Statistical Imaging Neuroscience

Over the last two decades neuroimaging has made significant contributions to our understanding of human brain function. The indirect nature of the data requires sophisticated modeling and analysis approaches in order to infer interpretable quantities of interest. The 'Statistical Imaging Neuroscience' group at the DCCN researches analytical approaches for the analysis of functional neuroimaging data. Main research efforts involve:

  • Computational methods for multimodal brain imaging using multivariate generative models
  • Exploratory Data Analysis, specifically Independent Component Analysis, multi-way generalisations to bilinear linear models (Parallel Factor Analysis and Tensor-ICA)
  • Bayesian time-series modeling, statistics and data fusion
  • Statistics for Imaging Genetics
  • Methods for pharmacological FMRI (phFMRI)
  • Neural networks, data mining and statistical pattern recognition for neuroimaging data
  • Biomarker development for clinical neuroscience
  • Connectomics and resting-state functional connectivity

We participate in the development of the FMRIB Software Library (FSL), to provide powerful multimodal research tools for imaging neuroscientists, and advanced practical tools for clinicians using multimodal brain imaging in medicine.


Research Group
Statistics Imaging Neuroscience

Principal Investigator
Prof. Christian Beckmann

Group members

Senior Researcher
Emma Sprooten

Postdoctoral Researchers
Dr. Myrthe Faber
Dr. Christienne Gonzales Damatac
Dr. Corina Greven
Dr. Koen Haak
Dr. Alberto Llera Arenas
Dr. Andre Marquand
Dr. Maarten Mennes
Dr. Marianne Oldehinkel
Dr. Aylin Mehren

PhD Students
Guilherme Blazquez Freches
Winke Francx
Tristan Looden
Lara Mentink
Peter Mulders
Tom Mulders
Lennart Oblong
Haowen Su
Zain Souweidane
Xuanwei Li

Research Assistant
Marije Mars
Sanne Kluin
Lotte Beckers
Elin Davelaar
Cagatay Demirel

MSc and BSc Students
Jitse Amelink
Lisa Berg
Stijn de Boer


Postbus 9101