On the Specificity of Bilingual Language Control: A Study with Parkinson's Disease Patients

Abstract

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.

Full text

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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
Acknowledgments
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
Email: lelecat3@gmail.com
T. (+34) 673469881
Abstract

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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.
Keywords: Bilingualism, Parkinson’s disease, bilingual language control,
reactive control, proactive control, between-language competition
1. Introduction

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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

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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

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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).
PLEASE INSERT TABLE 1 ABOUT HERE

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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.
PLEASE INSERT TABLE 2 ABOUT HERE
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

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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
fluencies.
PLEASE INSERT TABLE 3 ABOUT HERE
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

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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.

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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
factor.
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.
PLEASE INSERT FIGURE 1 ABOUT HERE

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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
resulted.
PLEASE INSERT TABLE 4 ABOUT HERE
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.
PLEASE INSERT FIGURE 2 ABOUT HERE
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
significant.

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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.
PLEASE INSERT TABLE 5 ABOUT HERE
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.
PLEASE INSERT FIGURE 3 ABOUT HERE
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

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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

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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).

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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
Controls
p values
Mean (SD)
Mean (SD)
Age (years)
71.3 (6.8)
71.5 (7.5)
0.95
Education(years)
10.7 (4.5)
9.9 (3.7)
0.59
UPDRS (0-159)
12.7 (4.3)
-
-
Age of L2 acquisition
3.2 (2.4)
3.3 (2.6)
0.81
Self rating questionnaire (1-4)
L1
Comprehension
4.0 (0.0)
4.0 (0.0)
-
Fluency
4.0 (0.2)
3.9 (0.3)
0.10
Pronunciation
3.9 (0.2)
3.9 (0.3)
0.37
Writing
2.0 (1.4)
3.1 (1.1)
0.01
Reading
3.8 (0.4)
3.9 (0.2)
0.11
L2
Comprehension
4.0 (0.0)
3.9 (0.2)
0.24
Fluency
3.9 (0.4)
3.8 (0.4)
0.46

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Pronunciation
3.8 (0.4)
3.8 (0.4)
0.93
Writing
3.0 (1.1)
3.3 (1.0)
0.46
Reading
3.9 (0.3)
3.8 (0.6)
0.26
Table 2. Neuropsychological assessment of participants. Means and standard deviations (in
parenthesis) of raw and adjusted scores for age and educations.
PD patients
Controls
p values
Raw scores
Adjusted scores*
Raw scores
Adjusted scores*
MMSE
28.7 (1.1)
-
28.5 (1.0)
-
0.43
Long-term Memory
CERAD immediate recall
16.7 (4.2)
-
16.3 (3.0)
-
0.77
CERAD delayed recall
4.1 (0.4)
-
4.7 (0.4)
-
0.28
CERAD recognition
18.2 (1.8)
-
18.3 (1.3)
-
0.88
Short-Term Memory
Forward digit span
5.2 (1.2)
9.7 (3.0)
5.4 (0.7)
10.9 (1.8)
0.56
Executive Function
Backward digit span
3.6 (1.0)
10.29 (1.7)
4.1 (0.6)
12.6 (1.2)
0.07
TMT A
48.7 (2.8)
10.39 (1.8)
39.7 (3.4)
12.1 (2.3)
0.05
TMT B
133.7 (38.4)
9.1 (1.3)
111.5 (31.3)
10.2 (1.5)
0.06
Language production

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Semantic fluency L1
10.14 (2.4)
10.1 (2.4)
10.24 (1.6)
10.2 (1.6)
0.89
Semantic fluency L2
9.77 (1.8)
9.8 (1.8)
9.9 (1.8)
9.9 (1.8)
0.78
Phonemic fluency L1
8.9 (1.6)
8.9 (1.6)
10.2 (1.1)
10.2 (1.1)
<0.01
Phonemic fluency L2
9.9 (1.8)
9.9 (1.8)
10.5 (1.5)
10.5 (1.5)
0.30
* 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
Controls
Mean (SD)
Mean (SD)
Noun
Verb
Total
Noun
Verb
Total
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)
Total
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)

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Table 4. Accuracy (%) of participants in the between languages switching task.
Between languages switching task - Accuracy (%)
PD patients
Controls
Mean (SD)
Mean (SD)
L1
L2
Total
L1
L2
Total
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)
Total
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)

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FIGURE 1

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FIGURE 2

25

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FIGURE 3