Effect of EEG Referencing Methods on Auditory Mismatch Negativity

"What" and "when" predictions modulate auditory processing in a mutually congruent manner

Introduction

Extracting regularities from ongoing stimulus streams to form predictions is crucial for adaptive behavior. Such regularities exist in terms of the content of the stimuli and their timing, both of which are known to interactively modulate sensory processing. In real-world stimulus streams such as music, regularities can occur at multiple levels, both in terms of contents (e.g., predictions relating to individual notes vs. their more complex groups) and timing (e.g., pertaining to timing between intervals vs. the overall beat of a musical phrase). However, it is unknown whether the brain integrates predictions in a manner that is mutually congruent (e.g., if "beat" timing predictions selectively interact with "what" predictions falling on pulses which define the beat), and whether integrating predictions in different timing conditions relies on dissociable neural correlates.

Methods

To address these questions, our study manipulated "what" and "when" predictions at different levels - (local) interval-defining and (global) beat-defining - within the same stimulus stream, while neural activity was recorded using electroencephalogram (EEG) in participants (N = 20) performing a repetition detection task.

Results

Our results reveal that temporal predictions based on beat or interval timing modulated mismatch responses to violations of "what" predictions happening at the predicted time points, and that these modulations were shared between types of temporal predictions in terms of the spatiotemporal distribution of EEG signals. Effective connectivity analysis using dynamic causal modeling showed that the integration of "what" and "when" predictions selectively increased connectivity at relatively late cortical processing stages, between the superior temporal gyrus and the fronto-parietal network.

Discussion

Taken together, these results suggest that the brain integrates different predictions with a high degree of mutual congruence, but in a shared and distributed cortical network. This finding contrasts with recent studies indicating separable mechanisms for beat-based and memory-based predictive processing.

Segregation and integration of sensory features by flexible temporal characteristics of independent neural representations

Segregation and integration are two fundamental yet competing computations in cognition. For example, in serial speech processing, stable perception necessitates the sequential establishment of perceptual representations to remove irrelevant features for achieving invariance. Whereas multiple features need to combine to create a coherent percept. How to simultaneously achieve seemingly contradicted computations of segregation and integration in a serial process is unclear. To investigate their neural mechanisms, we used loudness and lexical tones as a research model and employed a novel multilevel oddball paradigm with Electroencephalogram (EEG) recordings to explore the dynamics of mismatch negativity (MMN) responses to their deviants. When two types of deviants were presented separately, distinct topographies of MMNs to loudness and tones were observed at different latencies (loudness earlier), supporting the sequential dynamics of independent representations for two features. When they changed simultaneously, the latency of responses to tones became shorter and aligned with that to loudness, while the topographies remained independent, yielding the combined MMN as a linear additive of single MMNs of loudness and tones. These results suggest that neural dynamics can be temporally synchronized to distinct sensory features and balance the computational demands of segregation and integration, grounding for invariance and feature binding in serial processing.

The Effects of Different Reference Methods on Decision-Making Implications of Auditory Brainstem Response

Hearing loss is a common disease affecting public health all around the world. In clinic, auditory brainstem response (ABR) has been widely used for the detection of hearing loss based on its convenience and accuracy. The different reference methods directly influence the quality of the ABR waveform which in turn affects the ABR-based diagnosis. Therefore, in this study, a reference electrode standardization technique (REST) was adopted to systematically investigate and evaluate the effect of different reference methods on the quality of ABR waveform in comparison with the conventional average reference (AR) and mean mastoid (MM) methods. In this study, ABR signals induced by click stimulus were acquired via an EEG electrode cap arrays, and those located on the six channels along the midline were compared systemically. The results showed that, when considering the different channels, the ABR in the Cz channel showed the best morphology. Then, the ABR waveforms acquired via the REST method possessed better morphologies with large amplitude ( $0.06\pm 0.02$  μV for wave I, $0.07\pm 0.02$  μV for wave III, and $0.21\pm 0.04$  μV for wave V) when compared with the traditional method. Summarily, we found that the REST and MM methods improved the quality of ABR on both amplitude and morphology under different stimulation rates and levels without changing the latencies of ABR when compared with the conventional AR method, suggesting that the REST and MM methods have the potential to help physicians with high accurate ABR-based clinical diagnosis. Moreover, this study might also provide a theoretic basis of reference methods on the acquisition of electroencephalogram over public health issues.

Unified Coding of Spectral and Temporal Phonetic Cues: Electrophysiological Evidence for Abstract Phonological Features

Spoken word recognition models and phonological theory propose that abstract features play a central role in speech processing. It remains unknown, however, whether auditory cortex encodes linguistic features in a manner beyond the phonetic properties of the speech sounds themselves. We took advantage of the fact that English phonology functionally codes stops and fricatives as voiced or voiceless with two distinct phonetic cues: Fricatives use a spectral cue, whereas stops use a temporal cue. Evidence that these cues can be grouped together would indicate the disjunctive coding of distinct phonetic cues into a functionally defined abstract phonological feature. In English, the voicing feature, which distinguishes the consonants [s] and [t] from [z] and [d], respectively, is hypothesized to be specified only for voiceless consonants (e.g., [s t]). Here, participants listened to syllables in a many-to-one oddball design, while their EEG was recorded. In one block, both voiceless stops and fricatives were the standards. In the other block, both voiced stops and fricatives were the standards. A critical design element was the presence of intercategory variation within the standards. Therefore, a many-to-one relationship, which is necessary to elicit an MMN, existed only if the stop and fricative standards were grouped together. In addition to the ERPs, event-related spectral power was also analyzed. Results showed an MMN effect in the voiceless standards block—an asymmetric MMN—in a time window consistent with processing in auditory cortex, as well as increased prestimulus beta-band oscillatory power to voiceless standards. These findings suggest that (i) there is an auditory memory trace of the standards based on the shared (voiceless) feature, which is only functionally defined; (ii) voiced consonants are underspecified; and (iii) features can serve as a basis for predictive processing. Taken together, these results point toward auditory cortex's ability to functionally code distinct phonetic cues together and suggest that abstract features can be used to parse the continuous acoustic signal.

Evoked and Event-Related Potentials as Biomarkers of Consciousness State and Recovery

SUMMARY

The definition of consciousness has been the subject of great interest for many scientists and philosophers. To better understand how evoked potentials may be identified as biomarkers of consciousness and recovery, the different theoretical models sustaining neural correlates of consciousness are reviewed. A multimodal approach can help to better predict clinical outcome in patients presenting with disorders of consciousness. Evoked potentials are inexpensive and easy-to-implement bedside examination techniques. Evoked potentials are an integral part of prognostic evaluation, particularly in cases of cognitive motor dissociation. Prognostic criteria are well established in postanoxic disorders of consciousness, especially postcardiac arrest but are less well determined in other etiologies. In the early examination, bilateral absence of N20 in disorder of consciousness patients is strongly associated with unfavorable outcome (i.e., death or unresponsive wakefulness syndrome) especially in postanoxic etiologies. This predictive value is lower in other etiologies and probably also in children. Both N20 and mismatch negativity are proven outcome predictors for acute coma. Many studies have shown that mismatch negativity and P3a are characterized by a high prognostic value for awakening, but some patients presenting unresponsive wakefulness syndrome also process a P3a. The presence of long-latency event-related potential components in response to stimuli is indicative of a better recovery. All neurophysiological data must be integrated within a multimodal approach combining repeated clinical evaluation, neuroimaging, functional imaging, biology, and neurophysiology combining passive and active paradigms.

Cognitive Workload in an Auditory Digit Span Task When Memory Span Is in the Neighborhood of Seven Items

Abstract. Task performance of digit span has been widely used in the research on human short-term memory. The present study was conducted to show that the dynamic change of underlying mental effort can be further estimated by measuring the strength of theta oscillations at a forehead site on the scalp. Fourteen healthy adults ( Mage = 26.1 years) performed a passive listening (PL) task and an auditory digit span (DS) task, and electroencephalography (EEG) data were recorded simultaneously during the two tasks. Considering that the digit span paradigm has often been conducted in a non-laboratory location, the EEG data were collected with a wireless single-channel headset system. The headset system was validated in this study by replicating the EEG (an enhancement of frontal theta power) as well as event-related potential (N200 and P300) responses to the deviant tone stimuli in the PL task. The outcomes of the DS task showed that the memory span of the participants was at least eight items. Moreover, frontal theta power in response to a list of six to eight digits increased significantly. This pattern of results supports a hypothesis that additional mental effort is required for short-term retention of verbal items when the number of stimulus items exceeds the newly proposed limit of short-term memory capacity. Some strengths and limitations of the current EEG headset system are also discussed.

Repetitive Thoughts and Repetitive Behaviors in Williams Syndrome

The purpose of the study was to characterize repetitive phenomena in Williams syndrome (WS). The parents of 60 subjects with WS completed the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) or Children's Y-BOCS, the Yale Global Tic Severity Scale, the Stereotyped Behavior Scale, and the Spence Children's Anxiety Scale-Parent Version. Nineteen males and 41 females participated in the study. Six subjects (10%) had obsessions only, six (10%) had compulsions only, and eleven (18%) had at least one obsession and at least one compulsion. None of the subjects had tics. Fifty subjects (83.3%) endorsed at least one stereotypy. Increased anxiety was associated with increased severity of obsessions, but not severity of compulsions or stereotypies.

Extracting Phonetic Features From Natural Classes: A Mismatch Negativity Study of Mandarin Chinese Retroflex Consonants

How speech sounds are represented in the brain is not fully understood. The mismatch negativity (MMN) has proven to be a powerful tool in this regard. The MMN event-related potential is elicited by a deviant stimulus embedded within a series of repeating standard stimuli. Listeners construct auditory memory representations of these standards despite acoustic variability. In most designs that test speech sounds, however, this variation is typically intra-category: All standards belong to the same phonetic category. In the current paper, inter-category variation is presented in the standards. These standards vary in manner of articulation but share a common phonetic feature. In the standard retroflex experimental block, Mandarin Chinese speaking participants are presented with a series of "standard" consonants that share the feature [retroflex], interrupted by infrequent non-retroflex deviants. In the non-retroflex standard experimental block, non-retroflex standards are interrupted by infrequent retroflex deviants. The within-block MMN was calculated, as was the identity MMN (iMMN) to account for intrinsic differences in responses to the stimuli. We only observed a within-block MMN to the non-retroflex deviant embedded in the standard retroflex block. This suggests that listeners extract [retroflex] despite significant inter-category variation. In the non-retroflex standard block, because there is little on which to base a coherent auditory memory representation, no within-block MMN was observed. The iMMN to the retroflex was observed in a late time-window at centro-parieto-occipital electrode sites instead of fronto-central electrodes, where the MMN is typically observed, potentially reflecting the increased difficulty posed by the added variation in the standards. In short, participants can construct auditory memory representations despite significant acoustic and inter-category phonological variation so long as a shared phonetic feature binds them together.

Investigating Auditory Electrophysiological Measures of Participants with Mild Cognitive Impairment and Alzheimer's Disease: A Systematic Review and Meta-Analysis of Event-Related Potential Studies

BACKGROUND

Objectively measuring auditory functions has been proposed as an avenue in differentiating normal age-related cognitive dysfunction from Alzheimer's disease (AD) and its prodromal states. Previous research has suggested auditory event-related potentials (AERPs) to be non-invasive, cost-effective, and efficient biomarkers for the diagnosis of AD.

OBJECTIVE

The objective of this paper is to review the published literature on AERPs measures in older adults diagnosed with AD and those at higher risk of developing AD, i.e., mild cognitive impairment (MCI) and subjective cognitive decline.

METHODS

The search was performed on six major electronic databases (Ovid MEDLINE, OVID EMBASE, PsycINFO, PubMed, Scopus, and CINAHL Plus). Articles identified prior to 7 May 2019 were considered for this review. A random effects meta-analysis and analysis of between study heterogeneity was conducted using the Comprehensive Meta-Analysis software.

RESULTS

The search identified 1,076 articles; 74 articles met the full inclusion criteria and were included in the systematic review, and 47 articles were included into the analyses. Pooled analysis suggests that AD participants can be differentiated from controls due to significant delays in ABR, N100, P200, N200, and P300 latencies. P300 amplitude was significantly smaller in AD participants compared to controls. P300 latencies differed significantly between MCI participants and controls based on the pooled analysis.

CONCLUSION

The findings of this review indicate that some AERPs may be valuable biomarkers of AD. In conjunction with currently available clinical and neuropsychological assessments, AERPs can aid in screening and diagnosis of prodromal AD.

Pitch, Timbre and Intensity Interdependently Modulate Neural Responses to Salient Sounds

As we listen to everyday sounds, auditory perception is heavily shaped by interactions between acoustic attributes such as pitch, timbre and intensity; though it is not clear how such interactions affect judgments of acoustic salience in dynamic soundscapes. Salience perception is believed to rely on an internal brain model that tracks the evolution of acoustic characteristics of a scene and flags events that do not fit this model as salient. The current study explores how the interdependency between attributes of dynamic scenes affects the neural representation of this internal model and shapes encoding of salient events. Specifically, the study examines how deviations along combinations of acoustic attributes interact to modulate brain responses, and subsequently guide perception of certain sound events as salient given their context. Human volunteers have their attention focused on a visual task and ignore acoustic melodies playing in the background while their brain activity using electroencephalography is recorded. Ambient sounds consist of musical melodies with probabilistically-varying acoustic attributes. Salient notes embedded in these scenes deviate from the melody's statistical distribution along pitch, timbre and/or intensity. Recordings of brain responses to salient notes reveal that neural power in response to the melodic rhythm as well as cross-trial phase alignment in the theta band are modulated by degree of salience of the notes, estimated across all acoustic attributes given their probabilistic context. These neural nonlinear effects across attributes strongly parallel behavioral nonlinear interactions observed in perceptual judgments of auditory salience using similar dynamic melodies; suggesting a neural underpinning of nonlinear interactions that underlie salience perception.

A Comparative Study of Different EEG Reference Choices for Event-Related Potentials Extracted by Independent Component Analysis

In the event-related potential (ERP) of scalp electroencephalography (EEG) studies, the vertex reference (Cz), linked mastoids or ears (LM), and average reference (AVG) are popular reference methods, and the reference electrode standardization technique (REST) is increasingly applied. Because scalp EEG recordings are considered as spatially degraded signals, independent component analysis (ICA) is a widely used data-driven method for obtaining ERPs by decomposing EEG data. However, the accurate estimation of the differences in ERP components extracted by ICA with different references remains unclear. In this study, we first provided formal descriptions of the above reference methods (Cz, LM, AVG, and REST) and ICA decomposition in ERP and then investigated the influences of different reference techniques on simulation and real EEG datasets. The results revealed that (1) the reference method did not change the peak amplitudes and latencies of relative ERPs corresponding to some IC time courses; (2) there were non-negligible effects of different reference methods on both temporal ERPs and spatial topographies of some ICs; and (3) compared to Cz, LM, and AR, considering both the performances of temporal ERPs and spatial topographies, the REST reference had overall superiority. These findings provide a recommended choice of REST for ICA analysis at the trial level and contribute to empirical investigations regarding the use of reference methods in ERP domains with ICA analysis.

Electrophysiological Responses to Expectancy Violations in Semantic and Gambling Tasks: A Comparison of Different EEG Reference Approaches

Dynamically evaluating the outcomes of our actions and thoughts is a fundamental cognitive ability. Given its excellent temporal resolution, the event-related potential (ERP) technology has been used to address this issue. The feedback-related negativity (FRN) component of ERPs has been studied intensively with the averaged linked mastoid reference method (LM). However, it is unknown whether FRN can be induced by an expectancy violation in an antonym relations context and whether LM is the most suitable reference approach. To address these issues, the current research directly compared the ERP components induced by expectancy violations in antonym expectation and gambling tasks with a within-subjects design and investigated the effect of the reference approach on the experimental effects. Specifically, we systematically compared the influence of the LM, reference electrode standardization technique (REST) and average reference (AVE) approaches on the amplitude, scalp distribution and magnitude of ERP effects as a function of expectancy violation type. The expectancy deviation in the antonym expectation task elicited an N400 effect that differed from the FRN effect induced in the gambling task; this difference was confirmed by all the three reference methods. Both the amplitudes of the ERP effects (N400 and FRN) and the magnitude as the expectancy violation increased were greater under the LM approach than those under the REST approach, followed by those under the AVE approach. Based on the statistical results, the electrode sites that showed the N400 and FRN effects critically depended on the reference method, and the results of the REST analysis were consistent with previous ERP studies. Combined with evidence from simulation studies, we suggest that REST is an optional reference method to be used in future ERP data analysis.