Cayden Murray
PhD Student
​(2021-present)

Contact: [email protected]​

Research. ​​​I use computational neuroscience techniques alongside deep learning to understand how neuronal activity and behaviour evolve within the context of stress. Specifically, I work with a mixture of calcium imaging, fiber photometry, fMRI, and behavioural data to model how stress influences neuronal dynamics and how these dynamics correlate with changes in behaviour. The methods I use include matrix factorization, Markov models, and sparse identification of non-linear dynamics.

​Hobbies. ​​​I take part in multiple sports (e.g., hockey, rock climbing, spike ball, soccer). I play the violin and enjoy reading manga and horror novels.

Favourite paper. Brunton et al. (2016). Discovering governing equations from data by sparse identification of nonlinear dynamical systems. PNAS, 113(15): 3932-3937. This paper details a machine learning method capable of generating equations that describe how a dynamical system evolves with time. I love this paper because it uses traditionally black-box machine learning algorithms to describe dynamical systems in an interpretable way.

Publications

SELECT PUBLICATIONS

Murray C, Oladosu O, Joshi M, Kolind S, Oh J, Zhang Y. (2023). Neural network algorithms predict new diffusion MRI data for multi-compartmental analysis of brain microstructure in a clinical setting. Magnetic Resonance Imaging, 102: 9-19.
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Awards

• Alberta Graduate Excellence in Scholarship (2023), University of Calgary
• University of Calgary Graduate Studies Scholarship (2023)

education

I received my BHSc in Biomedical Sciences with distinction at the University of Calgary (2017-2021). I started my MSc in Neuroscience at the University of Calgary in the Fall of 2021. I transferred to the PhD program in the winter of 2023.