Current Position
Currently, I work as a postdoctoral researcher at the Dorris Neuroscience Center of The Scripps Research Institute, where I am supervised by Ann Kennedy.
Previously, I worked with and learned from Thomas Knoesche (PhD supervisor, Max Planck Institute for Human Cognitive and Brain Sciences) and Peter Koenig (Master thesis supervisor, Osnabrueck University).
Curriculum Vitae
Work experience
Since August 2024
The Scripps Research Institute, San Diego
PostDoc
January 2022 - July 2024
Northwestern University, Chicago
PostDoc
October 2021 - December 2021
Max Planck Institute for Human Cognitive and Brain Science, Leipzig
PostDoc
Education
October 2017 - September 2021
University of Leipzig
Dr. rer. nat. at Physics faculty
October 2014 - September 2017
University of Osnabrück
M.Sc. Cognitive Science
October 2011 - September 2014
University of Leipzig
B.Sc. Psychology
Fellowships
October 2018 - September 2021
Studienstiftung des Deutschen Volkes PhD Fellowship
October 2016 - September 2017
SMART START Computational Neuroscience Training Fellowship
Selected Publications
Gast, R., Solla, S., Kennedy, A. (2024) Neural heterogeneity controls computations in spiking neural networks. PNAS 121 (3), e2311885121.
Gast, R., Knoesche, T.R., Kennedy A. (2023) PyRates—A code-generation tool for modeling dynamical systems in biology and beyond. PLOS Computational Biology 19 (12), e1011761.
Gast, R., Solla, S., Kennedy, A. (2023) Macroscopic dynamics of neural networks with heterogeneous spiking thresholds. Physical Review E 107 (2), 024306.
Gast, R., Knoesche, T.R., Schmidt, H. (2021) Mean-field approximations of networks of spiking neurons with short-term synaptic plasticity. Physical Review E 104 (4), 044310.
Gast, R., Gong, R., Schmidt, H., Meijer, H.G.E., Knoesche, T. (2021) On the Role of Arkypallidal and Prototypical Neurons for Phase Transitions in the External Pallidum. Journal of Neuroscience 41 (31), 6673-6683.
Gast. R., Schmidt, H., Knoesche, T.R. (2020) A Mean-Field Description of Bursting Dynamics in Spiking Neural Networks with Short-Term Adaptation. Neural Computation 32 (9), 1615-1634.