The event-related potential (ERP) approach has provided a wealth of fine-grained information about the time course and the neural basis of cognitive processing events. However, in the 1980s and 1990s, an increasing number of researchers began to realize that an ERP only represents a certain part of the event-related electroencephalographic (EEG) signal. This chapter focuses on another aspect of event-related EEG activity: oscillatory EEG activity. There exists a meaningful relationship between oscillatory neuronal dynamics, on the one hand, and a wide range of cognitive processes, on the other hand. Given that the analysis of oscillatory dynamics extracts information from the EEG/magnetoencephalographic (EEG/MEG) signal that is largely lost with the traditional time-locked averaging of single trials used in the ERP approach, studying the dynamic oscillatory patterns in the EEG/MEG is at least a useful addition to the traditional ERP approach.
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Differences in the oscillatory EEG dynamics of reading open class (OC) and closed class (CC) words have previously been found (Bastiaansen et al., 2005) and are thought to reflect differences in lexical-semantic content between these word classes. In particu-lar, the theta-band (4-7 Hz) seems to play a prominent role in lexical-semantic retrieval. We tested whether this theta effect is robust in an older population of subjects. Additionally, we examined how the context of a word can modulate the oscillatory dynamics underly-ing retrieval for the two different classes of words. Older participants (mean age 55) read words presented in either syntactically correct sentences or in a scrambled order ("scram-bled sentence") while their EEG was recorded. We performed time-frequency analysis to examine how power varied based on the context or class of the word. We observed larger power decreases in the alpha (8-12 Hz) band between 200-700 ms for the OC compared to CC words, but this was true only for the scrambled sentence context. We did not observe differences in theta power between these conditions. Context exerted an effect on the alpha and low beta (13-18 Hz) bands between 0 and 700 ms. These results suggest that the previously observed word class effects on theta power changes in a younger participant sample do not seem to be a robust effect in this older population. Though this is an indi-rect comparison between studies, it may suggest the existence of aging effects on word retrieval dynamics for different populations. Additionally, the interaction between word class and context suggests that word retrieval mechanisms interact with sentence-level comprehension mechanisms in the alpha-band.
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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.
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There is growing evidence suggesting that synchronization changes in the oscillatory neuronal dynamics in the EEG or MEG reflect the transient coupling and uncoupling of functional networks related to different aspects of language comprehension. In this work, we examine how sentence-level syntactic unification operations are reflected in the oscillatory dynamics of the MEG. Participants read sentences that were either correct, contained a word category violation, or were constituted of random word sequences devoid of syntactic structure. A time-frequency analysis of MEG power changes revealed three types of effects. The first type of effect was related to the detection of a (word category) violation in a syntactically structured sentence, and was found in the alpha and gamma frequency bands. A second type of effect was maximally sensitive to the syntactic manipulations: A linear increase in beta power across the sentence was present for correct sentences, was disrupted upon the occurrence of a word category violation, and was absent in syntactically unstructured random word sequences. We therefore relate this effect to syntactic unification operations. Thirdly, we observed a linear increase in theta power across the sentence for all syntactically structured sentences. The effects are tentatively related to the building of a working memory trace of the linguistic input. In conclusion, the data seem to suggest that syntactic unification is reflected by neuronal synchronization in the lower-beta frequency band.
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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 1000. ms 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.
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Aesthetic experiences have an influence on many aspects of life. Interest in the neural basis of aesthetic experiences has grown rapidly in the past decade, and fMRI studies have identified several brain systems supporting aesthetic experiences. Work on the rapid neuronal dynamics of aesthetic experience, however, is relatively scarce. This study adds to this field by investigating the experience of being aesthetically moved by means of ERP and time–frequency analysis. Participants' EEG was recorded while they viewed a diverse set of artworks and evaluated the extent to which these artworks moved them. Results show that being aesthetically moved is associated with a sustained increase in gamma activity over centroparietal regions. In addition, alpha power over right frontocentral regions was reduced in high- and low-moving images, compared to artworks given intermediate ratings. We interpret the gamma effect as an indication for sustained savoring processes for aesthetically moving artworks compared to aesthetically less-moving artworks. The alpha effect is interpreted as an indication of increased attention for aesthetically salient images. In contrast to previous works, we observed no significant effects in any of the established ERP components, but we did observe effects at latencies longer than 1 sec. We conclude that EEG time–frequency analysis provides useful information on the neuronal dynamics of aesthetic experience.
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In this study, we used electroencephalography to investigate the influence of discourse-level semantic coherence on electrophysiological signatures of local sentence-level processing. Participants read groups of four sentences that could either form coherent stories or were semantically unrelated. For semantically coherent discourses compared to incoherent ones, the N400 was smaller at sentences 2–4, while the visual N1 was larger at the third and fourth sentences. Oscillatory activity in the beta frequency range (13–21 Hz) was higher for coherent discourses. We relate the N400 effect to a disruption of local sentence-level semantic processing when sentences are unrelated. Our beta findings can be tentatively related to disruption of local sentence-level syntactic processing, but it cannot be fully ruled out that they are instead (or also) related to disrupted local sentence-level semantic processing. We conclude that manipulating discourse-level semantic coherence does have an effect on oscillatory power related to local sentence-level processing.
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There is a growing literature investigating the relationship between oscillatory neural dynamics measured using electroencephalography (EEG) and/or magnetoencephalography (MEG), and sentence-level language comprehension. Recent proposals have suggested a strong link between predictive coding accounts of the hierarchical flow of information in the brain, and oscillatory neural dynamics in the beta and gamma frequency ranges. We propose that findings relating beta and gamma oscillations to sentence-level language comprehension might be unified under such a predictive coding account. Our suggestion is that oscillatory activity in the beta frequency range may reflect both the active maintenance of the current network configuration responsible for representing the sentence-level meaning under construction, and the top-down propagation of predictions to hierarchically lower processing levels based on that representation. In addition, we suggest that oscillatory activity in the low and middle gamma range reflect the matching of top-down predictions with bottom-up linguistic input, while evoked high gamma might reflect the propagation of bottom-up prediction errors to higher levels of the processing hierarchy. We also discuss some of the implications of this predictive coding framework, and we outline ideas for how these might be tested experimentally.
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Event-related potentials (ERPs) have been used for decades to study perception, cognition, emotion, neurological and psychiatric disorders, and lifespan development. ERPs consist of multiple components and reflect a specific neurocognitive process. In the past, there was no single source that could be consulted to learn about all the major ERP components; learning about a single ERP component required reading dozens or even hundreds of separate journal articles and book chapters. The Oxford Handbook of Event-Related Potential Components fills this void with a detailed review of the major ERP components. The book looks at the fundamental nature of ERP components, including essential information about how ERP components are defined and isolated. It explains in detail individual components, such as the N170, P300, and ERN. It further examines groups of related components within specific research domains, such as language, emotion, and memory. Finally, it analyses ERP components in special populations, including children, the elderly, nonhuman primates, and patients with neurological disorders, affective disorders, and schizophrenia.
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