We are pleased to announce that five workshops on a wide range of topics will be offered at the INM Retreat 2025. The tutorials offered have traditionally presented an exceptional opportunity to embrace the diversity of our research and expand one’s understanding of scientific concepts, methodological approaches, and future challenges that extend beyond our daily work routine. Scientists from different institutes will be sharing their knowledge and expertise on selected topics. In addition, there will be a workshop organized by the Career Center & Postdoc Office.
Below you will find brief descriptions of the planned workshops.
Beyond academia? Navigating your future career
Viola Middendorf
As an early career researcher, sooner or later the question arises, what comes next. Whether you're considering staying in academia or exploring other career paths, for example in industry or science management,this interactive workshop offers space to reflect on your goals, learn about different career options, and gain clarity on what suits you best. The workshop will be a mixture of input, reflection and peer exchange, so that you can take with you new perspectives and concrete ideas for your next steps.
Imaging
Beyond the Scan: Metabolic and Fiber Imaging Explained
James Eills and Markus Axer
The imaging tutorial will offer in-depth insights into cutting-edge neuroimaging techniques, with a focus on Hyperpolarized (HP) Carbon-13 Magnetic Resonance Imaging and 3D-Polarized Light Imaging (3D-PLI). Designed for participants interested in both the functional and structural aspects of brain imaging, the tutorial will highlight how these advanced modalities are expanding the frontiers of neuroscience research and clinical diagnostics.
The session on hyperpolarized carbon-13 MR imaging will introduce the principles behind this emerging metabolic imaging technique and its unique ability to capture real-time biochemical processes in vivo. In the second part of the tutorial, participants will explore 3D-PLI, a powerful histological imaging method for visualizing the complex architecture of white matter fiber pathways at high resolution.
Together, these sessions aim to provide participants not only with a conceptual understanding of each technique but also with an appreciation of their current and potential applications in brain research and translational medicine..
Linked data instead of excel/sciebo spreadsheet
Michał Szczepanik
This tutorial showcases an open source metadata tool stack and its application for science coordination such as tracking projects or publications. It is relevant for anyone who is responsible for reporting research information, motivated to improve administrative workflows in science, or just interested in the topic of linked data or metadata.
The tutorial will start with a seemingly trivial task: filling out a web form with often requested information (e.g. about a person, project, publication). We will then explore how the form is not handcrafted, but instead generated from a data model, which describes objects, their properties and relations. We will see how this approach helps eliminate duplication of work (e.g. a person already "in the system" can be selected as a publication author and a project member) and helps improve interoperability with other systems. We will also discuss data access scopes (not all users can see all records) and queries (e.g. find projects which run out within next months).
For the curious: the software stack uses LinkML (https://linkml.io/) as a language for expressing data models; our base set of schemas is called DataLad concepts (see e.g. https://concepts.datalad.org/s/demo-research-assets/unreleased/) and our form generation tool is called shacl-vue (https://hub.psychoinformatics.de/datalink/shacl-vue).
Machine Learning for neuroscience: Basics, pitfalls and interpretation
Kaustubh Patil
This tutorial introduces fundamentals of machine learning, especially supervised approaches. We will cover model training, and evaluation and highlight common pitfalls such as overfitting, confound effects, and data leakage due to improper cross-validation that can lead to misleading results. Practical examples and guidelines will be provided to help researchers apply ML rigorously and interpret results reliably.
The siibra toolsuit for accessing the EBRAINS human brain atlas
Timo Dickscheid
siibra is a software tool suite implementing an openly accessible brain atlas framework which connects multimodal datasets from different resources to anatomical structures in reference spaces at different spatial scales. The tool suite is designed to address both interactive exploration through an interactive 3D web viewer (siibra-explorer) as well as integration into data analysis and simulation workflows with a comprehensive Python library (siibra-python). In this session, we first introduce the multidimensional concept of the atlas framework and explore some key features such as the BigBrain interactively. We then turn to concrete programming tutorials in Python. These include fetching brain region maps, accessing the BigBrain dataset, and extracting multimodal regional features such as cortical thicknesses, cell and neurotransmitter densities, gene expressions and connectivity data. We will finish with some concrete data analysis examples.
