Open Science in human electrophysiology

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.

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.

Open and reproducible neuroimaging: From study inception to publication

Empirical observations of how labs conduct research indicate that the adoption rate of open practices for transparent, reproducible, and collaborative science remains in its infancy. This is at odds with the overwhelming evidence for the necessity of these practices and their benefits for individual researchers, scientific progress, and society in general. To date, information required for implementing open science practices throughout the different steps of a research project is scattered among many different sources. Even experienced researchers in the topic find it hard to navigate the ecosystem of tools and to make sustainable choices. Here, we provide an integrated overview of community-developed resources that can support collaborative, open, reproducible, replicable, robust and generalizable neuroimaging throughout the entire research cycle from inception to publication and across different neuroimaging modalities. We review tools and practices supporting study inception and planning, data acquisition, research data management, data processing and analysis, and research dissemination. An online version of this resource can be found at https://oreoni.github.io. We believe it will prove helpful for researchers and institutions to make a successful and sustainable move towards open and reproducible science and to eventually take an active role in its future development.

Good scientific practice in EEG and MEG research: Progress and perspectives

Good scientific practice (GSP) refers to both explicit and implicit rules, recommendations, and guidelines that help scientists to produce work that is of the highest quality at any given time, and to efficiently share that work with the community for further scrutiny or utilization. For experimental research using magneto- and electroencephalography (MEEG), GSP includes specific standards and guidelines for technical competence, which are periodically updated and adapted to new findings. However, GSP also needs to be regularly revisited in a broader light. At the LiveMEEG 2020 conference, a reflection on GSP was fostered that included explicitly documented guidelines and technical advances, but also emphasized intangible GSP: a general awareness of personal, organizational, and societal realities and how they can influence MEEG research. This article provides an extensive report on most of the LiveMEEG contributions and new literature, with the additional aim to synthesize ongoing cultural changes in GSP. It first covers GSP with respect to cognitive biases and logical fallacies, pre-registration as a tool to avoid those and other early pitfalls, and a number of resources to enable collaborative and reproducible research as a general approach to minimize misconceptions. Second, it covers GSP with respect to data acquisition, analysis, reporting, and sharing, including new tools and frameworks to support collaborative work. Finally, GSP is considered in light of ethical implications of MEEG research and the resulting responsibility that scientists have to engage with societal challenges. Considering among other things the benefits of peer review and open access at all stages, the need to coordinate larger international projects, the complexity of MEEG subject matter, and today's prioritization of fairness, privacy, and the environment, we find that current GSP tends to favor collective and cooperative work, for both scientific and for societal reasons.

Non-invasive brain stimulation modulates neural correlates of performance monitoring in patients with obsessive-compulsive disorder

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Effects of tDCS on performance monitoring examined in OCD and healthy individuals.

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A preregistered, randomized, sham-controlled tDCS–EEG study was conducted.

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Cathodal tDCS over the pre-SMA reduced the error-related negativity (ERN).

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Correct-response negativity was enhanced, error positivity reduced by cathodal tDCS.

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The findings substantiate the role of the ERN as a target for new interventions.

Overactive performance monitoring, as reflected by enhanced neural responses to errors (the error-related negativity, ERN), is considered a biomarker for obsessive-compulsive disorder (OCD) and may be a promising target for novel treatment approaches. Prior research suggests that non-invasive brain stimulation with transcranial direct current stimulation (tDCS) may reduce the ERN in healthy individuals, yet no study has investigated its efficacy in attenuating the ERN in OCD. In this preregistered, randomized, sham-controlled, crossover study, we investigated effects of tDCS on performance monitoring in patients with OCD (n = 28) and healthy individuals (n = 28). Cathodal and sham tDCS was applied over the presupplementary motor area (pre-SMA) in two sessions, each followed by electroencephalogram recording during a flanker task. Cathodal tDCS reduced the ERN amplitude compared to sham tDCS, albeit this effect was only marginally significant (p = .052; mean difference: 0.86 μV). Additionally, cathodal tDCS reduced the correct-response negativity and increased the error positivity. These neural modulations were not accompanied by behavioral changes. Moreover, we found no evidence that the tDCS effect was more pronounced in the patient group. In summary, our findings indicate that tDCS over the pre-SMA modulates neural correlates of performance monitoring across groups. Therefore, this study represents a valuable starting point for future research to determine whether repeated tDCS application induces a more pronounced ERN attenuation and normalizes aberrant performance monitoring in the long term, thereby potentially alleviating obsessive-compulsive symptoms and providing a psychophysiological intervention strategy for individuals who do not benefit sufficiently from existing interventions.