Topic: tractography

Tractography datasets, calculated from dMRI, represent the main WM structural connections in the brain. Thanks to advances in image acquisition and processing, the complexity and size of these datasets have constantly increased, also containing a large amount of artifacts. We present some examples of algorithms, most of them based on classical machine learning approaches, to analyze these data and identify common connectivity patterns among subjects.

Transcranial direct current stimulation (tDCS) has proven to be effective in reducing the seizure frequency in patients with epilepsy. This therapy greatly benefits from designing personalized electrode montages (electrode positions and currents) that target the appropriate areas of the brain. In the state-of-the-art pipelines, a specialized physician selects these areas and a biophysical model of the patient’s head is used to find an optimal electrode montage that inhibits them. In the Galvani project, we aim to go a step forward and develop a pipeline that uses personalized Neurotwins for mo