Publications

Abstract

In this study, we compared the performance of a long short-term memory (LSTM) neural network to the behavior of human participants on a language task that requires hierarchically structured knowledge. We show that humans interpret ambiguous noun phrases, such as second blue ball, in line with their hierarchical constituent structure. LSTMs, instead, only do
so after unambiguous training, and they do not systematically generalize to novel items. Overall, the results of our simulations indicate that a model can behave hierarchically without relying on hierarchical constituent structure.

Abstract

The endeavor to understand the human brain has seen more progress in the last few decades than in the previous two millennia. Still, our understanding of how the human brain relates to behavior in the real world and how this link is modulated by biological, social, and environmental factors is limited. To address this, we designed the Healthy Brain Study (HBS), an interdisciplinary, longitudinal, cohort study based on multidimensional, dynamic assessments in both the laboratory and the real world. Here, we describe the rationale and design of the currently ongoing HBS. The HBS is examining a population-based sample of 1,000 healthy participants (age 30-39) who are thoroughly studied across an entire year. Data are collected through cognitive, affective, behavioral, and physiological testing, neuroimaging, bio-sampling, questionnaires, ecological momentary assessment, and real-world assessments using wearable devices. These data will become an accessible resource for the scientific community enabling the next step in understanding the human brain and how it dynamically and individually operates in its bio-social context. An access procedure to the collected data and bio-samples is in place and published on https://www.healthybrainstudy.nl/en/data-and-methods.

https://www.trialregister.nl/trial/7955

Abstract

The ability to predict upcoming actions is a hallmark of cognition. It remains unclear, however, whether the predictive behaviour observed in controlled lab environments generalises to rich, everyday settings. In four virtual reality experiments, we tested whether a well-established marker of linguistic prediction (anticipatory eye movements) replicated when increasing the naturalness of the paradigm by means of immersing participants in naturalistic scenes (Experiment 1), increasing the number of distractor objects (Experiment 2), modifying the proportion of predictable noun-referents (Experiment 3), and manipulating the location of referents relative to the joint attentional space (Experiment 4). Robust anticipatory eye movements were observed for Experiments 1–3. The anticipatory effect disappeared, however, in Experiment 4. Our findings suggest that predictive processing occurs in everyday communication if the referents are situated in the joint attentional space. Methodologically, our study confirms that ecological validity and experimental control may go hand-in-hand in the study of human predictive behaviour.

Abstract

The present ERP study assessed whether grammatical aspect is used as a cue in online event comprehension, in particular when reading about events in which an object is visually changed. While perfective aspect cues holistic event representations, including an event's endpoint, progressive aspect highlights intermediate phases of an event. In a 2 × 3 design, participants read SVO sentences describing a change-of-state event (e.g., to chop an onion), with grammatical Aspect manipulated (perfective “chopped” vs progressive “was chopping”). Thereafter, they saw a Picture of an object either having undergone substantial state-change (SC; a chopped onion), no state-change (NSC; an onion in its original state) or an unrelated object (U; a cactus, acting as control condition). Their task was to decide whether the object in the Picture was mentioned in the sentence. We focused on N400 modulation, with ERPs time-locked to picture onset. U pictures elicited an N400 response as expected, suggesting detection of categorical mismatches in object type. For SC and NSC pictures, a whole-head follow-up analysis revealed a P300, implying people were engaged in detailed evaluation of pictures of matching objects. SC pictures received most positive responses overall. Crucially, there was an interaction of Aspect and Picture: SC pictures resulted in a higher amplitude P300 after sentences in the perfective compared to the progressive. Thus, while the perfective cued for a holistic event representation, including the resultant state of the affected object (i.e., the chopped onion) constraining object representations online, the progressive defocused event completion and object-state change. Grammatical aspect thus guided online event comprehension by cueing the visual representation(s) of an object's state.

Abstract

Brain connectivity plays a major role in the encoding, transfer, and
integration of sensory information. Interregional synchronization
of neural oscillations in the γ-frequency band has been suggested
as a key mechanism underlying perceptual integration. In a recent
study, we found evidence for this hypothesis showing that the
modulation of interhemispheric oscillatory synchrony by means of
bihemispheric high-density transcranial alternating current stimulation
(HD-TACS) affects binaural integration of dichotic acoustic features.
Here, we aimed to establish a direct link between oscillatory
synchrony, effective brain connectivity, and binaural integration.
We experimentally manipulated oscillatory synchrony (using bihemispheric
γ-TACS with different interhemispheric phase lags) and
assessed the effect on effective brain connectivity and binaural integration
(as measured with functional MRI and a dichotic listening
task, respectively). We found that TACS reduced intrahemispheric
connectivity within the auditory cortices and antiphase (interhemispheric
phase lag 180°) TACS modulated connectivity between the
two auditory cortices. Importantly, the changes in intra- and interhemispheric
connectivity induced by TACS were correlated with
changes in perceptual integration. Our results indicate that γ-band
synchronization between the two auditory cortices plays a functional
role in binaural integration, supporting the proposed role
of interregional oscillatory synchrony in perceptual integration.

Abstract

Linguistic labels exert a particularly strong top-down influence on perception. The potency of this influence has been ascribed to their ability to evoke category-diagnostic features of concepts. In doing this, they facilitate the formation of a perceptual template concordant with those features, effectively biasing perceptual activation towards the labelled category. In this study, we employ a cueing paradigm with moving, point-light stimuli across three experiments, in order to examine how the number of biological motion features (form and kinematics) encoded in lexical cues modulates the efficacy of lexical top-down influence on perception. We find that the magnitude of lexical influence on biological motion perception rises as a function of the number of biological motion-relevant features carried by both cue and target. When lexical cues encode multiple biological motion features, this influence is robust enough to mislead participants into reporting erroneous percepts, even when a masking level yielding high performance is used.

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.