Quantitative Approaches to Behaviour
Summer School, 22.5.2022 until 11.06.2022
Alex Jordan, Serena Ding
CAJAL Advanced Neuroscience Training Programme
Quantitative studies of behaviour are fundamental in our effort to understand brain function and malfunction. Recently, the techniques for studying behaviour, along with those for monitoring and manipulating neural activity, have progressed rapidly. This course provides promising young scientists with a comprehensive introduction to state-of-the-art techniques in quantitative behavioural methods. This course’s content is complementary to other summer courses that focus on measuring and manipulation neurophysiological processes. Our focus is on methodologies to acquire rich data representations of behavior, dissect them statistically, model their dynamics, and integrate behavioral measurements with other kinds of neurobiological data. To this end, students will 1) fabricate devices for recording the behavior experimental organisms, 2) learn, under the guidance of the scientists developing these methods, the modern tools to analyze behavioral data from these organisms, and 3) in a week-long independent project develop and conduct a behavioral study of their own design, with the support and guidance of the course instructors and teaching assistants. This 3-week course is a practical “hands-on” introduction to advanced methods in behavioural tracking and analysis. Our educational goal is to cover sufficient background such that all participants will be able to establish these techniques in their home laboratories. In the pedagogical portion of the course (blocks 1 and 2, see below) we will use two main experimental model systems: flies (Drosophila melanogaster) and zebrafish (Danio rerio). Several days of instruction will focus on analysis of video data, and on these days, students may use videos of flies and fish, videos we provide of mammals behaving, or videos of their own organism of choice. In the student project portion of the course (block 3), students may use these experimental organisms, as well as, subject to their availability, organisms in use at the Champalimaud. We will cover data acquisition (software, hardware, tools), preprocessing (single animal, body parts and multiple animals tracking systems), data analysis (clustering, ethograms) and modeling.
Ideas for projects for the upcoming course:
Manifolds in dynamical representations of behavior;
Deep attention models of collective fish behavior;
Modelling behavior with different tradeoffs of accuracy and complexity using symbolic regression;
Unsupervised discovery of motifs in rodent vocalizations.
Recommended for: PhD level