Publications

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.

Abstract

We hypothesized that areas in the temporal lobe that have been implicated in the phonological processing of spoken words would also be activated during the generation and phonological processing of imagined speech. We tested this hypothesis using functional magnetic resonance imaging during a behaviorally controlled task of metrical stress evaluation. Subjects were presented with bisyllabic words and had to determine the alternation of strong and weak syllables. Thus, they were required to discriminate between weak-initial words and strong-initial words. In one condition, the stimuli were presented auditorily to the subjects (by headphones). In the other condition the stimuli were presented visually on a screen and subjects were asked to imagine hearing the word. Results showed activation of the supplementary motor area, inferior frontal gyrus (Broca's area) and insula in both conditions. In the superior temporal gyrus (STG) and in the superior temporal sulcus (STS) strong activation was observed during the auditory (perceptual) condition. However, a region located in the posterior part of the STS/STG also responded during the imagery condition. No activation of this same region of the STS was observed during a control condition which also involved processing of visually presented words, but which required a semantic decision from the subject. We suggest that processing of metrical stress, with or without auditory input, relies in part on cortical interface systems located in the posterior part of STS/STG. These results corroborate behavioral evidence regarding phonological loop involvement in auditory–verbal imagery.

Abstract

Oscillatory neuronal dynamics, observed in the human electroencephalogram (EEG) during language processing, have been related to the dynamic formation of functionally coherent networks that serve the role of integrating the different sources of information needed for understanding the linguistic input. To further explore the functional role of oscillatory synchrony during language processing, we quantified event-related EEG power changes induced by the presentation of open-class (OC) words and closed-class (CC) words in a wide range of frequencies (from 1 to 30 Hz), while subjects read a short story. Word presentation induced three oscillatory components: a theta power increase (4–7 Hz), an alpha power decrease (10–12 Hz), and a beta power decrease (16–21 Hz). Whereas the alpha and beta responses showed mainly quantitative differences between the two word classes, the theta responses showed qualitative differences between OC words and CC words: A theta power increase was found over left temporal areas for OC words, but not for CC words. The left temporal theta increase may index the activation of a network involved in retrieving the lexical–semantic properties of the OC items.

Abstract

In speaking and comprehending language, word information is retrieved from memory and combined into larger units (unification). Unification operations take place in parallel at the semantic, syntactic and phonological levels of processing. This article proposes a new framework that connects psycholinguistic models to a neurobiological account of language. According to this proposal the left inferior frontal gyrus (LIFG) plays an important role in unification. Research in other domains of cognition indicates that left prefrontal cortex has the necessary neurobiological characteristics for its involvement in the unification for language. I offer here a psycholinguistic perspective on the nature of language unification and the role of LIFG.

Abstract

Children begin to talk at about age one. The vocabulary they need to do so must be built on perceptual evidence and, indeed, infants begin to recognize spoken words long before they talk. Most of the utterances infants hear, however, are continuous, without pauses between words, so constructing a vocabulary requires them to decompose continuous speech in order to extract the individual words. Here, we present electrophysiological evidence that 10-month-old infants recognize two-syllable words they have previously heard only in isolation when these words are presented anew in continuous speech. Moreover, they only need roughly the first syllable of the word to begin doing this. Thus, prelinguistic infants command a highly efficient procedure for segmentation and recognition of spoken words in the absence of an existing vocabulary, allowing them to tackle effectively the problem of bootstrapping a lexicon out of the highly variable, continuous speech signals in their environment.

Abstract

The chronic fatigue syndrome (CFS) is a disabling disorder of unknown etiology. The symptomatology of CFS (central fatigue, impaired concentration, attention and memory) suggests that this disorder could be related to alterations at the level of the central nervous system. In this study, we have used an automated and unbiased morphometric technique to test whether CFS patients display structural cerebral abnormalities. We mapped structural cerebral morphology and volume in two cohorts of CFS patients (in total 28 patients) and healthy controls (in total 28 controls) from high-resolution structural magnetic resonance images, using voxel-based morphometry. Additionally, we recorded physical activity levels to explore the relation between severity of CFS symptoms and cerebral abnormalities. We observed significant reductions in global gray matter volume in both cohorts of CFS patients, as compared to matched control participants. Moreover, the decline in gray matter volume was linked to the reduction in physical activity, a core aspect of CFS. These findings suggest that the central nervous system plays a key role in the pathophysiology of CFS and point to a new objective and quantitative tool for clinical diagnosis of this disabling disorder.

Abstract

We have used implicit motor imagery to investigate the neural correlates of motor planning independently from actual movements. Subjects were presented with drawings of left or right hands and asked to judge the hand laterality, regardless of the stimulus rotation from its upright orientation. We paired this task with a visual imagery control task, in which subjects were presented with typographical characters and asked to report whether they saw a canonical letter or its mirror image, regardless of its rotation. We measured neurovascular activity with fast event-related fMRI, distinguishing responses parametrically related to motor imagery from responses evoked by visual imagery and other task-related phenomena. By quantifying behavioral and neurovascular correlates of imagery on a trial-by-trial basis, we could discriminate between stimulusrelated, mental rotation-related, and response-related neural activity. We found that specific portions of the posterior parietal and precentral cortex increased their activity as a function of mental rotation only during the motor imagery task. Within these regions, the parietal cortex was visually responsive, whereas the dorsal precentral cortex was not. Response- but not rotation-related activity was found around the left central sulcus (putative primary motor cortex) during both imagery tasks. Our study provides novel evidence on the topography and content of movement representations in the human brain. During intended action, the posterior parietal cortex combines somatosensory and visuomotor information, whereas the dorsal premotor cortex generates the actual motor plan, and the primary motor cortex deals with movement execution. We discuss the relevance of these results in the context of current models of action planning.

Abstract

The authors examined whether people can use their knowledge of the wider discourse rapidly enough to anticipate specific upcoming words as a sentence is unfolding. In an event-related brain potential (ERP) experiment, subjects heard Dutch stories that supported the prediction of a specific noun. To probe whether this noun was anticipated at a preceding indefinite article, stories were continued with a gender-marked adjective whose suffix mismatched the upcoming noun's syntactic gender. Prediction-inconsistent adjectives elicited a differential ERP effect, which disappeared in a no-discourse control experiment. Furthermore, in self-paced reading, prediction-inconsistent adjectives slowed readers down before the noun. These findings suggest that people can indeed predict upcoming words in fluent discourse and, moreover, that these predicted words can immediately begin to participate in incremental parsing operations.

Abstract

An event-related brain potential experiment was carried out to investigate on-line syntactic processing in patients with Broca’s aphasia. Subjects were visually presented with sentences that were either syntactically correct or contained violations of word-category. Three groups of subjects were tested: Broca patients (N=11), non-aphasic patients with a right hemisphere (RH) lesion (N=9), and healthy aged-matched controls (N=15). Both control groups appeared sensitive to the violations of word-category as shown by clear P600/SPS effects. The Broca patients displayed only a very reduced and delayed P600/SPS effect. The results are discussed in the context of a lexicalist parsing model. It is concluded that Broca patients are hindered to detect on-line violations of word-category, if word class information is incomplete or delayed available.