Thesis defense Justin Shenk (Donders series 566)
4 October 2022
Promotor: prof. dr. A. Kiliaan
Co-promotor: dr. M. Wiesmann
Trajectory Data Mining in Mouse Models of Stroke
This thesis introduces a novel, freely available Python library, Traja, which was developed for the analysis of homecage trajectory data from mouse models of stroke.
Section 1.2 presents the biological context of the thesis and addresses the importance of movement analysis in research, diagnosis and treatment of neurological diseases. We also discuss the shift from traditional methods of locomotion and behavioral analysis towards automated HCM in research with rodent models, and the need that this creates for software to manage, process and analyze the resulting data. Section 1.3 provides the technical background relevant to the development of the Traja software.
Chapter 2 presents Traja, a Python package built for analyzing trajectory data. It provides an explanation of the software architecture and design and demonstrate various methods useful for preprocessing, analyzing, and modeling trajectory data, using data derived from the study on multinutrient intervention after ischemic stroke in mice. It was published as Traja: A Python toolbox for animal trajectory analysis in “Journal of Open Source Software”.
Then, we demonstrate how Traja may be used in research with mouse models of stroke by analyzing mouse homecage trajectory data. Chapter 3 is based on the paper Automated Analysis of Stroke Mouse Trajectory Data With Traja, which was published in “Frontiers in Neuroscience”. In this study, we used Traja to analyze trajectory data from stroke-induced mice receiving a fortified diet treatment, Fortasyn. We demonstrated the usability of Traja for analysis of mouse positions in terms of activity, distance travelled, velocity, and turns and laterality. Chapter 4 is based on the paper Hydroxytyrosol, the major phenolic compound of olive oil as acute therapeutic strategy after ischemic stroke, which was published in “Nutrients”. Here, we extended the methods developed in Chapter 3 to a larger study involving treatment of a stroke mouse model with Hydroxytyrosol (HT) also referred to as a Mediterranean diet. We used Traja to analyze the effects of light phase and HT treatment on activity, distance travelled, walking velocity, total turnings, and laterality index 24/7. The results of these two studies indicate that Traja can be successfully applied to trajectory data mining and analysis, providing insight to researchers and demonstrating the potential for home cage mouse tracking in neurological research.
Finally, Chapter 5 provides a unifying discussion for the thesis. It addresses recent advances in technology used for behavioral analysis, particularly automated home cage monitoring, and how these create a need for software like Traja. We also further discuss the capabilities and advantages of Traja, and the applications of the software presented in this thesis. Finally, we consider other possible applications of Traja and reflect on how the software fits into the changing landscape of scientific research today.