REVIEW ARTICLE
Moving From Bilingual Traits to States:
Understanding Cognition and Language
Processing Through Moment-to-Moment Variation
Lauren K. Salig1
, Jorge R. Valdés Kroff2
, L. Robert Slevc1,3
, and Jared M. Novick1,4
1Program in Neuroscience and Cognitive Science, University of Maryland, College Park, USA
2Department of Spanish and Portuguese Studies, University of Florida, Gainesville, USA
3Department of Psychology, University of Maryland, College Park, USA
4Department of Hearing and Speech Sciences, University of Maryland, College Park, USA
Keywords: bilingualism, executive function, language processing, individual differences, cognitive
control
ABSTRACT
The study of how bilingualism is linked to cognitive processing, including executive
functioning, has historically focused on comparing bilinguals to monolinguals across a range
of tasks. These group comparisons presume to capture relatively stable cognitive traits and
have revealed important insights about the architecture of the language processing system that
could not have been gleaned from studying monolinguals alone. However, there are
drawbacks to using a group-comparison, or Traits, approach. In this theoretical review, we
outline some limitations of treating executive functions as stable traits and of treating bilinguals
as a uniform group when compared to monolinguals. To build on what we have learned from
group comparisons, we advocate for an emerging complementary approach to the question of
cognition and bilingualism. Using an approach that compares bilinguals to themselves under
different linguistic or cognitive contexts allows researchers to ask questions about how
language and cognitive processes interact based on dynamically fluctuating cognitive and
neural states. A States approach, which has already been used by bilingualism researchers,
allows for cause-and-effect hypotheses and shifts our focus from questions of group differences
to questions of how varied linguistic environments influence cognitive operations in the
moment and how fluctuations in cognitive engagement impact language processing.
INTRODUCTION
Psycholinguistics research is concerned with developing comprehensive behavioral and neuro-
biological models of how humans process language at multiple levels of representation. An
important aspect of this agenda has been to study how nonlinguistic cognitive systems—such
as memory, executive function, and attention—interact with language use. Scientific investiga-
tion into such relationships is an attempt to specify how a broader mental architecture may
support linguistic procedures, or to reveal what traces variable linguistic experiences may leave
on cognitive processing. A conventional approach to this sort of issue is to examine correlated
variation in performance in large-scale individual differences studies (e.g., a person with ability
X also has ability Y), or to draw comparisons across groups that differ in either ability (as in
a n o p e n a c c e s s
j o u r n a l
Citation: Salig, L. K., Valdés Kroff, J. R.,
Slevc, L. R., & Novick, J. M. (2021).
Moving from bilingual traits to states:
Understanding cognition and language
processing through moment-to-
moment variation. Neurobiology of
Language, 2(4), 487–512. https://doi.org
/10.1162/nol_a_00046
DOI:
https://doi.org/10.1162/nol_a_00046
Received: 29 December 2020
Accepted: 16 June 2021
Competing Interests: The authors have
declared that no competing interests
exist.
Corresponding Author:
Lauren K. Salig
lsalig@umd.edu
Handling Editor:
Anthony Steven Dick
Copyright: © 2021
Massachusetts Institute of Technology
Published under a Creative Commons
Attribution 4.0 International
(CC BY 4.0) license
The MIT Press
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Moving from bilingual traits to states
Traits:
Attributes of a person that guide
behavior and remain relatively stable
across time and situations (Steyer
et al., 2015).
States:
Attributes of a person-in-a-situation
that fluctuate and involve situation-
driven variability (Steyer et al., 2015).
neuropsychological patients vs. healthy controls) or experience (as in bilinguals vs. mono-
linguals). The logic behind such methods is that observable associations provide insight into
common processes that are shared by the demands of both linguistic and nonlinguistic tasks,
which permits inferences about stable relationships among language and cognitive abilities
that may be modulated by aggregate experiential contrasts. For example, if bilinguals differ
from monolinguals on a particular task of executive function, then the underlying cognitive
and neural processes used to complete that task must also be recruited by each population
to a different extent while processing language over the course of a lifetime.
In this article, we advocate for a related but distinct approach to these issues, which aims to
understand how individuals compare with themselves, rather than to other groups, under dif-
ferent information-processing conditions. Akin to traditional group comparisons, the goal is to
uncover the functional interplay between language and cognitive systems. But unlike the
broadscale group approach, the goal is not to identify cumulative trait differences, but rather
to isolate more localized, situational effects such as how linguistic contexts influence cognitive
processing and/or (inversely) how manipulations of cognitive engagement influence language
processing in the moment. An approach that tests the effects of variable states can offer more
than correlational data and may allow inferences about when and how language and cogni-
tive processes interact in real time in a causal manner. We believe that such work can provide
new insights into the configuration of the bilingual mind and brain that builds on prior
research.
We begin by summarizing some findings from past group-comparison research regarding
the effects of bilingualism on language and cognition. We then define the Traits and States
approaches before turning to some methodological limitations of approaches that examine
cognitive abilities as relatively fixed traits to be compared across groups. To address these lim-
itations, we describe a complementary approach in which researchers manipulate either the
linguistic context to observe the consequence of these manipulations on cognitive performance
(e.g., Adler et al., 2020; Wu & Thierry, 2013) or an individual’s cognitive state to observe its
influence on language processing (e.g., Navarro-Torres et al., 2019). By employing a States
approach, language scientists can ask questions about how the dynamics of language process-
ing impact other cognitive abilities (and vice versa) on a moment-to-moment basis.
Brief Summary of Findings From Bilingualism Research on Cognitive Functions and
Language Processing
A perennial question in the study of bilingualism is how bilinguals represent their two lan-
guages in one mind. Is there a “switch” that completely deactivates one language when it is
not currently in use (Costa et al., 1999)? Or are the two linguistic systems interconnected, the
effects of which can be observed even in monolingual environments? Findings from bilingual
comprehension studies routinely show that words from both languages are simultaneously
activated even in single-language contexts, including when a bilingual’s two languages use
different scripts or modalities (Hoshino & Kroll, 2008; Marian & Spivey, 2003; Morford et al.,
2011; Slevc et al., 2016; Spivey & Marian, 1999; Thierry & Wu, 2007). That is, as spoken
words unfold in time, bilinguals do not limit retrieval to the language currently in use, as lex-
ical items from the currently unused language partially compete for selection. These results
suggest that there is no clear separation between a bilingual’s two languages; rather, there can
be “cross talk” between linguistic representations (e.g., phonological, semantic) for both pro-
duction and comprehension except in the presence of strong contextual cues (e.g., Chambers
& Cooke, 2009; Schwartz & Kroll, 2006).
Neurobiology of Language
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Moving from bilingual traits to states
While bilinguals’ two linguistic systems are not closed off from each other in terms of archi-
tecture, they manage to separate their languages in use, rarely failing to use the intended,
context-appropriate language. To select the desired word in a particular language, bilinguals
presumably must resolve the competition that arises from co-activated representations in both
languages. Studies suggest that the unintended language is inhibited when not in use. The more
dominant that language is, the more it must be suppressed, resulting in asymmetric switch costs
(e.g., Meuter & Allport, 1999, but see Blanco-Elorrieta & Caramazza, 2021, and Declerck &
Philipp, 2015, for criticisms of this point). For instance, after using the second language (L2), a
bilingual’s first language (L1) is temporarily inhibited and harder to reactivate (e.g., Costa &
Santesteban, 2004). This is also illustrated by L2-immersed learners demonstrating increased
difficulty producing words in the L1 (Botezatu et al., 2020; Linck et al., 2009). The impact of
managing two or more languages may also extend beyond the lexical level, as syntactic parsing
strategies in one language can come to impact parsing in another (Dussias & Cramer Scaltz,
2008; Dussias & Sagarra, 2007). For example, Spanish speakers with extensive immersion
experience in English as an L2 may begin to parse Spanish sentences with relative-clause attach-
ment ambiguities more like an English speaker; that is, they deploy low-attachment parsing pref-
erences more often than their Spanish monolingual peers or Spanish-immersed bilingual peers.
Together, this research demonstrates consistent cross-linguistic influences across a bilingual’s
languages over multiple timescales.
In the past three decades, language scientists have asked questions about whether the un-
ique language processing demands associated with bilingualism have cognitive conse-
quences. Namely, they have investigated whether a lifetime of navigating cross-linguistic
competition affects aspects of bilinguals’ cognitive processing, including constituents of exec-
utive functions: most notably, their ability to resolve competition in nonlinguistic domains.
Executive function refers to the family of cognitive mechanisms that manage information pro-
cessing in the brain and flexibly support goal-directed behavior. Some research suggests that
bilinguals may have an advantage over monolinguals on conflict detection/resolution tasks
(e.g., Flanker, Stroop, and Simon tasks) that test cognitive control, a sub-component of exec-
utive function that allows individuals to adjudicate among competing representations by pro-
moting task-relevant over -irrelevant information (Abutalebi et al., 2015; Bialystok et al., 2004,
2008; Costa et al., 2009). Neuroimaging findings have implicated neural networks associated
with cognitive control—such as the anterior cingulate within medial prefrontal cortex, and
subcortical structures such as the caudate and putamen—in bilingual language processing,
including relatively greater recruitment in bilinguals as compared to monolinguals
(Abutalebi et al., 2015; Luk et al., 2012; Parker Jones et al., 2012; Teubner-Rhodes et al.,
2019). Furthermore, bilinguals show less frontal activation than monolinguals for the same
performance level on nonverbal cognitive-control tasks, and greater modulation of functional
connectivity within frontoparietal networks based on executive-processing demands (see
Grundy et al., 2017, for a review). The inference from these findings is that bilinguals are able
to deal with conflict during information processing more efficiently, perhaps due to greater re-
liance on other networks, including the language network. Moreover, the finding that bilinguals
tend to experience a later onset of dementia symptoms than monolinguals (see Mendez, 2019,
for a review) has been ascribed to their neural shift away from relying on frontal regions for
executive-function demanding tasks, resulting in greater cognitive reserve (Grundy et al.,
2017; Mendez, 2019). These results from the Traits approach have improved our understanding
of the effects of bilingualism on brain function and its impact on cognitive processing. Overall,
however, findings about bilingual advantages in executive functions have been contentious and
disparate, with effects emerging in some tasks and contexts but not others (e.g., Bialystok et al.,
Executive function:
The family of cognitive mechanisms
that manage information processing
in the brain and support the flexible
guidance of goal-directed behavior.
Cognitive control:
An important sub-component of
executive function that specifically
detects and resolves conflict during
information processing.
Conflict:
Situations where task demands
require adjudicating among
incompatible ways of interpreting a
stimulus during information
processing (e.g., when the task
requires suppressing a
dominant/prepotent way of
characterizing a stimulus).
Neurobiology of Language
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Moving from bilingual traits to states
2009; de Bruin et al., 2015; Hilchey & Klein, 2011; Lehtonen et al., 2018; Paap & Greenberg,
2013; Valian, 2015; Ware et al., 2020).
Mixed findings aside, separating people into monolinguals and bilinguals for group com-
parisons can address only a subset of questions about the relationship between cognition and
language processing. For example, a Traits approach cannot explain why and when bilinguals
may need to engage cognitive control for language processing in the first place, considering
the diverse experiences of bilinguals and the range of in-the-moment demands they face.
Much of the variation in linguistic experience that makes bilingualism a good test case for
questions about language processing is lost when we collapse all bilinguals together into
one group. While all bilinguals deal with routine cross-language competition, their processing
demands will vary based on their stage of bilingualism (e.g., if they are still acquiring the sec-
ond language), the specific languages they know, their daily language environment, and the
immediate context. For instance, a bilingual who uses one language exclusively at work and
the other at home will have different daily processing demands than a bilingual who uses both
languages throughout their day, freely code-switching between them in any interactional con-
text (Beatty-Martínez et al., 2020; Green & Abutalebi, 2013). Furthermore, each of these bilin-
guals will have different processing demands from moment to moment, such as when talking to
a monolingual versus to another bilingual who shares their languages. These factors—switching
experience, proficiency, exposure, etc.—are exactly the sort of bilingual variation that is pro-
posed to result in different neural and cognitive outcomes (traits) and is likely changed by bi-
lingual experiences in a dynamic rather than a linear manner (DeLuca et al., 2020; Hernandez
et al., 2018; Pliatsikas, 2020). While such variation may be considered a nuisance in group
comparisons, bilingual variation can guide the questions we ask about language processing
in the future if we are willing to take a complementary approach to bilingualism research that
overcomes some limitations of the above-described group comparison, or Traits, approach.
DEFINING THE TRAITS AND STATES APPROACHES
Although the Traits vs. States distinction has only recently begun to be explicitly applied to the
development of neurobiological and cognitive models of bilingualism (e.g., Blanco-Elorrieta &
Pylkkänen, 2017), the distinction has a longer history in other disciplines. For example, when
a clinician takes a measure of an individual’s anxiety, the aim is to measure something about
the person and their propensity to be anxious—that is, they hope to measure that person’s
anxiety trait. However, two people with the same baseline anxiety trait could receive different
anxiety scores depending on how their day was going prior to testing or how they react to the
assessment situation. For decades, the field of clinical psychology has discussed how to extract
stable trait measures from instruments that capture some amalgamation of stable traits, situa-
tional impacts, trait-situation interactions, and measurement effects or errors (Kendall, 1978;
Steyer et al., 1999, 2015; cf. Allen & Potkay, 1981).
In this article, we consider states to be inherently informative, rather than a nuisance variable
to be subtracted out of trait measures. We will use the working definitions of states and traits
provided by the clinical field to distinguish between them in the study of bilingualism. A trait
can be considered an “attribute of a person” that guides their behavior while remaining relatively
stable across time and situations. On the other hand, a state can be considered an “attribute of a
person-in-a-situation” with fluctuations that are “typically reversible and represent systematic but
situation-driven variability,” which interacts with baseline traits (Steyer et al., 2015, pp. 72–73).
For our purposes, we consider the Traits approach to be the study of how a lifetime of spe-
cific language experience alters an individual’s baseline cognitive abilities or associated,
Neurobiology of Language
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Moving from bilingual traits to states
supporting brain structures. When a study measures different conditions of an executive-
function task, it usually takes a Traits approach. For example, a study may measure bilinguals’
performance on a Stroop task including congruent trials that require relatively less cognitive
control (e.g., saying “red” to the word red in red ink) and incongruent trials that demand more
cognitive control to resolve conflict (e.g., saying “green” to the word red in green ink). If aver-
aged performance on these two different conditions is used to compile an individual’s singular
cognitive control “score” or ability, then this is a trait measure. Studies that compare two
groups’ scores aim to test for trait differences.
By contrast, we describe the States approach as studying how an individual’s performance
fluctuates depending on the given situation. While the range of an individual’s behavioral or
neural responses may be limited by their traits, the States approach aims to determine what
conditions result in fluctuation within that range. This can be achieved using the same exper-
imental task as studies of traits but designed with modifications to allow for different infer-
ences. For example, a study may ask participants to complete the same Stroop or Flanker
task with congruent and incongruent trials in two different linguistic contexts to determine
how those contexts affect cognitive-control performance (e.g., higher accuracy and reduced
P300 amplitude when ignoring irrelevant words in a mixed- compared to a single-language
context; Wu & Thierry, 2013). The opposite direction can also apply: Researchers can use
different conditions of the Stroop or Flanker task to manipulate states of cognitive-control en-
gagement in real time and observe their immediate effect on language processing. This type
of design alters states to vary the status of moment-to-moment behavioral or neural processes
rather than using tasks as psychometric tests that attempt to measure stable traits. Studies that
investigate how cognitive or language processing differs within the same individual under dif-
ferent circumstances use a States approach. We propose that modulations in states are as impor-
tant to understanding the effects of bilingualism on cognitive processing, including executive
function, as individual differences in traits.
While a clearly defined difference between Traits and States approaches in bilingualism has
not previously been detailed, many others have raised the same limitations of the Traits ap-
proach that we will discuss and have called for research practices that we support (e.g., de
Bruin, 2019; Grundy, 2020; Luk & Bialystok, 2013; Whitford & Luk, 2019). One goal of this
article is to contribute to this ongoing discussion by clarifying the distinction between States
and Traits approaches and the questions about bilingualism that each can address. Some have
expressed concern about exploring the relationship between bilingualism and executive func-
tions without clear theories (de Bruin et al., 2021). We agree, and thus offer here a theory for
how a States approach can result in a clearer understanding of the shared processing demands
across linguistic and nonlinguistic behavior.
LIMITATIONS OF THE TRAITS APPROACH
Research on bilingualism and executive functions has often measured individuals’ perfor-
mance on a task at one point in time and compared the performance of all bilingual partici-
pants to that of all monolingual participants in a sample. This Traits approach led to major
advances in our understanding of bilinguals’ efficient reliance on executive functions in bilin-
gual language control, as sketched above. However, a Traits approach necessarily collapses
across diversity in language experience within groups and provides only a static illustration of
performance in the research lab, thus failing to address the fact that an individual’s cognitive
states can also fluctuate and be impacted by context. Given these considerations, we would
not want to characterize everyone who has a lapse in performance under laboratory
Neurobiology of Language
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Moving from bilingual traits to states
Attention control:
Another sub-component of executive
function that regulates collection of
information from the environment.
conditions to be “low” in the tested cognitive ability. In this section, we will address these
limitations in more detail and discuss how individual differences approaches may not be
well-suited for many of the emerging questions surrounding bilingualism and executive
function.
Cognitive and Neural States Fluctuate Within Individuals
The traits approach captures only a snapshot of performance
Defining anyone as having either good or bad executive function is likely a gross oversimpli-
fication of how people differ in this way, and adhering to such a strict dichotomy can lead to
conceptual and empirical mistakes. A person’s cognitive engagement status naturally fluctuates
over the course of a day (Lara et al., 2014) or even throughout a short-term activity such as those
used in laboratory tasks. For instance, mind-wandering studies have demonstrated that individ-
uals experience temporary attentional lapses frequently during language comprehension, with
some studies reporting that participants had fully on-task attention only about 50–60% of the
time (Boudewyn & Carter, 2018a; Smallwood et al., 2008a; Uzzaman & Joordens, 2011). Such
attentional fluctuations can influence how much information an individual has collected and
retained during their in-the-moment performance (Boudewyn & Carter, 2018a; Smallwood
et al., 2008b). One study found that lower levels of alpha oscillatory power at various points
during story listening (used as an index of higher attentional engagement) was associated with
fewer mind-wandering endorsements at those points and better recall of that information later
(Boudewyn & Carter, 2018a). Thus, fluctuations within individuals’ state of attention control
(another subcomponent of executive function), which regulates the collection of exogenous
information from the environment, directly impacts language comprehension.
Various factors can affect whether a person is engaged, including motivation, mood, level
of interest in a task, and its degree of difficulty (e.g., Chiew & Braver, 2014). Changes in bilin-
guals’ linguistic environment may be another such factor. This notion, which we spell out in the
Complementary States Approach section, is inspired by mind-wandering studies but also by
findings from studies that manipulate linguistic and cognitive states in monolinguals. Such stud-
ies are motivated, in part, by theoretical accounts that postulate that during language compre-
hension, readers and listeners often encounter conflicting cues to interpretation that can
generate misanalyses and the need to revise, which relies on cognitive control to prevent com-
prehension from running aground (Novick et al., 2005). For example, moment-to-moment var-
iation in the transient state of cognitive control, which detects and resolves conflict during
information processing, impacts the ease with which readers and listeners revise misinterpre-
tations of linguistic input in real time (Hsu & Novick, 2016; Hsu et al., 2021; Thothathiri et al.,
2018). Likewise, how easy or difficult a sentence is to understand—arguably a modulation in
linguistic state—recruits varying levels of cognitive-control procedures dynamically (Kan et al.,
2013). These findings have been interpreted within classic models of cognitive control, in
which the detection of conflict guides processing toward the most informative cues in the input
to maximize performance and decrease errors (Botvinick et al., 2001). Botvinick and col-
leagues’ classic conflict monitoring account of cognitive control (2001) describes a model ex-
clusively in terms of states, not individual traits—focusing on how and when cognitive-control
mechanisms engage to bias information processing toward currently-relevant over -irrelevant
cues in the service of optimizing performance. Such models can explain the findings briefly
summarized here. We advocate for a return to this sort of theorizing, concentrating for example
on how aspects of bilingual language processing vary the engagement status of different cog-
nitive systems (and why).
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Moving from bilingual traits to states
Studies that focus exclusively on whether a person with strong cognitive control (i.e., the
ability to promote task-relevant cues in the service of conflict resolution) performs differently
than a person with weak cognitive control on some other task—a trait contrast—capture only a
snapshot of individuals’ performance in time. Trait-based approaches miss important data
about how natural oscillations in attention or cognitive control impact behavior. Consider,
for instance, traditional comparisons between neuropsychological patients with cognitive-
control deficits and college students, who look starkly different in how they interpret language.
Healthy young adults are better than people with brain damage at revising misinterpretations
of language input, which involves cognitive control (Novick et al., 2005, 2009; Vuong &
Martin, 2011). Yet, other studies show that manipulations of healthy young adults’ cognitive
control—increasing it or decreasing it, either through neurostimulation or behavioral means—
immediately affects their language processing (Hsu & Novick, 2016; Hsu et al., 2021; Hussey
et al., 2015). A healthy person’s sentence interpretation can come closer to resembling that of
a patient with a cognitive-control disorder by temporarily downregulating their relative
cognitive-control engagement. The standard categories therefore do not uniformly apply in
any obviously fixed manner: A college-student participant does not fit tidily into a certain
bin of cognitive-control ability because that ability gets mobilized to a different extent depend-
ing on its state of engagement, with noticeable consequences on linguistic behavior. These
state-based data permit the inference that modulations in cognitive control cause modulations
in language processing. There are two noteworthy points: (1) Such shifting performance patterns
will be missed when classifying people categorically by their cognitive control “score,” and (2)
causal inferences cannot be drawn from individual-to-individual or group-by-group correla-
tions, in which such relationships could be mediated by additional, unmeasured factors.
Linking hypotheses and the logic of the traits approach
Additionally, studies that assess cognitive abilities as traits may be pushing the limits of what
can be reasonably concluded from the tasks used. One issue in this realm is the varied defi-
nitions applied by different researchers to “executive functions.” Hypotheses about how exec-
utive functions play a role in bilingual language processing should clearly articulate which
components of executive function are being measured, with a careful delineation of how such
components are shared across linguistic and nonlinguistic task demands. In other words, it is
insufficient to suggest that “attention control” or “inhibition,” for instance, are required for
tasks X and Y without stepping through a chain of inference—a linking hypothesis—that con-
nects how the necessary procedures for tasks X and Y are recruited as the relevant system
processes a stimulus in real time. Without these specifications, attempts to correlate abilities
across different tasks run the risk of Type II errors: for example, concluding that a certain cog-
nitive process is not involved in some linguistic process (when in fact it is) because the groups
do not differ, or clear patterns of individual differences do not emerge.
Consider the case of conflict trials from the color-word Stroop task (e.g., saying “blue” to the
word red written in blue font) and the arrow Flanker task (e.g., → → ← → →), both of which
are often used as measures of inhibition in some executive-function frameworks. Although
they contribute to a common factor in latent variable analyses, they often fail to correlate
(Friedman & Miyake, 2004; Gärtner & Strobel, 2021; Hedge et al., 2018; Unsworth, 2010),
which could generate possibly unwarranted conclusions about domain-specificity, e.g., infer-
ring that there are separate inhibition mechanisms for verbal and nonverbal tasks. Problems
with interpreting null results aside, there are theoretical issues. For performance to correlate
across tasks, one must assume that the same degree of some executive-function process (here,
inhibition) is similarly required across the two tasks, which is a dubious premise. For instance,
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Moving from bilingual traits to states
the representations one must overcome during Stroop, on account of a lifetime of reading, are
arguably stronger than those in a relatively novel Flanker task. This means that even someone
with a stable inhibition ability will have to apply inhibition to different extents across those two
tasks (more for Stroop, less for Flanker). For the inhibition signal to correlate in magnitude, we
must estimate approximately equal representational strengths, which, in this example, is likely
false (for more discussion, see Nozari & Novick, 2017, and Hsu et al., 2017). Thus, correlational
failures might reflect actually different mechanisms required for the two tasks, an ill-defined
linking hypothesis, and/or a shared process that goes undetected because it need not be
implemented to the same extent and so correlated variation is not observed (and should not
be expected).
As we will discuss further below, there are also theoretical reasons to expect that certain
executive functions will be upregulated more by particular bilingual experiences than others
(Green & Abutalebi, 2013). Even factoring out the nuances of bilingualism, executive func-
tions are not a monolith (Miyake et al., 2000), and spelling out the distinct procedures that
are engaged across different tasks may offer novel insight into the processing demands of cer-
tain linguistic tasks. For example, in studies of monolingual language processing, manipula-
tions of cognitive control shape the ease with which listeners resolve temporarily ambiguous
sentences and recover from misinterpretation, whereas manipulations of attention control do
not (Hsu et al., 2021). Attention control and cognitive control are terms that are frequently
used interchangeably in psycholinguistics research, but in fact they may reflect related but
independent constituents of executive function. Whereas attention control refers to the ability
to orient to, and collect information from, sensory input in the exogenous environment
(Petersen & Posner, 2012; Posner & Petersen, 1990), cognitive control refers to the ability to
characterize (and recharacterize) the input once it has been collected at some endogenous
level of representation (e.g., Botvinick et al., 2001). Indeed, attention control can remain en-
gaged over sustained periods of time, whereas cognitive control appears to operate more tran-
siently, as it is needed. Moreover, there are different neural markers of attention and cognitive
control (e.g., oscillatory power in the alpha and theta bands respectively; see Boudewyn &
Carter, 2018b, and Rommers et al., 2017). Failure to consider such definitional, empirical,
and neurobiological contrasts, alongside failure to articulate clear and consistent linking as-
sumptions, may yield misunderstandings about when and how performance across tasks
should be expected to interact, and also about the independent roles that different sorts of
executive functions might play during language processing.
Moreover, there are important statistical considerations: Tasks such as Flanker and Stroop
that are intended to measure executive functions such as response inhibition are not always
strongly correlated with each other, perhaps indicating that they may be tapping into distinct
abilities (Hedge et al., 2018), although latent variable analysis indicates they are related
(Unsworth, 2010). As argued above, performance may fail to correlate because task-specific
representations may not require inhibition to the same extent (Nozari & Novick, 2017).
Some of these commonly used tasks, furthermore, have been shown to have low test–retest
reliability, in part because of minimal between-participant variance. That is, while these tasks
can be good for manipulating people’s relative state of cognitive engagement (e.g., through
congruent vs. incongruent trials), they may not be stable enough to measure individual differ-
ences—and in fact, the robust effects these tasks elicit are part of what makes them ill-suited to
looking at individual differences (Hedge et al., 2018). This statistical issue can limit group
comparison approaches to executive functions even when taking an individual differences ap-
proach but highlights the strength in using executive-function tasks to measure in-the-moment
variation within (rather than among) individuals (Whitford & Luk, 2019).
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Moving from bilingual traits to states
Language affects cognitive/neural states
The findings discussed here indicate that relying upon the snapshot approach alone tells only
part of the story. Further, they suggest that it is important to consider the factors that affect
relative states of cognitive engagement in the moment, and how such dynamic fluctuations
shape behavior in that same moment. Recent research in bilingualism has adopted such an
approach by examining fluctuations of cognitive engagement under different linguistic con-
texts. Under this States approach, tasks like Flanker are not used as a stable individual differ-
ence measure but instead as a manipulation or measurement of cognitive control on a
moment-by-moment or blocked (contextual) basis, thus circumventing some of the limitations
listed above and leading to interesting findings. For example, emerging data indicate that
bilinguals’ cognitive-control engagement, as measured by Flanker performance, is adjusted
in real time depending on the linguistic context. Contexts that involve language mixing (i.e.,
the presence of both languages within an experimental session) or code-switching modulate
bilinguals’ Flanker performance compared to single-language input, allowing inferences that
such contexts affect the engagement status of cognitive control (Adler et al., 2020; Wu &
Thierry, 2013). The notion of language modes, popularized by Grosjean (1985, 1998, 2001),
means that people shift into different states of language expectancies based on their assump-
tions in any given context. These contexts create different processing demands, which affect
behavior in various ways.
Recent work demonstrates that this shift between language modes can dynamically affect
neural activity in the dorsolateral prefrontal cortex (dlPFC) and anterior cingulate cortex (ACC),
areas implicated in bilingual language control and cognitive control more generally (e.g.,
Braver et al., 2003; Crinion et al., 2006). Blanco-Elorrieta and Pylkkänen (2017) examined
switch costs as measured by reaction time and MEG in production and comprehension within
the same group of Arab-English bilingual participants. The tasks varied from artificial
externally cued language switching paradigms commonly used to examine bilingual language
control to more ecologically supported naturalistic switches, while also varying whether imag-
ined interlocutors were monolingual or bilingual. The greatest switch costs and neural activity
in dlPFC and ACC were observed in the artificial, pragmatically unsupported task and dimin-
ished in the more naturalistic tasks. Considering the different processing demands elicited by a
particular language mode offers information that is distinct from snapshot tests of cognitive
traits, in which we are capturing and averaging a person’s behavior throughout a context or
experimental setting, often without acknowledging what language mode they may be in.
Bilinguals and Monolinguals Are Not Monoliths
Bilinguals experience different interactional contexts
Given that bilinguals may engage different linguistic and cognitive processes dependent on
context, it is also important to consider what language mode(s) bilinguals experience on a
regular basis. Bilingual experiences differ in myriad ways. For example, some bilinguals are
likely to maintain a clear, functional separation between languages throughout their day
(Language A for work; Language B for home); others may constantly switch between their lan-
guages based on the relationships that they maintain with other people (Language A with
Person A; Language B with Person B; Languages A, B, and spontaneous code-switching with
Person C); while still others may switch freely between their languages with all members of
their community (Languages A and B and spontaneous code-switching with everyone; Green
& Abutalebi, 2013). Even if a bilingual spends most of their time in one of these modes, their
language mode or cognitive state can still vary based on context, making it important to con-
sider both differences between bilinguals and the current state a bilingual is in.
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Moving from bilingual traits to states
Each distinct interactional context may impose different processing demands that require
bilinguals to recruit different cognitive processes, and it is crucial that we consider these vary-
ing demands both among and within bilinguals. Green and Abutalebi’s Adaptive Control
Hypothesis (2013) proposes that varying interactional contexts allow bilinguals to develop dif-
ferent strategies in regard to their executive-control processes. For example, a bilingual who
uses two languages in one context, but each with a different person, may develop better
moment-to-moment task (dis)engagement skills, while a bilingual who uses a single language
in each interactional context might develop goal-maintenance skills, and a bilingual who freely
code-switches with everyone might benefit from opportunistic planning abilities. Indeed, one
study found that Spanish-English bilinguals from environments with different default interac-
tional contexts (a separated language context in Spain, an integrated language context in
Puerto Rico, and a varied context in the United States) differed in their performance on the
AX-continuous performance task (AX-CPT), which measures proactive and reactive control pro-
cesses (Beatty-Martínez et al., 2020). As the authors of that article point out, “by most past ac-
counts, the bilinguals from the three contexts examined here would be assumed to represent
samples drawn from the same or similar underlying populations of proficient Spanish–English
speakers” (p. 20). Alongside variable patterns across bilinguals’ proficiency levels, ages of ac-
quisition, etc., these observations suggest that it is inappropriate to treat “bilingual” as a single,
indivisible category, even when considering the specific language pair of bilingual participants.
Specific bilingual experience affects processing
Theories of bilingual language processing have also moved in the direction of considering the
various demands of bilingualism. While the Adaptive Control Hypothesis (Green &
Abutalebi, 2013) carefully considers how different bilingual language experiences modulate
processing and cognitive-control demands, the hypothesis reflects cumulative experience un-
der distinct interactional contexts, thus representing a Traits approach. Green and Wei (2014)
instead focus on the language control demands of different types of bilingual speech
(Muysken, 2000). This Control Process Model of Code-switching proposes distinct states of
speech planning (competitive or cooperative) based on the contextual demands and intentions
of bilingual speakers. Single language speech planning requires constant suppression of a
non-target language, thus invoking a competitive state. In contrast, code-switching falls under
cooperative planning even though different types of code-switches (e.g., single word or
copious switches across languages) invoke different control states (coupled vs. open control,
Green & Wei, 2014). Both models suggest that a bilingual’s dominant mode for interactional
contexts will affect their cognitive strategies in a fixed way, although acknowledging that each
bilingual may shift their mode of control as needed in particular situations. Indeed, both of
these hypotheses attribute fixed cognitive differences for different types of bilinguals to their
(at least initial) cognitive flexibility to adjust to the language demands of their dominant inter-
actional context. This flexibility is demonstrated by the adjustments that bilinguals and/or L2
learners’ linguistic systems make in immersion contexts (Botezatu et al., 2020; Dussias &
Sagarra, 2007; Linck et al., 2009). Recently, Green (2018) has expanded the Control Process
Model to account for more moment-to-moment changes in language control demands required
for bilingual code-switching, shifting to a more states-based hypothesis. As we will demonstrate in
the next section, language scientists have been pulling on ideas from these hypotheses and
increasingly applying their logic in States approaches that consider both an individual’s prior
experiences and in-the-moment demands.
Accounting for different bilingual experiences—from interactional context
to age of
acquisition—is also important when considering the potential neurological impacts of
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Moving from bilingual traits to states
bilingualism. DeLuca and colleagues recently proposed the UBET model, which outlines how
varied language experiences may affect distinct control processes and, in turn, supporting brain
structures (DeLuca et al., 2020). For example, the UBET model proposes that a bilingual’s
diversity of language use and language switching experience place variable demands on
executive-control processes, resulting in cognitive changes to proactive control and neural
changes to cortical grey matter and frontal activation. Factors such as proficiency and duration
of use are posited to have distinct cognitive and neural effects. Just as the UBET model supports
different outcomes for different bilingual experiences, Pliatsikas’s Dynamic Restructuring
Model (2020) supports different restructuring of gray and white matter based on the quantity
and quality of language experience. Importantly, these changes are not linear or incremental;
rather, initial increases in cortical and subcortical gray matter volume at an early stage of bilin-
gualism may be reduced at later stages of bilingualism, perhaps as connections are pruned to be
more efficient. Hernandez and colleagues’ framework of Neuroemergentism (2018) further
supports the idea that bilingualism has nonlinear, dynamic effects on cognition and neurology.
For example, age of acquisition may affect language representations in the basal ganglia, and
the resulting parasitic or symbiotic relationship between the L1 and L2 will dynamically affect
use of the prefrontal cortex. All of these models reflect the increasingly apparent conclusion that
bilingualism is not a singular category with uniform impacts on architectures and mechanisms
for information processing. Clearly defining and quantifying bilingualism or the language var-
iable of interest can help clarify what effects we expect to see in particular individuals under
different circumstances.
Diversity of experience beyond bilingualism
Although we have focused on the diversity of bilinguals, by pitting groups against each other,
traditional group-comparison approaches in bilingualism research may be masking variation
within even the monolingual group. Monolingual experiences also differ, yet group-level com-
parisons may focus on a particular version of monolingualism in participant samples. While
studies may include participants who are functionally monolingual (i.e., they would classify
themselves as monolingual), their experiences with a single language may vary. For instance,
bidialectal monolinguals whose two dialects are quite different in terms of lexicon as well as
grammatical and phonological rules (e.g., African American English vs. mainstream American
English) may engage in similar code-switching behaviors as bilinguals—shifting their language
use between speakers and contexts as necessary. This type of monolingual experience likely
also results in different cognitive demands and routines (e.g., Kirk et al., 2018; Oschwald et al.,
2018; cf. Poarch et al., 2019; Ross & Melinger, 2017).
Additionally, it is certainly possible that nonlinguistic factors such as particular types of
training or expertise might contribute to individuals’ performance on language processing or
executive-function tasks. As one example, musical training may affect individuals’ perfor-
mance on specific executive-function tasks (Moreno et al., 2011; Okada & Slevc, 2018).
And cognitive-control practice over the course of weeks can affect performance not only on
the trained nonlinguistic task (e.g., N-back with lures), but also on language-processing mea-
sures that have overlapping conflict-processing demands on the trained task (e.g., Hussey
et al., 2017; Novick et al., 2014). Presumably, these lab-based effects are miniature versions
of the kinds of effects that emerge through lifelong experience. Just as bilingualism can affect
the brain and behavior through experience-based plasticity (e.g., Pliatsikas et al., 2020), so
can other learning experiences. We do not always know each participant’s history with these
types of experiences, and the cumulative impact of lived experiences could give the group
comparison “edge” to either the monolingual or bilingual group. Given the difficulty of
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Moving from bilingual traits to states
controlling for each possible source of participant variation, it is beneficial to compare partic-
ipants to themselves under different conditions rather than making group generalizations.
Statistical issues and quantifying bilingualism
Clearly, there are various types of bilinguals and monolinguals. While our field has made great
strides from separating these diverse populations into two (simplified) groups, treating contin-
uous variables as dichotomous ones is a practice fraught with empirical and theoretical prob-
lems (Whitford & Luk, 2019). Dichotomizing variables that are actually continuous can mask
individual differences, reduce effect size and power, and hide nonlinear relationships, among
other statistical issues (see, e.g., MacCallum et al., 2002). Given the impact on individual dif-
ference detection, it is particularly important that we do not unnecessarily dichotomize vari-
ables when we are using language processing methods that already struggle to detect
individual differences in our effects of interest (e.g., the garden-path ambiguity effect in self-
paced reading; Cunnings & Fujita, 2021; James et al., 2018).
Thus far, it is clear that monolinguals and bilinguals can vary in their language experience
in ways that are important to capture on a continuum; however, it is not always clear how to
quantify that difference from the language history measures we collect. Recent work provides
one option, called language entropy, whereby researchers can estimate a bilingual’s diversity
of language use both as a function of their day-to-day language routines and across various
social contexts (Gullifer & Titone, 2019). For example, higher language entropy, or greater
diversity in language experience, relates to greater resting-state brain connectivity between
regions associated with second language speech production and executive functions (e.g.,
between the bilateral putamen and ACC; Gullifer et al., 2018). Another fruitful avenue is to
incorporate methods from social-network analysis to further quantify the nuances of bilingual
language experience (Tiv et al., 2020) and demonstrate its effect on language processing (e.g.,
Lev-Ari, 2018, Lev-Ari & Shao, 2017). Using an exposure-based approach to quantifying bilin-
gualism, one study drew different conclusions and interpretations about the effects of bilingual-
ism and age on executive function than studies that treat age and bilingualism as dichotomous
(Incera & McLennan, 2018). Unfortunately, many studies on bilingualism do not report objec-
tive measures of participants’ proficiency or language usage (Surrain & Luk, 2017).
Having to quantify bilingualism can help us specify exactly what aspect of bilingualism we
expect to have an effect on a given measure: Is it proficiency? Age of acquisition? Amount of
exposure to each language? Code-switching frequency? In doing so, we may find that people
previously labeled as monolingual actually demonstrate aspects of bilingual language process-
ing to some degree. This could be due to mislabeling of a sample. As Grundy points out in a
recent analysis (2020), there is no standardized method for splitting the continuum of bilingualism
into “monolinguals” and “bilinguals,” and participants labeled as part of the “monolingual”
group sometimes have experience learning an L2. Conversely, even “true” monolinguals
may look more like bilinguals after short-term learning experiences. For instance, one study
found that even beginner language learners showed a (small) cognate facilitation effect in elec-
trophysiological measures (Bice & Kroll, 2015). Another study found N400 differences in event-
related potential (ERP) responses to words versus nonwords in L2 learners after only 14 hours of
instruction (McLaughlin et al., 2004). Differences in linguistic diversity in the environment
may also impact how monolinguals process or learn a new language: Monolinguals surrounded
by a greater diversity of other languages (irrespective of their knowledge of those languages)
showed marginally significant late anterior positivity ERP to novel words versus nonwords in a
newly learned language that monolinguals from a more homogenous community did not dem-
onstrate (Bice & Kroll, 2019). Within monolinguals’ native language, increased exposure to
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Moving from bilingual traits to states
infrequent structures influences the ease with which monolinguals process difficult sentences,
such as object relative clauses (MacDonald & Christiansen, 2002; Wells et al., 2009). And
persistent experience with the grammatical environments in which particular verbs appear
continuously shapes the verb biases that individuals form to guide comprehension in real time
(Ryskin et al., 2017). Thus, it can be important to understand the background of participants
when drawing comparisons among them.
Bilingualism remains informative when treated as a continuum
In placing language experience on a continuum—where resolving competition and misanal-
ysis through domain-general control processes (even in monolinguals) is the norm—we might
ask: What is special about bilingualism? Why might certain aspects of bilingualism lead to
qualitative and/or quantitative differences with monolingual language experience? Here, we
may again turn to different experiences in bilingualism for insight. The majority of bilinguals
are unimodal bilinguals, meaning that they negotiate competition within and across lan-
guages through a single modality. In contrast, bimodal bilinguals, such as speech-sign bilin-
guals, are not constrained to a single modality (Emmorey et al., 2008a). If competition for
selection within the same modality is one underlying cause of increased reliance on and
efficiency in cognitive control, then bimodal bilingualism may place different demands on
bilingual language use (Blanco-Elorrieta et al., 2018; Emmorey et al., 2008b), despite the
continuing presence of bilingual language co-activation across modalities (e.g., Morford
et al., 2011; Pyers & Emmorey, 2008). Along similar lines, unimodal bilinguals are
constrained to producing code-switches, whereas bimodal bilinguals can additionally engage
in code-blending, in which both languages are produced at the same time across modalities
(e.g., spoken and signed). We can gain insights into the processing demands of bilingual
language practices by examining bimodal bilinguals who have been observed to engage in
code-blending over code-switching (Emmorey et al., 2008a), thus suggesting a biological
constraint to unimodal code-switching despite apparent costs.
Similarly, we can capitalize on different modalities of bilingualism to learn about bilingual
language control in general. For example, an MEG study investigated bimodal bilinguals in
two different states: transitioning from code-blending to using one language (“turning off” a
language) and transitioning from using one language to code-blending (“turning on” a lan-
guage), aspects of bilingual language control that simply cannot be dissociated in unimodal
bilinguals. Increased activity in bimodal bilinguals’ ACC when turning off but not turning on a
language suggests disengaging the no-longer-desired language is the more difficult aspect of
bilingual language control for bilinguals in general (Blanco-Elorrieta et al., 2018). In turn, these
insights from bimodal bilingualism suggest that bilingual code-switching is actually a skillful
language practice since bimodal bilinguals show a distinct preference for code-blending over
code-switching. Yet not all bilinguals engage in frequent code-switching and consequently
demonstrate differences in how they process code-switches in comprehension (Beatty-
Martínez & Dussias, 2017; Valdés Kroff et al., 2018). Interestingly, the P300, an early frontal
positivity component in EEG, is found to be modulated based on the self-reported code-
switching behavior of bilinguals and may be reflective of a switch cost for nonhabitual
code-switchers needing to shift from a “narrow” attentional state that supports unilingual pro-
cessing to a “broader” attentional state to accommodate code-switching (Beatty-Martínez &
Dussias, 2017; Valdés Kroff et al., 2020). In sum, treating bilingualism as a continuum does
not make studying its effects less interesting; it simply opens us up to studying a wider range of
bilingual factors and their effects (be they qualitatively or quantitatively different than effects of
monolingual experience) on various cognitive abilities and neural structures.
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Moving from bilingual traits to states
Given the methodological, statistical, logical, and theoretical concerns involved when
comparing bilinguals with monolinguals, we suggest that researchers should engage in a vigor-
ous inquiry into how bilinguals compare with themselves under different language-processing
conditions and observe the real-time consequences of these subtle manipulations. As we will
detail below, such an approach circumvents many of the concerns outlined here (see Box 1 for
example limitations of the Traits approach).
Box 1. Sample limitations of the Traits approach
Limitations related to
executive functions
Does not determine a person’s level of engagement at the
time of measuring their executive function.
Limitations related
to bilingualism
Does not allow for cause-and-effect claims about how
language processing affects executive-function
recruitment (or vice versa).
Uses executive-function tasks that can have low test–retest
reliability.
Uses group comparisons, which makes it difficult to control
for all possible experiential, cultural, and demographic
factors that affect executive functions.
Groups bilinguals from different interactional contexts
together even when they may recruit executive functions
differently.
Cannot capture moment-to-moment shifts in bilinguals’
control processes based on language context.
Does not consider diverse monolingual experiences that
could differentially impact executive functions (e.g.,
bidialectalism).
Treats the continuum of bilingualism as a dichotomy, which
has statistical and theoretical drawbacks.
May incorrectly classify people with minimal (but critical)
second-language experience as monolinguals.
A COMPLEMENTARY STATES APPROACH
In view of the limitations sketched above, it is incumbent upon language scientists to ask new
questions that are not about trait advantages that compare bilinguals to monolinguals. When
bilinguals have faster response times, higher accuracy, or more efficient behavioral or neural
activity, it may be due to bilinguals’ specific language backgrounds and/or to the immediate
testing context. Performance on a task at one point in time may not always reflect a lasting
advantage so much as an ability that has been temporarily upregulated at the time of testing
due to processing demands, linguistic or otherwise. In cases where routine linguistic process-
ing demands have resulted in different cognitive strategies at some baseline, we should be
careful not to think of this as a bilingual-wide advantage, but rather as a cognitive adaptation
to particular language demands that may also be present for certain monolinguals (e.g., mono-
linguals who are bidialectal, who navigate relatively more linguistic conflict, or who are
exposed to more linguistic diversity).
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Instead, we can turn to questions such as: What properties of bilingualism might engage
cognitive control or other executive functions in the first place? Are there unique language-
processing demands that bilinguals face in real time that might regulate attention and cognitive
control? Rather than comparing bilinguals to monolinguals, these questions focus on the spe-
cific demands of bilingualism and how linguistic and cognitive systems meet those demands.
The answers to these questions could eventually have significant implications for pedagogical
approaches and educational decisions by revealing how subtle manipulations of bilingual
behavior (e.g., interpreting a code-switch vs. not) recruit attention and cognitive-control
mechanisms (Antón et al., 2016; Mallikarjun et al., 2017). Such an approach therefore assumes
a more dynamic process at play rather than cumulative differences. Bilinguals’ experiences vary
widely, and their respective environments may place different pressures on cognitive systems
over time that may not apply uniformly across all bilinguals as a fixed trait and, indeed, may
not always result in default-state benefits to those systems. Consistent with these ideas, a recent
Bayesian meta-analysis found evidence to support executive-function advantages in bilinguals
over monolinguals but noted that such differences are on the order of milliseconds and may
depend on factors such as bilinguals’ interactional context (Grundy, 2020). Just as Grundy sug-
gests in that article, we are advocating for more research on when (not if ) bilinguals’ language
processing recruits executive functions, with well-articulated linking assumptions.
Grundy’s analysis included 167 studies from the 2000s on bilingualism and executive
functions, all of which took a group comparison (i.e., Traits) approach (Grundy, 2020).
Relatively speaking, there are far fewer bilingualism studies taking a within-participant
States approach, although some recent work has moved in that direction. Having learned a
lot—but also left with lingering questions—from past work using the traditional Traits
approach, researchers have increasingly been considering the diversity of within-language
experiences and contexts. For instance, recent studies have examined how same language-
pair bilinguals from different communities use language differently and/or perform differently
on cognitive ability tasks (e.g., Beatty-Martínez et al., 2020; Blokzijl et al., 2017; Hofweber
et al., 2016, 2020). Other work has tested how bilinguals’ experiences with particular produc-
tion distributions correlate with their ease of comprehension (Beatty-Martínez & Dussias,
2019; Rossi et al., 2021; Valdés Kroff et al., 2017, 2018) or their performance under different
task demands (Blanco-Elorrieta & Pylkkänen, 2017; Gollan & Ferreira, 2009). These types of
approaches are a great starting point for understanding the effects of different bilingual lan-
guage experiences.
Past Work Applying a States Approach to Bilingualism and Cognition
Manipulating states within experimental blocks
For the purposes of testing for relationships between language processing and cognition, we
have argued that within-bilingual comparisons allow us to answer questions about the
moment-to-moment demands of these systems and how they interact. Take, for example, a
study in which bilingual participants completed a Flanker task testing their cognitive control
while ignoring words interleaved between the trials (Wu & Thierry, 2013). When words from
both their languages were mixed with the Flanker task, bilinguals made fewer errors and had a
reduced P300 ERP mean amplitude on incongruent, conflict-laden Flanker items as compared
to a block when words from only one of their languages were interleaved. By observing the
same bilinguals in different linguistic contexts, they were able to conclude that a mixed-
language situation upregulated cognitive control more than a single-language situation, dem-
onstrated by performance modulations on the nonlinguistic Flanker task.
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Similarly, Jiao and colleagues found that Chinese-English bilinguals performed better on
incongruent and congruent Flanker trials when they were interleaved with reading or listening
comprehension tasks that appeared in both languages as opposed to in a single-language
block (Jiao et al., 2019). In follow-up experiments using a non-conflict version of the
Flanker task, the effect disappeared, suggesting that the mixed-language context upregulated
conflict monitoring rather than general alertness. In another study, incongruent and congruent
Flanker trials were interleaved with a picture-naming task that was completed in either one
language or both languages throughout a block. Although a block’s language context did
not affect behavioral performance on the Flanker task, using ERPs the authors found that a
mixed-language context resulted in larger N200, smaller P300, and smaller late positive com-
ponent (LPC) mean amplitudes on Flanker trials when compared to single-language contexts
(Jiao et al., 2020). Using a States approach that compared bilinguals to themselves under dif-
ferent linguistic conditions, the authors concluded that the mixed-language context resulted in
better efficiency on the task, perhaps due to upregulated conflict monitoring. Using a similar
blocked language context approach with fMRI, Guo and colleagues (2011) manipulated the
language demands of a picture naming task to draw conclusions about the brain regions
involved in distinct inhibitory processes. They determined that bilinguals engaged the ACC
and supplementary motor area relatively more in the mixed-language block versus single-
language blocks, which they took as a measure of local inhibition of specific other-language
representations. In general, these studies show that different language contexts engage distinct
executive-function processes within bilinguals.
While the aforementioned studies manipulated language context across blocked sessions to
observe its effect on a measure of executive function, it is also possible to design the opposite
paradigm by manipulating the type of conflict across blocked sessions to observe the effect on
language processing. In one such study, Chinese-English bilinguals completed a Stroop ink
color naming task where the words were color words in either language (conflict block) or
non-color words in either language (no-conflict block). Bilinguals took longer to name the
ink color when switching between languages from trial to trial (as compared to staying in
the same language) in the conflict block as compared to the no-conflict block, especially when
switching into the L1 (Liu et al., 2019). Comparing bilinguals with themselves in this way re-
vealed that general conflict-resolution or inhibition demands can affect bilinguals’ language
processing in the moment.
Manipulating states from trial-to-trial
A finer-grained approach is to investigate such effects at the trial level rather than in a more
global block context. This can be done by manipulating linguistic demands (e.g., interpreting a
code-switched sentence vs. a unilingual sentence) to observe the effects of such manipulations
on cognitive performance on a trial-by-trial basis. One such method leverages a recognized
effect in cognitive psychology known as conflict adaptation, where conflict trials (e.g., ! !
! ! ; incongruent trials of a Flanker task), relative to no-conflict trials (e.g., ! ! ! ! ! ;
congruent trials of a Flanker task), strengthen performance on subsequent conflict trials (e.g.,
Gratton et al., 1992; Ullsperger et al., 2005). This indicates that conflict detection engages
cognitive control, which sustains to facilitate processing of ensuing conflict on subsequent
trials by meeting task demands. Taking a cross-task conflict adaptation approach, one study
found that bilinguals responded faster to incongruent Flanker trials after reading a code-
switched sentence as compared to a unilingual sentence (Adler et al., 2020). In a similar design,
Bosma and Pablos (2020) found that the difference in P300 amplitude between congruent and
incongruent Flanker trials was modulated by a code-switch in a prior trial. These studies’
Conflict adaptation:
A behavioral phenomenon where
high-conflict trials in tasks like Stroop
or Flanker, relative to low-conflict
trials, enhance performance on
subsequent high-conflict trials.
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Moving from bilingual traits to states
findings are in line with others’ conclusion that dual-language contexts engage cognitive
control (Jiao et al., 2019; Wu & Thierry, 2013). Despite ostensible differences in stimulus
features between Flanker and sentence trials, the manipulation of switching condition
(code-switched vs. unilingual sentences) shifted performance on Flanker trials with conflicting
cues. One interpretation of this result is that the shared need for conflict resolution in both
tasks allows adaptation between them: Integrating a code-switch during comprehension
engages a common cognitive-control process, which remains engaged to accomplish opti-
mized performance on incongruent Flanker items. Specifically, this suggests that integrating
a code-switch during real-time comprehension deploys domain-general cognitive-control pro-
cedures to a different extent than unilingual sentence processing, presumably to resolve the
conflict that arises across linguistic representations. Thus, interpreting a code-switch represents
a different linguistic state than interpreting an otherwise matched unilingual sentence, resulting
in transient changes in cognitive-control recruitment.
The conflict-adaptation approach has also been implemented to observe whether the rel-
ative engagement status of a bilingual’s cognitive-control state influences their real-time
language processing, in particular, their ability to recover from temporary misinterpretations
(Navarro-Torres et al., 2019). To manipulate cognitive control, one study interleaved congru-
ent and incongruent Stroop trials with a language task in which participants had to follow
instructions that were either unambiguous or temporarily ambiguous and ripe for misanalysis
(e.g., “Put the frog on the napkin onto the box,” where “on the napkin” is initially interpreted
as a destination but must be revised once “onto the box” unfolds, conflicting with that inter-
pretation; Navarro-Torres et al., 2019). When cognitive control was upregulated after an
incongruent Stroop trial, eye-fixation data showed that bilinguals revised earlier as compared
to when cognitive control was comparatively less engaged (i.e., the prior trial was a congruent
Stroop trial). This replicates findings in monolinguals (e.g., Hsu & Novick, 2016; Hsu et al.,
2021; Thothathiri et al., 2018) and demonstrates how parsing and interpretation can be
rapidly affected by different states of cognitive engagement. Moreover, when comparing
the effect of variable states in bilinguals to monolinguals, the data revealed that bilingual
listeners began disambiguating the ambiguous sentences earlier than monolingual listeners,
suggesting group differences in the timing of cognitive-control engagement (Navarro-Torres
et al., 2019). This study exemplifies the value that a combined States and Traits approach can
have, especially for considering the effects of both immediate state-based effects and lifetime
experience.
Together, these studies demonstrate that bilinguals’ cognitive-control procedures are not
static and that different language processing demands mobilize them to different extents.
The findings also begin to converge on hypotheses about how certain bilingual demands
(e.g., processing a code-switch during comprehension, a situation in which a bilingual’s
two linguistic systems are drawn into direct conflict) deploy specific sorts of executive-function
processes (e.g., cognitive control, which biases information processing toward task-relevant
over -irrelevant cues). Moreover, these state-based findings indicate a causal interplay that
group comparisons cannot uncover: Increased conflict-processing demands during bilingual
comprehension (comprehending a code-switch vs. not) causes increased cognitive control
during Flanker performance. Similarly, engaging cognitive control from a prior Stroop trial
increased bilinguals’ (and monolinguals’) regulation of interpretations during syntactic pro-
cessing. Thus, comparing bilinguals to themselves under different conditions shows how lin-
guistic and nonlinguistic systems interact and are temporally connected and interdependent
from moment to moment. While most research on the relationship between cognitive function
and bilingual language concentrates on how cognitive traits are fixed within a group and
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differ between them, this work reveals how ordinary variations in linguistic context or cogni-
tive engagement within individuals also impact processing and performance.
Future Directions for a States Approach to Bilingualism
We have illustrated some of the questions that States approaches can address and reviewed
two state-based study designs: (1) blocking language, task, or pragmatic context to observe the
effect on cognitive control (or vice versa), and (2) using trial-to-trial, cross-task conflict adap-
tation to observe immediate effects of cognitive-control engagement on language processing
(or vice versa). As the relationship among bilingualism, executive functions, and their neural
correlates remains underspecified, we see these two design options—applied behaviorally
and/or with neuroimaging techniques—as viable options for future work that teases apart
the role of executive functions in various bilingual language processing contexts. However,
these are certainly not the only options for States approach designs.
For example, the extent to which language context affects attention remains underspecified
and could be explored using a States approach. Mind-wandering studies indicate that attention
is frequently off-task during language comprehension tasks (Boudewyn & Carter, 2018a;
Smallwood et al., 2008a; Uzzaman & Joordens, 2011). Future work could manipulate bilin-
gual language context to determine if different language states modulate attention in a mind-
wandering paradigm, measuring attentional state through behavioral self-reports or through
alpha oscillatory power (cf. Boudewyn & Carter, 2018a). Similarly, Kaan and colleagues dem-
onstrated that the LPC (Moreno et al., 2002)—an ERP component typically found when bilin-
guals parse a code-switch and reflective of reanalysis or unexpectedness—is reduced when a
bilingual participant parses code-switches in the presence of another bilingual interlocutor as
compared to a monolingual interlocutor. This suggests that bilingual processing demands are
modulated by the pragmatics of a linguistic context (a state) and that cognitive (or attention)
control operations may fluctuate on the basis of the interlocutors’ expected shared knowledge.
Another possibility would be to determine if prior language context (e.g., code-switched vs.
unilingual content) affects the ERP signatures associated with detecting acoustically deviant
stimuli in an “oddball” paradigm. For example, a speech disfluency preceding an attention-
grabbing, deviant stimulus can reduce the typical mismatch negativity and P300 effects, per-
haps because the disfluency had already captured the participants’ attention (Collard et al.,
2008). Code-switching may perform a similar attention-capturing function or may lead bilin-
gual listeners to better anticipate less expected or more difficult linguistic information (Tomic(cid:1)
& Valdés Kroff, 2021). Such effects may be due to modulations in bilingual comprehenders’
attention based on linguistic context (e.g., tracking a speaker’s state of mind as a window into
why they might have switched languages mid-utterance).
Moving beyond bilingualism’s effect on various constituents of executive function, it is also
reasonable to expect that bilingual experiences may drive recruitment of other types of cog-
nitive and neural machinery. For instance, the integrity of declarative memory systems, sup-
ported by the hippocampus, have been shown to influence aspects of online language
processing including reference resolution (Kurczek et al., 2013) and the use of common
ground to constrain interpretations (Rubin et al., 2011). Given that communication is facilitated
when interlocutors exploit shared knowledge (i.e., common ground), it would be well-
motivated to investigate whether different bilingual interactional contexts modulate the repre-
sentation and access of such information to guide comprehension (e.g., common ground
among speakers from the same vs. different sociological and linguistic communities).
Tracking information from the discourse, such as common- versus privileged-ground
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information or a pronoun’s antecedent, places pressure on the hippocampal declarative
memory system (Duff & Brown-Schmidt, 2012). By extension, the type of discourse situation
(e.g., code-switching vs. not; communicating with a group member vs. not) may also modulate
how much pressure is placed and the extent to which the hippocampus contributes to a linguistic
process like common-ground assessment. As before, however, relationships between bilingual
experience and cognitive performance should be investigated based on well-developed linking
assumptions (e.g., the pragmatic effects sketched above in Kaan et al., 2020).
Alongside these possible approaches, we echo others in calling for clear reporting of the
context in which bilingual testing occurs, given the effects of interactional context and partic-
ular language experiences (de Bruin, 2019; Luk & Bialystok, 2013; Whitford & Luk, 2019).
Recall that bilinguals shift their linguistic and cognitive states in accordance with the demands
of a particular situation. In recognizing this immense flexibility, we should adequately describe
the interactional context of the larger bilingual community at the site of testing (e.g., Beatty-
Martínez et al., 2020) as well as the immediate context of the experiment itself. This includes
considering the community’s attitudes toward the languages or toward linguistic behaviors
such as code-switching (Dewaele & Wei, 2014; Treffers-Daller et al., 2020), the location of
experimental testing along with the associated linguistic norms of that place, and the experi-
menters with whom the participants interact. Knowing that experimentally manipulated lan-
guage context can affect a bilingual’s cognitive state (Adler et al., 2020; Jiao et al., 2019, 2020;
Wu & Thierry, 2013), we must assume that the language context in the lab (e.g., considering
building location, experimenter’s language of choice, experimenter’s register) can affect a bi-
lingual’s cognitive state as well. Indeed, one benefit of a States approach is that these socio-
linguistic effects of community or lab context on processing can be investigated. However,
when these social implications are not the manipulation of interest, we join others in under-
lining the importance of reporting in detail the experimental context, because bilinguals (and
monolinguals) are surely adjusting to it.
CLOSING REMARKS
Conventional models of bilingual language processing that describe a role for executive func-
tions overwhelmingly provide correlational data on the individual- or group-level scales,
which has demonstrated how aggregate measures of performance compare across bilingual
and monolingual populations. Here, we advocate for an emerging and highly compatible ap-
proach, which examines the immediate or near-immediate impact of different language con-
texts on executive function performance and, correspondingly, of different states of cognitive
engagement on language processing.
By design, such an approach diverges from the typical one in that experiments within this
framework consider individuals against themselves under different linguistic or cognitive
states. Rather than provide insights about year-to-year, cumulative differences between
groups, this proposal suggests a moment-to-moment timescale that can offer data about
the architecture of the language processing system and what roles various cognitive mech-
anisms play in real time. Necessarily, this requires a shift in the types of narrow research
questions that psycholinguists ask (see Box 2). For instance: What are the unique
language-processing demands that bilinguals confront during real-time production and com-
prehension that generate the need for components of executive function to mitigate those
demands? Are there idiosyncratic pragmatic inferences a bilingual must draw during com-
munication with other bilinguals versus monolinguals? And, if so, what specific cognitive
regulatory mechanisms and associated brain regions does this engage? Do manipulations
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of attention control (vs. cognitive control) adjust a bilingual’s ability to isolate a speaker’s
voice from other sources of noise in a crowded restaurant, avoiding processing difficulty?
There is a current gap in knowledge in these areas, but closing it is crucial for advancement
toward a complete model of language processing in the bilingual (and monolingual) mind.
By manipulating language contexts, one can observe the consequences of those subtle
manipulations on particular aspects of cognitive performance; similarly, by manipulating
the engagement status of particular cognitive systems (e.g., upregulation of attention control
vs. cognitive control vs. some other executive function), with specific linking hypotheses
about what language tasks these systems interact with, one can observe the consequences
of these subtle manipulations on linguistic performance.
Box 2. Comparing typical states and traits approaches
Example questions
approach can
address
Typical Traits approach
Do monolinguals and bilinguals
recruit executive functions
differently?
Typical States approach
What moment-to-moment
bilingual language-processing
demands engage executive
functions?
If so, do bilinguals have an
How does a bilingual’s
advantage over monolinguals
on certain tasks (or vice
versa)?
cognitive state impact their
language processing (or
vice versa)?
Standard methods Group-comparisons between
participants; individual
differences studies.
Within-participant comparisons
under different conditions
(at the block level or at the
trial level).
Use of executive
functions
Examines individual differences
in one-time “snapshot”
performance on tasks.
Looks for fluctuations in
performance under different
conditions of tasks.
Categorizing
bilingualism
Dichotomization of
“monolingual” and
“bilingual” groups to carry
out critical between-groups
comparisons.
Newer continuous measures of
language experience (e.g.,
entropy) can be incorporated
since comparisons are
within-groups.
Some advantages
Detects differences that emerge
based on cumulative life
experiences.
Some limitations
Tasks may be poorly suited
for detecting individual
differences. Splits a
continuum of bilingualism
into a dichotomy.
Allows for cause-and-effect
claims. Considers an
individual’s state of
engagement at the time of
their performance on a task
and the processing demands
that task incurs.
Still summarizes an individual’s
performance (within each
condition). Continues to
use artificial, lab-based
conditions, which may tap
into a specific language mode.
Neurobiology of Language
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Moving from bilingual traits to states
We believe the within-person approach that we have summarized in this article, which has
been emerging in psycholinguistic studies of language processing in recent years, is well-
suited to address these and a range of other relevant questions and allows causal (rather than
correlational) inferences to be drawn about the real-time cognitive and/or linguistic demands
that shape performance in the moment. In sum, we suggest that the prevalent Traits approach
to bilingual language processing can be usefully complemented with a burgeoning States
approach, assessing how different aspects of the bilingual experience rely on executive func-
tions. This should allow us to move beyond discussions of bilingual-monolingual differences
toward a better understanding of the processing dynamics of bilingual language processing.
ACKNOWLEDGMENTS
We would like to thank Gigi Luk and an anonymous reviewer for their helpful feedback.
FUNDING INFORMATION
Jared M. Novick, National Science Foundation (https://dx.doi.org/10.13039/100000001),
Award ID: NSF BCS2020932. Jorge R. Valdés Kroff, National Science Foundation (https://dx
.doi.org/10.13039/100000001), Award ID: NSF BCS-2017251. Lauren K. Salig, National
Science Foundation (https://dx.doi.org/10.13039/100000001), Award ID: 1449815. Jorge R.
Valdés Kroff, National Science Foundation (https://dx.doi.org/10.13039/100000001), Award
ID: BCS-1941514.
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AUTHOR CONTRIBUTIONS
Lauren K. Salig: Conceptualization: Equal; Writing – original draft: Lead; Writing – review &
editing: Equal. Jorge R. Valdés Kroff: Conceptualization: Equal; Writing – original draft: Equal;
Writing – review & editing: Equal. L. Robert Slevc: Conceptualization: Equal; Writing –
original draft: Equal; Writing – review & editing: Equal. Jared M. Novick: Conceptualization:
Equal; Writing – original draft: Equal; Writing – review & editing: Equal.
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