Hi! I’m a PhD student at the Charité-Universitätsmedizin Berlin and at the Bernstein Center for Computational Neuroscience. I’m a member of the Quality in AI group, lead by Prof. Stefan Haufe. Prior to my PhD, I studied psychology at the University of Mannheim and at Bilgi Üniversitesi Istanbul, and neuroscience at the International Max Planck Research School in Tübingen.
My work ranges in the field between medicine and computer science. Specifically, I analyse medical data using data science tools. My main interest is the analysis of functional connectivity from electroencephalographic (EEG) or magnetoencephalographic (MEG) data. Functional connectivity reflects linear or non-linear statistical dependencies between different neural time series coming from different brain areas. Some works suggest that functional connectivity may be related to communication between brain areas.
The main goal of my PhD project is to validate and compare methods and analysis pipelines for studying functional connectivity. To this end, we build simulations to test the reliability of different pipelines. We are also implementing the most promising pipelines into an open source toolbox to make them easily accessible to others. The other part of my PhD focuses on functional connectivity analysis in movement disorders, particularly in Parkinson’s disease and dystonia. These disorders are network disorders in which communication between different parts of the brain is disrupted. We work closely together with the medical groups of Prof. Andrea Kühn and Prof. Ioannis Isaias. Through these collaborations, we are also part of the Retune CRC project.
I work to improve life in science by engaging in the Equal Opportunity Committee of the Retune Project. Outside of research, I play the cello and sing in a choir. I also enjoy gardening and the outdoors. Since I think that it is important to support our democracy, I recently joined a German democratic party and go to demonstrations regularly. I try to keep my carbon footprint small, e.g. by flying less.
Pellegrini, Franziska, Arnaud Delorme, Vadim Nikulin, and Stefan Haufe. Identifying Best Practices for Detecting Inter-Regional Functional Connectivity from EEG. BioRxiv, 2022. >code >toolbox implementation
Haufe, Stefan, Ioannis U. Isaias, Franziska Pellegrini, and Chiara Palmisano. Gait Event Prediction Using Surface Electromyography in Parkinsonian Patients. Bioengineering 10, no. 2 (2023): 212.
Haumesser, Jens K, Maximilian H Beck, Franziska Pellegrini, Johanna Kühn, Wolf-Julian Neumann, Jennifer Altschüler, Daniel Harnack, et al. Subthalamic Beta Oscillations Correlate with Dopaminergic Degeneration in Experimental Parkinsonism. Experimental Neurology 335 (2021): 113513.
Pellegrini, Franziska, David J Hawellek, Anna-Antonia Pape, Joerg F Hipp, and Markus Siegel. Motion Coherence and Luminance Contrast Interact in Driving Visual Gamma-Band Activity. Cerebral Cortex 31, no. 3 (2021): 1622–31.
Pellegrini, Franziska. Evolution of Beta Bursts in the 6-OHDA Rat Model. Master’s Thesis (2018).
Pellegrini, Franziska. Sleep Detection in Completely Locked-in ALS Patients. Lab Report (2018).
Pellegrini, Franziska. A Global Memory Model Perspective on the Revelation Effect. Bachelor’s Thesis (2015).
franziska.pellegrini(at)charite.de