Gamma EEG activity induced by semantic violation during sentence reading

Neural consequences of binaural beat stimulation on auditory sentence comprehension: an EEG study

A growing literature has shown that binaural beat (BB)-generated by dichotic presentation of slightly mismatched pure tones-improves cognition. We recently found that BB stimulation of either beta (18 Hz) or gamma (40 Hz) frequencies enhanced auditory sentence comprehension. Here, we used electroencephalography (EEG) to characterize neural oscillations pertaining to the enhanced linguistic operations following BB stimulation. Sixty healthy young adults were randomly assigned to one of three listening groups: 18-Hz BB, 40-Hz BB, or pure-tone baseline, all embedded in music. After listening to the sound for 10 min (stimulation phase), participants underwent an auditory sentence comprehension task involving spoken sentences that contained either an object or subject relative clause (task phase). During the stimulation phase, 18-Hz BB yielded increased EEG power in a beta frequency range, while 40-Hz BB did not. During the task phase, only the 18-Hz BB resulted in significantly higher accuracy and faster response times compared with the baseline, especially on syntactically more complex object-relative sentences. The behavioral improvement by 18-Hz BB was accompanied by attenuated beta power difference between object- and subject-relative sentences. Altogether, our findings demonstrate beta oscillations as a neural correlate of improved syntactic operation following BB stimulation.

Development of Gamma Oscillation during Sentence Processing in Early Adolescence: Insights into the Maturation of Semantic Processing

Children's ability to retrieve word meanings and incorporate them into sentences, along with the neural structures that support these skills, continues to evolve throughout adolescence. Theta (4-8 Hz) activity that corresponds to word retrieval in children decreases in power and becomes more localized with age. This bottom-up word retrieval is often paired with changes in gamma (31-70 Hz), which are thought to reflect semantic unification in adults. Here, we studied gamma engagement during sentence processing using EEG time-frequency in children (ages 8-15) to unravel the developmental trajectory of the gamma network during sentence processing. Children heavily rely on semantic integration for sentence comprehension, but as they mature, semantic and syntactic processing units become distinct and localized. We observed a similar developmental shift in gamma oscillation around age 11, with younger groups (8-9 and 10-11) exhibiting broadly distributed gamma activity with higher amplitudes, while older groups (12-13 and 14-15) exhibited smaller and more localized gamma activity, especially over the left central and posterior regions. We interpret these findings as support for the argument that younger children rely more heavily on semantic processes for sentence comprehension than older children. And like adults, semantic processing in children is associated with gamma activity.

Time course of EEG complexity reflects attentional engagement during listening to speech in noise

Auditory distractions are recognized to considerably challenge the quality of information encoding during speech comprehension. This study explores electroencephalography (EEG) microstate dynamics in ecologically valid, noisy settings, aiming to uncover how these auditory distractions influence the process of information encoding during speech comprehension. We examined three listening scenarios: (1) speech perception with background noise (LA), (2) focused attention on the background noise (BA), and (3) intentional disregard of the background noise (BUA). Our findings showed that microstate complexity and unpredictability increased when attention was directed towards speech compared with tasks without speech (LA > BA & BUA). Notably, the time elapsed between the recurrence of microstates increased significantly in LA compared with both BA and BUA. This suggests that coping with background noise during speech comprehension demands more sustained cognitive effort. Additionally, a two-stage time course for both microstate complexity and alpha-to-theta power ratio was observed. Specifically, in the early epochs, a lower level was observed, which gradually increased and eventually reached a steady level in the later epochs. The findings suggest that the initial stage is primarily driven by sensory processes and information gathering, while the second stage involves higher level cognitive engagement, including mnemonic binding and memory encoding.

The spatiotemporal dynamics of semantic integration in the human brain

Language depends critically on the integration of lexical information across multiple words to derive semantic concepts. Limitations of spatiotemporal resolution have previously rendered it difficult to isolate processes involved in semantic integration. We utilized intracranial recordings in epilepsy patients (n = 58) who read written word definitions. Descriptions were either referential or non-referential to a common object. Semantically referential sentences enabled high frequency broadband gamma activation (70-150 Hz) of the inferior frontal sulcus (IFS), medial parietal cortex, orbitofrontal cortex (OFC) and medial temporal lobe in the left, language-dominant hemisphere. IFS, OFC and posterior middle temporal gyrus activity was modulated by the semantic coherence of non-referential sentences, exposing semantic effects that were independent of task-based referential status. Components of this network, alongside posterior superior temporal sulcus, were engaged for referential sentences that did not clearly reduce the lexical search space by the final word. These results indicate the existence of complementary cortical mosaics for semantic integration in posterior temporal and inferior frontal cortex.

Beta and gamma binaural beats enhance auditory sentence comprehension

Binaural beats-an auditory illusion produced when two pure tones of slightly different frequencies are dichotically presented-have been shown to modulate various cognitive and psychological states. Here, we investigated the effects of binaural beat stimulation on auditory sentence processing that required interpretation of syntactic relations (Experiment 1) or an evaluation of syntactic well formedness (Experiment 2) with a large cohort of healthy young adults (N = 200). In both experiments, participants performed a language task after listening to one of four sounds (i.e., between-subject design): theta (7 Hz), beta (18 Hz), and gamma (40 Hz) binaural beats embedded in music, or the music only (baseline). In Experiment 1, 100 participants indicated the gender of a noun linked to a transitive action verb in spoken sentences containing either a subject or object-relative center-embedded clause. We found that both beta and gamma binaural beats yielded better performance, compared to the baseline, especially for syntactically more complex object-relative sentences. To determine if the binaural beat effect can be generalized to another type of syntactic analysis, we conducted Experiment 2 in which another 100 participants indicated whether or not there was a grammatical error in spoken sentences. However, none of the binaural beats yielded better performance for this task indicating that the benefit of beta and gamma binaural beats may be specific to the interpretation of syntactic relations. Together, we demonstrate, for the first time, the positive impact of binaural beats on auditory language comprehension. Both theoretical and practical implications are discussed.

Speech comprehension across time, space, frequency, and age: MEG-MVPA classification of intertrial phase coherence

Language is a key part of human cognition, essential for our well-being at all stages of our lives. Whereas many neurocognitive abilities decline with age, for language the picture is much less clear, and how exactly speech comprehension changes with ageing is still unknown. To investigate this, we employed magnetoencephalography (MEG) and recorded neuromagnetic brain responses to auditory linguistic stimuli in healthy participants of younger and older age using a passive task-free paradigm and a range of different linguistic stimulus contrasts, which enabled us to assess neural processing of spoken language at multiple levels (lexical, semantic, morphosyntactic). Using machine learning-based classification algorithms to scrutinise intertrial phase coherence of MEG responses in cortical source space, we found that patterns of oscillatory neural activity diverged between younger and older participants across several frequency bands (alpha, beta, gamma) for all tested linguistic information types. The results suggest multiple age-related changes in the brain's neurolinguistic circuits, which may be due to both healthy ageing in general and compensatory processes in particular.

Between alpha and gamma oscillations: Neural signatures of linguistic predictions and listener's attention to speaker's communication intention

When listeners hear a message produced by their interlocutor, they can predict upcoming words thanks to the sentential context and their attention can be focused on the speaker's communication intention. In two electroencephalographical (EEG) studies, we investigated the oscillatory correlates of prediction in spoken-language comprehension and how they are modulated by the listener's attention. Sentential contexts which were strongly predictive of a particular word were ended by a possessive adjective either matching the gender of the predicted word or not. Alpha, beta and gamma oscillations were studied as they were considered to play a crucial role in the predictive process. While evidence of word prediction was related to alpha fluctuations when listeners focused their attention on sentence meaning, changes in high-gamma oscillations were triggered by word prediction when listeners focused their attention on the speaker's communication intention. Independently of the endogenous attention to a level of linguistic information, the oscillatory correlates of word predictions in language comprehension were sensitive to the prosodic emphasis produced by the speaker at a late stage. These findings thus bear major implications for understanding the neural mechanisms that support predictive processing in spoken-language comprehension.

Dropping Beans or Spilling Secrets: How Idiomatic Context Bias Affects Prediction

Idioms can have both a literal interpretation and a figurative interpretation (e.g., to "kick the bucket"). Which interpretation should be activated can be disambiguated by a preceding context (e.g., "The old man was sick. He kicked the bucket."). We investigated whether the idiomatic and literal uses of idioms have different predictive properties when the idiom has been biased toward a literal or figurative sentence interpretation. EEG was recorded as participants performed a lexical decision task on idiom-final words in biased idioms and literal (compositional) sentences. Targets in idioms were identified faster in both figuratively and literally used idioms than in compositional sentences. Time-frequency analysis of a prestimulus interval revealed relatively more alpha-beta power decreases in literally than figuratively used idiomatic sequences and compositional sentences. We argue that lexico-semantic retrieval plays a larger role in literally than figuratively biased idioms, as retrieval of the word meaning is less relevant in the latter and the word form has to be matched to a template. The results are interpreted in terms of context integration and word retrieval and have implications for models of language processing and predictive processing in general.

Decoding EEG Brain Activity for Multi-Modal Natural Language Processing

Until recently, human behavioral data from reading has mainly been of interest to researchers to understand human cognition. However, these human language processing signals can also be beneficial in machine learning-based natural language processing tasks. Using EEG brain activity for this purpose is largely unexplored as of yet. In this paper, we present the first large-scale study of systematically analyzing the potential of EEG brain activity data for improving natural language processing tasks, with a special focus on which features of the signal are most beneficial. We present a multi-modal machine learning architecture that learns jointly from textual input as well as from EEG features. We find that filtering the EEG signals into frequency bands is more beneficial than using the broadband signal. Moreover, for a range of word embedding types, EEG data improves binary and ternary sentiment classification and outperforms multiple baselines. For more complex tasks such as relation detection, only the contextualized BERT embeddings outperform the baselines in our experiments, which raises the need for further research. Finally, EEG data shows to be particularly promising when limited training data is available.

EEG theta responses induced by emoji semantic violations

This study investigated emoji semantic processing by measuring changes in event-related electroencephalogram (EEG) power. The last segment of experimental sentences was designed as either words or emojis consistent or inconsistent with the sentential context. The results showed that incongruent emojis led to a conspicuous increase of theta power (4–7 Hz), while incongruent words induced a decrease. Furthermore, the theta power increase was observed at midfrontal, occipital and bilateral temporal lobes with emojis. This suggests a higher working memory load for monitoring errors, difficulty of form recognition and concept retrieval in emoji semantic processing. It implies different neuro-cognitive processes involved in the semantic processing of emojis and words.

Neuroplasticity in the phonological system: The PMN and the N400 as markers for the perception of non-native phonemic contrasts by late second language learners

Second language (L2) learners frequently encounter persistent difficulty in perceiving certain non-native sound contrasts, i.e., a phenomenon called "phonological deafness". However, if extensive L2 experience leads to neuroplastic changes in the phonological system, then the capacity to discriminate non-native phonemic contrasts should progressively improve. Such perceptual changes should be attested by modifications at the neurophysiological level. We designed an EEG experiment in which the listeners' perceptual capacities to discriminate second language phonemic contrasts influence the processing of lexical-semantic violations. Semantic congruency of critical words in a sentence context was driven by a phonemic contrast that was unique to the L2, English (e.g.,/ɪ/-/i:/, ship - sheep). Twenty-eight young adult native speakers of French with intermediate proficiency in English listened to sentences that contained either a semantically congruent or incongruent critical word (e.g., The anchor of theship/*sheepwas let down) while EEG was recorded. Three ERP effects were found to relate to increasing L2 proficiency: (1) a left frontal auditory N100 effect, (2) a smaller fronto-central phonological mismatch negativity (PMN) effect and (3) a semantic N400 effect. No effect of proficiency was found on oscillatory markers. The current findings suggest that neuronal plasticity in the human brain allows for the late acquisition of even hard-wired linguistic features such as the discrimination of phonemic contrasts in a second language. This is the first time that behavioral and neurophysiological evidence for the critical role of neural plasticity underlying L2 phonological processing and its interdependence with semantic processing has been provided. Our data strongly support the idea that pieces of information from different levels of linguistic processing (e.g., phonological, semantic) strongly interact and influence each other during online language processing.

EEG Correlates of Learning From Speech Presented in Environmental Noise

How the human brain retains relevant vocal information while suppressing irrelevant sounds is one of the ongoing challenges in cognitive neuroscience. Knowledge of the underlying mechanisms of this ability can be used to identify whether a person is distracted during listening to a target speech, especially in a learning context. This paper investigates the neural correlates of learning from the speech presented in a noisy environment using an ecologically valid learning context and electroencephalography (EEG). To this end, the following listening tasks were performed while 64-channel EEG signals were recorded: (1) attentive listening to the lectures in background sound, (2) attentive listening to the background sound presented alone, and (3) inattentive listening to the background sound. For the first task, 13 lectures of 5 min in length embedded in different types of realistic background noise were presented to participants who were asked to focus on the lectures. As background noise, multi-talker babble, continuous highway, and fluctuating traffic sounds were used. After the second task, a written exam was taken to quantify the amount of information that participants have acquired and retained from the lectures. In addition to various power spectrum-based EEG features in different frequency bands, the peak frequency and long-range temporal correlations (LRTC) of alpha-band activity were estimated. To reduce these dimensions, a principal component analysis (PCA) was applied to the different listening conditions resulting in the feature combinations that discriminate most between listening conditions and persons. Linear mixed-effect modeling was used to explain the origin of extracted principal components, showing their dependence on listening condition and type of background sound. Following this unsupervised step, a supervised analysis was performed to explain the link between the exam results and the EEG principal component scores using both linear fixed and mixed-effect modeling. Results suggest that the ability to learn from the speech presented in environmental noise can be predicted by the several components over the specific brain regions better than by knowing the background noise type. These components were linked to deterioration in attention, speech envelope following, decreased focusing during listening, cognitive prediction error, and specific inhibition mechanisms.

A Temporal Sampling Basis for Visual Processing in Developmental Dyslexia

Knowledge of oscillatory entrainment and its fundamental role in cognitive and behavioral processing has increasingly been applied to research in the field of reading and developmental dyslexia. Growing evidence indicates that oscillatory entrainment to theta frequency spoken language in the auditory domain, along with cross-frequency theta-gamma coupling, support phonological processing (i.e., cognitive encoding of linguistic knowledge gathered from speech) which is required for reading. This theory is called the temporal sampling framework (TSF) and can extend to developmental dyslexia, such that inadequate temporal sampling of speech-sounds in people with dyslexia results in poor theta oscillatory entrainment in the auditory domain, and thus a phonological processing deficit which hinders reading ability. We suggest that inadequate theta oscillations in the visual domain might account for the many magno-dorsal processing, oculomotor control and visual deficits seen in developmental dyslexia. We propose two possible models of a magno-dorsal visual correlate to the auditory TSF: (1) A direct correlate that involves "bottom-up" magnocellular oscillatory entrainment of the visual domain that occurs when magnocellular populations phase lock to theta frequency fixations during reading and (2) an inverse correlate whereby attending to text triggers "top-down" low gamma signals from higher-order visual processing areas, thereby organizing magnocellular populations to synchronize to a theta frequency to drive the temporal control of oculomotor movements and capturing of letter images at a higher frequency.

THE POWER OF NEURAL OSCILLATIONS TO INFORM SENTENCE COMPREHENSION: A LINGUISTIC PERSPECTIVE

The field of psycholinguistics is currently experiencing an explosion of interest in the analysis of neural oscillations - rhythmic brain activity synchronized at different temporal and spatial levels. Given that language comprehension relies on a myriad of processes, which are carried out in parallel in distributed brain networks, there is hope that this methodology might bring the field closer to understanding some of the more basic (spatially and temporally distributed, yet at the same time often overlapping) neural computations that support language function. In this review we discuss existing proposals linking oscillatory dynamics in different frequency bands to basic neural computations, and review relevant theories suggesting associations between band-specific oscillations and higher-level cognitive processes. More or less consistent patterns of oscillatory activity related to certain types of linguistic processing can already be derived from the evidence that has accumulated over the past few decades. The centerpiece of the current review is a synthesis of such patterns grouped by linguistic phenomenon. We restrict our review to evidence linking measures of oscillatory power to the comprehension of sentences, as well as linguistically (and/or pragmatically) more complex structures. For each grouping, we provide a brief summary and a table of associated oscillatory signatures that a psycholinguist might expect to find when employing a particular linguistic task. Summarizing across different paradigms, we conclude that a handful of basic neural oscillatory mechanisms are likely recruited in different ways and at different times for carrying out a variety of linguistic computations.

Co-registration of eye movements and neuroimaging for studying contextual predictions in natural reading

Sixteen years ago, Sereno and Rayner (2003. Measuring word recognition in reading: eye movements and event-related potentials. Trends in Cognitive Sciences, 7(11), 489-493) illustrated how "by means of review and comparison" eye movement (EM) and event-related potential (ERP) studies may advance our understanding of visual word recognition. Attempts to simultaneously record EMs and ERPs soon followed. Recently, this co-registration approach has also been transferred to fMRI and oscillatory EEG. With experimental settings close to natural reading, co-registration enables us to directly integrate insights from EM and neuroimaging studies. This should extend current experimental paradigms by moving the field towards studying sentence-level processing including effects of context and parafoveal preview. This article will introduce the basic principles and applications of co-registration and selectively review how this approach may shed light on one of the most controversially discussed issues in reading research, contextual predictions in online language processing.

Gamma Oscillatory Activity Related to Language Prediction

Using magnetoencephalography, the current study examined gamma activity associated with language prediction. Participants read high- and low-constraining sentences in which the final word of the sentence was either expected or unexpected. Although no consistent gamma power difference induced by the sentence-final words was found between the expected and unexpected conditions, the correlation of gamma power during the prediction and activation intervals of the sentence-final words was larger when the presented words matched with the prediction compared with when the prediction was violated or when no prediction was available. This suggests that gamma magnitude relates to the match between predicted and perceived words. Moreover, the expected words induced activity with a slower gamma frequency compared with that induced by unexpected words. Overall, the current study establishes that prediction is related to gamma power correlations and a slowing of the gamma frequency.

The neural oscillations of speech processing and language comprehension: state of the art and emerging mechanisms

Neural oscillations subserve a broad range of functions in speech processing and language comprehension. On the one hand, speech contains-somewhat-repetitive trains of air pressure bursts that occur at three dominant amplitude modulation frequencies, physically marking the linguistically meaningful progressions of phonemes, syllables and intonational phrase boundaries. To these acoustic events, neural oscillations of isomorphous operating frequencies are thought to synchronise, presumably resulting in an implicit temporal alignment of periods of neural excitability to linguistically meaningful spectral information on the three low-level linguistic description levels. On the other hand, speech is a carrier signal that codes for high-level linguistic meaning, such as syntactic structure and semantic information-which cannot be read from stimulus acoustics, but must be acquired during language acquisition and decoded for language comprehension. Neural oscillations subserve the processing of both syntactic structure and semantic information. Here, I synthesise a mapping from each linguistic processing domain to a unique set of subserving oscillatory mechanisms-the mapping is plausible given the role ascribed to different oscillatory mechanisms in different subfunctions of cortical information processing and faithful to the underlying electrophysiology. In sum, the present article provides an accessible and extensive review of the functional mechanisms that neural oscillations subserve in speech processing and language comprehension.

Language Prediction Is Reflected by Coupling between Frontal Gamma and Posterior Alpha Oscillations

Readers and listeners actively predict upcoming words during language processing. These predictions might serve to support the unification of incoming words into sentence context and thus rely on interactions between areas in the language network. In the current magnetoencephalography study, participants read sentences that varied in contextual constraints so that the predictability of the sentence-final words was either high or low. Before the sentence-final words, we observed stronger alpha power suppression for the highly compared with low constraining sentences in the left inferior frontal cortex, left posterior temporal region, and visual word form area. Importantly, the temporal and visual word form area alpha power correlated negatively with left frontal gamma power for the highly constraining sentences. We suggest that the correlation between alpha power decrease in temporal language areas and left prefrontal gamma power reflects the initiation of an anticipatory unification process in the language network.

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.

Brain Network Connectivity During Language Comprehension: Interacting Linguistic and Perceptual Subsystems

The dynamic neural processes underlying spoken language comprehension require the real-time integration of general perceptual and specialized linguistic information. We recorded combined electro- and magnetoencephalographic measurements of participants listening to spoken words varying in perceptual and linguistic complexity. Combinatorial linguistic complexity processing was consistently localized to left perisylvian cortices, whereas competition-based perceptual complexity triggered distributed activity over both hemispheres. Functional connectivity showed that linguistically complex words engaged a distributed network of oscillations in the gamma band (20-60 Hz), which only partially overlapped with the network supporting perceptual analysis. Both processes enhanced cross-talk between left temporal regions and bilateral pars orbitalis (BA47). The left-lateralized synchrony between temporal regions and pars opercularis (BA44) was specific to the linguistically complex words, suggesting a specific role of left frontotemporal cross-cortical interactions in morphosyntactic computations. Synchronizations in oscillatory dynamics reveal the transient coupling of functional networks that support specific computational processes in language comprehension.

Fast oscillatory dynamics during language comprehension: Unification versus maintenance and prediction?

The role of neuronal oscillations during language comprehension is not yet well understood. In this paper we review and reinterpret the functional roles of beta- and gamma-band oscillatory activity during language comprehension at the sentence and discourse level. We discuss the evidence in favor of a role for beta and gamma in unification (the unification hypothesis), and in light of mounting evidence that cannot be accounted for under this hypothesis, we explore an alternative proposal linking beta and gamma oscillations to maintenance and prediction (respectively) during language comprehension. Our maintenance/prediction hypothesis is able to account for most of the findings that are currently available relating beta and gamma oscillations to language comprehension, and is in good agreement with other proposals about the roles of beta and gamma in domain-general cognitive processing. In conclusion we discuss proposals for further testing and comparing the prediction and unification hypotheses.

Gamma oscillations as a neural signature of shifting times in narrative language

Verbs and other temporal expressions allow speakers to specify the location of events in time, as well as to move back and forth in time, shifting in a narrative between past, present and future. The referential flexibility of temporal expressions is well understood in linguistics but its neurocognitive bases remain unknown. We aimed at obtaining a neural signature of shifting times in narrative language. We recorded and analyzed event-related brain potentials (ERPs) and oscillatory responses to the adverb 'now' and to the second main verb in Punctual ('An hour ago the boy stole a candy and now he peeled the fruit') and Iterative ('The entire afternoon the boy stole candy and now he peeled the fruit') contexts. 'An hour ago' introduces a time frame that lies entirely in the past, 'now' shifts the narrative to the present, and 'peeled' shifts it back to the past. These two referential shifts in Punctual contexts are expected to leave very similar traces on neural responses. In contrast, 'The entire afternoon' specifies a time frame that may encompass past, present and future, such that both 'now' and 'peeled' are consistent with it. Here, no time shift is required. We found no difference in ERPs between Punctual and Iterative contexts either at 'now' or at the second verb. However, reference shifts modulated oscillatory signals. 'Now' and the second verb in Punctual contexts resulted in similar responses: an increase in gamma power with a left-anterior distribution. Gamma bursts were absent in Iterative contexts. We propose that gamma oscillations here reflect the binding of temporal variables to the values allowed by constraints introduced by temporal expressions in discourse.

Gamma- and theta-band synchronization during semantic priming reflect local and long-range lexical-semantic networks

Anterior and posterior brain areas are involved in the storage and retrieval of semantic representations, but it is not known how these areas dynamically interact during semantic processing. We hypothesized that long-range theta-band coherence would reflect coupling of these areas and examined the oscillatory dynamics of lexical-semantic processing using a semantic priming paradigm with a delayed letter-search task while recording subjects' EEG. Time-frequency analysis revealed facilitation of semantic processing for Related compared to Unrelated conditions, which resulted in a reduced N400 and reduced gamma power from 150 to 450ms. Moreover, we observed greater anterior-posterior theta coherence for Unrelated compared to Related conditions over the time windows 150-425ms and 600-900ms. We suggest that while gamma power reflects activation of local functional networks supporting semantic representations, theta coherence indicates dynamic coupling of anterior and posterior areas for retrieval and post-retrieval processing and possibly an interaction between semantic relatedness and working memory.

The non-stop road from concrete to abstract: high concreteness causes the activation of long-range networks

Current grounding theories propose that sensory-motor brain systems are not only modulated by the comprehension of concrete but also partly of abstract language. In order to investigate whether concrete or abstract language elicits similar or distinct brain activity, neuronal synchronization patterns were investigated by means of long-range EEG coherence analysis. Participants performed a semantic judgment task with concrete and abstract sentences. EEG coherence between distant electrodes was analyzed in various frequencies before and during sentence processing using a bivariate AR-model with time-varying parameters. The theta frequency band (3–7 Hz) reflected common and different synchronization networks related to working memory processes and memory-related lexico-semantic retrieval during processing of both sentence types. In contrast, the beta1 band (13–18 Hz) showed prominent differences between both sentence types, whereby concrete sentences were associated with higher coherence implicating a more widespread range and intensity of mental simulation processes. The gamma band (35–40 Hz) reflected the sentences' congruency and indicated the more difficult integration of incongruent final nouns into the sentence context. Most importantly, findings support the notion that different cognitive operations during sentence processing are associated with multiple brain oscillations.

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.

Brain Oscillations during Spoken Sentence Processing

Spoken sentence comprehension relies on rapid and effortless temporal integration of speech units displayed at different rates. Temporal integration refers to how chunks of information perceived at different time scales are linked together by the listener in mapping speech sounds onto meaning. The neural implementation of this integration remains unclear. This study explores the role of short and long windows of integration in accessing meaning from long samples of speech. In a cross-linguistic study, we explore the time course of oscillatory brain activity between 1 and 100 Hz, recorded using EEG, during the processing of native and foreign languages. We compare oscillatory responses in a group of Italian and Spanish native speakers while they attentively listen to Italian, Japanese, and Spanish utterances, played either forward or backward. The results show that both groups of participants display a significant increase in gamma band power (55–75 Hz) only when they listen to their native language played forward. The increase in gamma power starts around 1000 msec after the onset of the utterance and decreases by its end, resembling the time course of access to meaning during speech perception. In contrast, changes in low-frequency power show similar patterns for both native and foreign languages. We propose that gamma band power reflects a temporal binding phenomenon concerning the coordination of neural assemblies involved in accessing meaning of long samples of speech.