Building: Technohal, room TL 3381
Phone: +31 53 489 7985
Maria Carla Piastra studied Applied Mathematics at the University of Genova, Italy. In 2019, she obtained both a PhD in Applied Mathematics from the University of Muenster, Germany, in the group of Carsten H. Wolters, and one in Bioengineering from the University of Genova, Italy, in the group of Marco Fato.
Between 2018 and 2021, she worked as PostDoc in Nijmegen, at the Donders Institute. Specifically, she was involved first in the NeuroCIMT project, in the group of Thom Oostendorp (Radboud University Medical Center); and in the FLAG-ERA NeuronsReunited project, in the group of Paul Tiesinga (Radboud University).
In 2021, Maria Carla Piastra joined the University of Twente as Assistant Professor in the Clinical Neurophysiology group.
She develops mathematical models to simulate normal and abnormal neuronal activity at different levels. From brain activity measured with scalp and intracranial EEG systems to neuronal network activity measured in vitro with microelectrode arrays (MEA) devices. Within this framework, she is involved in several (open-source) software development initiatives.
Her main goal is to facilitate translational work between clinic and research, with a particular focus on epilepsy and stroke.
Piastra M.C. (2019). New finite element methods for solving the MEG and the combined MEG/EEG forward problem. Permalink: https://nbn-resolving.de/urn:nbn:de:hbz:6-53199662090
Piastra, M. C., Nüßing, A., Vorwerk, J., Bornfleth, H., Oostenveld, R., Engwer, C., & Wolters, C. H. (2018). The discontinuous Galerkin finite element method for solving the MEG and the combined MEG/EEG forward problem. Frontiers in Neuroscience, 12, 30. DOI: https://doi.org/10.3389/fnins.2018.00030
Piastra, M. C., Schrader, S., Nüßing, A., Antonakakis, M., Medani, T., Wollbrink, A., Engwer C. & Wolters, C. H. (2020). The WWU DUNEuro reference data set for combined EEG/MEG source analysis. Zenodo. DOI: https://doi.org/10.5281/zenodo.3888381
Piastra, M. C., Oostenveld, R., Schoffelen, J. M., & Piai, V. (2022). Estimating the influence of stroke lesions on MEG source reconstruction. NeuroImage, 119422. DOI: https://doi.org/10.1016/j.neuroimage.2022.119422