Computational methods and machine learning are currently THE hot-topics and they are also applied in neuroscience research, showing us where the field is heading in the future. If you have ever wondered how these methods work, what their advantages - but also limitations - are and how they are implemented in research on women's mental health: We got you!

In this episode Franziska is hosting Tobias Kaufmann, professor of neurotechnology and computational psychiatry at the University of Tübingen, who is also part of the IRTG2804. Tobias explains the basics of computational methods and gives us concrete examples of his own work, providing a first glimpse into the computational world. Also, we hear about his new ERC project: "HealthyMom: Modeling and maintaining maternal mental health".

Timestamps:

00:25 Introduction

01:18 Computational psychiatry: Advantages & limitations

10:15 Tobias' computational methods & examples: Prediction & classification models

21:14 Computational methods in women's (mental) health: Focus on adolescence

30:11 HealthyMom Project: Brain plasticity during pregnancy loss

40:26 Recruitment information for Healthy Mom Study

41:30 Summary

43:40 Next steps in computational psychiatry and women's mental health

Website to Kaufmann Lab: https://www.kaufmannlab.org/

About the HealthyMom Project: https://www.kaufmannlab.org/post/20230202-erc-consolidator-grant/

References:

• Population-based neuroimaging reveals traces of childbirth in the maternal brain (de Lange, Kaufmann et al., 2019). https://doi.org/10.1073/pnas.1910666116
• Menarche, pubertal timing and the brain: female-specific patterns of brain maturation beyond age-related development (Gottschwesky, Kraft, & Kaufmann, 2024). https://bsd.biomedcentral.com/articles/10.1186/s13293-024-00604-4
• Domain adapted brain network fusion captures variance related to pubertal brain development and mental health (Kraft, Alnaes, & Kaufmann, 2023). https://www.nature.com/articles/s41467-023-41839-w
• Modeling brain sex in the limbic system as phenotype for female-prevalent mental disorders (Matte Bon, Kraft, Comasco, Derntl, & Kaufmann, 2024). https://bsd.biomedcentral.com/articles/10.1186/s13293-024-00615-1

Outline & questions: Franziska Weinmar & Gloria Matte Bon

Sound recording: Franziska Weinmar with the equipment of the IRTG2804

Editing: Franziska Weinmar

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