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Open Neurophysiology - analysis tools and datasets
Provider: Faculty of Health and Medical Sciences

Activity no.: 3490-23-00-00 
Enrollment deadline: 17/03/2023
Date and time24.04.2023, at: 09:00 - 28.04.2023, at: 17:00
Regular seats16
Course fee5,640.00 kr.
LecturersHajime Hirase
ECTS credits4.00
Contact personAntonios Asiminas    E-mail address: a.asiminas@sund.ku.dk
Enrolment Handling/Course OrganiserPhD administration     E-mail address: phdkursus@sund.ku.dk

Aim and content
This course is free of charge for PhD students at Danish universities (except Copenhagen Business School), and for PhD Students from NorDoc member universities. All other participants must pay the course fee.

Anyone can apply for the course, but if you are not a PhD student at a Danish university, you will be placed on the waiting list until enrollment deadline.

This also applies to PhD students from NorDoc member universities. After the enrollment deadline, available seats will be allocated to applicants on the waiting list.


Learning objectives
A student who has met the objectives of the course will be able to:
1. Gain insights into open neuroscience initiatives, and more specifically open neurophysiology
2. Search for and explore open neuroscience datasets and tools
3. Use open access tools to analyze neurophysiology data (MATLAB and/or Python)
4. Use open access tools to track and analyze behavior (DeepLabCut)
5. Understand “FAIR” principles for data and code sharing


Content
In recent years, an increasing number of datasets and analysis tools have become freely available. These come for national and international research initiatives, as well as individual labs and researchers. However, the majority of researchers are not aware of these resources, or they do not possess the skills to make full use of them. This five-day course will focus on open data and tools in neurophysiology.

Day 1:
On day one we will provide an overview of open science initiatives, with a focus on neuroscience data depositories and tools. We will discuss the idea behind open science and how it can potentially revolutionize neuroscience research, but also the challenges ahead. We will introduce the tools we will use over the course and have a chance to make sure all students are ready for the practical exercises ahead. The day will close with two talks by external speakers who are spearheading open neuroscience (Ken Harris & Alexander Mathis)

Day 2:
On day two we will focus on open neurophysiology data. We will provide an overview of initiatives with a focus on neurophysiological data from the Allen Brain Observatory. Through hands-on follow-along exercises, participants will learn where and how can they access neurophysiology data from Allen Brain Observatory, and how to explore its basic features. The day will conclude with two talks from researchers who have answered interesting questions using open data and have been developing open analysis tools (Adrien Peyrache & Noam Nitzam)

Day 3:
On day three we will focus on open tools for analysis of behavior. We will provide a high level overview of the current available tools for conducting behavioral experiments and analyzing behavior. We will then focus on DeepLabCut, and through a series of walk-through tutorials, participants will learn how to create new projects, label data, training and refining their tracking algorithm using a standard laptop and online computing resources (Google Colab). At the end of the day, Jared Cregg will present his work in which he has used DeepLabCut to study motor function in mice.

Day 4:
On day four we will use open analysis tools (written in MATLAB and/or Python) to analyze neurophysiological data from the Allen Brain Observatory. This will involve a series of practical walkthroughs and discussions on how to interpret results. The day will close with a talk by Shreya Saxena who has been championing open neuroscience with her involvement in initiatives such as Neuromatch Academy.

Day 5:
On day five we will continue and conclude with the neurophysiology data analysis walkthroughs. We will also provide an overview on data and code sharing (e.g. “FAIR” principles). The course will finish with a talk by Liset de la Prida, a world expert in neurophysiology of hippocampus, whose lab has been developing open analysis and modeling tools.

All materials and additional links for further reading and practice will be made available to students at the end of the course.


Participants
The course is aimed at PhD students who would like to learn how to access and analyze open datasets in their research. The course involves use of analysis tools written in Python and MATLAB. While proficiency in any of these programming languages is not essential, participants with previous programming experience will be able to follow the material more easily. Prior to the course we will provide further information as well as material to help students take the most out of the course. The course is mainly relevant to PhD students specializing in neuroscience, but anyone interested in open science and open datasets can take part. Knowledge of calculus and linear algebra will be beneficial. Students should bring their laptops to follow tutorials and exercises. For students interested in using MATLAB for neurophysiology data analysis, we expect them to have a copy of the software installed on their laptops. For analysis of behavioural and neurophysiology data using Python, we will provide instructions prior to the course. No other specific software is needed, except from a Gmail account needed to access the Google Colab coding platform.
Relevance to graduate programmes
The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH:
- Neuroscience
- In Vivo Pharmacology and Experimental Animals


Language
English


Form
Lectures, group exercises, tutorials


Course director
Hajime Hirase, Professor, Center for Translational Neuromedicine, hirase@sund.ku.dk
Peter Petersen, Assistant Professor, Department of Neuroscience, petersen.peter@sund.ku.dk
Antonis Asiminas, Postdoctoral Researcher, Center for Translational Neuromedicine, a.asiminas@sund.ku.dk
Rune Nguyen Rasmussen, Postdoctoral Researcher, Center for Translational Neuromedicine, rune.nguyen.rasmussen@sund.ku.dk

Teachers
Antonis Asiminas, Postdoctoral Researcher, Center for Translational Neuromedicine
Peter Petersen, Assistant Professor, Department of Neuroscience
Rune Nguyen Rasmussen, Postdoctoral Researcher, Center for Translational Neuromedicine
External Speakers:
Adrien Peyrache, Assistant Professor, McGill University, Canada
Kenneth Harris, Professor, University College London, UK
Alexander Mathis, Assistant Professor, EPFL, Lausanne, Switzerland
Noam Nitzan, Postdoctoral Researcher, New York University, USA
Jared Cregg, Assistant Professor, Department of Neuroscience
Shreya Saxena, Assistant Professor, University of Florida, USA
Liset M de la Prida, Research Director, Instituto Cajal, Madrid, Spain


Dates
24-28 April 2023 at 9-17


Course location
Mærsk Tower, Room 7.15.149


Registration
Please register before 17th of March 2023

Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules.
Applications from other participants will be considered after the last day of enrolment.

Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

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