Overview Day 1#
Welcome to Day 1✨!
We will kick start 🚀 the week with two exciting lectures:
The neuronal cell types and circuits underlying locomotion, taught by Prof. Ole Kiehn from the University of Copenhagen and Karolinska (this years Brain Prize winner😎)
Studying natural behavior in corvids to elucidate cognition, taught by Prof. Nicky Clayton from the University of Cambridge
Click HERE to watch the lectures! Please do so at your own pace before the practical session.
Later, in the practical part, we will discuss what is behavior and how can we understand it 🤔!
Important
PLEASE NOTE: The live synchronous session for Day 1 is 2 hours long!
Day 1: Take home messages#
Tip
Defining behavior in a way that generates testable hypotheses requires careful observations of whole organisms and a firm grasp of the specific cellular anatomy & physiology of the species whose behavior you are studying.
Designing behavior experiments in a way that take feedback loops, homeostasis, and plasticity into account can necessitate totally new metrics and quantifications.
Taking time to “learn how to look” is an invaluable investment for anyone studying behavior.
Day 1: Major Goals ⚽️#
Important
Please ensure your DeepLabCut installation is ready! If you have a GPU, please make sure that it is utilized. You can ask the teaching assistants 📢, if you are not sure. To achieve this, check out our Installation guide.
Please remember to bring your videos, if you wish to work on your own data. Ideally select different videos that reflect the variability of the data in your setup and that you would like to analyze. If you do not have suitable datasets, check out our suggested demo datasets.
Please ensure that you have completed the Discord on-boarding process, and have chosen your tags in the “student-tags-2023” channel.
Read the following papers:
“You Say You Had a Revolution: Methodological Foundations of Closed-Loop Psychology”
“On the aims and methods of Ethology”: you can find a pdf of this paper on the course discord.
“Neuroscience Needs Behavior: Correcting a Reductionist Bias”
Skim the following papers:
“Primer on Motion Capture with Deep Learning: Principles, Pitfalls, and Perspectives” –> [MSLM20], linked below.
References
Alexander Mathis, Steffen Schneider, Jessy Lauer, and Mackenzie Weygandt Mathis. A primer on motion capture with deep learning: principles, pitfalls, and perspectives. Neuron, 108(1):44–65, October 2020. URL: https://doi.org/10.1016/j.neuron.2020.09.017, doi:10.1016/j.neuron.2020.09.017.