Publications

Abstract

When perceiving the world around us, we are constantly integrating pieces of information. The integrated experience consists of more than just the sum of its parts. For example, visual scenes are defined by a collection of objects as well as the spatial relations amongst them and sentence meaning is computed based on individual word semantic but also syntactic configuration. Having quantitative models of such integrated representations can help evaluate cognitive models of both language and scene perception. Here, we focus on language, and use a behavioral measure of perceived similarity as an approximation of integrated meaning representations. We collected similarity judgments of 200 subjects rating nouns or transitive sentences through an online multiple arrangement task. We find that perceived similarity between sentences is most strongly modulated by the semantic action category of the main verb. In addition, we show how non-negative matrix factorization of similarity judgment data can reveal multiple underlying dimensions reflecting both semantic as well as relational role information. Finally, we provide an example of how similarity judgments on sentence stimuli can serve as a point of comparison for artificial neural networks models (ANNs) by comparing our behavioral data against sentence similarity extracted from three state-of-the-art ANNs. Overall, our method combining the multiple arrangement task on sentence stimuli with matrix factorization can capture relational information emerging from integration of multiple words in a sentence even in the presence of strong focus on the verb.

Abstract

Recent artificial neural networks that process natural language achieve unprecedented performance in tasks requiring sentence-level understanding. As such, they could be interesting models of the integration of linguistic information in the human brain. We review works that compare these artificial language models with human brain activity and we assess the extent to which this approach has improved our understanding of the neural processes involved in natural language comprehension. Two main results emerge. First, the neural representation of word meaning aligns with the context-dependent, dense word vectors used by the artificial neural networks. Second, the processing hierarchy that emerges within artificial neural networks broadly matches the brain, but is surprisingly inconsistent across studies. We discuss current challenges in establishing artificial neural networks as process models of natural language comprehension. We suggest exploiting the highly structured representational geometry of artificial neural networks when mapping representations to brain data.

Abstract

Background: Despite a pervasive cortico-centric view in cognitive neuroscience, subcortical structures including the thalamus have been shown to be increasingly involved in higher cognitive functions. Previous structural and functional imaging studies demonstrated cortico-thalamo-cortical loops which may support various cognitive functions including language. However, large-scale functional connectivity of the thalamus during language tasks has not been examined before. Methods: The present study employed meta-analytic connectivity modeling to identify language-related coactivation patterns of the left and right thalami. The left and right thalami were used as regions of interest to search the BrainMap functional database for neuroimaging experiments with healthy participants reporting language-related activations in each region of interest. Activation likelihood estimation analyses were then carried out on the foci extracted from the identified studies to estimate functional convergence for each thalamus. A functional decoding analysis based on the same database was conducted to characterize thalamic contributions to different language functions. Results: The results revealed bilateral frontotemporal and bilateral subcortical (basal ganglia) coactivation patterns for both the left and right thalami, and also right cerebellar coactivations for the left thalamus, during language processing. In light of previous empirical studies and theoretical frameworks, the present connectivity and functional decoding findings suggest that cortico-subcortical-cerebellar-cortical loops modulate and fine-tune information transfer within the bilateral frontotemporal cortices during language processing, especially during production and semantic operations, but also other language (e.g., syntax, phonology) and cognitive operations (e.g., attention, cognitive control). Conclusion: The current findings show that the language-relevant network extends beyond the classical left perisylvian cortices and spans bilateral cortical, bilateral subcortical (bilateral thalamus, bilateral basal ganglia) and right cerebellar regions.

Abstract

The language faculty is physically realized in the neurobiological infrastructure of the human brain. Despite significant efforts, an integrated understanding of this system remains a formidable challenge. What is missing from most theoretical accounts is a specification of the neural mechanisms that implement language function. Computational models that have been put forward generally lack an explicit neurobiological foundation. We propose a neurobiologically informed causal modeling approach which offers a framework for how to bridge this gap. A neurobiological causal model is a mechanistic description of language processing that is grounded in, and constrained by, the characteristics of the neurobiological substrate. It intends to model the generators of language behavior at the level of implementational causality. We describe key features and neurobiological component parts from which causal models can be built and provide guidelines on how to implement them in model simulations. Then we outline how this approach can shed new light on the core computational machinery for language, the long-term storage of words in the mental lexicon and combinatorial processing in sentence comprehension. In contrast to cognitive theories of behavior, causal models are formulated in the “machine language” of neurobiology which is universal to human cognition. We argue that neurobiological causal modeling should be pursued in addition to existing approaches. Eventually, this approach will allow us to develop an explicit computational neurobiology of language.

Abstract

The neural correlates of sentence production have been mostly studied with constraining task paradigms that introduce artificial task effects. In this study, we aimed to gain a better understanding of syntactic processing in spontaneous production vs. naturalistic comprehension. We extracted word-by-word metrics of phrase-structure building with top-down and bottom-up parsers that make different hypotheses about the timing of structure building. In comprehension, structure building proceeded in an integratory fashion and led to an increase in activity in posterior temporal and inferior frontal areas. In production, structure building was anticipatory and predicted an increase in activity in the inferior frontal gyrus. Newly developed production-specific parsers highlighted the anticipatory and incremental nature of structure building in production, which was confirmed by a converging analysis of the pausing patterns in speech. Overall, the results showed that the unfolding of syntactic processing diverges between speaking and listening.

Abstract

The neural infrastructure for sentence production and comprehension has been found to be mostly shared. The same regions are engaged during speaking and listening, with some differences in how strongly they activate depending on modality. In this study, we investigated how modality affects the connectivity between regions previously found to be involved in syntactic processing across modalities. We determined how constituent size and modality affected the connectivity of the pars triangularis of the left inferior frontal gyrus (LIFG) and of the left posterior temporal lobe (LPTL) with the pars opercularis of the LIFG, the anterior temporal lobe (LATL) and the rest of the brain. We found that constituent size reliably increased the connectivity across these frontal and temporal ROIs. Connectivity between the two LIFG regions and the LPTL was enhanced as a function of constituent size in both modalities, and it was upregulated in production possibly because of linearization and motor planning in the frontal cortex. The connectivity of both ROIs with the LATL was lower and only enhanced for larger constituent sizes, suggesting a contributing role of the LATL in sentence processing in both modalities. These results thus show that the connectivity among fronto-temporal regions is upregulated for syntactic structure building in both sentence production and comprehension, providing further evidence for accounts of shared neural resources for sentence-level processing across modalities.

Abstract

The neural representations for compositional processing have so far been mostly studied during sentence comprehension. In an fMRI study of sentence production, we investigated the brain representations for compositional processing during speaking. We used a rapid serial visual presentation sentence recall paradigm to elicit sentence production from the conceptual memory of an event. With voxel-wise encoding models, we probed the specificity of the compositional structure built during the production of each sentence, comparing an unstructured model of word meaning without relational information with a model that encodes abstract thematic relations and a model encoding event-specific relational structure. Whole-brain analyses revealed that sentence meaning at different levels of specificity was encoded in a large left frontal-parietal-temporal network. A comparison with semantic structures composed during the comprehension of the same sentences showed similarly distributed brain activity patterns. An ROI analysis over left fronto-temporal language parcels showed that event-specific relational structure above word-specific information was encoded in the left inferior frontal gyrus. Overall, we found evidence for the encoding of sentence meaning during sentence production in a distributed brain network and for the encoding of event-specific semantic structures in the left inferior frontal gyrus.

Abstract

Language is inherently multimodal. In spoken languages, combined spoken and visual signals (e.g., co-speech gestures) are an integral part of linguistic structure and language representation. This requires an extension of the parallel architecture, which needs to include the visual signals concomitant to speech. We present the evidence for the multimodality of language. In addition, we propose that distributional semantics might provide a format for integrating speech and co-speech gestures in a common semantic representation.

Abstract

How we combine minimal linguistic units into larger structures remains an unresolved topic in neuroscience. Language processing involves the abstract construction of ‘vertical’ and ‘horizontal’ information simultaneously (e.g., phrase structure, morphological agreement), but previous paradigms have been constrained in isolating only one type of composition and have utilized poor spatiotemporal resolution. Using intracranial recordings, we report multiple experiments designed to separate phrase structure from morphosyntactic agreement. Epilepsy patients (n = 10) were presented with auditory two-word phrases grouped into pseudoword-verb (‘trab run’) and pronoun-verb either with or without Person agreement (‘they run’ vs. ‘they runs’). Phrase composition and Person violations both resulted in significant increases in broadband high gamma activity approximately 300ms after verb onset in posterior middle temporal gyrus (pMTG) and posterior superior temporal sulcus (pSTS), followed by inferior frontal cortex (IFC) at 500ms. While sites sensitive to only morphosyntactic violations were distributed, those sensitive to both composition types were generally confined to pSTS/pMTG and IFC. These results indicate that posterior temporal cortex shows the earliest sensitivity for hierarchical linguistic structure across multiple dimensions, providing neural resources for distinct windows of composition. This region is comprised of sparsely interwoven heterogeneous constituents that afford cortical search spaces for dissociable syntactic relations.

Abstract

During communication in real-life settings, our brain often needs to integrate auditory and visual information, and at the same time actively focus on the relevant sources of information, while ignoring interference from irrelevant events. The interaction between integration and attention processes remains poorly understood. Here, we use rapid invisible frequency tagging (RIFT) and magnetoencephalography (MEG) to investigate how attention affects auditory and visual information processing and integration, during multimodal communication. We presented human participants (male and female) with videos of an actress uttering action verbs (auditory; tagged at 58 Hz) accompanied by two movie clips of hand gestures on both sides of fixation (attended stimulus tagged at 65 Hz; unattended stimulus tagged at 63 Hz). Integration difficulty was manipulated by a lower-order auditory factor (clear/degraded speech) and a higher-order visual semantic factor (matching/mismatching gesture). We observed an enhanced neural response to the attended visual information during degraded speech compared to clear speech. For the unattended information, the neural response to mismatching gestures was enhanced compared to matching gestures. Furthermore, signal power at the intermodulation frequencies of the frequency tags, indexing non-linear signal interactions, was enhanced in left frontotemporal and frontal regions. Focusing on LIFG (Left Inferior Frontal Gyrus), this enhancement was specific for the attended information, for those trials that benefitted from integration with a matching gesture. Together, our results suggest that attention modulates audiovisual processing and interaction, depending on the congruence and quality of the sensory input.

Abstract

Words are not processed in isolation; instead, they are commonly embedded in phrases and sentences. The sentential context influences the perception and processing of a word. However, how this is achieved by brain processes and whether predictive mechanisms underlie this process remain a debated topic. Here, we employed an experimental paradigm in which we orthogonalized sentence context constraints and predictive validity, which was defined as the ratio of congruent to incongruent sentence endings within the experiment. While recording electroencephalography, participants read sentences with three levels of sentential context constraints (high, medium, and low). Participants were also separated into two groups that differed in their ratio of valid congruent to incongruent target words that could be predicted from the sentential context. For both groups, we investigated modulations of alpha power before, and N400 amplitude modulations after target word onset. The results reveal that the N400 amplitude gradually decreased with higher context constraints and cloze probability. In contrast, alpha power was not significantly affected by context constraint. Neither the N400 nor alpha power were significantly affected by changes in predictive validity.

Abstract

There is evidence from both behavior and brain activity that the way information is structured, through the use of focus, can up-regulate processing of focused constituents, likely to give prominence to the relevant aspects of the input. This is hypothesized to be universal, regardless of the different ways in which languages encode focus. In order to test this universalist hypothesis, we need to go beyond the more familiar linguistic strategies for marking focus, such as by means of intonation or specific syntactic structures (e.g., it-clefts). Therefore, in this study, we examine Makhuwa-Enahara, a Bantu language spoken in northern Mozambique, which uniquely marks focus through verbal conjugation. The participants were presented with sentences that consisted of either a semantically anomalous constituent or a semantically nonanomalous constituent. Moreover, focus on this particular constituent could be either present or absent. We observed a consistent pattern: Focused information generated a more negative N400 response than the same information in nonfocus position. This demonstrates that regardless of how focus is marked, its consequence seems to result in an upregulation of processing of information that is in focus.

Abstract

In Swedish, words are associated with either of two pitch contours known as Accent 1 and Accent 2. Using a psychometric test, we investigated how listeners judge pitch accent violations while interpreting discourse. Forty native speakers of Central Swedish were presented with auditory dialogues, where test words were appropriately or inappropriately accented in a given context, and asked to judge the correctness of sentences containing the test words. Data indicated a statistically significant effect of wrong accent pattern on the correctness judgment. Both Accent 1 and Accent 2 violations interfered with the coherent interpretation of discourse and were judged as incorrect by the listeners. Moreover, there was a statistically significant difference in the perceived correctness between the accent patterns. Accent 2 violations led to a lower correctness score compared to Accent 1 violations, indicating that the listeners were more sensitive to pitch accent violations in Accent 2 words than in Accent 1 words. This result is in line with the notion that Accent 2 is marked and lexically represented in Central Swedish. Taken together, these findings indicate that listeners use both Accent 1 and Accent 2 to arrive at the correct interpretation of the linguistic input, while assigning varying degrees of relevance to them depending on their markedness.

Abstract

It has long been recognised that phrases and sentences are organised hierarchically, but many computational models of language treat them as sequences of words without computing constituent structure. Against this background, we conducted two experiments which showed that participants interpret ambiguous noun phrases, such as second blue ball, in terms of their abstract hierarchical structure rather than their linear surface order. When a neural network model was tested on this task, it could simulate such “hierarchical” behaviour. However, when we changed the training data such that they were not entirely unambiguous anymore, the model stopped generalising in a human-like way. It did not systematically generalise to novel items, and when it was trained on ambiguous trials, it strongly favoured the linear interpretation. We argue that these models should be endowed with a bias to make generalisations over hierarchical structure in order to be cognitively adequate models of human language.

Abstract

Recent research has established that cortical activity “tracks” the presentation rate of syntactic phrases in continuous speech, even though phrases are abstract units that do not have direct correlates in the acoustic signal. We investigated whether cortical tracking of phrase structures is modulated by the extent to which these structures compositionally determine meaning. To this end, we recorded electroencephalography (EEG) of 38 native speakers who listened to naturally spoken Dutch stimuli in different conditions, which parametrically modulated the degree to which syntactic structure and lexical semantics determine sentence meaning. Tracking was quantified through mutual information between the EEG data and either the speech envelopes or abstract annotations of syntax, all of which were filtered in the frequency band corresponding to the presentation rate of phrases (1.1–2.1 Hz). Overall, these mutual information analyses showed stronger tracking of phrases in regular sentences than in stimuli whose lexical-syntactic content is reduced, but no consistent differences in tracking between sentences and stimuli that contain a combination of syntactic structure and lexical content. While there were no effects of compositional meaning on the degree of phrase-structure tracking, analyses of event-related potentials elicited by sentence-final words did reveal meaning-induced differences between conditions. Our findings suggest that cortical tracking of structure in sentences indexes the internal generation of this structure, a process that is modulated by the properties of its input, but not by the compositional interpretation of its output.

Abstract

Listening to speech is difficult in noisy environments, and is even harder when the interfering noise consists of intelligible speech as compared to unintelligible sounds. This suggests that the competing linguistic information interferes with the neural processing of target speech. Interference could either arise from a degradation of the neural representation of the target speech, or from increased representation of distracting speech that enters in competition with the target speech. We tested these alternative hypotheses using magnetoencephalography (MEG) while participants listened to a target clear speech in the presence of distracting noise-vocoded speech. Crucially, the distractors were initially unintelligible but became more intelligible after a short training session. Results showed that the comprehension of the target speech was poorer after training than before training. The neural tracking of target speech in the delta range (1–4 Hz) reduced in strength in the presence of a more intelligible distractor. In contrast, the neural tracking of distracting signals was not significantly modulated by intelligibility. These results suggest that the presence of distracting speech signals degrades the linguistic representation of target speech carried by delta oscillations.

Abstract

The neurobiology of sentence production has been largely understudied compared to the neurobiology of sentence comprehension, due to difficulties with experimental control and motion-related artifacts in neuroimaging. We studied the neural response to constituents of increasing size and specifically focused on the similarities and differences in the production and comprehension of the same stimuli. Participants had to either produce or listen to stimuli in a gradient of constituent size based on a visual prompt. Larger constituent sizes engaged the left inferior frontal gyrus (LIFG) and middle temporal gyrus (LMTG) extending to inferior parietal areas in both production and comprehension, confirming that the neural resources for syntactic encoding and decoding are largely overlapping. An ROI analysis in LIFG and LMTG also showed that production elicited larger responses to constituent size than comprehension and that the LMTG was more engaged in comprehension than production, while the LIFG was more engaged in production than comprehension. Finally, increasing constituent size was characterized by later BOLD peaks in comprehension but earlier peaks in production. These results show that syntactic encoding and parsing engage overlapping areas, but there are asymmetries in the engagement of the language network due to the specific requirements of production and comprehension.

Abstract

Understanding spoken language requires transforming ambiguous acoustic streams into a hierarchy of representations, from phonemes to meaning. It has been suggested that the brain uses prediction to guide the interpretation of incoming input. However, the role of prediction in language processing remains disputed, with disagreement about both the ubiquity and representational nature of predictions. Here, we address both issues by analyzing brain recordings of participants listening to audiobooks, and using a deep neural network (GPT-2) to precisely quantify contextual predictions. First, we establish that brain responses to words are modulated by ubiquitous predictions. Next, we disentangle model-based predictions into distinct dimensions, revealing dissociable neural signatures of predictions about syntactic category (parts of speech), phonemes, and semantics. Finally, we show that high-level (word) predictions inform low-level (phoneme) predictions, supporting hierarchical predictive processing. Together, these results underscore the ubiquity of prediction in language processing, showing that the brain spontaneously predicts upcoming language at multiple levels of abstraction.

Abstract

Typical adults read remarkably quickly. Such fast reading is facilitated by brain processes that are sensitive to both word frequency and contextual constraints. It is debated as to whether these attributes have additive or interactive effects on language processing in the brain. We investigated this issue by analysing existing magnetoencephalography data from 99 participants reading intact and scrambled sentences. Using a cross-validated model comparison scheme, we found that lexical frequency predicted the word-by-word elicited MEG signal in a widespread cortical network, irrespective of sentential context. In contrast, index (ordinal word position) was more strongly encoded in sentence words, in left front-temporal areas. This confirms that frequency influences word processing independently of predictability, and that contextual constraints affect word-by-word brain responses. With a conservative multiple comparisons correction, only the interaction between lexical frequency and surprisal survived, in anterior temporal and frontal cortex, and not between lexical frequency and entropy, nor between lexical frequency and index. However, interestingly, the uncorrected index*frequency interaction revealed an effect in left frontal and temporal cortex that reversed in time and space for intact compared to scrambled sentences. Finally, we provide evidence to suggest that, in sentences, lexical frequency and predictability may independently influence early (<150ms) and late stages of word processing, but interact during later stages of word processing (>150-250ms), thus helping to converge previous contradictory eye-tracking and electrophysiological literature. Current neuro-cognitive models of reading would benefit from accounting for these differing effects of lexical frequency and predictability on different stages of word processing.

Abstract

Traditional experiments indicate that prediction is important for efficient speech processing. In three virtual reality visual world paradigm experiments, we tested whether such findings hold in naturalistic settings (Experiment 1) and provided novel insights into whether disfluencies in speech (repairs/hesitations) inform one’s predictions in rich environments (Experiments 2–3). Experiment 1 supports that listeners predict upcoming speech in naturalistic environments, with higher proportions of anticipatory target fixations in predictable compared to unpredictable trials. In Experiments 2–3, disfluencies reduced anticipatory fixations towards predicted referents, compared to conjunction (Experiment 2) and fluent (Experiment 3) sentences. Unexpectedly, Experiment 2 provided no evidence that participants made new predictions from a repaired verb. Experiment 3 provided novel findings that fixations towards the speaker increase upon hearing a hesitation, supporting current theories of how hesitations influence sentence processing. Together, these findings unpack listeners’ use of visual (objects/speaker) and auditory (speech/disfluencies) information when predicting upcoming words.

Abstract

Introduction: Mood is a constant in our daily life and can permeate all levels of cognition. We examined whether and how mood influences the processing of discourse content that is relatively neutral and not loaded with emotion. During discourse processing, readers have to constantly strike a balance between what they know in long term memory and what the current discourse is about. Our general hypothesis is that mood states would affect this balance. We hypothesized that readers in a positive mood would rely more on default world knowledge, whereas readers in a negative mood would be more inclined to analyze the details in the current discourse.

Methods: Participants were put in a positive and a negative mood via film clips, one week apart. In each session, after mood manipulation, they were presented with sentences in discourse materials. We created sentences such as “With the lights on you can see...” that end with critical words (CWs) “more” or “less”, where general knowledge supports “more”, not “less”. We then embedded each of these sentences in a wider discourse that does/does not support the CWs (a story about driving in the night vs. stargazing). EEG was recorded throughout.

Results: The results showed that first, mood manipulation was successful in that there was a significant mood difference between sessions. Second, mood did not modulate the N400 effects. Participants in both moods detected outright semantic violations and allowed world knowledge to be overridden by discourse context. Third, mood modulated the LPC (Late Positive Component) effects, distributed in the frontal region. In negative moods, the LPC was sensitive to one-level violation. That is, CWs that were supported by only world knowledge, only discourse, and neither, elicited larger frontal LPCs, in comparison to the condition where CWs were supported by both world knowledge and discourse.

Discussion: These results suggest that mood does not influence all processes involved in discourse processing. Specifically, mood does not influence lexical-semantic retrieval (N400), but it does influence elaborative processes for sensemaking (P600) during discourse processing. These results advance our understanding of the impact and time course of mood on discourse.

Abstract

The ability to comprehend phrases is an essential integrative property of the brain. Here we evaluate the neural processes that enable the transition from single word processing to a minimal compositional scheme. Previous research has reported conflicting timing effects of composition, and disagreement persists with respect to inferior frontal and posterior temporal contributions. To address these issues, 19 patients (10 male, 19 female) implanted with penetrating depth or surface subdural intracranial electrodes heard auditory recordings of adjective-noun, pseudoword-noun and adjective-pseudoword phrases and judged whether the phrase matched a picture. Stimulus-dependent alterations in broadband gamma activity, low frequency power and phase-locking values across the language-dominant left hemisphere were derived. This revealed a mosaic located on the lower bank of the posterior superior temporal sulcus (pSTS), in which closely neighboring cortical sites displayed exclusive sensitivity to either lexicality or phrase structure, but not both. Distinct timings were found for effects of phrase composition (210–300 ms) and pseudoword processing (approximately 300–700 ms), and these were localized to neighboring electrodes in pSTS. The pars triangularis and temporal pole encoded anticipation of composition in broadband low frequencies, and both regions exhibited greater functional connectivity with pSTS during phrase composition. Our results suggest that the pSTS is a highly specialized region comprised of sparsely interwoven heterogeneous constituents that encodes both lower and higher level linguistic features. This hub in pSTS for minimal phrase processing may form the neural basis for the human-specific computational capacity for forming hierarchically organized linguistic structures.

Abstract

This study investigated two questions. One is: To what degree is sentence processing beyond single words independent of the input modality (speech vs. reading)? The second question is: Which parts of the network recruited by both modalities is sensitive to syntactic complexity? These questions were investigated by having more than 200 participants read or listen to well-formed sentences or series of unconnected words. A largely left-hemisphere frontotemporoparietal network was found to be supramodal in nature, i.e., independent of input modality. In addition, the left inferior frontal gyrus (LIFG) and the left posterior middle temporal gyrus (LpMTG) were most clearly associated with left-branching complexity. The left anterior temporal lobe (LaTL) showed the greatest sensitivity to sentences that differed in right-branching complexity. Moreover, activity in LIFG and LpMTG increased from sentence onset to end, in parallel with an increase of the left-branching complexity. While LIFG, bilateral anterior temporal lobe, posterior MTG, and left inferior parietal lobe (LIPL) all contribute to the supramodal unification processes, the results suggest that these regions differ in their respective contributions to syntactic complexity related processing. The consequences of these findings for neurobiological models of language processing are discussed.

Abstract

Vocal learning, the ability to produce modified vocalizations via learning from acoustic signals, is a key trait in the evolution of speech. While extensively studied in songbirds, mammalian models for vocal learning are rare. Bats present a promising study system given their gregarious natures, small size, and the ability of some species to be maintained in captive colonies. We utilize the pale spear-nosed bat (Phyllostomus discolor) and report advances in establishing this species as a tractable model for understanding vocal learning. We have taken an interdisciplinary approach, aiming to provide an integrated understanding across genomics (Part I), neurobiology (Part II), and transgenics (Part III). In Part I, we generated new, high-quality genome annotations of coding genes and noncoding microRNAs to facilitate functional and evolutionary studies. In Part II, we traced connections between auditory-related brain regions and reported neuroimaging to explore the structure of the brain and gene expression patterns to highlight brain regions. In Part III, we created the first successful transgenic bats by manipulating the expression of FoxP2, a speech-related gene. These interdisciplinary approaches are facilitating a mechanistic and evolutionary understanding of mammalian vocal learning and can also contribute to other areas of investigation that utilize P. discolor or bats as study species.

Abstract

While syntactic reanalysis has been extensively investigated in psycholinguistics, comparatively little is known about reanalysis in the semantic domain. We used event-related brain potentials (ERPs) to keep track of semantic processes involved in understanding short narratives such as ‘The girl was writing a letter when her friend spilled coffee on the paper’. We hypothesize that these sentences are interpreted in two steps: (1) when the progressive clause is processed, a discourse model is computed in which the goal state (a complete letter) is predicted to hold; (2) when the subordinate clause is processed, the initial representation is recomputed to the effect that, in the final discourse structure, the goal state is not satisfied. Critical sentences evoked larger sustained anterior negativities (SANs) compared to controls, starting around 400 ms following the onset of the sentence-final word, and lasting for about 400 ms. The amplitude of the SAN was correlated with the frequency with which participants, in an offline probe-selection task, responded that the goal state was not attained. Our results raise the possibility that the brain supports some form of non-monotonic recomputation to integrate information which invalidates previously held assumptions.

Abstract

An influential hypothesis regarding the neural basis of the mental lexicon is that semantic representations are neurally implemented as distributed networks carrying sensory, motor and/or more abstract functional information. This work investigates whether the semantic properties of words partly determine the topography of such networks. Subjects performed a visual lexical decision task while their EEG was recorded. We compared the EEG responses to nouns with either visual semantic properties (VIS, referring to colors and shapes) or with auditory semantic properties (AUD, referring to sounds). A time–frequency analysis of the EEG revealed power increases in the theta (4–7 Hz) and lower-beta (13–18 Hz) frequency bands, and an early power increase and subsequent decrease for the alpha (8–12 Hz) band. In the theta band we observed a double dissociation: temporal electrodes showed larger theta power increases in the AUD condition, while occipital leads showed larger theta responses in the VIS condition. The results support the notion that semantic representations are stored in functional networks with a topography that reflects the semantic properties of the stored items, and provide further evidence that oscillatory brain dynamics in the theta frequency range are functionally related to the retrieval of lexical semantic information.

Abstract

Several studies have reported an association between dyslexia and implicit learning deficits. It has been suggested that the weakness in implicit learning observed in dyslexic individuals may be related to sequential processing and implicit sequence learning. In the present article, we review the current literature on implicit learning and dyslexia. We describe a novel, forced-choice structural "mere exposure" artificial grammar learning paradigm and characterize this paradigm in normal readers in relation to the standard grammaticality classification paradigm. We argue that preference classification is a more optimal measure of the outcome of implicit acquisition since in the preference version participants are kept completely unaware of the underlying generative mechanism, while in the grammaticality version, the subjects have, at least in principle, been informed about the existence of an underlying complex set of rules at the point of classification (but not during acquisition). On the basis of the "mere exposure effect," we tested the prediction that the development of preference will correlate with the grammaticality status of the classification items. In addition, we examined the effects of grammaticality (grammatical/nongrammatical) and associative chunk strength (ACS; high/low) on the classification tasks (preference/grammaticality). Using a balanced ACS design in which the factors of grammaticality (grammatical/nongrammatical) and ACS (high/low) were independently controlled in a 2 × 2 factorial design, we confirmed our predictions. We discuss the suitability of this task for further investigation of the implicit learning characteristics in dyslexia.

Abstract

Claims that neuroscientific data do not contribute to our understanding of psychological functions have been made recently. Here I argue that these criticisms are solely based on an analysis of functional magnetic resonance imaging (fMRI) studies. However, fMRI is only one of the methods in the toolkit of cognitive neuroscience. I provide examples from research on event-related brain potentials (ERPs) that have contributed to our understanding of the cognitive architecture of human language functions. In addition, I provide evidence of (possible) contributions from fMRI measurements to our understanding of the functional architecture of language processing. Finally, I argue that a neurobiology of human language that integrates information about the necessary genetic and neural infrastructures will allow us to answer certain questions that are not answerable if all we have is evidence from behavior.

Abstract

This paper focuses on what electrical and magnetic recordings of human brain activity reveal about spoken language understanding. Based on the high temporal resolution of these recordings, a fine-grained temporal profile of different aspects of spoken language comprehension can be obtained. Crucial aspects of speech comprehension are lexical access, selection and semantic integration. Results show that for words spoken in context, there is no ‘magic moment’ when lexical selection ends and semantic integration begins. Irrespective of whether words have early or late recognition points, semantic integration processing is initiated before words can be identified on the basis of the acoustic information alone. Moreover, for one particular event-related brain potential (ERP) component (the N400), equivalent impact of sentence- and discourse-semantic contexts is observed. This indicates that in comprehension, a spoken word is immediately evaluated relative to the widest interpretive domain available. In addition, this happens very quickly. Findings are discussed that show that often an unfolding word can be mapped onto discourse-level representations well before the end of the word. Overall, the time course of the ERP effects is compatible with the view that the different information types (lexical, syntactic, phonological, pragmatic) are processed in parallel and influence the interpretation process incrementally, that is as soon as the relevant pieces of information are available. This is referred to as the immediacy principle.

Abstract

In an event-related potential experiment with Chinese discourses as material, we investigated how and when accentuation influences spoken discourse comprehension in relation to the different information states of the critical words. These words could either provide new or old information. It was shown that variation of accentuation influenced the amplitude of the N400, with a larger amplitude for accented than deaccented words. In addition, there was an interaction between accentuation and information state. The N400 amplitude difference between accented and deaccented new information was smaller than that between accented and deaccented old information. The results demonstrate that, during spoken discourse comprehension, listeners rapidly extract the semantic consequences of accentuation in relation to the previous discourse context. Moreover, our results show that the N400 amplitude can be larger for correct (new,accented words) than incorrect (new, deaccented words) information. This, we argue, proves that the N400 does not react to semantic anomaly per se, but rather to semantic integration load, which is higher for new information.

Abstract

Beim Sprechen und beim Sprachverstehen findet man die Wortbedeutung im Gedächtnis auf und kombiniert sie zu größeren Einheiten (Unifikation). Solche Unifikations-Operationen laufen auf unterschiedlichen Ebenen der Sprachverarbeitung ab. In diesem Beitrag wird ein Rahmen vorgeschlagen, in dem psycholinguistische Modelle mit neurobiologischer Sprachbetrachtung in Verbindung gebracht werden. Diesem Vorschlag zufolge spielt der linke inferiore frontale Gyrus (LIFG) eine bedeutende Rolle bei der Unifi kation

Abstract

Functional imaging studies have demonstrated involvement of the anterior temporal cortex in sentence comprehension. It is unclear, however, whether the anterior temporal cortex is essential for this function.We studied two aspects of sentence comprehension, namely syntactic and prosodic comprehension in temporal lobe epilepsy patients who were candidates for resection of the anterior temporal lobe. Methods: Temporal lobe epilepsy patients (n = 32) with normal (left) language dominance were tested on syntactic and prosodic comprehension before and after removal of the anterior temporal cortex. The prosodic comprehension test was also compared with performance of healthy control subjects (n = 47) before surgery. Results: Overall, temporal lobe epilepsy patients did not differ from healthy controls in syntactic and prosodic comprehension before surgery. They did perform less well on an affective prosody task. Post-operative testing revealed that syntactic and prosodic comprehension did not change after removal of the anterior temporal cortex. Discussion: The unchanged performance on syntactic and prosodic comprehension after removal of the anterior temporal cortex suggests that this area is not indispensable for sentence comprehension functions in temporal epilepsy patients. Potential implications for the postulated role of the anterior temporal lobe in the healthy brain are discussed.

Abstract

Chronic fatigue syndrome (CFS) is a disabling disorder, characterized by persistent or relapsing fatigue. Recent studies have detected a decrease in cortical grey matter volume in patients with CFS, but it is unclear whether this cerebral atrophy constitutes a cause or a consequence of the disease. Cognitive behavioural therapy (CBT) is an effective behavioural intervention for CFS, which combines a rehabilitative approach of a graded increase in physical activity with a psychological approach that addresses thoughts and beliefs about CFS which may impair recovery. Here, we test the hypothesis that cerebral atrophy may be a reversible state that can ameliorate with successful CBT. We have quantified cerebral structural changes in 22 CFS patients that underwent CBT and 22 healthy control participants. At baseline, CFS patients had significantly lower grey matter volume than healthy control participants. CBT intervention led to a significant improvement in health status, physical activity and cognitive performance. Crucially, CFS patients showed a significant increase in grey matter volume, localized in the lateral prefrontal cortex. This change in cerebral volume was related to improvements in cognitive speed in the CFS patients. Our findings indicate that the cerebral atrophy associated with CFS is partially reversed after effective CBT. This result provides an example of macroscopic cortical plasticity in the adult human brain, demonstrating a surprisingly dynamic relation between behavioural state and cerebral anatomy. Furthermore, our results reveal a possible neurobiological substrate of psychotherapeutic treatment.

Abstract

Background: Growing evidence for overlap in the syntactic processing of language and music in non-brain-damaged individuals leads to the question of whether aphasic individuals with grammatical comprehension problems in language also have problems processing structural relations in music.

Aims: The current study sought to test musical syntactic processing in individuals with Broca's aphasia and grammatical comprehension deficits, using both explicit and implicit tasks.

Methods & Procedures: Two experiments were conducted. In the first experiment 12 individuals with Broca's aphasia (and 14 matched controls) were tested for their sensitivity to grammatical and semantic relations in sentences, and for their sensitivity to musical syntactic (harmonic) relations in chord sequences. An explicit task (acceptability judgement of novel sequences) was used. The second experiment, with 9 individuals with Broca's aphasia (and 12 matched controls), probed musical syntactic processing using an implicit task (harmonic priming).

Outcomes & Results: In both experiments the aphasic group showed impaired processing of musical syntactic relations. Control experiments indicated that this could not be attributed to low-level problems with the perception of pitch patterns or with auditory short-term memory for tones.

Conclusions: The results suggest that musical syntactic processing in agrammatic aphasia deserves systematic investigation, and that such studies could help probe the nature of the processing deficits underlying linguistic agrammatism. Methodological suggestions are offered for future work in this little-explored area.

Abstract

We used simultaneously recorded EEG and fMRI to investigate in which areas the BOLD signal correlates with frontal theta power changes, while subjects were quietly lying resting in the scanner with their eyes open. To obtain a reliable estimate of frontal theta power we applied ICA on band-pass filtered (2–9 Hz) EEG data. For each subject we selected the component that best matched the mid-frontal scalp topography associated with the frontal theta rhythm. We applied a time-frequency analysis on this component and used the time course of the frequency bin with the highest overall power to form a regressor that modeled spontaneous fluctuations in frontal theta power. No significant positive BOLD correlations with this regressor were observed. Extensive negative correlations were observed in the areas that together form the default mode network. We conclude that frontal theta activity can be seen as an EEG index of default mode network activity.

Abstract

The discovery of mirror neurons in macaques and of a similar system in humans has provided a new and fertile neurobiological ground for rooting a variety of cognitive faculties. Automatic sensorimotor resonance has been invoked as the key elementary process accounting for disparate (dys)functions, like imitation, ideomotor apraxia, autism, and schizophrenia. In this paper, we provide a critical appraisal of three of these claims that deal with the relationship between language and the motor system. Does language comprehension require the motor system? Was there an evolutionary switch from manual gestures to speech as the primary mode of language? Is human communication explained by automatic sensorimotor resonances? A positive answer to these questions would open the tantalizing possibility of bringing language and human communication within the fold of the motor system. We argue that the available empirical evidence does not appear to support these claims, and their theoretical scope fails to account for some crucial features of the phenomena they are supposed to explain. Without denying the enormous importance of the discovery of mirror neurons, we highlight the limits of their explanatory power for understanding language and communication.

Abstract

The human capacity to implicitly acquire knowledge of structured sequences has recently been investigated in artificial grammar learning using functional magnetic resonance imaging. It was found that the left inferior frontal cortex (IFC; Brodmann's area (BA) 44/45) was related to classification performance. The objective of this study was to investigate whether the IFC (BA 44/45) is causally related to classification of artificial syntactic structures by means of an off-line repetitive transcranial magnetic stimulation (rTMS) paradigm. We manipulated the stimulus material in a 2 × 2 factorial design with grammaticality status and local substring familiarity as factors. The participants showed a reliable effect of grammaticality on classification of novel items after 5days of exposure to grammatical exemplars without performance feedback in an implicit acquisition task. The results show that rTMS of BA 44/45 improves syntactic classification performance by increasing the rejection rate of non-grammatical items and by shortening reaction times of correct rejections specifically after left-sided stimulation. A similar pattern of results is observed in FMRI experiments on artificial syntactic classification. These results suggest that activity in the inferior frontal region is causally related to artificial syntax processing.

Abstract

When do listeners take into account who the speaker is? We asked people to listen to utterances whose content sometimes did not match inferences based on the identity of the speaker (e.g., “If only I looked like Britney Spears” in a male voice, or “I have a large tattoo on my back” spoken with an upper-class accent). Event-related brain responses revealed that the speaker's identity is taken into account as early as 200–300 msec after the beginning of a spoken word, and is processed by the same early interpretation mechanism that constructs sentence meaning based on just the words. This finding is difficult to reconcile with standard “Gricean” models of sentence interpretation in which comprehenders initially compute a local, context-independent meaning for the sentence (“semantics”) before working out what it really means given the wider communicative context and the particular speaker (“pragmatics”). Because the observed brain response hinges on voice-based and usually stereotype-dependent inferences about the speaker, it also shows that listeners rapidly classify speakers on the basis of their voices and bring the associated social stereotypes to bear on what is being said. According to our event-related potential results, language comprehension takes very rapid account of the social context, and the construction of meaning based on language alone cannot be separated from the social aspects of language use. The linguistic brain relates the message to the speaker immediately.

Abstract

The large majority of humankind is more or less fluent in 2 or even more languages. This raises the fundamental question how the language network in the brain is organized such that the correct target language is selected at a particular occasion. Here we present behavioral and functional magnetic resonance imaging data showing that bilingual processing leads to language conflict in the bilingual brain even when the bilinguals’ task only required target language knowledge. This finding demonstrates that the bilingual brain cannot avoid language conflict, because words from the target and nontarget languages become automatically activated during reading. Importantly, stimulus-based language conflict was found in brain regions in the LIPC associated with phonological and semantic processing, whereas response-based language conflict was only found in the pre-supplementary motor area/anterior cingulate cortex when language conflict leads to response conflicts.

Abstract

Understanding language always occurs within a situational context and, therefore, often implies combining streams of information from different domains and modalities. One such combination is that of spoken language and visual information, which are perceived together in a variety of ways during everyday communication. Here we investigate whether and how words and pictures differ in terms of their neural correlates when they are integrated into a previously built-up sentence context. This is assessed in two experiments looking at the time course (measuring event-related potentials, ERPs) and the locus (using functional magnetic resonance imaging, fMRI) of this integration process. We manipulated the ease of semantic integration of word and/or picture to a previous sentence context to increase the semantic load of processing. In the ERP study, an increased semantic load led to an N400 effect which was similar for pictures and words in terms of latency and amplitude. In the fMRI study, we found overlapping activations to both picture and word integration in the left inferior frontal cortex. Specific activations for the integration of a word were observed in the left superior temporal cortex. We conclude that despite obvious differences in representational format, semantic information coming from pictures and words is integrated into a sentence context in similar ways in the brain. This study adds to the growing insight that the language system incorporates (semantic) information coming from linguistic and extralinguistic domains with the same neural time course and by recruitment of overlapping brain areas.

Abstract

Language is often perceived together with visual information. This raises the question on how the brain integrates information conveyed in visual and/or linguistic format during spoken language comprehension. In this study we investigated the dynamics of semantic integration of visual and linguistic information by means of time-frequency analysis of the EEG signal. A modified version of the N400 paradigm with either a word or a picture of an object being semantically incongruous with respect to the preceding sentence context was employed. Event-Related Potential (ERP) analysis showed qualitatively similar N400 effects for integration of either word or picture. Time-frequency analysis revealed early specific decreases in alpha and gamma band power for linguistic and visual information respectively. We argue that these reflect a rapid context-based analysis of acoustic (word) or visual (picture) form information. We conclude that although full semantic integration of linguistic and visual information occurs through a common mechanism, early differences in oscillations in specific frequency bands reflect the format of the incoming information and, importantly, an early context-based detection of its congruity with respect to the preceding language context

Abstract

In the present study, event-related brain potentials (ERP) were recorded to investigate the role of pitch accent and lexical tone in spoken discourse comprehension. Chinese was used as material to explore the potential difference in the nature and time course of brain responses to sentence meaning as indicated by pitch accent and to lexical meaning as indicated by tone. In both cases, the pitch contour of critical words was varied. The results showed that both inconsistent pitch accent and inconsistent lexical tone yielded N400 effects, and there was no interaction between them. The negativity evoked by inconsistent pitch accent had the some topography as that evoked by inconsistent lexical tone violation, with a maximum over central–parietal electrodes. Furthermore, the effect for the combined violations was the sum of effects for pure pitch accent and pure lexical tone violation. However, the effect for the lexical tone violation appeared approximately 90 ms earlier than the effect of the pitch accent violation. It is suggested that there might be a correspondence between the neural mechanism underlying pitch accent and lexical meaning processing in context. They both reflect the integration of the current information into a discourse context, independent of whether the current information was sentence meaning indicated by accentuation, or lexical meaning indicated by tone. In addition, lexical meaning was processed earlier than sentence meaning conveyed by pitch accent during spoken language processing.