332 citations · 355 across the 5 of their papers we have counts for
6 papers
Scalable Multi-Task Gaussian Process Tensor Regression for Normative Modeling of Structured Variation in Neuroimaging Data
Seyed Mostafa Kia, Christian F. Beckmann, Andre F. Marquand
Most brain disorders are very heterogeneous in terms of their underlying biology and developing analysis methods to model such heterogeneity is a major challenge. A promising appro…
Human brain parcellation using time courses of instantaneous connectivity
Erik S. B. van Oort, Maarten Mennes, Tobias Navarro Schröder +5
Functional neuroimaging studies have lead to understanding the brain as a collection of spatially segregated functional networks. It is thought that each of these networks is in tu…
Variational Mixture Models with Gamma or inverse-Gamma components
A. Llera, D. Vidaurre, R. H. R. Pruim +1
Mixture models with Gamma and or inverse-Gamma distributed mixture components are useful for medical image tissue segmentation or as post-hoc models for regression coefficients obt…
Increasing robustness of pairwise methods for effective connectivity in Magnetic Resonance Imaging by using fractional moment series of BOLD signal distributions
Natalia Bielczyk, Alberto Llera, Jan Buitelaar +2
Estimating causal interactions in the brain from functional magnetic resonance imaging (fMRI) data remains a challenging task. Multiple studies have demonstrated that all current a…
Connectopic mapping with resting-state fMRI
Koen V. Haak, Andre F. Marquand, Christian F. Beckmann
Brain regions are often topographically connected: nearby locations within one brain area connect with nearby locations in another area. Mapping these connection topographies, or '…
Models of Disease Spectra
Iead Rezek, Christian Beckmann
Case vs control comparisons have been the classical approach to the study of neurological diseases. However, most patients will not fall cleanly into either group. Instead, clinici…