Data quality and reliability metrics for event-related potentials (ERPs): The utility of subject-level reliability

Psychometric, pre-processing, and trial-type considerations in individual differences studies of EEG mid-frontal theta power and latency

EEG mid-frontal theta-band activity (MFT; 4-8 Hz) is of considerable interest as a possible biomarker in translational research on cognitive control. However, because most of the MFT literature has focused on experimental within-subjects effects, the impact of particular data processing choices on individual difference analyses is not well understood. This study aimed to reduce that gap by examining the psychometric properties of different pipelines for measuring individual differences in MFT power and latency. Ninety-three adults aged 60 or older completed a flanker task during EEG recording. Stimulus-locked MFT was extracted in three primary pipelines via the fast Fourier transform (FFT), linear- and log-spaced wavelet, and filter-Hilbert analyses. The effects of frequency resolution, electrode choice, overall versus peak power, and trial type (overall, congruent, incongruent, and subtraction- and regression-based residual scores contrasting congruent and incongruent activity) were examined, as was the degree of overlap among related variables. Internal consistency reliabilities and associations with reaction times (RT) during the Flanker were assessed for select measures. Results indicated no benefit of higher frequency resolutions or region of interest over single-electrode measurements from FCz. Two-part coefficient alpha reliabilities ranged from 0.63 to 1.00 for MFT power variables, and from 0.02 to 0.83 for latency variables. Contrary to hypotheses and common criticisms of derived scores, correlations with RT were generally strongest for the difference and residual scores, with an additional benefit of time-frequency-based peak power relative to FFT-based overall power (r ~ = 0.30 vs. 0.45). These findings add to the growing literature on psychometric properties of EEG biomarkers, and help clarify measurement strategies that may enhance detection of behavioral and clinical correlates of MFT power and latency.

Psychometric Reliability of ERN and Pe Across Flanker, Stroop, and Go/No-Go Tasks: A Direct and Conceptual Replication

The effectiveness of error-related negativity (ERN) in assessing individual differences hinges on its psychometric reliability. Despite evidence that the task used to record ERN moderates internal consistency, this moderation is rarely examined within the same sample, risking inaccurate generalizations of psychometrics. A direct and conceptual replication of Meyer et al. (2013, Psychophysiology) was conducted in 182 participants to assess the internal consistency of ERN from flanker, go/no-go, and Stroop tasks as a function of increasing trials. Analyses were extended to include error positivity (Pe) and difference scores (ΔERN, ΔPe), and generalizability theory and multilevel models were used to statistically compare internal consistency across tasks. Overall, data supported the internal consistency of results across three tasks in a healthy undergraduate sample, with values ranging from 0.70 to 0.97 when examining all data. However, estimates were in part outside the confidence intervals of the original study, and ERN scores showed lower internal consistency than previously reported for a flanker task and higher internal consistency than previously reported for a Stroop task. Pe score internal consistency was similar across tasks when examining the average number of error trials. These findings underscore the importance of examining reliability in each study rather than relying on universal trial cutoffs. Overall, a flanker task may be better suited for studies of ERN due to the higher internal consistency of ERN scores when including data from all error trials. However, exclusively using a single task is discouraged because understanding the functional significance of ERN and Pe requires considering task-specific nuances and the varying contributions of cognitive processes, such as cognitive control or response inhibition.

Stability of performance monitoring with prolonged task performance: A study of error-related negativity and error positivity

The use of forced-choice response tasks to study indices of performance monitoring, such as the error-related negativity (ERN) and error positivity (Pe), is common, and such tasks are often used as a part of larger batteries in experimental research. ERN amplitude typically decreases over the course of a single task, but it is unclear whether amplitude changes persist beyond a single task or whether Pe amplitude changes over time. This preregistered study examined how prolonged task performance affects ERN and Pe amplitude across two study batteries, each with three different tasks. We predicted ERN amplitude would show unique, nonlinear reductions over an individual task and over the task battery, and exploratory analyses were conducted on Pe. Electrophysiological data were recorded during two studies: 156 participants who completed three versions of the flanker task and 161 participants who completed flanker, Go/NoGo, and Stroop tasks. ERN showed unique nonlinear reductions over each flanker task and over the battery of flanker tasks. However, ERN showed a linear reduction in amplitude over the battery of three different tasks, and within-task changes were only observed during the Go/NoGo task, such that ERN increased. Pe generally linearly decreased with prolonged task performance. Variability in ERN and Pe scores generally increased with time, indicating decreases in data quality. Findings suggest that studying ERN and Pe early in a task battery with short tasks is optimal to avoid bias from prolonged performance. Identifying factors affecting ERN and Pe during prolonged performance can help develop optimized paradigms.

Impact of ERP Reliability Cutoffs on Sample Characteristics and Effect Sizes: Performance-Monitoring ERPs in Psychosis and Healthy Controls

In studies of event-related brain potentials (ERPs), it is common practice to exclude participants for having too few trials for analysis to ensure adequate score reliability (i.e., internal consistency). However, in research involving clinical samples, the impact of increasingly rigorous reliability standards on factors such as sample generalizability, patient versus control effect sizes, and effect sizes for within-group correlations with external variables is unclear. This study systematically evaluated whether different ERP reliability cutoffs impacted these factors in psychosis. Error-related negativity (ERN) and error positivity (Pe) were assessed during a modified flanker task in 97 patients with psychosis and 104 healthy comparison participants, who also completed measures of cognition and psychiatric symptoms. ERP reliability cutoffs had notably different effects on the factors considered. A recommended reliability cutoff of 0.80 resulted in sample bias due to systematic exclusion of patients with relatively few task errors, lower reported psychiatric symptoms, and higher levels of cognitive functioning. ERP score reliability lower than 0.80 resulted in generally smaller between- and within-group effect sizes, likely misrepresenting effect sizes. Imposing rigorous ERP reliability standards in studies of psychotic disorders might exclude high-functioning patients, which raises important considerations for the generalizability of clinical ERP research. Moving forward, we recommend examining characteristics of excluded participants, optimizing paradigms and processing pipelines for use in clinical samples, justifying reliability thresholds, and routinely reporting score reliability of all measurements, ERP or otherwise, used to examine individual differences, especially in clinical research.

Attenuated Doors-Locked P300 Amplitude and Elevated Depressive Symptoms: Effects of Age and Sex in Two Independent Samples of Youth

Deficits in cognitive and reward-related functions, measured via reductions in the P300 and reward positivity (RewP) event-related potential (ERP) components, are commonly observed in adults suffering with depression. Considering higher risk for depression emerges among females in adolescence, examination of the neurological underpinnings of depression during this critical developmental period can help further elucidate our overall understanding of the etiology of depressive disorders. Therefore, the present study sought to first examine associations between doors-locked P300 amplitude, RewP amplitude, current depression symptoms, and age in an all-female youth sample (sample 1: n = 296; age, 8 to 14). Next, we examined these same associations, as well as sex, in a second independent sample consisting of male and female youths (sample 2: n = 605; age, 11 to 14). Blunted doors-locked P300 was associated with higher depressive symptoms in both samples. Moreover, the association between P300 and depression was stronger among older youths in both samples. Sex further moderated this relationship in sample 2 such that smaller P300 related to greater depression only in females. There were no consistent associations between RewP amplitude and depressive symptoms in either youth sample. These findings suggest that the doors-locked P300 component is a reliable neural correlate of depression in youth that might specifically relate to pathways linked to increased risk for depression among adolescent females.

Registered replication report of the construct validity of the error-related negativity (ERN): A multi-site study of task-specific ERN correlations with internalizing and externalizing symptoms

Intact cognitive control is critical for goal-directed behavior and is widely studied using the error-related negativity (ERN). A common assumption in such studies is that ERNs recorded during different experimental paradigms reflect the same construct or functionally equivalent processes and that ERN is functionally distinct from other error-monitoring event-related brain potentials (ERPs; error positivity [Pe]), other neurophysiological indices of cognitive control (N2), and even other theoretically unrelated indices (visual N1). The present registered report represents a replication-plus-extension study of the psychometric validity of cognitive control ERPs and evaluated the convergent and divergent validity of ERN, Pe, N2, and visual N1 recorded during flanker, Stroop, and Go/no-go tasks. Data from 182 participants were collected from two study sites, and ERP psychometric reliability and validity were evaluated. Findings supported replication of convergent and divergent validity of ERN, Pe, and ΔPe (error minus correct)-these ERPs correlated more with themselves across tasks than with other ERPs measured during the same task. Convergent validity of ΔERN across tasks was not replicated, despite high internal consistency. ERN strongly correlated with N2 at levels similar or higher than those in support of convergent validity for other ERPs, and the present study failed to provide evidence of divergent validity for ERN and Pe from N2 or N1. ERN and ΔERN were unrelated to internalizing or externalizing symptoms. Findings underscore the importance of considering the psychometric validity of ERPs, as it provides a foundation for interpreting and comparing ERPs across tasks and studies.

Leveraging mixed-effects location scale models to assess the ERP mismatch negativity's psychometric properties and trial-by-trial neural variability in toddler-mother dyads

Trial-by-trial neural variability, a measure of neural response stability, has been examined in relation to behavioral indicators using summary measures, but these methods do not characterize meaningful processes underlying variability. Mixed-effects location scale models (MELSMs) overcome these limitations by accounting for predictors and covariates of variability but have been rarely used in developmental studies. Here, we applied MELSMs to the ERP auditory mismatch negativity (MMN), a neural measure often related to language and psychopathology. 84 toddlers and 76 mothers completed a speech-syllable MMN paradigm. We extracted early and late MMN mean amplitudes from trial-level waveforms. We first characterized our sample's psychometric properties using MELSMs and found a wide range of subject-level internal consistency. Next, we examined the relation between toddler MMNs with theoretically relevant child behavioral and maternal variables. MELSMs offered better model fit than analyses that assumed constant variability. We found significant individual differences in trial-by-trial variability but no significant associations between toddler variability and their language, irritability, or mother variability indices. Overall, we illustrate how MELSMs can characterize psychometric properties and answer questions about individual differences in variability. We provide recommendations and resources as well as example code for analyzing trial-by-trial neural variability in future studies.

A network analysis of affective and motivational individual differences and error monitoring in a non-clinical sample

Error monitoring, which plays a crucial role in shaping adaptive behavior, is influenced by a complex interplay of affective and motivational factors. Understanding these associations often proves challenging due to the intricate nature of these variables. With the aim of addressing previous inconsistencies and methodological gaps, in this study, we utilized network analysis to investigate the relationship between affective and motivational individual differences and error monitoring. We employed six Gaussian Graphical Models on a non-clinical population ($N$ = 236) to examine the conditional dependence between the amplitude of response-related potentials (error-related negativity; correct-related negativity) and 29 self-report measures related to anxiety, depression, obsessive thoughts, compulsive behavior, and motivation while adjusting for covariates: age, handedness, and latency of error-related negativity and correct-related negativity. We then validated our results on an independent sample of 107 participants. Our findings revealed unique associations between error-related negativity amplitudes and specific traits. Notably, more pronounced error-related negativity amplitudes were associated with increased rumination and obsessing, and decreased reward sensitivity. Importantly, in our non-clinical sample, error-related negativity was not directly associated with trait anxiety. These results underscore the nuanced effects of affective and motivational traits on error processing in healthy population.

Task-specific relationships between error-related ERPs and behavior: Flanker, Stroop, and Go/Nogo tasks

Performance monitoring has been widely studied during different forced-choice response tasks. Participants typically show longer response times (RTs) and increased accuracy following errors, but there are inconsistencies regarding the connection between error-related event-related brain potentials (ERPs) and behavior, such as RT and accuracy. The specific task in any given study could contribute to these inconsistencies, as different tasks may require distinct cognitive processes that impact ERP-behavior relationships. The present study sought to determine whether task moderates ERP-behavior relationships and whether these relationships are robustly observed when tasks and stimuli are treated as random effects. ERPs and behavioral indices (RTs and accuracy) recorded during flanker, Stroop, and Go/Nogo tasks from 180 people demonstrated a task-specific effect on ERP-behavior relationships, such that larger previous-trial error-related negativity (ERN) predicted longer RTs and greater likelihood of a correct response on subsequent trials during flanker and Stroop tasks but not during Go/Nogo task. Additionally, larger previous-trial error positivity (Pe) predicted faster RTs and smaller variances of RTs on subsequent trials for Stroop and Go/Nogo tasks but not for flanker task. When tasks and stimuli were treated as random effects, ERP-behavior relationships were not observed. These findings support the need to consider the task used for recording performance monitoring measures when interpreting results across studies.

A registered report of a two-site study of variations of the flanker task: ERN experimental effects and data quality

Error-related negativity is a widely used measure of error monitoring, and many projects are independently moving ERN recorded during a flanker task toward standardization, optimization, and eventual clinical application. However, each project uses a different version of the flanker task and tacitly assumes ERN is functionally equivalent across each version. The routine neglect of a rigorous test of this assumption undermines efforts to integrate ERN findings across tasks, optimize and standardize ERN assessment, and widely apply ERN in clinical trials. The purpose of this registered report was to determine whether ERN shows similar experimental effects (correct vs. error trials) and data quality (intraindividual variability) during three commonly used versions of a flanker task. ERN was recorded from 172 participants during three versions of a flanker task across two study sites. ERN scores showed numerical differences between tasks, raising questions about the comparability of ERN findings across studies and tasks. Although ERN scores from all three versions of the flanker task yielded high data quality and internal consistency, one version did outperform the other two in terms of the size of experimental effects and the data quality. Exploratory analyses of the error positivity (Pe) provided tentative support for the other two versions of the task over the paradigm that appeared optimal for ERN. The present study provides a roadmap for how to statistically compare psychometric characteristics of ERP scores across paradigms and gives preliminary recommendations for flanker tasks to use for ERN- and Pe-focused studies.

How variable are the classic ERP effects during sentence processing? A systematic resampling analysis of the N400 and P600 effects

Although event-related potential (ERP) research on language processing has capitalized on key, theoretically influential components such as the N400 and P600, their measurement properties-especially the variability in their temporal and spatial parameters-have rarely been examined. The current study examined the measurement properties of the N400 and P600 effects elicited by semantic and syntactic anomalies, respectively, during sentence processing. We used a bootstrap resampling procedure to randomly draw many thousands of resamples varying in sample size and stimulus count from a larger sample of 187 participants and 40 stimulus sentences of each type per condition. Our resampling investigation focused on three issues: (a) statistical power; (b) variability in the magnitudes of the effects; and (c) variability in the temporal and spatial profiles of the effects. At the level of grand averages, the N400 and P600 effects were both robust and substantial. However, across resamples, there was a high degree of variability in effect magnitudes, onset times, and scalp distributions, which may be greater than is currently appreciated in the literature, especially for the P600 effects. These results provide a useful basis for designing future studies using these two well-established ERP components. At the same time, the results also highlight challenges that need to be addressed in future research (e.g., how best to analyze the ERP data without engaging in such questionable research practices as p-hacking).

On the (un)reliability of common behavioral and electrophysiological measures from the stop signal task: Measures of inhibition lack stability over time

Response inhibition, the intentional stopping of planned or initiated actions, is often considered a key facet of control, impulsivity, and self-regulation. The stop signal task is argued to be the purest inhibition task we have, and it is thus central to much work investigating the role of inhibition in areas like development and psychopathology. Most of this work quantifies stopping behavior by calculating the stop signal reaction time as a measure of individual stopping latency. Individual difference studies aiming to investigate why and how stopping latencies differ between people often do this under the assumption that the stop signal reaction time indexes a stable, dispositional trait. However, empirical support for this assumption is lacking, as common measures of inhibition and control tend to show low test-retest reliability and thus appear unstable over time. The reasons for this could be methodological, where low stability is driven by measurement noise, or substantive, where low stability is driven by a larger influence of state-like and situational factors. To investigate this, we characterized the split-half and test-retest reliability of a range of common behavioral and electrophysiological measures derived from the stop signal task. Across three independent studies, different measurement modalities, and a systematic review of the literature, we found a pattern of low temporal stability for inhibition measures and higher stability for measures of manifest behavior and non-inhibitory processing. This pattern could not be explained by measurement noise and low internal consistency. Consequently, response inhibition appears to have mostly state-like and situational determinants, and there is little support for the validity of conceptualizing common inhibition measures as reflecting stable traits.

A multimodal approach integrating cognitive and motor demands into physical activity for optimal mental health: Methodological issues and future directions

Physical activity is known for its positive effects on cognition and affect, with existing literature suggesting that these mental health benefits may be optimally experienced by incorporating cognitive and motor demands during physical activity (PA). However, the existing body of literature lacks a comprehensive guideline for designing the qualitative characteristics of a PA program. Accordingly, this narrative review aimed to (1) provide a working two-dimension model that operationally defines the cognitive and motor demands involved in PA and the rationale for systematically studying these qualitative aspects of PA, (2) identify methods to assess the cognitive and motor demands of PA and address associated methodological issues, and (3) offer potential future directions for research on the cognitive and motor aspects of PA in support of the development of PA programs designed to maximize PA-induced cognitive and affective benefits. We anticipate this article to inform the need for future research and development on this topic, aiming to create clear, evidence-based guidelines for designing innovative and effective PA interventions.

The future of psychophysiology, then and now

Since its founding in 1973, Biological Psychology has showcased and provided invaluable support to psychophysiology, a field that has grown and changed enormously. This article discusses some constancies that have remained fundamental to the journal and to the field as well as some important trends. Some aspects of our science have not received due consideration, affecting not only the generalizability of our findings but the way we develop and evaluate our research questions and the potential of our field to contribute to the common good. The article offers a number of predictions and recommendations for the next period of growth of psychophysiology.

Robust single-trial event-related potentials differentiate between distress and fear disorders

Recent evidence indicates that measures of brain functioning as indexed by event-related potentials (ERPs) on the electroencephalogram align more closely to transdiagnostic measures of psychopathology than to categorical taxonomies. The Hierarchical Taxonomy of Psychopathology (HiTOP) is a transdiagnostic, dimensional framework aiming to solve issues of comorbidity, symptom heterogeneity, and arbitrary diagnostic boundaries. Based on shared features, the emotional disorders are allocated into subfactors Distress and Fear. Evidence indicates that disorders that are close in the HiTOP hierarchy share etiology, symptom profiles, and treatment outcomes. However, further studies testing the biological underpinnings of the HiTOP are called for. In this study, we assessed differences between Distress and Fear in a range of well-studied ERP components. In total, 50 patients with emotional disorders were divided into two groups (Distress, N = 25; Fear, N = 25) according to HiTOP criteria and compared against 37 healthy comparison (HC) subjects. Addressing issues in traditional ERP preprocessing and analysis methods, we applied robust single-trial analysis as implemented in the EEGLAB toolbox LIMO EEG. Several ERP components were found to differ between the groups. Surprisingly, we found no difference between Fear and HC for any of the ERPs. This suggests that some well-established results from the literature, e.g., increased error-related negativity in OCD, are not a shared neurobiological correlate of the Fear subfactor. Conversely, for Distress, we found reductions compared to Fear and HC in several ERP components across paradigms. Future studies could utilize HiTOP-validated psychopathology measures to more precisely define subfactor groups.

The impact of electrode selection for ocular correction on the reward positivity and late positive potential components in adolescents

Electroencephalography (EEG) data processing to derive event-related potentials (ERPs) follows a standard set of procedures to maximize signal-to-noise ratio. This often includes ocular correction, which corrects for artifacts introduced by eye movements, typically measured by electrooculogram (EOG) using facial electrodes near the eyes. Yet, attaching electrodes to the face may be uncomfortable for some populations, best to avoid in some situations, and contribute to data loss. Eye movements can also be measured using electrodes in a standard 10-20 EEG cap. An examination of the impact of electrode selection on ERPs is needed to inform best practices. The present study examined data quality when using different electrodes to measure eye movements for ocular correction (i.e., facial electrodes, cap electrodes, and no ocular correction) for two well-established and widely studied ERP components (i.e., reward positivity, RewP; and late positive potential, LPP) elicited in adolescents (N = 34). Results revealed comparable split-half reliability and standardized measurement error (SME) between facial and cap electrode approaches, with lower SME for the RewP with facial or cap electrodes compared to no ocular correction. Few significant differences in mean amplitude of ERPs were observed, but the LPP to positive images differed when using facial compared to cap electrodes. Findings provide preliminary evidence of the ability to collect high-quality ERP data without facial electrodes. However, when using cap electrodes for EOG measurement and ocular correction, it is recommended to use consistent procedures across the sample or statistically examine the impact of ocular correction procedures on results.

Meanness and affective processing: A meta-analysis of EEG findings on emotional face processing in individuals with psychopathic traits

BACKGROUND

The triarchic model (Patrick et al., 2009) conceptualizes psychopathy as a multidimensional construct encompassing three biobehavioral dimensions: meanness, boldness, and disinhibition. Meanness entails low empathy, shallow affect, and lack of remorse, and is associated with poor facial emotion recognition; however, the mechanistic processes contributing to these deficits are unclear. Emotional face processing can be examined on a neurophysiological level using event-related potentials (ERPs) such as N170, P200, and LPP. No quantitative review to date has examined the extent to which amplitude of these ERP components may be modulated by psychopathic traits.

METHOD

The current study performed random-effects model meta-analyses of nine studies (N = 1131) which examined affective face processing ERPs in individuals with psychopathic traits to provide an overall effect size for the association between meanness, boldness, and disinhibition and N170, P200, and LPP amplitudes across studies. Analyses were also conducted examining potential moderators and publication bias.

RESULTS

N170 amplitudes were significantly smaller (r =.18) among individuals high in meanness when processing fearful faces. Significant effects were not found for N170 amplitude when processing angry or happy faces, nor for LPP and P200 amplitudes across stimulus types. Additionally, significant effects were not found for the association between N170 amplitude and other dimensions of psychopathy. Meta-regression analyses indicated the manipulation of facial stimuli was significant in explaining some between-study heterogeneity of the meanness N170-fear model. No evidence of publication bias was found.

CONCLUSIONS

Diminished amplitude of the N170 when viewing fear faces appears to be a neurophysiological marker of psychopathic meanness. Deficits in early encoding of faces may account for empathy deficits characteristic of psychopathy.

The psychometric upgrade psychophysiology needs

Although biological measurements are constrained by the same fundamental psychometric principles as self-report measurements, these essential principles are often neglected in most fields of neuroscience, including psychophysiology. Potential reasons for this neglect could include a lack of understanding of appropriate measurement theory or a lack of accessible software for psychometric analysis. Generalizability theory is a flexible and multifaceted measurement theory that is well suited to handling the nuances of psychophysiological data, such as the often unbalanced number of trials and intraindividual variability of scores of event-related brain potential (ERP) data. The ERP Reliability Analysis Toolbox (ERA Toolbox) was designed for psychophysiologists and is tractable software that can support the routine evaluation of psychometrics using generalizability theory. Psychometrics can guide task refinement, data-processing decisions, and selection of candidate biomarkers for clinical trials. The present review provides an extensive treatment of additional psychometric characteristics relevant to studies of psychophysiology, including validity and validation, standardization, dimensionality, and measurement invariance. Although the review focuses on ERPs, the discussion applies broadly to psychophysiological measures and beyond. The tools needed to rigorously assess psychometric reliability and validate psychophysiological measures are now readily available. With the profound implications that psychophysiological research can have on understanding brain-behavior relationships and the identification of biomarkers, there is simply too much at stake to ignore the crucial processes of evaluating psychometric reliability and validity.

Beyond single paradigms, pipelines, and outcomes: Embracing multiverse analyses in psychophysiology

Psychophysiological research is an inherently complex undertaking due to the nature of the data, and its analysis is characterized by many decision points that shape the final dataset and a study's findings. These decisions create a "multiverse" of possible outcomes, and each decision from study conceptualization to statistical analysis can lead to different results and interpretations. This review describes the concept of multiverse analyses, a methodological approach designed to understand the impact of different decisions on the robustness of a study's findings and interpretation. The emphasis is on transparently showcasing different reasonable approaches for constructing a final dataset and on highlighting the influence of various decision points, from experimental design to data processing and outcome selection. For example, the choice of an experimental task can significantly impact event-related brain potential (ERP) scores or skin conductance responses (SCRs), and different tasks might elicit unique variances in each measure. This review underscores the importance of transparently embracing the flexibility inherent in psychophysiological research and the potential consequences of not understanding the fragility or robustness of experimental findings. By navigating the intricate terrain of the psychophysiological multiverse, this review serves as an introduction, helping researchers to make informed decisions, improve the collective understanding of psychophysiological findings, and push the boundaries of the field.

Associations between physical activity, sedentary time, and neurocognitive function during adolescence: Evidence from accelerometry and the flanker P300

Physical activity and sedentary behavior are two lifestyle factors related to overall health during adolescence. Public health efforts emphasize the importance of increasing physical activity to improve physical and mental health outcomes, including neurocognitive functioning. However, the unique effects of sedentary behavior on neurocognitive functioning remain unclear. This study aimed to investigate associations between daily moderate-to-vigorous physical activity (MVPA), sedentary time, and neurocognitive functioning during adolescence. Fifty-seven participants (37% female) between the ages of 13 and 17 years wore an accelerometer on their non-dominant wrist for approximately 1 week to quantify daily MVPA and sedentary time prior to completing a flanker task to elicit P300 amplitude at a laboratory visit. Results indicated that daily MVPA and sedentary time exhibited unique, significant associations with P300 amplitude in opposing directions: increased daily MVPA was correlated with larger P300 amplitudes, while increased daily sedentary time was linked to reduced P300 amplitudes. Notably, these associations remained significant even after adjusting for age, sex, and BMI-for-age percentile. These findings underscore the independent influence of daily MVPA and sedentary time on neurocognitive functioning during adolescence. Future research should explore whether modifying MVPA levels can improve neurocognitive outcomes-including the P300-during adolescence, and determine whether reducing sedentary time results in similar or differential effects.

Normal congruency sequence effects in psychopathology: A behavioral and electrophysiological examination using a confound-minimized design

Clinical studies of adaptive control emphasize the role disruptions in control play in psychopathology. However, many studies used confound-laden designs and examined only one type of psychopathology. Recent studies of event-related potentials (ERPs) suggest that robust congruency sequence effects (CSEs)-a popular index of adaptive control-appear in confound-minimized designs. Thus, the present study sought to determine whether a confound-minimized CSE paradigm could identify adaptive control dysfunction in people with major depressive disorder (MDD), generalized anxiety disorder (GAD), and obsessive-compulsive disorder (OCD). We predicted that participants with MDD and GAD would show smaller ERP CSEs and that participants with OCD would show larger ERP CSEs than healthy controls. Data from 44 people with GAD, 51 people with MDD, 31 people with OCD, and 56 healthy comparison participants revealed normal CSEs as indexed by response times (RTs) and ERPs in the psychopathology groups. Moreover, psychiatric symptoms did not moderate these CSEs. Finally, we observed a strong mean-variance relationship in RT CSEs, such that participants with stronger post-recruitment of control in mean RT scores showed the most consistent post-conflict responses (i.e., the least intraindividual variability). These findings suggest that prior findings from confound-laden tasks indicating altered CSEs in psychopathology stem from processes that are unrelated to adaptive control. Future research should employ experimental designs that isolate these processes to advance our understanding of abnormal CSEs in psychopathology.

Can we dissociate hypervigilance to social threats from altered perceptual decision-making processes in lonely individuals? An exploration with Drift Diffusion Modeling and event-related potentials

It has been hypothesized that lonely individuals demonstrate hypervigilance toward social threats. However, recent studies have raised doubts about the reliability of tasks commonly used to measure attentional biases toward threats. Two alternative approaches have been suggested to overcome the limitations of traditional analysis of attentional bias. First, the neurophysiological indicators of orienting to threats were shown to have superior psychometric characteristics compared to overt measures of behavioral performance. The second approach involves utilizing computational modeling to isolate latent components corresponding to specific cognitive mechanisms from observable data. To test the usefulness of these approaches in loneliness research, we analyzed behavioral and electroencephalographic (EEG) data from 26 lonely and 26 non-lonely participants who performed a dot-probe task using a computational modeling approach. We applied the Drift Diffusion Model (DDM) and extracted N2pc-an event-related potential that serves as an indicator of spatial attention. No evidence for social threat hypervigilance has been found in DDM parameters nor in N2pc characteristics in the current study. However, we did observe decreased drift rate and increased variability in drift rate between trials within the lonely group, indicating reduced efficiency in perceptual decision-making among lonely individuals. These effects were not detected using standard behavioral measures used in the dot-probe paradigm. Given that DDM indicators were sensitive to differences in perceptual discrimination between the two groups, even when no overt differences were found in standard behavioral measures, it may be postulated that computational approaches offer a more comprehensive understanding of cognitive processes.

Managing EEG studies: How to prepare and what to do once data collection has begun

In this paper, we provide guidance for the organization and implementation of EEG studies. This work was inspired by our experience conducting a large-scale, multi-site study, but many elements could be applied to any EEG project. Section 1 focuses on study activities that take place before data collection begins. Topics covered include: establishing and training study teams, considerations for task design and piloting, setting up equipment and software, development of formal protocol documents, and planning communication strategy with all study team members. Section 2 focuses on what to do once data collection has already begun. Topics covered include: (1) how to effectively monitor and maintain EEG data quality, (2) how to ensure consistent implementation of experimental protocols, and (3) how to develop rigorous preprocessing procedures that are feasible for use in a large-scale study. Links to resources are also provided, including sample protocols, sample equipment and software tracking forms, sample code, and tutorial videos (to access resources, please visit: https://osf.io/wdrj3/).

Enhancing precision in human neuroscience

Human neuroscience has always been pushing the boundary of what is measurable. During the last decade, concerns about statistical power and replicability - in science in general, but also specifically in human neuroscience - have fueled an extensive debate. One important insight from this discourse is the need for larger samples, which naturally increases statistical power. An alternative is to increase the precision of measurements, which is the focus of this review. This option is often overlooked, even though statistical power benefits from increasing precision as much as from increasing sample size. Nonetheless, precision has always been at the heart of good scientific practice in human neuroscience, with researchers relying on lab traditions or rules of thumb to ensure sufficient precision for their studies. In this review, we encourage a more systematic approach to precision. We start by introducing measurement precision and its importance for well-powered studies in human neuroscience. Then, determinants for precision in a range of neuroscientific methods (MRI, M/EEG, EDA, Eye-Tracking, and Endocrinology) are elaborated. We end by discussing how a more systematic evaluation of precision and the application of respective insights can lead to an increase in reproducibility in human neuroscience.

The ups and downs of bilingualism: A review of the literature on executive control using event-related potentials

Whether bilingualism enhances executive control (EC) is controversial. This article reviews 24 studies on the bilingual EC effect using event-related potentials (ERPs). It evaluates the evidence based on considerations of neural efficiency, different EC theories, and accounts regarding the locus of the bilingual effect. The review finds some evidence for a positive bilingual impact. This is more consistent for the P3 and response-locked ERPs. Moreover, when considering each component independently, evidence primarily supports a monitoring and secondarily an inhibition locus. Additionally, an N2/ERN (error-related negativity) dissociation (no bilingual N2 effect but positive ERN impact, evident as smaller ERN), coupled with the P3 results, suggest that monitoring may not be the (only) locus of a bilingual effect but (an)other post-monitoring mechanism(s). Attention disengagement also receives some support. Finally, results across studies are largely consistent with the Bilingualism Anterior to Posterior and Subcortical Shift model (BAPSS): Bilingual effects, when found, often manifest as shorter latencies, larger components or wider amplitude effects during earlier (N2, P3) but smaller components or narrower effects during later processing (stimulus-locked negativities and response-locked components). However, this evidence is not unequivocal. Many bilingual-monolingual comparisons reveal null or some suggest negative or opposite to prediction bilingual effects. Second, the scant evidence about which bilingual experiences impact EC is, generally, unclear, while some evidence indicates negative effects. Third, BAPSS is often not confirmed when multiple components are examined within subjects. Finally, this literature is challenged by confounds and small samples. Further research is required to conclude a positive bilingual effect on EC in ERPs.

Variations in ERP data quality across paradigms, participants, and scoring procedures

Although it is widely accepted that data quality for event-related potential (ERP) components varies considerably across studies and across participants within a study, ERP data quality has not received much systematic analysis. The present study used a recently developed metric of ERP data quality- the standardized measurement error (SME)-to examine how data quality varies across different ERP paradigms, across individual participants, and across different procedures for quantifying amplitude and latency values. The EEG recordings were taken from the ERP CORE, which includes data from 40 neurotypical college students for seven widely studied ERP components: P3b, N170, mismatch negativity, N400, error-related negativity, N2pc, and lateralized readiness potential. Large differences in data quality were observed across the different ERP components, and very large differences in data quality were observed across participants. Data quality also varied depending on the algorithm used to quantify the amplitude and especially the latency of a given ERP component. These results provide an initial set of benchmark values that can be used for comparison with previous and future ERP studies. They also provide useful information for predicting effect sizes and statistical power in future studies, even with different numbers of trials. More broadly, this study provides a general approach that could be used to determine which specific experimental designs, data collection procedures, and data processing algorithms lead to the best data quality.

Stability, change, and reliable individual differences in electroencephalography measures: a lifespan perspective on progress and opportunities

Electroencephalographic (EEG) methods have great potential to serve both basic and clinical science approaches to understand individual differences in human neural function. Importantly, the psychometric properties of EEG data, such as internal consistency and test-retest reliability, constrain their ability to differentiate individuals successfully. Rapid and recent technological and computational advancements in EEG research make it timely to revisit the topic of psychometric reliability in the context of individual difference analyses. Moreover, pediatric and clinical samples provide some of the most salient and urgent opportunities to apply individual difference approaches, but the changes these populations experience over time also provide unique challenges from a psychometric perspective. Here we take a developmental neuroscience perspective to consider progress and new opportunities for parsing the reliability and stability of individual differences in EEG measurements across the lifespan. We first conceptually map the different profiles of measurement reliability expected for different types of individual difference analyses over the lifespan. Next, we summarize and evaluate the state of the field's empirical knowledge and need for testing measurement reliability, both internal consistency and test-retest reliability, across EEG measures of power, event-related potentials, nonlinearity, and functional connectivity across ages. Finally, we highlight how standardized pre-processing software for EEG denoising and empirical metrics of individual data quality may be used to further improve EEG-based individual differences research moving forward. We also include recommendations and resources throughout that individual researchers can implement to improve the utility and reproducibility of individual differences analyses with EEG across the lifespan.

How low can you go? Measuring human event-related brain potentials from a two-channel EEG system

Over the past ten years, there has been a rapid increase in the availability and use of mobile electroencephalography (mEEG) in research. Indeed, researchers using mEEG have recorded EEG and event-related brain potentials in a wide range of environments - for example, while walking (Debener et al., 2012), riding a bike (Scanlon et al., 2020), or even in a shopping mall (Krigolson et al., 2021). However, given that low-cost, ease-of-use, and setup speed provide the primary advantages of an mEEG system over large array traditional EEG systems, an important and unresolved question is just how many electrodes does an mEEG system need to collect research-quality EEG data? Here, we tested whether or not a two-channel forehead-mounted mEEG system - the "Patch" - could measure event-related brain potentials within their established amplitude and latency characteristics (Luck, 2014). In the present study, participants performed a visual oddball task while we recorded EEG data from the Patch. Our results demonstrated that we could capture and quantify the N200 and P300 event-related brain potential components using a minimal electrode array forehead-mounted EEG system. Our data further support the idea that mEEG can be used for quick and rapid EEG-based assessments, such as measuring the impact of concussions on the sports field (Fickling et al., 2021) or assessing the impact of stroke severity in a hospital (Wilkinson et al., 2020).

Updating the relationship of the Ne/ERN to task-related behavior: A brief review and suggestions for future research

The error negativity/error-related negativity (Ne/ERN) is one of the most well-studied event-related potential (ERP) components in the electroencephalography (EEG) literature. Peaking about 50 ms after the commission of an error, the Ne/ERN is a negative deflection in the ERP waveform that is thought to reflect error processing in the brain. While its relationships to trait constructs such as anxiety are well-documented, there is still little known about how the Ne/ERN may subsequently influence task-related behavior. In other words, does the occurrence of the Ne/ERN trigger any sort of error corrective process, or any other behavioral adaptation to avoid errors? Several theories have emerged to explain how the Ne/ERN may implement or affect behavior on a task, but evidence supporting each has been mixed. In the following manuscript, we review these theories, and then systematically discuss the reasons that there may be discrepancies in the literature. We review both the inherent biological factors of the neural regions that underlie error-processing in the brain, and some of the researcher-induced factors in analytic and experimental choices that may be exacerbating these discrepancies. We end with a table of recommendations for future researchers who aim to understand the relationship between the Ne/ERN and behavior.

Towards thoughtful planning of ERP studies: How participants, trials, and effect magnitude interact to influence statistical power across seven ERP components

In the field of EEG, researchers generally rely on rules of thumb, rather than a priori statistical calculations, when planning the number of trials to include in an ERP study. To aid in this practice, studies have tried to establish minimum numbers of trials required to reliably isolate ERPs. However, these guidelines do not necessarily apply across different study designs, as the reliability of an ERP waveform is not the same as the statistical power of a given experiment. Experiment parameters such as number of participants, trials, and effect magnitude interact to affect power in complex ways. Both under- and over-powered ERP studies represent a waste of time and resources that impedes the progress of the field. The current study fills this gap by subsampling real ERP data to estimate the relationship between experiment design parameters and statistical power. The simulations include seven commonly studied ERP components: the ERN, LRP, N170, MMN, P3, N2pc, and N400. In the first set of experiments, we determined the probability of obtaining a statistically significant ERP effect for each component. In the second and third set of experiments, we determined the probability of obtaining a statistically significant difference in ERP amplitude within and between groups for each component. Results indicate that the rules of thumb for ERP experiment design in the literature often lead to underpowered studies. Going forward, these results provide researchers with experiment design guidelines that are specific to the component under study, allowing for the design of sufficiently powered ERP studies.

Reduced P300 amplitude is consistently associated with trait anhedonia across repeated assessments

Understanding how event-related potentials (ERPs) change following repeated assessments is critical to advance our understanding of neural mechanisms implicated in psychopathology. Specifically, it is unclear if associations between ERPs and individual differences can be reproduced when repeatedly measured within the same participants, or if clinical characteristics impact ERP trajectories over repeated assessments. The present study assessed P300 amplitude and latency from a flanker task at four time points over one month (M = 7.24 days between assessments [SD = 1.02]) in 79 female undergraduates to examine how P300 amplitude/latency changes across repeated assessments, the presence of associations between within- and between-subjects measures of current depressive symptoms and the P300, and if between-subjects depressive symptoms moderated change in P300 over repeated assessment. Results using multilevel modeling indicated a significant reduction in P300 amplitude and latency across assessments. Individuals with increased trait anhedonia (i.e., between-subjects) exhibited reduced P300 amplitudes across assessments; there were no associations of within-subjects fluctuations in anhedonia symptoms and P300 amplitude across assessments. There was also no interaction between number of assessments and between-subjects anhedonia in relation to P300 amplitude. Unlike anhedonia, between-subjects dysphoria was unrelated to P300. These results demonstrate a relatively specific and consistent association between an attenuated P300 amplitude and trait anhedonia across repeated assessments - data that may further suggest that flanker P300 amplitude reflects hedonic and motivational processes.

Developments in scalable strategies for detecting early markers of cognitive decline

Effective strategies for early detection of cognitive decline, if deployed on a large scale, would have individual and societal benefits. However, current detection methods are invasive or time-consuming and therefore not suitable for longitudinal monitoring of asymptomatic individuals. For example, biological markers of neuropathology associated with cognitive decline are typically collected via cerebral spinal fluid, cognitive functioning is evaluated from face-to-face assessments by experts and brain measures are obtained using expensive, non-portable equipment. Here, we describe scalable, repeatable, relatively non-invasive and comparatively inexpensive strategies for detecting the earliest markers of cognitive decline. These approaches are characterized by simple data collection protocols conducted in locations outside the laboratory: measurements are collected passively, by the participants themselves or by non-experts. The analysis of these data is, in contrast, often performed in a centralized location using sophisticated techniques. Recent developments allow neuropathology associated with potential cognitive decline to be accurately detected from peripheral blood samples. Advances in smartphone technology facilitate unobtrusive passive measurements of speech, fine motor movement and gait, that can be used to predict cognitive decline. Specific cognitive processes can be assayed using 'gamified' versions of standard laboratory cognitive tasks, which keep users engaged across multiple test sessions. High quality brain data can be regularly obtained, collected at-home by users themselves, using portable electroencephalography. Although these methods have great potential for addressing an important health challenge, there are barriers to be overcome. Technical obstacles include the need for standardization and interoperability across hardware and software. Societal challenges involve ensuring equity in access to new technologies, the cost of implementation and of any follow-up care, plus ethical issues.

The reliability of P300 and the influence of age, gender and education variables in a 50 years and older normative sample

OBJECTIVES

The present study aims to investigate the effects of age, gender, and level of education on P300 in a healthy population, aged 50 years and over; and determine the reliability metrics for different conditions and measurement methods.

METHOD

Auditory and visual oddball recordings of 171 healthy adults were investigated. A fully automated preprocessing was applied to elicit ERP P300. Maximum peak amplitude, latency and mean amplitudes were measured. Data were stratified by age, gender, and education to determine group-level differences by using repeat measures of ANOVA. The internal consistency of P300 was calculated by a split-half method using odd-even segments. Test-retest reliability was assessed by calculating the intraclass correlation coefficient (ICC).

RESULTS

Maximum peak P300 amplitudes were higher in the 50-64 years age group compared to the >65 years age group; and females showed increased P300 amplitudes compared to males. P300 measures showed fair to good internal consistency and poor to good test-retest reliability.

CONCLUSION

Age and gender should be taken into account when designing ERP studies with elderly individuals. P300 showed good internal consistency in general, between gender groups and age groups. Long-term test-retest reliability was lower but acceptable. These findings can be interpreted as the strength of P300 by being an objective and reliable method independent of cultural differences. Here we underline several factors that may affect P300 measures and discuss other possible factors that should be standardized for P300 to be used in clinical settings.

Intact differentiation of responses to socially-relevant emotional stimuli across psychotic disorders: An event-related potential (ERP) study

Event-related potential (ERP) studies of motivated attention in schizophrenia typically show intact sensitivity to affective vs. non-affective images depicting diverse types of content. However, it is not known whether this ERP pattern: 1) extends to images that solely depict social content, (2) applies across a broad sample with diverse psychotic disorders, and (3) relates to self-reported trait social anhedonia. We examined late positive potential (LPP) amplitudes to images involving people that were normatively pleasant (affiliative), unpleasant (threatening), or neutral in 97 stable outpatients with various psychotic disorders and 38 healthy controls. Both groups showed enhanced LPP to pleasant and unpleasant vs. neutral images to a similar degree, despite lower overall LPP in patients. Within the patients, there were no significant LPP differences among subgroups (schizophrenia vs. other psychotic disorders; affective vs. non-affective psychosis) for the valence effect (pleasant/unpleasant vs. neutral). Higher social anhedonia showed a small, significant relation to lower LPP to pleasant images across all groups. These findings suggest intact motivated attention to social images extends across psychotic disorder subgroups. Dimensional transdiagnostic analyses revealed a modest association between self-reported trait social anhedonia and an LPP index of neural sensitivity to pleasant affiliative images.

Neuroscience from the comfort of your home: Repeated, self-administered wireless dry EEG measures brain function with high fidelity

Recent advances have enabled the creation of wireless, “dry” electroencephalography (EEG) recording systems, and easy-to-use engaging tasks, that can be operated repeatedly by naïve users, unsupervised in the home. Here, we evaluated the validity of dry-EEG, cognitive task gamification, and unsupervised home-based recordings used in combination. Two separate cohorts of participants—older and younger adults—collected data at home over several weeks using a wireless dry EEG system interfaced with a tablet for task presentation. Older adults (n = 50; 25 females; mean age = 67.8 years) collected data over a 6-week period. Younger male adults (n = 30; mean age = 25.6 years) collected data over a 4-week period. All participants were asked to complete gamified versions of a visual Oddball task and Flanker task 5–7 days per week. Usability of the EEG system was evaluated via participant adherence, percentage of sessions successfully completed, and quantitative feedback using the System Usability Scale. In total, 1,449 EEG sessions from older adults (mean = 28.9; SD = 6.64) and 684 sessions from younger adults (mean = 22.87; SD = 1.92) were collected. Older adults successfully completed 93% of sessions requested and reported a mean usability score of 84.5. Younger adults successfully completed 96% of sessions and reported a mean usability score of 88.3. Characteristic event-related potential (ERP) components—the P300 and error-related negativity—were observed in the Oddball and Flanker tasks, respectively. Using a conservative threshold for inclusion of artifact-free data, 50% of trials were rejected per at-home session. Aggregation of ERPs across sessions (2–4, depending on task) resulted in grand average signal quality with similar Standard Measurement Error values to those of single-session wet EEG data collected by experts in a laboratory setting from a young adult sample. Our results indicate that easy-to-use task-driven EEG can enable large-scale investigations in cognitive neuroscience. In future, this approach may be useful in clinical applications such as screening and tracking of treatment response.

The viability of the frequency following response characteristics for use as biomarkers of cognitive therapeutics in schizophrenia

Deficits in early auditory information processing contribute to cognitive and psychosocial disability; this has prompted development of interventions that target low-level auditory processing, which may alleviate these disabilities. The frequency following response (FFR) is a constellation of event-related potential and frequency characteristics that reflect the processing of acoustic stimuli at the level of the brainstem and ascending portions of the auditory pathway. While FFR is a promising candidate biomarker of response to auditory-based cognitive training interventions, the psychometric properties of FFR in schizophrenia patients have not been studied. Here we assessed the psychometric reliability and magnitude of group differences across 18 different FFR parameters to determine which of these parameters demonstrate adequate internal consistency. Electroencephalography from 40 schizophrenia patients and 40 nonpsychiatric comparison subjects was recorded during rapid presentation of an auditory speech stimulus (6000 trials). Patients showed normal response amplitudes but longer latencies for most FFR peaks and lower signal-to-noise ratios (SNRs) than healthy subjects. Analysis of amplitude and latency estimates of peaks, however, indicated a need for a substantial increase in task length to obtain internal consistency estimates above 0.80. In contrast, excellent internal consistency (>0.95) was shown for FFR sustained responses. Only SNR scores reflecting the FFR sustained response yielded significant group differences and excellent internal consistency, suggesting that this measure is a viable candidate for use in clinical treatment studies. The present study highlights the use of internal consistency estimates to select FFR characteristics for use in future intervention studies interested in individual differences among patients.

Utility of linear mixed effects models for event-related potential research with infants and children

Event-related potentials (ERPs) are advantageous for investigating cognitive development. However, their application in infants/children is challenging given children's difficulty in sitting through the multiple trials required in an ERP task. Thus, a large problem in developmental ERP research is high subject exclusion due to too few analyzable trials. Common analytic approaches (that involve averaging trials within subjects and excluding subjects with too few trials, as in ANOVA and linear regression) work around this problem, but do not mitigate it. Moreover, these practices can lead to inaccuracies in measuring neural signals. The greater the subject exclusion, the more problematic inaccuracies can be. We review recent developmental ERP studies to illustrate the prevalence of these issues. Critically, we demonstrate an alternative approach to ERP analysis-linear mixed effects (LME) modeling-which offers unique utility in developmental ERP research. We demonstrate with simulated and real ERP data from preschool children that commonly employed ANOVAs yield biased results that become more biased as subject exclusion increases. In contrast, LME models yield accurate, unbiased results even when subjects have low trial-counts, and are better able to detect real condition differences. We include tutorials and example code to facilitate LME analyses in future ERP research.

Reliability of reward ERPs in middle-late adolescents using a custom and a standardized preprocessing pipeline

Despite advantage of neuroimaging measures in translational research frameworks, less is known about the psychometric properties thereof, especially in middle-late adolescents. Earlier, we examined evidence of convergent and incremental validity of reward anticipation and response event-related potentials (ERPs) and here we examined, in the same sample of 43 adolescents (M_age  = 15.67 years; SD = 1.01; range: 14-18; 32.6% boys), data quality (signal-to-noise ratio [SNR]), stability (mean amplitude across trials), and internal consistency (Cronbach's α and split-half reliability) of the same ERPs. Further, because observed time course and peak amplitude of ERP grand averages and thus findings on SNR, stability, and internal consistency may depend on preprocessing method, we employed a custom and a standardized preprocessing pipeline and compared findings across those. Using our custom pipeline, reward anticipation components were stable by the 40th trial, achieved acceptable internal consistency by the 19th, and all (but the stimulus-preceding negativity [SPN]) achieved acceptable SNR by the 41st trial. Initial response to reward components were stable by the 20th trial and achieved acceptable internal consistency by the 11th and acceptable SNR by the 45th trial. Difference scores had worse psychometric properties than parent measures. Time course and peak amplitudes of ERPs and thus results on SNR, stability, and internal consistency were comparable across preprocessing pipelines. In case of reward anticipation ERPs examined here, 41 trials (+4 artifacted and removed) and, in case of reward response ERPs, 45 trials (+5 artifacted) yielded stable and internally consistent estimates with acceptable SNR. Results are robust across preprocessing methods.

Open Science in human electrophysiology

Open science practices are gaining momentum in psychophysiological research, but at the nascent stage of this special issue in the International Journal of Psychophysiology there was no systematic collection of resources to support the adoption of open science practices specific to studies of human electrophysiology (EEG). The purpose of this special issue was to gather and provide resources that identify the idiosyncratic considerations and implications of open science practices specifically for studies of human EEG and event-related potentials (ERPs). Papers also show the importance of promoting good scientific practices in the application of open science principles to EEG and ERPs. This introduction to the special issue provides a roadmap for identifying the resources necessary to begin and improve the application of open science principles to EEG and ERP research. We are optimistic that open science practices will help increase the robustness, rigor, and replicability of EEG research and ultimately become the norm in studies of EEG and ERPs.

The data-processing multiverse of event-related potentials (ERPs): A roadmap for the optimization and standardization of ERP processing and reduction pipelines

In studies of event-related brain potentials (ERPs), numerous decisions about data processing are required to extract ERP scores from continuous data. Unfortunately, the systematic impact of these choices on the data quality and psychometric reliability of ERP scores or even ERP scores themselves is virtually unknown, which is a barrier to the standardization of ERPs. The aim of the present study was to optimize processing pipelines for the error-related negativity (ERN) and error positivity (Pe) by considering a multiverse of data processing choices. A multiverse analysis of a data processing pipeline examines the impact of a large set of different reasonable choices to determine the robustness of effects, such as the impact of different decisions on between-trial standard deviations (i.e., data quality) and between-condition differences (i.e., experimental effects). ERN and Pe data from 298 healthy young adults were used to determine the impact of different methodological choices on data quality and experimental effects (correct vs. error trials) at several key stages: highpass filtering, lowpass filtering, ocular artifact correction, reference, baseline adjustment, scoring sensors, and measurement procedure. This multiverse analysis yielded 3,456 ERN scores and 576 Pe scores per person. An optimized pipeline for ERN included a 15 Hz lowpass filter, ICA-based ocular artifact correction, and a region of interest (ROI) approach to scoring. For Pe, the optimized pipeline included a 0.10 Hz highpass filter, 30 Hz lowpass filter, regression-based ocular artifact correction, a -200 to 0 ms baseline adjustment window, and an ROI approach to scoring. The multiverse approach can be used to optimize pipelines for eventual standardization, which would support efforts toward establishing normative ERP databases. The proposed process of analyzing the data-processing multiverse of ERP scores paves the way for better refinement, identification, and selection of data processing parameters, ultimately improving the precision and utility of ERPs.

Internal consistency reliability of the P300 to novelty in infants: The influence of trial number and data loss due to artifacts

The P300 is an event-related potential component that reflects attention to motivationally salient stimuli and may be a promising tool to examine individual differences in cognitive-affective processing very early in development. However, the psychometric properties of the P300 in infancy are unknown, a fact that limits the component's utility as an individual difference measure in developmental research. To address this gap, 38 infants completed an auditory three-stimulus oddball task that included frequent standard, infrequent deviant, and novel stimuli. We quantified the P300 at a single electrode site and at region of interest (ROI) and examined the internal consistency reliability of the component, both via split-half reliability and as a function of trial number. Results indicated that the P300 to standard, deviant, and novel stimuli fell within moderate to high internal consistency reliability thresholds, and that scoring the component at an ROI led to slightly higher estimates of reliability. However, the percentage of data loss due to artifacts increased across the course of the task, suggesting that including more trials will not necessarily improve the reliability of the P300. Together, these results suggest that robust and reliable measurement of the P300 will require designing tasks that minimize trial number and maximize infant tolerability.

Understanding the Error in Psychopathology: Notable Intraindividual Differences in Neural Variability of Performance Monitoring

BACKGROUND

Abnormal performance monitoring is a possible transdiagnostic marker of psychopathology. Research on neural indices of performance monitoring, including the error-related negativity (ERN), typically examines group and interindividual (between-person) differences in mean/average scores. Intraindividual (within-person) variability in activity captures the capacity to dynamically adjust from moment to moment, and excessive variability appears maladaptive. Intraindividual variability in ERN represents a unique and largely unexamined dimension that might impact functioning. We tested whether psychopathology group differences (major depressive disorder [MDD], generalized anxiety disorder [GAD], obsessive-compulsive disorder [OCD]) or corresponding psychiatric symptoms account for intraindividual variability in single-trial ERN scores.

METHODS

High-density electroencephalogram (Electrical Geodesics, Inc.) was recorded during a semantic flanker task in 51 participants with MDD, 44 participants with GAD, 31 participants with OCD, and 56 psychiatrically-healthy participants. Mean ERN amplitude was scored 0-125ms following participant response across four fronto-central sites. Multilevel location-scale models were used to simultaneously examine interindividual and intraindividual differences in ERN.

RESULTS

Analyses indicated considerable intraindividual variability in ERN that was common across groups. However, we did not find strong evidence to support relationships between ERN and psychopathology groups or transdiagnostic symptoms.

CONCLUSIONS

These findings point to important methodological implications for studies of performance monitoring in healthy and clinical populations-the common assumption of fixed intraindividual variability (i.e., residual variance) may be inappropriate for ERN studies. Implementation of multilevel location-scale models in future research can leverage between-person differences in intraindividual variability in performance monitoring to gain a rich understanding of trial-to-trial performance monitoring dynamics.

Peak selection and latency jitter correction in developmental event-related potentials

Event-related potentials (ERPs) provide great insight into neural responses, yet developmental ERP work is plagued with inconsistent approaches to identifying and quantifying component latency. In this analytical review, we describe popular conventions for the selection of time windows for ERP analysis and assert that a data-driven strategy should be applied to the identification of component latency within individual participants' data. This may overcome weaknesses of more general approaches to peak selection; however, it does not account for trial-by-trial variability within a participant. This issue, known as ERP latency jitter, may blur the average ERP, misleading the interpretation of neural mechanisms. Recently, the ReSync MATLAB toolbox has been made available for correction of latency jitter. Although not created specifically for pediatric ERP data, this approach can be adapted for developmental researchers. We have demonstrated the use of the ReSync toolbox with individual infant and child datasets to illustrate its utility. Details about our peak detection script and the ReSync toolbox are provided. The adoption of data processing procedures that allow for accurate, study-specific component selection and reduce trial-by-trial asynchrony strengthens developmental ERP research by decreasing noise included in ERP analyses and improving the representation of the neural response.

Evaluation of the frequency following response as a predictive biomarker of response to cognitive training in schizophrenia

Neurophysiological biomarkers of auditory processing show promise predicting outcomes following auditory-based targeted cognitive training (TCT) in schizophrenia, but the viability of the frequency following response (FFR) as a biomarker has yet to be examined, despite its ecological and face validity for auditory-based interventions. FFR is an event-related potential (ERP) that reflects early auditory processing. We predicted that schizophrenia patients would show acute- and longer-term FFR malleability in the context of TCT. Patients were randomized to either TCT (n = 30) or treatment as usual (TAU; n = 22), and electroencephalography was recorded during rapid presentation of an auditory speech stimulus before treatment, after one hour of training, and after 30 h of training. Whereas patients in the TCT group did not show changes in FFR after training, amplitude reductions were observed in the TAU. FFR was positively associated with performance on a measure of single word-in-noise perception in the TCT group, and with a measure of sentence-in-noise perception in both groups. Psychometric reliability analyses of FFR scores indicated high internal consistency but low one-hour and 12-week test-rest reliability. These findings support the dissociation between measures of speech discriminability along the hierarchy of cortical and subcortical early auditory information processing in schizophrenia.

Correct response negativity may reflect subjective value of reaction time under regulatory fit in a speed-rewarded task

Error-related negativity (ERN), an electroencephalogram (EEG) component following an erroneous response, has been associated with the subjective motivational relevance of error commission. A smaller EEG event, the correct response negativity (CRN), occurs after a correct response. It is unclear why correct behavior evokes a neural response similar to error commission. CRN might reflect suboptimal performance: in tasks where speed is motivationally relevant (i.e., incentivized), a correct but slow response may be experienced as a minor error. The literature is mixed on the relationship between CRN and response time (RT), possibly due to different motivational structures, tasks, or individual traits. We examined ERN and CRN in a go/no-go task where correctness and speed were encouraged using a points-based feedback system. A key individual trait, regulatory focus, describes a person's tendency to seek gains (promotion focus) and avoid losses (prevention focus). Trait regulatory focus was measured, and participants were randomly assigned to one of three conditions: points gain, points loss, and informative-only feedback. Participants committed too few errors to reliably model ERN effects. CRN amplitude related to RT in all feedback conditions, with slower responses having larger CRN. Participants with stronger promotion focus had a more exaggerated RT/CRN relationship in the point gain condition, suggesting that regulatory fit influences the motivational relevance of speed and thus the negative subjective experience and CRN for slower responses. These findings are consistent with the claim that CRN reflects RT when RT is motivationally relevant and that the CRN/RT relationship reflects the degree of subjective motivational relevance.

Neurocognitive efficiency in breast cancer survivorship: A performance monitoring ERP study

Breast cancer diagnosis and treatment can lead to longer term cognitive and emotional vulnerability, making the ability to efficiently adapt to setbacks critical. Whilst cancer-related cognitive impairments (CRCI) are often reported amongst breast cancer survivors, investigation into the capacity to efficiently process errors is limited. The present study investigated the neurocognitive correlates of cognitive-control related performance monitoring, an important function influencing behavioural adjustment to mistakes. 62 participants (30 Breast Cancer Survivors, 32 Non-Cancer) completed a modified flanker task designed to challenge response inhibition as we measured neurocognitive indices of performance monitoring (ERN, the error-related negativity; CRN, the correct-response negativity; Pe, the error positivity). Findings indicated a blunted CRN and larger ∆ERN in the breast cancer survivors compared to the non-cancer group, in the absence of performance effects. This was followed by a larger Pe in the breast cancer survivors' group, indicating an exaggerated performance monitoring response. For women affected by breast cancer, findings suggest an early disrupted neural response to monitoring cognitive performance, followed by the requirement for more effortful processing in the conscious response to errors, indicating deficits in neurocognitive efficiency. These findings have important implications for developing cognitive rehabilitation programmes for breast cancer survivors affected by cognitive dysfunction to assist in the monitoring and adjustment of performance required to meet established goals in the face of adversity.

Standardized measurement error: A universal metric of data quality for averaged event-related potentials

Event-related potentials (ERPs) can be very noisy, and yet, there is no widely accepted metric of ERP data quality. Here, we propose a universal measure of data quality for ERP research-the standardized measurement error (SME)-which is a special case of the standard error of measurement. Whereas some existing metrics provide a generic quantification of the noise level, the SME quantifies the data quality (precision) for the specific amplitude or latency value being measured in a given study (e.g., the peak latency of the P3 wave). It can be applied to virtually any value that is derived from averaged ERP waveforms, making it a universal measure of data quality. In addition, the SME quantifies the data quality for each individual participant, making it possible to identify participants with low-quality data and "bad" channels. When appropriately aggregated across individuals, SME values can be used to quantify the combined impact of the single-trial EEG noise and the number of trials being averaged together on the effect size and statistical power in a given experiment. If SME values were regularly included in published articles, researchers could identify the recording and analysis procedures that produce the highest data quality, which could ultimately lead to increased effect sizes and greater replicability across the field.