Estimating statistical power for event-related potential studies using the late positive potential

Decoding in the Fourth Dimension: Classification of Temporal Patterns and Their Generalization Across Locations

Neuroimaging research has increasingly used decoding techniques, in which multivariate statistical methods identify patterns in neural data that allow the classification of experimental conditions or participant groups. Typically, the features used for decoding are spatial in nature, including voxel patterns and electrode locations. However, the strength of many neurophysiological recording techniques such as electroencephalography or magnetoencephalography is in their rich temporal, rather than spatial, content. The present report introduces the time-GAL toolbox, which implements a decoding method based on time information in electrophysiological recordings. The toolbox first quantifies the decodable information contained in neural time series. This information is then used in a subsequent step, generalization across location (GAL), which characterizes the relationship between sensor locations based on their ability to cross-decode. Two datasets are used to demonstrate the usage of the toolbox, involving (1) event-related potentials in response to affective pictures and (2) steady-state visual evoked potentials in response to aversively conditioned grating stimuli. In both cases, experimental conditions were successfully decoded based on the temporal features contained in the neural time series. Spatial cross-decoding occurred in regions known to be involved in visual and affective processing. We conclude that the approach implemented in the time-GAL toolbox holds promise for analyzing neural time series from a wide range of paradigms and measurement domains providing an assumption-free method to quantifying differences in temporal patterns of neural information processing and whether these patterns are shared across sensor locations.

Beneath the Surface of Self-Reports: Dissecting Subjective and Neural Responses to Age-Specific Visual Stimuli

The current study examined how adolescents respond to emotionally arousing images that are considered age-appropriate, such as sports, food, and threatening animals. Prior research in adults has shown a mismatch between subjective arousal ratings and the late positive potential (LPP) for pleasant images, and we aimed to test whether this discrepancy is also present in adolescents. The results showed a larger LPP in response to unpleasant, compared to pleasant, contents. However, comparisons across the different emotional contents showed that the concordance between subjective and neural engagement varies depending on the emotional contents of the scenes. Specifically, images of threatening animals were rated high in emotional arousal and prompted the largest LPP in adolescents, while images of sad people and images of mundane activities were rated lower in emotional arousal and prompted the smallest LPP responses. However, adolescents showed significant divergence in their responses to pleasant images depicting food and sport: despite being rated high in emotional arousal, these images elicited relatively small LPPs. These results highlight the challenges of selecting emotional pictures to assess neuroaffective responses to pleasant and unpleasant pictures in adolescents. To overcome these challenges, future studies may adopt experimental paradigms that will allow researchers to measure neuroaffective responses not just in free-viewing contexts but also during anticipation and reception of actual rewards (and punishments).

EEG might be better left alone, but ERPs must be attended to: Optimizing the late positive potential preprocessing pipeline

The late positive potential (LPP) is an ERP component commonly used to study emotional processes and has been proposed as a neuroaffective biomarker for research and clinical uses. These applications, however, require standardized procedures for elicitation and ERP data processing. We evaluated the impact of different EEG preprocessing steps on the LPP's data quality and statistical power. Using a diverse sample of 158 adults, we implemented a multiverse analytical approach to compare preprocessing pipelines that progressively incorporated more steps: artifact detection and rejection, bad channel interpolation, and bad segment deletion. We assessed each pipeline's effectiveness by computing the standardized measurement error (SME) and conducting simulated experiments to estimate statistical power in detecting significant LPP differences between emotional and neutral images. Our findings highlighted that artifact rejection is crucial for enhancing data quality and statistical power. Voltage thresholds to reject trials contaminated by artifacts significantly affected SME and statistical power. Once artifact detection was optimized, further steps provided minor improvements in data quality and statistical power. Importantly, different preprocessing pipelines yielded similar outcomes. These results underscore the robustness of the LPP's affective modulation to preprocessing choices and the critical role of effective artifact management. By refining and standardizing preprocessing procedures, the LPP can become a reliable neuroaffective biomarker, supporting personalized clinical interventions for affective disorders.

Stimulus-related oscillatory brain activity discriminates hoarding disorder from OCD and healthy controls

Hoarding disorder (HD) and obsessive-compulsive disorder (OCD) are highly comorbid and genetically related, but their similarities and differences at the neural level are not well characterized. The present study examined the time-frequency information contained in stimulus-related EEG data as participants worked on a visual flanker task. Three groups were included: participants diagnosed with HD (N = 33), OCD (N = 26), and healthy controls (N = 35). Permutation-controlled mass-univariate analyses found no differences between groups in terms of the magnitude of the oscillatory responses. Differences between groups were found selectively for phase-based measures (phase-locking across trials and across sensors) in time ranges well after those consistent with initial visuocortical processes, in the alpha (10 Hz) as well as theta and beta frequency bands, centered around 6 Hz and 15 Hz, respectively. Specifically, HD showed attenuated phase locking in theta and alpha compared to OCD and HC, while OCD showed heightened inter-site phase locking in alpha/beta. Including age as a covariate attenuated, but did not eliminate, the group differences. These findings point to signatures of cortical dynamics and cortical communication task processing that are unique to HD, and which are specifically present during higher-order visual cognition such as stimulus-response mapping, response selection, and action monitoring.

How is social dominance related to our short-term memory? An EEG/ERP investigation of encoding and retrieval during a working memory task

Social hierarchies exist in all societies and impact cognitive functions, brain mechanisms, social interactions, and behaviors. High status individuals often exhibit enhanced working memory (WM) performance compared to lower status individuals. This study examined whether individual differences in social dominance, as a predictor of future status, relate to WM abilities. Five hundred and twenty-five students completed the Personality Research Form dominance subscale questionnaire. From this sample, students with the highest and lowest scores were invited to participate in the study. Sixty-four participants volunteered to take part and were subsequently categorized into high- and low-dominance groups based on their dominance subscale questionnaire (PRF_d) scores. They performed a Sternberg WM task with set sizes of 1, 4, or 7 letters while their EEG was recorded. Event-related potential (ERP) and power spectral analysis revealed significantly reduced P3b amplitude and higher event-related synchronization (ERS) of theta and beta during encoding and retrieval phases in the high-than low-dominance group. Despite these neural processing differences, behavioral performance was equivalent between groups, potentially reflecting comparable cognitive load demands of the task across dominance levels. Further, there were similar P3b patterns for each set-size within groups. These findings provide initial evidence that individual differences in social dominance trait correlate with WM functioning, as indexed by neural processing efficiency during WM performance.

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).

Improved data quality and statistical power of trial-level event-related potentials with Bayesian random-shift Gaussian processes

Studies of cognitive processes via electroencephalogram (EEG) recordings often analyze group-level event-related potentials (ERPs) averaged over multiple subjects and trials. This averaging procedure can obscure scientifically relevant variability across subjects and trials, but has been necessary due to the difficulties posed by inference of trial-level ERPs. We introduce the Bayesian Random Phase-Amplitude Gaussian Process (RPAGP) model, for inference of trial-level amplitude, latency, and ERP waveforms. We apply RPAGP to data from a study of ERP responses to emotionally arousing images. The model estimates of trial-specific signals are shown to greatly improve statistical power in detecting significant differences in experimental conditions compared to existing methods. Our results suggest that replacing the observed data with the de-noised RPAGP predictions can potentially improve the sensitivity and accuracy of many of the existing ERP analysis pipelines.

Different language control mechanisms in comprehension and production: Evidence from paragraph reading

Chinese-English bilinguals read paragraphs with language switches using a rapid serial visual presentation paradigm silently while ERPs were measured (Experiment 1) or read them aloud (Experiment 2). Each paragraph was written in either Chinese or English with several function or content words switched to the other language. In Experiment 1, language switches elicited an early, long-lasting positivity when switching from the dominant language to the nondominant language, but when switching to the dominant language, the positivity started later, and was never larger than when switching to the nondominant language. In addition, switch effects on function words were not significantly larger than those on content words in any analyses. In Experiment 2, participants produced more cross-language intrusion errors when switching to the dominant than to the nondominant language, and more errors on function than content words. These results implicate different control mechanisms in bilingual language selection across comprehension and production.

Spatiotemporal characteristics of the neural representation of event concepts

Events are a fundamentally important part of our understanding of the world. How lexical concepts denoting events are represented in the brain remains controversial. We conducted two experiments using event and object nouns matched on a range of psycholinguistic variables, including concreteness, to examine spatial and temporal characteristics of event concepts. Both experiments used magnitude and valence tasks on event and object nouns. The fMRI experiment revealed a distributed set of regions for events, including the angular gyrus, anterior temporal lobe, and posterior cingulate across tasks. In the EEG experiment, events and objects differed in amplitude within the 300-500 ms window. Together these results shed light into the spatiotemporal characteristics of event concept representation and show that event concepts are represented in the putative hubs of the semantic system. While these hubs are typically associated with object semantics, they also represent events, and have a likely role in temporal integration.

Estimating statistical power for ERP studies using the auditory N1, Tb, and P2 components

The N1, Tb, and P2 components of the event-related potential (ERP) are thought to reflect the sequential processing of auditory stimuli in the human brain. Despite their extensive use in biological, cognitive, and clinical neuroscience, there are no guidelines for how to appropriately power ERP studies using these components. In the present study, we investigated how the number of trials, number of participants, effect magnitude, and study design influenced statistical power. Using Monte Carlo simulations of ERP data from a passive listening task, we determined the probability of finding a statistically significant effect in 58,900 experiments repeated 1,000 times each. We found that as the number of trials, number of participants, and effect magnitude increased, so did statistical power. We also found that increasing the number of trials had a bigger effect on statistical power for within-subject designs than for between-subject designs, and that within-subject designs required a smaller number of trials and participants to provide the same level of statistical power for a given effect magnitude than between-subject designs. These results show that it is important to carefully consider these factors when designing ERP studies, rather than relying on tradition or anecdotal evidence. To improve the robustness and reproducibility of ERP research, we have built an online statistical power calculator (https://bradleynjack.shinyapps.io/ErpPowerCalculator), which we hope will allow researchers to estimate the statistical power of previous studies, as well as help them design appropriately-powered studies in the future.

Exenatide as an adjunct to nicotine patch for smoking cessation and prevention of postcessation weight gain among treatment-seeking smokers with pre-diabetes and/or overweight: study protocol for a randomised, placebo-controlled clinical trial

INTRODUCTION

Obesity and smoking are the two leading causes of preventable death in the USA. Unfortunately, most smokers gain weight after quitting. Postcessation weight gain (PCWG) is frequently cited as one of the primary barriers to a quit attempt and a common cause of relapse. Further, excessive PCWG may contribute to the onset or progression of metabolic conditions, such as hyperglycaemia and obesity. The efficacy of the current treatments for smoking cessation is modest, and these treatments have no clinically meaningful impact on mitigating PCWG. Here, we outline a novel approach using glucagon-like peptide 1 receptor agonists (GLP-1RA), which have demonstrated efficacy in reducing both food and nicotine intake. This report describes the design of a double-blind, placebo-controlled, randomised clinical trial that evaluates the effects of the GLP-1RA exenatide as an adjunct to nicotine patches on smoking abstinence and PCWG.

METHODS AND ANALYSIS

The study will be conducted at two university-affiliated research sites in Houston, Texas, the UTHealth Center for Neurobehavioral Research on Addiction and Baylor College of Medicine Michael E. DeBakey VA Medical Centre. The sample will consist of 216 treatment-seeking smokers with pre-diabetes (haemoglobin A1c of 5.7%-6.4%) and/or overweight (body mass index of 25 kg/m² or above). Participants will be randomised (1:1) to receive subcutaneous injections of placebo or 2 mg exenatide, once weekly for 14 weeks. All participants will receive transdermal nicotine replacement therapy and brief smoking cessation counselling for 14 weeks. The primary outcomes are 4-week continuous abstinence and changes in body weight at the end of treatment. The secondary outcomes are (1) abstinence and changes in body weight at 12 weeks post end of treatment and (2) changes in neuroaffective responses to cigarette-related and food-related cues as measured by electroencephalogram.

ETHICS AND DISSEMINATION

The study has been approved by the UTHealth Committee for the Protection of Human Subjects (HSC-MS-21-0639) and Baylor College of Medicine Institutional Review Board (H-50543). All participants will sign informed consent. The study results will be disseminated via peer-reviewed publications and conference presentations.

TRIAL REGISTRATION NUMBER

NCT05610800.

Do numbers make us handy? Behavioral and electrophysiological evidence for number-hand congruency effect

Finger counting facilitates numerical representations and mathematical processing. The current study investigated the association between finger counting habits and number processing by employing behavioral and electrophysiological measures. We explored whether small and large numerical primes influence the recognition of embodied target hand stimuli. Twenty-four right-handed participants that were grouped into right-starters (n = 13) and left-starters (n = 11) for finger counting performed a hand recognition task that consisted of numerical magnitudes as prime and hand recognition as targets. Based on the finger counting habits, congruent (i.e., left-starters: small number/left hand or large number/right hand; right-starters: small number/right hand or large number/left hand) and incongruent (i.e., left-starters: large number/left hand or small number/right hand; right-starters: large number/right hand or small number/left hand) conditions were presented to the participants. The participants were required to indicate whether the targets were left or right hand by simply pressing the left or the right key, respectively. Results indicated faster reaction times (RTs) for congruent as opposed to incongruent trials for all participants. The mean amplitude of the centro-parietal P300 component was significantly increased for the incongruent compared to congruent condition, indicating increased mental effort. Also, analysis of the latency of the P300 in terms of congruency effect in all participants revealed significant results. These combined results provide behavioral and electrophysiological evidence indicating the embodied nature of numbers. The results are interpreted in light of the general findings related to the P300 component. This research supports the association of number-hand representations and corroborates the idea of embodied numerosity.

Effects of Transcranial Direct Current Stimulation on Attentional Bias to Methamphetamine Cues and Its Association With EEG-Derived Functional Brain Network Topology

BACKGROUND

Although transcranial direct current stimulation (tDCS) has shown to potentially mitigate drug craving and attentional bias to drug-related stimuli, individual differences in such modulatory effects of tDCS are less understood. In this study, we aimed to investigate a source of the inter-subject variability in the tDCS effects that can be useful for tDCS-based treatments of individuals with methamphetamine (MA) use disorder (IMUD).

METHODS

Forty-two IMUD (all male) were randomly assigned to receive a single-session of either sham or real bilateral tDCS (anodal right/cathodal left) over the dorsolateral prefrontal cortex. The tDCS effect on MA craving and biased attention to drug stimuli were investigated by quantifying EEG-derived P3 (a measure of initial attentional bias) and late positive potential (LPP; a measure of sustained motivated attention) elicited by these stimuli. To assess the association of changes in P3 and LPP with brain connectivity network (BCN) topology, the correlation between topology metrics, specifically those related to the efficiency of information processing, and the tDCS effect was investigated.

RESULTS

The P3 amplitude significantly decreased following the tDCS session, whereas the amplitudes increased in the sham group. The changes in P3 amplitudes were significantly correlated with communication efficiency measured by BCN topology metrics (r = -0.47, P = .03; r = -0.49, P = .02). There was no significant change in LPP amplitude due to the tDCS application.

CONCLUSIONS

These findings validate that tDCS mitigates initial attentional bias, but not the sustained motivated attention, to MA stimuli. Importantly, however, results also show that the individual differences in the effects of tDCS may be underpinned by communication efficiency of the BCN topology, and therefore, these BCN topology metrics may have the potential to robustly predict the effectiveness of tDCS-based interventions on MA craving and attentional bias to MA stimuli among IMUD.

The more you know: Schema-congruency supports associative encoding of novel compound words. Evidence from event-related potentials

We aimed to investigate the neurocognitive mechanisms of event congruency with prior (schema) knowledge for the learning of novel compound words. Event-related potentials (ERPs) were recorded during an incidental learning task, in which novel noun-noun compounds were presented in a semantically congruent context, enabling schema-supported processing, or in a neutral context. As expected, associative memory performance was better for compounds preceded by a congruent context. Although the N400 was attenuated in the congruent condition, subsequent memory effects (SMEs) in the N400 time interval did not differ across conditions, suggesting that the processes reflected in the N400 cannot account for the memory advantage in the congruent condition. However, a parietal SME was obtained for compounds preceded by a congruent context, only, which we interpret as reflecting the schema-supported formation of a conceptual compound representation. A late frontal SME was obtained in both conditions, presumably reflecting the more general inter-item associative encoding of compound constituents.

Do rare emotional scenes enhance LPP modulation?

The slow wave late positive potential (LPP) is one of the most dependable measures of emotional processing in human neuroscience. While LPP positivity shows modest malleability by emotional regulation and competing tasks, its fundamental enhancement by emotional scene perception is extremely reliable. Here we assess the impact of emotional scene frequency (67%, 50% and 17%) on the strength of LPP modulation, across 3 groups of participants, using consistent presentation and analysis methods. The results demonstrate strong consistency in the strength of emotional modulation across frequent, equiprobable, and rare emotion conditions. However, a small enhancement of LPP positivity was found during unpleasant scenes in the rare emotion condition. The LPP thus appears to be largely insensitive to contextual features such as scene frequency and predictability, suggesting that strong emotional cues persistently engage orienting and evaluation processes because this tendency was selected in phylogeny.

Effects of emotional study context on immediate and delayed recognition memory: Evidence from event-related potentials

Whilst research has largely focused on the recognition of emotional items, emotion may be a more subtle part of our surroundings and conveyed by context rather than by items. Using ERPs, we investigated which effects an arousing context during encoding may have for item-context binding and subsequent familiarity-based and recollection-based item-memory. It has been suggested that arousal could facilitate item-context bindings and by this enhance the contribution of recollection to subsequent memory judgements. Alternatively, arousal could shift attention onto central features of a scene and by this foster unitisation during encoding. This could boost the contribution of familiarity to remembering. Participants learnt neutral objects paired with ecologically highly valid emotional faces whose names later served as neutral cues during an immediate and delayed test phase. Participants identified objects faster when they had originally been studied together with emotional context faces. Items with both neutral and emotional context elicited an early frontal ERP old/new difference (200-400 ms). Neither the neurophysiological correlate for familiarity nor recollection were specific to emotionality. For the ERP correlate of recollection, we found an interaction between stimulus type and day, suggesting that this measure decreased to a larger extend on Day 2 compared with Day 1. However, we did not find direct evidence for delayed forgetting of items encoded in emotional contexts at Day 2. Emotion at encoding might make retrieval of items with emotional context more readily accessible, but we found no significant evidence that emotional context either facilitated familiarity-based or recollection-based item-memory after a delay of 24 h.

Psychometric properties of the late positive potential in adult females

The late positive potential (LPP) is an event related potential (ERP) that has been used to study the processing of emotional stimuli and has been proposed as a biomarker for depression. However, to relate the LPP to trait-like individual differences it is important to first determine its psychometric properties. The current study assessed the reliability and internal consistency of the LPP in a large adult sample of women. We assessed the LPP following pleasant, unpleasant, and neutral images at baseline (n = 266) and approximately eight weeks later (n = 193). The LPP demonstrated good test-retest reliability and good-to-excellent internal consistency at both time points. The LPP response was not associated with concurrent depressive symptoms. These findings suggest the LPP is a relatively stable and reliable measure of emotional processing, but further research with larger samples and more elevated depression scores may be needed in order to clarify the associations between depression and LPP.

Open science in psychophysiology: An overview of challenges and emerging solutions

The present review is the result of a one-day workshop on open science, held at the Annual Meeting of the Society for Psychophysiological Research in Washington, DC, September 2019. The contributors represent psychophysiological researchers at different career stages and from a wide spectrum of institutions. The state of open science in psychophysiology is discussed from different perspectives, highlighting key challenges, potential benefits, and emerging solutions that are intended to facilitate open science practices. Three domains are emphasized: data sharing, preregistration, and multi-site studies. In the context of these broader domains, we present potential implementations of specific open science procedures such as data format harmonization, power analysis, data, presentation code and analysis pipeline sharing, suitable for psychophysiological research. Practical steps are discussed that may be taken to facilitate the adoption of open science practices in psychophysiology. These steps include (1) promoting broad and accessible training in the skills needed to implement open science practices, such as collaborative research and computational reproducibility initiatives, (2) establishing mechanisms that provide practical assistance in sharing of processing pipelines, presentation code, and data in an efficient way, and (3) improving the incentive structure for open science approaches. Throughout the manuscript, we provide references and links to available resources for those interested in adopting open science practices in their research.

Biomarkers and neuromodulation techniques in substance use disorders

Addictive disorders are a severe health concern. Conventional therapies have just moderate success and the probability of relapse after treatment remains high. Brain stimulation techniques, such as transcranial Direct Current Stimulation (tDCS) and Deep Brain Stimulation (DBS), have been shown to be effective in reducing subjectively rated substance craving. However, there are few objective and measurable parameters that reflect neural mechanisms of addictive disorders and relapse. Key electrophysiological features that characterize substance related changes in neural processing are Event-Related Potentials (ERP). These high temporal resolution measurements of brain activity are able to identify neurocognitive correlates of addictive behaviours. Moreover, ERP have shown utility as biomarkers to predict treatment outcome and relapse probability. A future direction for the treatment of addiction might include neural interfaces able to detect addiction-related neurophysiological parameters and deploy neuromodulation adapted to the identified pathological features in a closed-loop fashion. Such systems may go beyond electrical recording and stimulation to employ sensing and neuromodulation in the pharmacological domain as well as advanced signal analysis and machine learning algorithms. In this review, we describe the state-of-the-art in the treatment of addictive disorders with electrical brain stimulation and its effect on addiction-related neurophysiological markers. We discuss advanced signal processing approaches and multi-modal neural interfaces as building blocks in future bioelectronics systems for treatment of addictive disorders.