Workshops

Workshop number	Title and abstract of workshop	Instructor(s)
1	Dynamic similarity analysis of brain data and artificial neural networks Information processing in the brain (consequently, behavior) is realized through complex dynamics of the brain, which we can understand through high-dimensional, and noisy neural recordings. For example, how much do the brain’s dynamics differ during a decision-making task as compared to a working memory task, and how do they unfold in time? How can we understand the computations realized through their dynamics? To answer these questions, we need to compare the activity of the brain across these tasks. Many widely used comparison tools (e.g., representational similarity analysis, correlations, or most multivariate statistical tools) in neuroscience and machine learning neglect the dynamic nature of neural computations, primarily comparing snapshots or time-averaged summaries rather than the rules of temporal evolution that shape the information processing. Incorporating temporal dynamics is essential because mechanistic interpretations in model-to-brain and brain-to-brain comparisons depend on the unfolding of activity over time, not merely on static representational structure. This workshop introduces a family of methods for dynamical similarity analysis as a principled alternative: rather than comparing trajectories pointwise or geometrically, these methods compare the dynamical evolution over time. We will also cover recent practical advances that make these ideas usable at scale, like fast Dynamical Similarity Analysis (fastDSA). The workshop is structured in two parts: first, an intuitive, concept-forward introduction to the principles behind dynamical similarity analysis (data preparation, Koopman/linearization-based on dynamic mode decomposition, rank optimization, alignment analysis); second, a hands-on tutorial in which participants apply fastDSA to real and simulated neural time series and to recurrent network models, and learn practical guidance on embedding choices, rank selection, and interpretation of dynamical similarity results.	Armand Behrad & Jun. Prof. Dr Shervin Safavi
2	Extracting brain activity from EEG and MEG – How to get it right Neuronal activity in the human brain is complex yet isolating and interpreting true signals from eeg meg remains challenging. this workshop addresses critical sources of bias conduction signal-to-noise ratio long-range temporal dependencies affect interpretation. moreover essential inverse modeling principles including choice priors constraints filter settings channel numbers will be discussed with practical guidance for balancing anatomical realism computational efficiency source localization. attending students also have opportunity to discuss how these approaches can benefit their own research projects.	Prof. Dr habil. Thomas R. Knoesche , Dr Burkhard Maess , and Dr Vadim Nikulin
3	Coordinate-based meta-analyses and meta-analytic connectivity modeling 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.	Dr Annika Konrad & Dr Lara Zoe Maliske
4	How to implement sex as a biological variable (SABV) in your research 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.	Prof. Dr Julia Sacher , Dr Jellina Prinsen , Livia Ruehr , and Kim Carina Hoffmann
5	Explainable Ai and Neuro Ai tba	Dr Nico Scherf
6	Evolution and development of social cognition and language in the brain The workshop explores the intersection of social communication, (brain) development, and evolution through two key topics. First, we examine the trajectory of social communicative development in human infants and non-human primates. Language and social skills develop along parallel tracks during early childhood, with milestones often co-occurring and reinforcing one another. Preverbal infants navigate social interactions using communicative gestures. Specifically, pointing gestures used to establish joint attention serve as a critical precursor to language acquisition. From an evolutionary perspective, communicative gestures are linked to leftward structural asymmetry in the primate temporal cortex. In the practical session, participants will learn to code infant gestures using video case studies. The second part shifts focus to the cerebellum's involvement in social communication. Traditionally viewed as a motor center, the cerebellum is now increasingly recognized for its crucial role in social cognition. This function is vital during development, as the cerebellum is thought to scaffold the early organization of cortical social functions, such as joint attention. We will discuss how the developing cerebellum supports early social cognition and examine its evolutionary significance in primates. The practical component will offer guidance on methodologies for studying cerebellar contributions to these social processes.	Cheslie Klein , Katerina Manoli , and Dr Yannick Becker
7	Hands-on coding workshop: How to model human memory How can neurons store and retrieve memories reliably, despite noise and biological constraints? This hands-on coding workshop introduces mechanistic, computational models of memory anchored in the idea that stable neural activity patterns, attractors, can represent persistent internal states. The core of the workshop is practical model-building in two complementary attractor regimes. First, we implement a head-direction circuit as a continuous attractor, illustrating how recurrent connectivity can sustain a bump of activity that remembers the direction. We then switch to a discrete attractor framework by coding a small Hopfield network, examining how associative memories emerge from neural assemblies that interact over time.	Fei Wang , Daniel C. Schad
8	Computational modeling of transcranial magnetic stimulation (TMS) using SimNIBS and pyNIBS. 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.	Dr Ole Nummsen
9	Comparative neuroanatomy tba	Dr Evgeniya Kirlina and Dr Alfred Anwander
10	From protons to segmentation of neuroanatomical structures- Hands on 7T. 7-Tesla MRI enables the mapping of structure and function in vivo at an unprecedented spatial resolution. In addition, the quantification of physical processes, like T1 and T2 relaxation, further enhances our understanding of the structure-function relationship in the human brain. In our workshop, we will introduce the basic concepts of quantitative structural and functional MRI. After shortly explaining the theoretical background of MR relaxometry and BOLD imaging, we will conduct an in vivo scanning session at our 7 Tesla TERRA.X system. We will measure T1 and T2 relaxation effects in the brain of a human volunteer and map the function of specific cortical areas. During the hands-on session the attendees may interact with the MR operator and change the MR protocol in order to gain further insight into the huge potential of ultra-high field MRI for investigating the human brain.	Dr Robert Trampel and Prof. Dr Nik Weiskopf