Patricia Rubisch

Patricia Rubisch

PostDoctoral Researcher

Medical School Berlin

Biography

I am a PostDoctoral researcher in the group of Melanie Stefan at Medical School Berlin working on computational models of synaptic plasticity. My research interest is focused on the biological processes of learning. I hope to elucidate the role of temporal-spatial signalling of the various actors within the plasticity cascades in health and disease. My approach uses multi-scale models including biochemical reaction system and electrophysiology in order to translate the highly detailed biologically-plausible models and results into functional learning rules suitable for large network simulations. I studied functional development in spiking neural networks during my PhD at the University of Edinburgh under supervision of Matthias Hennig.

I believe that the transfer of knowledge and inter-disciplinary communication is central for the scientific process. Therefore, I try to take part in science outreach and teaching in online accessible courses e.g. Neuromatch. At Medical School Berlin, I organise the INBICA Journal Club to facilitate interdisciplinary communication between researchers within the Institute for Neuroscience and Biopsychology for Clinical Application. Science thrives with a good community. As the postdoc representative of the Bernstein Network, I try to take a more active role in creating an open and welcoming community with strong peer-support.

Interests
  • Synaptic Plasticity
  • Models of Learning in the health and disease
  • Synaptopathologies
  • Multi-scale modelling
  • Spiking Neural Networks
  • Biological credit assingment
Education
  • PhD in Computational Neuroscience, 2024

    University of Edinburgh

  • MScR in Computational Neuroscience, 2019

    Univeristy of Edinburgh

  • BSc in Cognitive Science, 2018

    Eberhard Karls Universität Tübingen

Experience

 
 
 
 
 
PostDoctoral Researcher
Medical School Berlin
December 2023 – Present Berlin, Germany
Modelling synaptic plasticity taking into account electrohpysiology, calcium signalling and kinase activity at the Stefan Lab. Dabbeling in Computational Biology side projects like protein synthesis models.
 
 
 
 
 
Teaching Assistant
July 2024 – July 2024 online
Teaching Assistant for the course NeuroAI.
 
 
 
 
 
Teaching Assistant
University of Edinburgh
September 2019 – October 2023 Edinburgh, UK
Providing teaching support for various courses. Computational Cognitive Neuroscience (Teaching Assistant), Neural Computation (Marker), Introduction to Cognitive Science (Tutor, Demonstrator, Marker)
 
 
 
 
 
Student Research Assistant
AG Neural Information Processing, Eberhard Karls Universität Tübingen
December 2015 – September 2018 Tübingen, Germany
Implementation and execution of psychophysics experiments

Teaching & Workshop Materials

Grundlagen der KI für Gesundheitsberufe
This app walks students without a computer science or math background through the basics of Artificial Intelligence and Machine Learning systems. It covers regression, clustering and classification as well as demonstrates bias in training data. It is part of the teaching material for the WPF at Medical School Berlin of the same name.
GRS Workshop - Modelling Inhibition in Spiking Neural Networks (with Elizabeth Herbert)
The notebooks present a step-by-step introduction to modelling with Spiking Neural Networks. The two accompanying talks for this workshop have been titled “Modelling the effect of inhibition on synchronicity and regularity in spiking network” and “De-correlating activity via inhibitory plasticity during memory recall”. It covers the following papers: Brunel, N. (2000). Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. Journal of Computational Neuroscience, 8, 183–208. and Vogels, T. P., Sprekeler, H., Zenke, F., Clopath, C., & Gerstner, W. (2011). Inhibitory plasticity balances excitation and inhibition in sensory pathways and memory networks. Science, 334(6062), 1569–1573.

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