The Virtual Brain (TVB - www.thevirtualbrain.org) is a powerful and increasingly used neuroinformatic platforms to build personalized models of brain activity. Neural population models are implemented on the structural brain connectome, and model parameters are tuned to maximize resemblance with the spectral characteristics and connectivity patterns of empirical data. When modelling fMRI data, the simulated neural activity is convolved with a standard model of the hemodynamic response function (HRF), the same across the brain and across subjects.
To improve this last step we propose to use a toolbox developed in our lab (including past GSoC work), the rsHRF (https://www.nitrc.org/projects/rshrf). We would retrieve the resting state HRF for each voxel and each subject. We would then average it across the regions used in the TVB and use them as transfer functions in the model. This modification would be a valid and effective addition to the TVB package.
Mentor: Daniele Marinazzo
Knowledge: python, git. Preferred: bash scripting, high performance computing, knowledge of dynamical systems and/or neuroscience.