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Received: August 31, 2021. Revised: October 17, 2021. Accepted: October 18, 2021
© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com
Cerebral Cortex, 2022, 32, 3224–3242
https://doi.org/10.1093/cercor/bhab411
Advance access publication date: 9 December 2021
Original Article
Cross-task adaptation effects of bilingual language
control on cognitive control: a dual-brain EEG
examination of simultaneous production and
comprehension
Huanhuan Liu1, 2, †,Wan qin g L i1, 2, †,Mingyue Zuo1,2,Fenqi Wang3,Zibin Guo1, 2, John W. Schwieter4
1Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029, China,
2Key Laboratory of Brain and Cognitive Neuroscience, Dalian, Liaoning Province 116029, China,
3Department of Linguistics, University of Florida, Gainesville, FL 32611-5454, USA,
4Language Acquisition, Cognition, and Multilingualism Laboratory/Bilingualism Matters @ Wilfrid Laurier University, Waterloo, ON N2L 3C5, Canada
*Address correspondence to Huanhuan Liu, Research Center of Brain and Cognitive Neuroscience, Liaoning Normal University, Dalian 116029,China.
Email: abcde69503@126.com.
†Authors H. Liu and W. Li equally contributed to this study
For bilinguals, speaking and listening are assisted by complex control processes including conf lict monitoring and inhibition. However,
the extent to which these processes adapt to linguistic and situational needs has been examined separately for language production
and comprehension. In the present study, we use a dual-EEG to record the carry-over effects of language control on general cognitive
control in three language contexts (single-first language [L1], single-second language [L2], and mixed). Chinese learners of English were
placed in dyads in which one participant was asked to name pictures while the other listened.Interleaved after each naming/listening
trial were flanker trials. The results from picture naming and listening revealed higher delta and theta synchronization in the single-
L2 and mixed contexts compared with the single-L1 context and higher theta synchronization in the mixed context compared with
the single-L2 and single-L1 contexts. The results from the interleaved flanker trials demonstrated that inhibition was adaptively
generalized in the single-L2 and mixed contexts. Altogether, the findings support the natural adaptation of language control to
cognitive control and underscore the importance of linguistic context. We argue that these adaptive patterns have the potential
to affect corresponding control processes across language and cognitive control tasks.
Key words:adaptative control; bilingual language control; cognitive control; dual-EEG; interbrain synchronization.
Introduction
If experience with language influences and shapes
thought (Whorf 1956), how does experience with two
or more languages factor in? Bilinguals are a unique
example of how the brain orchestrates a series of exec-
utive functions, such as conf lict monitoring, updating,
inhibitory control, and working memory, as needed
to regularly engage in/with two or more languages
(Bialystok et al. 2005;Abutalebi and Green 2007;Kovács
and Melher 2009;Prior and Gollan 2013;Calvo and
Bialystok 2014;Verreyt et al. 2016;Declerck et al. 2017).
For instance, the ability for bilinguals to switch back
and forth between their two languages or to speak
in one language without intrusions from the other
is facilitated by complex control processes that react
and adjust to the various linguistic situations in which
bilinguals find themselves (Abutalebi et al. 2012). This
claim is at the core of the Adaptive Control Hypothesis
(Green and Abutalebi 2013) which argues that bilingual
experiences require different processes of language
control that adapt to communicative contexts and needs.
Consequently, bilinguals have flexible language control
mechanisms that allow them to proactively/globally
inhibit second-language (L2) interference in a predom-
inantly first-language (L1) context or to reactively/
locally inhibit L1 interference in a predominantly L2
context (Green and Abutalebi 2013;Timmer et al. 2019;
Declerck 2020).
A growing body of research using a cross-task adap-
tation paradigm has found a relationship between
language control and general cognitive control in both
language production (Jiao et al. 2020a) and comprehen-
sion (Jiao et al. 2019;Jiao et al. 2020b;Jiao et al. 2021). In
the context of these studies, cross-task adaptation refers
to the observable effects that conflict resolution has in
one task on a subsequent task (Freitas et al. 2007). This
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Liu et al. |3225
adaptation is in line with the congruency sequence effect
that emerges in selective attention tasks (Egner 2007)
and refers to the observation that congruency effects
are smaller when following an incongruent stimulus
than when following a congruent one. According to the
conflict monitoring account (Botvinick et al. 2001), this
effect reflects conflict-driven adjustments in cognitive
control (but see Hommel et al. 2004, who argue that
it may reflect episodic memory effects of stimulus–
response association). In situations of congruency effects
when following incongruent stimuli, cognitive control
has been put into conflict resolution and bound with spe-
cific tasks, whereas when following congruent stimuli,
cognitive control must be called upon to resolve conflicts
(Notebaert and Verguts 2008,2011;Braem et al. 2014;
Zhao et al. 2020). These differences can be interpreted
as “automatic adaptive changes in cognitive control
as a result from homogeneous conflict resolutions
mechanisms” (Yuan et al. 2021, para. 4; see also Egner
2008,2014). Different language contexts will incur
different magnitudes of cognitive control. Therefore, a
single language context can be understood as a conflict-
free task compared with a mixed-language context.
The electrophysiological data elicited in the studies by
Jiao and colleagues suggested that compared to single-
language contexts (i.e., situations in which either the L1
or L2 is exclusively used), mixed contexts (i.e., situations
in which both languages are involved) elicited more neg-
ative N2s and attenuated P3s in a successive cognitive
control task. These findings indicate that the improve-
ment of conflict monitoring and resolution caused by
frequent language switching in the mixed context affects
cognitive control. To our knowledge, however, no study
has yet examined both production and comprehension
within the same experimental setting. Given that com-
munication is an interactive activity in which speakers
and listeners exchange information (Pickering and Gar-
rod 2004), a novel design which incorporates both pro-
duction and comprehension is merited to better under-
stand whether or how language control processes adapt
to domain-general cognitive control in different com-
municative situations (e.g., single- and mixed-language
contexts).
In the present study, we designed an experiment
which included interleaved flanker trials in a joint
naming-listening task. The experiment involved dyads
of participants in which one individual named pictures
in single- and mixed-language contexts, the other
participant listened, and both responded to flanker
trials. Throughout the experiment, temporal coupling of
the two participants’ brain activity was recorded with
dual-EEG and analyzed by phase-locking value (PLV).
PLV has been used as an index of interbrain phase
synchronization between production and comprehen-
sion in previous work (Lachaux et al. 1999;Tognoli et
al. 2007;Pérez et al. 2017;Liu et al. 2019). Speakers
and listeners reach higher synchronization in delta
oscillation by suppressing cross-language interference
(Liu et al. 2019). However, with more and more speak-
ing and listening, theta synchronization decreases,
implying that the engagement of control processes
attenuates. Electrophysiological evidence has shown
that the frontal-midline N2 component is associated
with theta oscillations, reflecting the top-down goal-
direction typical in conflict monitoring, inhibition, and
task updating (Kirmizi-Alsan et al. 2006;Cavanagh et
al. 2009;Schmiedt-Fehr et al. 2011;Cavanagh et al.
2012;Huster et al. 2013;Cavanagh and Frank 2014).
The frontopariental P3 component is closely associated
with delta oscillations and reflects cognitive control of
interference suppression/inhibition (Kamarajan et al.
2004;Knyazev 2007;Knyazev et al. 2009;Putman 2011;
Cohen and Donner 2013;Huster et al. 2013;Cavanagh
and Frank 2014;Cohen 2014;Helfrich et al. 2019). In
line with these studies, the present investigation uses
event-related delta and theta synchronization as indexes
of control mechanisms corresponding to P3 and N2
components, respectively, to examine the influence of
language control on domain-general cognitive control.
The Present Study
By examining interbrain synchronization through a
novel experimental design that examines simultaneous
production by one participant and comprehension by
another, our findings will offer new insight on the
relationship between language and cognitive control
and will have important implications for understanding
the underpinnings of human communication. We
hypothesize that brain oscillations of participants who
listen will temporally resonate with brain oscillations of
the speakers with whom they are paired. Compared with
the single-L1 context, we expect that increased delta
and theta synchronization in the single-L2 and mixed
contexts will emerge due to the sustained inhibition
of the dominant L1, conflict monitoring and updating
of language schema, and transient inhibition of cross-
language interference. Consequently, we anticipate
that the brief exposure to the mixed context in which
participants must constantly activate and inhibit both
languages will elicit similar delta and theta synchroniza-
tion for the speaker and listener participants and lead
to improved domain-general cognitive control in flanker
trials.
Method
Participants
Research ethics approval was granted by the Research
Center of Brain and Cognitive Neuroscience at Liaoning
Normal University. The calculated sample size was 22
using G.power 3.1.9.6 according to the following set-
tings: F-tests >ANOVA: Repeated measures, within fac-
tors, Effect size f=0.25, αerror probability =0.05, cor-
relation among repeat measures=0.5, Power (1-βerror
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3226 |Cerebral Cortex, 2022, Vol. 32, No. 15
probability) =0.8, Number of groups =2, Number of mea-
surements =5, and nonsphericity correct ∈=1. Accord-
ingly, 23 dyads L1 Chinese learners of L2 English (N=40
female, 6 male; Mage =24 years, SDage =1 year) were
recruited from the aforementioned university. All partic-
ipants were right-handed with normal or corrected-to-
normal vision. They reported having no history of neuro-
logical or psychological impairments nor were currently
taking a psychoactive medication.
After providing written informed consent to partici-
pate in the study, the participants were randomly divided
into 23 dyads, each consisting of individuals who were of
the same gender and were not familiar with one another.
In each dyad, participants were randomly assigned to
either an A role if they were to name pictures and a B
role if they were to listen. Except for this naming and
listening, the participants had no further contact. Two
dyads were excluded from the study because of excessive
EEG data artifacts during the preprocessing stage.
At the time of data collection, the participants had
been studying English as an L2 for an average of 10 years.
To assess their L1 and L2 proficiency, we asked partic-
ipants to rate their reading, writing, speaking, and lis-
tening skills on a six-point scale in which “6” indicated
highest fluency and “1” indicated no fluency. Paired sam-
ple t-tests demonstrated that their proficiency ratings
were significantly higher for all four language skills in the
L1 compared with the L2 (see Table 1). We also admin-
istered the Oxford Placement Test (Allan 2004) prior to
the experimental procedures. The participants’ mean
score was 37.55 (SD=2.68), which is at the upper end
of the test’s 21–40 range that is equivalent to level A2
in the Common European Framework of Reference for
Languages.
Materials
We chose 68 black-and-white line drawings (Snodgrass
and Vanderwart 1980; standardized by Zhang and Yang
2003) of which 50 were used in the experiment and 18
were used in a practice block (see Appendix Table A1).
The pictures in the practice block did not appear in
the formal experiment. We consulted a word frequency
database for Chinese (Cai and Brysbaert 2010) and
English (Brysbaert and New 2009). T-tests revealed no
significant difference between the frequency of the L1
and L2 names (L1: M=77.44, SD =107.30; L2: M=77.17,
SD =111.29, t(67) =−0.28, P=0.78), although there were
large SDs. Thus, a separate group of participants
(N=26, Chinese-L1, English-L2) rated how familiar they
were with the L1 and L2 names of the experimental
and practice pictures on a five-point scale (1 =“very
unfamiliar,” 5 =“very familiar”). T-tests again revealed
no significant difference between their familiarity
with the pictures names in the two languages (L1:
M=4.82, SD =0.14, L2: M=4.83, SD =0.13, t(67) =−1.10,
P=0.28). Refer to the appendix to see a list of the
picture names in Chinese and English along with
their familiarity and frequency means and standard
deviations.
Interleaved after each joint naming-listening trial was
a flanker trial which appeared on a black background
screen as a row of five white arrows: one central target
arrow and two flanking arrows on each side.
Design and Procedure
Flanker Task
Prior to the joint naming-listening task, we adminis-
tered a traditional flanker task to each participant to
see whether the typical flanker effects would emerge
without contextual interference. This flanker task was
conducted in a quiet room separate from the experimen-
tal room and included 50 congruent and 50 incongru-
ent trials. As is typical in flanker-type tasks, the par-
ticipants were asked to determine whether the central
target arrow was congruent or incongruent with the
flanking arrows. Participant A used the “F” and “J” keys
and Participant B used the “C” and “N” keys to respond
to congruent and incongruent flanking arrows, respec-
tively.
Joint Naming-Listening Task with Interleaved Flanker
Trials
After the flanker task, we administered the joint naming-
listening task with interleaved flanker trials to the dyads
of participants. During the experiment, each dyad sat
side-by-side in front of the same computer screen. There
was an opaque foam board (1 m ×0.5 m) between the two
individuals in order to obstruct their view of each other
and to divide the computer screen into two equal parts,
with the left half being visible only to Participant A and
the right half only to Participant B.
The two EEG recording systems were synchronized
using a pulse signal from the control server computer
which was delivered to each EEG system simultaneously.
Two identical ANT amplifiers with independent grounds
were optically coupled to the computer and recorded
through the same software interface, ensuring synchro-
nization between the two electrode sets. A microphone
was used to record response times (RTs) of picture nam-
ing and two keyboards (i.e., one for Participant A, one
for Participant B) were used to record flanker RTs and
accuracy. Naming accuracy was digitally recorded with
incorrect responses being removed prior to data analyses.
The experimenter explained the instructions to each
dyad while the researcher applied gel to the electrode
caps. Prior to the experiment,the participants were asked
to familiarize themselves with the L1 and L2 picture
names on a PowerPoint presentation which they con-
trolled on the computer. After this, a practice block of 18
pictures in the mixed-language context was conducted.
The procedure for the practice and subsequent exper-
imental blocks was the same. Figure 1 (upper panel)
displays the full sequence of one trial (i.e., one nam-
ing/listening trial followed by one flanker trial). In each
trial, a picture with a red or blue border simultaneously
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Liu et al. |3227
Tab l e 1 . Mean (and SDs) self-ratings of L1 and L2 proficiency
Language skill Chinese L1 English L2 t P
Reading 5.52 (0.71) 2.36 (0.48) 29.51 <0.001
Writing 5.38 (0.58) 4.33 (0.61) 7.70 <0.001
Speaking 5.69 (0.46) 3.19 (0.45) 25.54 <0.001
Listening 5.29 (0.60) 3.19 (0.55) 15.98 <0.001
Tab l e 2 . Results of the mixed-effects model analysis performed
on RT and accuracy data from the flanker task and joint
naming-listening task
Predictor F P
RT
Flanker task
Congruency 7.16 0.007
Picture naming in the joint task
Context 641.50 <0.001
Interleaved flanker trials in the joint task
Context 36.14 <0.001
Congruency 49.45 <0.001
Context ×Congruency 3.48 0.03
Accuracy
Flanker task
Congruency 2.57 0.01
Picture naming in the joint task
Context <0.001 0.999
Interleaved flanker trials in the joint task
Context 4.15 0.17
Congruency 42.46 <0.001
Context ×Congruency 3.20 0.03
Tab l e 3 . Results of the linear mixed model analyses separately
performed on the delta and theta synchronization of picture
naming and interleaved flanker trials
Predictor F P
Picture naming (delta)
Context 6.45 0.002∗∗
Surrogate 0.09 0.77
Context ×Surrogate 6.91 0.002∗∗
Picture naming (theta)
Context 5.54 0.004∗∗
Surrogate 5.33 0.02∗
Context ×Surrogate 4.67 0.01∗
Interleaved flanker trials (delta)
Context 6.91 0.002∗∗
Surrogate 82.88 <0.001∗∗∗
Congruency 0.30 0.59
Context ×Surrogate 8.58 <0.001∗∗∗
Context ×Congruency 7.14 <0.001∗∗∗
Surrogate ×Congruency 0.43 0.51
Context ×Surrogate ×Congruency 5.39 0.005∗∗
Interleaved flanker trials (theta)
Context 3.12 0.05∗
Surrogate 0.26 0.61
Congruency 1.15 0.28
Context ×Surrogate 3.38 0.04∗
Context ×Congruency 6.75 0.001∗∗
Surrogate ×Congruency 1.12 0.29
Context ×Surrogate ×Congruency 6.49 0.002∗∗
∗<0.05. ∗∗<0.01. ∗∗∗<0.001.
appeared in the center of the left and right sides of the
dyad’s shared screen. The color square was a cue that
indicated in what language the picture was to be named:
In the single-L1 block, all pictures appeared in a red box;
in the single-L2 block, pictures appeared in a blue box;
and in the mixed block, pictures were displayed in either
red or blue. The picture appeared on the screen until a
response was uttered by Participant A or after 1500 ms.
A blank screen of 500 ms was then presented followed
by a flanker trial that appeared simultaneously on both
sides of the screens and remained until both participants
responded on their keyboards or after 2000 ms. Finally, a
blank screen appeared for 1000 ms before another trial
began.
After the practice, we ensured that the participants
had no questions before continuing on to the experiment,
which included four blocks: a single-L1 block, a single-L2
block, and two mixed L1-L2 blocks. The order of the three
contexts was counterbalanced across the dyads. In the
single-language blocks,the 50 pictures were repeated two
times, with at least 20 trials between each appearance.
In the mixed-language blocks, the 50 pictures appeared
only once in each language. Although the response lan-
guage in the mixed blocks was randomly arranged, we
ensured that the maximum run length was two trials
(i.e., the response language switched either every trial or
every other trial). In all four blocks, flanker trials were
interleaved after each picture such that there were 100
naming/listening trials and 100 flanker trials in each
block. Congruency of the flanker trials was randomized
throughout the experiment with half being congruent
and the other half incongruent.
To ensure that Participant B was listening while Partic-
ipant A was naming pictures,in each block, we randomly
placed eight filler trials in the form of a bolded right
or left arrows (see Fig. 1, lower panel). When a white
arrow appeared for Participant A (but was not visible
to Participant B), Participant A verbally indicated the
direction of the arrow by uttering “left” or “right” and
Participant B pressed either the “C” key (left) or “N”(right).
The filler trials did not form part of the data analy-
ses.
Data Recording and Analyses
Electrophysiological data were recorded from each dyad
using two 64-channel caps with Ag/AgCl impedance-
optimized active electrodes (ANT Neuro). Standard elec-
trode sites based on the international 10–20 system were
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3228 |Cerebral Cortex, 2022, Vol. 32, No. 15
Fig. 1. Procedure of the joint naming-listening task showing the simultaneous utterance (Participant A) and comprehension (Participant B) of picture
names (upper panel) and filler items (lower panel) followed by an interleaved flanker trial. Note: The square in which pictures appeared was red or blue
to indicate naming in L1 or L2, respectively.
used and impedances were kept below 5 kΩ. The contin-
uous EEG was recorded with a sampling rate of 1000 Hz,
a low cut-off filter of 0.01 Hz, and a high cut-off filter of
100 Hz. All electrode sites were referenced online to the
electrode placed over the CPz and rereferenced offline to
the average of the right and left mastoids.The EEG signal
was resampled to 500-Hz offline. Using EEGLAB for data
processing, the EEG data were consistent with the trial
of the retained behavioral data, and electroencephalo-
graphic activity was filtered online within a high-pass
filter for 0.01 Hz and a low-pass filter for 30 Hz. To reduce
ocular movement artifacts, an independent component
analysis (Delorme and Makeig 2004) was conducted on
the EEG data. A 100-ms prestimulus (i.e., naming picture)
period was used as a baseline. We analyzed 600 ms after
the baseline because after this time point, the earliest
speech production artifacts started to contaminate the
EEG signal. In the preprocessing stage, the time series of
each dyad were aligned,and the number of trials retained
between each condition was the same for each dyad.Due
to the fact that we focused on the cross-task adaptation
which could be reflected by the synchronization covaria-
tion of the naming-listening task and the flanker task, we
kept the same data from the 21 dyads in these two tasks.
Behavioral data were obtained from both the flanker
task and the joint naming-listening task with interleaved
flanker trials. We excluded the following trials from
the analyses: filler trials and trials that followed the
filler one; null trials; trials in the flanker task that
were lower than 200 ms and higher than 1000 ms; and
trials lower than 200 ms and higher than 1300 ms in
the joint naming-listening task. Furthermore, data from
the first two trials of each block and the naming RT
beyond M±3SD per participant were also excluded. No
analyses were performed on accuracy (flanker task:
97.30%; picture naming in the joint naming-listening
task: 97.95%; interleaved flanker trials in the joint
naming-listening task: 97.44%). Flanker effects were
calculated by the difference between congruent and
incongruent trials in the flanker task. Analyses were
conducted using mixed-effects models with crossed
random effects for Subjects and Items using R software
(version 3.6) (lme4 and lmerTest package, Bates et al.
2014;Kuznetsova et al. 2017). The reason for using
mixed-effects models was to allow random effects of
subjects and items to be considered simultaneously,
making the data modeling more appropriate and the
results generalizable to other subjects and items.
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Liu et al. |3229
The reported P-values were adjusted with Bonferroni
correction.
Interbrain Synchronization Data
We used PLV to estimate the synchronization of the
participants’ brain signals (Tognoli et al. 2007;Pérez et
al. 2017;Liu et al. 2019) for two frequency bands (1–
3 Hz delta and 4–7 Hz theta) at each time point between
each pair of participants. Since each participant in the
dyad has 35 effective electrodes (35×35), there are 1224
possible combinations of electrode pairs. For example,
in the F2-F5 pair, the PLV was calculated using the F2
from the Participant A (i.e., speaker) and the F5 from
Participant B (i.e., listener). The calculation formula of
the PLV is as follows:
PLVi,k=1
N|
N
t=1
expj(φ(t)−φk(t))|.
In the formula, iand krepresent the EEG signals of F2
(language production) and F5 (language comprehension),
Nrepresents the sampling points of time window, and
is the phase of the trial starting from time tat channel i.
When the PLV value is equal to 1, the EEG signals of two
channels were perfectly phase-locked with each other.
Conversely, if the value is 0, they are not synchronized at
all. A 300-ms overlapping moving time window was used
in a time series of 20 400 ms.
To eliminate the possibility that our results were
obtained by chance,we compared the PLVs obtained from
the experiment against those obtained from surrogate
data. The surrogate data were created by scrambling
the sequence of the time series in each pair of channels
and then calculating the average PLV for each pair of
channels (without one-to-one corresponding time points)
1000 times. We conducted a linear mixed-effects (lme)
model to compare the PLV of experimental data and ran-
dom data with Context (single-L1, single-L2, mixed) and
Congruency (congruent, incongruent) as fixed effects.
The PLV values from the combination of the electrode
pairs in each context (e.g., single-L1: FCz-FC2, single-L2:
P1-C1, mixed: F2-F5) were submitted to the lme model.
When the models did not converge,we removed the slope
that explained the least amount of variance until the
model converged. Parameters were estimated with the
restricted maximum likelihood approach,and the results
from the best-fitting model representing the most signif-
icant times of electrode pair combinations are reported.
Behavioral Results
Flanker Task
RT Results
The best-fitting mixed-effect model of the flanker task
used log RT as the dependent variable. The mixed-
effects model for RT included Congruency (Congruent,
Incongruent) as the fixed effect, as well as the by-subject
and by-item random intercepts. There was a main effect
for Congruency such that incongruent trials (M=512 ms,
SD =118 ms) were significantly slower than congruent
trials (M=506 ms, SD =107 ms), indicating a typical
flanker effect (see Table 2).
Accuracy Results
For the analyses of accuracy, there was a significant main
effect for Congruency: the accuracy in incongruent trials
(M=0.95, SD =0.22) was higher compared with congru-
ent trials (M=0.94, SD =0.23).
Picture Naming in the Joint Naming-Listening
Task
RT Results
The best-fitting mixed-effects model for the picture-
naming analysis treated log-transformed RT as the
dependent variable. The linear mixed-effects model for
RT included Context (single-L1, single-L2, mixed) as
the fixed effect, as well as the by-subject and by-item
random intercepts. The mixed context was treated as
the baseline in the linear mixed-effects model. As shown
in Table 2, the results of the best-fitting model revealed a
main effect for Context such that picture naming in the
mixed context (M=877 ms, SD =168 ms) was slower than
in both the single-L1 context (M=753 ms, SD =157 ms;
β=−0.16, SE =0.01, t=−31.26, P<0.001) and the single-
L2 context (M=767 ms, SD =156 ms; β=−0.14, SE =0.01,
t=−27.17, P<0.001). These findings are visualized in
Figure 2.
Accuracy Results
The generalized linear mixed-effects model for accuracy
included Context (single-L1, single-L2, mixed) as fixed
effects, as well as the by-subject random intercepts. As
shown in Table 2, there was no effect for the results of
the best-fitting model for accuracy (Fig. 3).
Interleaved Flanker Trials in the Joint
Naming-Listening Task
RT Results
To examine the performance of the interleaved flanker
trials that appeared throughout the joint naming-
listening task, results of the best-fitting mixed-effect
model used log RT as the dependent variable. The
linear mixed-effects model for RT included Context
(single-L1, single-L2, mixed context) and Congruency
(Congruent, Incongruent) as fixed effects, as well as
the by-subject and by-item random intercepts. Using
the mixed context as the baseline for RTs, the main
effect for Context was significant, with slower RTs in
the mixed-language context (M=537 ms, SD =109 ms)
than in the single-L2 context (M=522 ms, SD =108 ms,
β=−0.02, SE =0.01, t=−4.32, P<0.001), but not when
compared with the single-L1 context (M=533 ms,
SD =102 ms, β=−0.01, SE =0.01, t=−0.71, P=0.96) (see
Table 2). Using the L1 context as the baseline, flanker
responses in the single-L1 context were slower than
those in the single-L2 context (β=−0.02, SE =0.01,
t=−4.39, P<0.001). The main effect of Congruency was
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3230 |Cerebral Cortex, 2022, Vol. 32, No. 15
Fig. 2. Mean RTs and accuracy for picture naming in single-L1, single-L2, and mixed-language contexts. Note: White circles and white lines represent
participants’ mean and median, respectively, and dark rectangular box plots represent the quartiles 25% and 75%. ∗∗∗P<0.001.
also significant, with slower RTs in congruent trials
(M=537 ms, SD =109 ms) than in incongruent trials
(M=527 ms, SD =105 ms), indicating a reversed flanker
effect.
Importantly, there was a significant interaction
between Context ×Congruency. Congruent trials (single-
L1: M=540 ms, SD =103 ms; single-L2: M=528 ms,
SD =109 ms; mixed: M=540 ms, SD =111 ms) were
slower than incongruent trials (single-L1: M=527 ms,
SD =99 ms; β=0.02, SE =0.01, t=4.66, P<0.001; single-
L2: M=517 ms, SD =105 ms; β=0.02, SE =0.01, t=4.60,
P<0.001; mixed: M=533 ms, SD =107 ms; β=0.01,
SE =0.01, t=2.65, P=0.01), indicating a reversed flanker
effect in all three conditions. To further investigate the
significant interaction, using the mixed context as the
baseline, we found that the flanker effect in the single-L1
and single-L2 contexts did not differ from mixed context
(mixed vs. single-L1: β=−2.496, SE =6.255, t=−0.399,
P=0.96; mixed vs. single-L2: β=−10.251, SE =6.255,
t=−1.639, P=0.11). Similarly, using the single-L1 context
as the baseline, the flanker effect in the single-L2 and
mixed contexts did not differ from single-L1 context
(single-L1 vs. L2: β=−7.755, SE =6.255, t=−1.240,
P=0.22; single-L1 vs. mixed: β=−2.496, SE =6.255,
t=−0.399, P=0.69).
Accuracy Results
The generalized linear mixed-effects model for accu-
racy included Context (single-L1, single-L2, mixed)
and Congruency (Congruent, Incongruent) as fixed
effects, as well as the by-subject and by-item random
intercepts. Using the mixed context as the baseline for
accuracy, the main effect of Congruency was signif-
icant: congruent trials (M=0.97, SD =0.18) were less
accurate than incongruent trials (M=0.98, SD =0.13),
indicating no speed-accuracy∗∗∗ tradeoffs. Additionally,
there was a significant interaction between Context ×
Congruency for accuracy. Congruent trials (single-L1:
M=0.97, SD =0.18; single-L2: M=0.97, SD =0.17; mixed:
M=0.96, SD =0.19) were less accurate than in incon-
gruent trials in all three contexts (single-L1: M=0.99,
SD =0.11; β=−1.17, SE =0.25, z=−4.67, P<0.001; single-
L2: M=0.99, SD =0.10; β=−1.11, SE =0.27, z=−4.13,
P<0.001; mixed: M=0.98, SD =0.15; β=−0.53, SE =0.14,
z=−3.68, P<0.001), indicating a reversed flanker effect
regardless of language condition. To further investigate
this significant interaction, we ran a generalized linear
mixed-effects model which included Context (single-
L1, single-L2, mixed context) as fixed effects, as well
as by-subject random intercepts. Using the mixed
context as a baseline, the flanker effect was greater
in both the single-L1 (M=0.023, SD =0.03) and single-
L2 contexts (M=0.018, SD =0.03) compared with the
mixed context (M=0.015, SD =0.03) (single-L1 vs. mixed:
β=0.01, SE <0.001, t=19.00, P<0.001; single-L2 vs.
mixed: β=0.003, SE <0.001, t=7.82, P<0.001). Likewise,
using the single-L1 context as the baseline, the flanker
effect was bigger in the single-L1 context than both
the single-L2 and mixed-contexts (single-L2 vs. single-
L1: β=−0.005, SE <0.001, t=−9.81, P<0.001; mixed vs.
single-L1: β=−0.01, SE <0.001, t=−19.00, P<0.001).
In sum, the typical flanker effect (faster RTs in con-
gruent trials than in incongruent trials), which we found
in a separate flanker task, was no longer apparent when
interleaved in a joint naming-listening task. On the con-
trarily, we found a reversed flanker effect for both RT
and accuracy regardless of whether performing in single-
language or mixed-language blocks. Importantly,flanker
effects were greater in the single-L2 and mixed context
than in the single-L1 context, suggesting that cognitive
control was sensitive to the degree of language control
required.
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Liu et al. |3231
Correlation Analyses of RTs within Dyads
To investigate whether speaker and listener participants
were collaboratively performing the flanker task, we con-
ducted a Pearson correlation analysis on trial-to-trial RTs
within the dyads. We found significant positive corre-
lations between speaker and listener dyads in all three
language contexts (single-L1: r=0.075, P=0.001; single-
L2: r=0.058, P=0.01; mixed: r=0.039, P=0.02) (see
Fig. 4). These findings further indicate that the changes
in the flanker task are causally related to the interleaved
language task (We would like to thank an anonymous
reviewer for suggesting that we conduct and include
these correlation analyses. It should be noted that the
RTs reflect the sum of all psychological processes and
therefore do not best reflect the specific components
analyzed when using PLV.).
Interbrain Synchronization Results
Picture Naming in the Joint Naming-Listening
Task
Delta Oscillation (1–3 Hz)
A mixed-effects model based on the mixed context was
established for delta oscillation and surrogate data, with
Context and Surrogate (Experimental, Random) as fixed
effects and Subject intercepts as random-effects. The
selected electrode pairs for each context were: FCz-FC2
for single-L1; P1-C1 for single-L2; and F2-F5 for mixed.
As shown in Table 3 and Figure 4, there was a significant
main effect for Context in which delta synchronization
was higher in the mixed context relative to the single-
L1 context (β=−0.05, SE =0.01, t=−4.72, P<0.001).
Delta synchronization was also higher in the single-L2
context compared with the single-L1 context (β=0.06,
SE =0.01, t=4.62, P<0.001). There was no difference in
delta synchronization between the mixed and single-
L2 context (β=0.01, SE =0.01, t=1.13, P=0.26) (see
Fig. 5).
A significant interaction between Context ×Surrogate
revealed that for the experimental data, the delta syn-
chronization in the mixed context was higher than the
single-L1 context (β=0.05, SE =0.01, t=4.72, P<0.001),
but no different than in the single-L2 context (β=−0.01,
SE =0.01, t=−1.13, P=0.50). In addition, delta synchro-
nization was higher in the single-L2 context compared
with the single-L1 context (β=−0.06, SE =0.01, t=−4.62,
P<0.001). In contrast, for the surrogate data, there was
no significant difference between the three contexts
(mixed vs. single-L1: β=−0.001, SE =0.01, t=−0.09,
P>0.99; mixed vs. single-L2: β<−0.001, SE =0.01,
t=−0.01, P>0.99; single-L1 vs. single-L2: β<−0.001,
SE =0.01, t=0.07, P>0.99), indicating that the delta
synchronizing in the experimental data, compared with
the surrogate data, was likely not due to chance.
Theta Oscillation (4–7 Hz)
As in the delta synchronization analysis, a mixed-effects
model based on the mixed context was established
for theta oscillation and surrogate data, with Context
and Surrogate (Experimental, Random) as fixed effects
and Subject intercepts as random-effects. The selected
electrode pairs in the theta synchronization analysis
for each context were: FC5-F4 for single-L1; C6-C6 for
single-L2; and F6-C5 for mixed. As shown in Table 3,
the main effect of Context indicated higher theta
synchronization in the mixed context compared with
the single-language contexts: (mixed vs. single L1:
β=−0.03, SE =0.01, t=−3.45, P<0.001; mixed vs. single-
L2: β=−0.03, SE =0.01, t=−3.54, P<0.001), but no
difference between the single-L2 and single-L1 contexts
(β<0.001, SE =0.01, t=−0.07, P=0.946) (see Fig. 6).
The interaction between Context ×Surrogate showed
that, for the experimental data, higher theta synchro-
nization was observed in the mixed context compared
with the single-language contexts (mixed vs. single-
L1: β=0.03, SE =0.01, t=3.45, P=0.002; mixed vs.
single-L2: β=0.03, SE =0.01, t=3.54, P=0.001), but no
difference between single-L1 and single-L2 contexts
(L1-L2: β<0.001, SE =0.01, t=0.07, P>0.99). In con-
trast, for the surrogate data, the synchronization of
three contexts did not differ from one other (mixed
vs. single-L1: β<0.001, SE =0.01, t=0.07, P>0.99;
mixed vs. single-L2: β=0.01, SE =0.01, t=0.22, P=0.97;
single-L1 vs. single-L2: β=0.001, SE =0.01, t=0.12,
P>0.99).
Interleaved Flanker Trials in the Joint
Naming-Listening Task
Delta Oscillation (1–3 Hz)
A mixed-effects model based on the mixed context was
established for delta oscillation and Surrogate, with Con-
text, Congruency, and Surrogate (Experimental, Random)
as fixed effects and Subject intercepts as random-effects.
The selected electrode pairs for each context listed were:
CP4-FC2 for single-L1; P1-C1 for single-L2; and CP6-F5 for
mixed. As shown in Table 3, the main effect of Context
showed that delta synchronization was higher in the
mixed context relative to the single-L2 context (β=0.05,
SE =0.01, t=3.96, P<0.001). Delta synchronization was
also higher in the single-L1 compared with the single-L2
context (β=0.05, SE =0.02, t=2.39, P=0.018). However,
there was no significant difference between the mixed
and single-L1 contexts (β=−0.002, SE =0.01, t=−0.13,
P=0.894) (see Fig. 7).
The two interactions between Context ×Surrogate
and Context ×Congruency were significant. More
importantly, in the experimental data, a three-way
interaction between Context ×Congruency ×Surrogate
revealed that delta synchronization in congruent trials
was higher than in incongruent trials in the mixed
context (β=0.03, SE =0.01, t=3.23, P=0.001) and the
single-L2 context (β=0.05, SE =0.02, t=3.0, P=0.003),
while the delta synchronization of incongruent trials
was higher than congruent trials in the single-L1
context (β=−0.05, SE =0.02, t=−3.38, P<0.001). There
was no significant difference between congruent and
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3232 |Cerebral Cortex, 2022, Vol. 32, No. 15
Fig. 3. Mean RTs and accuracy for the effects from the flanker task and from interleaved flankers in the single-L1, single-L2, and mixed-language
contexts during the joint naming-listening task. Note: In the violin plot, the white circle represents participants’ mean, the white line reflects the
median, and the box plot shows the quartiles (75% and 25%). ∗∗P<0.01; ∗∗∗P<0.001.
incongruent trials in each context of the surrogate data
(mixed: β=0.003, SE =0.01, t=0.37, P=0.72; single-
L1: β=−0.005, SE =0.02, t=−0.30, P=0.77; single-L2:
β<0.001, SE =0.02, t=0.000, P>0.99), indicating that
the delta synchronization in the experimental data was
not caused by chance.
Theta Oscillation (4–7 Hz)
Again, a mixed-effects model based on the mixed context
was established, this time for theta oscillation and
Surrogate, with Context, Congruency, and Surrogate
(Experimental, Random) as fixed effects and Subject
intercepts as random-effects. The selected electrode
pairs for each context were: FC5-F4 for single-L1; F3-
FC6 for single-L2; and P2-P3 for mixed. As shown in
Table 3, the main effect of Context revealed that the theta
synchronization in the mixed and single-L2 contexts
was higher than that in the single-L1 context (mixed vs.
single-L1: β=−0.06, SE =0.01, t=−5.56, P<0.001; single-
L2 vs. single-L1: β=0.04, SE =0.02, t=2.18, P=0.030) but
was no different when comparing the mixed and single-
L2 contexts (β=−0.02, SE =0.01, t=−1.71, P=0.088) (see
Fig. 8).
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Liu et al. |3233
Fig. 4. RT correlations between speakers and listeners for the interleaved flanker trials of the joint naming-listening task during single-L1, single-L2,
and mixed-language contexts.
Fig. 5. Interbrain delta synchronization and coupled electrode pairs during the joint naming-listening task. Note: (A) Theinterbrain delta synchronization
obtained using a 300-ms sliding window during picture naming. (B) The average interbrain delta synchronization of experimental (top panel) and
surrogate (bottom panel) data during picture naming in each context. In the violin plot, the white circle represents participants’ mean, the white line
reflects the median, and the box plot shows the quartiles (75% and 25%). ∗∗∗<0.001. (C) The significantly coupled electrode pairs, determined by the PLV
analysis with FDR correction (P<0.05). The darker head represents the speaker, and the lighter head represents the listener.
The two interactions between Context ×Surrogate
and Context ×Congruency were significant. More impor-
tantly, for the experimental data, a significant three-way
interaction between Context ×Congruency ×Surrogate
suggested that congruent and incongruent trials were
different in the three contexts such that theta synchro-
nization in congruent trials was higher than incongruent
trials in the mixed context (β=0.04, SE =0.01, t=5.01,
P<0.001) and single-L2 context (β=0.04, SE =0.01,
t=2.82, P=0.005), whereas theta synchronization in
incongruent trials was higher than incongruent trials
in the single-L1 context (β=−0.04, SE =0.01, t=−3.06,
P=0.002). For the Surrogate data,there was no difference
between congruent and incongruent trials in the three
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3234 |Cerebral Cortex, 2022, Vol. 32, No. 15
Fig. 6. Interbrain theta synchronization and coupled electrode pairs during the joint naming-listening task. Note: (A) The interbrain theta- synchro-
nization obtained using a 300-ms sliding window during picture naming. (B) The average interbrain theta synchronization experimental (top panel) and
surrogate (bottom panel) data during picture naming provided for each context, respectively. In the violin plot, the white circle represents participants’
mean, the white line ref lects the median, and the box plot shows the quartiles (75% and 25%). ∗∗<0.01, ∗∗∗<0.001. (C) The significantly coupled electrode
pairs, determined by PLV analysis with FDR correction (P<0.05). The darker head represents the speaker, and the lighter head represents the listener.
contexts (mixed: β=0.001, SE =0.01, t=0.15, P=0.883;
single-L1: β<−0.001, SE =0.01, t=−0.01, P>0.99; single-
L2: β<−0.001, SE =0.01, t=−0.05, P=0.96), indicating
once again that synchronization in the experimental
data was not caused by chance.
To summarize, compared with the single-L1 context,
picture naming in the mixed context led to higher delta
and theta synchronization and naming in the single-
L2 context revealed higher delta synchronization as a
consequence of more language control recruited. Fur-
thermore, there was a reversed flanker effect (i.e., higher
synchronization in incongruent trials relative to congru-
ent trials) in mixed- and single-L2 contexts, but not in the
single-L1 context, as a function of the carry-over effects
of language control.
Discussion
This study examined the relationship between language
control and cognitive control during simultaneous
production and comprehension in single- and mixed-
language contexts. We first conducted a traditional
flanker task which replicated the typical flanker effect
in which participants were slower to respond to incon-
gruent versus congruent trials. Following this, we
administered a joint naming-listening task with inter-
leaved flanker trials. The results suggested that the
mixed-language context elicited slower picture-naming
latencies and higher delta synchronization compared
with the single-L1 context. The mixed-language context
also caused higher theta synchronization compared
with both single-L1 and single-L2 contexts. Furthermore,
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Liu et al. |3235
Fig. 7. Interbrain delta synchronization and coupled electrode pairs during the interleaved flanker trials in the joint naming-listening task. Note:
(A) The interbrain delta synchronization obtained using a 300-ms sliding window during interleaved flanker trials. (B) The average interbrain delta
synchronization of experimental (top panel) and surrogate (bottom panel) data during the flanker task provided for each context, respectively. In the
violin plot, the white circle represents participants’ mean, the white line reflects the median, and the box plot shows the quartiles (75% and 25%).
∗∗<0.01, ∗∗∗<0.001. (C) The significantly coupled electrode pairs, determined by PLV analysis with FDR correction (P<0.05). The darker head represents
the speaker,and the lighter head represents the listener.
picture naming in the single-L2 context compared to the
single-L1 context elicited larger delta synchronization,
but not larger theta synchronization. These findings
suggest that more recruitment of inhibition and conflict
monitoring increased synchronization and slowed
naming.
With regard to the interleaved flanker trials, the
behavioral data revealed reversed flanker effects (i.e.,
slower RTs and less accuracy in congruent trials
compared with incongruent trials) in all three language
contexts. Patterns in the interbrain synchronization data
confirmed this atypical flanker effect in the single-
L2 and mixed contexts (i.e., higher delta and theta
synchronization in congruent trials compared with
incongruent trials) but not in the single-L1 context.
Interbrain synchronization in the single-L1 context
demonstrated a typical flanker effect (i.e., higher
delta and theta synchronization in incongruent trials
compared with congruent trials). Taken together, these
behavioral and electrophysiological results indicate that
context-involved language control modulates cognitive
control.
Recruitment of Language Control Changes
Cognitive Control Synchronization
Accumulating evidence has shown that experience
with language switching improves language control
abilities that subsequently can be generalized to domain-
general cognitive control (Bialystok et al. 2005;Abutalebi
and Green 2007;Kovács and Melher 2009;Prior and
Gollan 2013;Calvo and Bialystok 2014;Verreyt et al.
2016;Declerck et al. 2017). However, these studies have
examined language control and cognitive control during
production and comprehension separately. The present
study incorporated both production and comprehension
and employed interbrain PLV to provide electrophysio-
logical evidence for the influence of language control
on cognitive control and its adaptive nature to different
language contexts.
As hypothesized, we found that language context
differentially affected cognitive control. The decreased
theta and delta synchronization and faster RTs in incon-
gruent trials compared with congruent trials demon-
strated a reversed flanker effect. However, because less
language control was recruited during picture naming
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3236 |Cerebral Cortex, 2022, Vol. 32, No. 15
Fig. 8. Interbrain theta synchronization and coupled electrode pairs during the interleaved f lanker trials in the joint naming-listening task. Note:
(A) The interbrain theta-synchronization obtained using a 300-ms sliding window during interleaved flanker trials. (B) The average interbrain theta
synchronization experimental (top panel) and surrogate (bottom panel) data during the flanker task provided for each context, respectively. In the
violin plot, the white circle represents participants’ mean, the white line reflects the median, and the box plot shows the quartiles (75% and 25%).
∗∗<0.01, ∗∗∗<0.001. (C) The significantly coupled electrode pairs, determined by PLV analysis with FDR correction (P<0.05). The darker head represents
the speaker,and the lighter head represents the listener.
in the single-L1 context, it is likely that participants
had sufficient cognitive resources to reactively monitor
and suppress incoming interference arising from the
subsequent flanker trials. Although we found a reversed
flanker effect in the RTs, the flanker effect hampered
accuracy in the single-L1 context relative to the single-L2
and mixed contexts. This indicates that reactive control
in the single-L1 context may not have been efficient
enough to monitor and inhibit interference in the flanker
trials. Under this assumption, more recruitment of
inhibition and conflict monitoring in the single-L2 and
mixed contexts likely reflects proactive control. Thus,
compared with congruent trials, participants were able
to adaptively generalize their conflict monitoring and
language control to domain-general cognitive control.
This interpretation additionally resonates with the
Dual Mechanism Control model (Braver 2012). Proactive
control is responsible for preprocessing the target-
related aspects, facilitating the processing of possible
upcoming conflicts, and suppressing potential interfer-
ence in a top-down manner (Bialystok and Feng 2009;
Braver 2012;Ma et al. 2016;Calabria et al. 2019). In
contrast, reactive control mirrors bottom-up transient
stimulus-driven goal activation mediated either by the
detection of interference or through episodic associa-
tions (Botvinick et al. 2001;Braver 2012). Similarly, the
language control observed when naming pictures in
the single-L2 and mixed contexts might exert proactive
control to subsequent domain-general cognitive control
via adaptive conflict monitoring and (sustained and
transient) inhibition. On the other hand, in the absence
of proactive control in the single-L1 context, participants
must monitor conflict and reactively suppress irrelevant
information. These findings suggest that adaption is a
carry-over effect derived from language control.
Recruitment of Language Control Increases
Interbrain Synchronization
Our results demonstrated that conflict monitoring and
inhibition of cross-language interference in a mixed-
language context caused higher delta and theta syn-
chronizations compared with the single-L1 context. The
mixed context also led to higher theta synchronization
compared with the single-L2 context. This is likely
because in the single-L2 context, individuals had to
persistently inhibit interference from the L1, eliciting
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Liu et al. |3237
higher delta synchronization relative to the L1 context.
The role of delta and theta in our study aligned with
the inhibition of nontarget interference (Harmony 2013;
Harper et al. 2017),with theta also indexing conf lict mon-
itoring (Kirmizi-Alsan et al. 2006;Cavanagh et al. 2009).
Importantly, the increased interbrain synchronization in
the single-L2 and mixed contexts was also accompanied
by slower naming latencies, further indicating that
an increased demand for language control caused
higher synchronization. Moreover, in the mixed context,
there was evidence not only for inhibition but also for
conflict monitoring as shown by the increased theta
synchronization and slower naming latencies compared
with the single-L2 context.
These findings are consistent with previous work
demonstrating that more language control recruitment
causes higher interbrain synchronization (Liu et al.
2019). Crucially, however, the current study revealed
that language control recruitment arising from dif-
ferent language contexts leads to distinct oscillation
synchronization. Compared with the single-L1 context,
picture naming in the mixed and single-L2 contexts was
slower because of interference from the irrelevant L1.
These results support the adaptive nature of language
control (Green and Abutalebi 2013) and underscore
the important role of language context. When naming
pictures exclusively in the L2, inhibition, as indicated by
delta synchronization, is greater. Whereas when naming
pictures in the mixed-language context, both inhibition
and conflict monitoring are greater, as indexed by delta
and theta synchronization.
Language Control Is Adaptive
The constructs of language control and cognitive con-
trol share multiple subsets, such as conflict monitoring
and inhibition of prepotent interference (Emmorey et
al. 2008;Abutalebi et al. 2012;Abutalebi et al. 2013;
de Bruin et al. 2014;Branzi et al. 2015;De Baene et
al. 2015;Blanco-Elorrieta and Pylkkänen 2016;Wu et
al. 2019). Given that bilinguals frequently use different
languages depending on situational and communicative
needs, this notion assumes that language control is part
of domain-general cognitive control (Craik and Bialystok
2006;Abutalebi and Green 2007;Emmorey et al. 2008;
Garbin et al. 2010;Abutalebi et al. 2013;Blanco-Elorrieta
and Pylkkänen 2016). In the current study, we found
evidence that language control influences cognitive con-
trol, but this effect was limited to single-L2 and mixed
contexts. This carry-over influence provides compelling
evidence that conflict monitoring and inhibition, caused
by the activation of the language in the previous trial,can
be adaptively generalized to cognitive control. This view
is additionally supported by studies that have reported
overlapping neural substrates for both types of control
(Hernandez et al. 2001;Rodriguez-Fornells et al. 2002;
Crinion et al. 2006;Wang et al. 2007;Abutalebi 2008;
Branzi et al. 2015;Blanco-Elorrieta and Pylkkänen 2016,
2017;Blanco-Elorrieta et al. 2018;Wu et al. 2019;Liu,
Kong, et al. 2020a;Liu, Zhang, et al. 2020b).
Our finding that language context differentially influ-
enced cognitive control aligns with the previous finding
that different linguistic contexts require distinct cogni-
tive demands (Wu and Thierry 2013). More importantly,
however, our findings demonstrating the generalization
of language control to domain-general cognitive control
come from an experimental design in which we simulta-
neously examined language production and comprehen-
sion. Furthermore, by interleaving flanker trials into the
joint naming-listening task, we were able to examine how
domain-general cognitive control is affected in real time
for both speakers and listeners.
Finally, the electrophysiological data suggested that
the adaption of language control to domain-general con-
trol occurred in incongruent trials in the single-L2 and
mixed contexts, but not in the single-L1 context. This
suggests that the adaption of language control was lim-
ited to a situation involving similar control mechanisms
(see analogous findings in Calabria et al. 2015;Declerck
et al. 2017;Dick et al. 2019;Gollan and Goldrick 2016;
Lehtonen et al. 2018;Massa et al. 2020;Paap et al. 2015;
Prior and Gollan 2013). The alignment of language con-
trol and domain-general cognitive control in incongru-
ent trials can be explained by the conflict monitoring
account (Botvinick et al. 2001;Botvinick et al. 2004),
which holds that when monitoring mechanisms detect
a conflict, this interference leads to an enhanced focus
on the task-relevant stimulus dimension. This implies
that the binding between stimulus-specific conflict and
response-cognitive control would be restricted to the
enhancement of task-specific processes and therefore
would not generalize to alternative tasks (Egner 2008,
2014). Put differently, cross-task adaptation will only be
observed when the previous and current task-relevant
information remain the same. In this vein, assuming
that inhibitory control will persist for a brief period of
time, a subsequent conflict is temporarily prevented.
This homogeneous conflict adaptation effect improved
the performance of incongruent trials (faster RTs and
lower delta and theta synchronization relative to congru-
ent trials) in the single-L2 and mixed contexts. This find-
ing suggests that heightened conflict monitoring may be
limited to certain language contexts or specific types of
cognitive control (see Paap et al. 2015).
Limitations
Although our study is a first attempt to investigate the
adaption effect using dual-brain EEG synchronization,
and although the results are useful in understanding
the modulatory influence of context-involved language
control on cognitive control during simultaneous produc-
tion and comprehension, there are limitations that we
must acknowledge in hopes that future research may
reconcile these shortcomings. First, we did not require
Participants B to overtly respond during comprehension
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3238 |Cerebral Cortex, 2022, Vol. 32, No. 15
because previous studies have indicated that partici-
pants process information regardless of whether an overt
response is required or not (Liu, Kong, et al. 2020a;Liu et
al. 2021). The study by Liu et al. (2021) compared explicit
responses in a categorization task with passive listening
responses and found that both conditions produced the
same effect. Even another of our study (Liu, Kong, et
al. 2020a;Liu, Zhang, et al. 2020b) required participants
just to listen and complete a recognition task after a
block, there was still a higher recognition rate relative
to a guessing rate. Although these results may indicate
that participants who are not required to overtly make
responses indeed process the task at hand, future studies
should consider requiring listener participants to offer
explicit responses, such as a verbal version of a cat-
egorization task or word association task. Given that
oral artifacts from naming pictures aloud can interfere
with EEG signals, it is desirable to keep oral interaction
to a minimum. That said, future studies may benefit
from functional near infrared reflectance spectroscopy—
a technology that has very effective antinoise control.
These methods could improve the ecological validity of
research investigating the effects of language context on
cognitive control.
A second limitation is that we only included a pure
flanker task prior to the joint naming task, but not also
after. Therefore, the results should be interpreted with
caution regarding whether the changes in the flanker
task are causally related to the interleaved language
task. Although we found different synchronization of
flanker trials depending on language context, we are not
able to compare this with post-experiment performance.
Nonetheless, the finding that language context differen-
tially affects cognitive control underscores the adaptive
characteristics of control processes across single- and
mixed language conditions.
Conclusion
This study demonstrated that the delta and theta oscil-
lations responsible for inhibition and conflict monitoring
in bilingual production and comprehension can adap-
tively generalize to domain-general cognitive control.
This finding supports the notion that bilinguals have
adaptive language control mechanisms that support a
gambit of communicative contexts, including those in
which one, the other, or both languages are used. This
study uniquely sheds light on the fundamental charac-
terization of the specific contribution of language control
to domain-general cognitive control and offers the first
interbrain synchronization results supporting the natu-
ral adaptation from language control to cognitive control
in both language production and comprehension.
Notes
Conflict of Interest: We have no known conflict of interest
to disclose.
Funding
Dalian Science and Technology Star Fund of China
(2020RQ055); Liaoning Social Science Planning Fund of
China (L20AYY001); and Youth Foundation of Social
Science and Humanity, China Ministry of Education
(21C10165001).
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Liu et al. |3241
Appendix
Tab l e A 1 . Mean (and SDs) for participants’ ratings of their familiarity with picture names in the joint naming-listening task and the
frequency of occurrence in Chinese and English
Chinese Familiarity Frequency (in millions) English Familiarity Frequency (in
millions)
MSD MSD
4.81 0.79 149.64 Corn 4.88 0.42 10.92
4.73 0.71 7.39 Frog 4.58 0.79 5.35
4.88 0.42 22.83 Boot 4.92 0.38 23.67
4.92 0.38 24.86 Kite 4.92 0.38 65.41
4.88 0.42 111.73 Tie 4.92 0.38 94.04
4.88 0.58 212.27 Ant 4.88 0.58 104.96
4.88 0.58 11.77 Bell 4.92 0.38 10.73
4.69 0.77 4.41 Basket 4.85 0.60 13.18
4.81 0.68 43.82 Sheep 4.85 0.60 57.41
4.92 0.38 193.91 Flag 4.92 0.27 187.12
4.58 0.88 10.08 Gun 4.77 0.50 39.33
4.88 0.58 64.75 Mirror 4.88 0.58 45.45
4.81 0.62 126.48 Pear 4.96 0.19 95.78
4.96 0.19 213.20 Fox 4.96 0.19 176.98
4.42 0.79 14.31 Bottle 4.62 0.68 11.14
4.88 0.32 14.96 Guitar 4.69 0.87 50.75
4.96 0.19 35.80 Knife 4.96 0.19 28.33
4.92 0.27 13.32 Duck 4.96 0.19 74.18
4.96 0.19 59.23 Piano 4.96 0.19 45.06
4.85 0.53 70.74 Ruler 4.85 0.60 483.06
4.73 0.59 13.86 Elephant 4.88 0.32 48.02
4.88 0.58 105.05 Rabbit 4.88 0.58 66.33
4.92 0.27 10.82 Finger 4.92 0.27 11.75
4.88 0.42 95.69 Glasses 4.92 0.27 59.04
4.54 0.75 19.70 Mouse 4.31 0.87 14.22
4.88 0.58 351.99 Snowman 4.88 0.58 192.84
4.77 0.58 34.67 Airplane 4.92 0.27 87.20
4.77 0.70 13.24 Hat 4.77 0.70 24.76
4.73 0.94 12.40 Monkey 4.73 0.94 11.37
4.92 0.38 169.11 Shirt 4.92 0.38 111.78
4.92 0.38 29.93 Bear 4.73 0.76 36.67
4.62 0.74 3.31 Boat 4.69 0.61 17.49
4.88 0.42 266.70 Cloud 4.92 0.27 22.76
4.88 0.42 114.35 Foot 4.92 0.38 64.92
4.69 0.72 8.59 Glass 4.62 1.00 21.61
4.62 0.74 10.11 Car 4.54 0.89 11.82
4.92 0.27 393.39 Dress 4.92 0.27 557.12
4.88 0.42 16.13 Star 4.92 0.27 60.71
4.96 0.19 23.82 Ball 4.92 0.38 33.12
4.81 0.62 21.16 Computer 4.73 0.86 15.59
4.69 0.72 353.24 Nose 4.73 0.71 213.20
4.88 0.32 46.29 Bird 4.77 0.50 64.18
4.88 0.42 245.12 Bread 4.92 0.38 514.00
4.92 0.38 111.81 Cards 4.92 0.38 86.86
4.65 0.68 3.13 Pen 4.58 0.88 2.29
4.77 0.64 81.71 Pig 4.81 0.56 46.80
4.81 0.56 23.01 Tel e phon e 4.73 0.59 24.18
4.81 0.62 26.56 Tra i n 4.88 0.58 33.51
Continued
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3242 |Cerebral Cortex, 2022, Vol. 32, No. 15
Tab l e A 1 . Continued
Chinese Familiarity Frequency (in millions) English Familiarity Frequency (in
millions)
MSD MSD
4.92 0.38 12.79 Dog 4.96 0.19 49.96
4.73 0.76 36.78 Bag 4.81 0.68 19.12
4.88 0.58 40.96 Cat 4.88 0.58 69.75
4.81 0.68 4.98 Flower 4.69 0.82 1.33
4.88 0.42 3.07 Key 4.88 0.42 24.73
4.85 0.77 21.94 TV 4.81 0.79 24.86
4.88 0.58 59.95 Wat ch 4.88 0.58 39.14
4.88 0.58 23.76 Apple 4.85 0.60 20.94
4.96 0.19 0.30 Arm 4.88 0.32 3.18
4.73 0.71 20.78 Banana 4.73 0.65 13.43
4.85 0.36 9.12 Bed 4.92 0.27 46.37
4.73 0.59 1.67 Eye 4.85 0.60 1.90
4.31 0.07 1.31 Girl 4.77 0.70 81.35
4.96 0.19 48.92 House 4.96 0.19 105.63
4.96 0.19 547.72 Tabl e 4.88 0.58 32.37
4.50 0.80 15.23 Book 4.69 0.67 44.43
4.88 0.32 45.70 Bus 4.85 0.60 95.06
4.96 0.19 64.09 Cake 4.96 0.19 65.00
4.88 0.42 9.27 Moon 4.88 0.58 101.94
4.92 0.38 15.23 Tre e 4.88 0.58 330.02
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