Modeling the dynamics of disease states in depression

Major depressive disorder(MDD) is a disabling condition that adversely affects a person general health, work or school life, sleeping and eating habits, and person's family. Despite intense research efforts, the response rate of antidepressant treatments are relatively low and the etiology and progression of MDD remain poorly understood. To advance our understanding of MDD, we use computational modelling as described in our article.

For further information consult the projectpage.

The model to simulate the dynamics of disease states in depression can be downloaded as a zip File and can be used with Matlab.


Parametric Anatomical Modeling

With Parametric Anatomical Modeling (PAM), we propose a technique and a Python implementation to create artificial neural networks that meet connectivity patterns and connection lengths of large scale neural networks.

The basic idea of PAM is to trace neural, synaptic and intermediate layers from anatomical data and relate those layers to each other. With a set of mapping techniques, complex relationships between those layers can be defined to determine how axonal and dendritic projections traverse through space and where synapses are formed.

For further information consult the project page
or the separate web page.

PAM is available as an Addon for Blender and can be downloaded from a repository on Bitbucket. An importer for the neural network simulator NEST is available in a separate repository.


Free high-quality figures

Our group aims to provide neuroscientific community with a collection of high-quality SVG-figures for free use in publications, presentations, websites etc. via GitHub.

All SVG-files in the repository underlie the Create Commons Attribution 4.0 International License.

A ZIP-file containing all of the currently available figures as well as additional information concerning their creation can be downloaded here.