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Bilingualism: Language and Cognition 13 (2), 2010, 253–262 C
Cambridge University Press 2009 doi:10.1017/S1366728909990526 253
A bilingual advantage in task
switching∗
ANAT PRIOR
Edmond J. Safra Brain Research Center for the Study of
Learning Disabilities, University of Haifa
BRIAN MACWHINNEY
Department of Psychology, Carnegie Mellon University
(Received: December 3, 2008; Revised: May 19, 2009; Accepted: June 1, 2009; First published online 17 December 2009)
This study investigated the possibility that lifelong bilingualism may lead to enhanced efficiency in the ability to shift between
mental sets. We compared the performance of monolingual and fluent bilingual college students in a task-switching paradigm.
Bilinguals incurred reduced switching costs in the task-switching paradigm when compared with monolinguals, suggesting
that lifelong experience in switching between languages may contribute to increased efficiency in the ability to shift flexibly
between mental sets. On the other hand, bilinguals did not differ from monolinguals in the differential cost of performing
mixed-task as opposed to single-task blocks. Together, these results indicate that bilingual advantages in executive function
most likely extend beyond inhibition of competing responses, and encompass flexible mental shifting as well.
Most people in the world today use more than one
language in the course of daily life, and the acquisition
and dynamic interaction of multiple languages are being
intensely studied within the domain of psycholinguistics
(Kroll and De Groot, 2005). Alongside this work, there is
growing interest in the possibility that bilingualism might
exert its influence beyond the language system, and have
implications for cognition more generally (for a recent
review, see Bialystok, 2009). Evidence for extralinguistic
differences in the cognitive function of monolinguals and
bilinguals can illuminate the degree to which language
production and comprehension rely on domain-general
cognitive skills (O’Grady, 2005). Specifically, the current
paper focuses on the possibility that lifelong bilingualism
can produce basic changes in executive control.
Recent studies of young children have provided
evidence for robust bilingual advantages in the
development of executive control (Bialystok and Martin,
2004; Bialystok and Shapero, 2005; Carlson and
Meltzoff, 2008; Martin-Rhee and Bialystok, 2008).
There is also evidence that bilingualism can protect
against the age-related decline of executive function in
older adults (Bialystok, Craik, Klein and Viswanathan,
2004; Bialystok, Craik and Ryan, 2006; Bialystok,
Craik and Luk, 2008). However, the findings regarding
young college-age populations have been mixed, with
some studies showing bilingual advantages and others
documenting comparable performance for bilinguals and
monolinguals (Bialystok et al., 2008; Bialystok, Martin
* The authors thank Anna Guitchounts for impeccable data collection
and coding, Giora Unger for programming assistance, Nick Yeung and
Hagit Magen for helpful discussions, and Tamar Degani, Dave Plaut,
Ellen Bialystok, Albert Costa, Addie Johnson and Andrea Philipp for
comments on a previous version of the manuscript. AP was funded
by post-doctoral NRSA F32HD049255.
Address for Correspondence:
Anat Prior, Edmond J. Safra Brain Research Center for the Study of Learning Disabilities, Faculty of Education, University of Haifa, Israel
aprior@construct.haifa.ac.il
and Viswanathan, 2005; Costa, Hern´
andez and Sebasti´
an-
Gall´
es, 2008; Colzato et al., 2008). One explanation
offered is that this age group is at peak performance
in terms of its ability to exercise executive control, and
therefore ceiling effects might impede the detection of
group differences (Bialystok, 2006; Costa et al., 2008).
The bilingual advantage in executive control is
assumed to stem from bilinguals’ constant need to manage
and monitor their two languages. There is abundant
evidence that, perhaps counter-intuitively, both languages
of bilingual speakers are constantly active (van Heuven,
Schriefers, Dijkstra and Hagoort, 2008). Thus, it seems
that the intention to speak in one language is not sufficient
to suppress all activation of the other language (for a recent
review see Costa, 2005; and for a different perspective
see La Heij, 2005). This might be especially true in non-
balanced bilinguals speaking in the second language (L2;
Kroll, Bobb and Wodniecka, 2006), but is not limited
to this population. Similarly, lexical candidates become
activated in both languages, even in a monolingual setting,
for both auditory (Spivey and Marian, 1999) and visual
word recognition (for a recent review see Dijkstra, 2005).
The need for executive control is arguably greater in the
case of language production, as it calls for managing active
competition.
Recent research has demonstrated, however, that
executive control is not a unitary construct, and can
be decomposed into several functions. Miyake et al.
(2000) identify three separate, but correlated, executive
functions: updating of working memory, inhibition of
distractors or responses, and shifting between mental
sets (see also Friedman, Miyake, Corley, Young, DeFries
and Hewitt, 2006). The tasks used to date to explore
the impact of bilingualism on executive functions –
including the Simon, anti-saccade, stop-signal and flanker
254 A. Prior and B. MacWhinney
tasks – fall mostly into the category of inhibition
(for further distinctions regarding types of inhibition,
see Friedman and Miyake, 2004), rather than controlled
shifting of mental sets. However, during language
production, bilingualism places particularly high demands
on shifting abilities, as speakers have to decide, at
least in certain circumstances, when and how to switch
back and forth between their two languages. Thus, it is
important to measure the possible effects of bilingualism
on experimental paradigms that require executive shifting.
The current study set out to investigate the possibility
that lifelong bilingualism could lead to advantages in the
ability to shift efficiently between mental sets.
Two studies conducted with children provide
supporting evidence for bilingual advantages in the ability
to shift mental set. Bialystok and Martin (2004; see also
Martin-Rhee and Bialystok, 2008) found that bilingual
preschoolers successfully performed the dimensional
change card sort task (DCCS; Zelazo, Resnick and Pinon,
1995) at an earlier age than their monolingual peers.
This task requires children to shift from sorting based
on one dimension (color) to sorting based on a second
dimension (shape), through activation of the new criterion
and inhibition of the previous sorting principle. Along the
same lines, Bialystok and Shapero (2005) demonstrated
an advantage in bilingual children’s ability to identify
alternative images in reversible figures when compared
with monolinguals. Further, performance on the reversible
figure task was correlated with performance on the
DCCS task, suggesting that both rely on similar control
mechanisms. Both of these experimental tasks rely, to
some extent, on the inhibition of perceptual interference.
However, both tasks also require subjects to shift between
mental sets or tasks.
One highly relevant study (Bialystok, Craik and
Ruocco, 2006) examined a similar issue with older
and younger adults, using a dual-task paradigm. The
results showed a bilingual advantage in performing the
classification of visual images during concurrent classifi-
cation of auditory information. There were two possible
classification schemes – stimuli were classified as letters
or numbers in one scheme and as animals or instruments in
the other. The concurrent visual and auditory tasks relied
on the same classification scheme in some experimental
conditions, and in other cases a different classification
scheme was assigned to each modality. The results
demonstrate a bilingual advantage only in the visual
classification of numbers and letters, which was the easier
of the two tasks. Further, for this task, the advantage
was stable both when the auditory task used the same
classification scheme and when it required classifying
stimuli as animals or instruments. The authors concluded
that the bilingual advantage stemmed from enhanced
bilingual inhibitory control, and not from the ability to
switch between tasks. The dual-task paradigm used in this
study emphasized a comparison between dual-task and
single-task performance, but did not measure the actual
cost of switching between tasks, as opposed to the overall
cost of monitoring two incoming streams of information
and coordinating the simultaneous performance.
In the current study, we revisit this issue by examining
college-aged bilinguals’ ability to switch between tasks,
using a measure that allows a direct comparison of local
switching costs with general mixing, or monitoring, costs.
To this end, the stimuli used in the current task-switching
paradigm are “bivalent”, in the sense that they afford two
competing responses. Although the task to be executed
is cued on every trial, efficient performance requires
voluntary internal switching of task-set configurations.
This situation is reminiscent of the conditions faced by
bilinguals when they are required to name a picture or an
object. In such cases there are typically two competing
articulatory responses, which need to be resolved by
control mechanisms for selecting the appropriate language
(Green, 1998). In the task-switching paradigm, the task
schema can be compared to the language selection, and
competition needs to be resolved before an accurate
response can be produced. The demands of language
switching in bilingual speakers have many parallels with
task switching, and both paradigms rely on the executive
function of mental shifting (Miyake, Friedman, Emerson,
Witzki, Howerter and Wager, 2000).
Language-switching costs are cited as evidence for
the continuous activation of both languages in bilingual
speakers, and the need to inhibit one language in order
to allow output in the other (Meuter and Allport, 1999).
Meuter and colleagues have demonstrated that, on a
given trial, changing the language of response from
the previous trial results in a slowed reaction, when
compared with reaction times for trials in which there
is no language change (Jackson, Swainson, Cunnington
and Jackson, 2001; see Meuter, 2005, for a review).
The interpretation given to these results is that switching
between languages necessitates establishing the new
language set and overcoming the language set inertia of
the language used on the previous trial. These processes
are very similar to the ones described in the general task-
switching literature (Meiran, Chorev and Sapir, 2000;
though see, e.g., Bryck and Mayr, 2008, for an alternative
account of switching costs).
Another similarity that can be drawn between the task-
switching and language-switching domains involves the
phenomenon of switching cost asymmetries. Specifically,
switching from an easier (or dominant) to a more
difficult task often results in smaller switching costs
than switching from a difficult task to an easier one
(Allport, Styles and Hsieh, 1994; Allport and Wylie, 1999,
2000; Rubinstein, Meyer and Evans, 2001; see Yeung and
Monsell, 2003; and Monsell, Yeung and Azuma, 2000, for
specific conditions that lead to switching asymmetries).
Bilingual task switching 255
In bilingual language-switching experiments, switching
into the stronger, more proficient first language (L1)
incurs a greater switching cost, a finding that might seem
paradoxical at first glance, since overall performance in
L1 is generally faster and more efficient (Meuter and
Allport, 1999). According to the Inhibitory Control model
of bilingual performance (Green, 1998), language task
schemas control the linguistic output of bilinguals. These
schemas are similar to the action schemas described by
Norman and Shallice (1986; Shallice and Burgess, 1996)
for controlling behavior in general. The language task
schemas either inhibit or activate the lemma nodes in the
lexicon, which are tagged for language, in order to allow
production in the desired language. Thus, naming a picture
in L2 requires inhibiting the competing response in L1, as
well as the task goal of speaking in L1, and unbalanced
bilinguals must rely on strong inhibition of L1 in order to
allow for production in the L2. When switching from a trial
in which the L2 is used, and the L1 is inhibited, to a trial
in which the L1 language schema is called upon, a large
degree of inhibition must be overcome. Conversely, when
producing in a highly dominant L1, unbalanced bilinguals
need to inhibit L2 to a lesser degree, and therefore
switching into producing in L2 on a consequent trial
has a lower cost. Further support for this analysis comes
from the fact that balanced bilinguals do not show the
language-switching cost asymmetry between L1 and L2
(Costa and Santesteban, 2004; but see Costa, Santesteban
and Ivanova, 2006, for an interpretation of these findings
that does not rely on inhibitory control mechanisms).
Finally, there is also evidence that similar brain regions
may support language switching and task switching.
Several studies (Hernandez, Martinez and Kohnert, 2000;
Hernandez, Dapretto, Mazziotta and Bookheimer, 2001;
Wang, Xue, Chen, Xue and Dong, 2007) have found
increased activation in dorsolateral prefrontal cortex,
when comparing mixed-language with single-language
blocks of naming. The involvement of prefrontal areas
has also been identified in imaging studies of task
switching, though activation correlating with different
components of control during shifting attention has
spanned lateral as well as medial prefrontal areas,
with recent research focusing on the specific role of
anterior cingulate areas in monitoring conflict and guiding
control (Botvinick, Braver, Yeung, Ullsperger, Carter and
Cohen, 2004; Dove, Pollmann, Schubert, Wiggins and
von Cramon, 2000; Wager, Jonides, Smith and Nichols,
2005; Wager, Jonides and Smith, 2006). Further, a direct
comparison of between-language switching and within-
language register switching in a bilingual population
demonstrated significant similarity in the spatio-temporal
ERP signatures of the two processes, suggesting that
they rely on partially shared neural substrates (Khateb,
Abutalebi, Michel, Pegna, Lee-Jahnke and Annoni, 2007).
Along similar lines, Rodriguez-Fornells, van der Lugt,
Rotte, Britti, Heinze and Munte (2005) found evidence
that bilinguals recruit brain areas not identified as
language specific, i.e., the middle prefrontal cortex, for
the purpose of controlling interference from the non-
intended language. Finally, in a review of the literature,
Abutalebi and Green (2007) argue convincingly for shared
neural representations for the two languages of bilinguals,
and more importantly in the present context, for the
recruitment of general cognitive control mechanisms for
the selection, inhibition and production of one language
by bilinguals.
In light of these parallels, higher efficiency of
bilinguals in task switching, when compared with
monolinguals, would lend support to the idea that
bilingual advantages in executive control extend
beyond inhibitory control, as demonstrated in previous
research. Further, because task-switching paradigms are
notoriously difficult and incur large costs even for young
high-performing participants (for a review, see Monsell,
2003), there is a reduced risk of encountering ceiling
effects and a better chance of demonstrating group
differences in performance.
Task-switching paradigms normally include two types
of experimental blocks – single-task blocks, and mixed-
task blocks. From this basic setup, two measures of
executive control can be computed. Switching costs (also
called specific or local switching costs) are defined as
the difference in response time between switch and non-
switch trials in the mixed-task blocks, and are thought
to reflect the difficulty in switching from one task
set to another. Mixing costs (also called general or
global switching costs) are defined as the difference in
performance between single-task blocks and non-switch
trials in the mixed-task blocks. Mixing costs may reflect
the activation of global sustained control mechanisms
necessary for maintaining two competing task/response
sets, for monitoring the task cued or for a process of task
decision on each trial (Braver, Reynolds and Donaldson,
2003; Koch, Prinz and Allport, 2005; Rubin and Meiran,
2005). Conversely, switching costs have been described as
arising from more transient control processes necessary
for selecting the appropriate task, such as goal updating, or
linking task cues with the appropriate response mappings,
retrieved from long-term memory (Braver et al., 2003;
Mayr and Kliegl, 2000, 2003). It has also been suggested
(Philipp, Kalinich, Koch and Schubotz, 2008) that while
mixing costs reflect the need to resolve interference caused
by the target on each and every trial, switching costs are
additionally driven by proactive interference caused by
the previous trial.
Task-switching paradigms can be implemented in
a variety of ways: switches can be predictable or
unpredictable, the time interval for preparing the task
switch (cue–target SOA) can vary, the type of stimuli
used can be bivalent or univalent, and the response
256 A. Prior and B. MacWhinney
mappings can also be bivalent or univalent. The specific
implementation we chose is modeled on that described by
Rubin and Meiran (2005). Specifically, from the various
configurations described in that paper, we chose the
conditions that would allow for both mixing costs and
switching costs to emerge. We did not, however, include
conditions that are aimed at investigating the influences of
working memory load on task mixing and switching, for
two reasons. First, the current study included a separate
measure of working memory performance, to ensure that
the two participant groups would be matched in this
capacity. Second, the effect of bilingualism on executive
function has not been ascribed to working memory
advantages, and we did not wish to complicate the present
design with additional factors.
The two tasks used in the current study were shape
decision and color decision. To maximize mixing cost
we used bivalent stimuli (red and green circles and
triangles) that have dual affordances and thus lead to
the bottom-up activation of both task sets on each trial
in the mixed-task blocks (Rubin and Meiran, 2005).
Our decision to use cued task switching, rather than an
alternating runs paradigm, was motivated both by findings
that increased task uncertainty, which is 50% in our case,
leads to increased mixing costs (Meiran, Hommel, Bibi
and Lev, 2002), and by our desire to keep working memory
load to a minimum. For the same reason, we chose to
use non-overlapping response mappings, such that each
task was mapped to one hand. A cued task-switching
paradigm also allows the experimenter to easily control
the duration of task preparation. Because long preparation
times have been shown to dramatically reduce switching
costs (Meiran, 1996; Meiran et al., 2000; Rogers and
Monsell, 1995) we chose a short cue–target interval of
250 ms to allow for robust switching costs.
Our predictions regarding the outcomes of the task-
switching paradigm were as follows. We expected to
find significant mixing costs and switching costs for both
participant groups, and no difference was expected in the
basic reaction times of the two groups in the single-task
blocks. A bilingual advantage could take several forms,
each one hinting at different underlying mechanisms.
A reduced mixing cost for bilinguals as compared to
monolinguals would link the bilingual advantage to more
global control processes and the ability to resist distractor
interference. Alternatively, a reduced switching cost for
bilinguals would point towards the locus of the bilingual
advantage as lying in more transient executive control
mechanisms (Miyake et al., 2000), such as time-sensitive
goal updating or resistance to proactive interference.
Finally, the monolingual and bilingual participants also
completed several additional tasks, including a test of
receptive vocabulary in English, a measure of working
memory and a language history questionnaire, including
information on SAT scores. These additional data were
collected to ensure that the two groups were matched on
various cognitive domains, so that any differences found
could be attributed to the different language experience.
Method
Participants
Forty-five monolingual (32 female) and 47 bilingual (27
female) students enrolled in introductory psychology
courses at Carnegie Mellon University participated in the
study, for course credit or payment. One self-described
monolingual was excluded because of early exposure to
another language in the home. Two bilingual participants
were eliminated because they had ceased using one of their
languages completely. Data from one additional bilingual
participant was discarded due to equipment failures,
resulting in 44 participants in each experimental group.
Bilingual participants had learned English and another
language before the age of six, and used both languages
continuously ever since. Besides English, the bilingual
participants spoke a variety of other languages, including
Mandarin (13), Korean (11), Spanish (4), Russian (3),
Cantonese (3) and one speaker each of Japanese, Hebrew,
Italian, Bengali, Malay, Bosnian, Marathi, Hindi, French
and Greek. Monolingual participants were native English
speakers, and had not studied or been exposed to any
other language before the age of twelve, though some had
limited proficiency in a second language at the time of
testing.
The background variables of both groups are detailed
in Table 1. The mean ages for the two language groups
were 18.7 years (SD =.9) for the monolinguals and 19.5
years (SD =1.5) for the bilinguals. Overall self-reported
SAT scores were taken as a measure of general cognitive
ability, and there was no significant difference between
monolinguals and bilinguals. We further administered
the operation-span task, a measure of working memory
capacity. There was no difference between the groups in
their performance on either the verbal or the mathematical
components of the task.
Two variables were used to tap the verbal ability of
the participants: the verbal component of the SAT and the
Peabody Picture Vocabulary Test (PPVT-IIIL; Dunn and
Dunn, 1997, a test of receptive vocabulary in English).
Although there was no significant difference between the
groups in the verbal portion of the SAT, the monolinguals
did outperform the bilinguals on the PPVT-III [t(86) =
3.23, p<.001)]. Because previous findings have
demonstrated relative deficiencies for bilinguals, when
compared with monolinguals, on language tasks (e.g.,
Bialystok et al., 2008), this finding is not surprising.
Indeed, an attempt to create groups matched on vocabulary
performance might have resulted in selective inclusion of
bilinguals of higher ability, relative to the distribution of
bilinguals, than monolinguals. Further, the task-switching
Bilingual task switching 257
Tabl e 1 . Monolingual and bilingual participant
characteristics, mean (SEM).
Monolinguals Bilinguals
N4444
Age∗18.7(.14) 19.5(.23)
SAT general (self-report) 1356 (19.5) 1378 (14.1)
SAT verbal (self-report) 682 (12.4) 666 (11.7)
Ospan word (accuracy,
max =60)
55.82 (.58) 56.22 (.49)
Ospan math (accuracy,
max =60)
54.98 (.64) 56.38 (.54)
PPVT∗∗ 109.95 (1.5) 102.30 (1.8)
English proficiency
(self-rating)
9.3(.15) 9.3(.11)
Other language
proficiency∗∗
(self-rating)
3.1(.34) 7.8(.25)
Percent of time English
used daily∗∗
97% (.01) 73% (.02)
Self-ratings are on a scale from 1 (not at all) to 10
(perfect command) and are averaged across oral and written
comprehension and expression.
∗Groups significantly different, p<.05.
∗∗Groups significantly different, p<.001.
paradigm performed in this experiment did not rely
on verbal skills and indeed any finding of bilingual
advantages would be operating in the face of their
somewhat lower verbal performance in English.
Design and procedure
All participants completed the following tasks in a
single experimental session that lasted approximately 90
minutes.1The tasks were presented in the same order to
all participants.
Language history questionnaire. Participants com-
pleted questions regarding their language skills,
proficiency, age of acquisition, immersion experience,
daily use patterns and SAT scores (see Table 1 for
participant characteristics).
Peabody Picture Vocabulary Test, PPVT-III.A
receptive vocabulary test, in which the experimenter
names a word in English, and the participant has to
select the appropriate picture among an array of four
possibilities. The test was administered to each participant
individually by the experimenter. Raw scores were then
standardized according to the participants’ age.
1Participants also completed a Color Flanker task and a Simon task,
the results of which are not reported in this paper. There were no
significant differences between the language groups on either task.
All computerized tasks were presented on a Sony Vaio
desktop computer, with a 15-inch screen. Experimental
scripts and data collection were managed by E-prime
using a Serial Response Box (both by Psychological
Software Tools Inc, Pittsburgh, PA), to assure accurate
reaction time measurement. Participants were seated
approximately 60 cm from the monitor.
Task switching paradigm. The procedure was adapted
from Rubin and Meiran (2005). Each trial started with
a fixation cross presented for 350 ms, followed by a
150 ms blank screen. The task cue then appeared on the
screen for 250 ms, 2.8◦above the fixation cross. To avoid
using linguistic information, which might interact with
the participants’ language experience, we decided to use
graphic task cues. Thus, the cue for the color task was a
color gradient and the cue for the shape task was a row
of small black shapes (4.5◦×0.8◦). The cue remained
on the screen, and the target appeared in the center of the
screen. Targets were red or green circles (2.8◦×2.8◦) and
triangles (2.3◦×2.3◦). The cue and target remained on the
screen until the participant responded, or for a maximum
duration of 4 seconds. Incorrect responses were followed
by a 100 ms beep. An 850 ms inter-trial blank screen
interval was presented before the onset of the following
trial.
Participants were instructed to perform one task (either
shape or color, counterbalanced across participants) using
the right hand, and the other task using the left hand.
In each case, the “red” response was assigned to the
index finger, and the “green” response was assigned to
the middle finger. Similarly, the “circle” response was
assigned to the index finger and the “triangle” response
was assigned to the middle finger. This mapping of task to
hand was preserved throughout the single-task and mixed-
task blocks. The response keys for the color task were
labeled with the appropriate colors, and the response keys
for the shape task were labeled with the appropriate shape,
in black.
Participants completed three parts of the experiment,
comprising a sandwich design. In the first part, they
performed two single-task blocks (color and shape, order
counterbalanced across participants), each including 8
practice trials followed by 36 experimental trials. In
the second part, participants performed 16 mixed-task
practice trials, followed by 3 mixed-task blocks. Each
mixed-task block included 48 trials, half of which were
switch trials and half of which were non-switch trials, of
both the color and shape tasks, randomly ordered with
a maximum of 4 consecutive trials of the same type.
Two additional dummy trials were added at the beginning
of each block and were not included in the analysis.
Finally, in the third part of the experiment, participants
again performed two single-task blocks, presented in
the opposite order from that used in the first part. The
sandwich design enables a comparison of 72 switch trials,
258 A. Prior and B. MacWhinney
72 non-switch trials, and 144 single-task trials (72 color
and 72 shape).
Operation span task: This working memory task
allowed us to compare monolingual and bilingual
participants’ performance. The procedure was adapted
from the Turner and Engle (1989) operations–word
task. Participants solved mathematical expressions, while
maintaining sets of English words in memory. In each trial,
a fixation cross appeared in the middle of the screen for
1000 ms, followed by a single mathematical expression,
which remained on the screen for 2500 ms, and was
replaced by a question mark appearing for 1250 ms. While
the question mark remained on the screen, participants
had to push a button indicating whether the mathematical
expression was correct or incorrect. Upon response, or
time-out, the question mark was replaced with a word
appearing for 1250 ms. Participants had to retain the words
in memory until the end of the set, when a recall prompt
appeared on the screen. At that point, participants wrote
down in a booklet as many words as they recalled from
that set, and pressed a button to initiate the following
set. Sets ranged in size from two to six operation–word
pairs per set, and were presented in ascending order, with
three sets of each size, for a total of fifteen sets. Each
set included approximately equal numbers of correct and
incorrect mathematical expressions. Before completing
the experimental sets, participants performed two practice
sets (one with four items and one with six items).
Participants were encouraged to solve the math
problems as quickly and accurately as possible, while
remembering all the words from a given set. Participants
received two scores for their performance on this task:
a verbal score, namely the number of correctly recalled
words (see Conway, Kane, Bunting, Hambrick, Wilhelm
and Engle, 2005, for considerations of scoring working
memory span), and a mathematical score, namely the
number of correctly classified mathematical expressions.
Results
The results for both groups in the task switching paradigm
are presented in Table 2.
Switching costs
Switching costs are defined as the difference in
performance on Switch trials as opposed to Non-Switch
trials, within the mixed-task blocks. Switching costs
in accuracy and RT were analyzed using a two-way
repeated measures ANOVA, with language group as a
between-participant factor (monolingual, bilingual) and
trial type as a within-participant factor (switch trials, non-
switch trials). The main effect of trial type was highly
significant for both accuracy and RT [F(1,86) =34.9,
MSE =.11, p<.001; F(1,86) =189.2, MSE =1,356,263,
p<.001, respectively], because non-switch trials received
faster and more accurate responses than switch trials.
The main effect of language group was not significant
in either analysis [F(1,86) =1.1, MSE =.03, p=.29;
F<1; for accuracy and RT, respectively). However, the
interaction between trial type and language group was
significant in the RT [F(1,86) =6.0, MSE =42,950,
p<.05] but not the accuracy [F(1,86) =1.1, MSE =
.003, p=.33] analysis. As can be seen in Table 2, this
interaction is driven by the fact that both language groups
performed identically on non-switch trials, but bilinguals
were much faster than monolinguals on the switch trials.
Thus, bilinguals incurred a much lower switching cost
than monolinguals. An additional analysis was carried out
in which the switching cost was calculated individually for
each participant, by subtracting their mean RT for non-
switch trials from the mean RT for switch trails. When
switching cost was compared across the two groups, the
bilinguals again incurred smaller switching costs (M=
144 ms, SE =16) than the monolinguals (M=206 ms,
SE =20), [t(86) =2.45, p<.05].
Finally, the bilinguals in the current sample used
their non-English language on average only 27% of the
time. Thus, they were less balanced in their patterns of
daily language use than bilingual participants in previous
studies, who approximated 50% usage of each language
(Bialystok et al., 2008; Costa et al., 2008). Further,
participants who used English for a larger percentage of
the time also tended to have higher scores on the PPVT-
III score, the English vocabulary measure, though the
correlation was only marginally significant (r=0.25,
p=.09). To explore whether the percentage of use
might be related to the magnitude of the switching cost,
we examined whether the two variables were correlated
within the sample of our bilingual participants. However,
we found no reliable relation between the percentage
of the time the non-English language was used and
the magnitude of the switching cost (r=.01, p>.9).
Therefore, it seems that our findings hold across the range
of proficiency and the degree of balance in language use
that was represented in our sample (from 50% to 90%).
Mixing costs
Mixing costs were defined as the difference between the
performance in the single-task blocks and the performance
on non-switch trials of each task in the mixed-task blocks.
As there was no significant difference between the color
and shape tasks (F<1), results are collapsed across the
two tasks. Thus, mixing effects, for RT and accuracy, were
analyzed using a two-way repeated measures ANOVA,
with language group as a between-participant factor
(monolingual, bilingual) and trial type as a within-
participant factor (Single task trials, Non-Switch trials).
The main effect of trial type was significant for both
RT and Accuracy [F(1,86) =251.5, MSE =2251273,
p<.001; F(1,86) =8.4, MSE =.013, p<.01,
Bilingual task switching 259
Tabl e 2 . Mean reaction time in milliseconds (SEM) and % correct for single task,
non-switch and switch trials, by language group.
Mixed-task blocks
Single-task blocks Non-switch Switch
Bilingual RT 437.97 (11.2) 670.16 (28.7) 814.16 (33.2)
% correct 95.994.291.8
Monolingual RT 448.8(11.8) 669.05 (26.7) 875.54 (39.2)
% correct 97.896.192.2
respectively), because trials in the single-task blocks
were performed more quickly and accurately than non-
switch trials in the mixed-task blocks. However, there
was no significant difference between the groups, and no
interaction (all Fs<1). In addition, we calculated a mixing
cost for each participant, by subtracting performance on
single-task trials from that on non-switch trials in mixed-
task blocks. Again, we found no significant differences in
the mixing costs of the two groups [bilinguals M=304 ms,
SE =23; monolinguals M=323 ms, SE =23, t(86) =
.57, p>.5].
This pattern demonstrates that both groups exhibited
significant mixing costs, but there was no difference in
the magnitude of the mixing costs between the groups.
Thus, despite bilinguals having reduced switching costs,
both groups were equally susceptible to the cognitive load
imposed by the mixed-block trials.
Discussion
The present study investigated possible bilingual
advantages in shifting between mental sets, by using
a non-linguistic task-switching paradigm, and found
a pronounced bilingual reduction in switching costs.
Specifically, both participant groups performed similarly
in single-task blocks and on the non-switch trials within
mixed-task blocks, but bilinguals were significantly faster
to correctly perform the new task on switch trials. Thus,
bilinguals displayed greater facility at activating a task set
in response to a cue, and took less time to overcome any
residual interference or activation from the task performed
on the previous trial (Meiran et al., 2000; Philipp et al.,
2008).
Enhanced bilingual executive function has been
ascribed to the constant need to select the appropriate
language, a process which involves achieving a
coordinated and resonant activation of the interrelated
features of the chosen language (MacWhinney, 2005).
Secondarily, it also involves the rejection of competition
and interference from the other language. The present
study demonstrated that lifelong practice with language
switching can lead to specific bilingual advantages, by
using a task-switching paradigm that measures switching
per se, and directly targets the executive function of
shifting (Miyake et al., 2000). The reduced bilingual
switching cost lends support to accounts assigning the
bilingual advantage to the successful navigation of two
active language systems (Bialystok et al., 2004; Costa
et al., 2008; Green, 1998).
The specific pattern of results found in the task-
switching paradigm can contribute to a detailed under-
standing of bilingual executive advantage. Specifically,
the bilingual advantage was limited to reduced switching
costs, which arise from transient control processes for
selecting between competing tasks, such as activating
current task goals and reconfiguring stimulus–response
mappings. Conversely, no group difference was found in
mixing costs that have been related to more sustained
control mechanisms, and the ability to resolve concurrent
distractor interference (Braver et al., 2003; Philipp et al.,
2008).
Switching costs have also been described as reflecting
proactive interference (Philipp et al., 2008), and thus
the present results support enhanced bilingual efficiency
in resistance to proactive interference, a subtype of
inhibitory function (Miyake et al., 2000). This aligns with
previous claims in the literature (Bialystok, Craik and
Ryan, 2006; Costa et al., 2008), regarding a bilingual
advantage in inhibitory control. Further, there is a
moderate correlation between the shifting and inhibition
executive functions (Miyake et al., 2000), raising the
possibility that both might rely on a shared mechanism
such as controlled attention.
The results of the current study are clear and can
be interpreted directly by contrasting transient control
processes, time-sensitive shifting of mental sets and
resistance to proactive interference on the one hand,
with more sustained control processes and resistance
to distractor interference on the other hand (Friedman
and Miyake, 2004). Specifically, bilinguals in the current
study showed advantages in the former, but not the
latter, set of abilities. However, integrating the current
findings with the wider literature on bilingual advantages
is more difficult, largely because of the inconsistency with
260 A. Prior and B. MacWhinney
which these component processes have been measured.
In particular, several studies (Bialystok, Craik and Ryan,
2006; Bialystok et al. 2004; Bialystok, 2006; Bialystok
and Viswanathan, 2004; Costa et al., 2008) have pointed
to enhanced bilingual performance in experimental blocks
with changing stimulus characteristics, findings that have
been interpreted as reflecting a bilingual advantage in
ongoing monitoring, which would be expected to parallel
mixing costs in the present study. However, in all
these studies, the performance in experimental blocks,
conceptualized as similar to mixed blocks in the task-
switching paradigm, was not compared to an appropriately
controlled single-task block. Some experiments did not
include such blocks (Bialystok, 2006; Costa et al.,
2008) and others included control blocks that presented
different stimuli than those used in the experimental
blocks, specifically limited to non-conflict displays (e.g.
Bialystok, Craik and Ryan, 2006; Bialystok et al., 2004).
Bialystok and Viswanathan (2004) do report reduced
mixing costs for bilinguals, by comparing mixed blocks
with single-task blocks, but failed to find switching
costs for all participant groups, leading to a difficulty
in interpreting the results. Therefore, an account that
ascribes bilingual advantages in the experimental blocks
to reduced mixing costs cannot be preferred over accounts
relying on reduced switching costs, or perhaps still other
mechanisms.
Finally, Bialystok and colleagues (Bialystok et al.,
2004; Bialystok, Craik and Ruocco, 2006; Bialystok,
Craik and Ryan, 2006; Bialystok et al., 2008) have
described aspects of cognitive executive function that
deteriorate with aging, but are enhanced by bilingualism.
Thus, it is interesting to compare the current study with
the impact of aging on task-switching performance.2
Several studies report increased mixing cost with aging,
but no significant changes in switching cost (Kray
and Lindenberger, 2000; Mayr, 2001; Reimers and
Maylor, 2005). Further, Viswanathan and Bialystok
(2007) examined younger and older monolinguals and
bilinguals, and found reduced mixing costs for younger
participants and for bilinguals. These findings seem
incommensurate with the present patterns, which showed
reduced bilingual switching costs, but comparable mixing
costs across groups. However, age effects in mixing
costs seem to emerge only with alternating runs task-
switching paradigms (Kray and Lindenberger, 2000;
Reimers and Maylor, 2005), or when there is complete
overlap in the response sets of the two tasks (Mayr,
2001; Viswanathan and Bialystok, 2007). Interestingly, a
study by Kray, Li and Lindenberger (2002) implemented a
task-switching paradigm that included a high percentage
of unpredictable cued switches, similar to the current
experiment. Under these conditions, older individuals
2The authors wish to thank Ellen Bialystok for raising this issue.
incurred larger switching costs, but no age differences
were found in mixing costs. Thus, if the effects of
bilingualism on executive function are conceptualized as
mirroring those of ageing, only in the opposite direction,
the present results agree with previous findings using
comparable designs.
In conclusion, the present study compared the
performance of monolingual and lifelong bilingual young
adults in a task-switching paradigm. We demonstrated
a robust bilingual advantage in performance, suggesting
that lifelong bilingualism may lead to enhanced efficiency
in the executive function of shifting between mental
sets. Specifically, the reduced switching costs found for
bilinguals can be linked to the process of language
switching that calls on general mechanisms of shifting,
and utilizes overlapping neural resources. Further, we
suggest that the increased bilingual efficiency in shifting
might have contributed to some extent to previous findings
of bilingual advantages linked to inhibitory function,
especially in light of the correlation between these two
executive functions. Future work on this important topic
should investigate how the cognitive consequences of
lifelong bilingualism are expressed through variations in
executive function.
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