Lexical prediction in the aging brain: The effects of predictiveness and congruency on the N400 ERP component

Examining the role and neural electrophysiological mechanisms of adjective cues in size judgment

Numerous influential theories have attempted to elucidate the relationship between language and thought. The debate persists on whether language and thought are distinct entities or if language is deeply embedded in individual cognitive processes. This study employs adjective cues combined with a mental imagery size judgment task as an experimental paradigm, utilizing neurophysiological techniques to preliminarily explore the role of adjectives in size judgment tasks and their underlying neurophysiological mechanisms. Findings reveal that performance is best when adjectives are congruent with the size of the object, with EEG microstate results indicating strong activity in Class A, related to language networks under this condition. Additionally, when adjectives conflict with object size, the discovery of the Ni component suggests that individuals monitor and inhibit the conflict between adjectives and object size, leading to decreased task performance in this condition. Moreover, when object size is ambiguous, individuals' size judgments do not benefit significantly from clear adjective cues. Event-related potentials and EEG microstate results suggest that under this condition, top-down cognitive resources are recruited more extensively. In conclusion, language plays a more crucial role in simpler judgment tasks; as tasks become more complex, judgment processes engage a greater number of distributed brain regions to collaborate, while the language system remains active. This study provides initial cognitive neuroscience evidence for understanding the relationship between language and simple forms of thought, offering preliminary insights for future investigations into the connection between language and thought.

Tailoring Semantic Interventions for Older Adults: Task-Focused and Person-Centered Approaches

In this narrative review, we explore the latest evidence on semantic interventions for older adults, including both prevention and rehabilitation/remediation efforts, discussing them particularly in the context of dementia. Cognitive interventions vary in their level of structure, encompassing standardized (task-focused tasks) and unstandardized tasks (person-centered tasks). These interventions also differ in their target: rehabilitation or prevention. Addressing semantic knowledge/semantic memory/semantics is important, primarily because its efficiency impacts other cognitive domains. Semantic tasks are commonly included in preventive and rehabilitation programs, typically as standardized tasks with pre-defined semantic referents. On the other hand, person-centered approaches introduce personally relevant semantics, allowing patients to share thoughts and experiences with expressive language. Although these approaches offer benefits beyond cognitive improvement, their lack of structure may pose challenges. Our question club (CQ) program blends structured activities with personally relevant semantics, aiming to harness the advantages of both methods. Additionally, in this narrative review, we discuss future challenges and directions in the field of semantic interventions.

A mapping-knowledge-domain analysis of ERP research on language processing

The event-related potentials (ERPs) technique represents a newly developed methodology in cognitive neuroscience and has significantly extended the scope of linguistic studies, offering valuable insights into cognitive processes related to language. While extant literature reviews have addressed specific facets of ERP research on language processing, a comprehensive overview of this domain remains notably absent. This study aims to fill this gap by pioneering a mapping-knowledge-domain analysis of ERP research on language processing using Citespace, a visualized bibliometric software. The current study conducted a meticulous survey and evaluation of relevant literature extracted from the Web of Science core collection. Initially, this study outlines the spatial-temporal distribution within this domain. Subsequently, employing document co-citation analysis, keyword co-occurrence analysis, cluster analysis, and burst detection analysis, this study delved deeper into the research landscape. Findings reveal that key areas in ERP research on language processing predominantly focus on sentence comprehension, reading comprehension, and mismatch negativity, with notable emphasis on topics such as speech perception, temporal dynamics, and working memory. The current study advocates for future investigations to concentrate on larger linguistic units, explore the integration of ERP components and their functional significance, and scrutinize individual differences among participants. These directions are imperative for advancing the understanding of language processing mechanisms.

Effects of age on the time course of syntactic priming in Chinese sentence production: an ERP study

Using a syntactic priming task, we investigated the time course of syntactic encoding in Chinese sentence production and compared encoding patterns between younger and older adults. Participants alternately read sentence descriptions and overtly described pictures, while event-related potentials (ERPs) were recorded. We manipulated the abstract prime structure (active or passive) as well as the lexical overlap of the prime and the target (verb overlap or no overlap). The syntactic choice results replicated classical abstract priming and lexical boost effects in both younger and older adults. However, when production latency was taken into account, the speed benefit from syntactic repetition differed between the two age groups. Meanwhile, preferred priming facilitated production in both age groups, whereas nonpreferred priming inhibited production in the older group. For electroencephalography, an earlier effect of syntactic repetition and a later effect of lexical overlap showed a two-stage pattern of syntactic encoding. Older adults also showed a more delayed and interactive encoding pattern than younger adults, indicating a greater reliance on lexical information. These results are illustrative of the two-stage competition and residual activation models.

Prediction during language comprehension: what is next?

Prediction is often regarded as an integral aspect of incremental language comprehension, but little is known about the cognitive architectures and mechanisms that support it. We review studies showing that listeners and readers use all manner of contextual information to generate multifaceted predictions about upcoming input. The nature of these predictions may vary between individuals owing to differences in language experience, among other factors. We then turn to unresolved questions which may guide the search for the underlying mechanisms. (i) Is prediction essential to language processing or an optional strategy? (ii) Are predictions generated from within the language system or by domain-general processes? (iii) What is the relationship between prediction and memory? (iv) Does prediction in comprehension require simulation via the production system? We discuss promising directions for making progress in answering these questions and for developing a mechanistic understanding of prediction in language.

Reduction or enhancement? Repetition effects on early brain potentials during visual word recognition are frequency dependent

Most studies on word repetition have demonstrated that repeated stimuli yield reductions in brain activity. Despite the well-known repetition reduction effect, some literature reports repetition enhancements in electroencephalogram (EEG) activities. However, although studies of object and face recognition have consistently demonstrated both repetition reduction and enhancement effects, the results of repetition enhancement effects were not consistent in studies of visual word recognition. Therefore, the present study aimed to further investigate the repetition effect on the P200, an early event-related potential (ERP) component that indexes the coactivation of lexical candidates during visual word recognition. To achieve a high signal-to-noise ratio, EEG signals were decomposed into various modes by using the Hilbert-Huang transform. Results demonstrated a repetition enhancement effect on P200 activity in alpha-band oscillation and that lexicality and orthographic neighborhood size would influence the magnitude of the repetition enhancement effect on P200. These findings suggest that alpha activity during visual word recognition might reflect the coactivation of orthographically similar words in the early stages of lexical processing. Meantime, there were repetition reduction effects on ERP activities in theta-delta band oscillation, which might index that the lateral inhibition between lexical candidates would be omitted in repetition.

Heuristic interpretation as rational inference: A computational model of the N400 and P600 in language processing

Much inquiry in psycholinguistics has focused on evidence from the N400 and P600 components of the event-related potential (ERP) signal-and a central theoretical challenge in this area is accounting for the so-called "semantic P600", which involves unexpected patterns in these components relative to traditional theories of the underlying mechanisms. In this paper we present a computational model of the language processing mechanisms underlying these ERP components, which builds on existing psycholinguistic theories in positing a heuristic interpretation stage of processing, but which deviates from existing theories in formulating this heuristic interpretation process as probabilistic selection via a noisy channel model, and in quantifying and accounting for fine-grained variation in statistical and representational properties of individual stimuli. Our model successfully simulates N400 and P600 patterns from eight psycholinguistic experiments, reflecting the full range of N400-only, P600-only, and biphasic N400-P600 effects, and its behaviors shed light on a number of key patterns that have presented challenges for existing theories. The model's success indicates that a strong account for the processing mechanisms underlying these effects is one in which language comprehension involves a probabilistic heuristic interpretation stage resembling a noisy channel process, feeding into subsequent processes that assess target word fit and reconcile between heuristic and literal interpretations. The model's success also indicates that these mechanisms are critically sensitive to statistical variation in individual stimuli, and that modeling the effects of this variation is essential to account for the full range of observed effects in language processing.

A systematic review of the prediction of consumer preference using EEG measures and machine-learning in neuromarketing research

Introduction

The present paper discusses the findings of a systematic review of EEG measures in neuromarketing, identifying which EEG measures are the most robust predictor of customer preference in neuromarketing. The review investigated which TF effect (e.g., theta-band power), and ERP component (e.g., N400) was most consistently reflective of self-reported preference. Machine-learning prediction also investigated, along with the use of EEG when combined with physiological measures such as eye-tracking.

Methods

Search terms ‘neuromarketing’ and ‘consumer neuroscience’ identified papers that used EEG measures. Publications were excluded if they were primarily written in a language other than English or were not published as journal articles (e.g., book chapters). 174 papers were included in the present review.

Results

Frontal alpha asymmetry (FAA) was the most reliable TF signal of preference and was able to differentiate positive from negative consumer responses. Similarly, the late positive potential (LPP) was the most reliable ERP component, reflecting conscious emotional evaluation of products and advertising. However, there was limited consistency across papers, with each measure showing mixed results when related to preference and purchase behaviour.

Conclusions and implications

FAA and the LPP were the most consistent markers of emotional responses to marketing stimuli, consumer preference and purchase intention. Predictive accuracy of FAA and the LPP was greatly improved through the use of machine-learning prediction, especially when combined with eye-tracking or facial expression analyses.

Functional Role of the N400 and P600 in Language-Related ERP Studies with Respect to Semantic Anomalies: An Overview

In this study, the language-related ERP studies relevant to the functional role of the N400 and P600 in semantically anomalous sentences and the underlying reasons which may affect their functions were reviewed. Since their discovery, the N400 and P600 have been the most important language-related ERP components. The N400 has been mostly elicited as a result of processing sentences with lexical and semantic anomalies, but later on, in many studies instead of the expected lexical-semantic N400 effect, semantic anomalies elicited a P600 effect called semantic P600. However, the functional interpretation of these two ERP components has constantly been a matter of debate. Perhaps most notably, it is proposed that it is not just the N400 which is related to semantic anomalies but the P600 can also be reflected as a result of these kinds of anomalies. Reviewing the literature for explaining the functions of the two ERP components, the N400 and the P600, during the processing of semantic anomalies revealed that still there is a need for more research on language processing in order to make the researchers capable of describing the underlying factors influencing them, especially more focused investigations of the functional-anatomical and neurocomputational models may provide a clearer understanding of them. Moreover, any practical theory or model of the N400 and the P600 in language comprehension needs to consider the apparent inconsistencies in the elicitation pattern of the N400 and the P600 in order to successfully capture the full data spectrum.

Semantic Processing in Healthy Aging and Alzheimer's Disease: A Systematic Review of the N400 Differences

Semantic deficits are common in individuals with Alzheimer’s disease (AD). These deficits notably impact the ability to understand words. In healthy aging, semantic knowledge increases but semantic processing (i.e., the ability to use this knowledge) may be impaired. This systematic review aimed to investigate semantic processing in healthy aging and AD through behavioral responses and the N400 brain event-related potential. The results of the quantitative and qualitative analyses suggested an overall decrease in accuracy and increase in response times in healthy elderly as compared to young adults, as well as in individuals with AD as compared to age-matched controls. The influence of semantic association, as measured by N400 effect amplitudes, appears smaller in healthy aging and even more so in AD patients. Thus, semantic processing differences may occur in both healthy and pathological aging. The establishment of norms of healthy aging for these outcomes that vary between normal and pathological aging could eventually help early detection of AD.

How the Brain Understands Spoken and Sung Sentences

The present study investigates whether meaning is similarly extracted from spoken and sung sentences. For this purpose, subjects listened to semantically correct and incorrect sentences while performing a correctness judgement task. In order to examine underlying neural mechanisms, a multi-methodological approach was chosen combining two neuroscientific methods with behavioral data. In particular, fast dynamic changes reflected in the semantically associated N400 component of the electroencephalography (EEG) were simultaneously assessed with the topographically more fine-grained vascular signals acquired by the functional near-infrared spectroscopy (fNIRS). EEG results revealed a larger N400 for incorrect compared to correct sentences in both spoken and sung sentences. However, the N400 was delayed for sung sentences, potentially due to the longer sentence duration. fNIRS results revealed larger activations for spoken compared to sung sentences irrespective of semantic correctness at predominantly left-hemispheric areas, potentially suggesting a greater familiarity with spoken material. Furthermore, the fNIRS revealed a widespread activation for correct compared to incorrect sentences irrespective of modality, potentially indicating a successful processing of sentence meaning. The combined results indicate similar semantic processing in speech and song.