Max Hinne

Currently, I am an assistant professor at the Cognitive Artificial Intelligence department, at the Radboud University of Nijmegen.

My research is aimed at the development of (Bayesian) statistical methods for inference of network structure, with applications in neuroscience as well as cognitive psychology. In general, I'm interested in network modeling, graphical models, Bayesian nonparametrics, causal inference and connectomics & brain dynamics.

My contact information is listed below.

“All stable processes we shall predict. All unstable processes we shall control.”

John von Neumann


PhD thesis

On June 9th 2017, I defended my doctoral thesis entitled Bayesian Connectomics: a probabilistic perspective on brain networks with a cum laude distinction.




The Bayesian Connectomics Toolbox contains Matlab/MEX scripts that implement MCMC approximations for:

Basic usage of each of the scripts is demonstrated in demo.m. Feel free to email me with any questions or comments.

Latent space modeling

Matlab code and Stan models are available for the latent space model that was used for link prediction. Running the sample requires that you have Stan and the MatlabStan interface installed.


Code for the causal inference / effective connectivity estimation using GP CaKe is available here. There is a tutorial for GP CaKe in the form of a series of blog post, which you can read on the MindCodec website.

Data sets

Two data sets are currently available:

  1. Probabilistic streamline counts based on diffusion-weighted MRI, for 162 regions (FreeSurfer parcellation: 74 cortical regions per hemisphere, 7 subcortical regions per hemisphere). These data were used in the paper regarding the clustered connectome.
  2. Functional MRI BOLD response timeseries, as well as probabilistic streamline counts based on diffusion-weighted MRI, for 14 subcortical regions (7 per hemisphere). These data were used in the paper on conditional independence and data fusion.
Credit for collecting these data goes to Erik van Oort.

Contact information


Email &
Google Scholar
Max Hinne



Visiting Address PM

Room G.0.33
Nieuwe Achtergracht 129B
1018 WS Amsterdam




Visiting Address AI

Room B.00.67B
Montessorilaan 3
6525 HR Nijmegen