The PIMS Postdoctoral Fellow Seminar: Jordan Culp

  • Date: 05/04/2022
  • Time: 09:30
Jordan Culp, UCalgary



Mesoscale Imaging Reveals the Markovian Dynamics of the Brain (video)


With mesoscale imaging, we can optogenetically record the calcium signals from the entire cortical surface of the mouse brain. However, a mathematical analysis to assess the stability or changes to the brains dynamics remains elusive due to the size and complexity of the underlying data. Here, we apply a novel Continuous-Time Markov Chain approach to assess changes to the dynamics of the mouse brain under the application of different drugs, visual stimulation, and seizure induction. In all cases we can create a kind of dynamical bar-code of the brain dynamics of the mouse by computing Markov transition probability matrices and occupancy distributions. This dynamical bar-code is unique and reproducible for each mouse, yet changes in consistent ways as a result of our experimental manipulations. Thus, we argue that a Markovian description of the mesoscale brain is sufficient for detecting dynamical changes. In this talk, I will describe the experimental background and significance of our results, along with the derivation and detailed presentation of our mathematical model. This is joint work with the McGirr, Teskey, and Nicola labs at the University of Calgary.


Speaker Biography: Jordan Culp completed his PhD in Mathematics, with a graduate minor in Statistics, from Washington State University in Spring 2021, under the supervision of Dr. Xueying Wang. His area of research focused on the development and analysis of an ordinary differential equations model to predict the types of cluster solutions that should be expected in a network of weakly coupled oscillators on a lattice network topology with periodic boundary conditions and a von Neumann neighborhood connectivity structure. In his current post-doctoral position at the University of Calgary, he works on a collaborative project under the co-supervision of Dr. Wilten Nicola and Dr. Alex McGirr. In this project a Markovian model is used to describe the underlining temporal dynamics of the mesoscale neural imaging recordings from the McGirr lab. This project brings together analytical and numerical techniques from linear algebra, data science, and statistics.


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This event is part of the Emergent Research: The PIMS Postdoctoral Fellow Colloquium Series.

Other Information: 

This seminar takes places across multiple time zones: 9:30 AM Pacific/ 10:30 AM Mountain / 11:30 AM Central


Register via Zoom to receive the link for this event and the rest of the series.


See past seminar recordings on MathTube.