Workshops

Neuronal activity in the human brain is complex, yet isolating and interpreting true brain signals from EEG and MEG remains challenging. This workshop addresses critical sources of bias—volume conduction, signal-to-noise ratio, and long-range temporal dependencies—that affect brain activity interpretation. Moreover, essential inverse modeling principles, including the choice of priors, constraints, filter settings, and channel numbers, will be discussed, with practical guidance for balancing anatomical realism and computational efficiency in source localization. Attending students will also have the opportunity to discuss how these approaches can benefit their own research projects.

In this workshop, participants will learn how to plan and conduct coordinate-based meta-analyses. In the first part, participants receive a brief overview of the theoretical background of neuroimaging meta-analyses (focusing on coordinate-based meta-analyses), practical steps involved in planning and conducting a coordinate-based meta-analysis (literature search and screening, data extraction and preparation, model estimation, statistical inference, robustness and sensitivity analyses), as well as best practices for reporting methodology and results. In a hands-on practice session, participants will work through the steps of a coordinate-based meta-analysis using an example data set. In the second part, we will introduce the method of meta-analytic connectivity modeling, describe its applications, and discuss practical steps for conducting meta-analytic connectivity modeling.

Historically, basic and preclinical biomedical research has relied predominantly on male participants, animals and cells, a bias that limits our understanding of fundamental sex influences on biological processes and health outcomes. To address this gap, an increasing number of (inter)national funding agencies now requires that sex be considered as a biological variable (SABV) in all stages of research; from formulating questions and designing studies to analyzing and reporting results. This workshop will provide a practical framework for integrating SABV into study design, data collection, statistical analysis, and publication practices. Participants will learn how to plan experiments that include both sexes, disaggregate and interpret data by sex, and apply these principles to enhance the rigor, reproducibility, and translational relevance of their work. Through hands-on examples and discussion, the workshop aims to equip researchers with the tools to make sex-based considerations an integral and insightful part of their scientific approach.

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This workshop introduces participants to computational modeling of transcranial magnetic stimulation (TMS) using SimNIBS and pyNIBS. Accurate estimation of TMS-induced electric fields (E-fields) is essential for understanding inter- and intra-individual variability and optimizing stimulation protocols. Participants will learn how to generate high-quality, subject-specific head meshes from structural MRI data, verify tissue segmentation, and correct common meshing errors. Building on these models, the session covers setting up TMS coil configurations, defining stimulation parameters, and running E-field simulations. We will demonstrate how to extract and compare E-field distributions across stimulation conditions—such as different coil orientations or intensities—to evaluate focality and depth of cortical stimulation. An applied section focuses on integrating neuronavigation data (e.g., from Localite TMS Navigator), allowing participants to import recorded coil placement files, align them to head meshes, and reproduce realistic stimulation setups in SimNIBS. The workshop concludes with a discussion of E-field–based dosing strategies, emphasizing individualized calibration of stimulation intensity to achieve consistent cortical exposure across participants. By the end, attendees will understand how to construct, simulate, and analyze personalized TMS models, linking experimental neuronavigation data with computational E-field analysis for more precise and reproducible neurostimulation research.

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