Presentations

Abstract

Subject-verb agreement is one of the most common
grammatical encoding operations in language
production. In many languages, morphological
inflection on verbs code for the number of the head
noun of a subject phrase (e.g., The key to the cabinets
is rusty). Despite the relative ease with which subjectverb
agreement is accomplished, people sometimes
make agreement errors (e.g., The key to the cabinets
are rusty). Such errors offer a window into the early
stages of production planning. Agreement errors are
influenced by both syntactic and semantic factors, and
are more likely to occur when a sentence contains either
conceptual or syntactic number mismatches. Little
is known about the timecourse of these influences,
however, and some controversy exists as to whether
they are independent. The current study was designed
to address these two issues using EEG. Semantic and
syntactic factors influencing number mismatch were
factorially-manipulated in a forced-choice sentence
completion paradigm. To avoid EEG artifact associated
with speaking, participants (N=20) were presented with
a noun-phrase, and pressed a button to indicate which
version of the verb ‘to be’ (is/are) should continue
the sentence. Semantic number was manipulated
using preambles that were semantically-integrated or
unintegrated. Semantic integration refers to the semantic
relationship between nouns in a noun-phrase, with
integrated items promoting conceptual-singularity.
The syntactic manipulation was the number (singular/
plural) of the local noun preceding the decision. This
led to preambles such as “The pizza with the yummy
topping(s)... “ (integated) vs. “The pizza with the tasty
bevarage(s)...” (unintegrated). Behavioral results showed
effects of both Local Noun Number and Semantic
Integration, with more errors and longer reaction times
occurring in the mismatching conditions (i.e., plural
local nouns; unintegrated subject phrases). Classic ERP
analyses locked to the local noun (0-700 ms) and to the
time preceding the response (-600 to 0 ms) showed no
systematic differences between conditions. Despite this
result, we assessed whether difference might emerge
using multivariate pattern analysis (MVPA). Using the
same epochs as above, support-vector machines with a
radial basis function were trained on the single-trial level
to classify the difference between Local Noun Number
and Semantic Integration conditions across time and
channels. Results revealed that both conditions could
be reliably classified at the single subject level, and
that classification accuracy was strongest in the epoch
preceding the response. Classification accuracy was
at chance when a classifier trained to dissociate Local
Noun Number was used to predict Semantic Integration
(and vice versa), providing some evidence of the
independence of the two effects. Significant inter-subject
variability was present in the channels and time-points
that were critical for classification, but earlier timepoints
were more often important for classifying Local Noun
Number than Semantic Integration. One result of this
variability is classification performed across subjects was
at chance, which may explain the failure to find standard
ERP effects. This study thus provides an important first
test of semantic and syntactic influences on subject-verb
agreement with EEG, and demonstrates that where
classic ERP analyses fail, MVPA can reliably distinguish
differences at the neurophysiological level.

Abstract

Information in language is organized according to a principle called information structure: new and important information (focus) is highlighted and distinguished from less important information (non-focus). Most studies so far have been concerned with how focused information is emphasized linguistically and suggest that listeners expect focus to be accented and process it more deeply than non-focus (Wang et al., 2011). Little is known about how listeners deal with non-verbal cues like beat gestures, which also emphasize the words they accompany, similarly to pitch accent. ERP studies suggest that beat gestures facilitate the processing of phonological, syntactic, and semantic aspects of speech (Biau, & Soto-Faraco, 2013; Holle et al., 2012; Wang & Chu, 2013). It is unclear whether listeners expect beat gestures to be aligned with the information structure of the message. The present ERP study addresses this question by testing whether beat gestures modulate the processing of accented-focused vs. unaccented-non focused words in context in a similar way. Participantswatched movies with short dialogues and performed a comprehension task. In each dialogue, the answer “He bought the books via amazon” contained a target word (“books”) which was combined with a beat gesture, a control hand movement (e.g., self touching movement) or no gesture. Based on the preceding context, the target word was either in focus and accented, when preceded by a question like “Did the student buy the books or the magazines via Amazon?”, or the target word was in non-focus and unaccented, when preceded by a question like “Did the student buy the books via Amazon or via Marktplaats?”. The gestures started 500 ms prior to the target word. All gesture parameters (hand shape, naturalness, emphasis, duration, and gesture-speech alignment) were determined in behavioural tests. ERPs were time-locked to gesture onset to examine gesture effects, and to target word onset for pitch accent effects. We applied a cluster-based random permutation analysis to test for main effects and gesture-accent interactions in both time-locking procedures. We found that accented words elicited a positive main effect between 300-600 ms post target onset. Words accompanied by a beat gesture and a control movement elicited sustained positivities between 200-1300 ms post gesture onset. These independent effects of pitch accent and beat gesture are in line with previous findings (Dimitrova et al., 2012; Wang & Chu, 2013). We also found an interaction between control gesture and pitch accent (1200-1300 ms post gesture onset), showing that accented words accompanied by a control movement elicited a negativity relative to unaccented words. The present data show that beat gestures do not differentially modulate the processing of accented-focused vs. unaccented-non focused words. Beat gestures engage a positive and long lasting neural signature, which appears independent from the information structure of the message. Our study suggests that non-verbal cues like beat gestures play a unique role in emphasizing information in speech.

Abstract

IIn spoken utterances important or new information is
often linguistically marked, for instance by prosody
or syntax. Such highlighting prevents listeners from
skipping over relevant information. Linguistic cues like
pitch accents lead to a more elaborate processing of
important information (Wang et al., 2011). In a recent
fMRI study, Kristensen et al. (2013) have shown that the
neurobiological signature of pitch accents is linked to the
domain-general attention network. This network includes
the superior and inferior parietal cortex. It is an open
question whether non-prosodic markers of focus (i.e. the
important/new information) function similarly on the
neurobiological level, that is by recruiting the domaingeneral
attention network. This study tried to address
this question by testing a syntactic marker of focus. The
present fMRI study investigates the processing of it-clefts,
which highlight important information syntactically,
and compares it to the processing of pitch accents, which
highlight information prosodically. We further test if
both linguistic focusing devices recruit domain-general
attention mechanisms. In the language task, participants
listened to short stories like “In the beginning of February
the final exam period was approaching. The student did
not read the lecture notes”. In the last sentence of each
story, the new information was focused either by a pitch
accent as in “He borrowed the BOOK from the library”
or by an it-cleft like “It was the book that he borrowed
from the library”. Pitch accents were pronounced without
exaggerated acoustic emphasis. Two control conditions
were included: (i) sentences with fronted focus like “The
book he borrowed from the library”, to account for word
order differences between sentences with clefts and
accents, and (ii) sentences without prosodic emphasis
like ”He borrowed the book from the library”. In the
attentional localizer task (adopted from Kristensen et al., 2013), participants listened to tones in a dichotic
listening paradigm. A cue tone was presented in one ear
and participants responded to a target tone presented
either in the same or the other ear. In line with Kristensen
et al. (2013), we found that in the localizer task cue
tones activated the right inferior parietal cortex and the
precuneus, and we found additional activations in the
right superior temporal gyrus. In the language task,
sentences with it- clefts elicited larger activations in the
left and right superior temporal gyrus as compared to
control sentences with fronted focus. For the contrast
between sentences with pitch accent vs. without pitch
accent we observed activation in the inferior parietal
lobe, this activation did however not survive multiple
comparisons correction. In sum, our findings show that
syntactic focusing constructions like it-clefts recruit
the superior temporal gyri, similarly to cue tones in
the localizer task. Highlighting focus by pitch accent
activated the parietal cortex in areas overlapping with
those reported by Kristensen et al. and with those we
found for cue tones in the localizer task. Our study
provides novel evidence that prosodic and syntactic
focusing devices likely have a distinct neurobiological
signature in spoken language comprehension.

Abstract

Sentence processing requires the ability to establish thematic relations between constituents. Here we investigate the computational basis of this ability in a neurobiologically motivated comprehension model. The model has a tripartite architecture where input representations are supplied by the mental lexicon to a network that performs incremental thematic role assignment. Roles are combined into a representation of sentence-level meaning by a downstream system (semantic unification). Recurrent, sparsely connected, spiking networks were used which project a time-varying input signal (word sequences) into a high-dimensional, spatio-temporal pattern of activations. Local, adaptive linear read-out units were then calibrated to map the internal dynamics to desired output (thematic role sequences) [1]. Read-outs were adjusted on network dynamics driven by input sequences drawn from argument-structure templates with small variation in function words and larger variation in content words. Models were trained on sequences of 10K words for 200ms per word at a 1ms resolution, and tested on novel items generated from the language. We found that a static, random recurrent spiking network outperformed models that used only local word information without context. To improve performance, we explored various ways of increasing the model’s processing memory (e.g., network size, time constants, sparseness, input strength, etc.) and employed spiking neurons with more dynamic variables (leaky integrate-and-fire versus Izhikevich-neurons). The largest gain was observed when the model’s input history was extended to include previous words and/or roles. Model behavior was also compared for localist and distributed encodings of word sequences. The latter were obtained by compressing lexical co-occurrence statistics into continuous-valued vectors [2]. We found that performance for localist-input was superior even though distributed representations contained extra information about word context and semantic similarity. Finally, we compared models that received input enriched with combinations of semantic features, word-category, and verb sub-categorization labels. Counter-intuitively, we found that adding this information to the model’s lexical input did not further improve performance. Consistent with previous results, however, performance improved for increased variability in content words [3]. This indicates that the approach to comprehension taken here might scale to more diverse and naturalistic language input. Overall, the results suggest that active processing memory beyond pure state-dependent effects is important for sentence interpretation, and that memory in neurobiological systems might be actively computing [4]. Future work therefore needs to address how the structure of word representations interacts with enhanced processing memory in adaptive spiking networks. [1] Maass W., Natschläger T., & Markram H. (2002). Real-time computing without stable states: A new framework for neural computation based on perturbations. Neural Computation, 14: 2531-2560. [2] Mikolov, T., Chen, K., Corrado, G., & Dean, J. (2013). Efficient estimation of word represen-tations in vector space. Proceedings of the International Conference on Learning Represen-tations, Scottsdale/AZ. [3] Fitz, H. (2011). A liquid-state model of variability effects in learning nonadjacent dependencies. Proceedings of the 33rd Annual Conference of the Cognitive Science Society, Austin/TX. [4] Petersson, K.M., & Hagoort, P. (2012). The neurobiology of syntax: Beyond string-sets. Philo-sophical Transactions of the Royal Society B 367: 1971-1883.

Abstract

Hagoort [1] suggested that the posterior temporal cortex is involved in the retrieval of lexical frames that form building blocks for syntactic unification, supported by the inferior frontal gyrus (IFG). FMRI results support the role of the IFG in the unification operations that are performed at the structural/syntactic [2] and conceptual/ semantic levels [3]. While these studies tackle the unification operations within linguistic components, in the present event-related FMRI study we investigated the interplay between sentence-level semantics and syntax by adapting an EEG comprehension paradigm [4]. The ERP results showed typical P600 and N400 effects, while their combined effect revealed an interaction expressed in the N400 component ([CB-SE] - [SY-CR] > 0). Although the N400 component was similar in the correct and syntactic conditions (SY  CR), the combined effect was significantly larger than the effect of semantic anomaly alone. In contrast, the size of the P600 effect was not affected by an additional semantic violation, suggesting an asymmetry between semantic and syntactic processing. In the current FMRI study we characterize this asymmetry by means of a 2x2 experimental design included the conditions: correct (CR), syntactic (SY), semantic (SE), and combined (CB) anomalies. Standard SPM procedures were used for analysis and only clusters significant at P <.05 family-wise error corrected are reported. The main effect of semantic anomaly ([CB+SE] > [SY+CR]) yielded activation in the anterior IFG (BA 45/47). The opposite contrast revealed the theory-ofmind and default-mode network. The main effect of syntactically correct sentences ([SE+CR] > [CB+SY]), showed significant activation in the IFG (BA 44/45), including the mid-anterior insula extending into the superior temporal poles (BA 22/38). In addition, significant effects were observed in medial prefrontal/ anterior cingulate cortex, posterior middle and superior temporal regions (BA 21/22), and the basal ganglia. The reverse contrast yielded activations in the MFG (BA 9/46), the inferior parietal region (BA 39/40), precuneus and the posterior cingulate region. The only region that showed a significant interaction ([CBSE]  [SYCR] > 0) was the left temporo-parietal region (BA 22/39/40). In summary, the results show that the IFG is involved in unification during comprehension. The effect of semantic anomaly and its implied unification load engages the anterior IFG while the effect of syntactic anomaly and its implied unification failure engages MFG. Finally, the results suggest that the syntax of gender agreement interacts with sentence-level semantics in the left temporo-parietal region. [1] Hagoort, P. (2005). On Broca, brain, and binding: A new framework. TICS, 9, 416-423. [2] Snijders, T. M., Vosse, T., Kempen, G., Van Berkum, J. J. A., Petersson, K. M., Hagoort, P. (2009). Retrieval and unification of syntactic structure in sentence comprehension: An fMRI study using word-category ambiguity. Cerebral Cortex, 19, 1493-1503. doi:10.1093/ cercor/bhn187. [3] Hagoort, P., Hald, L., Baastiansen, M., Petersson, K.M. (2004). Integration of word meaning and world knowledge in language comprehension. Science 304, 438-441. [4] Hagoort, P. (2003). Interplay between syntax and semantics during sentence comprehension: ERP effects of combining syntactic and semantic violations. Journal of Cognitive Neuroscience, 15, 883- 899.

Abstract

This study aims to test a prediction of recent
theoretical frameworks in speech motor control: if
speech production targets are specified in auditory
terms, people with better auditory acuity should
have more precise speech targets.
To investigate this, we had participants perform
speech perception and production tasks in a
counterbalanced order. To assess speech perception
acuity, we used an adaptive speech discrimination
task. To assess variability in speech production,
participants performed a pseudo-word reading task;
formant values were measured for each recording.
We predicted that speech production variability to
correlate inversely with discrimination performance.
The results suggest that people do vary in their
production and perceptual abilities, and that better
discriminators have more distinctive vowel
production targets, confirming our prediction. This
study highlights the importance of individual
differences in the study of speech motor control, and
sheds light on speech production-perception
interaction.

Abstract

Speech production is one of the most complex motor skills, and involves close interaction
between the perceptual and the motor system. Recently, prediction via forward models has
been at the forefront of speech neuroscience research. For example, neuroimaging evidence
has demonstrated that activation of the auditory cortex is suppressed to self-produced speech
relative to listening without speaking. This finding has been explained via a forward model
that predicts the auditory consequences of our own speech actions. An accurate prediction
cancels out (part of) the auditory cortical activation.
The present study was designed to test two critical predictions from these frameworks: First,
whether the cortical auditory response during speech production varies as a function of the
acoustic distance between feedback and prediction, and second, whether this in turn is predictive
of the amount of adaptation in people’s speech production. MEG was recorded while
subjects performed an online speech imitation task. Each subject heard and imitated Dutch
vowels, varying in their distance from the original vowel in both F1 and F2.
The results did not show clear evidence that the amount of suppression scaled with the
distance between participants’ speech and the speech target. However, we found that subjects’
auditory response did correlate with imitation performance. This result supports the
view that an enhanced auditory response may act as an error signal, driving subsequent
speech adaptation. This suggests that individual differences in SIS could act as a marker for
subsequent adaptation.

Abstract

The classical Wernicke-Lichtheim-Geschwind model of the neurobiology of language was based on an analysis of single word perception and production. However, language processing involves a lot more than production and comprehension of single words. In this talk I will focus on the neurobiological infrastructure for processing language beyond single words. The Memory, Unification and Control (MUC) model provides a neurobiological plausible account of the underlying neural architecture. I will focus on operations that unify the lexical building blocks into larger structures. MEG, fMRI, resting state connectivity data, and results from Psycho-Physiological Interactions will be discussed, suggesting a division of labour between temporal and inferior frontal cortex. These results indicate that Broca’s area and adjacent cortex play an important role in semantic and syntactic unification operations. I will discuss to what extent these operations are shared between language comprehension and production. I will also discuss fMRI results that indicate the insufficiency of the Mirror Neuron Hypothesis to explain language understanding. In short, I will sketch a picture of language processing from an embrained perspective.

Abstract

When we read literature, we often become immersed and dive into fictional worlds. The way we perceive those worlds is the result of skillful arrangement of linguistic features by story writers in order to create certain mental representations in the reader. Narrative perspective, or focalization, is an important tool for storywriters to manipulate reader's perception of a story. Despite the fact that narrative perspective is generally considered a fundamental element in narrative comprehension, the cognitive effects on story reading remain unclear. In previous research, various methodologies were employed to investigate the cognitive processes underlying narrative comprehension. However, studies used either self-report procedures or behavioral tests to investigate reader's reactions and refrained from combined methodologies. In the present study we combined skin conductance measurements and questionnaires while participants read short stories in 1st and 3rd person perspective. The results show that immersion, imagery and appreciation are higher when participants read stories in 1st person perspective. To our surprise, we found higher arousal for reading 3rd person perspective compared to 1st person perspective narratives. We find evidence, that individual difference in arousal between the two conditions is related to how much readers empathize with the fictional characters. The combination of methodologies allows us a more differentiated understanding of the underlying mechanisms of immersion. In my talk, I want to highlight how we can gain more from interdisciplinary research and combinations from various methodologies to investigate cognitive processes underlying narrative comprehension under natural conditions.

Abstract

Morphology is the aspect of language concerned with
the internal structure of words. In the past decades,
a large body of masked priming (behavioral and
neuroimaging) data has suggested that the visual
word recognition system automatically decomposes
any morphologically complex word into a stem and
its constituent morphemes. Yet, it remains equivocal
whether this morphemic decomposition relies primarily
on orthography or on semantics. Here, we approached
the issue straightforwardly by applying a task of
morphological unification, that is, by assembling internal
(morphemic) units into a whole-word. Morphemic units
were sequentially presented while participants were
requested to judge whether their assemblage represented
real- or pseudo-words. Trials representing real words
were divided into words with a transparent (true) or a
non-transparent (pseudo) morphological relationship.
Morphological unification of truly suffixed words
occurred in a more straightforward way (shorter RT and
higher accuracy). Additionally, oscillatory brain activity
was monitored with magnetoencephalography and
revealed that real, compared to pseudo morphological unification enhanced narrow gamma band oscillations
(60-85 Hz, 300-450 ms) in the left posterior occipitotemporal
junction, which is known as a cerebral hub for
visual word processing. This neural signature could not
be explained by a mere automatic lexical processing (i.e.
stem perception), but more likely it related to a semantic
access step during the morphological unification process.
These findings highlight a plausible retrieval of lexical
semantic associations for enabling true morphological
unification, and further instantiate the pivotal role of
the left occipito-temporal junction in visual word form
processing.

Abstract

In conversation, speakers mimic each other’s (linguistic)
behavior. For example, speakers are likely to repeat
each other’s sentence structures: a phenomenon
known as syntactic priming. In a previous fMRI study
(Schoot et al., 2014) we reported that the magnitude
of priming effects is also mimicked between speakers.
Here, we follow-up on that result. Specifically, we test
the hypothesis that in a communicative context, the
priming magnitude of your interlocutor can predict your
own priming magnitude because you have adapted
your individual susceptibility to priming to the other
speaker. 40 participants were divided into 20 pairs who
performed the experiment together. They were asked
to describe photographs to each other. Photographs
depicted two persons performing a transitive action
(e.g. a man hugging a woman). Participants were
instructed to describe the photographs with an active
or a passive sentence depending on the color-coding
of the photograph (stop light paradigm, Menenti et al.,
2011). Syntactic priming effects were measured in speech
onset latencies: a priming effect is found when speakers
are faster to produce sentences with the same structure
as the preceding sentence (i.e. two consecutive actives
or passives) than to produce sentences with a different
structure (active follows passive or vice versa). Before
participants performed the communicative task, we ran
a non-communicative pretest for each participant, to
measure their individual priming effect without influence
of the partner’s priming effect. To test whether speakers
influence each other’s syntactic priming magnitude in
conversation, we ran an rANCOVA with the syntactic
priming effect of each participant’s communicative
partner as a covariate. Results showed that there was
an interaction between this covariate and Syntactic
Repetition (F(1,38) = 435.93, p < 0.001). The more your
partner is primed by you, the more you are primed by
your partner. In a second analysis, we found that the
difference between paired speakers’ individual syntactic
priming effects (as measured in the pretest) predicted
how much speakers adapt their syntactic priming effects
when they are communicating with their partner in the
communicative experiment (ß = -0.467, p < 0.001). That
means that if your partner’s individual susceptibility for
syntactic priming is stronger than yours, you will increase
your own priming magnitude in the communicative
context. On the other hand, if your partner’s individual
susceptibility for syntactic priming is less strong, you
will decrease your priming effect. Furthermore, the
strength of the in-/decrease is proportional to how
different you are from your speaker to begin with. We
interpret the results as follows. Syntactic priming effects
in conversation are said to result from speakers aligning
their syntactic representations by mimicking sentence
structure (Pickering & Garrod, 2004; Jaeger & Snider,
2013). Here we show that on top of that, the magnitude
of syntactic priming effects is also mimicked between
interlocutors. Future research should focus on further
investigation of the neural correlates of this process, for
example with fMRI hyper-scanning. Indeed, our findings
stress the importance of studying language processing in
real, communicative contexts, which is now also possible
in neuroimaging paradigms.

Abstract

Previous studies have shown the possibility to decode
the semantic category of an object from the fMRI signal in
different modalities of object presentation. Furthermore,
by generalizing a classifier across different modalities
(for instance, from pictures to written words), cortical
structures that process semantic information in an
amodal fashion have been identified. In this study we
employ high-resolution fMRI in combination with
surface-based searchlight mapping to further explore
the architecture of modality-independent responses.
Stimuli of 2 semantic categories (animals and tools)
were presented in 2 modalities: photographs and
written words. Stimuli were presented in 40-seconds
blocks with 10-seconds intervals. Subjects (N=3) were
instructed to judge whether each stimulus within a
block was semantically consistent with the others. The
experiment also included 8 free recall blocks, in which
name of a category appeared on the screen for 2 seconds,
followed by 40 seconds of a blank screen. In theses blocks
subjects were instructed to covertly recall all entities
from the probed category that they had seen during the
experiment. Subjects were scanned with 7 Tesla MRIscanner,
using 3D EPI sequence with isotropic resolution
of 1.5 mm. In each subject, reconstruction of cortical
surface was performed. After that, for each vertex on the
surface, a set of adjacent voxels in the functional volume
was assigned. Subsequently, a linear support vector
machine classifier was used to decode object category in
each surface-based patch. Generalization analysis across
picture and written word presentation was performed,
where the classifier was trained on the fMRI data from
blocks of written words, and tested on the data from picture blocks, and vice versa. The second analysis was
performed on the free recall blocks, where the classifier
was trained on merged data from pictures and written
words blocks, and tested on the free recall blocks.
Further, we explored how the decoding accuracy in the
inferior temporal cortex changes with the diameter of the
searchlight patch. Since surface-based voxel grouping
takes into account the cortical folding and ensures that
voxels belonging to different gyri do not fall in the same
searchlight group, it allows answering the question,
at what spatial scale is the modality-independent
information is represented. The cross-modal analysis in
all three subjects revealed a cluster of voxels in inferior
temporal cortex (lateral fusiform and inferotemporal gyri)
and posterior middle temporal gyrus. The topography
of significant clusters also suggested involvement of
the inferior frontal gyrus, lateral prefrontal cortex, and
medial prefrontal cortex. Interestingly, these areas were
the most evident in the free recall test, although the
searchlight maps of the three subjects showed substantial
individual differences in this analysis. Overall, the data
yield a similar picture as previous research, highlighting
the role of IT/pMTG and prefrontal cortex in the crossmodal
semantic representation. We further extended
previous research, by showing that the classification
accuracy in these areas decreases with the increase of
the searchlight patch size. These results indicate that the
modality-independent categorical activations in the IT
cortex are represented on the spatial scale of millimetres.

Abstract

Although monitoring and subsequent control have
received quite some attention for cognitive systems
other than language, few studies have probed the neural
mechanisms underlying monitoring and control in overt
speech production. Recently, it has been hypothesized
that conflict signals within the language production
system might serve as cues to increase monitoring
and control (Nozari, Dell & Schwartz, 2011; Cognitive
Psychology). This hypothesis was linked directly to the
conflict monitoring hypothesis in non-linguistic action
control, which hypothesizes that one of the critical
cues to self-monitoring is the co-activation of multiple
response candidates (Yeung, Botvinick & Cohen, 2004;
Psychological Review). A region of the medial prefrontal
cortex (mPFC), the dorsal anterior cingulate cortex
(dACC), as well as the basal ganglia have consistently
been observed in both errors of commission and high
conflict.. Hence these regions serve as an important
testing ground for whether comparable monitoring
mechanisms are at play in language production. The
current study tests whether these regions are also
implicated in response to speech errors and high conflict
situations that precede the response. 32 native Dutch
subjects performed a tongue twister task and a factorial
combination of the Simon and Flanker task. In the tongue
twister task, participants overtly produced a string of
4 nonwords 3 times. In tongue twister trials (TT), the
onset phonemes followed a pattern of A-B-B-A, whereas
rhymes followed an A-B-A-B pattern (e.g. wep ruust
rep wuust). In non-tongue twister trials (nonTT), the
nonwords contained minimal phonological overlap
(e.g. jots brauk woelp zieg). These two conditions
correspond to a high conflict and a low conflict condition
respectively. In an arrow version of the the Simon-
Flanker task, subjects responded to the direction of a
middle arrow while flanking arrows faced in the same
(i.e., congruent; >>>>>) or different (i.e., incongruent;
>><>>) directions. These stimuli were presented either
on the right side or the left side of the screen, potentially
creating a spatial incongruency with their response
as well. Behavioral results demonstrated sensitivity
to conflict in both tasks, as subjects generated more
speech errors in tongue twister trials than non-tongue
twister trials, and were slower to incongruent relative
to congruent flanker trials. No difference between
spatial incongruency was observed. Neuroimaging
results showed that activation in the ACC significantly
increased in response to the high conflict flanker trials.
In addition, regions of interest analyses in the basal
ganglia showed a significant difference between correct
high and low conflict flanker trials in the left putamen
and right caudate nucleus. For the tongue twister task,
a large region in the mPFC - overlapping with the ACC
region from the flanker task - was significantly more
active in response to errors than correct trials. Significant
differences were also found in the left and right caudate
nuclei and left putamen. No differences were found
between correct TT and nonTT trials. The study therefore
provides evidence for overlap in monitoring between
language production and non-linguistic action at the
time of response (i.e. errors), but little evidence for preresponse
conflict engaging the same system.

Abstract

In order to communicate efficiently, speakers have to
take into account which information they share with their
addressee (common ground) and which information
they do not share (privileged ground). Two views
have emerged about how and when common ground
influences language production. In one view, speakers
take common ground into account early on during
utterance planning (e.g., Brennan & Hanna, 2009).
Alternatively, it has been proposed that speakers’ initial
utterance plans are egocentric, but that they monitor
their plans and revise them if needed (Horton & Keysar,
1996). In an fMRI study, we investigated which neural
mechanisms support speakers’ ability to take into account
common ground, and at what stage during speech
planning these mechanisms come into play. We tested
22 pairs of native Dutch speakers (20 pairs retained in
the analysis), who were assigned to the roles of speaker
or listener for the course of the experiment. The speaker
performed the experiment in the MRI scanner, while the
listener sat behind a computer in the MRI control room.
The speaker performed a communicative and a noncommunicative
task in the scanner. The communicative
task was a referential communication game in which
the speaker described objects in an array to the listener.
The listener could hear the speaker’s descriptions over
headphones and tried to select the intended object on
her screen using a mouse. We manipulated common
ground within the communicative task. In the privileged
ground condition, the speaker saw additional competitor
objects that were occluded from the listener’s point of
view. In order to communicate efficiently, the speaker
had to ignore the occluded competitor objects. In the
control conditions, all relevant objects were in common
ground. The non-communicative task was identical to
the communicative task, except that the speaker was
instructed to describe the objects without the listener
listening. When comparing the BOLD response during
speech planning in the communicative and the noncommunicative
tasks, we found activations in the right
medial prefrontal cortex and bilateral insula, brain areas
involved in mentalizing and empathy. These results
confirm previous neuroimaging research that found that
speaking in a communicative context as compared to a
non-communicative context activates brain areas that
are involved in mentalizing (Sassa et al., 2007; Willems
et al., 2010). We also contrasted brain activity in the
privileged ground and control conditions within the
communicative task to tap into the neural mechanisms
that allow speakers to take common ground into account.
We again found activity in brain regions involved in
mentalizing and visual perspective-taking (the bilateral
temporo-parietal junction and medial prefrontal cortex).
In addition, we found a cluster in the dorsolateral
prefrontal cortex, a brain area that has previously been
proposed to support the inhibition of task-irrelevant
perspectives (Ramsey et al., 2013). Interestingly, these
clusters are located outside the traditional language
network. Our results suggest that speakers engage in
mentalizing and visual perspective-taking during speech
planning in order to compute common ground rather
than monitoring and adjusting their initial egocentric
utterance plans.