Publications

Abstract

The meaning of a sentence can be understood, whether presented in written or spoken form. Therefore it is highly probable that brain processes supporting language comprehension are at least partly independent of sensory modality. To identify where and when in the brain language processing is independent of sensory modality, we directly compared neuromagnetic brain signals of 200 human subjects (102 males) either reading or listening to sentences. We used multiset canonical correlation analysis to align individual subject data in a way that boosts those aspects of the signal that are common to all, allowing us to capture word-by-word signal variations, consistent across subjects and at a fine temporal scale. Quantifying this consistency in activation across both reading and listening tasks revealed a mostly left hemispheric cortical network. Areas showing consistent activity patterns include not only areas previously implicated in higher-level language processing, such as left prefrontal, superior & middle temporal areas and anterior temporal lobe, but also parts of the control-network as well as subcentral and more posterior temporal-parietal areas. Activity in this supramodal sentence processing network starts in temporal areas and rapidly spreads to the other regions involved. The findings do not only indicate the involvement of a large network of brain areas in supramodal language processing, but also indicate that the linguistic information contained in the unfolding sentences modulates brain activity in a word-specific manner across subjects.

Abstract

Bodily mimicry often makes the mimickee have more positive feelings about the mimicker. Yet, little is known about the causes of mimicry’s social effects. When people mimic each other’s bodily movements face to face, they can either adopt a mirrorwise perspective (moving in the same absolute direction) or an anatomical perspective (moving in the same direction relative to their own bodies). Mirrorwise mimicry maximizes visuo-spatial similarity between the mimicker and mimickee, whereas anatomical mimicry maximizes the similarity in the states of their motor systems. To compare the social consequences of visuo-spatial and motoric similarity, we asked participants to converse with an embodied virtual agent (VIRTUO), who mimicked their head movements either mirrorwise, anatomically, or not at all. Compared to participants who were not mimicked, those who were mimicked mirrorwise tended to rate VIRTUO more positively, but those who were mimicked anatomically rated him more negatively. During face-to-face conversation, mirrorwise and anatomical mimicry have opposite social consequences. Results suggest that visuo-spatial similarity between mimicker and mimickee, not similarity in motor system activity, gives rise to the positive social effects of bodily mimicry.

Abstract

Language processing involves the ability to store and integrate pieces of
information in working memory over short periods of time. According to
the dominant view, information is maintained through sustained, elevated
neural activity. Other work has argued that short-term synaptic facilitation
can serve as a substrate of memory. Here, we propose an account where
memory is supported by intrinsic plasticity that downregulates neuronal
firing rates. Single neuron responses are dependent on experience and we
show through simulations that these adaptive changes in excitability pro-
vide memory on timescales ranging from milliseconds to seconds. On this
account, spiking activity writes information into coupled dynamic variables
that control adaptation and move at slower timescales than the membrane
potential. From these variables, information is continuously read back into
the active membrane state for processing. This neuronal memory mech-
anism does not rely on persistent activity, excitatory feedback, or synap-
tic plasticity for storage. Instead, information is maintained in adaptive
conductances that reduce firing rates and can be accessed directly with-
out cued retrieval. Memory span is systematically related to both the time
constant of adaptation and baseline levels of neuronal excitability. Inter-
ference effects within memory arise when adaptation is long-lasting. We
demonstrate that this mechanism is sensitive to context and serial order
which makes it suitable for temporal integration in sequence processing
within the language domain. We also show that it enables the binding of
linguistic features over time within dynamic memory registers. This work
provides a step towards a computational neurobiology of language.

Abstract

Speakers and listeners usually interact in larger discourses than single words or even single sentences. The goal of the present study was to identify the neural bases reflecting how the mental representation of the situation denoted in a multi-sentence discourse (situation model) is constructed and shared between speakers and listeners. An fMRI study using a variant of the ambiguous text paradigm was designed. Speakers (n=15) produced ambiguous texts in the scanner and listeners (n=27) subsequently listened to these texts in different states of ambiguity: preceded by a highly informative, intermediately informative or no title at all. Conventional BOLD activation analyses in listeners, as well as inter-subject correlation analyses between the speakers’ and the listeners’ hemodynamic time courses were performed. Critically, only the processing of disambiguated, coherent discourse with an intelligible situation model representation involved (shared) activation in bilateral lateral parietal and medial prefrontal regions. This shared spatiotemporal pattern of brain activation between the speaker and the listener suggests that the process of memory retrieval in medial prefrontal regions and the binding of retrieved information in the lateral parietal cortex constitutes a core mechanism underlying the communication of complex conceptual representations.

Abstract

Visual context facilitates perception, but how this is neurally implemented remains unclear. One example of contextual facilitation is found in reading, where letters are more easily identified when embedded in a word. Bottom-up models explain this word advantage as a post-perceptual decision bias, while top-down models propose that word contexts enhance perception itself. Here, we arbitrate between these accounts by presenting words and nonwords and probing the representational fidelity of individual letters using functional magnetic resonance imaging. In line with top-down models, we find that word contexts enhance letter representations in early visual cortex. Moreover, we observe increased coupling between letter information in visual cortex and brain activity in key areas of the reading network, suggesting these areas may be the source of the enhancement. Our results provide evidence for top-down representational enhancement in word recognition, demonstrating that word contexts can modulate perceptual processing already at the earliest visual regions.

Abstract

Recent neuroimaging evidence suggests that the frequency of entrained oscillations in auditory cortices influences the perceived duration of speech segments, impacting word perception (Kösem et al. 2018). We further tested the causal influence of neural entrainment frequency during speech processing, by manipulating entrainment with continuous transcranial alternating
current stimulation (tACS) at distinct oscillatory frequencies (3 Hz and 5.5 Hz) above the auditory cortices. Dutch participants listened to speech and were asked to report their percept of a target Dutch word, which contained a vowel with an ambiguous duration. Target words
were presented either in isolation (first experiment) or at the end of spoken sentences (second experiment). We predicted that the tACS frequency would influence neural entrainment and
therewith how speech is perceptually sampled, leading to a perceptual over- or underestimation of the vowel’s duration. Whereas results from Experiment 1 did not confirm this prediction, results from experiment 2 suggested a small effect of tACS frequency on target word
perception: Faster tACS lead to more long-vowel word percepts, in line with the previous neuroimaging findings. Importantly, the difference in word perception induced by the different tACS frequencies was significantly larger in experiment 1 vs. experiment 2, suggesting that the
impact of tACS is dependent on the sensory context. tACS may have a stronger effect on spoken word perception when the words are presented in continuous speech as compared to when they are isolated, potentially because prior (stimulus-induced) entrainment of brain oscillations
might be a prerequisite for tACS to be effective.

Abstract

Perceiving speech requires the integration of different speech cues, that is, formants. When the speech signal is split so that different cues are presented to the right and left ear (dichotic listening), comprehension requires the integration of binaural information. Based on prior electrophysiological evidence, we hypothesized that the integration of dichotically presented speech cues is enabled by interhemispheric phase synchronization between primary and secondary auditory cortex in the gamma frequency band. We tested this hypothesis by applying transcranial alternating current stimulation (TACS) bilaterally above the superior temporal lobe to induce or disrupt interhemispheric gamma-phase coupling. In contrast to initial predictions, we found that gamma TACS applied in-phase above the two hemispheres (interhemispheric lag 0°) perturbs interhemispheric integration of speech cues, possibly because the applied stimulation perturbs an inherent phase lag between the left and right auditory cortex. We also observed this disruptive effect when applying antiphasic delta TACS (interhemispheric lag 180°). We conclude that interhemispheric phase coupling plays a functional role in interhemispheric speech integration. The direction of this effect may depend on the stimulation frequency.

Abstract

This neuroimaging study investigated the neural infrastructure of sentence-level language production. We compared brain activation patterns, as measured with BOLD-fMRI, during production of sentences that differed in verb argument structures (intransitives, transitives, ditransitives) and the lexical status of the verb (known verbs or pseudoverbs). The experiment consisted of 30 mini-blocks of six sentences each. Each mini-block started with an example for the type of sentence to be produced in that block. On each trial in the mini-blocks, participants were first given the (pseudo-)verb followed by three geometric shapes to serve as verb arguments in the sentences. Production of sentences with known verbs yielded greater activation compared to sentences with pseudoverbs in the core language network of the left inferior frontal gyrus, the left posterior middle temporalgyrus, and a more posterior middle temporal region extending into the angular gyrus, analogous to effects observed in language comprehension. Increasing the number of verb arguments led to greater activation in an overlapping left posterior middle temporal gyrus/angular gyrus area, particularly for known verbs, as well as in the bilateral precuneus. Thus, producing sentences with more complex structures using existing verbs leads to increased activation in the language network, suggesting some reliance on memory retrieval of stored lexical–syntactic information during sentence production. This study thus provides evidence from sentence-level language production in line with functional models of the language network that have so far been mainly based on single-word production, comprehension, and language processing in aphasia.

Abstract

Catecholamine (CA) function has been widely implicated in cognitive functions that are tied to the prefrontal cortex and striatal areas. The present study investigated the effects of methylphenidate, which is a CA agonist, on the electroencephalogram (EEG) response related to semantic processing using a double-blind, placebo-controlled, randomized, crossover, within-subject design. Forty-eight healthy participants read semantically congruent or incongruent sentences after receiving 20-mg methylphenidate or a placebo while their brain activity was monitored with EEG. To probe whether the catecholaminergic modulation is task-dependent, in one condition participants had to focus on comprehending the sentences, while in the other condition, they only had to attend to the font size of the sentence. The results demonstrate that methylphenidate has a task-dependent effect on semantic processing. Compared to placebo, when semantic processing was task-irrelevant, methylphenidate enhanced the detection of semantic incongruence as indexed by a larger N400 amplitude in the incongruent sentences; when semantic processing was task-relevant, methylphenidate induced a larger N400 amplitude in the semantically congruent condition, which was followed by a larger late positive complex effect. These results suggest that CA-related neurotransmitters influence language processing, possibly through the projections between the prefrontal cortex and the striatum, which contain many CA receptors.

Abstract

Previous research on the effect of perturbed auditory feedback in speech production has focused on two types of responses. In the short term, speakers generate compensatory motor commands in response to unexpected perturbations. In the longer term, speakers adapt feedforward motor programmes in response to feedback perturbations, to avoid future errors. The current study investigated the relation between these two types of responses to altered auditory feedback. Specifically, it was hypothesised that consistency in previous feedback perturbations would influence whether speakers adapt their feedforward motor programmes. In an altered auditory feedback paradigm, formant perturbations were applied either across all trials (the consistent condition) or only to some trials, whereas the others remained unperturbed (the inconsistent condition). The results showed that speakers’ responses were affected by feedback consistency, with stronger speech changes in the consistent condition compared with the inconsistent condition. Current models of speech-motor control can explain this consistency effect. However, the data also suggest that compensation and adaptation are distinct processes, which are not in line with all current models.

Abstract

In this contribution, the following four questions are discussed: (i) where is meaning?; (ii) what is meaning?; (iii) what is the meaning of mechanism?; (iv) what are the mechanisms of meaning? I will argue that meanings are in the head. Meanings have multiple facets, but minimally one needs to make a distinction between single word meanings (lexical meaning) and the meanings of multi-word utterances. The latter ones cannot be retrieved from memory, but need to be constructed on the fly. A mechanistic account of the meaning-making mind requires an analysis at both a functional and a neural level, the reason being that these levels are causally interdependent. I will show that an analysis exclusively focusing on patterns of brain activation lacks explanatory power. Finally, I shall present an initial sketch of how the dynamic interaction between temporo-parietal areas and inferior frontal cortex might instantiate the interpretation of linguistic utterances in the context of a multimodal setting and ongoing discourse information.

Abstract

In this Review, I propose a multiple-network view for the neurobiological basis of distinctly human language skills. A much more complex picture of interacting brain areas emerges than in the classical neurobiological model of language. This is because using language is more than single-word processing, and much goes on beyond the information given in the acoustic or orthographic tokens that enter primary sensory cortices. This requires the involvement of multiple networks with functionally nonoverlapping contributions

Abstract

Prediction in language has traditionally been studied using
simple designs in which neural responses to expected
and unexpected words are compared in a categorical
fashion. However, these designs have been contested
as being ‘prediction encouraging’, potentially exaggerating
the importance of prediction in language understanding.
A few recent studies have begun to address
these worries by using model-based approaches to probe
the effects of linguistic predictability in naturalistic stimuli
(e.g. continuous narrative). However, these studies
so far only looked at very local forms of prediction, using
models that take no more than the prior two words into
account when computing a word’s predictability. Here,
we extend this approach using a state-of-the-art neural
language model that can take roughly 500 times longer
linguistic contexts into account. Predictability estimates
fromthe neural network offer amuch better fit to EEG data
from subjects listening to naturalistic narrative than simpler
models, and reveal strong surprise responses akin to
the P200 and N400. These results show that predictability
effects in language are not a side-effect of simple designs,
and demonstrate the practical use of recent advances
in AI for the cognitive neuroscience of language.

Abstract

Human language processing involves combinatorial operations that make human communication stand out in the animal kingdom. These operations rely on a dynamic interplay between the inferior frontal and the posterior temporal cortices. Using source reconstructed magnetoencephalography, we tracked language processing in the brain, in order to investigate how individual words are interpreted when part of sentence context. The large sample size in this study (n = 68) allowed us to assess how event-related activity is associated across distinct cortical areas, by means of inter-areal co-modulation within an individual. We showed that, within 500 ms of seeing a word, the word's lexical information has been retrieved and unified with the sentence context. This does not happen in a strictly feed-forward manner, but by means of co-modulation between the left posterior temporal cortex (LPTC) and left inferior frontal cortex (LIFC), for each individual word. The co-modulation of LIFC and LPTC occurs around 400 ms after the onset of each word, across the progression of a sentence. Moreover, these core language areas are supported early on by the attentional network. The results provide a detailed description of the temporal orchestration related to single word processing in the context of ongoing language.

Abstract

How does the human brain combine a finite number of words to form an infinite variety of sentences? According to the Memory, Unification and Control (MUC) model, sentence processing requires long-range feedback from the left inferior frontal cortex (LIFC) to left posterior temporal cortex (LPTC). Single word processing however may only require feedforward propagation of semantic information from sensory regions to LPTC. Here we tested the claim that long-range feedback is required for sentence processing by reducing visual awareness of words using a masking technique. Masking disrupts feedback processing while leaving feedforward processing relatively intact. Previous studies have shown that masked single words still elicit an N400 ERP effect, a neural signature of semantic incongruency. However, whether multiple words can be combined to form a sentence under reduced levels of awareness is controversial. To investigate this issue, we performed two experiments in which we measured electroencephalography (EEG) while 40 subjects performed a masked priming task. Words were presented either successively or simultaneously, thereby forming a short sentence that could be congruent or incongruent with a target picture. This sentence condition was compared with a typical single word condition. In the masked condition we only found an N400 effect for single words, whereas in the unmasked condition we observed an N400 effect for both unmasked sentences and single words. Our findings suggest that long-range feedback processing is required for sentence processing, but not for single word processing.

Abstract

This dataset, colloquially known as the Mother Of Unification Studies (MOUS) dataset, contains multimodal neuroimaging data that has been acquired from 204 healthy human subjects. The neuroimaging protocol consisted of magnetic resonance imaging (MRI) to derive information at high spatial resolution about brain anatomy and structural connections, and functional data during task, and at rest. In addition, magnetoencephalography (MEG) was used to obtain high temporal resolution electrophysiological measurements during task, and at rest. All subjects performed a language task, during which they processed linguistic utterances that either consisted of normal or scrambled sentences. Half of the subjects were reading the stimuli, the other half listened to the stimuli. The resting state measurements consisted of 5 minutes eyes-open for the MEG and 7 minutes eyes-closed for fMRI. The neuroimaging data, as well as the information about the experimental events are shared according to the Brain Imaging Data Structure (BIDS) format. This unprecedented neuroimaging language data collection allows for the investigation of various aspects of the neurobiological correlates of language.

Abstract

Speakers are influenced by the linguistic context: hearing one syntactic alternative leads to an increased chance that the speaker will repeat this structure in the subsequent utterance (i.e., syntactic priming, or structural persistence). Top-down influences, such as whether a conversation partner (or, interlocutor) is present, may modulate the degree to which syntactic priming occurs. In the current study, we indeed show that the magnitude of syntactic alignment increases when speakers are interacting with an interlocutor as opposed to doing the experiment alone. The structural persistence effect for passive sentences is stronger in the presence of an interlocutor than when no interlocutor is present (i.e., when the participant is primed by a recording). We did not find evidence, however, that a speaker’s syntactic priming magnitude is influenced by the degree of their conversation partner’s priming magnitude. Together, these results support a mediated account of syntactic priming, in which syntactic choices are not only affected by preceding linguistic input, but also by top-down influences, such as the speakers’ communicative intent.

Abstract

Interactions between top-down and bottom-up information streams are integral to brain function but challenging to measure noninvasively. Laminar resolution, functional MRI (lfMRI) is sensitive to depth-dependent properties of the blood oxygen level-dependent (BOLD) response, which can be potentially related to top-down and bottom-up signal contributions. In this work, we used lfMRI to dissociate the top-down and bottom-up signal contributions to the left occipitotemporal sulcus (LOTS) during word reading. We further demonstrate that laminar resolution measurements could be used to identify condition-specific distributed networks on the basis of whole-brain connectivity patterns specific to the depth-dependent BOLD signal. The networks corresponded to top-down and bottom-up signal pathways targeting the LOTS during word reading. We show that reading increased the top-down BOLD signal observed in the deep layers of the LOTS and that this signal uniquely related to the BOLD response in other language-critical regions. These results demonstrate that lfMRI can reveal important patterns of activation that are obscured at standard resolution. In addition to differences in activation strength as a function of depth, we also show meaningful differences in the interaction between signals originating from different depths both within a region and with the rest of the brain. We thus show that lfMRI allows the noninvasive measurement of directed interaction between brain regions and is capable of resolving different connectivity patterns at submillimeter resolution, something previously considered to be exclusively in the domain of invasive recordings.

Abstract

A commonly held assumption in cognitive neuroscience is that, because measures of human brain function are closer to underlying biology than distal indices of behavior/cognition, they hold more promise for uncovering genetic pathways. Supporting this view is an influential fMRI-based study of sentence reading/listening by Pinel et al. (2012), who reported that common DNA variants in specific candidate genes were associated with altered neural activation in language-related regions of healthy individuals that carried them. In particular, different single-nucleotide polymorphisms (SNPs) of FOXP2 correlated with variation in task-based activation in left inferior frontal and precentral gyri, whereas a SNP at the KIAA0319/TTRAP/THEM2 locus was associated with variable functional asymmetry of the superior temporal sulcus. Here, we directly test each claim using a closely matched neuroimaging genetics approach in independent cohorts comprising 427 participants, four times larger than the original study of 94 participants. Despite demonstrating power to detect associations with substantially smaller effect sizes than those of the original report, we do not replicate any of the reported associations. Moreover, formal Bayesian analyses reveal substantial to strong evidence in support of the null hypothesis (no effect). We highlight key aspects of the original investigation, common to functional neuroimaging genetics studies, which could have yielded elevated false-positive rates. Genetic accounts of individual differences in cognitive functional neuroimaging are likely to be as complex as behavioral/cognitive tests, involving many common genetic variants, each of tiny effect. Reliable identification of true biological signals requires large sample sizes, power calculations, and validation in independent cohorts with equivalent paradigms.

SIGNIFICANCE STATEMENT A pervasive idea in neuroscience is that neuroimaging-based measures of brain function, being closer to underlying neurobiology, are more amenable for uncovering links to genetics. This is a core assumption of prominent studies that associate common DNA variants with altered activations in task-based fMRI, despite using samples (10–100 people) that lack power for detecting the tiny effect sizes typical of genetically complex traits. Here, we test central findings from one of the most influential prior studies. Using matching paradigms and substantially larger samples, coupled to power calculations and formal Bayesian statistics, our data strongly refute the original findings. We demonstrate that neuroimaging genetics with task-based fMRI should be subject to the same rigorous standards as studies of other complex traits.

Abstract

New linguistic information must be integrated into our existing language system. Using a novel experimental task that incorporates a syntactic priming paradigm into artificial language learning, we investigated how new grammatical regularities and words are learned. This innovation allowed us to control the language input the learner received, while the syntactic priming paradigm provided insight into the nature of the underlying syntactic processing machinery. The results of the present study pointed to facilitatory syntactic processing effects within the first days of learning: Syntactic and lexical priming effects revealed participants’ sensitivity to both novel words and word orders. This suggested that novel syntactic structures and their meaning (form–function mapping) can be acquired rapidly through incidental learning. More generally, our study indicated similar mechanisms for learning and processing in both artificial and natural languages, with implications for the relationship between first and second language learning.

Abstract

Semantic unification during sentence comprehension has been associated with amplitude change of the N400 in event-related potential (ERP) studies, and activation in the left inferior frontal gyrus (IFG) in functional magnetic resonance imaging (fMRI) studies. However, the specificity of this activation to semantic unification remains unknown. To more closely examine the brain processes involved in semantic unification, we employed simultaneous EEG-fMRI to time-lock the semantic unification related N400 change, and integrated trial-by-trial variation in both N400 and BOLD change beyond the condition-level BOLD change difference measured in traditional fMRI analyses. Participants read sentences in which semantic unification load was parametrically manipulated by varying cloze probability. Separately, ERP and fMRI results replicated previous findings, in that semantic unification load parametrically modulated the amplitude of N400 and cortical activation. Integrated EEG-fMRI analyses revealed a different pattern in which functional activity in the left IFG and bilateral supramarginal gyrus (SMG) was associated with N400 amplitude, with the left IFG activation and bilateral SMG activation being selective to the condition-level and trial-level of semantic unification load, respectively. By employing the EEG-fMRI integrated analyses, this study among the first sheds light on how to integrate trial-level variation in language comprehension.