Peak Coordinates

z Score Extent

Inferior parietal lobule

Superior frontal gyrus

Superior frontal sulcus

−39 −40 46

−24 −1 55

30 −1 58

Middle occipital gyrus

−48 −58 −11

Superior parietal lobule

15 −61 55

Insula

Rostral cingulate zone

36 17 7

9 20 49

7.79

7.73

6.28

6.22

5.62

4.98

4.94

475

486

85

116

131

33

30

(Figura 4; Tavolo 4). Switch-specific activity in left inferior
parietal lobule, left superior frontal gyrus, right superior
frontal sulcus, left middle occipital gyrus, right superior
parietal lobule, right insula, and the rostral cingulate zone
was only observed in task switching and not in language
switching. To find additional support for these findings,
ROI analyses in these areas using a GLM repeated-
measures ANOVA with Activity as a dependent variable
and Transition (switch vs. repeat) and Condition (lan-
guage switching vs. task switching) as independent vari-
ables were performed. All areas showed a higher activity
in switch compared to repeat trials across conditions
(main effect Transition; all ps < .001). However, all these areas also showed a significant interaction between Condi- tion and Transition (all ps < .004). For the left superior frontal gyrus, the right superior frontal sulcus, and the right 1760 Journal of Cognitive Neuroscience Volume 27, Number 9 insula, this interaction is driven by a significant task switch cost (all ps < .001) in combination with no language switch cost (all ps > .32). For left inferior parietal lobule
and left middle occipital gyrus, this interaction is driven
by a significant task switch cost (all ps < .001) in combi- nation with a marginally significant language switch cost (all ps < .085). Finally, the interaction between condition and transition in the rostral cingulate zone and the right superior parietal lobule is driven by a combination of a significant task switch cost ( p < .001) with a significant but much smaller language switch cost (all ps < .05). DISCUSSION Over the last decade, several studies have provided evi- dence that bilingual language control shares (at least partly) functional mechanisms with domain-general cog- nitive control (e.g., Calabria, Hernández, Branzi, & Costa, 2012; Weissberger, Wierenga, Bondi, & Gollan, 2012). Recently, attempts have been made to provide neural evidence for the bilingual overlap between language con- trol and cognitive control (e.g., Abutalebi et al., 2012; Garbin et al., 2011; Abutalebi & Green, 2007, 2008; Wang et al., 2007). The available neural evidence suggests that language control is achieved through multiple areas that are also engaged in cognitive control. The support for this claim of neural overlap between language control and cognitive control in bilinguals, however, remained indirect. Direct evidence for neural overlap between two conditions may only be provided if both conditions are compared within the same par- ticipants. Furthermore, to capture the full scope of cog- nitive control processes involved in language switching, the task requirements of the different conditions need to be closely matched. Previous studies did not meet both prerequisites. The aim of the current study was to provide such direct evidence for the first time by exam- ining the neural overlap between switch-specific activity in a linguistic switching task and a closely matched non- linguistic switching task, within participants, in early, highly proficient bilinguals. The current results support the claim that language control and more domain-general cognitive control in early, highly proficient bilinguals rely on common areas within the distributed frontoparietal network, which are also engaged in task-switching. Indeed, lateral and medial PFC as well as the inferior and superior parietal lobule were commonly active in linguistic and nonlinguistic switching. Furthermore, voxel-by-voxel analyses (e.g., Peelen et al., 2006) for all involved areas supported the similar contribution of these areas across linguistic and nonlinguistic switching. Consequently, the functions that are typically attributed to these areas for task switching could also apply for language switching. Classically, the lateral PFC is linked to the mainte- nance, retrieval, and implementation of task goals and in performance adjustments by engaging regulatory processes to overcome interference and resolve com- petition from the previously implemented task set (e.g., Hyafil, Summerfield, & Koechlin, 2009; MacDonald, Cohen, Stenger, & Carter, 2000; Sohn et al., 2000). This fits the role proposed for lateral PFC in language switch- ing in which the relevant language needs to be retrieved and implemented while resolving competition with the no-longer relevant language (see Abutalebi & Green, 2007). The medial PFC (comprising dorsal ACC and pre-SMA) has generally been attributed a monitoring and confi- guration role (e.g., Hyafil et al., 2009; Ridderinkhof, Ullsperger, Crone, & Nieuwenhuis, 2004). The dACC detects conflict between, for instance, the previous and the new task in case of a task change (Ridderinkhof et al., 2004). The pre-SMA configures the cognitive sys- tem for the upcoming task by resolving the conflict by suppressing active but inappropriate actions from a pre- vious task set and boosting the selection of appropriate actions as demanded by the new task set (Hikosaka & Isoda, 2010; Isoda & Hikosaka, 2007). Similarly, the medial PFC has been suggested to monitor the language context for bilingual or multilingual speakers (Abutalebi et al., 2013) and to withhold the language not in use (see Abutalebi & Green, 2007). Additional evidence for the domain-general involvement of medial PFC in detect- ing and aiding the resolution of conflicts comes from a recent study of Abutalebi et al. (2012). They showed that the dACC and pre-SMA were the only areas that were common to a language control task and a flanker task in highly proficient bilinguals. Although the peak coordi- nates of the medial frontal area observed in the current study are slightly more anterior (x = 0, y = 14, z = 52 vs. x = 0, y = 2, z = 60), this area overlaps with the pre-SMA reported by Abutalebi et al. (2012). The superior parietal lobule has previously been shown to be involved in switching the attentional focus to the newly relevant task information when a change is detected (e.g., Braver et al., 2003). Furthermore, Mevorach, Humphreys, and Shalev (2006) showed that left and right posterior parietal cortex have comple- mentary roles, respectively pulling attention away and pushing attention to the stimuli. Similarly, Abutalebi and Green (2007, 2008) proposed that also in unpredict- able language switching, the left posterior parietal cortex might bias the attention away from the previous, now irrelevant language whereas the right part might bias the attention towards the new, relevant language. Finally, the inferior parietal lobule (and sulcus) is commonly thought to be important for integration of sensory, cognitive, and motor information (Gottlieb, 2007; Andersen & Buneo, 2002; Pouget, Deneve, & Duhamel, 2002). These areas are assumed to be involved in representing and maintaining cue-associated response contingencies (Bunge, Kahn, Wallis, Miller, & Wagner, 2003) or stimulus–response mappings (e.g., De Baene et al., 2012; Hartstra, Kühn, Verguts, & Brass, 2011; Woolgar, De Baene et al. 1761 D o w n l o a d e d f r o m l l / / / / j t t f / i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 7 / 9 2 7 1 / 7 9 5 / 2 1 1 7 9 5 4 2 9 / 8 1 1 7 0 8 o 3 c 5 n 5 _ 3 a / _ j 0 o 0 c 8 n 1 7 _ a p _ d 0 0 b 8 y 1 g 7 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j . / t f u s e r o n 1 7 M a y 2 0 2 1 Thompson, Bor, & Duncan, 2011; Hester, D’Esposito, Cole, & Garavan, 2007; Brass & von Cramon, 2004). This is in line with the assumption that the inferior parietal lobule is related to the maintenance of word representations (Wang, Kuhl, Chen, & Dong, 2009) in language switching. Although early, highly proficient bilinguals seem to rely on common areas within the distributed frontoparietal network in language switching and task switching, some areas seem specifically involved in one of the two condi- tions, as is evident from the disjunction analyses. This might follow from the fact that the language-switching and task-switching paradigms, although matched to a very high degree, do necessarily differ in some respects. For instance, because we wanted to compare a pure lin- guistic task with a pure nonlinguistic task, the response modality is different in the two conditions: Whereas language switching is generally examined using verbal responses, button presses were used to respond in the task-switching condition. This could explain why switch- specific activation in precentral and postcentral gyri were only observed in language switching. These areas have been related to articulatory processing (Hillis et al., 2004) and are assumed to reflect the retrieval of stored phonological representations in overt naming (Murtha, Chertkow, Beauregard, & Evans, 1999). All these pro- cesses are not involved in the nonlinguistic switching condition. By contrast, the superior frontal gyrus and superior frontal sulcus, areas corresponding to the dorsal pre- motor cortex (Mayka, Corcos, Leurgans, & Vaillancourt, 2006), were only observed in task switching. The dorsal premotor cortex integrates multiple sets of information on actions and integrates them to perform an intended action (Hoshi & Tanji, 2007; O’Shea, Johansen-Berg, Trief, Göbel, & Rushworth, 2007; Serrien, Ivry, & Swinnen, 2007). As such, the dorsal premotor cortex executes the specific arbitrary association between a stimulus and a response in task switching (Badre & D’Esposito, 2009). Whereas the association between a stimulus and the button response in task switching is indeed totally arbi- trary, this is less so for the association between a picture and its name. This could explain why these areas were not observed in language switching. Alternatively, the observation of switch-specific activation in dorsal premotor cortex only in task switching could be explained by dif- ferent switching demands in the language-switching and task-switching conditions. In a recent meta-analysis, Kim, Cilles, Johnson, and Gold (2012) showed that the dorsal premotor cortex is mainly involved in perceptual switching and does not contribute to switching between response mappings. Perceptual switching refers to switching atten- tion between perceptual features of a stimulus. This is exactly what our participants needed to do in the task- switching condition: They needed to switch their attention between perceptual features of the stimulus, namely the direction of motion of the moving noise, the color of the pixels and the gender of the face. This switching between perceptual stimulus features was not involved in language switching. Here, they needed to select and switch between different responses associated with the same stimulus. The network of areas common to language switching and task switching observed here comprise all areas pro- posed by Abutalebi and Green (2007), except for the caudate nucleus. The role of the caudate in language switching remains puzzling as some studies report its activation (e.g., Abutalebi et al., 2008, 2013; Garbin et al., 2011; Wang et al., 2007; Crinion et al., 2006; for a meta-analysis, see Luk, Green, Abutalebi, & Grady, 2012) whereas others do not (Hernandez, 2009; Wang et al., 2009; Hernandez et al., 2001). One possible interpreta- tion for the absence of the caudate in the current study is that it is a consequence of the use of three different languages and the associated distribution of switch and repeat trials in the different languages. In a recent study, Ma et al. (2014) found the caudate when contrasting the switch condition with a simple naming condition in L1. However, the caudate was not observed when comparing the switch condition with a simple naming condition in L2. Ma et al. (2014) concluded that the caudate is involved in conditions that require much inhibition, hence in lan- guage switching and during the L2 naming condition, when inhibition of L1 is necessary. Consequently, the caudate should also be involved during L3 naming. Therefore, in the current study, the caudate might be involved in all switching conditions and in L2 and L3 repeat conditions. If the caudate is not activated in only one condition (i.e., the L1 repeat condition) out of six con- ditions in total, the contrast between switch and repeat conditions across languages might not be sensitive enough to capture this activation. Note that some previous studies presented the language cue simultaneously with the stimulus (e.g., Abutalebi et al., 2008, 2013; Garbin et al., 2011; Guo et al., 2011) whereas others, including this study, pre- sented the cue slightly before the stimulus (200–400 msec; e.g., Ma et al., 2014; Hernandez, 2009; Wang et al., 2007, 2009; Hernandez et al., 2000, 2001). We think that both approaches have advantages and disadvantages. The advantage of the simultaneous presentation of cue and target is to exclude task preparation and therefore amplifies switch costs. The disadvantage is that visual pro- cessing of the cue and cue–task translation takes place while the target is already presented. This can be ruled out by using a small cue–target interval (CTI) that warrants that participants can process the cue before the target appears. A CTI of 300 msec does not leave much room for advance preparation because this time period is pre- sumably necessary to visually process the cue and translate it into a task instruction. In any case, although manipula- tions of the CTI have substantial effects on performance, the influence on neural activity is restricted. Brass and von Cramon (2002), for example, showed that brain activity as measured with fMRI does not differ substantially for short and long CTIs. The reason is that participants need 1762 Journal of Cognitive Neuroscience Volume 27, Number 9 D o w n l o a d e d f r o m l l / / / / j f / t t i t . : / / h t t p : / D / o m w i n t o p a r d c e . d s f i r o l m v e h r c p h a d i i r r e . c c t . o m m / j e d o u c n o / c a n r a t r i t i c c l e e - p - d p d 2 f 7 / 9 2 7 1 / 7 9 5 / 2 1 1 7 9 5 4 2 9 / 8 1 1 7 0 8 o 3 c 5 n 5 _ 3 a / _ j 0 o 0 c 8 n 1 7 _ a p _ d 0 0 b 8 y 1 g 7 u . e p s t d o f n b 0 y 8 S M e I p T e m L i b b e r r a 2 r 0 2 i 3 e s / j . / t f u s e r o n 1 7 M a y 2 0 2 1 to establish the task-set regardless of the CTI. Because the BOLD response is not sensitive to small timing varia- tions, delays in the preparation process of a few hundred milliseconds do not show up in the BOLD response. Therefore, we are convinced that this precuing has not markedly affected our results and does not hinder a direct comparison of the current results with previously reported findings of studies where no precuing has been used. To conclude, the current findings provide direct evi- dence that in early, highly proficient bilinguals, highly similar brain circuits are involved in language control and domain-general cognitive control. Importantly, we have shown a more extensive overlap of regions for the two tasks than previously shown, given the direct contrast of language switching and task switching in the same highly proficient individuals. Acknowledgments This research was made possible by the Research Foundation- Flanders (FWO-Vlaanderen; FWO10/ PDO/234 and FWO13/ PDOH1/234), of which the first author is a postdoctoral research fellow, and further supported by the Special Research Fund (BOF) of Ghent University (BOF06/24JZAP and BOF08/GOA/ 011), from grant PSI2012-31448 from the Spanish Ministry of Sci- ence and Innovation and from grant ERC-2011-ADG-295362 from the European Research Council. Reprint requests should be sent to Wouter De Baene, Department of Experimental Psychology, Ghent University, Henri Dunantlaan 2, Ghent, B-9000, Belgium, or via e-mail: Wouter.DeBaene@ ugent.be. REFERENCES Abutalebi, J., Annoni, J. M., Zimine, I., Pegna, A. J., Seghier, M. L., Lee-Jahnke, H., et al. (2008). Language control and lexical competition in bilinguals: An event-related fMRI study. Cerebral Cortex, 18, 1496–1505. Abutalebi, J., Della Rosa, P. A., Ding, G., Weekes, B., Costa, A., & Green, D. W. (2013). 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