Stawyskyj, Joey (Zoe), Dr.
- Since 2025 Post doctoral researcher with Julijana Gjorgjieva at TUM and affiliated researcher with the CIDBN
- 2021 – 2024 PhD in Theoretical and Computational Neuroscience (Dr. rer. nat), GGNB University of Göttingen
- 2019 – 2021 Tutor, supervisor and course coordinator of programs in Experimental Physics and Data Science, University of Sydney
- 2018 – 2019 Honours (first class) in Physics, University of Sydney
- 2015 – 2018 Bachelor of Advanced Science, majors in Physics and Chemistry, University of Sydney
Major Research Interests
THE OPTIMISATION OF THE DEVELOPMENT AND SPATIAL ORGANISATION OF SENSORY NEURAL NETWORKS
Understanding evolutionary invariance of orientation preference maps in primates, carnivores, scandentia and primates
Robust methods that aim to maximise comparability of results and to understand the origins and extent of noise in different data sets to enhance this comparability are essential when working with intrinsic signal imaging data, a common technique when investigating orientation preference maps. We developed such protocols that can then be applied to diverse species such as the Australian fat-tailed dunnart.
Optimisation of orientation preference maps to minimise turnover in neuronal preference during development
Neural turnover during development allows for a system to allow for a self-organising process to reach a stable processing state. Despite the benefit of allowing learning, turnover can pose challenges to systems processing stability and readout accuracy, especially where the system is an elementary processing step as is the case with orientation preference maps. We constructed an optimisation model based on minimising turnover during development and find that turnover is indeed minimal for biologically realistic patterns.
Optimisation of the spatial organisation of orienation preference maps for spatial predicitive information
Extending the Gaussian information bottleneck theory to two dimensions and continuous fields has allowed us to apply this theory to the spatial organisation of orientation preference maps. The field representing the spatial location and orientation preference of a neuron is optimised such that it keeps maximal information about distant locations and minimal information about the neurons receptive field. We are interested in understanding the parameters of the patterns resembling biological orientation preference maps.
For further information visit zoestawyskyj.com/.