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ORIGINAL RESEARCH
published: 13 August 2019
doi: 10.3389/fpsyg.2019.01839
Edited by:
Michal Ben-Shachar,
Bar-Ilan University, Israel
Reviewed by:
Mathieu Declerck,
Aix-Marseille Université, France
Esli Struys,
Vrije Universiteit Brussel, Belgium
*Correspondence:
Ruiming Wang
wangrm@scnu.edu.cn
Specialty section:
This article was submitted to
Language Sciences,
a section of the journal
Frontiers in Psychology
Received: 06 March 2019
Accepted: 25 July 2019
Published: 13 August 2019
Citation:
Liu C, Yang C-L, Jiao L,
Schwieter JW, Sun X and Wang R
(2019) Training in Language Switching
Facilitates Bilinguals’ Monitoring
and Inhibitory Control.
Front. Psychol. 10:1839.
doi: 10.3389/fpsyg.2019.01839
Training in Language Switching
Facilitates Bilinguals’ Monitoring and
Inhibitory Control
Cong Liu1,2 , Chin-Lung Yang3, Lu Jiao2, John W. Schwieter4, Xun Sun1and
Ruiming Wang1*
1Guangdong Provincial Key Laboratory of Mental Health and Cognitive Science, Center for Studies of Psychological
Application, School of Psychology, South China Normal University, Guangzhou, China, 2Department of Psychology, Qingdao
University, Qingdao, China, 3Department of Linguistics and Modern Languages, Chinese University of Hong Kong,
Hong Kong, China, 4Language Acquisition, Multilingualism, and Cognition Laboratory, Wilfrid Laurier University, Waterloo,
ON, Canada
In the present study, we use a training design in two experiments to examine whether
bilingual language switching facilitates two components of cognitive control, namely
monitoring and inhibitory control. The results of Experiment 1 showed that training in
language switching reduced mixing costs and the anti-saccade effect among bilinguals.
In Experiment 2, the findings revealed a greater decrease of mixing costs and a smaller
decrease of the anti-saccade effect from pre- to post-training for the language switching
training group compared to the second language training group. Overall, the results
suggest that extensive exercise in monitoring and inhibitory control in an experimental
setting may enhance the corresponding components of cognitive control. We discuss
these findings in the context of the relationship between bilingual language control and
executive control.
Keywords: bilingualism, language switching training, cognitive control, monitoring, inhibitory control,
positive psychology
INTRODUCTION
Bilinguals constantly switch between the languages they speak in their multilingual societies,
according to the needs of the interactional contexts. Given that previous studies have indicated that
both languages are activated in parallel during bilingual speech production (Liu et al., 2019b; for a
review, see Declerck and Philipp, 2015), and that during language switching, when bilinguals speak
in the intended language, they utilize language control mechanisms to inhibit the interference from
the other language. The extent to which this bilingual language control (BLC) overlaps with control
processes implemented in non-linguistic processing has been debated for years (e.g., Declerck et al.,
2017;Segal et al., 2019; for a review, see Calabria et al., 2019).
Some behavioral correlational studies have shown a clear link between BLC and domain-general
executive control (EC) as revealed by a correlation between performances on the two control
tasks (Prior and Gollan, 2013;Declerck et al., 2017;Timmer et al., 2018), whereas others have not
(Calabria et al., 2015;Branzi et al., 2016). Subsequent neuroimaging studies further have revealed
the similarities between the underlying brain networks of BLC and EC (De Baene et al., 2015;
Weissberger et al., 2015), but only in a limited number of studies. More recently, some studies
started to investigate this relationship by assessing the effect of short language switching training
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Liu et al. Training in Language Switching
on task switching (Prior and Gollan, 2013;Timmer et al., 2019).
The evidence regarding cross-talk that comes from training
studies is based on the idea that if the two controls share cognitive
processes, then training in BLC during language switching would
transfer to EC. The findings from Timmer et al. suggested
that short-term language switching training indeed transfers
to the non-linguistic domain for certain sub-mechanisms (i.e.,
switch cost) but not for others (mixing cost). However, different
results were reported in Prior and Gollan’s study in which there
was no transfer effect from language switching training to EC
performance (neither for switch cost nor mixing cost). Thus, it
is still an open question as to whether BLC overlaps with EC.
The present study addresses this issue by examining the effects
of short-term language switching training on monitoring and
inhibitory control among Chinese (L1)-English (L2) bilinguals.
In the next section, we provide a background of some of the
work that has recently examined monitoring and inhibitory
control with regard to BLC and EC. We then describe the two
experiments in the present study including the participants,
design, procedures, and experimental tasks. Finally, we discuss
the findings, implications, and suggestions for future work.
BACKGROUND
Conflict Monitoring and Inhibitory
Control
Conflict monitoring (monitoring in short below; Jylkkä et al.,
2018;Struys et al., 2019) and inhibitory control (Babcock
and Vallesi, 2015;Declerck and Philipp, 2015) are two main
processing systems used in language switching (Hartanto and
Yang, 2019). Specifically, bilinguals monitor the conflict (i.e.,
cross-language interference) in the communicative environment
for changes that trigger a language switch, and then instigate the
language control process to inhibit cross-language interference.
Given that monitoring and inhibitory control are essential
to language switching, we focus on these two processing
components in the present study.
Monitoring is the ability to detect a potential conflictive
situation and signal that the situation demands a specific action
(Costa et al., 2008). The global response time (RT) and mixing
costs within a switch task are two different indexes that are used to
measure monitoring. While global RT refers to the overall faster
responses (Hartanto and Yang, 2019), mixing costs refers to the
performance difference between single-language blocks which do
not involve monitoring and repetition trials of mixed-language
blocks which place high demands on monitoring (Braver et al.,
2003;Prior and MacWhinney, 2010;Jylkkä et al., 2018). Ma et al.
(2016) indicated that mixing costs also reflect proactive control
during word production. In the current study, we used the latter
index as it has been argued to be a purer measure of monitoring
than global RT (Paap and Greenberg, 2013).
Inhibitory control is the ability to control one’s attention,
behavior, or internal predisposition for executing appropriate
responses (Clark, 1996;Bunge et al., 2002). There are various
indexes from different tasks to measure inhibitory control. For
example, the flanker effect in the flanker task, the Simon effect
in the Simon task, or the anti-saccade effect in the anti-saccade
task (Paap and Sawi, 2014;Jiao et al., 2019). Here, we chose the
anti-saccade task because it is a more difficult task (Hamilton
and Martin, 2005) that could avoid ceiling effects. The anti-
saccade effect refers to the performance difference between anti-
saccade blocks which place a high demand on inhibitory control
and control blocks which do not involve inhibitory control
(Paap and Greenberg, 2013).
According to the adaptive control hypothesis (Green and
Abutalebi, 2013), control processes adapt to the demands
imposed on them by context. In this way, certain components
of EC would show a bilingual facilitative effect when the context
imposes demands on it. In the present study, we examine
whether the specific exercise in monitoring and inhibitory control
during language switching transfers to the corresponding parts of
domain-general cognitive control.
Coss-Talk Between BLC and EC
Previous studies have introduced two theoretical accounts to
explain the relationship between BLC and the two components of
EC (i.e., monitoring and inhibitory control). These explanations
include the bilingual executive processing advantage hypothesis
(Hilchey and Klein, 2011) and the inhibitory control model
(Green, 1998). The former postulates that bilinguals are better
at global conflict-monitoring than monolinguals because of their
constant practice with coordination of two competitive languages
which should be beneficial for the monitoring aspects of cognitive
control.1The inhibitory control model (Green, 1998) postulates
that because two languages are coactivated automatically and
compete with each other in the mind, bilinguals constantly
recruit inhibitory control mechanisms to select the intended
language while suppressing the irrelevant language. Bilinguals’
routine practice of inhibiting the irrelevant language should be
beneficial for the inhibitory control aspects of EC.
In line with the bilingual executive processing advantage
hypothesis (Hilchey and Klein, 2011) and the inhibitory control
model (Green, 1998), many previous studies have revealed a
positive relationship between BLC and monitoring (e.g., Costa
et al., 2009) and between BLC and inhibitory control (e.g.,
Bialystok et al., 2006;Fan et al., 2012). However, other studies
have found no such relationship (Prior and MacWhinney,
2010;Paap and Greenberg, 2013). For example, Paap and
Greenberg compared bilinguals to monolinguals on 15 indicators
of executive processing (EP). The results showed no bilingual
facilitative effect on any indicator suggesting no relationship
between BLC and EC.
One possible reason for the inconsistent findings regarding the
cross-talk between BLC and EC is due to the experimental design.
Most studies examining the relationship between bilingualism
and cognitive control directly compared the performance of a
bilingual group and a monolingual group. Such cross-sectional
designs involve larger individual differences and might not
reveal the causal relationship between bilingualism and cognitive
control. However, a training design may better match the
1Although today, Hilchey and Klein (2011) no longer support their bilingual
executive processing advantage hypothesis.
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Liu et al. Training in Language Switching
background information of different groups, and benefit the
assessment of causal relation between the language experience
and cognitive capabilities (Li and Grant, 2015) because it enables
the tracking of basic comprehension processes such as word
knowledge/processes in the second language (Grant et al., 2015;
Yang et al., 2015) and of the effects of linguistic and non-linguistic
control, respectively, in the development of cognitive control
(Moreno et al., 2011).
For instance, in a training setting Zhang et al. (2015) examined
the effects of language switching on the component processes
of cognitive control (i.e., proactive control and reactive control;
Braver, 2012). Participants were randomly and evenly divided
into experimental and control groups. Both groups completed
the same cognitive control task (i.e., the AX version of the
Continuous Performance Test in Braver and Barch, 2002, and
Rosvold et al., 1956) in the pre- and post-training phase
whereas only experimental group received a training phase which
included a series of language switching training in between
the pre- and post-training phases. The results showed that
the language switching experience facilitated cognitive control,
suggesting a positive relationship between BLC and EC. By
comparing the task performance between the pre- and post-
training phase and by comparing the experimental group with the
control group, this facilitative effect on cognitive control could
be more straightforwardly attributable to the effect of language
switching training.
THE PRESENT STUDY
In the present study, we explore the effect of language switching
on monitoring and inhibitory control by adopting a training
design. We conducted two experiments, both of which included,
sequentially, a pre-training phase, a training phase, and a post-
training phase. In Experiment 1, both groups of participants were
required to complete two cognitive control tasks (i.e., a color-
shape switching task and an anti-saccade task) that are useful
in assessing the two components processes of EC of interest in
pre- and post-training phases. The language switching training
group received a series of language switches in the training phase
and hence engaged monitor and inhibition processes, whereas
the control group received no training. Hence, by comparing
the language switching training group’s performance in the pre-
and post-training phase, we can assess the potential effect of
language switching training on the monitoring (i.e., mixing costs
in the color-shape switching task) and inhibitory control (i.e.,
anti-saccade effects in the anti-saccade task). We hypothesize that
if BLC and these two components of EC share some processes,
then the training on BLC should lead to benefits in EC. Moreover,
because the language switching training group trained specifically
on monitoring and inhibition during language switching while
the control group did not train on these abilities, we expect a
greater decrease of the anti-saccade effect and mixing cost from
pre- to post-training for the language switching training group
compared to the control group.
In Experiment 2, we further explored which factors contribute
to the positive relationship between BLC and EC. Specifically,
we aimed to reveal where the facilitative effect on monitoring
or inhibitory control derived from: the specific training on
monitoring, the specific training on inhibitory control, or both.
Two different groups of participants were asked to complete
two cognitive control tasks similar to those in the pre- and
post-training phase in Experiment 1. In the training phase, one
group of participants received a series of language switches
engaging monitoring and inhibitory control processes (language
switching training group), whereas the other group received
training which only engaged inhibitory control processing (L2
training group). If the facilitative effect is only derived from
training on monitoring during language switching, there will be
a greater decrease of mixing costs and anti-saccade effect from
pre- to post-training for the language switching training group
compared to the L2 training group. However, if the facilitative
effect is only derived from training on inhibitory control during
language switching, there will be a greater decrease of mixing
costs and anti-saccade effect from pre- to post-training for the
L2 training group compared to the language switching training
group. Furthermore, if the facilitative effect derived from training
on both monitoring and inhibitory control during language
switching, there will be a greater decrease of mixing cost and
smaller decrease of anti-saccade effect from pre- to post-training
for the language switching training group compared to the
L2 training group.
EXPERIMENT 1
Participants
Sixty Chinese-English bilinguals (all non-English majors) at the
South China Normal University (SCNU), aged 18–24: M= 20.6,
SD = 1.2, participated in Experiment 1. These individuals were
all right-handed with normal or corrected-to-normal vision. All
participants were English-as-a-foreign-language (EFL) learners
whose mean age of first exposure was 9 years, SD = 1.7.
Participants were asked to complete a questionnaire about their
language background, including the age of L2 acquisition (L2
AoA), L2 proficiency, and the frequency of language switching
(see Table 1). The participants rated their L2 proficiency level
on a seven-point Likert scale, with seven indicating the highest
level of proficiency and one indicating the lowest. They also rated
their frequency of language switching on a five-point Likert scale,
with five indicating the highest frequency of language switching
and one indicating the lowest. All participants were Han Chinese
without experience with immigration. Participants were divided,
evenly and randomly, into two groups (language switching
training vs. control) at first, but there was one participant in
the language switching group who did not undergo language
switching training between pre- and post-training, which lead
to 29 participants in the language switching group and 31
participants in the control group. Additionally, two participants
in the language switching group were excluded from data analysis
due to test incompletion, eventually leaving 27 for the language
switching training group and 31 for the control group. Pair-wise
t-tests revealed no significant differences between the two groups
regarding their language background information (p>0.05). The
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TABLE 1 | Language background information for participants in Experiment 1.
L2 AoA L2 proficiency Frequency of
language switching∗
Control group 9.1 ±1.8 4.5 ±1.14 2.7 ±0.4
Switching training group 9.6 ±1.8 4.9 ±1.33 2.6 ±0.4
∗As measured by a language switching questionnaire
(Rodriguez-Fornells et al., 2012).
study was approved by the Human Research Ethics Committee
of South China Normal University. All participants provided
informed consent before the start of the experiment and were
informed of their right to withdraw at any time. Participants
received monetary compensation for their participation.
Design and Procedure
The experiment involved three phases: (1) a pre-training phase,
in which participants of both language switching training
and control groups were asked to complete the language
questionnaire and then to participate in two non-linguistic
cognitive control tasks (i.e., the color-shape switching task
and the anti-saccade task which measure monitoring and
inhibitory control, respectively); (2) a training phase, in
which only the language switching training group received
language switching training (linguistic switching-task training)
for a total of eight times on four consecutive days, two
times per day. It took approximately 30 min for each
participant to receive the language-switching training each
day; and 3) a post-training phase, held on the day after
the training, in which all participants in both groups once
again performed the same two non-linguistic cognitive control
tasks. The waiting period between pre- and post-training
was the same for both the control group and language
switching training group.
Two strategies were adopted to minimize potential confounds
that may undermine the effects of language-switching training on
the non-verbal tasks of cognitive control when comparing the
performance differences between the pre-training and the post-
training phases and between the language switching training and
the non-training (control) groups. First, to mitigate differences
in task expectancy between the experimental and control groups,
both groups were offered no explicit information regarding
the types and sequence of tasks being administered in each
test phase (i.e., pre- and post-training). They were merely
informed, during recruitment, that they would be taking a set
of tests twice. The sequence of the two non-linguistic cognitive
control tasks in the pre- and post-training phases was also
randomly assigned for each participant. Half of the participants
started with color-shape switching task and the other half
started with anti-saccade tasks. Furthermore, because it has been
shown that goal-imposed tasks, verbal or non-verbal, potentially
enhance the abilities associated with the cognitive control for
subsequent cognitive processes (Gratton et al., 1992;Ullsperger
et al., 2005;Wu and Thierry, 2013), we opted to offer neither
linguistic nor non-linguistic tasks for the control group during
the training phase.
Language Switching Training Task
Only participants in the language switching training group
received this training task. We used the cued naming task as the
language switching training task because the process of language
production has been shown to be highly related to cognitive
control abilities (Liu et al., 2015;Sikora et al., 2016;Lu et al.,
2017). This task was conducted between the pre-training and
post-training phases, and required participants to name a target
number (e.g., Arabic numerals 0–9), presented on the computer
screen, in their L1 (Mandarin) and L2 (English) according to flag
cues (Chinese flag for L1; American flag for L2) that preceded the
target number (i.e., participants responded by verbally producing
the numbers). The training trials began with a center fixation for
500 ms, followed by a blank screen for 250 ms. Next, the flag cue
was presented for 250 ms and the target number then appeared
on the screen for participants’ responses (maximum duration:
2000 ms). The flag cues were presented in a pseudo-random order
with a maximum of 3 consecutive trials of the same type of cue.
There was an inter-stimulus interval of 500 ms before the onset
of the next trial. The ratio of repetition and switch trials was 1:1
for each language in both blocks. Each training session lasted for
approximately 15 min. Again, there was a total of eight training
sessions during four consecutive days: two sessions per day, once
in the morning and once in the afternoon. On each training day,
the time interval between the two training sessions was identical
to avoid the potential confounds of training mode.
Cognitive Control Measures: Color-Shape Switching
and Anti-saccade Tasks
Participants in both groups received two tasks in the pre-
training and post-training phases. The first task, the color-
shape switching task, was a non-verbal experiment based on
Prior and MacWhinney (2010) consisting of two single blocks
(one pure color and one pure shape) and one mixed block.
Each trial began with the presentation of a center fixation
cross for 500 ms followed by a blank screen for 250 ms. The
target item then appeared in the center of the screen until the
participant responded (maximum duration: 4000 ms). The target
set included a blue circle, a blue triangle, a red circle, and a
red triangle. The inter-stimulus interval was 250 ms. Participants
were instructed to place the left-hand middle and index fingers
on the “Q” and “W” keys, respectively, for the color task; and
the right-hand middle and index fingers on the “O” and “P”
keys, respectively, for the shape task. In the pure color block, the
participants were instructed to press the “W” key if the target was
red and the “Q” key if the target was blue. In the pure shape
block, they were asked to press the “P” key if the target was a
triangle and the “O” key if the target was a circle. In the mixed
block, a pre-cue preceded the target for 250 ms. Participants were
instructed to make a color decision about the target if the pre-
cue was a rainbow figure and a shape decision on the target if the
pre-cue was a geometric figure. They were required to respond
as quickly as possible based on the pre-cue dimension (color or
shape). The blocks (two single blocks and one mixed block) were
counterbalanced across participants. Each single block contained
8 practice trials, followed by 24 experimental trials that were
randomly presented. The ratio of repetition and switch trials
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was 1:1 for each task and in both blocks. The mixed block
included 16 practice trials (four for each kind of target) and 50
experimental trials. The shape and color tasks in the mixed blocks
were randomly ordered with a maximum of four consecutive
trials of the same type. Following Prior and MacWhinney, two
additional dummy trials were added at the beginning of each
block and were excluded in the analysis.
Our second task which measured cognitive control was the
anti-saccade task. We modeled this experiment after Paap and
Greenberg (2013) in terms of material, design, and procedure.
The task included one anti-saccade block and one control
block, counterbalanced across participants. The anti-saccade
trials started with a center fixation, presented at various durations
(600/1000/1400/1820/2200 ms), that was followed by a blank
screen for 250 ms. A motionless symbolic distracter (i.e., “#”)
then flickered about 2◦to one side of fixation twice (each flicker
duration was 100 ms with a blank screen of 50 ms in between).
Upon the offset of the second flickering, the target letter (i.e., “B”,
“P”, or “R”) was presented for 150 ms about 2◦next to the fixation
that was opposite to the distractor, followed by a visually similar
mask (i.e., “8”) in the same location. Participants were instructed
to identify the target letter by pressing the corresponding labels
using three fingers of the right hand. Each letter was assigned
different labels for the correct response. There was an inter-
stimulus interval of 500 ms before the onset of the next trial.
According to Paap and Greenberg, when the eventual target is
presented on the opposite side of the distracter, the best strategy
is to inhibit the reflexive, automatic urge to attend to a visual
stimulus (i.e., distracter) that appears abruptly in the peripheral
visual field. Thus, faster RTs should be expected if bilinguals
are superior in their inhibitory control ability. For the control
trials, the target letters appeared on the center of the screen
after the center fixation with no presentation of the opposite
field distracter.
The trials were organized as follows: The anti-saccade block
consisted of 12 practice trials and 60 anti-saccade trials in which
the presence of the target letters was counterbalanced between the
left and right sides of the screen. In the control block, participants
performed six practice trials, in which three target letters were
presented two times each in a random order; and 30 control
trials which were formed by the random combination of the
aforementioned five fixation durations. Again, the sequence of
the anti-saccade block and control block was counterbalanced
across participants.
Results
Only trials with correct responses were included in the analyses.
RTs slower than 200 ms and greater than 2000 ms were excluded
from the analyses. We also discarded trials whose RTs were
2.5 SDs below or above the mean (Liu et al., 2019a,b). This
data-trimming procedure applied to both anti-saccade (12.6%
excluded) and color-shape switching tasks (8.8% excluded).
Considering the high accuracy of each task, our analyses focused
mainly on RTs. We conducted multilevel mixed effects models
with participants and trial order as crossed random effects
in the R computing environment (lme4 package, Bates et al.,
2007; lmerTest package, Kuznetsova et al., 2014). The reason
for using mixed-effect models was to allow random effects of
participants and trial order to be considered simultaneously
(Baayen et al., 2008). Their results also are more reliable than
traditional statistics (Barr et al., 2013).
For each task, we employed linear models for the RT data
and included multiple fixed effects of theoretical interest (i.e.,
test, group, task condition, and their full interactions). All
variables were contrast-coded, yielding tests of the main effects
directly analogous to those obtained from an ANOVA (Fraundorf
and Jaeger, 2016;Tullis and Fraundorf, 2017). As for random
effects, we assessed the contribution of each random slope to
each model by using likelihood-ratio tests and reported the
best-fitting model with the maximal random effects structure
justified by the data.
Color-Shape Switching Task
In the data analyses for the color-shape switching task, one
additional participant from the language switching training
group was excluded due to low accuracy. This left 31 for
the control group and 26 for the language switching training
group to be included in the linear mixed effect model analysis.
The mean RTs and mean accuracy are shown in Table 2.
The mixing costs were defined as the difference between the
non-switch (i.e., repetition) trials in the mixed block and the
trials in the single block (Prior and MacWhinney, 2010). We
fit a linear mixed effect model with the fixed effect of test
(pre-training, post-training), group (control, language switching
training), task condition (single block, mixed block), and their
full interactions. For the random effect, the best-fitting model
included a random intercept for subjects and trial order;
by-subject random slopes for test, task condition, and their
interaction; and by-trial order for test, the interaction between
test and task condition, and the interaction between test and
group. Other random slopes did not improve model fit (p>0.1)
and were thus omitted.
The results of the mean RTs are summarized in Table 3.
These analyses showed a significant effect for test (t= 9.11,
p<0.001), suggesting overall faster responses in the post-
training phase relative to the pre-training phase. There was also
a significant effect for task condition (t= 16.08, p<0.001),
indicating slower responses of the repetition trials in the mixed
block compared to the trials in the single block. In our design, the
interactions relating to the task condition were the crucial index
TABLE 2 | Mean RTs (and SDs) and accuracy (and SDs) of the color-shape
switching task in Experiment 1.
Pre-training Post-training
Single Mix Single Mix
RT
(ms)
Control group 418 ±114 655 ±237 425 ±123 594 ±194
Language switching
training group
479 ±152 806 ±349 383 ±96 538 ±176
ACC
(%)
Control group 97 ±18 94 ±24 96 ±19 97 ±15
Language switching
training group
96 ±18 94 ±23 94 ±23 94 ±23
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Liu et al. Training in Language Switching
for the mixing costs, especially as demonstrated by the three-way
interaction. The interactive effect between the test and the task
condition was significant (t= 6.40, p<0.001), indicating that
mixing costs in the post-training were significantly smaller than
those in the pre-training. Crucially the three-way interaction for
test ∗group ∗task condition in the color-shape switching task
was significant (t=−3.28, p<0.001). Further analyses of this
interaction suggest a greater reduction of the mixing costs from
pre- to post-training for the language switching training group
(172 ms) compared to the control group (68 ms) (see the left
graph in Figure 1). Such improvement for the language switching
training group suggests greater gains of monitoring ability from
the switching-task training which we interpret as evidence for a
training effect.
Anti-saccade Task
The descriptive results (i.e., mean RTs and mean accuracy) are
reported in Table 4. The anti-saccade effect was assessed by
subtracting the mean RT of the control block from that of the
anti-saccade block (Paap and Greenberg, 2013). We fit a linear
mixed effect model with the fixed effect of test (pre-training,
post-training), group (control, language switching training), task
condition (control, anti), and their full interactions. For the
random effect, the best-fitting model included random intercept
for subjects and trial order; by-subject random slopes for
test and task condition; and by-trial order for task condition.
Other random slopes did not significantly improve model fit
and were omitted (p>0.1).
The main effects of both test and task conditions were
significant (p<0.001) (see Table 5). The mean RT in the
TABLE 3 | Model parameters for the best-fitting linear mixed effects model of the
color-shape switching task in Experiment 1.
Model parameters Estimate SE t p
(Intercept) 540.95 10.50 51.53 <0.001
Test 105.68 11.60 9.11 <0.001
Task condition 225.31 14.01 16.08 <0.001
Group −30.85 17.85 −1.72 0.08
Test: Task condition 119.28 18.63 6.40 <0.001
Test: Group −150.60 21.42 −7.03 <0.001
Group: Task condition −36.95 20.68 −1.78 0.07
Test: Group: Task condition −106.76 32.55 −3.28 <0.001
TABLE 4 | Mean RTs (and SDs) and mean accuracy (and SDs) of the anti-saccade
task in Experiment 1.
Pre-training Post-training
Control Anti Control Anti
RT
(ms)
Control group 603 ±153 661 ±152 614 ±158 664 ±158
Language switching
training group
704 ±193 801 ±198 555 ±131 585 ±121
ACC
(%)
Control group 93 ±24 85 ±35 95 ±21 91 ±28
Language switching
training group
91 ±28 87 ±33 93 ±25 90 ±30
post-training phase was shorter than the mean RT in the pre-
training phase, and the mean RT of the anti-saccade block was
longer than the mean RT of the control block. We focused on
the interactions that were related to the task condition because
of our major theoretical motive in the anti-saccade effect. The
interactive effect between test and task condition was significant
(t=−7.17, p<0.001), indicating that the anti-saccade effect in
the post-training was significantly smaller than the anti-saccade
effect in the pre-training. Same as the color-shape switching task,
the three-way interaction for test ∗group ∗task condition was
significant, demonstrating a difference between the control and
language switching training groups in terms of the anti-saccade
effect (t= 5.34, p<0.001). As shown in Table 5, the language
switching training group exhibited a greater decrease in the anti-
saccade effect from pre- to post-training (67 ms) compared to
the control group (8 ms). A visual representation of this finding
can be seen in the graph on the right in Figure 1. Similar to
the color-shape switching task, this greater improvement for
the language switching training group suggests greater gains of
inhibitory control ability from the switching-task training and
supports evidence for a training effect.
Discussion
The results of Experiment 1 show that language switching
training reduced mixing costs and the anti-saccade effect within
cognitive control in bilinguals, which suggest that a bilingual
language switching experience could facilitate monitoring and
inhibition. These results were consistent with the bilingual
executive processing advantage hypothesis (Hilchey and Klein,
2011) and the inhibitory control model (Green, 1998), suggesting
a positive relationship between BLC and EC. As mentioned
above, during language switching, bilinguals need to monitor
the communicative environment for changes that trigger a
language switch and subsequently inhibit the non-target language
when speaking in the intended language. For the language
switching training group, monitoring and inhibitory control
ability were enhanced through intensive language switching
training compared to the control group.
While the findings of Experiment 1 show that the language
switching training facilitated monitoring and inhibitory control
within cognitive control, they do not tell us specifically where this
facilitative effect comes from. This is due to the fact that we could
not separate the monitoring processing and inhibitory control
TABLE 5 | Model parameters for the best-fitting linear mixed effects model of the
anti-saccade task in Experiment 1.
Model parameters Estimate SE t p
(Intercept) 648.94 10.43 62.18 <0.001
Test 89.17 12.65 7.04 <0.001
Task condition −68.36 8.81 −7.75 <0.001
Group −23.49 20.21 −1.16 0.25
Test: Task condition −40.77 5.68 −7.17 <0.001
Test: Group −190.16 25.30 −7.51 <0.001
Group: Task condition 8.08 16.15 0.50 0.61
Test: Group: Task condition 60.70 11.36 5.34 <0.001
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FIGURE 1 | Mixing cost of the color-shape switching task (left) and anti-saccade effect of the anti-saccade task (right) in Experiment 1. Error bar represents
standard error.
processing during one language switching task. To address this,
in Experiment 2, one group of participants received a series
of L2 training which only engaged inhibition processing (L2
training group) while another group received language switching
training as in Experiment 1. According to the adaptive control
hypothesis (Green and Abutalebi, 2013), certain components
of cognitive control show facilitative effects when the context
imposes demands on it. Hence, the training of monitoring
during language switching would facilitate monitoring ability
within cognitive control and the training of inhibitory control
during language switching would facilitate inhibitory control
ability within cognitive control. If this is the case, then a
greater decrease of mixing cost and a smaller decrease of
anti-saccade effect from pre- to post-training for the language
switching training group compared to the L2 training group
should be observed.
EXPERIMENT 2
Participants
Fifty Chinese-English bilinguals (all non-English majors) who
did not participate in Experiment 1 but were from the same
population, participated in Experiment 2. The ages ranged
from 18 to 24 (M= 20.2, SD = 1.6). These individuals
were all right-handed with normal or corrected-to-normal
vision. As in Experiment 1, all participants were EFLs, with a
mean age of first exposure to English of 8 years (SD = 2.9)
and were also asked to complete a language background
questionnaire. The two groups were not significantly different
in their language background (p>0.1). Table 6 shows
participants’ language background information, including L2
AoA, L2 proficiency, and frequency of language switching.
One participant was excluded from data analysis due to
test incompletion. The remaining participants were randomly
and evenly divided into two groups: 24 for the language
switching training group and 25 for the L2 training group.
All participants provided written informed consent before the
experiment and were informed of their right to withdraw at
any time. Each participant received monetary compensation
for participation.
Design and Procedure
As in Experiment 1, Experiment 2 was conducted in three phases
(i.e., a pre-training phase, a training phase and a post-training
phase). Participants of both language switching training and L2
training groups were asked to complete the same non-linguistic
cognitive control tasks (the anti-saccade task and the color-
shape switching task) in both pre- and post-training phases.
During the training phase, participants in both groups were
required to complete the training task for a total of four times
(instead of eight times in Experiment 1) on four consecutive
days. However, each training time in Experiment 2 lasted for
approximately 30 min rather than 15 min as in Experiment
TABLE 6 | Language background information for participants in Experiment 2.
L2 AoA L2 proficiency Frequency of
language switching∗
L2 training group 8.4 ±2.1 4.0 ±1.0 2.7 ±0.5
Switching training group 8.3 ±2.7 4.2 ±0.8 2.8 ±0.4
∗As measured by a language switching questionnaire
(Rodriguez-Fornells et al., 2012).
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Liu et al. Training in Language Switching
1. We reduced the number of training days but maintained
the same amount of time to avoid participant attrition due to
multiple sessions. Participants in the language switching training
group were instructed the same as those in Experiment 1 to
perform a cued naming task which required high demands of
switching between languages whereas participants in the L2
training group were instructed to name all stimuli only in L2,
and thus they did not switch between languages. All other
aspects of the design and procedure were the same as those
in Experiment 1.
Results
The procedure of data trimming and analysis was the same as in
Experiment 1. Only trials with correct responses were included
in the analyses.
Color-Shape Switching Task
Data from both groups were entered into a linear mixed effect
model analysis. Applying the same data trimming procedure
as above resulted in 8.6% data exclusion. Table 7 shows the
mean RTs and accuracy and Table 8 summarizes the results
of the mean RTs. Like Experiment 1, both the test and the
task conditions were significant (p<0.001), indicating that
participants responded faster in the post-training phase than in
the pre-training phase and slower for the repetition trials in
the mixed block compared to the trials in the single block. The
interactive effect between the test and the task condition was
significant (t= 11.26, p<0.001), indicating that the mixing
costs in the post-training were significantly smaller than those
in the pre-training. More importantly, the three-way interaction
for test ∗group ∗task condition was significant (t=−2.18,
p= 0.02), suggesting that the language switching training group
showed a greater decrease in mixing costs from pre- to post-
training (98 ms) compared to the L2 training group (68 ms)
(see left graph in Figure 2). This pattern is consistent with that
of Experiment 1 in that both the control group in Experiment
1 and the L2 training group in Experiment 2 do not involve
monitoring process.
Anti-saccade Task
Data from one participant in the L2 training group was excluded
due to low accuracy, resulting in 24 participants in the L2
TABLE 7 | Mean RTs (and SDs) and mean accuracy (and SDs) of the color-shape
switching task in Experiment 2.
Pre-training Post-training
Single Mix Single Mix
RT
(ms)
L2 training group 437 ±114 683 ±241 439 ±126 617 ±204
Language switching
training group
442 ±110 724 ±267 428 ±106 612 ±214
ACC
(%)
L2 training group 94 ±23 92 ±27 96 ±19 94 ±22
Language switching
training group
97 ±18 94 ±24 96 ±19 96 ±20
training group and 24 in switching training group. The same
data-trimming criteria described above resulted in 10.6% data
exclusion. Table 9 shows the mean RTs and mean accuracy for the
two groups in the anti-saccade task and Table 10 summarizes the
results of the mean RTs. Following the same analysis procedure of
fitting a linear mixed effect model, both test and task conditions
were again significant. Participants responded faster in the post-
training phase than in the pre-training phase, and they responded
slower in the anti-saccade block than in the control block. Both
the interaction for test ∗task condition (t=−6.75, p<0.001)
and, crucially, the three-way interaction for test ∗group ∗task
condition (t=−2.56, p= 0.01) were significant. Resolution of
the interaction revealed that, consistent with our hypothesis, it is
now the L2 training group that showed a greater decrease of the
anti-saccade effect from pre- to post-training (54 ms) compared
to the language switching training group (17 ms) (see right
graph in Figure 2). These results arise from more demands on
inhibitory control for the L2 training group than for the language
switching training group.
Discussion
The findings of Experiment 2 showed a greater decrease in mixing
costs and a smaller decrease in the anti-saccade effect from
pre- to post-training for the language switching training group
compared to the L2 training group. Combined with the results
in Experiment 1, both suggest a bilingual facilitative effect on
monitoring and inhibitory control. These findings are consistent
with the bilingual executive processing advantage hypothesis
(Hilchey and Klein, 2011) and the inhibitory control model
(Green, 1998).
Critically, the results in Experiment 2 were able to illuminate
the finding that the bilingual facilitative effect seems to emerge
from training on both monitoring and inhibitory control
during language switching. Training monitoring during language
switching facilitates monitoring abilities within cognitive control
and training inhibitory control facilitates inhibitory control
abilities within cognitive control. These findings can be
explained by the adaptive control hypothesis (Green and
Abutalebi, 2013) which proposes that the control processes
themselves can adapt to the demands imposed on them by
context. Specifically, in the present study, different training
contexts placed different demands on the control processes
under scrutiny (i.e., monitoring or inhibitory control), which
TABLE 8 | Model parameters for the best-fitting linear mixed effects model of the
color-shape switching task in Experiment 2.
Model parameters Estimate SE t p
(Intercept) 552.26 11.29 48.89 <0.001
Test 48.70 7.92 6.14 <0.001
Task condition 226.18 15.55 14.53 <0.001
Group −8.60 19.85 −0.43 0.66
Test: Task condition 85.52 7.59 11.26 <0.001
Test: Group −36.82 15.84 −2.32 0.02
Group: Task condition −24.10 22.02 −1.09 0.27
Test: Group: Task condition −33.19 15.18 −2.18 0.02
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FIGURE 2 | Mixing costs of the color-shape switching task (left) and anti-saccade effect of the anti-saccade task (right) in Experiment 2. The error bar represents
standard error.
eventually improve the specific monitoring or inhibitory
control abilities.
GENERAL DISCUSSION
Our empirical focus is the debate on whether BLC overlaps
two componential processes of EC: monitoring and inhibitory
control. Instead of using a traditional cross-sectional approach
the current study adopted a training design in which participants
received language switching training and completed the same
cognitive control tasks in the pre- and post-training. By
comparing the performance of a language switching training
group and a control group from pre- and post-training in
Experiment 1, we found that language switching training
significantly enhanced the performance of monitoring and
inhibitory control within EC, to some extent, suggesting a
positive relationship between BLC and EC. Such relationship was
demonstrated by the gains of the inhibitory control component
(i.e., anti-saccade effect) in the anti-saccade task, and the
monitoring component (i.e., mixing costs) in the color-shape
switching task. Furthermore, by comparing the performance of
the language switching training group and the L2 training group
from pre- and post-training in Experiment 2, we found that the
observed positive relationship between BLC and two components
process of EC (i.e., monitoring and inhibitory control) arise from
the corresponding training on both monitoring and inhibitory
control during language switching.
The Positive Relationship Between BLC
and EC
Regarding the ongoing debate as to whether BLC overlaps
with EC or not, previous researchers mainly have conducted
studies with cross-sectional designs to examine facilitative effects
on EC among bilinguals. In contrast, by using a training
design, the current study uniquely examined two components
of EC based on the two main control processing in language
switching, namely monitoring and inhibitory control. Because
the monitoring and inhibitory control processes contained
TABLE 9 | Mean RTs (and SDs) and mean accuracy (and SDs) of the anti-saccade
task in Experiment 2.
Pre-training Post-training
control anti control anti
RT
(ms)
L2 training group 631 ±145 719 ±150 618 ±140 652 ±126
Language switching
training group
682 ±192 729 ±162 642 ±168 672 ±150
ACC
(%)
L2 training group 93 ±26 89 ±31 95 ±21 92 ±27
Language switching
training group
93 ±24 90 ±29 94 ±23 93 ±24
TABLE 10 | Model parameters for the best-fitting linear mixed effects model of the
anti-saccade task in Experiment 2.
Model parameters Estimate SE t p
(Intercept) 669.81 12.63 52.99 <0.001
Test 41.23 7.50 5.49 <0.001
Task condition −52.21 7.32 −7.12 <0.001
Group −26.20 24.86 −1.05 0.29
Test: Task condition −41.33 6.12 −6.75 <0.001
Test: Group −5.62 14.69 −0.38 0.70
Group: Task condition −22.54 13.50 −1.66 0.11
Test: Group: Task condition −30.74 12.00 −2.56 0.01
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in language switching received intensive exercises during the
training phase, such abilities improved and further facilitated the
performance of corresponding domains of EC.
Mixing costs in switching tasks are typically used to assess
the processing of monitoring components (Braver et al., 2003;
Prior and MacWhinney, 2010). Our results in Experiment
1 showed evidence for a positive relationship between BLC
and monitoring such that language switching training led
to significant reductions in mixing costs, suggesting that the
adaptive changes resulted from our language switching training
mainly reflected monitoring processing. The facilitative effect
on monitoring processes has been demonstrated by previous
studies. Bialystok et al. (2005) reported reduced mixing costs for
bilinguals by comparing mixed blocks with single-task blocks.
Costa et al. (2009), for example, using a flanker task, found an
advantage for bilinguals, relative to monolinguals, on conflict
monitoring processing under demanding circumstances (i.e.,
50% or 75% congruent trials, at least 25% intermixed incongruent
trials). However, the bilingual effects on monitoring components
(i.e., mixing costs) are still in dispute. For example, two recent
studies adopting similar non-linguistic switching tasks provide
a comparison to our results. Prior and MacWhinney reported
that there was no bilingual advantage compared to monolinguals
in terms of mixing costs. In contrast, Soveri et al. (2011) found
that bilinguals outperformed monolinguals in the mixing costs.
One possible reason for this may be due to confounding factors
contained in traditional cross-sectional designs. Instead, by using
the training method, we found a facilitative effect on mixing costs,
supporting the bilingual advantage in monitoring ability (Hilchey
and Klein, 2011), which is consistent with the findings from a
recent study by Timmer et al. (2019).
Inhibitory control has been recognized as a core element of
EC (Diamond, 2013). Beyond the facilitative effect in monitoring,
the findings in Experiment 1 also showed that specific training
on inhibition during language switching facilitates the inhibition
process in EC, suggesting a positive relationship between BLC
and inhibitory control. This result is consistent with previous
studies demonstrating that bilingualism exerts positive effects on
inhibitory control processes (Bialystok and Viswanathan, 2009).
However, Paap and Greenberg (2013), with similar employment
of the anti-saccade task, reported no cognitive advantage
of inhibitory control processing for bilinguals compared to
monolinguals. Given that our study differed from Paap and
Greenberg—primarily in that ours is based on a training design
whereas Paap and Greenberg’s used cross-sectional comparisons
between monolinguals and bilinguals—it seems likely that these
differences might contribute to the inconsistencies found in
research investigating these issues.
Taken together, the current study indicates that short-term
bilingual language switching training facilitates inhibitory control
and monitoring processing within EC, which is in line with
bilingual executive processing advantage hypothesis (Hilchey
and Klein, 2011) and inhibitory control model (Green, 1998),
supporting the bilingual advantage effect on monitoring and
inhibitory control. These results further suggested a positive
relationship between BLC and EC. However, we note that these
positive relationships are observed in a short-term, experimental
setting which is different from the cross-sectional studies.
The latter have examined whether bilinguals compared to
monolinguals show improved cognitive control due to the long-
term, daily practice with language switching that bilinguals
have. As daily language switching is not as intense as was
our language switching training protocol in the current study,
we could conclude that there are positive effects of short-
term language switching training on inhibitory control or
monitoring abilities. However, we cannot disentangle whether
long-term daily language switching experience could facilitate
such cognitive control abilities (for a review, see Blanco-Elorrieta
and Pylkkänen, 2016).
The Sources of the Positive Relationship
Between BLC and EC
Most of the studies that have reported a positive relationship
between BLC and EC have only focused on whether such a
relationship existed or not, without further investigating the
source of the positive relationship they observed (Bialystok et al.,
2006;Dong and Xie, 2014;Liu et al., 2016; among others).
In Experiment 2, we found the L2 training group showed a
greater decrease in the anti-saccade effect from pre- to post-
training (54 ms) compared to the language switching training
group (17 ms). This is because the L2 training group had
more demand for inhibitory control than the language switching
training group. For the L2 training group in our study, mainly
inhibitory control is engaged. Moreover, the participants in the
present study are unbalanced Chinese-English bilinguals who
lived in the dominant L1 (i.e., Chinese) environment with very
low proficiency in their L2 language (i.e., English). According
to inhibitory control model (Green, 1998), since L1 initially has
a larger activation than L2, more inhibition will be needed to
suppress L1 during L2 production than vice versa. Specifically,
naming in L2 requires inhibiting the competing response in
the L1, as well as the task goal of speaking in the L1, and
unbalanced bilinguals must rely on strong inhibition of the L1
in order for production in the L2. Conversely, when producing
in a highly dominant L1, unbalanced bilinguals need to inhibit
the L2 to a lesser degree (Costa and Santesteban, 2004; for
a review, see Declerck and Philipp, 2015). By contrast, for
the language switching group, both monitoring and inhibitory
control are engaged, and more importantly, the inhibitory control
contains both strong inhibition of L1 and weak inhibition of
L2. Thus, the overall inhibition for the language switching
group is smaller than the L2 training group. On the other
hand, the language switching training group showed a greater
decrease of mixing costs from pre- to post-training (98 ms)
compared to the L2 training group (68 ms), due to the fact
that the language switching training group demanded more
monitoring than the L2 training group as there is little conflict
monitor processing during L2 training with only one language.
These results together indicated that the bilingual facilitative
effects on monitoring and inhibitory control derived from the
corresponding specific training of these abilities during language
switching, which provided empirical evidence for the source of
the positive relationship between BLC and EC.
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Also in Experiment 2, one group of participants received
a series of language switching training sessions that engaged
monitor and inhibitory control processes (language switching
training group), whereas the other group received L2 training
that only engaged inhibition processing (L2 training group).
The results showed a greater decrease of mixing cost from
pre- to post-training for the language switching training group
compared to the L2 training group, and a greater decrease of
the anti-saccade effect from pre- to post-training for the L2
training group compared to the language switching training
group, suggesting that the observed positive relationship between
BLC and EC derived from the training on both monitoring
and inhibition during language switching. Specifically, the short-
term training on monitoring during language switching in an
experimental setting facilitates the monitoring process within
cognitive control and the training on inhibitory control during
language switching facilitates the inhibitory control process
within cognitive control.
As mentioned above, these findings are in line with the
adaptive control hypothesis (Green and Abutalebi, 2013), which
proposes that depending on the context, language control
processes may change the way they work or the way they
cooperate with other processes. The findings in the present
study show the after-effects adapting to the contexts. Specifically,
the bilingual facilitative effect in monitoring and inhibitory
control reflected the adaptive changes to the demand imposed
by the language switching training contexts. During the training
sessions, participants needed to name the target number in
accordance with the flag cue. To do so, participants had
to choose the accurate language by continuously monitoring
the flag cue, then inhibit the interference from the non-
target language using inhibitory control processes. Such intense
training on monitoring and inhibition during language switching
in an experimental setting led to facilitative effects on
corresponding domains of EC.
In sum, combined with the observed positive relationship
between BLC and the two components of EC (i.e., monitoring
and inhibitory control) in Experiment 1, and the empirical
evidence for the sources of such positive relationship in
Experiment 2, it is reasonable to believe that the observed positive
relationship between BLC and EC is reliable, at least in an
experimental setting.
Limitations
One limitation of the current study is the lack of training the
control group received in the first experiment. These leaves open
whether the observed training effects are related to training in
general or to the specific language training that the experimental
group underwent. Particularly, it is unclear as to whether it is
the “switching” aspect or the “language” aspect of the training
that is driving the effects, as other studies have shown that other
more general task-switching training also improves monitoring
and inhibitory control (e.g., Karbach and Kray, 2009). More
research needs to be conducted to examine these issues further.
Finally, another limitation is that the experimental groups
were not well matched at pre-training, although we divided
the participants randomly. This limitation may bring some
confounding effects as these participants may have been closer
to ceiling performance and thus, may not have had that much
room to improve.
CONCLUSION
The present study reveals that there is a positive relationship
between BLC and two components of EC: monitoring and
inhibitory control, and such positive relationship can be observed
as a result of short-term training on both monitoring and
inhibitory control during language switching in an experimental
setting. These findings not only inform the ongoing debate on the
relationship between BLC and EC, but they also open the door for
discussion as to how these issues can be explained through other
theoretical lenses. Future studies are encouraged and merited that
will help explore the potential cognitive benefits of bilingualism
through complementary lines of thought.
DATA AVAILABILITY
The datasets generated for this study are available on request to
the corresponding author.
ETHICS STATEMENT
This study was carried out in accordance with the
recommendations of the Human Research Ethics Committee
for Non-Clinical Faculties at the School of Psychology of South
China Normal University with written informed consent from
all subjects. All subjects gave written informed consent in
accordance with the Declaration of Helsinki. The protocol was
approved by the Human Research Ethics Committee for Non-
Clinical Faculties at the School of Psychology of South China
Normal University.
AUTHOR CONTRIBUTIONS
CL, LJ, and RW designed the study. CL, LJ, and XS acquired and
analyzed the data. CL, LJ, CY, JS, and RW wrote the manuscript.
FUNDING
This research was supported by the National Social Science
Foundation of China (19AYY009).
ACKNOWLEDGMENTS
We thank Prof. Ping Li for his comments on the experimental
design and Errong Zhang for her help in the data collection.
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Conflict of Interest Statement: The authors declare that the research was
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