Modern Approaches to Behavioural Analysis 2023

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Modern Approaches to Behavioural Analysis 2023

Application form for NeuroKit course online as participant
Course co-directors:

Alexander Mathis, course Director EPFL, Switzerland

Danbee Kim, co-director, Matter Neuroscience, UK

Modern Approaches to Bheavioural Analysis: Disclaimer

This course will emphasize the philosophical and observational skills required to understand behaviour, while also providing training in motion capture technologies and computer vision methods that can assist in the collection and analysis of video recorded behaviour datasets.

Focusing on the tool DeepLabCut, students will analyse either their own original video dataset or datasets of general interest and have the opportunity to practice tracking, pose estimation, action segmentation, kinematic analysis and modelling of behaviour.

By the end of the course, you will:

- be familiar with modern and historical frameworks for studying the behaviour of living biological systems
- practice methods for carefully and precisely observing and defining behaviours
- understand the limits and capabilities of computer vision
- develop an intuition for how to build experimental setups that can take advantage of tools such as DeepLabCut
Furthermore, this course shares and promotes open source software, and we encourage students to try new ideas, share insights, and connect with the open-source community.

Requirements

For the course, you will need access to a computer, and a stable internet connection for the online tutorials.

Checklist

Please make sure to have gathered all required information below before you start your application.

Marked (*) items are mandatory.
- Personal information (contact details, …)*
- Curriculum vitae (submitted as a separate file, max 3 pages, pdf format) *
- List of publications in peer-reviewed journals (no meeting abstracts, supply list in PubMed format)
- First author presentations (up to six) at meetings (with co-authors and titles)
- Motivation for attending this course (about 300 words)*
- Research interests and background relevant for attending this Cajal Neurokit (about 300 words)*
- Stipend requested (provide arguments for stipend, 200 words), if applicable
- One referee (Full name, e-mail)* (the referee will receive an e-mail asking him/her to support your application. Please make sure that your referee fill in the form that will be sent to them, as your application will be considered as incomplete if they don't.)

Full Name*

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Number of publications in peer-reviewed journals (optional):

None1 or 23 to 5More than 5
Indicate publications in peer-reviewed journals (optional)
Do not include meetings abstracts
IMPORTANT: Check the FENS website for correct formatting of your publication list!
First author presentations at scientific meetings (optional)

NoneLess than 3More than 3
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Maximum 6

Motivation for attending the course*

Max 300 words0/300
Please describe below your prior experience with the technologies used in neuroscience: programming, electronics, data acquisition, data analysis, imaging, machine learning/AI, etc. This course does not require prior experience, but your answers to this question will help us organize the interactive training sessions.*

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Did you attend a Cajal course in the past?*

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Kindly note that if you benefited from a Cajal stipend in the past, you are no longer eligible to receive this type of funding. However other types of funding (such as partial travel grants from sponsors) might be made available after the participants selection process, depending on the course.

Indicate one referee. The referee will receive an email asking to rate your application.

It is important that you make sure that your referee:
- is aware of your request for recommendation
- received the email with the form
- fills in the form that will be sent to them

If no form is submitted, your application will be considered as incomplete.

The referee can fill reference form up to two days after the applications deadline.
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