A practical course at University College London, 27 - 29 April 2020
Neuropixels probes are transforming neurophysiology, with over 265 laboratories worldwide adopting them in 2019 alone. The probes have 1,000 sites closely spaced on a 1 cm shank, yielding recordings of up to 500 neurons per probe.
This practical course aims to train students and postdocs to use these probes and to spike sort using Kilosort and Phy.
The course is supported by the Wellcome Trust and generously funded and hosted by the Sainsbury-Wellcome Centre. Because it is a practical course, we can only offer a limited number of places. To apply please fill out this form before 24 January 2020. We will select students and send out invitations in early February. Also, see the Neuropixels Wiki for alternative courses.
Organizers
- Nick Steinmetz (University of Washington)
- Matteo Carandini (UCL)
Lecturers
- Nick Steinmetz (University of Washington)
- Kenneth Harris (UCL)
- Matteo Carandini (UCL)
- Andrew Peters (UCL)
- Andre Marques-Smith (UCL)
Teaching Assistants
- Maxime Beau
- Jai Bhagat
- Antonin Blot
- Dario Campagner
- George Dimitriadis
- Mayo Faulkner
- Alex Fratzl
- Sepiedeh Keshavarzi
- Dimitar Kostadinov
- Yaara Lefler
- Anna Lebedeva
- Cristina Mazuski
- Nate Miska
- Viktor Plattner
- Sylvia Schroeder
- Karolina Socha
- Mateo Velez-Fort
Demo Labs
Schedule (this is from the 2019 course and will be updated)
Day 1
- Introduction to Neuropixels - Carandini - slides
- Ground-truth data with Neuropixels - Marques-Smith - slides
- Science with large recordings - Harris - slides
- Recording across the brain with Neuropixels - Steinmetz - slides
- Practicalities of Neuropixels recordings - Steinmetz - slides
- Overview of the demos in Day 2 - Teaching Assistants
Day 2
- Implanting chronic Neuropixels in rats - Dimitriadis - slides - CAD - more CAD
- Implanting chronic Neuropixels in mice - Campagner - slides
- Demos: Chronic recordings
- Demos: Acute recordings
Day 3
- Spike sorting with Kilosort and Phy - Steinmetz - slides
- Analyze ground-truth data
- Analyze the data acquired on Day 2
- Project presentations
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