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Frontiers in Communication 01 frontiersin.org
Individual dierences in discourse
management
DeryaÇokal
1*, JasonBishop
2, JacopoTorregrossa
3,
ClarePatterson
1, MartineGrice
1, SimonWehrle
1, MariaLialiou
1,
SophieRepp
1, HeikoSeeliger
1, SonjaEisenbeiß
1,
KlausvonHeusinger
1, KaiVogeley
1 and PetraB.Schumacher
1
1 University of Cologne, Cologne, Germany, 2 The City University of NewYork, NewYork, NY,
UnitedStates, 3 Goethe University Frankfurt, Frankfurt, Germany
Every utterance in discourse weproduce arises from the interaction of numerous
cognitive functions, such as semantic memory, where westore the meanings
of words, executive function and working memory as required for maintenance
of a discourse goal, and social cognitive abilities, such as mind-reading capacity
as required for tuning what wesay to what others know or believe. In this way,
a single utterance potentially integrates very dierent cognitive capacities into
a basic discourse processing unit. This suggests that discourse processing and
management is a very rich phenomenon that requires a multidimensional approach.
Wepropose that a model of discourse management is comprised of three primary
components that interact synergistically: (i) dynamicity, (ii) predictability, and (iii)
meta-representationality. Cognitive functions play a pivotal role in the underlying
processes, contributing to the development and unfolding of discourse. Understanding
the correspondence between individual dierences in discourse management
(i.e., discourse perception and production) and cognitive functions can shed
light on the intricate relationship between language and cognition in discourse
management, as well as the appropriate psychometric measures to address this
complex interaction. This narrative review presents aspects of discourse management,
psychometric measures to comprehensively address these aspects. Weclose with
a discussion of challenges and open questions.
KEYWORDS
discourse, cognitive functions, autism, bilingualism, individual dierences, prosody,
anaphora processing, social cognition
1 Introduction
Eective discourse management across both spoken and written modalities involves
the interplay of three cognitive key components: dynamicity, predictability, and meta-
representationality (Newen and Vogeley, 2003; Vogeley and Bartels, 2011; von Heusinger
and Schumacher, 2019). ese components are fundamental for navigating both spoken
and written discourse, including engaging in conversations with multiple participants,
resolving ambiguity, and adapting to continuously unfolding information in discourse
representation. In this narrative review, weargue that these components are central to
discourse management (e.g., the construction and updating of a discourse), and are
intimately linked to basic cognitive functions such as working memory (WM) and
executive functions (EFs), as well as social cognition capacities such as mind-reading
capacity (e.g., also referred to as social reasoning, mentalizing or theory of mind).
Ultimately, this link between discourse management processes and underlying cognitive
functions may account for individual dierences in the choice and interpretation of
expressions and constructions in discourse. Understanding this connection matters
OPEN ACCESS
EDITED BY
Antonio Benítez-Burraco,
University of Seville, Spain
REVIEWED BY
Rob Davies,
Lancaster University, UnitedKingdom
Hannah Lutzenberger,
Stockholm University, Sweden
*CORRESPONDENCE
Derya Çokal
dcokal@uni-koeln.de
RECEIVED 13 June 2024
ACCEPTED 20 January 2025
PUBLISHED
CITATION
Çokal D, Bishop J, Torregrossa J, Patterson C,
Grice M, Wehrle S, Lialiou M, Repp S,
Seeliger H, Eisenbeiß S, von Heusinger K,
Vogeley K and Schumacher PB (2025)
Individual dierences in discourse
management.
Front. Commun. 10:1448463.
doi: 10.3389/fcomm.2025.1448463
COPYRIGHT
© 2025 Çokal, Bishop, Torregrossa, Patterson,
Grice, Wehrle, Lialiou, Repp, Seeliger,
Eisenbeiß, von Heusinger, Vogeley and
Schumacher. This is an open-access article
distributed under the terms of the Creative
Commons Attribution License (CC BY). The
use, distribution or reproduction in other
forums is permitted, provided the original
author(s) and the copyright owner(s) are
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distribution or reproduction is permitted
which does not comply with these terms.
TYPE Review
PUBLISHED
DOI 10.3389/fcomm.2025.1448463
07 February 2025
07 February 2025
Çokal et al. 10.3389/fcomm.2025.1448463
Frontiers in Communication 02 frontiersin.org
because it allows us to identify measurable cognitive processes
underlying discourse management. By doing so, wecan determine
how individual dierences in cognitive functions such as WM, EFs,
and social cognition shape interactions in discourse. is insight
not only deepens our understanding of language use but also
informs the design of psycho/neurolinguistic experiments and new
psychometric tools to assess and predict communication
eectiveness in diverse contexts (cf. Brysbaert’s (2024) tutorial on
designing and evaluating tasks to measure individual dierences).
Such insights are foundational for advancing linguistic theory and
they also hold practical relevance for education, clinical diagnosis,
innovative communication technologies, and speech therapy (e.g.,
for people with communication problems). Establishing this link
enables the identication of cognitive proles that inuence
language use, helping us better understand how individuals
process, adapt, and engage in discourse, particularly in diverse
social and cognitive contexts.
Individual dierences refer to variations among individuals in
discourse management, particularly in relation to key cognitive
aspects such as WM, EFs, social cognition capacities, personality
traits and states, and/or personal interests. Specically, in our
research within the framework of Prominence in Discourse, wehave
encountered signicant individual variability at the discourse level.
Furthermore, a very recent article by Dietrich et al. (2024)
underscores the importance of investigating individual dierences
in future research. Specically, they suggest examining how
discourse processing strategies correlate with variations in working
memory (e.g., working memory load aects intact and violated
presupposition). A similar call is echoed in the recent book
Individual Dierences in Anaphora Resolution by Fotiadou and
Tsimpli (2023), which underscores the scarcity of research on
individual dierences at the discourse level and the cognitive
processing involved. Accordingly, weprovide a narrative review of
components of discourse management, present a model of
discourse management that relies on prominence relations, and
examine how these components may beinuenced by individual
traits. is is the rst attempt to connect a discourse management
model with cognitive functions, demonstrating how individual
dierences can inform, and how research on individual dierences
can beinformed by such a model. Our focus encompasses both
spoken (conversation) and written (text-based)
discourse management.
To lay out the basis for our review, in the following sections
werst provide a brief overview of previous review articles on
individual dierences in linguistics. Next, we outline our
methodology. ird, wediscuss the three fundamental components
of discourse management that participants utilize. Wethen identify
the cognitive processes and resources involved in discourse
management. Following that, wereview psychometric measures of
individual dierences in cognitive functions and social cognition
capacities. To establish the idea that discourse management can
beassessed by psychometric tests addressing cognitive functions,
wethen review case studies that specically investigate individual
dierences in discourse management, covering prosody,
neurotypicality, online language comprehension, and bilingualism.
Finally, wediscuss the challenges involved in testing and analyzing
individual dierences data, and we highlight directions for
future studies.
1.1 Previous reviews on individual
dierences
To our knowledge, there are no reviews specically addressing
individual variation in discourse management that encompasses
both spoken and written modalities. erefore, to situate our
review, werst survey previous review articles on individual
dierences across sub-disciplines of linguistics. In a review article,
Kidd etal. (2018) examine recent research in psycholinguistics,
and propose that linguistic and psycholinguistic theories have
downplayed the existence of meaningful variation in language use
among individuals. Specically, they discuss how a focus on
individual dierences oers critical insights into language
acquisition and processing. Specically, they emphasize the
importance of language experience in language acquisition,
processing, attainment, as well as the underlying structure of the
language system. erefore, they show the relationship and
interaction between language and cognitive systems and thus put
forth three key imperatives for theories and future studies: (1) e
existence imperative, which calls for theories of acquisition and
processing of language to predict meaningful individual dierences
in language; (2) e environmental imperative that highlights the
role of input, emphasizing the relationships between language
abilities and the amount and nature of linguistic input individuals
receive; and (3) e architectural imperative, which urges
theoreticians to explain the connections between linguistic
subsystems and underlying cognitive processes.
Building upon this research, Matthews et al. (2018) review
studies on pragmatic skills in children, and highlight their
associations with pragmatic abilities, formal language (vocabulary
and grammar), social cognition [eory of Mind (ToM)], and EFs.
In addition, Matthews etal. (2018) point out that very few studies
have examined such relationships because there are relatively few
tests of individual dierences in pragmatic skills that have good
psychometrics in terms of reliability, validity, and distributional
properties. ey also demonstrate that the cognitive processes
underlying pragmatic inferences are oen not well-dened,
making it dicult to determine why specic pragmatic tasks
should correlate with broader cognitive measures. While their
approach examines components like formal language, social
cognition, and EFs to understand discrete abilities such as irony
comprehension and contingent conversation, our approach
emphasizes discourse management. Wefocus on the interplay of
dynamicity, predictability, and meta-representationality as
essential for managing discourse representation, resolving
ambiguity, and processing unfolding information. Moreover, while
the authors point to methodological limitations (i.e., sample size,
good quality measures for sucient variance in pragmatics, clear
information on processing, and controls for theoretical important
covaraites like formal language and non-verbal IQ) and propose
developmental taxonomies of pragmatic skills, we provide a
framework for discourse management across spoken and written
modalities and propose how components of discourse management
interact with cognitive and social abilities.
Expanding the focus to a phonological perspective, Yu a n d
Zellou (2019) observe that individual variation is evident in most
phonological behaviors. However, few studies address the
heterogeneity of language processing and production, as the focus
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Frontiers in Communication 03 frontiersin.org
tends to remain on group-level patterns. ey provide an overview
of individual variability within phonology, examining how
linguistic patterns can dier among individuals. ey compare a
traditional population-level approach, which relies on experimental
manipulations and aggregated responses, with an individual-
dierences approach that explores naturally occurring variability.
eir review suggests that language variation and sound change
may beinuenced by individual dierences in how phonological
information is stored and processed. Interindividual variation has
also been examined with respect to the use of various phonetic
parameters demonstrating that individual listeners and speakers
weigh certain acoustic cues dierently (e.g., Bishop, 2016;
Baumann and Winter, 2018; Bishop et al., 2022; Lorenzen and
Baumann, 2024).
While previous reviews have explored individual dierences
within specic language domains—such as pragmatic abilities
among children, and phonological processing—our review oers an
integrated view, since several aspects of discourse management
across spoken and written modalities are considered at the same
time. Responding to Kidd etal.’s (2018) call, weprovide a model of
discourse management comprised of three key components and
propose that the link between these discourse management
components and cognitive functions may explain individual
variability at the discourse level. Our review builds on existing
literature by specically examining the relationship between
discourse management and cognitive functions across dierent
contexts and populations. In particular, wecover discourse related
prosody in production and comprehension, online discourse
comprehension, and reference management among bilinguals,
thereby bringing a new dimension to discussions of individual
dierences at the discourse level. is novelty arises both from the
domains weexplore and the approach weadopt.
1.2 Methods
Given that our review is a narrative review with critical reection,
our methodology involves the targeted selection of studies that
provide both theoretical and empirical insights that illustrate the
fundamental components of discourse management and their
interaction with cognitive functions. Psychometric measures were
chosen based on their frequency of use within sub-domains of
linguistics and their relevance to exploring the relationship between
cognitive functions and discourse management. Wechose case studies
where weobserve individual variation at the discourse level, where
evidence exists for the utility of components as distinct constructs, or
where the predictive validity of cognitive measures related to discourse
management was present. Specically, weincluded studies from our
own labs and other published research highlighting individual
dierences in discourse management.
1.3 Components of discourse management
and their interaction with cognitive
functions
To show the signicance of the discourse components and their
contributions to discourse management and cognition, weconsider a
written text that describes a scenario involving two individuals, a cello
player and a critic, at a concert.
(1)
(a) e cello player wants to impress the critic. (b) However,
he is asleep at the wheel. (c) e cello player is completely
frustrated about the situation.
In (1a), the cello player and his feelings about the critic are
introduced. When the personal pronoun he is read or heard by readers
and listeners in (1b), the pronoun is immediately associated with the
cello player since the interpretation is guided by features of the
antecedent expression (i.e., cello player in (1a) represents the rst-
mentioned, subject, more agentive entity) and is thus the prominent
antecedent for the personal pronoun he (cf. e.g., the rst-mentioned
entity advantage in pronoun resolution in Gernsbacher and
Hargreaves, 1988; Carreiras etal., 1995). However, as the discourse
unfolds (i.e., “asleep at the wheel”), it becomes evident that he refers
to the critic, not the cello player because this is the more plausible
scenario at this stage of the discourse. Hence referential discontinuity
(i.e., a shi from the cello player to the critic), necessitates a dynamic
update of the discourse representation, yielding co-reference of the
personal pronoun in (1b) with the critic. As (1) shows, dynamicity is
crucial for constructing and managing a coherent discourse
representation (e.g., Kamp, 1981; Lascarides and Asher, 2007; Dek ker,
2012; von Heusinger and Schumacher, 2019). is process requires the
active processing of incoming information, integrating it with existing
knowledge, and tracking information structures within discourse. In
addition, it involves constructing and updating mental models and
discourse structure (cf. mental models in Garnham, 2001; Johnson-
Laird, 1983; Johnson-Laird and Garnham, 1980; Kintsch and van
Dijk, 1978).
As seen above, predictability also plays a major role in
understanding the next discourse units (Friston, 2010; Bornkessel-
Schlesewsky and Schumacher, 2016; von Heusinger and Schumacher,
2019). Based on the information in (1a), readers and listeners predict
that the narrative will beabout the cello player’s actions and/or the
critic’s response. However, in (1b), the idiomatic expression ‘asleep at
the wheel’ suggests negligence by the critic, prompting readers and
listeners to predict the potential consequences of this negligence. In
(1c), readers and listeners conclude the cello player’s disappointment
is a consequence of the critic’s behavior. In such cases, they anticipate
the narrative’s development, facilitating the creation of a mental
representation of discourse. Numerous theoretical frameworks have
modelled this predictive behavior in discourse with respect to
accessibility, activation, or attentional centering (see von Heusinger
and Schumacher, 2019 for an overview). Weadopt the prominence
framework, where varies cues contribute to discourse management.
Traditionally, grammatical and thematic cues have been the focus of
research on prominence-lending cues. However, our proposal also
extends to multimodal cues, such as (pointing) gesture, head nods or
other non-manual cues.
In addition to these two components of dynamicity and
predictability, meta-representationality come into play as readers and
listeners consider how language mirrors thoughts and emotions
(Alcalá-López etal., 2018, 2019 for the perspective of neuroscience;
Lin et al., 2018; Hinterwimmer, 2019). For ecient discourse
management, they need to understand verbal and non-verbal
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cues—including linguistic expressions, tone of voice, facial
expressions, and body posture. Diculties in meta-representationality
can cause discourse management problems, such as misunderstanding
the interlocutor’s intended meaning and purpose. is, in turn, can
result in communication failures, including miscommunication, lack
of coherence in replies, and misuse of expressions. For instance, the
sentence ‘the cello player wants to impress the critic’ conveys the cello
player’s desire for approval. In this case, meta-representation also
prompts the readers and listeners to activate the meaning of the
gurative expression ‘asleep at the wheel’. In (1c), meta-representations,
by means of which wemodel the inner experience or the mental
phenomena of another person, enable the readers and listeners to
understand the emotional and cognitive states of the cello player
(Baron-Cohen etal., 1985; Frith and Frith, 1999; Frith, 2012; Gallagher
etal., 2002; Newen and Vogeley, 2003 for psychopathology). ey
recognize that the cello player’s disappointment is linked to the critic’s
absent-mindedness (i.e., ‘asleep at the wheel’).
ese components – dynamicity, predictability, meta-
representationality– are not entirely independent or orthogonal;
rather, they function together to facilitate discourse management.
During the interaction of these three components, several cognitive
processes are assumed to underlie these functions on a cognitive level
(see 2.2 & 3 below). Working Memory (WM) and Executive Functions
(EFs) are involved in both dynamicity and predictability (see the
predictive capacity of WM in Baddeley, 2022; Rönnberg etal., 2022a,
2022b). WM covers various memory types, including short-and long-
term, explicit, implicit, episodic, and visuospatial memory and
contributes to active retention (Baddeley, 2000, 2012). EFs
1
are
essential abilities to control one’s attention updating and suppress
irrelevant information to keep track of entities (executive attention in
Engle, 2018; attentional control mechanism in Miyake etal., 2000).
Specically, the roles of WM and EFs in prediction and postdiction
(i.e., including inference-making and repair) are supported by the case
studies from cognitive hearing science (Rönnberg et al., 2021).
Mismatches between predictions and linguistic inputs trigger
postdictions, enabling further access to WM (e.g., long term memory)
(Rönnberg etal., 2021).
Social cognition is an empirical indicator of meta-
representationality. With this in mind, it is based on perspective
taking, theory of mind (ToM), empathy, language prociency, and
language experience. e use and development of social cognition is
typically explicit and reliant on WM and EFs (Carlson etal., 2002;
Truscott and Smith, 2022), as well as language experience.
Representations of social cognition, which involve the coactivation of
associated representations or “schemas,” are closely related to WM
(Truscott and Smith, 2022). Moreover, the combination of inhibition
and WM is central to the relation between EFs and ToM. is is
supported by studies on developmental trajectories and interrelations
between EFs and ToM (Carlson etal., 2002, 2004), reviews of the
relation between EFs and ToM (Pineda-Alhucema etal., 2018), and
1 EF also plays a crucial role in connecting or facilitating communication
between the frontal lobes and the long-term memory systems-specifically
those involved in language comprehension and production (Coolidge and
Wynn, 2022).
research on the relation between EFs, ToM, and autism (Hemmers
etal., 2022).
Language experience also facilitates the interpretation of linguistic
and subtle social cues, such as implicatures or prosody, which are
essential for inferring emotions and intentions. Some individuals
perform well with respect to these cognitive functions including social
cognition capacities, while others may struggle, leading to individual
dierences in discourse management. Several psychometric tests (e.g.,
complex span task for working memory; the Hick task for processing
speed) are used to measure these cognitive functions and social
cognition capacities (We discuss these in section 2.). erefore,
we propose that discourse management can be assessed by
psychometric tests addressing cognitive functions. In the next section
weprovide a summary of commonly used psychometric tests for
assessing individual dierences related to the components of the
discourse management proposed above.
2 Cognitive factors in discourse
management
As was discussed in the introduction, the following cognitive
functions and social cognition abilities are essential to ensure coherent
and contextually relevant discourse management:
(a) Working memory (WM), which allows for the storage and
manipulation of information within the mental workspace
while working on other levels of the discourse model (i.e.,
essential for dynamicity, predictability, &
meta-representationality).
(b) Executive functions (EFs), which facilitate the inhibition,
updating, and shiing of information (i.e., critical for
dynamicity, predictability, & meta-representationality).
(c) Social cognition, which involves the mental representation of
others’ minds and the social aspects of discourse and which is
closely related to language experience, including language and
reading prociency (i.e., critical for dynamicity, predictability,
& meta- representationality).
Variations in any of these cognitive functions can lead to
individual dierences in discourse management and processing across
spoken and written modalities. In the following section, wepresent
frequently used psychometric tests in sub-domains of linguistics,
designed to measure the critical components of our discourse model.
2.1 Dynamicity and predictability
As seen in Example (1) above, eective discourse management
necessitates dynamicity, which requires the active processing of
incoming information, integrating it with existing knowledge, and
tracking linguistic cues within discourse. is dynamic process is
facilitated by WM, which holds and updates information, and EFs,
which maintains attention on unfolding information. Predictability
plays a crucial role in this process, allowing individuals to predict
upcoming information or events based on the current context and
prior knowledge. Continuously generating predictions about what
might come next guides attention, suppresses irrelevant information,
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facilitates comprehension, and lls in gaps in the discourse [see review
on measuring individual dierences in WM and attentional control
and their contribution to language comprehension in Burgoyne etal.
(2022)]. Following Frischkorn etal. (2022), weview EFs as cognitive
processes related to attention during goal-oriented processing,
subdivided into three subsequent categories: inhibition, shiing, and
updating. By making predictions, recalling/holding previously
mentioned information in WM, and updating these predictions
through EFs, individuals make inferences and adjust their discourse
representations accordingly. erefore, WM and EFs are essential for
handling the dynamic nature of discourse management and making
accurate predictions during communication. In addition to WM and
EFs, processing speed signicantly inuences individual dierences
in dynamic discourse, representation and prediction (Huettig, 2015;
Huettig and Janse, 2016). Faster processing allows for quicker
integration of new information and more accurate predictions, while
slower processing may hinder the ability to update and generate
accurate predictions. Below, weprovide an overview of frequently
used psychometric measures.
As mentioned earlier, working memory capacity (WMC) is
associated with various cognitive skills, including attention,
concentration, and cognitive exibility. e most frequently used
instrument for estimating WMC is the family of so-called complex
span tasks (Daneman and Carpenter, 1980; Turner and Engle, 1989;
Engle etal., 1992; Oberauer etal., 2000; Miyake etal., 2001; Wilhelm
etal., 2013). A widely used alternative complex span task, which
requires storage and recall of stimulus items and includes an additional
processing task, is the reading span task introduced by Daneman and
Carpenter (1980). e task is sometimes criticized for its similarity to
reading comprehension (see Daneman and Hannon for further
discussions). Subsequent research adapted the original reading span
task and developed dierent versions (LaPointe and Engle, 1990;
Whitney etal., 2001; van den Noort etal., 2008).
Other WMC paradigms that entail both storage and processing
include an n-back task and a running memory span task (Kirchner,
1958). In the n-back task, participants are presented with a sequence
of stimuli for which they must indicate whether the current stimulus
in the sequence matches a stimulus that was presented n times back.
Similarly, in a running memory span task, participants are presented
with a list consisting of an unpredictable number of items. As soon as
the list ends, participants must recall items from the end of the list.
Both paradigms require an ability to maintain and continuously
update information in WM. In a recent fMRI study, the n-back task
has been used to examine the general feature of brain processing for
predictions of upcoming events (e.g., see studies that examine WMC
for predictions with individuals with hearing loss in Rönnberg etal.,
2013, 2022a, 2022b; Sörqvist etal., 2016). In addition to WMC,
measuring executive processes appears to bean important tool in
understanding individual behavior in discourse management. For this
purpose, commonly used tasks in experimental psychology are the
Stroop task (Stroop, 1935), the Flanker task (Eriksen and Eriksen,
1974), and the Simon task (Simon etal., 1981). All these standard tasks
assess how conicting information inuences both response choice
and response speed. While the Stroop task is assumed to becross-
linguistically valid (Matthews etal., 2018), the Stroop and Flanker
measures, in particular, do not appear to becorrelated (Hedge etal.,
2018). In addition, the Stroop and Flanker inhibition tasks might
be unrelated due to low correlations in larger datasets and thus
contradicting the concept of a unied account (Rouder and Haaf,
2019) (see potential analyses in 4.1 below).
Processing speed signicantly inuences individual dierences in
discourse management. As discussed in Frischkorn etal. (2022), the
term “processing speed” is quite diverse as it can refer to mental speed,
information processing speed as well as attention speed. However,
there is consensus that processing speed is essential to better
understand individual dierences. Commonly used tasks that attempt
to measure processing speed include the Hick, the Sternberg, and the
Odd-Man-Out paradigms (Hick, 1952; Sternberg, 1969; Frearson and
Eysenck, 1986), and the Letter and Pattern Comparison tasks
(Salthouse, 1991; Salthouse and Babcock, 1991).
2.2 Meta-representationality
e meta-representationality in discourse management can
be assessed through measures of social cognition, language
prociency, and reading prociency. Below, weprovide an overview
of psychometric measures to evaluate these capacities.
2.2.1 Social cognition
We should note that there are more psychometric measures on
social cognition (Msika etal., 2024) but we, here, refer to the ones
broadly used in linguistic studies. In research on pragmatic abilities,
individual measures of social cognition have garnered increasing
attention since they may reect eory of Mind, or perspective taking,
capacity and social reasoning impacting discourse management and
the processing of speaker’s meaning. For instance, the Autism
Spectrum Quotient Questionnaire (AQ) (Baron-Cohen etal., 2001b)
is a self-assessment questionnaire measuring autistic traits in adults.
It consists of ve subscales that assess communication skills, social
skills, imagination, attention to local detail, and capacity to switch
attention. e communication subscale taps into pragmatic abilities
directly. Some examples of the items from this subscale are “Other
people frequently tell me that what Ihave said is impolite, even though
Ithink it is polite,” “I nd it hard to ‘read between the lines’ when
someone is talking to me,” and “I amoen the last to understand the
point of a joke.” e score on the overall test– or sometimes just a
subscale score– has been used to account for individual variation
(Bishop, 2012). Although originally developed as screening tool for
the detection of autism spectrum disorder, the AQ has been used in
the recent past to measure communicative abilities with the
understanding that autism can serve as a model disturbance for social
cognition. e AQ communication subscale and measures are related
to the Reading the Mind in the Eyes Test (Baron-Cohen etal., 2001a).
Two personality-related measurements assess empathy (e.g.,
Interpersonal Reactivity Index [IRI] by Davis, 1980, Empathy Quotient
by Baron-Cohen and Wheelwright, 2004). For example, the IRI
includes four sub-scales—perspective taking, fantasy, emphatic
concern, and personal distress—on which participants rate themselves.
2.2.2 Language proficiency
Language prociency tests evaluate an individual’s language
experience to process linguistic cues in discourse. When including
dierent groups of speakers/listeners in studies on language processing
(adults and children with dierent linguistic proles, e.g., speaking the
language as their rst or a second language, literate or illiterate, etc.),
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there will likely beconsiderable variation, attributable to dierent
levels of prociency in the language (Tremblay, 2011; Park etal., 2022).
As wewill discuss in Section 3.1.3, prociency may also beconnected
to the use of one language across dierent contexts over time.
Crucially, language prociency may aect a speaker’s ability to develop
meta-representations of related to the form and function of linguistic
units used in discourse (Karmilo-Smith, 1992). Such representations
are essential for eectively managing the components of discourse
management. Where prociency-based individual variation is itself
under investigation, researchers should use standardized tests and
consider using several dierent prociency measures.
It is outside the scope of this article to review the many dierent
ways of assessing prociency, as well as advantages and disadvantages
of these methods (for reviews of prociency reporting practices, see
Tremblay, 2011; Hulstijn, 2012; Park etal., 2022). Here we briey
present three commonly used prociency measures suitable for
psycholinguistic research because of their availability, ease of
administration, and validity. It should benoted that these tests may
be more reective of reading prociency than oral prociency;
researchers should consider other prociency measures such as
Elicited Imitation if oral prociency is relevant (Torregrossa etal.,
2024). LexTALE represents a test designed to measure vocabulary
knowledge and general prociency in advanced leaners (Lemhöfer
and Broersma, 2012). Participants are presented with words and
non-words one by one and they must make an untimed lexical
decision (e.g., Is this a word in language x or not?). While the test was
originally designed and validated for English (Lemhöfer and
Broersma, 2012), Dutch, German and French versions are also
available (see lextale.com for German and Dutch, and Brysbaert,
2013).e advantages of LexTALE are that it is quick to administer,
freely available, validated (English version), and pre-programmed for
several experimental soware programs. While LexTALE appears to
tap lexical knowledge and speed of lexical retrieval, test scores map
well onto more standardized general prociency test results. In
addition, LexTALE scores have been shown to correlate with
knowledge of discourse phenomena (Wetzel etal., 2020).
In a Cloze test, participants are given a text that contains one-word
gaps and the task is to correctly ll in the gaps. Carefully designed
Cloze tests are thought to reect morphosyntactic, lexical and
discourse competencies (Tremblay, 2011). Cloze tests have many of
the same advantages as LexTALE: quick and easy to administer, and
freely available in several languages including Arabic, Bengali, English,
German, Dutch, Japanese, Korean, Turkish, French, Portuguese, and
Spanish (Norris, 2018). e disadvantage of a Cloze test is text
complexity. In addition, researchers should ensure tests are appropriate
for the precise population they wish to test and validate against
standardized prociency tests (Tremblay and Garrison, 2010;
Norris, 2018).
ough criticized for its subjectivity and lack of independent
verication (Hulstijn, 2012; Park et al., 2022), self-reports of
prociency are widely used in psycholinguistic studies where
prociency is not part of the main research question. Participants are
usually asked to rate their second language (L2) prociency in four
areas: reading, writing, speaking, and listening. Ratings are usually on
a 5, 7, or 10-point scale. ere is evidence that participants are good
at estimating their own prociency and that self-reported prociency
correlates well with standardized prociency tests (Ross, 1998; Marian
etal., 2007; Lemhöfer and Broersma, 2012).
2.2.3 Reading proficiency
Reading prociency tests are used to evaluate an individual’s
ability to understand and interpret texts. While these tests primarily
focus on reading comprehension skills, they can also provide insights
into a person’s capacity to consider an interlocutor’s perspective in
discourse. Eective reading comprehension oen requires readers to
infer authors’ intentions, understand characters’ perspectives, and
grasp underlying themes.
A number of studies converge on a set of individual dierences or
latent factors that inuence reading comprehension success. For
instance, Ahmed et al. (2016) demonstrated that knowledge and
vocabulary contribute indirectly to reading comprehension through
inferencing. Follmer and Sperling (2018) showed the role of EFs in
processing of referential cohesion. While shiing predicted reading
comprehension for lower cohesion, updating was essential for higher
cohesion. Notably, metacognitive monitoring and reading strategies
contributed to reading comprehension. Kulesz etal. (2016) highlighted
vocabulary and background knowledge as dominant predictors of
comprehension, with genre emerging as the most inuential text
feature, whereas other skills like word reading, reading uency, and
working memory, were less signicant in accounting for reading
comprehension. ese studies highlight the critical roles of vocabulary,
background knowledge, and inferential reasoning in reading
comprehension, while emphaszing the need to consider text demands
and reader-specic skills (e.g., see Perfetti and Stafura (2013) for an
over-arching theoretical syntheses of ndings on individual dierences
in reading).
While reading comprehension is inuenced by these higher-level
cognitive processes, reading prociency also encompasses low-level
skills, such as word decoding (e.g., Hamilton etal., 2016) and visual
word recognition (Yap et al., 2011). It entails integrating new
information with existing knowledge, predicting upcoming
information or events based on context, and constructing and
updating discourse representations (see Tighe and Schatschneider,
2016 for a review). Some decoding tasks include (1) a Phonological
Decision Task (Bell and Perfetti, 1994); (2) Non-word Naming Task
(Bell and Perfetti, 1994); and (3) Orthographic Decision Task (e.g.,
DEAL vs. DEEL) (Bell and Perfetti, 1994). While reading prociency
may aect reading speed and word identication, it also reects upon
a more general (medium-independent) capacity relating to discourse
management, enabling individuals to navigate complex
communicative interactions successfully.
In psycholinguistics, reading prociency is further assessed
through standardized tests that probe vocabulary knowledge and
reading comprehension, such as the Nelson Denny Reading Test
(Brown, 1960; Nelson, 1991), which consists of a multi-choice
vocabulary and a reading comprehension test. In addition, print
exposure measures such as the Author Recognition Test (ART)
(Stanovich and West, 1989) are used to investigate individual
dierences in reading experience (Acheson etal., 2008; Arnold
etal., 2018; Johnson and Arnold, 2021; Langlois and Arnold, 2020;
Scholman etal., 2020; Wetzel etal., 2020; Zuerey and Gygax, 2020).
In the ART, participants are shown a list of real and fake (i.e., foils)
author names and are asked to identify the author names they
recognize. Participants earn one point for every real author they
tick, and one point is deducted for every foil ticked. e inclusion
of foils provides additional validity to the test because participants
cannot simply obtain a high score by ticking every author. e
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original version contained 50 authors and 50 foils. e ART serves
as a proxy for print exposure, providing an indirect measure of how
much participants read. While print exposure is correlated with
reading prociency, it is more specically a measure of reading
experience rather than a direct measure of prociency. Print
exposure has been shown to correlate with lower level (word
recognition) and higher level (vocabulary knowledge, reading
comprehension) reading skills (Mol and Bus, 2011; Moore and
Gordon, 2015).
Obviously, the author list must becurrent and relevant to the
target participant group, which is why the test is oen adapted to the
area of study. is has resulted in a proliferation of test versions (e.g.,
Acheson etal., 2008; Martin-Chang and Gould, 2008; Moore and
Gordon, 2015), including versions targeting particular age- and
language-groups (e.g., Cunningham and Stanovich, 1990; Grolig etal.,
2017, 2020; Schroeder et al., 2016; Zuerey and Gygax, 2020). In
addition, author names are oen taken from recent bestseller lists for
a particular region. Compared to more standardized cognitive tests,
this tailoring of the ART to a participant group may make comparison
of performance across studies challenging.
3 Case studies in discourse
management
e studies in this section provide insights into why it is essential
to assess the components of discourse management (i.e., dynamicity,
predictability, and meta-representationality) with psychometric
measures addressing cognitive functions (i.e., WM, EFs) and social
cognition capacities.
3.1 Individual dierences in prosody for
discourse management
We review some recent ndings from prosodic prominence to
illustrate individual dierences across dierent domains and
modalities, emphasizing their role in dynamicity, predictability, and
meta-representationality in discourse management. To begin with,
speakers choose dierent prosodic means to signal dierent speech
acts (Repp, 2020; Repp and Seeliger, 2020; Seeliger and Repp, 2023).
For instance, prosodic prominence marking can dynamically signal
specic elements in discourse, such as the verb participle in (2a) or the
subject d-pronoun “der” in (2b), to mark the speech acts question and
exclamation, respectively.
(2)
(a) Question speech act—accent on the verb participle:
Hat der geSCHRIen? (Has hescreamed?)
(b) Exclamations—accent on der/he: Hat DER geschrien!
((Boy), did hescream!) (Repp and Seeliger, 2020, p.1).
ese ndings highlight the dynamicity of prosodic prominence
as speakers adaptively make choices in discourse. In addition,
production studies reveal that the placement of the so-called
exclamative accent, which is a speech-act-specic prominent accent
whose placement is fairly independent of information structure, like
the accent on the subject d-pronoun “der” in (2b), is
individual-specic. While some speakers consistently accent the
pronoun “der,” while others consistently accent the nite verb “hat”
(Repp and Seeliger, 2020). Such individual-specic patterns highlight
the dynamic nature of prosodic prominence marking in discourse.
us, interlocutors need to predict such prosodic prominence markers
and update their representation to ensure coherent discourse.
Having examined production variability in exclamatives, wenow
turn to rejecting questions, which further underscore the interplay of
dynamicity, predictability, and meta-representationality. Similarly,
inter-individual dierences in prosodic prominence marking are also
evident in rejecting questions in German. Rejecting questions are
questions that speakers use to express their disbelief in something the
contextual evidence suggests (English: “Surely, youdo not want to steal
this paper”). Production studies show that speakers dier in their
preferences for rising vs. falling contours for these questions (Repp and
Seeliger, 2020). is variability demonstrates how speakers dynamically
adapt prosodic prominence marking to signal pragmatic meaning. At
the intra-individual-level, speakers exhibit considerable variability,
which does not seem to depend on particular discourse contexts (Repp
and Seeliger, 2020). Since such variability does not align with discourse
context, the role of meta-representationality and dynamicity in
prosodic prominence production becomes essential for managing
discourse successfully. Further research is needed to understand the
cognitive and meta-representation reasons behind such variations, as
well as how these variations impact discourse management.
Compared with production, less is known about how individual
dierences aect the perception of prosodic prominence, though
emerging evidence strongly implicates socio-cognitive abilities. Much
of what weknow so far has come from work exploring the role of
social cognition capacities in various perception or comprehension-
related tasks involving prosodic manipulations. For example, Bishop
(2012, 2017) found that listeners with higher scores on the AQ (a
socio-cognitive measure previously mentioned above), show weaker
sensitivity to prosodic prominence patterns in tasks requiring
predictability of prosodic cues, such as a cross-modal lexical decision
task. Importantly, sensitivity is not related to overall AQ scores but to
subscale scores targeting communication (the communication
subscale), pointing to a nuanced link between socio-cognitive
abilities and prosodic processing. is suggests that listeners’ meta-
representational abilities—such as the capacity to integrate prosodic
cues into higher-order social reasoning—might play a central role in
prosodic perception. In subsequent work, the AQ communication
subscale and measures closely related to it—such as the Reading the
Mind in the Eyes Test (Baron-Cohen etal., 2001a). e pragmatic
language subscale of the Broad Autism Phenotype Questionnaire
(Hurley etal., 2007)—have also been shown to predict sensitivity to
prominence patterns in tasks in which listeners must explicitly rate
or identify prominence in auditory stimuli (Bishop, 2016; Bishop
etal., 2020) or use it to recover information structure for sentence
completion (Hurley and Bishop, 2016). Notably, listeners exhibit
dierential sensitivity depending on social cognition measures,
pointing to the role of social cognition abilities in
discourse management.
Moreover, in two studies designed to prime prosodic structure
(analogous to syntactic priming), Jun and Bishop (2015a, 2015b)
argue that individuals with more autistic-like or weaker
communication skills exhibit less robust implicit representations of
prosodic prominence (i.e., subvocal) during silent reading. Such
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social-cognitive decits results in weaker meta-representationality of
discourse management, which impacts individuals’ ability to predict,
adapt, and manage discourse eectively.
ese ndings underscore the importance of considering
individual dierences in socio-cognitive abilities when examining
prosodic prominence in discourse management. erefore, several
empirical ndings indicate that scores on measures like the AQ
communication subscale can predict some of the variation listeners
exhibit in response to prosodic prominence patterns in spoken, and
perhaps even internally-generated utterances. At present, however,
it remains unclear just what aspect of social cognition these
measures reect. We assume that this is related to a decit in
implicit social cognition that is used during ongoing conversations,
whereas in oine studies without personal participation (e.g.,
written language), persons with ASD can eectively participate in
and manage activities (Zimmermann etal., 2021).
Interestingly, and possibly consistent with this interpretation,
Jouravlev et al. (2020) present fMRI data that show AQ
communication scores (but not scores on the other subscales of the
AQ) are associated with less hemispheric lateralization during
neurotypical language processing in the direction of increased right
hemisphere activity. As wediscuss further below, our understanding
of this sort of variation will benet from the employment of more
rigorous psychometric methodologies. Tentative evidence pointing
in this direction includes recent studies showing that measures of
empathy—a construct broadly related to perspective taking but
arguably distinct from ToM—also seem to predict variation in
sensitivity to prosody and intonation (Esteve-Gibert etal., 2020;
Orrico and D’Imperio, 2020; Arvaniti etal., 2022). Above all, the
ndings suggest that a dierent, or perhaps more general socio-
cognitive construct, might in fact bethe relevant one. Whatever the
correct circumscription of this relationship between social
cognition and sensitivity to prosody turns out to be, understanding
the implications for inter-individual variation in discourse
representation and management will bean important task.
Finally, in conversational interactions, melodic speech patterns
and backchannels further reveal the role of socio-cognitive abilities
in discourse management. For example, in a corpus with Autism
Spectrum Disorder (ASD) speakers, most speakers produced a
more melodic intonation style than non-autistic speakers (Wehrle
etal., 2022). In another production study on backchannels (e.g.,
“mmhm, okay”), many ASD speakers produced rising intonation
contours regardless of the backchannel type, indicating a less
exible mapping of intonation contours to backchannel type
(Wehrle etal., 2024b). e ASD group also produced fewer of the
expected level contours on lled pauses (e.g., “uhm”), although once
again this pattern did not hold true for all speakers (Wehrle etal.,
2024a). ese studies point to the importance of inter-individual
variability in clinical groups such as speakers with autism (Bishop,
2012, 2017; Grice etal., 2016; Grice etal., 2023; Wehrle, 2023).
ese ndings suggest that individuals with dierent socio-
cognitive proles may exhibit varying sensitivities to melodic
speech patterns and backchannels, impacting their ability to predict
and interpret discourse dynamicity eectively.
In summary, studies on individual dierences in prosodic
prominence marking, melodic speech patterns, and backchannels
highlight how components of discourse management interact with
cognitive and social abilities.
3.2 Individual dierences in discourse
comprehension
Referentiality plays a critical role in discourse management,
bridging non-verbal cognitive and linguistic skills to facilitate
communication. Anaphoric expressions, such as pronouns in sentence
comprehension, engage processes related to dynamicity, predictability,
and meta-representationality.
Anaphoric expressions require continual updating of mental
representations as new information becomes available, enabling
readers to anticipate upcoming text based on syntactic constructions.
For instance, resumptive pronouns (RPs) are pronouns that appear in
a position where a gap would normally bepredicted, as the italicized
RP it in (3a).2 Constructions that block a dependency between a gap
and an extracted entity are referred to as islands.
(3)
(a) RP in the non-island condition: Jane liked the magazine
that the hairdresser had talked about it before going to the salon.
(b) RP in the island condition: Jane liked the magazine that
the hairdresser [RC who had talked about it before going to the
salon] bought (Çokal and Sturt, 2022).
e reader promptly establishes a gap in (3a) right aer the
embedded verb (such as “talked about”), creating a dependency
with the so-called ller “that.” However, when the explicit direct
object (such as it) is encountered in the input, it conicts with
initial prediction, resulting in a disruption in processing, which
leads to a dynamic updating of discourse representation to resolve
the conict. Moreover, dependency formation is sensitive to islands
and thus a lled gap eect is not observed in (3b), where the RP it
appears inside a strong island (i.e., relative clause). In two
eye-tracking reading experiments, Çokal and Sturt (2017)
demonstrate that ller-gap dependency formation interacts with
individual reading skills, which were measured using the Nelson-
Denny Reading Test (Brown, 1960). e interaction pattern shows
that high-skilled readers’ total reading times increase in the
non-island condition in (3b) compared to low-skilled readers.
Low-skilled readers’ processing times for non-island condition in
(3a) and island condition in (3b) do not dier. e fact that
low-skilled readers’ reading times do not dier across conditions
suggests that maintaining multiple interpretations is less robust in
individuals with lower reading prociency. While Çokal and Sturt’s
(2017) study shows a relationship between reading prociency and
ller-gap dependency formation in islandhood conditions, the
intricate relationship between processing of RPs and cognitive
functions (particularly WM & EFs) has not yet been investigated.
Further research is needed to understand whether the observed
processing disadvantage for pronouns in island congurations
implies that individuals with higher WM and EFs may beable to
predict syntactic complexity and maintain referential dependencies
across clause boundaries.
2 In fact, they are ungrammatical in English, but some studies have shown
that they can facilitate sentence comprehension (Beltrama and Xiang, 2016)
and thus their acceptability (Hofmeister and Norclie, 2013).
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While Çokal and Sturt highlight the role of individual reading
skills in processing syntactic dependencies, other studies explore how
print exposure inuences the predictability and dynamicity of
referential prominence at the discourse level. Arnold etal. (2018)
investigate ambiguous pronoun processing and its relationship to
print exposure (measured by the ART). is study found a higher
ART score correlated with a higher subject-bias for ambiguous
pronoun comprehension in English but not WM and
ToM. Importantly, Arnold etal. (2018) propose that increased print
exposure strengthens participants’ prediction about which referents
(e.g., subjects versus objects) are likely to bere-mentioned. is ability
reects a dynamic process of updating mental representations, as
individuals must maintain a strong candidate referent for ambiguous
pronouns while simultaneously suppressing irrelevant ones. e study
by Arnold et al. (2018) suggests the interplay between dynamicity,
predictability and EFs, showing how print exposure enhances readers’
ability to anticipate referents and suppress irrelevant candidates.
However, to our best knowledge, Arnold etal. have not tested the role
of executive functions (EFs) in the processing of ambiguous pronouns.
Examining the interaction between EFs and print exposure could shed
further light on how individuals dynamically manage and predict
referential candidates in larger discourse contexts. is remains an
important avenue for future research.
e role of cognitive functions is further supported by
electrophysiological evidence, which underscores individual
dierences in processing ambiguous pronouns. Individual dierences
with respect to ambiguous pronouns (e.g., “Jennifer Lopez told
Madonna that she had too much money.”) have been tested using
ERPs and the Reading Span Task (Nieuwland and Van Berkum, 2006).
While ambiguous pronouns elicit a sustained, frontal negative shi
(Nref) relative to non-ambiguous pronouns at the group-level, the size
of this eect positively correlates with the reading span and contextual
bias. Individuals who are sensitive to ambiguous pronouns have
higher reading skills than low skilled readers. is seems to indicate
that high-span readers demonstrate greater dynamicity in anticipating
and maintaining ambiguous referents, while low-span readers adopt
the most plausible interpretation immediately, reecting weaker
dynamicity and predictability. ese ndings provide neurocognitive
evidence for the interaction between WM and components of
discourse management (i.e., dynamicity and predictability) in
processing referential expressions.
To understand how cognitive functions and social cognition
abilities inuence referential resolution, Vogelzang et al. (2021)
present a computational model. Vogelzang etal. (2021) modeled
individual dierences using the Cognitive Architecture-Adaptive
Control of ought-Rational Model (ACT-R Model) (Anderson and
Anderson, 2007). eir ndings specically demonstrate that eective
discourse management involves understanding the perspectives and
intentions of others, as well as incorporating dynamicity and
predictability. In Italian– the language considered by the authors—
null pronouns are used to refer to a prominent entity in the previous
discourse, signalling topic continuation, whereas overt pronouns are
used to refer to a less prominent entity, indicating a shi of topic from
a prominent to a less prominent entity. Individual dierences in
processing of pronouns have been observed in both children and
adults. With this in mind, Vogelzang et al. (2021) simulate the
processing of pronouns by adults. Vogelzang etal. (2021) add high
WM load to their model as an additional component through a
spreading mechanism. us, the selection of discourse topic is
predicted to be inuenced by WMC. Based on this framework,
Vogelzang et al. (2021) model adults’ processing of null/overt
pronouns, specifying the eects of WMC and processing speed.
According to the default mechanisms of the ACT-R Model, a referent’s
base-level activation is determined by how recently and frequently it
has appeared in the discourse. is activation gradually diminishes
over time but is boosted when the referent reappears. Vogelzang etal.
(2021) formulate hypotheses about children’s processing of pronouns
and then create a simulation for children. According to their model,
null pronoun interpretation is inuenced by WMC, which appears to
depend on the dynamicity of discourse. On the other hand, for adult
processing, overt pronoun interpretation is inuenced by processing
speed, which is related to perspective taking. However, children are
not “adult-like” in their interpretation of null pronouns due to a lack
of perspective taking. eir results demonstrate that discourse
processing is inuenced by WMC, while social cognition capacities
are inuenced by processing speed.
In conclusion, the processing of anaphoric expressions (e.g.,
resumptive pronouns, personal pronouns, null or overt pronouns) is
the interaction between components of discourse management and
cognitive and social abilities. For example, print exposure strengthens
predictability (Arnold et al., 2018), reading prociency or WM
enhances dynamic updating of representations (Çokal and Sturt, 2017;
Nieuwland and Van Berkum, 2006), and processing speed supports
meta-representational strategies like perspective-taking (Vogelzang
etal., 2021). Further investigation is warranted to elucidate the specic
contributions of these cognitive functions to the management of larger
discourse units. Specically, knowledge of the weight of each cognitive
factor in pronoun resolution in a larger discourse context is needed.
3.3 Interspeaker and intraspeaker variation
in bilingual reference management
Bilingual speakers provide a unique perspective for
understanding how components of discourse management interact
with cognitive and social abilities, owing to their variability in
language experience and cognitive and social-cognitive proles
[e.g., working memory (WM), executive functions (EFs), and
theory of mind (ToM)]. Specically, the analysis of bilingual
reference production allows us to examine inter- and intraspeaker
variations in discourse management. Let us consider interspeaker
variation rst. Bilingual speakers may dier with respect to meta-
representationality—specically language experience and ToM
variables. In general, bilinguals may bedominant in one language,
depending on the contexts of language use. Furthermore, bilingual
speakers may vary from each other in their cognitive proles (i.e.,
WM, EFs, mentalizing). e same variation in cognitive proles can
be observed among monolingual speakers. However, bilingual
speakers represent a privileged viewpoint for understanding how
social cognition capacities and cognitive proles interact with each
other in discourse processing, as also observed among monolingual
speakers. For instance, Torregrossa etal. (2021) investigate how
discourse updating skills, language prociency, and their interaction
predict the use of overspecied and underspecied referring
expressions in bilingual children. To achieve this, they analyzed the
narrative production of 125 bilingual Greek children (aged
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7;2–13;1) who spoke Greek as their heritage language and Albanian,
English, or German as their societal languages. e study measured
the frequency of overspecied (full nouns) and underspecied
(null-subjects/clitics) referring expressions, which dier in
ambiguity. e children also completed vocabulary tasks in both
languages and a 2-back task to assess updating skills (a component
of EFs). Parents provided information about language use through
a questionnaire, from which a dominance index was calculated
based on vocabulary scores and language exposure. e study
examined how updating skills, dominance, and their interaction
predicted the use of referring expressions in Greek, with separate
analyses for children dominant in Greek or the societal language.
In Torregrossa etal. (2021), the use of overspecied forms was
predicted by their discourse updating skills: the lower their skills,
the more overspecied forms they produce. is highlights how
cognitive exibility and updating contribute to referential
predictability by allowing children to balance specicity and
ambiguity eectively. For children dominant in the societal
language, language prociency emerges as the primary predictor of
overspecied forms. Interestingly, language combination also
impacts referential strategies: Greek-German children produce
more overspecied forms compared to Greek-Albanian children.
is variation underscores the role of meta-representationality in
integrating linguistic and social experience to manage discourse.
For underspecied forms, the ndings reveal an inverse pattern.
e more balanced the two languages, the more underspecied
forms are produced. is suggests that balanced bilingualism
enhances exibility in choosing referring expressions, reecting the
dynamicity of bilingual discourse management.
A contribution by Torregrossa et al. (2023) relates to the
understanding of intraspeaker variation in bilingual children’s
metalinguistic knowledge concerning the use of referring
expressions in discourse, considering the eect of language mode
(Torregrossa etal., 2023). e study provided the sentences in
three modes: (1) Italian sentences in isolation (one-language mode,
one sentence); (2) Italian sentences paired with their correct
counterparts (one-language mode, two sentences), and (3) Italian
sentences paired with their Greek counterparts (bilingual mode).
e results show that children perform better in the bilingual
mode (Italian alongside Greek), particularly in identifying errors
in referring expressions. is nding highlights the dynamicity in
bilingual discourse management, where the interaction between
two languages enhances meta-representational awareness. e
ability to identify errors more accurately in bilingual contexts
suggests that bilingual children can draw on cross-linguistic cues
to strengthen referential predictability and maintain coherence in
discourse management. is study underscores the role of language
context in shaping meta-representationality related to language use
and discourse management.
By examining inter- and intraspeaker variation, these bilingual
studies reveal how linguistic factors, cognitive function, and social
cognition abilities including language experience shape discourse
management strategies among bilinguals. e ndings emphasize
the following:
• Dynamicity: Bilinguals choose referring expressions based on
cognitive exibility, discourse updating skills, and cross-
linguistic interaction.
• Predictability: Linguistic dominance and prociency strengthen
the ability to predict upcoming discourse, choose correct
referential expressions, and detect referential errors that
mismatch the previous context.
• Meta-representationality: Meta-linguistic awareness and cross-
linguistic comparison enhance the ability to manage errors and
integrate referential strategies dynamically across contexts.
Importantly, these results suggest that discourse management can
beassessed through psychometric tools targeting cognitive function
and social-cognitive abilities.
4 Discussion
It is theoretically meaningful to understand the interplay
between individual dierences in discourse management (i.e.,
dynamicity, predictability, and meta-representationality), cognitive
functions (e.g., WM, EFs), and social cognition capacities, as well
as to examine how individuals’ characteristics interact with
discourse management. However, this research topic has not yet
received enough attention. Nevertheless, a few studies have utilized
psychometric measures to explore this aspect (see section 3.). From
these studies wehave learned: (1) Social cognition abilities and
prosody: Two social cognition measures, namely the sub-scales of
the Autism Quotient (AQ) and measures of empathy, can predict
individual dierences in subjects’ sensitivity to prosodic
prominence patterns in discourse management (Bishop, 2012,
2017); (2) Variability in discourse management among clinical
groups (e.g., ASD speakers): socio-cognitive abilities eect
discourse management by inuencing individuals’ sensitivity to
melodic speech patterns and backchannels. (3) Cognitive
functions, reading prociency and referential ambiguity resolution:
Individuals with greater WM, faster processing speed, and higher
reading skills oen excel in tasks that require them to consider
multiple potential antecedents and rapidly resolve pronoun
ambiguity in a coherent and ecient manner. (4) Social cognition
abilities in children: Children were not “adult-like” in their
interpretation of null pronouns due to a lack of perspective taking.
In addition, processing of null and overt pronouns is inuenced by
WM, while perspective taking is inuenced by processing speed
and ToM. (5) Bilingual meta-representationality: e role of
metalinguistic knowledge in reference production in bilinguals’
discourse, and its relationship with social cognition measures such
as ToM, vocabulary knowledge, and language prociency has been
shown in Torregrossa etal. (2021, 2023). (6) Dynamicity and
predictability in discourse management: Children who are skilled
at updating their mental representation of a sentence as it unfolds
(a skill associated with WM and cognitive exibility) seem to
be able to adapt their language production and discourse
management strategies, avoiding over- or underspecication
(Torregrossa etal., 2021).
In light of these ndings, weclaim that discourse management
can beassessed by psychometric tests addressing cognitive functions.
e interplay between discourse components and cognitive functions
occurs as language and visual input enter the cognition and language
system. Language and visual input activate WM and EFs, which
correspond to each other. e information from these cognitive
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functions combined with language and visual input in discourse is
used to generate predictions about upcoming input. If there is a rapid
match between language/visual input and predictions, then discourse
management is dynamically updated. However, when there is a
mismatch between language/visual input and predictions, postdiction
(including inference-making and repair) commences, which feeds
back into new predictions, creating a dynamic interacting system
(Rönnberg etal., 2013, 2022a, 2022b). ere is also an interaction
between dynamicity and predictability with meta-representationality.
Consequently, postdiction may or may not be successfully
accomplished depending on individuals’ meta-representationality.
With psychometric measures addressing cognitive functions, wecan
identify individuals’ discourse abilities and provide insights into
discourse management.
4.1 Which psychometric measures of
cognitive functions can be used to assess
discourse management?
Our review shows that several psychometric measures have been
used in previous studies on discourse management: WM (e.g.,
complex span tasks, which include some kind of additional mental
task in-between exposure and recall), processing speed, Nelson Denny
Reading Test, Author Recognition Test, Language Prociency Test,
and two social-cognition measures (namely communication-related
sub-scales of measures like the Autism Quotient (AQ) and the Broad
Autism Phenotype Questionnaire, and measures of empathy).
Interestingly, previous studies have not thoroughly explored
the role of EFs (i.e., inhibition). In fact, inhibition– ltering/
suppressing irrelevant thoughts while updating mental
representations, maintaining coherence, making predictions,
logical progression in discourse, and inhibiting one’s own
perspective while focusing on contextual information – is a
fundamental cognitive and social skill that helps individuals
navigate the complexities of discourse management.
We propose that conscientiousness (i.e., one of the basic
personality/processing types in some models of personality types)
might assess individual dierences as the propensity to beself-
controlled, responsible to others, and rule abiding (Roberts etal.,
2009, 2012). e level of perfectionism that individuals might
possess can be linked to their conscientiousness in discourse
management. To our knowledge, such a connection between
perfectionism and discourse management has not yet been
investigated. e perfectionism model of Gaudreau and ompson,
2010; Gaudreau (2013), which has two interacting sub-traits of
perfectionism: (a) personal standards perfectionism (PSP) and (b)
evaluative concerns perfectionism (ECP) can beused to address
this gap (see Drizinsky et al., 2016 for perfectionism-related
variations in behavioral and neurophysiological correlates of error
recognition). Including such measurement in future studies will
serve as a control to demonstrate that the correlation between
cognitive functions– EFs and WM– is not solely attributable to
the general cognitive functions assessed but is also related to
personality traits. In other words, some people might consider a
“good enough” completion of a task to besucient, whereas others
might aim for perfection. us, attitudes can also contribute to
individual variation.
4.2 What challenges arise when testing and
analyzing individual dierences data?
ere are some challenges to consider before conducting a study
on individual dierences in discourse management (cf. Boogert etal.,
2018 for major challenges), during data analysis (Tremblay, 2011), and
when developing and evaluating experiments (Brysbaert, 2024).
Below, wediscuss these challenges (which include inter-correlation
measures and multicollinearity, and sampling concerns) and provide
potential analysis approaches to address them. Weemphasize that
addressing these challenges needs to bedone in future studies.
Many cognitive constructs (e.g., WM, ART, reasoning) are
intercorrelated, complicating the attribution of outcomes to specic
predictors (Dubois etal., 2018; James etal., 2018). High correlations
across tasks can lead to inconsistent ndings (e.g., Martin etal., 2020;
Freed etal., 2017). A major challenge in this context is multicollinearity,
where highly correlated predictors (e.g., WM and ART) complicate
regression analysis (Cohen etal., 2003). Increasing sample size reduces
random noise but does not fully resolve multicollinearity because
correlations between variables oen persist. Alternative approaches
include reducing predictor correlations, combining redundant
predictors, or selecting variables based on theoretical relevance.
Statistical adjustments like ridge regression can help but are
insucient on their own. oughtful variable selection and careful
experimental design are critical to ensuring model clarity and
minimizing multicollinearity (Cohen etal., 2003).
e next challenge is sample size and amount of variation in the
data. If there is a higher level of measurement uncertainty (i.e., more
variability or error in measurements), then more samples will
berequired to achieve reliable results. For instance, if wewant to test
for a correlation between a prominence in discourse management
(such as the “rate of pronouns and full NPs”) and a variable
representing a cognitive construct (such as the “EFs”), there needs to
be enough variation in both variables. However, if the range of
variation across individuals in one or both variables is small—either
because individuals do not actually vary much along the dimension
in question or because the sample size is too small—this would not
allow for a robust test of individual dierences. is limitation might
also result in a type II error (i.e., a false negative). In addition,
traditional approaches have attempted to classify individuals as
“do-ers” (who show an eect) and “do not-ers” (who do not show an
eect) based on individuals’ cognitive processing style and eect (Haaf
and Rouder, 2019; Hedge, 2021). However, Haaf and Rouder (2019)
argue that this classication approach is inadequate. Oversight of such
variability can mask meaningful ndings or anomalies (e.g., spike-
and-slab model below).
Sampling representativeness is oen incongruous with research
goals in individual dierences. For instance, studies on individual
dierences do not focus on obtaining a representative sample of
participants across dierent socio-cognitive proles. Instead, recruited
participants are oen relatively homogeneous—such as easily
accessible participants, monolingual/bilingual speakers of a specic
language, or university students raised in similar linguistic
environments, and exposed to controlled or consistent language input.
Since no single measure can provide a pure and error-free measure
of a construct such as WM, researchers are advised to follow several
strategies. To capture variation between individuals in the use of
components of discourse, it is essential to employ multiple experiment
Çokal et al. 10.3389/fcomm.2025.1448463
Frontiers in Communication 12 frontiersin.org
tasks with a strong theoretical perspective across phonology, discourse
processing, and speech production. en, multiple trials (i.e., test–
retest) should beconducted to examine whether the tasks capture stable
characteristics (see Boogert et al., 2018 for further methodological
issues). It should benoted that there could beadditional sources of error
in a test–retest reliability context due to uctuations in mood, health,
and training eects (Hedge, 2021). Alternatively, instead of multiple
trials, researchers can use multiple measures for each construct to “…
assess the degree of common variance between them and use composite
scores within a construct” (James etal., 2018, p.5). For instance, a
composite score can be created by administering the Stroop task
(Stroop, 1935), the Flanker task (Eriksen and Eriksen, 1974), and/or the
Simon task (Simon etal., 1981) (cf. James et al., 2018 for syntactic
processing). However, Rouder and Haaf (2019) demonstrated that
Stroop and Flanker inhibition tasks seem unrelated and contradict the
unied concept of inhibition (see Friedman and Miyake, 2017 for the
details of unied account). ese ndings highlight the need to critically
assess whether a single task (or multiple tasks for that matter) can
accurately capture individual dierences in discourse management.
To address these challenges, advanced statistical methods like
Structural Equation Modelling (SEM) and Psychometric Network
Modelling are particularly eective. SEM handles inter-correlations
among cognitive functions (e.g., WM, uid intelligence, ART) while
accounting for measurement error and multidimensional relationships
(Schreiber et al., 2006; Marsh et al., 2014). On the other hand,
Psychometric Network Modelling (Goring etal., 2021; Kovacs and
Conway, 2016) conceptualizes cognitive abilities as networks of
interconnected processes rather than latent variables. Observed
variables are nodes, with partial correlations modeled as edges. is
isolates direct relationships while ltering out shared variance, providing
a modern alternative to latent variable approaches.
To avoid oversimplied classications (e.g., “do-ers” vs. “do
not-ers”), Vogelzang and Torregrossa etal. (2024) also propose cluster
analysis to identify behavioral proles, which are then compared on
cognitive and linguistic dimensions. e spike-and-slab model (Haaf
and Rouder, 2019) further renes this by identifying mixtures of eects
(e.g., “some do, some do not”) and determining whether tasks capture
a single dimension or distinct processes. To deal with eect sizes within
tasks, correlations of these eects across tasks, and noise from nite
trials (i.e., trial noise), Rouder and Haaf (2019) propose hierarchical
models (see Bayes Factor). is is necessary when aggregating scores
across trials for individuals introduces trial-level noise, which
contaminates measures like eect size, reliability, and correlation,
resulting in articially low values. is method provides cleaner
estimates of individual performance and enables robust evaluation of
correlations between tasks. All these statistical methods highlight the
need for careful experimental design (e.g., many trials per condition) to
accurately measure and interpret individual dierences.
As seen above, the way data is modelled (e.g., using a specic
statistical model) can impact the interpretation of relationships between
measures (see conict in modelling in Freed etal., 2017; Goring etal.,
2021). It should bekept in mind that dierent modelling approaches can
lead to dierent theoretical conclusions about cognitive functions
(Goring etal., 2021). However, computational models generally require
participant numbers in the hundreds rather than the dozens. Unlike
mixed-eects regression, these methods help researchers avoid suering
from multicollinearity among independent variables, allowing for a
better understanding of the associations between cognitive functions
and discourse management. To address some of these challenges,
researchers have begun conducting multi-lab studies to tackle
diculties related to replication and methodological issues (e.g.,
manybabies: https://manybabies.org/).
4.3 How critical are the challenges to the
validity of the case studies reported above?
e challenges outlined in section 3 will be considered here in
relation to their potential impact on the validity of the case studies
reported above, as well as future research directions. Construct validity
in the case studies is ensured through the use of psychometric measures
targeting well-dened components of discourse, such as WM, EF, and
social cognition capacities. It should benoted that while the challenges
highlight areas for improvement, they do not invalidate the claims
themselves. Instead, they underscore the need for continued
methodological renement and replication of results.
As discussed in section 4.2, while inter-correlation and
multicollinearity between psychometric measures oen pose challenges
by leading to redundant predictors and reducing interpretability, these
issues may beless critical for many of the case studies discussed here.
Most of these case studies utilize only a single psychometric measure to
link a specic cognitive construct to discourse management. For
instance, the Nelson Denny Test in Çokal and Sturt (2017) assesses
reading skills, the Reading Span Task in Nieuwland and Van Berkum
(2006) measures WMC, while socio-cognitive measures– such as the
AQ (Bishop, 2012; Bishop, 2017) and the Broad Autism Phenotype
Questionnaire (Bishop, 2016; Bishop et al., 2020)—examine social
cognition capacities. e use of a single psychometric measure in these
studies minimizes the risk of overlapping variance between multiple
predictors within the same analysis, thereby simplifying interpretability
and reducing concerns about inter-correlation and multicollinearity.
However, multicollinearity can arise if two or more independent
variables in a model share a signicant amount of variance, potentially
obscuring their unique contributions. is challenge is particularly
relevant in studies employing multiple psychometric measures, such as
Arnold etal. (2018) and Vogelzang etal. (2021). In Arnold etal. (2018),
the predictors (e.g., WMC, ToM, & ART) did not correlate. erefore,
intercorrelation might not bean issue. It is important to note that this
review article is not a meta-analysis but rather a discussion of individual
case studies to highlight that discourse management can beassessed by
psychometric tests addressing cognitive functions.
In turn, it should benoted that sample size and amount of variation
in the data could critically inuence the validity of the case studies
discussed above. For instance, prosody studies wereported above involve
sample sizes ranging between 84 and 160 participants (e.g., Bishop, 2012;
Bishop, 2016; Bishop etal., 2020; Hurley and Bishop, 2016; Jun and
Bishop, 2015a, 2015b). Lab-based experiments, such as those utilizing
EEG or eye-tracking, oen include smaller sample sizes, ranging from
31 to 40 participants (e.g., Nieuwland and Van Berkum, 2006; Çokal and
Sturt, 2017), with exceptions such as Arnold et al. (2018) involving 72
and 60 participants, and Torregrossa etal. (2021), which examined 125
bilingual Greek children. Similarly, clinical studies frequently rely on
small participant groups due to the specicity of their inclusion criteria
(Grice etal., 2016; Wehrle, 2023; Wehrle etal., 2024a). ese sample size
constraints are oen related to the requirements of such studies, which
involve recruiting participants who meet precise criteria and
Çokal et al. 10.3389/fcomm.2025.1448463
Frontiers in Communication 13 frontiersin.org
compensating them for their time. While small sample sizes and
constrained variation can reduce studies’ generalizability, such challenges
may be less critical for studies with robust designs. For example,
two-by-two designs, as employed by Nieuwland and Van Berkum (2006)
and Çokal and Sturt (2017), allow for more controlled comparisons,
mitigating issues of variability in the data. is suggests that while sample
size and variability may impact generalizability, the methodological rigor
of specic studies can somewhat oset these challenges.
e representativeness of the samples depends on the specic
purpose of each study. e reported case studies predominantly include
university students, which limits the generalizability of ndings to
populations with dierent socio-cognitive proles. Similarly, clinical
studies oen focus on a specic group (e.g., high-functioning individuals
with ASD), whose recruitment and accessibility present challenges
compared to more commonly studied groups, such as native speakers in
phonological experiments. Furthermore, studies involving bilingual
participants tend to target specic language pairs aligned with the
research goals. While representativeness is less critical for the current
focus of this review (i.e., proposing the groundwork for the intricacies of
discourse management and its relationship to cognitive functions
inuencing individual variation rather than population-level eects), it
is relevant for future research.
e statistical approaches employed in these case studies, including
mixed-eects models with binary categorization (e.g., “doers vs.
non-doers” or “high vs. low skilled”), can also berened. Advanced
methods, such as cluster analysis, structural equation modeling (SEM),
or psychometric network modeling, are well suited to disentangle
relationships between predictors and outcomes while accounting for
trial-level variability and measurement error. Such methods are
particularly valuable in studies examining complex relationships among
constructs like WM and EFs. Moving beyond binary classications and
employing robust statistical models that integrate multiple psychometric
tasks for targeted cognitive functions would enhance the validity and
interpretability of ndings in the case studies.
Overall, while methodological challenges such as inter-correlation,
multicollinearity, sample size, representativeness, and statistical
approaches are areas for renement, the case studies reviewed here
maintain validity within their specic contexts and oer valuable insights
into the link between cognitive functions and discourse management,
paving the way for more comprehensive and generalizable future research.
4.4 Future directions
Our review poses several open questions that further studies need
to address:
(1) Do weobserve the same individual dierences at the single-
sentence level for larger discourse-level contexts/units?
(2) What is the relation between executive functions (EFs) and
processing ambiguous pronouns in discourse management
within a larger context?
(3) How does the perception, processing, and interpretation of
prosodic prominence vary across individuals? Do weobserve
inter-individual variation in perception as wedo in production?
(4) Can discourse management success be predicted by
psychometric measures associated with cognitive functions?
Can such success bea biomarker for clinical groups?
(5) To what extent can the proposed framework beextended to
visual–spatial modalities such as sign language and gesture?
What additional considerations are necessary for such
an extension?
In conclusion, in this review wehave laid the groundwork for a more
in-depth exploration of this nuanced and underexplored eld, opening
the door to further investigations into the intricacies of discourse
management and its relationship to cognitive functions inuencing
individual variation. While our focus has been on spoken and written
modalities, werecognize the importance of multimodality—particularly
the visual–spatial domain—and emphasize the need for future research
to explore how our proposed framework applies to sign language and
gesture. e proposed measures and considerations outlined here oer
valuable insights and pathways for future research, promising to enhance
our understanding of this complex and evolving subject area.
Author contributions
DÇ: Conceptualization, Investigation, Project administration,
Writing– original dra, Writing– review & editing. JB: Writing–
original dra, Writing – review & editing. JT: Conceptualization,
Funding acquisition, Writing– original dra, Writing– review &
editing. CP: Writing– original dra, Writing– review & editing. MG:
Writing– original dra, Writing– review & editing. SW: Writing–
original dra, Writing– review & editing. ML: Writing– original
dra, Writing – review & editing. SR: Writing – original dra,
Writing– review & editing. HS: Writing– original dra, Writing–
review & editing. SE: Writing– original dra, Writing– review &
editing. KH: Funding acquisition, Writing– original dra, Writing–
review & editing. KV: Funding acquisition, Writing– original dra,
Writing – review & editing. PS: Conceptualization, Funding
acquisition, Project administration, Writing– original dra, Writing–
review & editing.
Funding
e author(s) declare that nancial support was received for the
research, authorship, and/or publication of this article. is research
was funded by the Deutsche Forschungsgemeinscha (DFG, German
Research Foundation) -Project-ID 281511265 -SFB 1252 Prominence
in Language -at the University of Cologne, Department of German
Language and Literature I, Linguistics.
Acknowledgments
We would like to express our gratitude to Tuncay Tosun for his
assistance in gathering and organizing the references.
Conflict of interest
e authors declare that the research was conducted in the
absence of any commercial or nancial relationships that could
beconstrued as a potential conict of interest.
Çokal et al. 10.3389/fcomm.2025.1448463
Frontiers in Communication 14 frontiersin.org
Publisher’s note
All claims expressed in this article are solely those of the authors
and do not necessarily represent those of their aliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may beevaluated in this article, or claim
that may bemade by its manufacturer, is not guaranteed or endorsed
by the publisher.
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