Donders Institute for Brain, Cognition and Behaviour
Zoek in de site...
Theme 4: Brain Networks and Neuronal Communication

Predictive Clinical Neuroscience

The Predictive Clinical Neuroscience group aims to develop statistical and machine learning techniques to make predictions relevant to brain disorders and to understand their underlying neurobiology on the basis of neuroimaging data. We focus both on supervised techniques for predicting clinical variables as well as unsupervised approaches for stratifying clinical groups on the basis of the underlying biology. Specific methodological techniques of interest include:

  • Bayesian non-parameteric methods for pattern classification and regression (e.g. Gaussian processes)
  • Spatial statistical methods (e.g. continuous stochastic processes, point processes)
  • Kernel and regularization methods for high-dimensional data
  • Multivariate statistical methods for finding associations between datasets (e.g. canonical correlation analysis)
  • Markov chain Monte Carlo methods for inference in probabilistic models
  • Multi-output, multi-task and structured output learning methods
  • Neural network and deep learning models

While the methods we develop have applications in many clinical settings, we have a particularly strong focus on psychiatric and neurological disorders.

Name: Andre Marquand
Telephone: 024-3668492
Visiting address:

Donders Centre for Cognitive Neuroimaging
Kapittelweg 29
6525EN Nijmegen
The Netherlands

Postal address: Donders Centre for Cognitive Neuroimaging
Kapittelweg 29
6525EN Nijmegen
The Netherlands

Back to:
Theme 4:
Natural Computing & Neurotechnology

Research Group
Predictive Clinical Neuroscience

Principal Investigator
Dr. A. Marquand

Group members

Nathalie Holz

Richard Dinga
Ismael Huertas
Imogen Leaning
Thomas Wolfers
Mariam Zabihi
Loran Knol
Letizia Clementi

Research assistents
Linda Schlüter

Master students
Christina Isakoglu
Jannik Piper
Meike Jodies

Update MAR 17 EL