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Bilingual brain training: A neurobiological framework of how bilingual experience improves executive function

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Individuals who develop bilingually typically outperform monolinguals on tests of executive functions. This advantage likely reflects enhanced prefrontal function, but the mechanisms that underlie this improvement are still poorly understood. This article describes a theory on the nature of the neural underpinnings of improved executive function in bilinguals. Specifically, we propose that growing up in a bilingual environment trains a gating system in the striatum that flexibly routes information to the prefrontal cortex. This article is divided into three sections. Firstly, literature establishing a three-way connection between bilingualism, executive function, and fronto-striatal loops is summarized. Secondly, a computational model of information processing in the basal ganglia is described, illustrating how the striatal nuclei function to transfer information between cortical regions under prerequisite conditions. Finally, this model is extended to describe how bilingualism may “train the brain,” enabling improved performance under conditions of competitive information selection during information transfer. Theoretical implications and predictions of this theory are discussed.
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International Journal of Bilingualism
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DOI: 10.1177/1367006912456617
published online 23 August 2012International Journal of Bilingualism
Andrea Stocco, Brianna Yamasaki, Rodion Natalenko and Chantel S Prat
improves executive function
Bilingual brain training: A neurobiological framework of how bilingual experience
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DOI: 10.1177/1367006912456617
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Bilingual brain training: A
neurobiological framework of how
bilingual experience improves
executive function
Andrea Stocco, Brianna Yamasaki, Rodion
Natalenko and Chantel S Prat
University of Washington, USA
Abstract
Individuals who develop bilingually typically outperform monolinguals on tests of executive
functions. This advantage likely reflects enhanced prefrontal function, but the mechanisms
that underlie this improvement are still poorly understood. This article describes a theory
on the nature of the neural underpinnings of improved executive function in bilinguals.
Specifically, we propose that growing up in a bilingual environment trains a gating system
in the striatum that flexibly routes information to the prefrontal cortex. This article is
divided into three sections. Firstly, literature establishing a three-way connection between
bilingualism, executive function, and fronto-striatal loops is summarized. Secondly, a
computational model of information processing in the basal ganglia is described, illustrating
how the striatal nuclei function to transfer information between cortical regions under
prerequisite conditions. Finally, this model is extended to describe how bilingualism
may “train the brain,” enabling improved performance under conditions of competitive
information selection during information transfer. Theoretical implications and predictions
of this theory are discussed.
Keywords
Bilingualism, executive functions, learning, prefrontal cortex, basal ganglia, striatum, inhibition,
shifting
It is well known that bilingual individuals outperform monolinguals in a number of tasks
involving executive function (e.g., Bialystok, 1998, 1999, 2004, 2009). The cognitive nature of
this advantage, however, is still debated, and its neural mechanism unspecified. In this paper,
we propose a brain-based computational model of information routing from the striatum to the
frontal cortex that simultaneously explains how bilingualism “trains” the brain and clarifies the
Corresponding author:
Chantel S Prat, Institute for Learning & Brain Sciences (I-LABS), Box 357988, University of Washington, Seattle, WA
98195-7988, USA.
Email: csprat@uw.edu
456617IJB
0010.1177/1367006912456617International Journal of BilingualismStocco et al.
2012
Article
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2 International Journal of Bilingualism 0(0)
nature of improved computations in bilinguals. Our explanation links recent developments
from two apparently distinct areas of neuroscience (the neuroscience of bilingualism and the
neuroscience of cognitive flexibility) to support the hypothesis that extensive bilingual experi-
ence reinforces the basal ganglia’s capacity to modulate the flow of signals across cortical
regions. This hypothesis helps unify existing results, explaining a number of apparently contra-
dictory findings in bilingual research, and is supported by recent findings on the neural sub-
strates of executive function. In addition, the use of a neurocomputational model of the basal
ganglia allows us to make predictions about the precise nature of improved information pro-
cessing in bilingual individuals.
This article is divided into three sections. Firstly, literature establishing a three-way connection
between bilingualism, executive function, and the basal ganglia is summarized. Secondly, a com-
putational model of information processing in the basal ganglia is described. This model is extended
to describe how bilingualism may “train the brain” to perform better under conditions of competi-
tive selection during information transfer, thus enabling earlier and improved executive function in
bilingual individuals. Finally, the theoretical implications and predictions of this theory are
discussed.
Improved executive function in bilinguals
The bilingual advantage on tasks that measure executive function has been well documented
throughout the lifespan (e.g., Bialystok, 2001, 2009; Bialystok, Martin, & Viswanathan, 2005).
For example, children developing bilingually show improved and earlier development of non-
linguistic executive function (Carlson & Meltzoff, 2008), and the effects of aging on declining
executive function are ameliorated in bilingual individual (Bialystok et al., 2005). Studies of
both children and adults show superior performance in a number of tasks that tap into execu-
tive function, such as the Simon task (Bialystok, Craik, Klein, & Viswanathan, 2004), task-
switching paradigms (Prior & MacWhinney, 2010), and tasks that require managing internal
response conflicts (Carlson & Metzoff, 2008). Most of these tasks do not directly assess lin-
guistic competence, and some of them (like the Simon task) are non-verbal in nature. In addi-
tion, research shows that the amount of bilingual experience an individual has (Carlson &
Meltzhoff, 2008) and their ability to control use of their two languages (e.g., Festman, 2012)
are also related to the extent to which improved executive function is observed. The research
suggests, therefore, that a particular linguistic experience, bilingualism, translates into a
domain-general advantage in cognitive function.
“Executive function” is a general name for a number of activities that, to a certain extent, can
be dissociated from one another. Experts in executive function have described at least three
distinct components of performance on executive tasks: inhibition, shifting, and updating (e.g.,
Miyake et al., 2000). These various aspects of executive function have been discussed and
debated in the bilingual research, but no consensus has been reached about which facet (or
facets) is specifically improved in bilinguals. Because increased demands for language selec-
tion and switching in bilinguals overlaps most directly with the inhibition and shifting compo-
nents of executive function, investigations of the executive advantage in bilinguals have
primarily focused on these aspects. Relatively little work has addressed a bilingual advantage
in updating, but one study did report a bilingual advantage on a visually cued recall task involv-
ing an updating component (Carlson & Meltzoff, 2008). In this section, we will provide a brief
overview of the remaining research that links bilinguals’ improved performance on executive
tasks to better inhibitory control and switching processes.
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Stocco et al. 3
Inhibitory control
One proposed explanation of bilinguals’ advantage in executive function is that it reflects a supe-
rior capacity for inhibitory control, or the capacity of controlling and halting dominant and auto-
matic responses that are strongly associated to environmental stimuli but are not appropriate for
the current task (Miyake et al., 2000). Bilinguals may benefit from additional inhibitory control
because they need to deal with interfering responses from the unwanted language—responses that
are typically activated in parallel with those of the target language (e.g., Bialystok, 2001; Bialystok
& Martin, 2004; Carlson & Meltzoff, 2008; Festman, Rodriguez-Fornells, & Münte, 2010). In an
investigation comparing the performance of bilinguals and monolinguals across three experi-
ments using the Simon task, a non-verbal response competition paradigm (Simon, Acosta,
Mewaldt, & Speidel, 1976), Bialystok and colleagues (2004) presented particularly compelling
evidence that bilingual individuals exhibit advanced inhibitory control. The Simon task requires
participants to respond to a simple visual stimulus with the left or right hand; the response is based
on the stimulus’ color. When the stimulus is presented on a screen position that is opposite to the
response’s hand (i.e., one has to answer with the left hand but the stimulus is presented on the
right), response times increase, implying an additional effort to control the natural tendency to
respond with the hand that is on the same side as the stimulus. Bialystok et al. (2004) found that,
across different experiments and conditions, bilinguals’ response times were less affected by the
spatial interference during incongruent trials, suggesting improved inhibitory control. These
results, however, did not replicate in subsequent experiments (Bialystok, 2006; Bialystok, Martin,
& Viswanathan, 2005).
Colzato et al. (2008) advanced the debate by outlining two possible models for inhibitory pro-
cess in bilinguals: (a) an active model in which inhibition spreads “vertically” from task goals to
the irrelevant responses; and (b) a reactive model where task goals activate both relevant and irrel-
evant response, but inhibition spreads “horizontally” from the relevant to the irrelevant ones.
Colzato et al. (2008) compared the performance of bilinguals and monolinguals across three tasks
that engage different inhibitory models: the stop-response task (Logan & Cowan, 1984), the inhi-
bition-of-return task (Posner & Cohen, 1984), and the attentional blink task (Raymond, Shapiro, &
Arnell, 1992). Bilinguals did not exhibit any advantage over monolinguals in the first two tasks,
but they did show a clear disadvantage in the attentional blink task. In this task, participants
observe a rapid serial visual presentations of simple visual stimuli (e.g., numbers) in which two
targets (e.g., letters) are embedded. While participants can easily detect both targets when they are
either in immediate succession or separated by three or more stimuli, they are typically unable to
report the second target when it is separated from the first by one or two intermediate distractors.
This effect is akin to a temporary “blink” of visual attention. Colzato et al. (2008) found that blink
effects were larger in bilinguals than in monolinguals. The authors interpreted this finding as the
result of inhibition originating from the attention devoted to the first stimulus, therefore favoring
the “reactive” model of inhibition (Colzato et al., 2008). Our model offers a different interpretation
of the results discussed in this section. Specifically, it proposes that the larger blink effect in bilin-
guals is due to the top-down processing of the first stimulus that is mediated by the basal ganglia,
a set of brain nuclei that are particularly important for bilingual language production and override
the automatic visual processing of the second stimulus.
In summary, while improved inhibitory control has been one of the most popular explanations
of improved executive function in bilinguals, a number of recent experimental findings suggest
that this may not be the best characterization of bilinguals’ cognitive advantage (e.g., Bialystok,
2006; Colzato et al., 2008; Festman et al., 2010).
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Set shifting
Another possible explanation for improved executive function in bilinguals is that they are better
at the shifting component of complex tasks, or the capacity of flexibly switching back and forth
between multiple tasks, mental operations, or response sets (Miyake et al., 2000). The assumption
behind this hypothesis is that bilingual experience is a linguistic instantiation of task set shifting,
and thus bilinguals’ advantage in executive function reflects improved shifting abilities in general.
In other words, to be a fluent bilingual, individuals need to switch effectively between the appro-
priate grammatical rules and phonological outputs for each of the languages they speak. Thus, it is
conceivable that bilinguals obtain a general benefit from this continuous practice with shifting.
Evidence in this sense can be seen in a study by Festman et al. (2010) that compared the perfor-
mance of a group of bilinguals across different tasks. In this study, participants were initially
required to name pictures alternating between two languages. The number of errors made (i.e.,
failures to switch language) was taken as a measure of their language control ability. The authors
then proceeded to divided the group into “switchers” (less errors, better control) and “non-
switchers” (more errors, worse control), and compared these two subgroups on a number of execu-
tive function tasks. It was found that “switchers” also performed better on all the executive func-
tion tasks, suggesting that having better executive functions is related to the capacity to switch
between languages.
A few studies have specifically compared the set-shifting abilities of bilinguals and monolin-
guals. This line of research has primarily employed task-switching paradigms to investigate shift-
ing abilities. In task-switching experiments, participants shift between two tasks that can be
performed on an identical set of stimuli (e.g., Monsell, 2003). For instance, the experimental stim-
uli might be one-digit numbers, and participants might be required to switch between categorizing
each digit as even or odd (Task 1) or as smaller or larger than five (Task 2). The first trial after
participants switch tasks takes longer than any trial where they are continuing to perform the same
task. The increase in reaction time constitutes the switch cost, which is interpreted as the additional
control needed to prepare for a new set of mental operations. At least two studies (Garbin et al.,
2010; Prior & MacWhinney, 2010) compared bilinguals and monolinguals in a task-switching
paradigm, and found that bilinguals exhibit significantly lower switch costs than monolinguals,
suggesting a more efficient shifting processes.
One of the most intriguing findings in the task-switching literature is the task-switching asym-
metry observed when individuals switch from a more difficult, less automatic task to an easier, or
more automatic, task (e.g., Monsell, 2003). In this condition, a larger switching cost is observed
than when switching from an easier, more automatic task to a more difficult one (e.g., Allport,
Styles, & Hsieh, 1994; Yeung & Monsell, 2003). Interestingly, this asymmetry has a direct coun-
terpart in the bilingual literature: when switching between languages, “unbalanced” bilinguals (i.e.,
bilingual individuals who are more proficient in L1 than L2) find it harder to switch from the less
proficient to the most dominant language, and not vice versa (e.g., Costa & Santesteban 2004).
This finding provides empirical support that switching between languages for bilinguals involves
some of the same general information-processing principles that operate in non-linguistic task-
switching paradigms. This lends plausibility to the theory that bilinguals’ cognitive advantage
arises because bilingual practice trains the switching sub-component of executive function.
One problem with both the inhibition and switching explanations is that they rely on hypotheti-
cal cognitive constructs that are not well specified at the neural or computational level. For instance,
vastly different computational models can account for the switching costs (Altmann & Gray, 2002;
Gilbert & Shallice, 2002; Schneider & Logan, 2005; Sohn & Anderson, 2001); these models rely
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Stocco et al. 5
on different underlying biological mechanisms to explain the nature of changing tasks. The next
two sections will review the most relevant findings about the neural bases of bilingualism and their
connections with the neural bases of executive function.
The neural basis of bilingualism
Differences in cognitive function ultimately result from differences in brain processes. Thus, what-
ever the nature of the bilingual advantage in executive function is, it must be reflected in some
feature or features that characterize the bilingual brain. Investigations of the bilingual brain have
centered around two problems: how multiple languages are represented in the brain, and how they
are controlled in the brain (see Abutalebi & Green, 2007, for a review).
Recent neuroimaging research suggests a great deal of overlap in the representation of multiple
languages (see Abutalebi & Green, 2007, p. 256, Table 1). An abundance of studies (Abutalebi,
2008; Buchweitz, Mason, Hasegawa, & Just, 2009; Chee, Tan, & Thiel, 1999; Dehaene et al.,
1997; Gandour, et al., 2007; Hernandez & Meschyan, 2006; Vingerhoets et al., 2003) showed that
second languages (L2) have a more distributed representation and engage larger cortical areas than
do first languages (L1). Most of these differences, however, can be accounted for by differences in
proficiency levels in the two languages (Abutalebi, 2008; Perani et al., 2003; Yokoyama et al.,
2006). Thus, the general view is that a highly overlapping network of regions is recruited by both
languages, and that eventual differences depend on the recruitment of additional regions (often
prefrontal regions) to compensate for the less automatic control of the second language (Abutalebi
& Green, 2007). An example of the degree of overlap between L1 and L2 comes from a study by
Buchweitz, Shinkareva, Mason, Mitchell, and Just (2012). The authors used machine learning
techniques to investigate the neural substrates of semantic representations of L1 and L2 in profi-
cient English-Portuguese bilinguals. In particular, the authors trained a multi-voxel pattern classi-
fier to correctly associate distinct patterns of activation elicited by words in L1 (e.g., the pattern of
activation elicited by the Brazilian word “Avião”), and found that the same classifier could reliably
recognize the homologous words when presented in L2 (e.g., the English word “Airplane”). This
finding suggests that words in L1 and L2 not only recruit the same brain network to be processed,
but are similarly represented at the neural level.
The fact that L1 and L2 languages share a common neural substrate implies that languages must
compete for access to shared neural resources. Thus, a control mechanism must be operating in the
bilingual brain to monitor and select which language to use. In our opinion, the neural substrates of this
control mechanism are tied to the neural mechanisms of the shifting component in executive function.
Investigations of bilingual language control typically involve translation paradigms, language-
switching paradigms, or language selection paradigms (see Abutalebi & Green, 2008, for a review).
Research has yielded regions of activation that highly overlap with those observed in non-
linguistic cognitive control tasks, such as the prefrontal cortex and the anterior cingulate (e.g.,
Hernandez, Martinez, & Kohnert, 2000; Rodriguez-Fornells et al., 2005). Of particular interest to
our hypothesis, a series of investigations have reported subcortical involvement, specifically the
basal ganglia, during switching or translating paradigms (e.g., Lehtonen et al., 2005; Price, Green,
& von Studnitz, 1999). This research is discussed in more detail in the subsequent section.
The role of the basal ganglia in language
The basal ganglia are a set of interconnected gray matter nuclei located in the middle of the brain.
Together, these nuclei form a complex circuit that, by maintaining a careful balance of inhibitory
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Table 1. Comparison of basal ganglia activation foci in neuroimaging studies of bilingualism.
Study Atlas Region
Coordinates
(x, y, z)
Analysis
Wartenburger,
Abutalebi,
Cappa,
Villringer, &
Perani (2003)
MNI
L putamen/thalamus –20 8 6
Grammatical judgment
comparison
L caudate nucleus –20 0 17
R putamen/thalamus 20 4 0
Abutalebi,
Simona,
et al. (2007)
Talairach
L head of caudate –2 10 14
Language switching vs. non-
switching in the middle of a
sentence
L putamen –28 –12 10
R putamen 28 –6 8
R globus pallidum 14 –6 –2
Abutalebi,
Annoni,
et al. (2007)
Talairach
L caudate nucleus –16 6 6
Bilingual vs. monolingual in
naming
R caudate nucleus 16 8 12
L caudate nucleus –18 0 22
Bilingual > monolingual in
naming
L caudate nucleus –10 4 4
Naming in L1 > L2R caudate nucleus 14 4 6
R putamen 30 14 10
Garbin et al.
(2010).
MNI L striatum –16 10 2
Bilinguals > monolinguals in
task switching
Waldie,
Badzakova-
Trajkov,
Miliivojevic, &
Kirk (2009)
Talairach L caudate tail –15 –31 20
Bilinguals > monolinguals in
Stroop incongruent trials
Ghosh, Basu,
Khushu, &
Kumaran (2009)
Talairach
R sublobar extra
nuclear, caudate body
14 –2 16
Lexical decision > syllable
discrimination
Majerus et al.
(2008)
MNI
L caudate tail –12 –30 –18
Low proficiency > high
proficiency
R caudate tail 22 –38 14
L pallidum –12 0 –4
High proficiency > Low
proficiency
R pallidum 14 2 –14
Klein, Milner,
Zatorre, Meyer,
& Evans (1995)
Talairach L putamen –15 10 –6
Translation (L1 to L2) vs.
repetition (L1 to L1).
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Stocco et al. 7
Study Atlas Region
Coordinates
(x, y, z)
Analysis
Grogan, Green,
Ali, Crinion, &
Price (2009)
MNI
R head of caudate 14 0 16
Correlation between phonemic
task and gray matter volume
L head of caudate –14 10 14
R head of caudate (L2) 16 10 14
Phonemic task > semantic task
L head of caudate (L2) –14 14 10
R head of caudate (L1) 12 –2 16
L head of caudate (L1) –8 4 20
Klein, Watkins,
Zatorre, &
Milner (2006)
Talairach
L head of caudate –15 13 6
Word repetition minus silent
baseline in L2
L putamen –28 13 -8
Meschyan &
Hernandez
(2006)
Talairach
R putamen 24 10 14 L2 > L1 in single word reading
R putamen 26 10 12 L2 > rest in single word reading
Rueschemeyer,
Fiebach, Kempe,
& Friederici
(2005)
Talairach
L caudate –5 18 3
Correct sentences: Native
speakers vs. non-native
speakers L2 > L1
R caudate 11 15 6
L caudate –7 6 3
Syntactically anomalous
sentences: Native speakers vs.
non-native speakers
R caudate 8 12 9
L caudate –5 6 3
Semantically anomalous
sentences: Native speakers vs.
non-native speakers L2 > L1
R caudate 8 12 9
Price, Green,
& von Studnitz
(1999)
Talairach
L putamen/head of
caudate
–16 18 0
Translation relative to
reading—increases in
activation
–18 22 16
R putamen/head of
caudate
16 26 2
18 14 4
18 8 14
Lehtonen et al.
(2005)
MNI L globus pallidus –16 4 –4
Sentences translation >
control
Crinion et al.
(2006)
MNI
L caudate –6 6 8
Language-specific priming
(English-German)
L caudate –4 14 2
Language-specific priming
(English-Japanese)
Klein, Milner,
Zatorre, Meyer,
& Evans (1995)
Talairach L putamen –15 10 –6 L1 to L2 translation
MNI: Montreal Neurological Institute template.
Talairach: Talairach-Tournoux template.
Table 1. (Continued)
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8 International Journal of Bilingualism 0(0)
and excitatory signals conveyed through parallel pathways, controls the thalamic inputs to the
frontal lobe (Albin, Young, & Penney, 1989; DeLong, 1990). The most important structure within
the basal ganglia is the striatum, which is the largest of the basal ganglia nuclei and constitutes the
input station of the circuit. The striatum receives organized projections from the entire cortex
(Alexander, DeLong, & Strick, 1986), and projects to and modulates the activity of lower-level
nuclei of the basal ganglia, which ultimately control the output of thalamic neurons to the prefron-
tal cortex. Thus, the striatum is in an ideal position to gather information from all the cortical areas
in the brain, and use this information to modulate the subcortical inputs to the prefrontal cortex. In
turn, the prefrontal cortex is the part of the brain that is responsible for higher-level behavior
(Miller, 2000), including working memory (Cohen et al., 1997), planning (Shallice & Burgess,
1991), rule-based behavior (Strange, Henson, Friston, & Dolan, 2001) and, of course, language
(e.g., Just, Carpenter, Keller, Eddy, & Thulborn, 1996).
Until recently, the role of the basal ganglia has been largely disregarded in neuroimaging
investigations of language processes—an example of a more general “cortico-centric myo-
pia” that has characterized the cognitive neurosciences (Parvizi, 2009). However, neuropsy-
chological studies have shown that language impairments such as aphasia, normally associated
with cortical lesions, can also originate from basal ganglia damage (e.g., Brunner, Kornhuber,
Seemüller, Suger, & Wallesch, 1982; D’Esposito & Alexander,1995) or from basal ganglia
abnormalities of genetic origin (e.g., Vargha-Khadem et al., 1998; Watkins et al., 2002). In
addition, an increasing number of contemporary neuroimaging studies have discussed the
relevance of the basal ganglia to language processing, suggesting that this region is substan-
tial for the control of language (e.g., Friederici, 2006; Prat & Just, 2011). To illustrate, we
conducted a review of existing neuroimaging research and found that 16 investigations of the
neural basis of bilingualism reported activation foci within the basal ganglia nuclei under
different conditions (see Table 1). The centroids of these activations in Montreal Neurological
Institute (MNI) coordinates are depicted in Figure 1. Taken together, Figure 1 and Table 1
suggest that basal ganglia activation is often found (although not always discussed and
addressed) in studies of bilingualism. Furthermore, the distribution of the activation foci in
Figure 1 follows a consistent pattern, with the majority of reported foci concentrated on the
head of the caudate nucleus, which crucially receives inputs from (and projects to) the pre-
frontal cortex and has been associated with individual differences in executive function (e.g.,
Prat & Just, 2011).
One explanation for the different contributions of cortical and subcortical structures to lan-
guage processes is that language is underpinned by two processes with distinct neural instantia-
tions: a semantic representation system (which involves the cortex) and a grammatical (or rule
composition) system (which involves subcortical structures: e.g., Paradis, 2004; Ullman 2001a,
2001b; Ullman et al., 1997). This framework largely overlaps with the ideas of language repre-
sentation and control previously discussed; however, the constructs are defined within a mem-
ory framework. Within this framework, lexical information is represented as part of the
declarative memory system, while syntactic knowledge is stored as part of the procedural mem-
ory system. In the human brain, declarative memory is thought to be underpinned by cortical
structures, and in particular with the temporal lobe (for the encoding of information: Squire,
1992, 2004) and the left inferior frontal gyrus (for the retrieval of information: Sohn, Goode,
Stenger, Carter, & Anderson, 2003; Thompson-Schill, D’Esposito, Aguirre, & Farah, 1997).
Procedural memory, on the other hand, is typically associated with the basal ganglia circuit
(Cohen & Squire, 1980; Packard & Knowlton, 2002); thus, this framework establishes a link
between linguistic rule representation and the basal ganglia. Computationally, the distinction
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Stocco et al. 9
between dictionary-like semantic knowledge and rule-like procedural knowledge provides an
intuitive and powerful basis for explaining the complex phenomenon of natural language use.
In fact, this dual mechanism has been applied in computational models of language acquisition
(Taatgen & Anderson, 2002), understanding (Lewis & Vasishth, 2005), and language impair-
ments (Stocco & Crescentini, 2005), and is a staple of general-purpose cognitive architectures
such as Adaptive Control of Thought—Rational (ACT-R: Anderson et al., 2004) and Executive
Processes / Interactive Control (EPIC: Meyer & Kieras, 1997).
The idea that syntactic rules can be encoded in the basal ganglia is supported by this cir-
cuit’s involvement in acquiring procedural knowledge (Knowlton, Mangels, & Squire, 1996).
Experiments with animals have shown, for instance, that basal ganglia impairments prevent
the acquisition of stimulus–response associations (e.g., Packard & McGaugh, 1992). In
humans, diseases affecting the basal ganglia (e.g., Parkinson’s or Huntington’s disease)
impair the acquisition of new perceptual-motor skills, such as mirror reading (Cohen &
Squire, 1980) and the acquisition of complex stimulus–response associations (Knowlton
et al., 1996). Thus, experimental and neuropsychological evidence suggest that the basal
ganglia circuit is responsible for learning and applying complex stimulus–response transfor-
mations—a function that is consistent with the application of grammatical rules.
Figure 1. Locations of basal ganglia foci of activations in 16 neuroimaging studies of bilingualism (see Table
1 for references). The foci of activations are overlaid on the Montreal Neurological Institute (MNI) Colin 27
template (Sagittal view, x = –20). Different colors (color online only) represent results from different studies;
dots of the same color represent distinct foci of activation reported in the same paper (e.g., in two different
contrasts). Stereotactic coordinates that were originally given in the Talairach-Tourneaux system were
converted to the MNI system using the non-linear transformation algorithm provided in the GingerALE
software (Eickhoff et al., 2009).
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The basal ganglia and the bilingual brain
This declarative/procedural framework can be usefully applied to explain the proficiency-related
differences between L1 and L2 in late bilinguals. While learning a second language, grammatical
rules are more likely to be encoded explicitly, and thus retrieved and held in working memory dur-
ing language tasks. This additional activity would be reflected in larger activation of prefrontal
regions for L2 compared to L1. With increasing practice, however, grammatical rules for L2 would
be eventually stored in the basal ganglia in the form of procedural rules, thus reducing the differ-
ence between L1 and L2 (Paradis, 2004; Ullman, 2001b). This view is confirmed by the fact that,
in bilingual individuals with degenerative disorders of the basal ganglia such as Parkinson’s dis-
ease, greater impairment is found in the language spoken with higher proficiency, whereas less
impairment is observed in the language spoken with less proficiency (Zanini, Tavano, & Fabbro,
2010; Zanini et al., 2004; see Fabbro, 2001, for a review).
However, experimental and neuropsychological evidence suggest that, in the bilingual brain,
the basal ganglia play the additional role of controlling which language to use. For instance, bilin-
gual patients with injuries spanning the basal ganglia circuit show a pathological tendency to
switch back and forth between languages (Fabbro, 2001). This neuropsychological evidence is also
corroborated by experimental investigations; for instance, direct stimulation of the left striatum
(the largest nucleus of the basal ganglia) during open-skull surgery causes spontaneous language
switching (Robles, Gatignol, Capelle, Mitchell, & Duffau, 2005).
One important neuroimaging study conducted by Crinion et al. (2006; see also Friederici,
2006, for a discussion of this study’s implications) examined the nature of automatic language
switching by using a priming paradigm. In the experiment, bilinguals responded to words that
were preceded by either semantically related or unrelated primes. More importantly, the prime
word was presented in either the same language as the target word, or in a different language.
Noticeably, the authors did not compare L1 against L2, but instead used priming to investigate
the nature of language processing when a language switch (L1 or L2) is processed. Semantic
priming crosses the language boundary, so that seeing the prime word “Salmon” in English still
results in a decreased response time for the target word “Trout” in German (“Forelle”). The
priming effect was significant in a distributed cortical network involving most of the brain
regions that were recruited by the task. The only exception to this rule was a region in the left
striatum. Semantically related words reduced activation in this region only when they were in
the same language. In other words, the priming effect in the striatum was selectively modulated
by the specific language input.
Crinion et al.’s (2006) finding suggests that the striatum is involved in monitoring which lan-
guage is in use. It is conceivable that damage to this structure impairs a specific brain circuit that
controls which language is used, thus explaining the neuropsychological symptoms described
above. Friederici (2006) recognized the connection between this putative function of language
selection and the established role of the basal ganglia circuit in selecting motor programs (e.g.,
Albin et al., 1989).
Summary
In summary, investigations of the nature of language processing in bilinguals have shown that dif-
ferent languages are represented in highly overlapping cortical networks, especially when one
accounts for different levels of proficiency and exposure. The basal ganglia seem to play a role
both in controlling language selection and in subsequent application of rules. Importantly, in the
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Stocco et al. 11
bilingual brain, this subcortical circuit is involved in a specific function (i.e., switching or translat-
ing between languages) that is analogous to the facet of executive function, where bilinguals seem
to excel (i.e., switching between tasks or response sets). The next section will describe the func-
tions of this circuit in more detail and their relevance for executive function and shifting.
The basal ganglia and executive function
How might practice with language switching in bilinguals provide an advantage in executive func-
tion? We propose that the critical link between bilingual experience and improved executive func-
tion arises with training of the fronto-striatal loops, which are involved in both language control
and executive function.
The basal ganglia are primarily known for their role in learning and skill acquisition (Knowlton
et al., 1996; see Packard & Knowlton, 2002, for a review). However, this circuit has been impli-
cated in a larger number of higher-level cognitive functions, including working memory (McNab
& Klingberg, 2008), decision making (Montague, King-Casas, & Cohen, 2006; Tom, Fox, Trepel,
& Poldrack, 2007), language (Frederici, 2006; Prat & Just, 2011; Ullman, 2001a, 2001b), planning
(Monchi, Petrides, Strafella, Worsley, & Doyon, 2006), and reasoning (Frank, Seeberger, &
O’Reilly, 2004; Stocco & Anderson, 2008).
Of particular interest to the theory presented herein, the basal ganglia have also been pro-
posed to play a role in the shifting component of executive function. Some evidence of this
comes from deficits observed in patients with diseases such as Parkinson’s and Huntington’s
disease, which selectively damage the basal ganglia. Patients with Parkinson’s disease, for
instance, have problems switching to new rules in the Wisconsin Card Sorting Task (Gotham,
Brown, & Marsden, 1988; Owen, Roberts, Hodges, & Robbins, 1993). In this task, participants
go through a deck of cards with colored symbols and are required to put them in piles according
to a specific rule. The rule itself is not revealed explicitly; instead, participants need to rely on
the yes/no feedback from the experimenter to know whether putting a card in a particular pile
(e.g., the pile with all red symbols) is a correct move. Unpredictably, the experimenter some-
times changes the sorting rule (switching from color to shape), so that participants have to learn
a different criterion for piling up the cards.
Both Parkinson’s (e.g., Rogers et al., 1998) and Huntington’s (e.g., Aron et al., 2003)
patients exhibit impairments when shifting to new task rules in standard task-switching para-
digms, again suggesting a specific involvement of the basal ganglia in the control of alternat-
ing behavioral rules. Additional evidence can be found in a number of neuroimaging studies,
which report basal ganglia activation in healthy populations during task-switching experi-
ments (Cools, Clark, & Robbins, 2004; Crone, Wendelken, Donohue, & Bunge 2006; Gu et
al., 2008; Sohn, Ursu, Anderson, Stenger, & Carter, 2000). Finally, a critical link between set
shifting, the basal ganglia, and bilingualism is reported in one neuroimaging investigation of
task switching (Garbin et al., 2010). The authors compared the brain activation of bilinguals
and monolinguals while performing a task-switching paradigm. The paradigm was designed
to be non-linguistic, with the two tasks involving classifying colored shapes according to
either their shape (e.g., circle or square) or their color (e.g., orange or blue). Consistent with
previous findings (e.g., Prior & MacWhinney, 2010), bilinguals showed a reduced switching
cost (e.g., reduced increase in latency) when switching between tasks. Most importantly,
however, the size of the switch costs was negatively associated with the activity of the left
caudate nucleus in bilinguals, suggesting that successful recruitment of this nucleus results
in faster switches. The same correlation was not observed in monolinguals, suggesting that
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one crucial difference between the bilingual and the monolingual brain is that the bilingual
brain relies on the left caudate to switch between tasks, while the monolingual brain does not
(Garbin et al., 2010).
In summary, the literature suggests a three-way connection between executive function, the
basal ganglia, and bilingualism. Bilinguals exhibit behavioral advantages in executive func-
tion, which reflect, in part, superior cognitive control in switching between different rule-
based behaviors. This superior control ability relies on the basal ganglia, a set of nuclei that
are crucially involved in both switching between different task sets and in switching between
languages. Two questions arise at this point. (a) What is the mechanism by which the basal
ganglia contribute to linguistic and behavioral switching? (b) Can we use this information to
better understand how growing up in a bilingual environment trains the brain in a way that
generalizes to non-linguistic executive function? The next two sections will attempt to provide
answers to both questions.
Identifying basal ganglia computations in task and language switching
To understand the mechanism behind improved executive function in bilinguals, one must first
specify the neural computations that take place in the basal ganglia. Specifically, we must deter-
mine whether the same neural computations are involved both in the control and switching between
languages and in the control and switching between other, non-linguistic, tasks. In addition, we
must determine how this circuit is shaped by practice and, in particular, how domain-specific train-
ing (i.e., speaking two languages) generates a domain-general benefit (i.e., improved executive
function).
One way to better understand the computations of a specific neural circuit is by generating a
computational model of the circuit. Biologically based models are particularly useful, because
they provide a direct connection between anatomical structure and function (e.g., O’Reilly &
Munakata, 2000). Because of their elaborate patterns of connectivity with the cortex, and their
wide involvement in cognitive functions, several models of the basal ganglia have been gener-
ated (see Cohen & Frank, 2009; Gillies & Arbuthnott, 2000, for reviews), and some consensus
has emerged about the basic nature of their computations. According to several of these models,
the basal ganglia provide a complex and flexible mechanism to control information flow to the
prefrontal cortex. In many recent models (e.g., Amos, 2000; Frank, Loughry, & O’Reilly, 2001;
Gurney, Prescott, & Redgrave, 2001; O’Reilly & Frank, 2006; Stocco, Lebiere, & Anderson,
2010) this “gating” of signals to the prefrontal cortex is performed by monitoring all possible
incoming signals from the cortex, and then using the internal inhibitory connections within the
basal ganglia to suppress those signals that are not of interest. The signals of interest are then
selected and routed to the prefrontal cortex.
This paper adopts one such model, the Conditional Routing Model proposed by Stocco, Lebiere,
and Anderson (2010), as a framework for understanding the role of basal ganglia function in the
bilingual brain. This model offers a number of advantages over other models. Firstly, it provides a
detailed account of both how signals are gated to the prefrontal cortex and of how rule-based
behaviors can be encoded in the basal ganglia. Secondly, this model provides a means to explain
the activity of the striatum in terms of the execution of abstract “IF–THEN” rules. Finally, the
model is biologically plausible and incorporates all of the known inhibitory and excitatory connec-
tions between the basal ganglia, the thalamus, and the cortex. These features are important because
they can potentially explain both how the appropriate language outputs and grammar processes are
selected and switched in the bilingual brain.
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Stocco et al. 13
The conditional routing model
According to the conditional routing model, the basal ganglia operate as a system that imposes
order over the highly overlapping exchange of signals between networks of cortical regions. In the
absence of basal ganglia interventions, the flow of signals across the network is determined by the
relative strength of cortico-cortical projections. Such relative strength is in turn shaped by previous
practice and reward contingencies, and under normal conditions is sufficient to produce effective
behavior. However, during learning (where preexisting cortical networks cannot accomplish the
task at hand) or in situations where predetermined or automatized cognitive routines cannot accom-
plish a task goal (such as in a task-switching paradigm), the basal ganglia shape behavior by prior-
itizing different signals and overriding preexisting cortico-cortical connections.
This idea is visually summarized in Figure 2. Figure 2(a) illustrates a situation where a single
prefrontal area (the “target”) receives competing signals from three different regions (the “sources”)
at the same time. As an example, these regions are placed in the frontal (A), parietal (B), and tem-
poral (C) lobes. These three regions contain different types of information, and the “target” pre-
frontal area must select a signal from only one of them. Since the prefrontal cortex lies at the apex
of a hierarchy of converging pathways (e.g., Miller, 2000), such a conflict situation (where multi-
ple signals compete to affect a single region) must not be uncommon. In the absence of basal
ganglia routing, the relative strength of these projections, shaped by previous experience and
reward contingencies, is sufficient to prioritize signals and produce efficient behavior. In Figure
2(a), the relative strength of cortico-cortical projections is represented by the different lines, with
dashed lines indicating weaker connections and solid lines depicting stronger ones. In this hypo-
thetical situation, Region B in the parietal lobes is sending the signal that will have the largest
influence on the prefrontal target region.
Figure 2. A visual illustration of the role of the basal ganglia in controlling how information is routed in
the cortex. (a) Because of the large number of incoming projections, the prefrontal cortex receives many
concurrent signals from different cortical areas; under normal conditions, the region with the strongest
cortico-cortical connections (region B, continuous line) is more likely to successfully affect the prefrontal
region than other regions with weaker connection (regions A and C, dotted lines). (b) The basal ganglia
can modify the flow of signals through the cortex by selecting a different pathway (from region B, thicker
continuous line) and enhancing its strength through the fronto-striatal loops.
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Under certain situations, however, behavior must be flexibly modified and adapted to perform
novel tasks, and the same cortical input region must shift its priority to inputs from another region
or regions (e.g., when switching tasks requires attending to a new set of features of the stimuli, or
when switching languages requires applying a new set of rules for parsing sentences). According
to the conditional routing model, this change in behavior is mediated by the basal ganglia. In par-
ticular, the model suggests that the basal ganglia circuit can enhance signals coming from a selected
source region, thus increasing the probability of this source’s signal to influence the behavior of the
target region despite otherwise weaker cortico-cortical connections. The name “Conditional
Routing” refers precisely to these circumstances, which can be seen as imposing new routes of
information transfer between cortical regions when specific circumstances (or “conditions”) arise.
An instance of conditional routing is depicted in Figure 2(b), which illustrates a hypothetical situ-
ation in which the basal ganglia are routing information from Region C in the temporal lobe to the
target area, thus amplifying the signal and reprioritizing the cortico-cortical connections such that
Region C is now influencing the target area rather than Region B. In Figure 2(b), the effect of the
basal ganglia is illustrated by the thicker line from the temporal region to the target, which replaces
the previously weaker (dotted) line.
This process is made possible by the internal organization of the basal ganglia, and in particular
of the striatum. According to Stocco, Lebiere, and Anderson (2010), the striatum is internally
organized in a way that mirrors the cortico-cortical network, so that “routing” a signal corresponds
to activating one particular set of neurons that would eventually activate the corresponding cortico-
cortical projection. Importantly, the authors have shown that the routing activity of the basal gan-
glia can be understood as the execution of conditional rules (i.e., rules of the form “IF … THEN
…”). The conditional routing mechanism of this framework has essential implications for the two
cognitive functions that are discussed in this paper, namely executive functions and language. The
next sections will provide a brief overview of these implications.
Conditional routing, executive functions, and language
As outlined above, there is experimental evidence that connects the basal ganglia to the shifting
component of executive function (Yehene, Meiran, & Soroker, 2008). Within the conditional rout-
ing framework, such shifting results naturally from the capacity of the basal ganglia to modify the
course of information flow within the cortex (e.g., Amos, 2000; Stocco, Lebiere & Anderson,
2010).
According to the conditional routing framework, the importance of basal ganglia function to
language arises in part because of the complexity of linguistic rules. Complex rules pose a natural
challenge to established cortico-cortical pathways, because they may require flexible activation of
particular pathways under specific circumstances. In addition, grammatical rules often depend on
complex dependencies between their terms. Take, for instance, the relatively simple English rule
for pluralization, which can be stated as: “IF X is the singular form and you want to use the plural
form, THEN add -s to X.Applying this rule requires knowing the specific conditions under which
it can be applied (for instance, it does not apply to the word “sheep”), mapping the proper word to
the variable X, and applying an invariant constant term (“-s”). The conditional routing model pre-
dicts that, with learning, grammatical rules become permanently stored in the basal ganglia in the
form of patterns of synaptic strengths that determine signal routing (Stocco, Lebiere & Anderson,
2010).
Thus, the conditional routing model can explain why the impact of basal ganglia lesions on
language depends on proficiency (Fabbro, 2001; Zanini et al., 2004). With practice, rules become
encoded in the basal ganglia in abstract form, and can be applied whether or not an explicit,
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Stocco et al. 15
conscious representation of the rule exists in the cortex. The model also explains why damage to
the basal ganglia would impair precisely these types of automated rule-based behaviors, while
sparing to a greater extent behaviors where the rules are explicitly encoded and represented in the
cortex (for example, how to pluralize nouns in a less-proficient second language).
The conditional routing model also makes specific predictions about the nature of linguistic
errors and mistakes that occur in basal ganglia patients. In particular, the model predicts that com-
plex transformations, requiring simultaneous integration of many sources of information, will
require the computations of the striatum, whereas the more direct stimulus–response mappings can
be handled by cortico-cortical connections. Because of this dual representation, the model predicts
that basal ganglia lesions should impair the production of sentences that require complex gram-
matical transformations (because they rely on learned patterns in the striatum), but spare those
structures that are highly familiar and automatic, such as idiomatic expressions (because their fixed
structure remains stored within cortico-cortical connections). Consistent with this prediction,
patients with language impairments due to basal ganglia lesions exhibit impoverished grammar in
their native language and produce a large amount of language automatisms (Brunner et al., 1982;
Code, 1994). While the idea that the basal ganglia encode syntactic rules is common to other
accounts (e.g., Paradis, 2004; Ullman, 2001a), the prediction that familiarity predicts the extent to
which the basal ganglia will be involved is specific to the conditional routing model.
The connection between language and executive function can be fully appreciated when one
notices that, within the conditional routing model, language and executive function share a com-
mon set of computations that rely on the basal ganglia circuitry. In particular, the capacity of shift-
ing between tasks and mental sets and the capacity of applying complex rules both depend on the
ability of the basal ganglia to properly and timely route the appropriate signals within the network
of regions involved in a task. Thus, even if distinct cognitive functions (e.g., language and execu-
tive functions) are underpinned by different brain networks, they still rely on the basal ganglia
when the communication between different regions needs to be organized according to some com-
plex and non-habitual template. This common ground is central to our theory about how practice
within one cognitive function (i.e., managing two languages in the case of bilingualism) can have
positive effects on the other (i.e., executive functions).
Conditional routing and bilingualism
To understand how being raised bilingually “trains the brain” in a way that gives rise to improved
executive function, one must first explain how bilingualism shapes the basal ganglia circuit. From
the point of view of the conditional routing framework, bilingual language experience imposes two
concurrent challenges on the basal ganglia circuit. The first is that representation of the two lan-
guages needs to be kept distinct, despite the overlapping contexts and information they share.
Think, for instance, of an Italian-English bilingual; both languages have morphological rules to
mark the plural, but the two rules are different. Deciding which rule to apply depends only on the
specific intended language output. According to the conditional routing model, the striatum is nec-
essary to select the appropriate rule based on a specific linguistic context (IF the desired output is
English, THEN add “s” to the target noun to pluralize). Recent research has also provided evidence
that the basal ganglia are important for maintaining distinct representations of words between lan-
guages (Crinion et al., 2006). In Crinion’s experiment, the striatum was the only region that showed
language-specific priming effects (i.e., it was the only region where reduced activation was only
observed for semantically related words presented in the same language). As the authors acknowl-
edged, this effect implies that the activity of the striatal neurons is modulated by language, consist-
ent with its role in discriminating between linguistic contexts. Additional support for this can be
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found in research showing that direct electrical stimulation of the striatum causes spontaneous and
uncontrolled switches between L1 and L2 (Robles et al., 2005).
Thus, for bilinguals, the basal ganglia (and in particular the striatum) face increasing
demands to select appropriate rules and representations, and to switch between rules and repre-
sentations depending on the intended language. Much like switching tasks, switching between
languages requires the capacity to override the signals from a network of brain regions that are
still active. In many ways, it is even more difficult than the standard task-switching paradigm
as it requires switching between two “tasks” (L1 and L2) that are largely automatic and whose
neural underpinnings are significantly overlapping. Due to this pressure, we propose that effi-
cient practice in two or more languages has the side effect of increasing the ability of the basal
ganglia to exert control over established cortico-cortical connections, resulting in the ability to
flexibly reroute signals to the frontal cortex. Note that we chose the word “override,” instead of
“inhibit,” to characterize this process. This choice reflects the fact that, at the neural level,
“inhibition” refers to the active reduction of a particular signal’s strength. The basal ganglia-
based mechanism outlined here does not perform “inhibition” in this sense, and relies instead
on the timely strengthening of otherwise weaker signals to modify the way information is trans-
ferred between different regions of the brain.
In summary, the conditional routing framework predicts that bilingual practice capitalizes on
two key functions of the basal ganglia—the capacity of selecting the appropriate rules in response
to very specific conditions and the capacity of overriding habitual responses encoded within cor-
tico-cortical connections. These functions are also important in tasks that demand executive func-
tions, such as those that rely on maintaining a top-down goal in the face of distracting information
(e.g., the Stroop Task) and those that rely on “shifting” from one determined set of responses to
another.
Empirical support
In the previous sections, we have outlined a framework for understanding the mechanisms by
which bilingual language practice provides an advantage in executive function. The framework
assumes that this advantage is mediated by the basal ganglia and, in particular, that it results from
the strengthening of the ability of the basal ganglia to prioritize information flow to the prefrontal
cortex, and override cortico-cortical connections. This framework allows for the generation of
several predictions, some of which are supported in existing data from other researchers, and oth-
ers that we are currently investigating.
Perhaps the most interesting prediction concerns situations where the model predicts a dis-
advantage for bilinguals. By predicting that the bilinguals’ advantage occurs in terms of a
strengthening of the influx of basal ganglia at the disadvantage of cortico-cortical projections,
our framework implicitly lays out conditions where bilingual performance should be inferior to
monolinguals. One can conceive of the difference between striato-cortical and cortico-cortical
connections as a difference between endogenous and exogenous control (Monsell, 2003) or,
alternatively, as a difference between top-down and bottom-up attentional processes. The
research described in the first section of the paper provides extensive evidence that bilinguals
are better at exerting top-down control, but are they really worse at capitalizing on bottom-up
processes? There is some evidence that this is, indeed, the case. For instance, as seen above,
Colzato et al. (2008) reported that bilinguals exhibit inferior performance in the attentional
blink task. Successful performance in this task depends on capturing perceptual information
flowing in at a fast pace, and missing the second target (during the “blink”) might be caused by
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interference from top-down processes that are still processing the first stimulus. That is, notic-
ing the second target requires suspending, or blocking, the top-down processing that has been
initiated on the first target (see Taatgen et al., 2007, for a model of this task that is consistent
with this interpretation).
This top-down processing bias is also apparent in the second experiment by Colzato et al.
(2008), where the authors compared monolinguals and bilinguals in an inhibition-of-return para-
digm. In this paradigm, participants have to attend a stimulus appearing at a particular location. A
cue appearing at the same location before the stimulus has the effect of increasing the response
reaction time at short Stimulus Onset Asynchronies (SOAs); this fact is usually explained in terms
of an automatic inhibition of the previously attended location. The authors reasoned that, if bilin-
guals’ advantage were due to improved inhibitory control, the effect of inhibition of return should
be larger in bilinguals, but the prediction was not confirmed. According to our framework, bilin-
guals’ top-down bias should have the effect of speeding up the response times overall (because of
the facilitation in setting up the appropriate response set) and actually reducing the effect of the
cue (because of the better capacity of ignoring bottom-up information). Colzato’s data (see Figure
4, p. 307) suggests that this is, indeed, the case.
Another example of increased top-down control in bilinguals comes from Experiments 2 and
3 in Bialystok et al.’s (2004) paper. In this paper, the authors compared bilinguals and monolin-
guals in variants of the Simon task. Remember that in the Simon task participants have to respond
to the color of the stimulus (e.g., red or green) with the appropriate hand, and ignore its location
(left or right). Across different conditions bilinguals showed smaller Simon effects (i.e., smaller
costs for responding with the hand to the opposite side of the stimulus), which can be explained
as evidence for either better inhibition or for better capacity for ignoring irrelevant perceptual
information. In Experiments 2 and 3, however, the authors modified the Simon task by doubling
the number of colors of the stimuli. In this condition, the stimuli could have four possible colors
(e.g., red, green, yellow, and blue); participants had to respond with the left hand for two out of
four possible colors (e.g., red and yellow), and with the right hand for the other two (e.g., green
and blue). Thus, instead of selecting between two alternative rules (“if green then press left” and
“if red then press right”), participants have to manage four possible rules, some of which entail
the same response (e.g., “if red then press right” and “if yellow then press right”). In this modi-
fied paradigm, bilinguals showed virtually no increased cost for the additional number of rules,
while monolinguals were significantly slower than in the traditional, two-rule version. Our
framework can easily account for these findings as a result of the bilinguals’ better capacity for
rapidly selecting the relevant task rules. An alternative explanation is that bilingual participants
had better working memory capacity. The bilingual and monolingual groups, however, were
equated for working memory span across two working memory tasks (the alpha span and the
sequencing span tasks), thus making our account preferable.
In summary, our framework is consistent not only with the data that show a superiority of bilin-
guals in switching tasks and managing interference, but also with a number of previously puzzling
findings from experiments that used tasks that were designed to examine different components of
executive function, such as attentional blink and inhibition of return.
Discussion
This paper provides a comprehensive explanation of the nature of the cognitive advantage that
bilinguals exhibit in tasks that require executive function. The proposed theory is that the
advantage resides in an increased ability of the signals originating in the striatum to influence
the activity of the prefrontal cortex, thus reducing the more automated contributions of other
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cortical areas. This theory is based on two types of evidence: (a) Evidence that the basal ganglia
circuit, and in particular the striatum, is responsible for language selection in bilinguals; and (b)
evidence that the same region plays a crucial role in the very same type of tasks where bilin-
guals outperform monolinguals. In support of this theory, we have described a computational
model of how the basal ganglia control and route signals to prefrontal cortex, and propose that
extensive language-switching practice in bilinguals strengthens the ability of this system to
reroute, or override, cortico-cortical connections, resulting in the empirically observed cogni-
tive advantages in bilinguals.
Understanding the costs of bilingualism
Our proposed framework can be tested and extended in a number of ways.
For instance, it can be used to predict not only those cases in which bilinguals exhibit superior
performance over monolinguals, but also the situations in which bilinguals are at a disadvantage
over monolinguals. This has been demonstrated in a number of linguistic tasks, such as those meas-
uring lexical retrieval and verbal fluency (see Bialystok & Feng, 2009, for an example). Our frame-
work can explain these findings in terms of practice effects; because they speak two languages,
bilinguals cannot reach the level of performance within one language that can be reached by mono-
linguals. In addition, at the retrieval level, bilinguals have more interference than monolinguals,
with multiple lexical representations sharing an underlying semantic structure.
Crucially, however, our framework predicts conditions where monolinguals should outperform
bilinguals in non-linguistic tasks. In particular, we expect that their bias in favor of top-down process-
ing over bottom-up processing would make bilingual individuals less reactive to sudden contextual
or perceptual changes that require immediate changes of behavior. Imagine, for instance, an everyday
multitasking condition, such as driving and talking to a cell phone. Our framework predicts that bilin-
guals would be better at performing both tasks concurrently (as indexed, for instance, by measures of
lane deviation in the driving task and memory for conversation in the cell phone task), but less reac-
tive to sudden changes in the outside world (for instance, slower at responding to a pedestrian sud-
denly stepping into the street ahead of them). We see this as an interesting avenue for future research.
Implications for neuroimaging research
The conditional routing framework can also be used to generate testable predictions at the neural
level. In particular, it highlights the importance of the striatum as the source of differential abilities
to bilinguals. The framework predicts, therefore, that activity of the basal ganglia should exert
increased control over the prefrontal cortex in bilinguals. Such differences can be tested using
Dynamic Causal Modeling (Friston, Harrison, & Penny, 2003), a methodology that permits com-
paring the strength of the causal effect exerted by one region on another. It is also conceivable that
bilingual practice would result in a measurable increase in the functional connectivity between the
striatal nuclei and other language centers (such as Broca’s area) or non-linguistic cognitive areas,
such as the dorsal prefrontal cortex. A preliminary analysis of this hypothesis has been attempted
by Luk, Bialystok, Craik, and Grady (2011) and has yielded positive results, which were also con-
firmed by more direct measures of structural connectivity, including Diffusor Tensor Imaging.
The case of multilingualism
This paper has primarily discussed how managing two languages produces long-lasting
changes in behavior and brain circuitry when compared to managing one language. But what
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Stocco et al. 19
can the model say of multilingual individuals (i.e., individuals who speak more than two lan-
guages)? Our framework makes two qualitative predictions on this topic. The first prediction
is that the behavioral and neural effects of bilingualism should be increased in multilingual-
ism. This prediction arises because the specific operations that “train” the bilingual brain (i.e.,
switching between languages and overriding intrusive signals from the unwanted language)
occur more frequently (and thus are more practiced) in multilinguals than in bilinguals. In
other words, an individual that manages three languages in his/her ordinary life needs to
switch language more often than an individual who uses only two languages. Furthermore,
each linguistic operation of a multilingual needs to override not one, but two or more unwanted
languages. Thus, in multilinguals, the amount of interference at any given point is greater than
in bilinguals. Within the conditional routing model, this implies that the strength of the fronto-
striatal connections needs to be even more enhanced to manage the increasing bottom-up
interference. Thus, successful control of many languages should result in an even stronger
top-down processing bias (behaviorally) and stronger effect of the basal ganglia on prefrontal
activation (neurally).
At the same time, one should not expect these effects to grow linearly with the number of
languages spoken by an individual. While a bilingual individual needs to cope with processing
difficulties and neural-level conflicts that a monolingual never faces, a multilingual individual
can largely use the same brain circuitry that is enhanced in bilingual practice. The specific brain
circuit that resolves language conflict in bilinguals is already in place for multilinguals, and
while it might need to be “tuned up” to deal with additional interference, it does not require the
same amount of reorganization that is necessary to move from speaking one language to speak-
ing two languages. In summary, our model predicts that the behavioral and neural consequences
of bilingualism (both positive and negative) should be magnified in multilingualism, but that
these effects should follow a law of diminishing returns, with the mastering of each additional
language yielding increasingly reduced benefits. This is a testable prediction, which we are
currently investigating.
Bilingualism as brain training
Finally, our framework allows for the application of what we have learned from bilinguals to
other domains. Specifically, we can adapt bilingual practice as a means to improve cognitive
performance or rehabilitate cognitive decline. It is possible that extensive training in task
switching produces general cognitive benefits. A great deal has been written about brain train-
ing; typically, the results are very domain specific with limited generalization to other domains.
As an extreme example, with 230 hours of practice Ericsson, Chase, and Faloon (1980) were
able to increase one’s subject digit span from 7 to 79 items; in other memory tests, however, the
same participant’s performance improved only modestly. Bilingualism is one of the very few
practices that results in general cognitive benefits that have been assessed and replicated.
Interestingly, one of the few “brain training” experiments that elicited general cognitive
improvements (Jaeggi, Buschkuehl, Jonides, & Perrig, 2008) involved a training regimen that
required participants to perform two N-back tasks at the same time, with visually presented and
aurally presented stimuli. This training task presents the same characteristics of bilingual prac-
tice, including internal control of switching between similar tasks, top-down resistance to inter-
ference, and dual tasking. Ultimately, an improved understanding of the mechanisms underlying
bilingual brain training could lead to widespread applications for improvement in general cog-
nitive functions.
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20 International Journal of Bilingualism 0(0)
Funding
This research received no specific grant from any funding agency in the public, commercial, or not-for-profit
sectors.
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Author biographies
Andrea Stocco is a Research Assistant Professor in the Department of Psychology and at the Institute for
Learning and Brain Sciences at the University of Washington. His research uses the combination of func-
tional neuroimaging and computational models to investigate the nature of higher-level cognitive processes.
He is particularly interested in the role of the basal ganglia in cognitive flexibility.
Briana Yamasaki is a first-year graduate student in the Department of Psychology at the University of
Washington. In collaboration with Drs Prat and Stocco, her research investigates the nature of improved
executive functions in individuals who develop bilingually.
Rodion Natalenko is an honors student in the Department of Psychology at the University of Washington,
working at the Cognition and Cortical Dynamics Laboratory in collaboration with Drs Prat and Stocco. His
research interests include individual differences in cognitive styles and their implications for information
processing.
at Universitaetsbibliothek Potsdam on August 28, 2012ijb.sagepub.comDownloaded from
26 International Journal of Bilingualism 0(0)
Chantel S Prat is an Assistant Professor in the Department of Psychology and at the Institute for Learning
and Brain Sciences at the University of Washington. Her research uses multiple methodologies to explore the
biological basis of individual differences in cognitive abilities, with an emphasis on language comprehension.
Recently, in collaboration with Dr Stocco, she has begun a series of investigations of the biological basis of
improved executive functioning in bilinguals.
at Universitaetsbibliothek Potsdam on August 28, 2012ijb.sagepub.comDownloaded from
... In the current study, the critical question we sought to answer was the following: does typological similarity between the two languages significantly modulate inhibitory control performance in multilinguals? A relevant theoretical framework for this particular question is the Conditional Routing Model (CRM) by Stocco, Yamasaki, Natalenko, and Prat (2014). The model is based upon the notion that the multilingual experience dynamically impacts domain-general executive functions, including inhibitory control, as a result of the parallel activation of the languages (Bialystok & Martin, 2004;Festman et al., 2010). ...
... Behaviourally speaking, this would be reflected in higher accuracy and shorter RTs for congruent trials compared to incongruent trials. Next, in line with the CRM (Stocco et al., 2014) we hypothesised overall shorter RTs for the Italian-Spanish group compared to the Dutch-Spanish group. Finally, we expected a difference in inhibitory control performance as a function of typological similarity: we expected an interaction effect of condition (congruent vs. incongruent) and typological similarity (typologically similar vs. typologically dissimilar) on Stroop effect sizes. ...
... A smaller Stroop effect for the Italian-Spanish group would imply that the overall inhibitory control performance is better for the typologically similar languages compared to the less typologically similar Dutch-Spanish group. In turn, this would support the CRM (Stocco et al., 2014). ...
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Both inhibitory control and typological similarity between two languages feature frequently in current research on multilingual cognitive processing mechanisms. Yet, the modulatory effect of speaking two typologically highly similar languages on inhibitory control performance remains largely unexplored. However, this is a critical issue because it speaks directly to the organisation of the multilingual's cognitive architecture. In this study, we examined the influence of typological similarity on inhibitory control performance via a spatial Stroop paradigm in native Italian and native Dutch late learners of Spanish. Contrary to our hypothesis, we did not find evidence for a differential Stroop effect size for the typologically similar group (Italian–Spanish) compared to the typologically dissimilar group (Dutch–Spanish). Our results therefore suggest a limited influence of typological similarity on inhibitory control performance. The study has critical implications for characterising inhibitory control processes in multilinguals.
... /fnhum. . not always replicated (see Lehtonen et al., 2018), studies have shown that, at least under certain conditions, the brain adapts structurally, functionally and chemically to bilingual experience (e.g., Stocco et al., 2014;Abutalebi and Green, 2016;Weekes et al., 2018;DeLuca et al., 2019a;Pliatsikas, 2019;Grundy, 2020;Pliatsikas et al., 2021). And yet, the study of bilingualism and neurocognition has primarily focused on monolingual vs. bilingual (dichotomous) group comparisons across a variety of domains and tasks (see Salig et al., 2021 for review). ...
... Acknowledging and dealing empirically with the above reality has manifold consequences. Indeed, several recent models make distinct predictions regarding specific effects for duration and extent of engagement with bilingual experience (Stocco et al., 2014;Abutalebi and Green, 2016;Grundy et al., 2017;DeLuca et al., 2020;Pliatsikas, 2020). In this light, it seems reasonable to ponder the extent to which some of the discrepancies within the empirical record might be better explained in relation to the (non-)comparability of how important individual-level variables are distributed across participants (Leivada et al., 2021). ...
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... Contemporary research treating bilingualism as a complex spectrum of experiences has shown that certain levels of activity and engagement with bilingualism are linked with increased probabilities for measurable knockon effects (e.g., Kuhl et al., 2016;Gullifer et al., 2018;DeLuca et al., 2019b;Luo et al., 2019;Gallo et al., 2021). It seems that bilingualism par excellence, as aforementioned, is not a sufficient qualifier, but rather active engagement with bilingual experiences provides increased opportunity for mental conflict and resolution FIGURE 1 | Overview of selected models of bilingualism and neural adaptations based on various aspects of bilingual experience (Green and Abutalebi, 2013;Stocco et al., 2014;Grundy et al., 2017;Pliatsikas, 2020). Overlap in key brain areas/structures implicated in bilingualism depicted in the summary panel on the right. ...
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As a result of advances in healthcare, the worldwide average life expectancy is steadily increasing. However, this positive trend has societal and individual costs, not least because greater life expectancy is linked to higher incidence of age-related diseases, such as dementia. Over the past few decades, research has isolated various protective “healthy lifestyle” factors argued to contribute positively to cognitive aging, e.g., healthy diet, physical exercise and occupational attainment. The present article critically reviews neuroscientific evidence for another such factor, i.e., speaking multiple languages. Moreover, with multiple societal stakeholders in mind, we contextualize and stress the importance of the research program that seeks to uncover and understand potential connections between bilingual language experience and cognitive aging trajectories, inclusive of the socio-economic impact it can have. If on the right track, this is an important line of research because bilingualism has the potential to cross-over socio-economic divides to a degree other healthy lifestyle factors currently do not and likely cannot.
... Indeed, a number of authors who have developed influential cortico-centric models of language have also conducted seminal studies of subcortical language function, e.g., Angela Friederici (Jeon et al., 2014;Kotz et al., 2002Kotz et al., , 2003Mestres-Misse et al., 2012;Wahl et al., 2008) and Peter Hagoort (Snijders et al., 2010). While the notion that subcortical structures contribute to language remains, in our view, a minority position, there are nevertheless a range of researchers who appear to be converging on the view that subcortex is recruited for language; for instance, in bilingualism (Bice et al., 2020;Burgaleta et al., 2016;Cargnelutti et al., 2019;Hervais-Adelman et al., 2018, Stocco et al., 2012, phonological processing (Booth et al., 2007), syntax (Lieberman 2006(Lieberman , 2015, reading (Braun et al., 2019;Yeatman & White 2021), word learning (Takashima et al. (2014) and lexical access (Crinion et al., 2013;Hernandez & Li, 2007;Meinzer et al., 2006). Our aim is not to label various models as subcortical-inclusive or subcortical-exclusive, but to evaluate the apparent roles of subcortical structures in higher-order language processing, with particular emphasis on brain dynamics (Hoshi, 2017). ...
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Subcortical contributions to core linguistic computations pertaining to syntax-semantics remain drastically under-studied. We critique the cortico-centric focus which has largely accompanied research into these higher-order linguistic functions and suggest that, while much remains unknown , there is nevertheless a rich body of research concerning the possible roles of subcortex in natural language. Although much current evidence emerges from distinct domains of cognitive neuroscience, in this review article we attempt to show that there is a clear place for subcortex in models of natural language syntax-semantics, including a role in binary set-formation, categorized object maintenance, lexico-semantic processing, conceptual-to-lexical transformations, morphosyntactic linearization, semantic feature-binding, and cross-cortical representational integration. In particular, we consult models of language processing relying on oscillatory brain dynamics in order to investigate both the apparent and possible functional roles of subcortex in language.
... In addition, one could consider a growing SOM mechanism (e.g., Farkas and Li, 2002) to enable more resources for late L2 for the processing of embodied perceptual-spatial-sensorimotor features. Such studies could incorporate important information based on neurocognitive evidence that involves processing in both the neocortical and subcortical brain regions (see Green and Abutalebi, 2013;Stocco et al., 2014;see Grant et al., 2019, for a review). This new direction using the computational modeling approach, in conjunction with behavioral and neurocognitive studies, will lead to significant insights into the mechanisms and principles underlying individual difference in L2 learning and representation. ...
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In this paper, we present a computational approach to bilingual speakers’ non-native (L2) lexical-semantic representations. Specifically, based on detailed analyses of the error patterns shown in our previous simulation results ( Zhao and Li Int. J. Bilingual. Educ. Bilingual., 2010, 13, 505–524 ; Zhao and Li, Bilingualism, 2013, 16, 288–303 ), we aim at revealing the underlying learning factors that may affect the extent of fuzzy category boundaries within bilinguals’ L2 representation. Here, we first review computational bilingual models in the literature that have focused on simulating L2 lexical representations, including the Developmental Lexicon II (DevLex-II) model ( Zhao and Li, Int. J. Bilingual. Educ. Bilingual., 2010, 13, 505–524 ; Zhao and Li, Bilingualism, 2013, 16, 288–303 ), on which the current study is based. The DevLex-II modeling results indicate a strong age of acquisition (AoA) effect: When the learning of L2 is early relative to that of native language (L1), functionally distinct lexical representations may be established for both languages; when the learning of L2 is significantly delayed relative to that of L1, fuzzy L2 representations may occur due to the structural consolidation (or the entrenchment ) of the L1 lexicon. Next, we explore the error patterns shown in both lexical comprehension and production in DevLex-II. A novel contribution of the current study is that we systematically compare the computational simulation results with empirical findings. Such model-based error analyses extend our previous findings by indicating, especially in the late L2 learning condition, that fuzzy L2 semantic representations emerge and lead to processing errors, including errors in unstable phonology-semantic and semantic-phonemic mappings. The DevLex-II model provides a computational account of the development of bilinguals’ L2 representation with reference to the dynamic interaction and competition between the two lexicons. We point to future directions in which fuzzy L2 representations may be overcome, through a framework that highlights the social learning of L2 (SL2) and the embodied semantic representation of the lexicon in the new language ( Li and Jeong, Npj Sci. Learn., 2020, 5, 1–9 ; Zhang, Yang, Wang and Li, Lang. Cogn. Neurosci., 2020, 35, 1223–1238 ).
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The goal of computational cognitive neuroscience is to understand how the brain embodies the mind by using biologically based computational models comprising networks of neuronlike units. This text, based on a course taught by Randall O'Reilly and Yuko Munakata over the past several years, provides an in-depth introduction to the main ideas in the field. The neural units in the simulations use equations based directly on the ion channels that govern the behavior of real neurons, and the neural networks incorporate anatomical and physiological properties of the neocortex. Thus the text provides the student with knowledge of the basic biology of the brain as well as the computational skills needed to simulate large-scale cognitive phenomena.The text consists of two parts. The first part covers basic neural computation mechanisms: individual neurons, neural networks, and learning mechanisms. The second part covers large-scale brain area organization and cognitive phenomena: perception and attention, memory, language, and higher-level cognition. The second part is relatively self-contained and can be used separately for mechanistically oriented cognitive neuroscience courses. Integrated throughout the text are more than forty different simulation models, many of them full-scale research-grade models, with friendly interfaces and accompanying exercises. The simulation software (PDP++, available for all major platforms) and simulations can be downloaded free of charge from the Web. Exercise solutions are available, and the text includes full information on the software.