Education

CSM Optogenetics aims to support educational development by offering  comprehensive training, support, and teaching for our users.

We provide on-demand training or advice on experimental design, data collection, and data analysis.

Annually, we offer REALISE modules on Modern Approaches to Optogenetics and Behavioural Neuroscience as well as An Introduction to MATLAB for Optogenetics and Behavioural Neuroscience. Additionally, in 2023 we started our yearly, true hands-on imaging workshop on Fiber photometry and are planning our Miniscope workshop for 2024.

Moreover, we welcome summer students to engage in prototyping cutting-edge behavioral tools, data analysis software, and sensors. These activities are often published and contribute to enhancing the visiting students' professional profiles.

Fibre Photometry Workshop

Fiber photometry workshop

The CSMOpto Advanced Fiber Photometry Course provides an intensive 4 day, hands on course that covers the basic principles, the surgical approaches, and hurdles to the analysis of photometry data and results interpretation.

Realise

Modern Approaches to Optogenetics and Behavioral Neuroscience

Learn the basics of optogenetics, behavioural testing, and modern data analysis techniques.
This module will provide participants with an introduction on how to effectively incorporate optogenetics and behavioural analysis into their research. Lectures will cover the basics and general principles guiding optogenetics and rodent behavioural testing and analysis. Participants will also become familiar with classic and more modern approaches for behavioural and statistical data analysis. 
 

REALISE

An Introduction to MATLAB for Optogenetics and Behavioural Neuros

Learn the basics of computer coding in MATLAB for practical applications related to optogenetics and behavioural neuroscience.
This module will introduce computer coding in MATLAB with a focus on basic principles and practical applications for optogenetics and behavioural neuroscience. Participants will be provided with an introduction on how to navigate the MATLAB environment and effectively code in MATLAB.

Current students

  • Madina Shayne

    Madina is an undergraduate Mechanical Engineering student with a minor in Biomedical Engineering at the University of Calgary. In Summer 2021, Madina worked on hardware development for rodent home-cage monitoring, under the supervision of Leonardo Molina. She created models of camera holders on SolidWorks and produced these models through 3D printing.

    Madina is now working on computational algorithms for time-series data analysis, running on embedded devices, under the supervision of Dr. Taylor Chomiak.

Previous students

  • Seamus Munkholm

    Seamus joined CSM Opto in June 2022 as a co-op student from UBC pursuing a BASc in Electrical Engineering. He had the opportunity to work on the electrical and software systems of new and ongoing CSM Opto projects requiring R&D, under the supervision of Leo Molina, including improving the power supply and the reliability of serial communication for an operant conditioning chamber, and prototyping a room booking system using radar presence detection wirelessly connected to a battery-powered touchscreen user interface. Additionally, he assisted in annotating behavioral data for a research project, repairing a 3D printer and custom-made equipment, re-stocking lab supplies, and sourcing parts online. These projects required prototyping circuits, CAD modeling of both 3D parts and PCB components, programming micro-controllers, documenting code, wiring, and usage of custom-made tools, and using a variety of workshop tools including 3D printers, soldering stations, multimeter, etc. 

  • Eric Fan

    Eric joined CSM Opto in January 2022 to develop a method to capture animal behavior using embedded systems. His work allowed to stream videos from multiple home cages simultaneously and to detect individual mice using machine learning.

  • Robert Fiker

    Robert developed and maintained a novel desktop research application that leverages a Deep Learning framework for gait analysis. During his position he collaborated with CSM Opto core researchers Leo Molina, Dr. Taylor Chomiak and Dr. Patrick Whelan, and researchers from the HBI to published this work in The Journal of Neuroscience.