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This study investigates the relationship between mechanisms involved in language control within dual- and single-language contexts by examining whether they are similarly impaired in bilingual PD patients. To do so, we explored the performance of bilingual individuals affected by PD and healthy controls on two linguistic tasks: between-language and within-language switching tasks. We focused on switch and mixing costs as measures of linguistic control. The results indicate that, whereas larger switch costs were observed in PD patients, compared to controls, solely during the between-language task, larger mixing costs appeared during both the between-language task and the within-language task. These results are discussed within the framework of the dual mechanism hypothesis, which suggests that switch and mixing costs are measures of two types of control: specifically reactive and proactive control. Therefore, we conclude that reactive control for switching between languages is domain-specific while proactive control mechanisms are more domain-general.
Short title: On the Specificity of Bilingual Language Control
Full title: On the Specificity of Bilingual Language Control: A Study with
Parkinson's Disease Patients
Gabriele Cattaneo 1, Albert Costa 1,3, Alexandre Gironell 2, Marco Calabria 1
¹ Center for Brain and Cognition, Pompeu Fabra University, Barcelona, Spain
² Movement Disorders Unit, Neurology Department, Sant Pau Hospital, Barcelona, Spain
³ ICREA, Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain
This work was supported by grants from Agencia Estatal de Investigación (AEI)
and Fondo Europeo de Desarrollo Regional (FEDER) (PSI2011-23033, PSI2014-52210-
P, PSI2017-87784-R), the Catalan Government (SGR 2014-1210, 2017SGR268), and the
European Research Council (Cooperation grant agreement n. 613465 - AThEME) as well
as by La Marató-TV3 Foundation (935422602). Marco Calabria is supported by the
Ramón y Cajal Program from the Spanish Government (RYC-2013-14013). A special
thanks is extended to all participants for their invaluable collaboration.
Address for Correspondence
Gabriele Cattaneo
Universitat Pompeu Fabra
Center for Brain and Cognition
Carrer Ramon Trias Fargas, 25-27, 08005, Barcelona, Spain
T. (+34) 673469881
This study investigates the relationship between mechanisms involved in language
control within dual- and single-language contexts by examining whether they are
similarly impaired in bilingual PD patients. To do so, we explored the performance of
bilingual individuals affected by PD and healthy controls on two linguistic tasks:
between-language and within-language switching tasks. We focused on switch and
mixing costs as measures of linguistic control.
The results indicate that, whereas larger switch costs were observed in PD
patients, compared to controls, solely during the between-language task, larger mixing
costs appeared during both the between-language task and the within-language task.
These results are discussed within the framework of the dual mechanism hypothesis
which suggests that switch and mixing costs are measures of two types of control,
specifically reactive and proactive control. Therefore, we conclude that reactive control
for switching between languages is domain-specific while proactive control mechanisms
are more domain-general.
Keywords: Bilingualism, Parkinson’s disease, bilingual language control,
reactive control, proactive control, between-language competition
1. Introduction
The aim of this study is to explore the mechanisms that allow bilingual speakers
to control their two languages during language processing mechanisms often referred
as bilingual language control. A large body of research has shown that bilingual language
control is maintained by a complex network of neural circuitry involving classical
language areas and executive control areas. Of particular relevance in this context are the
basal ganglia, a conglomerate of brain structures that has been argued to be fundamental
in the control of two or more languages (Abutalebi et al., 2008; Abutalebi & Green, 2007;
Abutalebi et al., 2013; Branzi, Della Rosa, Canini, Costa, & Abutalebi, 2016; Calabria,
Costa, Green, & Abutalebi, 2018; Crinion et al., 2006; Lehtonen et al., 2005; Price, Green,
& Von Studnitz, 1999; Zou, Ding, Abutalebi, Shu, & Peng, 2012). For example, damage
to these structures sometimes results in the inability to control the two languages at will,
producing involuntary mixing of them during discourse, known as pathological switching
(for a review in aphasic patients see Ansaldo & Marcotte, 2007). Similarly, tasks that
involve mixing languages tend to activate the left caudate to a larger extent than tasks
involving just one language (Crinion et al., 2006; Seo, Stocco, & Prat, 2018).
We further explore the involvement and specificity of these structures in bilingual
language control by assessing the performance of patients with basal ganglia dysfunctions
as a consequence of Parkinson’s disease (PD). These patients showed deficits, as
compared to healthy controls, in tasks involving two languages such as a language
switching task (as we recently showed in Cattaneo et al., 2015). Interestingly, some of
these deficits were not always present when the task involved switching between non-
linguistic task sets, suggesting a more specific role of basal ganglia structures in language
control. There is, however, a remaining question about specificity: are the basal ganglia
involved in language control, be it that of a monolingual or bilingual individual, or is it
especially relevant in bilingual language control? In more practical terms, will bilingual
PD patients show deficits in any task that involves language control or only on those
involving the control of two languages?
To answer this question, we asked participants to perform two switching tasks: a)
a switching task that involved switching between two languages; and b) a switching task
that involved switching within a single language, such as changing the grammatical
category within a language. In fact, these two tasks have been shown to elicit different
activity in basal ganglia structures (specifically the left caudate), suggesting certain
structural specificity in controlling the two languages (Abutalebi & Green, 2008; Marian,
Bartolotti, Rochanavibhata, Bradley, & Hernandez, 2017). Hence, if this observation can
be understood as revealing that basal ganglia structures are fundamental for bilingual
language control and not just for language control in general, then it is expected that PD
patients’ performance on the within-language switching task would be better than on the
between-language switching task.
1. 1. Bilingual language processing in PD patients
Few studies have explored the linguistic performance of Parkinson’s disease
patients in bilingual contexts. In two studies, Zanini et al. (2004) and Zanini, Tavano, &
Fabbro, (2010) showed that PD leads to difficulties in sentence and syntactic
comprehension as well as spontaneous speech production. Moreover, in these studies,
performance on an executive control (EC) task correlated with the performance on their
sentence comprehension task, suggesting a link between grammatical processing and
executive functions. Similar results were replicated recently by Johari et al. (2013) in
Azari-Farsi bilinguals.
As for bilingual language control, in our previous study with bilingual PD patients,
we found that patients were impaired in between-language switching when their
performance was compared to healthy controls (Cattaneo et al., 2015). However, we were
unable to determine whether these linguistic deficits, likely due to basal ganglia
pathology, were limited to switching between languages or if they also extend to single-
language conditions. Based on previous neuroimaging studies that showed the
involvement of basal ganglia in switching between languages, but not within one
language, we would predict impaired language control for PD patients when they need to
control two languages and not in other single-language switching tasks (Abutalebi et al.,
2008). However, in our previous study we found that the domain-specificity of bilingual
language control abilities was dependent on the index of control that we measured (switch
vs. mixing). In order to account for this, we employ both of these measures in this study
to explore the extent to which the underlying processes of language control overlap
between the two linguistic domains (dual-language and single-language).
1.2. Control measures in switching tasks
The switching tasks that we have used in previous experiments can be utilized to
calculate two different control measures: switch cost and mixing cost (Cattaneo et al.,
2015; but see also Ma, Li, & Guo, 2016; Weissberger, Wierenga, Bondi, & Gollan, 2012).
Consider an experimental block in which the participant is asked to name pictures in
language A (if the picture appears in blue) or in language B (if it is in red); this would be
defined as a mixing block. Within said block, there would be some trials in which the
target language is the same as the trial immediately encountered before, and other trials
in which the target language is different than before. The first type of trial would be
considered a repeat trial whereas the second one would be a switch trial, and the
switch cost is the difference in reaction times between these types of trials. Now consider
an experimental block in which the language to be used is always the same (single block),
and hence all trials could be considered as repeated. The difference in reaction times
between the repeat trials in the mixing blocks with those in the single blocks would be
the mixing cost.
In the present study, we used the design described above. For the between-
language switching task, participants were asked to switch between languages (Catalan
and Spanish). For the within-language switching task, participants were asked to switch
between grammatical classes but maintaining just one language. That is, they were asked
to name a given picture (broom) either with the noun it represents (broom) or with the
verb corresponding to the action that it evokes (to sweep), according to the provided cue.
Our main experimental question is whether patient’s performance on these two
tasks would be comparable to that of healthy controls. In particular, we are especially
interested in determining whether patients show deficits in the within-language switching
condition, given that deficits for the between-language condition have already been
reported (Cattaneo et al., 2015). In our previous study, we found that, when compared to
healthy controls, the magnitude of the switch cost was specifically affected in PD patients
when switching between languages but not when switching between non-linguistic tasks
(sorting by colour or shape). On the other hand, mixing costs were equally affected by
the disease in both tasks. These two costs have been associated with two different types
of control in the context of dual-mechanisms of control (DMC) framework (Braver, 2012;
De Pisapia & Braver, 2006). That is, reactive control, measured in both tasks by switch
cost (calculated as the difference between switch and repeat trials in a mixed block), is
defined as a bottom-up, transient and stimulus-driven type of control. Proactive control
instead, measured by mixing cost (calculated as the difference between repeat trial in
single and mixed blocks), is top-down, more sustained and goal-directed (for bilingual
language control see Ma et al., 2016, see Table 1).
2. Methods
2.1. Participants
24 bilinguals with a diagnosis of PD (12 female, mean age = 71.3 ± 6.8, mean
education = 10.7 ± 4.5) and 17 matched healthy controls (12 female, mean age = 71.5 ±
7.5, p = 0.95; mean education = 9.9 ± 3.7, p = 0.59) took part in this study. Participants
were early and highly proficient Catalan-Spanish bilinguals. Participants self-rated as
highly proficient in both languages (Table 2) and their residence in the metropolitan area
of Barcelona, a highly bilingual context, regularly exposed them to both languages. Seven
patients and four controls considered themselves Spanish dominant, while the others were
Catalan dominant.
All individuals with PD were diagnosed according to the clinical criteria of the
UK Parkinson’s Disease Brain Bank (Hughes, Daniel, Kilford, & Lees, 1992) by a senior
neurologist (A.G.) who specializes in movement disorders. Based on the Unified
Parkinson Disease Rating Scale (UPDRS, mean = 12.8 ±4.4 out of 159, range = 8-21;
Fahn et al. 1987) and Hoehn and Yahr score (all rating from I to IIa; Hoehn & Yahr,
1967), all patients were in the mild stage of disease, and their Mini Mental State
Examiniation (MMSE) scores indicated that they did not have dementia (Folstein,
Folstein, & McHugh, 1975; mean 28.7 ±1.1, range = 26-30). All patients were stable,
without motor fluctuations, and receiving anti-Parkinsonian pharmacological treatment.
The study excluded patients with psychiatric and neurological disorders other than PD,
clinically recognized hearing or vision impairments, or a past history of alcohol abuse.
The ethics committee of the Pompeu Fabra University (CEIC, Parc de Salut MAR)
approved the study procedure. Informed consent was obtained from patients and
caregivers prior to testing and following a full explanation of the study.
2.2. Neuropsychological Assessment
Participants were administered a neuropsychological assessment (see Table 3) that
included a Mini Mental State Examination (Folstein et al., 1975), a word list test from the
Consortium to establish a registry for Alzheimer's disease (CERAD; Morris et al., 1989),
Digit Span Test Forward and Backward (Test Barcelona, Peña-Casanova, 2005), Parts A
and B of the Trail Making Test (Reitan & Wolfson, 1985), and semantic and letter
2.3. Materials and Procedures
Participants were tested on two switching tasks: a within-language switching task
(in their dominant language as well as in their second language) and a between-language
switching task. All tasks were administered on a laptop (screen 15.6” and resolution of
1280x800) and vocal responses were recorded by the DMDX software (Forster & Forster,
2003). Responses were analyzed offline, and naming latencies were measured through
Checkvocal software (Protopapas, 2007).
a. Within-language switching task
Eight pictures of objects were selected from Snodgrass and Vanderwart (1980).
Participants were required to name the pictures or produce the related verb as quickly as
possible. All the pictures were selected in such a way to ensure that the noun and the verb
that participants had to produce did not phonologically overlap within the same language
(Catalan and Spanish: “Got/Beure” and “Vaso/Beber” [Glass/to Drink]; “Ocell/Volar”
and Pájaro/Volar” [Bird/to Fly]; “Paella/Fregir” and “Sartén/Freir” [Pan/to Fry];
“Piano/Tocar” and “Piano/Tocar'” [Piano/to Play Piano]; “Tren/Viatjar” and
“Tren/Viajar” [Train/to Travel]; “Cigarreta/Fumar” and “Cigarro/Fumar” [Cigarette/to
Smoke]; “Plat/Menjar” and “Plato/Comer” [Dish/to Eat]; and “Ganivet/Tallar” and
“Cuchillo/Cortar” [Knife/to Cut]).
There were two types of blocks: single and mixed. In the single blocks, the
grammatical category to produce (name or verb) was always the same, whereas in mixed
blocks participants had to name the pictures or produce the related verb according to a
cue that appeared on the screen. Therefore, there were two types of trials in the mixed
blocks: repeat trials, wherein participants had to respond according to the same
grammatical category that the previous trial used, and switch trials, which required
participants to answer according to a grammatical category that differed from that of the
previous trial. The order of blocks had a sandwich design in which participants completed
two single blocks, three mixed blocks and then two more single blocks. There were a
total of 96 trials (48 for nouns and 48 for verbs) in the single-block condition and 96 in
the mixed-block condition (33 noun repeat trials, 33 verb repeat trials, 15 noun switch
trials, and 15 verb switch trials). The proportions of switch and repeat trials were 31%
and 69%, respectively.
Every trial started with a fixation point (a white cross) in the center of the screen
that appeared for 500 ms and was followed by a cue of 500 ms (“NOM”/“NOMBRE”
for nouns and “VERB”/“VERBO’” for verbs). Then, the screen displayed the picture for
a maximum of 2,500 ms. At the beginning of each block, the screen presented a word
cue for 1,000 ms to indicate the grammatical category with which participants must start.
b. Between-language switching task.
Eight pictures of objects were selected from Snodgrass and Vanderwart (1980).
All objects were non-cognate words (Spanish/Catalan names: “Manzana/Poma” [Apple];
“Calcetín/Mitjó” [Sock]; “Queso/Formatge” [Cheese]; “Silla/Cadira” [Chair];
“Zanahoria/Pastanaga” [Carrot]; “Cepillo/Raspall” [Brush]; “Tenedor/Forquilla” [Fork];
and “Mariposa/Papallona” [Butterfly]). Participants were required to name the pictures
in Catalan or in Spanish as quickly as possible according to a cue, presented as a flag.
The task structure, type and number of blocks, and type and number of trials were
the same as for the within-language switching task.
3. Results
We compared the performance of PD patients and older adults on the two
linguistic tasks, and correlated the costs between them in order to explore similarities
between the control mechanisms that are engaged in the two language context conditions.
As previously reported, we calculated switch and mixing costs for both tasks. Switch
costs were calculated as the difference in naming latencies between switch and repeat
trials in a mixed-language condition, while mixing costs were calculated as the difference
between repeat trials (in the mixed condition) and trials in a blocked naming condition.
The analysis excluded naming latencies that exceeded three standard deviations
(SDs) above or below a given participant’s mean in addition to incorrect responses.
3.1. Within-language switching task
The task was performed in both L1 and L2 for all participants. Repeated measures
analyses of variance (ANOVAs) were run on accuracy and reaction times (RTs) with
variables of type of trial (single, repeat, switch), language (L1, L2), and category (noun,
verb) as within-subject factors and the group (controls, PD patients) as a between-subjects
Reaction Times. Participants were slower in switch trials (1,092 ms) than in repeat
trials (1,045 ms, p<0.01) and slower in repeat trials than in single trials (959 ms, p<0.01)
(type of trial: F [2, 78] =41.14, p<0.01, ηp²=0.51) (see Figure 1). The main effect of the
category was also significant (F [1, 39] = 30.63, p<0.01, ηp²=0.44), which indicates that
participants produced nouns (1,007 ms) more quickly than verbs (1,057 ms). However,
the language used in the task did not modulate participants’ naming latencies (language:
F [1, 39] = 0.89, p=0.35, ηp²=0.02).
The main effect of the group was significant, as individuals with PD were slower
overall (1,106 ms) than controls (957 ms) (F [1, 39] = 6.65, p<0.05, ηp²=0.15). Finally,
the interaction between the group and the type of trial was significant (F [2, 78] =6.73,
p<0.01, ηp²=0.15), which suggests a difference in the magnitude of the costs (mixing,
switch, or both) between the two groups.
To further analyze this interaction, we calculated the magnitude of the costs and
then performed a separate one-way ANOVA for each cost, with the group as a between-
subjects factor. In order to avoid bias due to different baseline RTs for the two groups,
we calculated the costs as proportions. Proportional switch costs were calculated as the
difference between RTs in switch trials and repeat trials (mixed blocks) divided by RTs
in repeat trials. Proportional mixing costs were calculated as the difference between RTs
in repeat and single trials divided by RTs in single trials.
The results revealed that individuals with PD had increased mixing costs
compared to controls (13.4% and 4.0%; F [1, 39] =10.58, p<0.01, ηp²=0.21) but not
increased switch costs (3.4% and 4.8%, respectively; F [1, 39] =1.00, p=0.33, ηp²=0.02).
No other significant interaction resulted.
Accuracy. The main effect of the type of trial was significant (F [2, 78] =9.59,
p<0.01, ηp²=0.20), and post-hoc analysis revealed that participants were less accurate in
switch trials (95.6%) than in repeat (97.3%, p<0.01) and single trials (97.5%, p<0.01),
but they performed with the same accuracy in the two latter types (p=0.39; see Table 4).
There was no difference in accuracy between L1 (96.6%) and L2 (97.0%) (language: F
[1,39] =0.58, p=0.45, ηp²=0.01) or between nouns (97.2%) and verbs (96.5%) (category:
F [1, 39] =1.81, p=0.19, ηp²=0.04). No other significant main effect or interaction
3.2. Between-language switching task
A repeated measures ANOVA was performed on accuracy and RTs that
considered the type of trial (single, repeat, switch) and language (L1, L2) as within-
subject factors and the group (controls, PD) as a between-subjects factor.
Reaction Times. The main effect of the type of trial was significant (F [2,
78]=70.45, p<0.01, ηp²=0.64). Post-hoc analyses indicated that single trials were the
fastest (928 ms), switch trials were the slowest (1076 ms; p<0.01), and repeat trials were
in between (1,017 ms, ps<0.01; see Figure 2). The main effect of the group was also
significant, which suggests that individuals with PD were slower (1,080 ms) overall than
controls (934 ms) (F [1, 39] =8.45, p<0.01, ηp²=0.18). Moreover, the interaction between
the group and type of trial was significant (F [2, 78] =8.47, p<0.01, ηp²=0.18), which
signifies a difference in the magnitude of the costs between the two groups.
We therefore analyzed the magnitude of the proportional switch costs and mixing
costs with an ANOVA with group as a between-subjects factor. The results revealed that
individuals with PD had increased switch costs compared to controls (7.4% and 3.7%,
respectively; F [1, 39] =5.26, p<0.05, ηp²=0.12) as well as increased mixing costs (11.7%
and 6.8%; F [1, 39] =4.69, p<0.05, ηp²=0.11). No other interaction or main effect was
Accuracy. The main effect of the type of trial was significant (type of trial: F [2,
78] =22.64, p<0.01, ηp²=0.37), and post-hoc analysis revealed that participants were less
accurate in switch trials (91.5%) than in repeat (96.8%, p<0.01) and single (97.5%,
p<0.01) trials, and they performed similarly in the latter two trial conditions (p=0.41; see
Table 5). Moreover, individuals with PD were less accurate (93.1%) than controls
(97.3%) (group: F [1, 39] =5.27, p<0.05, ηp²=0.12). No other interaction or main effect
was significant.
3.3. Linguistic control tasks: correlations
To explore the relationship between the mechanisms involved in the two language
control tasks, we correlated the costs (switch and mixing) that we obtained.
When we ran correlations with all participants, we found a non-significant
correlation between the switch costs in the two linguistic tasks (r = 0.20, p = 0.22) but a
significant positive correlation between the two mixing costs (r = 0.59, p < 0.01, see
Figure 3).
For PD patients, we confirmed these results (r = 0.22, p = 0.30 and r = 0.63, p <
0.01, respectively), while for the control group, neither the switch costs (r = 0.40, p =
0.11) nor the mixing costs (r = 0.19, p = 0.48) were significantly correlated across tasks.
4. Discussion
The present study investigates the relationship between mechanisms that are
involved in different contexts of language control by examining associations and
dissociations of control deficits in bilingual PD patients.
We explored two measures of control (switch and mixing costs) following up on
our previous study (Cattaneo et al., 2015) with PD in which we found dissociations
between these costs and between control domains (linguistic and non-linguistic). The
literature on language switching has primarily focused on the reactive control (inhibitory)
mechanism and measured it in terms of switching costs; however, researchers have
recently proposed that a second mechanism underlies language control, namely proactive
control, which can be measured with mixing costs (Braver, 2013; Christoffels et al., 2007;
Green & Abutalebi, 2013; Ma et al., 2016; Misra, Guo, Bobb, & Kroll, 2012).
Moreover, we investigated dissociations and associations of these two types of
control in two linguistic switching tasks: one that engages bilingual language control
(between-language switching task) and one that involves mechanisms of language control
in general – that is, the set of control mechanisms that operate in situations in which two
languages are not mixed (within-language switching).
In the next paragraphs we discuss what our findings suggest for the domain-
general and domain-specific nature of language control.
4.1. Reactive control and its domain specificity
Our findings indicate that, compared to controls, PD patients were impaired in
reactive control in the between-language switching task, but not in the within-language
switching task. Moreover, reactive control indexes (switch costs) did not correlate in the
two tasks. In our previous study with bilingual PD patients, we similarly determined that
reactive control was selectively impaired in the between-language task but not in the non-
linguistic switching task (Cattaneo et al., 2015). Both results suggest that reactive
bilingual language control processes are domain-specific, revealed in situations that
require bilinguals to switch back and forth between languages.
The specific activation of the left caudate when bilinguals switch between
languages supports the domain specificity of bilingual language control. The results of a
study by Abutalebi et al. (2008) has evidenced that the left caudate was specifically
activated when bilinguals performed a language-switching task, but not when participants
were asked to switch between naming objects or actions in the same language. Similarly,
Marian et al. (2017) found the activation of the same subcortical area in a task of visual
word recognition with auditory stimuli when bilinguals performed it in a between-
language condition, but not when words belonged to same language.
One possible interpretation from Abutalebi and Green (2008, 2016) is that the
basal ganglia would be responsible for managing cross-language interference and
supervising the selection of the correct language, and they would therefore be sensitive
to language-switching deficits, as appears to be the case in our PD patients. These
structures activate and inhibit languages in cooperation with frontal areas for conflict
resolution and parietal areas for maintaining language representations (see Branzi et al.,
2016; Calabria et al., 2018; Seo et al., 2018; Zou et al., 2012). Alternatively, and
specifically in relation to executive control deficits related to striatal degeneration, it has
been proposed that longer switch costs in non-linguistic tasks are indexes of impaired
response suppression at selection level, as in the case of two languages (e.g., Lawrence,
Sahakian, & Robbins, 1998).
This is in line with previous evidence of the selectivity of the basal ganglia’s
involvement in cross-language interference (Abutalebi et al., 2008; Crinion et al., 2006)
as well as of pathological behaviors due to damage to the subcortical (basal ganglia and
subthalamic) regions and their connections with striatal structures. For example,
Abutalebi, Miozzo, and Cappa (2000) reported a case of a trilingual (Armenian-English-
Italian) female (A.H.) who, after a subcortical white matter infarction adjacent to the left
caudate nucleus, developed a non-fluent aphasia which was characterized by pathological
language switching between these languages in speech production. Similarly, Aglioti,
Beltramello, Girardi, and Fabbro (1996) have discussed a bilingual patient (E.M.) who,
after a stroke in the left capsular-putaminal region, suffered cross-language intrusions
during spontaneous speech (see also Mariën, Abutalebi, Engelborghs, & De Deyn, 2005).
4.2. Proactive control and its domain-general nature
In addition to our findings on reactive control, we observed that proactive control
was similarly impaired in PD patients, compared to healthy controls, in both linguistic
tasks. This suggests that this type of control is generalized across domains and that it is a
control process elicited by conditions that require the active maintenance of two memory-
related tasks. Indeed, the effects on non-linguistic proactive control are comparable to
those on linguistic control in PD patients, which implies that proactive control is not
sensitive to the domain (e.g. linguistic; Cattaneo et al., 2015). Therefore, such control
may be related to certain sub-components of working memory mechanisms, such as the
demand to maintain task goals and update information in a dual-task situation (Braver,
Reynolds, & Donaldson, 2003; Kray & Lindenberger, 2000; Pettigrew & Martin, 2015;
Rogers & Monsell, 1995). Alternatively, proactive control may relate to monitoring and
resolving interferences without working memory involvement as other researchers have
suggested (Philipp, Kalinich, Koch, & Schubotz, 2008; Prior & Gollan, 2013; Prior &
Macwhinney, 2010; Rubin & Meiran, 2005).
The relationship between these two control types and the dysfunction of the
striatum is only speculative in our study, seeing that we do not have measures in our PD
patients to qualify/quantify their subcortical degeneration. Moreover, although numerous
proposals have related both proactive and reactive inhibitory control to the basal ganglia
(e.g. Jahanshahi et al., 2015), others have demonstrated that they are unrelated (e.g. van
Belle et al., 2014). The concept of reactive control that we use in this study might
resemble that which Jahanshahi et al. (2015) have used for reactive inhibition, which
defines it as stimulus-driven and useful for avoiding interference from distracting stimuli.
However, in light of our results, a direct relationship between basal ganglia and specific
control processes is only speculative and beyond the scope of this study.
5. Conclusion
In conclusion, this study contributes further knowledge of the relationship
between different language control deficits in bilinguals experiencing PD. We
demonstrated a dissociation of impairments in reactive mechanisms engaged during
language control in different language contexts and an association of impairment for
proactive language control mechanisms. Therefore, this suggests that bilingual language
control abilities are domain-specific for reactive control, whereas they are domain-
general for proactive control. However, we found a positive correlation between proactive
control mechanisms in the two tasks in PD patients and not in controls. This might
indicate that brain pathology increases the variability in performance and the statistical
power for cross-task correlations.
Further research is needed to better understand the nature of reactive and proactive
control, and how they can be related to qualitatively different mechanisms such as
inhibition, working memory, or conflict monitoring.
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Table 1. Socio-demographic characteristics of the participants and clinical data of the PD patients.
PD patients
p values
Mean (SD)
Age (years)
71.3 (6.8)
10.7 (4.5)
UPDRS (0-159)
12.7 (4.3)
Age of L2 acquisition
3.2 (2.4)
Self rating questionnaire (1-4)
4.0 (0.0)
4.0 (0.2)
3.9 (0.2)
2.0 (1.4)
3.8 (0.4)
4.0 (0.0)
3.9 (0.4)
3.8 (0.4)
3.0 (1.1)
3.9 (0.3)
Table 2. Neuropsychological assessment of participants. Means and standard deviations (in
parenthesis) of raw and adjusted scores for age and educations.
PD patients
p values
Raw scores
Adjusted scores*
Raw scores
Adjusted scores*
28.7 (1.1)
28.5 (1.0)
Long-term Memory
CERAD immediate recall
16.7 (4.2)
16.3 (3.0)
CERAD delayed recall
4.1 (0.4)
4.7 (0.4)
CERAD recognition
18.2 (1.8)
18.3 (1.3)
Short-Term Memory
Forward digit span
5.2 (1.2)
9.7 (3.0)
5.4 (0.7)
10.9 (1.8)
Executive Function
Backward digit span
3.6 (1.0)
10.29 (1.7)
4.1 (0.6)
12.6 (1.2)
48.7 (2.8)
10.39 (1.8)
39.7 (3.4)
12.1 (2.3)
133.7 (38.4)
9.1 (1.3)
111.5 (31.3)
10.2 (1.5)
Language production
Semantic fluency L1
10.14 (2.4)
10.1 (2.4)
10.24 (1.6)
10.2 (1.6)
Semantic fluency L2
9.77 (1.8)
9.8 (1.8)
9.9 (1.8)
9.9 (1.8)
Phonemic fluency L1
8.9 (1.6)
8.9 (1.6)
10.2 (1.1)
10.2 (1.1)
Phonemic fluency L2
9.9 (1.8)
9.9 (1.8)
10.5 (1.5)
10.5 (1.5)
* Mean scores adjusted for age and education on the basis of the “Spanish multicenter Normative
studies (NEURONORMA PROJECT)” (Peña- Casanova et al.,2009).
Table 3. Accuracy (%) of participants in the within language switching task.
Within language switching task - Accuracy (%)
PD patients
Mean (SD)
Mean (SD)
Single trials
96.9 (1.9)
97.9 (3.5)
97.4 (2.3)
97.3 (2.5)
97.9 (3.5)
97.6 (2.4)
Repeat trials
96.8 (2.6)
97.2 (6.1)
97.0 (3.8)
97.1 (2.8)
97.9 (3.1)
97.5 (2.7)
Switch trials
95.6 (5.2)
95.0 (6.9)
95.3 (4.9)
95.7 (4.4)
96.3 (6.8)
96.0 (4.2)
96.4 (2.0)
96.7 (4.2)
96.6 (2.8)
96.7 (2.1)
97.4 (3.6)
97.0 (2.6)
Switch costs
1.2 (4.6)
2.2 (3.8)
1.7 (3.1)
1.4 (5.2)
1.6 (4.8)
1.5 (3.2)
Mixing costs
0.1 (2.5)
0.7 (5.6)
0.4 (3.1)
0.2 (3.2)
0 (1.6)
0.1 (1.7)
Table 4. Accuracy (%) of participants in the between languages switching task.
Between languages switching task - Accuracy (%)
PD patients
Mean (SD)
Mean (SD)
Single trials
95.7 (6.7)
97.0 (3.9)
96.4 (4.7)
98.9 (2.7)
98.7 (1.6)
98.8 (1.6)
Repeat trials
94.6 (8.7)
95.2 (8.0)
94.9 (8.0)
98.4 (2.2)
99.2 (1.7)
98.8 (1.7)
Switch trials
87.2 (12.6)
90.0 (10.8)
88.6 (10.9)
95.0 (5.7)
93.7 (2.4)
94.4 (4.5)
92.5 (8.3)
94.1 (6.1)
93.3 (7.0)
97.4 (2.6)
97.2 (2.7)
97.3 (1.9)
Switch costs
8.5 (7.0)
7.0 (8.1)
7.8 (5.3)
3.9 (5.4)
5.0 (7.0)
4.4 (4.3)
Mixing costs
1.1 (6.8)
1.8 (7.7)
1.5 (7.0)
0.5 (2.6)
-0.5 (2.5)
0.0 (2.1)
... However, in light of more recent findings of mixing benefits in some bilingual populations [18,19], it would be more accurate to refer to these general measures as switching effects and mixing effects. Conceptually, switching effects can be thought of as reflections of the ability to resolve cross-language interference, language engagement, and disengagement, while mixing effects are related to working memory mechanisms, such as the demand in maintaining task goals that are present in a dual-language situation [17,20,21]. ...
... Calabria et al. [23] found that, in semantic dementia, switching abilities measured via language switching tasks may be spared despite a marked degradation of semantic memory and anomic deficits. Finally, a series of studies in patients with neurodegeneration in the basal ganglia have highlighted an increased impact on BLC deficits compared to other control mechanisms; results indicated that language switching abilities can be more affected than non-linguistic control abilities in bilingual patients with Parkinson's disease (PD) [20] and that language switching is clearly dissociated from other language control abilities [21]. These studies thus reveal a crucial distinction between BLC deficits affecting control pathways in bilingual language production and generalized language deficits, as PD patients did not exhibit any type of language disorder. ...
... dual-language contexts of speech production (e.g., [16,17]). Furthermore, recent findings from cued language switching tasks in bilingual patients with PD have demonstrated that switch and mixing costs are possibly related to two qualitatively different mechanisms [20,21]. Within the context of the dual mechanisms of control (DMC) framework of non-linguistic executive control [39,40], these two dual-language effects have been associated with two different types of control, reactive control and proactive control. ...
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As studies of bilingual language control (BLC) seek to explore the underpinnings of bilinguals' abilities to juggle two languages, different types of language switching tasks have been used to uncover switching and mixing effects and thereby reveal what proactive and reactive control mechanisms are involved in language switching. Voluntary language switching tasks, where a bilingual participant can switch freely between their languages while naming, are being utilized more often due to their greater ecological validity compared to cued switching paradigms. Because this type of task had not yet been applied to language switching in bilingual patients, our study sought to explore voluntary switching in bilinguals with aphasia (BWAs) as well as in healthy bilinguals. In Experiment 1, we replicated previously reported results of switch costs and mixing benefits within our own bilingual population of Catalan-Spanish bilinguals. With Experiment 2, we compared both the performances of BWAs as a group and as individuals against control group performance. Results illustrated a complex picture of language control abilities, indicating varying degrees of association and dissociation between factors of BLC. Given the diversity of impairments in BWAs' language control mechanisms, we highlight the need to examine BLC at the individual level and through the lens of theoretical cognitive control frameworks in order to further parse out how bilinguals regulate their language switching.
... If the origin of enhancement is related more to these higher-order processes, other types of processes that require categorization (e.g., linguistic categories like nouns and verbs) even within one language could also impact attentional control. Previous studies have shown that within-language switching (i.e., naming pictures as nouns/objects or verbs/actions) reveals both differential and overlapping patterns of activation with between-language switching (i.e., naming pictures in different languages) (Abutalebi et al., 2013;Cattaneo, Costa, Gironell, & Calabria, 2020;Khateb et al., 2007). While between-language switching has a need for interference control, both between-context and within-context switching require monitoring of the language context as part of a more general task monitoring system. ...
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Bilinguals who switch from a monolingual context to a bilingual context enhance their domain-general attentional system. But what drives the adaptation process and translates into the observed increased efficiency of the attentional system? To uncover the origin of the plasticity in a bilingual’s language experience, we investigated whether switching between other types of categories also modulated domain-general attentional processes. We compared performance of Catalan-Spanish bilinguals across three experiments in which participants performed the Attentional Network Test in a mixed context and in two single contexts that were created by interleaving words with flankers. The contexts were related to switching (or not) between languages (Experiment-1) or between low-level perceptual color categories (Experiment-2) or between linguistic categories (Experiment-3). Both switching between languages and linguistic categories revealed increased target-P3 amplitudes in mixed contexts compared to single contexts. These findings can inform the Inhibitory Control model regarding the locus and domain-generality of attentional adaptations.
... Indeed, the ATLs, the focus of atrophy in svPPA, are not thought to contribute to language switching (Abutalebi & Green, 2007;Calabria, Costa, Green, & Abutalebi, 2018) -rather left caudate, left inferior frontal gyrus, and middle temporal gyrus are implicated (Coderre, Emily, Smith, Jason, van Heuven, & Horwitz, 2015;Garbin et al., 2011;Luk, Green, Abutalebi, & Grady, 2011). Therefore, we expected that TC would not be impaired at this task, since deficits in language switching are more associated with dysfunction in frontal-striatal connections (Cattaneo et al., 2015;Cattaneo, Costa, Gironell, & Calabria, 2019) or lesions in basal ganglia (Mariën, Abutalebi, Engelborghs, & De Deyn, 2005). ...
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Background: Patients with the semantic variant of Primary Progressive Aphasia (svPPA) offer a unique opportunity to study the relationship between lexical retrieval and semantics, as they are characterised by progressive degradation of central semantic representations. However, there are few studies of how lexical retrieval across languages is affected in multilingual speakers. Aims: We examine the impact of conceptual degradation in a trilingual patient (TC) with svPPA, to investigate whether the semantic memory breakdown affects her three languages similarly (English-Catalan-Spanish) in different linguistic tasks. Methods & Procedures: We followed up her performance over one year in several tasks including: (a) naming with or without semantic interference contexts, (b) word translation, (c) word- and sentence-picture matching, (d) associative semantic priming and (e) language switching. Outcomes & Results: There was significant response consistency between languages in the items that were relatively well-known and more semantically degraded, at least in a standard picture naming task. The patient’s sentence-to-picture matching did not show progressive deterioration in any language. However, some aspects of lexical retrieval showed language-dependency, as indexed by different patterns of performance in semantically-blocked cyclical naming task across languages. Conclusions: These data suggest that while degradation of central semantic representations affects all languages, this deficit can be amplified or ameliorated by the strength of conceptual to lexical mappings, which varies across languages.
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Acquiring and speaking a second language increases demand on the processes of language control for bilingual as compared to monolingual speakers. Language control for bilingual speakers involves the ability to keep the two languages separated to avoid interference and to select one language or the other in a given conversational context. This ability is what we refer with the term “bilingual language control” (BLC). It is now well established that the architecture of this complex system of language control encompasses brain networks involving cortical and subcortical structures, each responsible for different cognitive processes such as goal maintenance, conflict monitoring, interference suppression, and selective response inhibition. Furthermore, advances have been made in determining the overlap between the BLC and the nonlinguistic executive control networks, under the hypothesis that the BLC processes are just an instantiation of a more domain‐general control system. Here, we review the current knowledge about the neural basis of these control systems. Results from brain imaging studies of healthy adults and on the performance of bilingual individuals with brain damage are discussed. Acquiring and speaking a second language (L2) increases demand on the processes of language control for bilingual as compared to monolingual speakers. Language control for bilingual speakers involves the ability to keep the two languages separated to avoid interference and to select one language or the other in a given conversational context. Here, we review the current knowledge about the neural basis of these control systems. Results from brain imaging studies of healthy adults and on the performance of bilingual individuals with brain damage are discussed.
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The human capacity to master multiple languages is remarkable and leads to structural and functional changes in the brain. Understanding how the brain accommodates multiple languages simultaneously is crucial to developing a complete picture of our species’ linguistic capabilities. To examine the neural mechanisms involved in processing two languages, we looked at cortical activation in Spanish-English bilinguals in response to phonological competition either between two languages or within a language. Participants recognized spoken words in a visual world task while their brains were scanned using functional magnetic resonance imaging (fMRI). Results revealed that between-language competition recruited a larger network of frontal control and basal ganglia regions than within-language competition. Bilinguals also recruited more neural resources to manage between-language competition from the dominant language compared to competition from the less dominant language. Additionally, bilinguals’ activation of the basal ganglia was inversely correlated with their executive function ability, suggesting that bilinguals compensated for lower levels of cognitive control by recruiting a broader neural network to manage more difficult tasks. These results provide evidence for differences in neural responses to linguistic competition between versus within languages, and demonstrate the brain’s remarkable plasticity, where language experience can change neural processing.
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Classically, the basal ganglia have been considered to have a role in producing habitual and goal-directed behaviours. In this article, we review recent evidence that expands this role, indicating that the basal ganglia are also involved in neural and behavioural inhibition in the motor and non-motor domains. We then distinguish between goal-directed and habitual (also known as automatic) inhibition mediated by fronto-striato-subthalamic-pallido-thalamo-cortical networks. We also suggest that imbalance between goal-directed and habitual action and inhibition contributes to some manifestations of Parkinson's disease, Tourette syndrome and obsessive-compulsive disorder. Finally, we propose that basal ganglia surgery improves these disorders by restoring a functional balance between facilitation and inhibition.
Research on the neural bases of bilingual language control has largely overlooked the role of preparatory processes, which are central to cognitive control. Additionally, little is known about how the process involved in global language selection may differ from those involved in the selection of words and morpho-syntactic rules for manipulating them. These processes were examined separately in an fMRI experiment, with an emphasis on understanding how and when general cognitive control regions become activated. Results of region-of-interest analyses on 23 early Spanish-English bilinguals showed that the anterior cingulate cortex (ACC) was primarily engaged during the language preparation phase of the task, whereas the left prefrontal (DLPFC) and pre-supplementary motor areas showed increasing activation from preparation to execution. Activation in the basal ganglia (BG), left middle temporal lobe, and right precentral cortical regions did not significantly differ throughout the task. These results suggest that three core cognitive control regions, the ACC, DLPFC, and BG, which have been previously implicated in bilingual language control, engage in distinct neurocognitive processes. Specifically, the results are consistent with the view that the BG "keep track" of the target language in use throughout various levels of language selection, that the ACC is particularly important for top-down target language preparation, and that the left prefrontal cortex is increasingly involved in selection processes from preparation through task execution.
Speaking more than one language demands a language control system that allows bilinguals to correctly use the intended language adjusting for possible interference from the non-target language. Understanding how the brain orchestrates the control of language has been a major focus of neuroimaging research on bilingualism and was central to our original neurocognitive language control model (Abutalebi & Green, 2007). We updated the network of language control (Green & Abutalebi, 2013) and here review the many new exciting findings based on functional and structural data that substantiate its core components. We discuss the language control network within the framework of the adaptive control hypothesis (Green & Abutalebi, 2013) that predicts adaptive changes specific to the control demands of the interactional contexts of language use. Adapting to such demands leads, we propose, to a neural reserve in the human brain.
Few detailed clinico-pathological correlations of Parkinson's disease have been published. The pathological findings in 100 patients diagnosed prospectively by a group of consultant neurologists as having idiopathic Parkinson's disease are reported. Seventy six had nigral Lewy bodies, and in all of these Lewy bodies were also found in the cerebral cortex. In 24 cases without Lewy bodies, diagnoses included progressive supranuclear palsy, multiple system atrophy, Alzheimer's disease, Alzheimer-type pathology, and basal ganglia vascular disease. The retrospective application of recommended diagnostic criteria improved the diagnostic accuracy to 82%. These observations call into question current concepts of Parkinson's disease as a single distinct morbid entity.
Theories of task switching have emphasized a number of control mechanisms that may support the ability to flexibly switch between tasks. The present study examined the extent to which individual differences in working memory (WM) capacity and two measures of interference resolution, response-distractor inhibition and resistance to proactive interference (PI), account for variability in task switching, including global costs, local costs, and N-2 repetition costs. 102 young and 60 older adults were tested on a battery of tasks. Composite scores were created for WM capacity, response-distractor inhibition, and resistance to PI; shifting was indexed by rate residual scores which combine response time and accuracy and account for individual differences in processing speed. Composite scores served as predictors of task switching. WM was significantly related to global switch costs. While resistance to PI and WM explained some variance in local costs, these effects did not reach significance. In contrast, none of the control measures explained variance in N-2 repetition costs. Furthermore, age effects were only evident for N-2 repetition costs, with older adults demonstrating larger costs than young adults. Results are discussed within the context of theoretical models of task switching.
The present study examined how reactive control (indexed by switching costs) and proactive control (indexed by mixing costs) during bilingual language production was modulated by three factors reflected by different time-courses of stimulus presentation. In three experiments, unbalanced Chinese–English bilinguals named digits in Chinese or English according to a naming cue. In Experiment 1, switching costs reduced when participants had longer preparation time to select the target language to name digits (during the Cue-Stimulus interval, CSI), indicating that longer preparation time helps overcome reactive inhibition. In addition, mixing costs declined drastically at a longer preparation time, indicating that a tiny amount of preparation time allows bilinguals to overcome costs associated with proactively preparing two languages. In Experiment 2, the stimuli were presented prior to the cues, so that participants were given different amounts of time to activate the target lexical nodes in both languages before they were informed of the naming language (during the Stimulus-Cue interval, SCI). Symmetrical switching and mixing costs were observed, indicating that bilinguals can strategically boost activation of the target lexical item in the second language (L2) and attempt to equalize it with its translation equivalent in the native language (L1), when they know previously the specific lexical items to be prepared in two languages. In Experiment 3, different Response-Cue intervals (RCIs) were provided after participants named a digit. It was found that the switching cost asymmetry was more prominent when the time to resolve competition was shorter, while the mixing cost asymmetry emerged only with the longest waiting time. These findings provide the first piece of evidence for the dissipation of the reactive inhibition over time, and suggest that longer preparation would allow the proactive control mechanism to be sensitive the relative proficiency levels of the two languages, leading to stronger proactive control on the dominant language. Taken together, the findings in the present study suggest the dynamic nature of reactive and proactive control in unbalanced bilinguals and have important implications for the current models of bilingual language production, which do not explicitly distinguish the two types of control or address how they adapt to the fine-grained time course of the situation.