Integration or predictability? A further specification of the functional role of gamma oscillations in language comprehension

Language deficits in schizophrenia and autism as related oscillatory connectomopathies: An evolutionary account

Schizophrenia (SZ) and autism spectrum disorders (ASD) are characterised by marked language deficits, but it is not clear how these arise from gene mutations associated with the disorders. Our goal is to narrow the gap between SZ and ASD and, ultimately, give support to the view that they represent abnormal (but related) ontogenetic itineraries for the human faculty of language. We will focus on the distinctive oscillatory profiles of the SZ and ASD brains, in turn using these insights to refine our understanding of how the brain implements linguistic computations by exploring a novel model of linguistic feature-set composition. We will argue that brain rhythms constitute the best route to interpreting language deficits in both conditions and mapping them to neural dysfunction and risk alleles of the genes. Importantly, candidate genes for SZ and ASD are overrepresented among the gene sets believed to be important for language evolution. This translational effort may help develop an understanding of the aetiology of SZ and ASD and their high prevalence among modern populations.

Alpha and theta band dynamics related to sentential constraint and word expectancy

Despite strong evidence for prediction during language comprehension, the underlying mechanisms, and the extent to which they are specific to language, remain unclear. Re-analyzing an ERP study, we examined responses in the time-frequency domain to expected and unexpected (but plausible) words in strongly and weakly constraining sentences, and found results similar to those reported in nonverbal domains. Relative to expected words, unexpected words elicited an increase in the theta band (4-7 Hz) in strongly constraining contexts, suggesting the involvement of control processes to deal with the consequences of having a prediction disconfirmed. Prior to critical word onset, strongly constraining sentences exhibited a decrease in the alpha band (8-12 Hz) relative to weakly constraining sentences, suggesting that comprehenders can take advantage of predictive sentence contexts to prepare for the input. The results suggest that the brain recruits domain-general preparation and control mechanisms when making and assessing predictions during sentence comprehension.

Oscillatory Brain Dynamics during Sentence Reading: A Fixation-Related Spectral Perturbation Analysis

The present study investigated oscillatory brain dynamics during self-paced sentence-level processing. Participants read fully correct sentences, sentences containing a semantic violation and "sentences" in which the order of the words was randomized. At the target word level, fixations on semantically unrelated words elicited a lower-beta band (13-18 Hz) desynchronization. At the sentence level, gamma power (31-55 Hz) increased linearly for syntactically correct sentences, but not when the order of the words was randomized. In the 300-900 ms time window after sentence onsets, theta power (4-7 Hz) was greater for syntactically correct sentences as compared to sentences where no syntactic structure was preserved (random words condition). We interpret our results as conforming with a recently formulated predictive-coding framework for oscillatory neural dynamics during sentence-level language comprehension. Additionally, we discuss how our results relate to previous findings with serial visual presentation vs. self-paced reading.

Neural activity during sentence processing as reflected in theta, alpha, beta, and gamma oscillations

We used magnetoencephalography (MEG) to explore the spatiotemporal dynamics of neural oscillations associated with sentence processing in 102 participants. We quantified changes in oscillatory power as the sentence unfolded, and in response to individual words in the sentence. For words early in a sentence compared to those late in the same sentence, we observed differences in left temporal and frontal areas, and bilateral frontal and right parietal regions for the theta, alpha, and beta frequency bands. The neural response to words in a sentence differed from the response to words in scrambled sentences in left-lateralized theta, alpha, beta, and gamma. The theta band effects suggest that a sentential context facilitates lexical retrieval, and that this facilitation is stronger for words late in the sentence. Effects in the alpha and beta bands may reflect the unification of semantic and syntactic information, and are suggestive of easier unification late in a sentence. The gamma oscillations are indicative of predicting the upcoming word during sentence processing. In conclusion, changes in oscillatory neuronal activity capture aspects of sentence processing. Our results support earlier claims that language (sentence) processing recruits areas distributed across both hemispheres, and extends beyond the classical language regions.

Developmental differences in beta and theta power during sentence processing

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Changes in ERPs and oscillatory dynamic occur during auditory sentence processing.

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Adults are significantly better at identifying syntactic errors compared to children.

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Adults display a significant P600 effect and theta/beta power decrease.

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Children display a significant N400 effect and smaller decrease in theta/beta power.

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These findings suggest syntactic processing skills are still developing by age 12.

Although very young children process ongoing language quickly and effortlessly, research indicates that they continue to improve and mature in their language skills through adolescence. This prolonged development may be related to differing engagement of semantic and syntactic processes. This study used event related potentials and time frequency analysis of EEG to identify developmental differences in neural engagement as children (ages 10–12) and adults performed an auditory verb agreement grammaticality judgment task. Adults and children revealed very few differences in comprehending grammatically correct sentences. When identifying grammatical errors, however, adults displayed widely distributed beta and theta power decreases that were significantly less pronounced in children. Adults also demonstrated a significant P600 effect, while children exhibited an apparent N400 effect. Thus, when identifying subtle grammatical errors in real time, adults display greater neural activation that is traditionally associated with syntactic processing whereas children exhibit greater activity more commonly associated with semantic processing. These findings support previous claims that the cognitive and neural underpinnings of syntactic processing are still developing in adolescence, and add to them by more clearly identifying developmental changes in the neural oscillations underlying grammatical processing.

Ways of making-sense: Local gamma synchronization reveals differences between semantic processing induced by music and language

Similar to linguistic stimuli, music can also prime the meaning of a subsequent word. However, it is so far unknown what is the brain dynamics underlying the semantic priming effect induced by music, and its relation to language. To elucidate these issues, we compare the brain oscillatory response to visual words that have been semantically primed either by a musical excerpt or by an auditory sentence. We found that semantic violation between music-word pairs triggers a classical ERP N400, and induces a sustained increase of long-distance theta phase synchrony, along with a transient increase of local gamma activity. Similar results were observed after linguistic semantic violation except for gamma activity, which increased after semantic congruence between sentence-word pairs. Our findings indicate that local gamma activity is a neural marker that signals different ways of semantic processing between music and language, revealing the dynamic and self-organized nature of the semantic processing.

Increased Resting-State Gamma-Band Connectivity in First-Episode Schizophrenia

BACKGROUND

Schizophrenia has long been suggested to represent a disorder with prominent neural dysconnectivity. Gamma-band oscillations are highly relevant in this context, due both to their proposed involvement in neuronal synchronization and to their association with neurotransmitter systems relevant for schizophrenia. Several task-related studies have confirmed reduced power and synchronization of gamma-band oscillations in schizophrenia, but it has been suggested that these findings might not apply to the resting state. The present study aimed to investigate resting-state gamma-band connectivity in patients with schizophrenia.

METHODS

Sixty-four channel resting-state electroencephalography (eyes closed) was recorded in 22 patients with first-episode schizophrenia and 22 healthy controls matched for age and gender. Orthogonalized power envelope correlation was used as a measure of connectivity across 80 cortical regions at 40 Hz. Mean connectivity at each region was compared across groups using the nonparametric randomization approach. Additionally, the network-based statistic was applied to identify affected networks in patients.

RESULTS

Patients displayed increased mean functional gamma-band connectivity compared to controls in the left rolandic operculum. Network-based analyses indicated increased connectivity in patients within a strongly lateralized network consisting mainly of left inferior frontal/orbitofrontal, lateral and medial temporal, and inferior parietal areas. Within this network, gamma-band connectivity was higher in patients with low positive and disorganization symptom levels.

CONCLUSIONS

The present study provides a link between resting-state gamma-band connectivity and the core symptoms of schizophrenia. The observed findings are different than those reported by task-related studies, suggesting that resting-state studies might reveal new aspects in the pathophysiology of schizophrenia.

Frequency-based Segregation of Syntactic and Semantic Unification during Online Sentence Level Language Comprehension

During sentence level language comprehension, semantic and syntactic unification are functionally distinct operations. Nevertheless, both recruit roughly the same brain areas (spatially overlapping networks in the left frontotemporal cortex) and happen at the same time (in the first few hundred milliseconds after word onset). We tested the hypothesis that semantic and syntactic unification are segregated by means of neuronal synchronization of the functionally relevant networks in different frequency ranges: gamma (40 Hz and up) for semantic unification and lower beta (10-20 Hz) for syntactic unification. EEG power changes were quantified as participants read either correct sentences, syntactically correct though meaningless sentences (syntactic prose), or sentences that did not contain any syntactic structure (random word lists). Other sentences contained either a semantic anomaly or a syntactic violation at a critical word in the sentence. Larger EEG gamma-band power was observed for semantically coherent than for semantically anomalous sentences. Similarly, beta-band power was larger for syntactically correct sentences than for incorrect ones. These results confirm the existence of a functional dissociation in EEG oscillatory dynamics during sentence level language comprehension that is compatible with the notion of a frequency-based segregation of syntactic and semantic unification.

The effects of selective attention and speech acoustics on neural speech-tracking in a multi-talker scene

Attending to one speaker in multi-speaker situations is challenging. One neural mechanism proposed to underlie the ability to attend to a particular speaker is phase-locking of low-frequency activity in auditory cortex to speech's temporal envelope ("speech-tracking"), which is more precise for attended speech. However, it is not known what brings about this attentional effect, and specifically if it reflects enhanced processing of the fine structure of attended speech. To investigate this question we compared attentional effects on speech-tracking of natural versus vocoded speech which preserves the temporal envelope but removes the fine structure of speech. Pairs of natural and vocoded speech stimuli were presented concurrently and participants attended to one stimulus and performed a detection task while ignoring the other stimulus. We recorded magnetoencephalography (MEG) and compared attentional effects on the speech-tracking response in auditory cortex. Speech-tracking of natural, but not vocoded, speech was enhanced by attention, whereas neural tracking of ignored speech was similar for natural and vocoded speech. These findings suggest that the more precise speech-tracking of attended natural speech is related to processing its fine structure, possibly reflecting the application of higher-order linguistic processes. In contrast, when speech is unattended its fine structure is not processed to the same degree and thus elicits less precise speech-tracking more similar to vocoded speech.

Oscillatory brain dynamics associated with the automatic processing of emotion in words

This study examines the automaticity of processing the emotional aspects of words, and characterizes the oscillatory brain dynamics that accompany this automatic processing. Participants read emotionally negative, neutral and positive nouns while performing a color detection task in which only perceptual-level analysis was required. Event-related potentials and time frequency representations were computed from the concurrently measured EEG. Negative words elicited a larger P2 and a larger late positivity than positive and neutral words, indicating deeper semantic/evaluative processing of negative words. In addition, sustained alpha power suppressions were found for the emotional compared to neutral words, in the time range from 500 to 1000ms post-stimulus. These results suggest that sustained attention was allocated to the emotional words, whereas the attention allocated to the neutral words was released after an initial analysis. This seems to hold even when the emotional content of the words is task-irrelevant.

Item parameters dissociate between expectation formats: a regression analysis of time-frequency decomposed EEG data

During language comprehension, semantic contextual information is used to generate expectations about upcoming items. This has been commonly studied through the N400 event-related potential (ERP), as a measure of facilitated lexical retrieval. However, the associative relationships in multi-word expressions (MWE) may enable the generation of a categorical expectation, leading to lexical retrieval before target word onset. Processing of the target word would thus reflect a target-identification mechanism, possibly indexed by a P3 ERP component. However, given their time overlap (200-500 ms post-stimulus onset), differentiating between N400/P3 ERP responses (averaged over multiple linguistically variable trials) is problematic. In the present study, we analyzed EEG data from a previous experiment, which compared ERP responses to highly expected words that were placed either in a MWE or a regular non-fixed compositional context, and to low predictability controls. We focused on oscillatory dynamics and regression analyses, in order to dissociate between the two contexts by modeling the electrophysiological response as a function of item-level parameters. A significant interaction between word position and condition was found in the regression model for power in a theta range (~7-9 Hz), providing evidence for the presence of qualitative differences between conditions. Power levels within this band were lower for MWE than compositional contexts when the target word appeared later on in the sentence, confirming that in the former lexical retrieval would have taken place before word onset. On the other hand, gamma-power (~50-70 Hz) was also modulated by predictability of the item in all conditions, which is interpreted as an index of a similar "matching" sub-step for both types of contexts, binding an expected representation and the external input.

Early anticipation lies behind the speed of response in conversation

RTs in conversation, with average gaps of 200 msec and often less, beat standard RTs, despite the complexity of response and the lag in speech production (600 msec or more). This can only be achieved by anticipation of timing and content of turns in conversation, about which little is known. Using EEG and an experimental task with conversational stimuli, we show that estimation of turn durations are based on anticipating the way the turn would be completed. We found a neuronal correlate of turn-end anticipation localized in ACC and inferior parietal lobule, namely a beta-frequency desynchronization as early as 1250 msec, before the end of the turn. We suggest that anticipation of the other's utterance leads to accurately timed transitions in everyday conversations.

Prediction in the service of comprehension: modulated early brain responses to omitted speech segments

Speech signals are often compromised by disruptions originating from external (e.g., masking noise) or internal (e.g., inaccurate articulation) sources. Speech comprehension thus entails detecting and replacing missing information based on predictive and restorative neural mechanisms. The present study targets predictive mechanisms by investigating the influence of a speech segment's predictability on early, modality-specific electrophysiological responses to this segment's omission. Predictability was manipulated in simple physical terms in a single-word framework (Experiment 1) or in more complex semantic terms in a sentence framework (Experiment 2). In both experiments, final consonants of the German words Lachs ([laks], salmon) or Latz ([lats], bib) were occasionally omitted, resulting in the syllable La ([la], no semantic meaning), while brain responses were measured with multi-channel electroencephalography (EEG). In both experiments, the occasional presentation of the fragment La elicited a larger omission response when the final speech segment had been predictable. The omission response occurred ∼125-165 msec after the expected onset of the final segment and showed characteristics of the omission mismatch negativity (MMN), with generators in auditory cortical areas. Suggestive of a general auditory predictive mechanism at work, this main observation was robust against varying source of predictive information or attentional allocation, differing between the two experiments. Source localization further suggested the omission response enhancement by predictability to emerge from left superior temporal gyrus and left angular gyrus in both experiments, with additional experiment-specific contributions. These results are consistent with the existence of predictive coding mechanisms in the central auditory system, and suggestive of the general predictive properties of the auditory system to support spoken word recognition.

What changes in neural oscillations can reveal about developmental cognitive neuroscience: language development as a case in point

EEG is a primary method for studying temporally precise neuronal processes across the lifespan. Most of this work focuses on event related potentials (ERPs); however, using time-locked time frequency analysis to decompose the EEG signal can identify and distinguish multiple changes in brain oscillations underlying cognition (Bastiaansen et al., 2010). Further this measure is thought to reflect changes in inter-neuronal communication more directly than ERPs (Nunez and Srinivasan, 2006). Although time frequency has elucidated cognitive processes in adults, applying it to cognitive development is still rare. Here, we review the basics of neuronal oscillations, some of what they reveal about adult cognitive function, and what little is known relating to children. We focus on language because it develops early and engages complex cortical networks. Additionally, because time frequency analysis of the EEG related to adult language comprehension has been incredibly informative, using similar methods with children will shed new light on current theories of language development and increase our understanding of how neural processes change over the lifespan. Our goal is to emphasize the power of this methodology and encourage its use throughout developmental cognitive neuroscience.

Long-range neural synchronization supports fast and efficient reading: EEG correlates of processing expected words in sentences

Word reading is heavily influenced by the information provided by previous context. In this study, we analyzed the neurophysiological bases of sentence reading through the EEG activity elicited during reading the same word embedded in differently constraining contexts: a) a low-constraining context; b) a high-constraining semantic compositional context; c) a high-constraining collocational context in which the item was in final position of a multi-word fixed-order expression. Cloze-probability of the two high-constraining contexts was equated. Before reading the target word we observed increased EEG gamma phase synchronization for the high-constraining compositional context and increased EEG theta synchronization for the collocational context (both compared to the low-constraining condition). After reading the target word we observed increased frontal positive EEG evoked activity (~220ms) for the high-constraining compositional context but an even earlier (~120ms) effect for the high-constraining collocational condition that was distributed over the scalp. A positive correlation was found only between the increased theta synchronization and the early EEG effect for the high-constraining collocational condition. Results indicate that long-range frontal-occipital interactions in the theta band - indexing working memory operations - support early visual-orthographic analysis of an incoming stimulus (such as the expected word); gamma-phase synchronization better represents binding operations between feed-forward activation and matching feedback. These data suggest that internal linguistic knowledge stored in long-term memory - if unambiguously pre-activated - supports the low-level perceptual processes involved in reading.

Context-dependent Semantic Processing in the Human Brain: Evidence from Idiom Comprehension

Language comprehension involves activating word meanings and integrating them with the sentence context. This study examined whether these routines are carried out even when they are theoretically unnecessary, namely, in the case of opaque idiomatic expressions, for which the literal word meanings are unrelated to the overall meaning of the expression. Predictable words in sentences were replaced by a semantically related or unrelated word. In literal sentences, this yielded previously established behavioral and electrophysiological signatures of semantic processing: semantic facilitation in lexical decision, a reduced N400 for semantically related relative to unrelated words, and a power increase in the gamma frequency band that was disrupted by semantic violations. However, the same manipulations in idioms yielded none of these effects. Instead, semantic violations elicited a late positivity in idioms. Moreover, gamma band power was lower in correct idioms than in correct literal sentences. It is argued that the brain's semantic expectancy and literal word meaning integration operations can, to some extent, be “switched off” when the context renders them unnecessary. Furthermore, the results lend support to models of idiom comprehension that involve unitary idiom representations.