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Flatiron CCN Software Workshop, January 2025

The Flatiron Center for Computational Neuroscience is excited to announce a workshop on using open source packages to analyze neural data in January 2025!

Over the course of this two-day workshop, we will teach you how to use pynapple and NeMoS to analyze, model, and visualize neural data.

Where?

In person at the Flatiron Institute, 160 5th Ave, New York, NY 10010.

πŸ“† When?

January 29 – 31, 2025.

🀩 Interested?

Applications have closed. Watch our website for announcements of future workshops!

❓Questions?

Email us at neurorse [at] flatironinstitute.org.

Intended audience

  • This workshop is intended for grad students and postdocs who are systems neuroscientists, i.e., who analyze electrophysiology or calcium imaging data.
  • In order to make best use of the limited space in the workshop, we will prioritize accepting one applicant per lab.
  • Applicants are expected to have basic familiarity with python:
    • They should have used python and standard scientific python libraries (e.g., numpy, matplotlib, scikit-learn).
    • They should be able to write their own functions to analyze and visualize data.
    • They are not expected to familiar with either pynapple or NeMoS.
  • This workshop is intended for folks who are located within a three-hour flight of New York City. (We will host other workshops in other locations!)

Important dates

  • Applications opens October 1
  • Applications due November 1
  • Applicants notified of acceptance by November 8
  • Applicants must notify us of their attendance by November 11
  • Workshop: January 29 to 31, 2025

Logistics

  • The workshop will take place at the Flatiron Institute Center for Computational Neuroscience in midtown Manhattan.
  • We will accept approximately 30 attendees.
  • For those not in the New York City area to accommodations will be provided. A limited number of travel scholarships are also available.
  • Meals will be provided, including one off-site dinner.

Workshop contents

Over the course of this workshop, attendees will learn how to use pynapple and NeMoS to explore and analyze electrophysiogical data, making use of real datasets. Users will:

  • Use pynapple to represent neural data, taking advantage of the shared time axis to perform common manipulations.
  • Use pynapple to characterize neural responses, e.g., compute tuning curves, cross-correlograms, power spectral densities.
  • Use NeMoS to fit generalized linear models to spiking data, investigating functional connectivity and comparing among possible models.

To get a sense of the material we will cover, see our workshop from FENS 2024.

Tentative schedule

Day 0 (Wed, Jan 29) Β 
2pm – 5pm Installation help
5pm – 7pm Welcome reception
Day 1 (Thurs, Jan 30) pynapple
9 – 10am Breakfast
10 – 11am Welcome and introduction to data standards
11 – 11:30am Coffee break
11:30am – 1pm Pynapple core
1 – 2pm Lunch
2 – 3:30pm Standard analyses in systems neuroscience, part 1: cross-correlations and tuning curves
3:30 – 4pm Coffee break
4 – 5:45pm Standard analyses in systems neuroscience, part 2: signal processing
5:45 – 6pm fastplotlib advertisement
6 – 8pm Dinner
Day 2 (Fri, Jan 31) NeMoS
9 – 10am Breakfast
10 – 11am Introduction to Generalized Linear Models (GLMs)
11 – 11:30am Coffee break
11:30am – 1pm Fitting a basic GLM to single neuron patch-clamp recordings
1 – 2pm Lunch
2 – 4pm Functional connectivity analysis of head-direction neurons
4 – 4:30pm Coffee break
4:30 – 6pm Feature selection and model comparison
6 – 8pm Dinner

Speakers

Edoardo Balzani

Associate Research Scientist, CCN

Billy Broderick

Associate Research Scientist, CCN

Oliver RΓΌbel

Staff Scientist, Lawrence Berkeley National Laboratory

Sarah Jo Venditto

Associate Research Scientist, CCN

Guillaume Viejo

Associate Research Scientist, CCN

TAs

Isabel Garon

PhD candidate, NYU

Caitlin Lewis

PhD student, Duke University

Erik Schomburg

Research Scientist, CCN

Aramis Tanelus

Research analyst, CCN