LS/MCB100: Introduction to Computational Ethology

offered at Harvard University

by Souvik Mandal

Faculty advisor: Venkatesh N. Murthy

Welcome to Computational Ethology!

One of the most important parts of ethological studies is testing hypotheses by collecting and analyzing behavioral data. Pioneers of ethological studies recorded quantitative data on behavior through manual observations. Though conducting such manual observation is still very relevant for so many reasons, it could be cumbersome. With the advent of technology, however, now we can automatize "extracting" behavioral data from videos. And in this course, we introduce cutting-edge computational tools that can do this job. We designed it especially for students who have a compelling question on behavior but have little or no experience in modern computation!

Goal of the course: What will you learn?

This course aims to make students comfortable with using modern computational tools for quantitatively measurement of behavior from videos. We will focus on behaviors that are defined by the movements of body-parts (although behavior can be auditory and olfactory). For that, tracking precise movements of body-parts in a sub-second resolution is critical, and you will learn to do so using deep learning tools. Specifically, you will learn to formulate a behavior-related question into a scientific hypothesis; testing it by using computer vision, artificial intelligence, cloud computing, clustering methods and statistical analyses and data visualization in Python and/or R; and presenting your work, and writing a final report.

Learning style

It is a hand-on experience based course! You can access all the reading materials on this website any time suitable for you - find these on the "GUIDING MATERIAL" and "DOWNLOAD CODES". Go through those at your own pace. If you face any problem, shoot me an email. We will discuss that during the next meeting.

“Our organ of thought may be superior, and we may play it better, but it is surely vain to believe that other possessors of similar instruments leave them quite untouched.”

- Stephen walker