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.

📆 When?

January 29 – 31, 2025.

🤩 Interested?

Apply here!

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 7
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)
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