Frontal Alpha Asymmetry and Theta Oscillations Associated With Information Sharing Intention

Social media has gained increasing importance in many aspects of everyday life, from building relationships to establishing collaborative networks between individuals worldwide. Sharing behavior is an essential part of maintaining these dynamic networks. However, the precise neural factors that could be related to sharing behavior in online communities remain unclear. In this study, we recorded electroencephalographic (EEG) oscillations of human subjects while they were watching short videos. The subjects were later asked to evaluate the videos based on how much they liked them and whether they would share them. We found that, at the population level, subjects watching videos that would not be shared had higher power spectral density (PSD) amplitudes in the theta band (4–8 Hz), primarily over the frontal and parietal sites of the right hemisphere, than subjects watching videos that would be shared. Previous studies have associated task disengagement with an increase in scalp-wide theta activation, which can be interpreted as a mind-wandering effect. This might suggest that the decision to not share the video may lead to a more automatic/effortless neural pattern. We also found that watching videos that would be shared was associated with lower PSD amplitudes in the alpha band (8–12 Hz) over the central and right frontal sites, and with more negative scores of frontal alpha asymmetry (FAA) index scores. These results may be related to previous work linking right-sided frontal EEG asymmetry to the pursuit of social conformity and avoidance of negative outcomes, such as social isolation. Finally, using support vector machine (SVM) algorithms, we show that these EEG parameters and preference rating scores can be used to improve the predictability of sharing information behavior. The information sharing-related EEG pattern described here could therefore improve our understanding of the neural markers associated with sharing behavior and contribute to studies about stimuli propagation

EEGManyPipelines: A Large-scale, Grassroots Multi-analyst Study of Electroencephalography Analysis Practices in the Wild

The ongoing reproducibility crisis in psychology and cognitive neuroscience has sparked increasing calls to re-evaluate and reshape scientific culture and practices. Heeding those calls, we have recently launched the EEGManyPipelines project as a means to assess the robustness of EEG research in naturalistic conditions and experiment with an alternative model of conducting scientific research. One hundred sixty-eight analyst teams, encompassing 396 individual researchers from 37 countries, independently analyzed the same unpublished, representative EEG data set to test the same set of predefined hypotheses and then provided their analysis pipelines and reported outcomes. Here, we lay out how large-scale scientific projects can be set up in a grassroots, community-driven manner without a central organizing laboratory. We explain our recruitment strategy, our guidance for analysts, the eventual outputs of this project, and how it might have a lasting impact on the field

ARTEM-IS lexicon

ARTEM-IS lexicon is a work in progress to create a vocabulary of EEG terms used in ARTEM-IS templates, which will serve as an accompanying tool to the templates

EEGManyPipelines:A Large-scale, Grassroots Multi-analyst Study of Electroencephalography Analysis Practices in the Wild

The ongoing reproducibility crisis in psychology and cognitive neuroscience has sparked increasing calls to re-evaluate and reshape scientific culture and practices. Heeding those calls, we have recently launched the EEGManyPipelines project as a means to assess the robustness of EEG research in naturalistic conditions and experiment with an alternative model of conducting scientific research. One hundred sixty-eight analyst teams, encompassing 396 individual researchers from 37 countries, independently analyzed the same unpublished, representative EEG data set to test the same set of predefined hypotheses and then provided their analysis pipelines and reported outcomes. Here, we lay out how large-scale scientific projects can be set up in a grassroots, community-driven manner without a central organizing laboratory. We explain our recruitment strategy, our guidance for analysts, the eventual outputs of this project, and how it might have a lasting impact on the field.</p

EEGManyPipelines:A Large-scale, Grassroots Multi-analyst Study of Electroencephalography Analysis Practices in the Wild

The ongoing reproducibility crisis in psychology and cognitive neuroscience has sparked increasing calls to re-evaluate and reshape scientific culture and practices. Heeding those calls, we have recently launched the EEGManyPipelines project as a means to assess the robustness of EEG research in naturalistic conditions and experiment with an alternative model of conducting scientific research. One hundred sixty-eight analyst teams, encompassing 396 individual researchers from 37 countries, independently analyzed the same unpublished, representative EEG data set to test the same set of predefined hypotheses and then provided their analysis pipelines and reported outcomes. Here, we lay out how large-scale scientific projects can be set up in a grassroots, community-driven manner without a central organizing laboratory. We explain our recruitment strategy, our guidance for analysts, the eventual outputs of this project, and how it might have a lasting impact on the field.</p

ARTEM-IS for ERP: Agreed Reporting Template for EEG Methodology - International Standard for documenting studies on Event-Related Potentials

Given that the choices made during recording, preprocessing and analysis of event-related potentials (ERP) data can affect study outcomes, it is critical that they are transparently reported to allow for reproducibility and replicability. Yet, systematic reviews of reporting practices in the field have shown that journal articles do not meet this goal and that guidelines for writing them better have not resulted in a sufficient improvement to reporting transparency. ARTEM-IS aims to address this issue by building dynamic, interactive web applications that support documenting information required by existing publication guidelines in the form of a standardised metadata template. Completing an ARTEM-IS form results in a human-reader-friendly PDF and a machine-readable JSON summary of methodological information, which allows for a level of reporting precision higher than what is typically found in journal articles. These can be used as supplements to a publication, as a memory aid when writing a paper, or as records that allow easier metadata extraction in comparison to verbal descriptions in papers. Here, we present the ARTEM-IS for ERP, which supports describing a typical ERP study, including most of its core methodological aspects (study description, experimental design, hardware, data acquisition, pre-processing, measurement, visualisation, additional comments). We discuss the current contents of the form, web application functionalities, current limitations, and potential directions for future developments. In addition, the process of building the form contents and the web application through a collaborative grassroots initiative is described. Finally, we argue that a wider adoption of ARTEM-IS can bring benefits to different stakeholders: researchers themselves or their collaborators, especially on large-scale projects, reviewers, readers of a paper, and the scientific community at large

ARTEM-IS for ERP

Given that the choices made during recording, preprocessing and analysis of event-related potentials (ERP) data can affect study outcomes, it is critical that they are transparently reported to allow for reproducibility and replicability. Yet, systematic reviews of reporting practices in the field have shown that journal articles do not meet this goal and that guidelines for writing them better have not resulted in a sufficient improvement to reporting transparency. ARTEM-IS aims to address this issue by building dynamic, interactive web applications that support documenting information required by existing publication guidelines in the form of a standardised metadata template. Completing an ARTEM-IS form results in a human-reader-friendly PDF and a machine-readable JSON summary of methodological information, which allows for a level of reporting precision higher than what is typically found in journal articles. These can be used as supplements to a publication, as a memory aid when writing a paper, or as records that allow easier metadata extraction in comparison to verbal descriptions in papers. Here, we present the ARTEM-IS for ERP, which supports describing a typical ERP study, including most of its core methodological aspects (study description, experimental design, hardware, data acquisition, pre-processing, measurement, visualisation, additional comments). We discuss the current contents of the form, web application functionalities, current limitations, and potential directions for future developments. In addition, the process of building the form contents and the web application through a collaborative grassroots initiative is described. Finally, we argue that a wider adoption of ARTEM-IS can bring benefits to different stakeholders: researchers themselves or their collaborators, especially on large-scale projects, reviewers, readers of a paper, and the scientific community at large. Learn more in our preprint: https://psyarxiv.com/mq5sy/ Try the web-app: artemis.incf.or