Understanding human brain organization
We develop and apply novel methods for mapping the regional organization of the human brain into cortical areas as well as the topography of large-scale, distributed networks recruited by cognitive, socio-affective or sensorimotor tasks.
Modelling inter-individual differences
We characterize the variability of brain structure, function and connectivity in large cohorts and their relation to age, gender and behavioral measurements. Using machine-learning approaches we train predictive models for inference on phenotypical characteristics of new, individual subjects from brain imaging data.
Translating technology into clinical applications
We implement and evaluate novel machine-learning approaches for improved diagnosis, stratification and outcome prediction at the level of individual patients based on neuroimaging and wearable technology.
Enabling research through open science
An important focus of our work is to provide the developed tools and results to the scientific public through free software-tools and open data sets to encourage broad use.
Focus
Applied Machine Learning
Group leader:
Dr. Kaustubh Patil
The group focuses on designing and evaluating machine-learning algorithms and pipelines. The application areas include mental health and psychiatric disorders as well as basic understanding of brain structure, function and development.
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Behavioural Neuroscience
Group leader:
Dr. Robert Langner
The group aims to further our understanding of how the brain contributes to human behaviour. The group investigates cognitive and affective processes and their associations with brain activity, connectivity and morphology.
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Biomarker Development
Group leader:
Dr. Jürgen Dukart
The aim of the group is to identify, validate and integrate novel neuroimaging and digital biomarkers that can be applied for early detection and treatment evaluation of changes in brain organization in advanced age as well as in neurological and psychiatric diseases.
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Brain Variability
Group leader:
PD Dr. Susanne Weis
The group investigates the relationship between variability of structural and functional brain organization and individual differences in experience, information processing and behavior.
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Psychoinformatics
Group leader:
Prof. Dr. Michael Hanke
The group "Psychoinformatics" focuses on the interface of neuroscience, psychology and computer science and the combination of classical experimental methodology with machine learning methods.
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