NeuroNex Theory Hub Programs

Our NeuroNex Theory Hub is designed to provide neuroscience research and neuroscience researchers with outstanding theoretical and statistical support, guidance and inspiration. The primary ways we do this is to collaborate with other researchers and to provide them with a vibrant place to come to advance these collaborations. Columbia's NeuroNex Theory Hub brings together researchers with experience in developing and applying advanced statistical and modeling methods and who are embedded in an extensive network of collaborations across the entire field of neuroscience. We do this in part through the programs listed below.

Our NeuroNex programs are sponsored by NSF award DBI-1707398.


NeWS: NeuroNex Neurotheory Workshop Series 

A hands-on workshop for PhD students and Postdocs who want to learn new and advanced techniques in modelling and data analysis. Open to experimentalists and theorists, funded by NSF's NeuroNex initiative. Workshops will be held at Columbia University's Jerome L Greene Science Center.


Spring 2020 Workshop Schedule

1/22/2020, 1.30pm-5.30pm: Ella Batty and Matt Whiteway
BehaveNet: nonlinear embedding and Bayesian neural decoding of behavioral videos

2/19/2020, 1.30pm-5.30pm: Shreya Saxena 
Interpretable models of multi-regional calcium imaging data

Postponed until further notice due to COVID-19: Minni Sun
Understanding the functional and structural differences across excitatory and inhibitory neurons

Postponed until further notice due to COVID-19: Fabio Stefanini
A distributed neural code in the dentate gyrus and CA1

These workshops are intended for PhD students and postdocs who want to learn new and advanced techniques in modelling and data analysis.  During the workshops, attendees will hear about a research project (published or pre-print) followed by a hands-on tutorial. 

Workshops will include a presentation, a tutorial session and lots of time and space for unfiltered in-depth discussions and data hacking sessions.  If possible, participants are therefore encouraged to bring their own data so that they can apply the learned techniques on their own research projects.  

In order to maximize in-depth discussions and hands-on interaction within the group, we are limiting the group size on a first come first serve basis. A limited budget to cover short-travel expenses (e.g., train rides from the tri-state area) is also available. Interested participants should fill out this form.

We encourage participation from female scientists and those belonging to underrepresented minority groups.

Questions?  Email

The Spring 2020 workshop series will be held at Columbia University's Jerome L Green Science Center.

Organizers: Mario Dipoppa, Rainer Engelken, Ramon Nogueira, and Fabio Stefanini.

NeWS is funded by NSF's NeuroNex Award DBI-170739.

neurotheory banner


WANDA: Junior Scientist Workshop on Advanced Neural Data Analysis 

The Junior Scientist Workshop is organized in partnership with the NeuroNex Theory Team at the University of Houston and funded by the NSF's NeuroNex initiative.

This workshop is intended for PhD students and postdocs who want to learn and share with their peers new advanced techniques in data analysis and apply them to complex neural datasets. During the workshop, attendees will present their research projects, followed by a hands-on programming tutorial on the computational techniques used in their work. The purpose is to gain detailed understanding of the complexity of data and of the appropriateness of the different analysis techniques. The ideal participants are theoreticians with experience in analyzing experimental data as well as computationally minded experimentalists. By mixing a group of scientists with diverse background but with overlapping goals of uncovering structure in neural data, the participants will learn an array of techniques and foster fruitful collaborations.

The workshop will include presentations, tutorial sessions and lots of time and space for unfiltered in-depth discussions and data hacking sessions. We envision tutorials both on advanced data analysis as well as on specific experimental techniques and data processing. Participants are therefore expected to contribute with code or data to share and a reasonable dose of energy for giving tutorials on their work. Data and/or code can come in any format, including artificially generated data, but we encourage to make them available in a form that everyone can explore them with minimal overhead. Any data is shared only within the workshop. 

In order to foster an interactive atmosphere and allow everyone to give a detailed description and tutorial of their work, the workshops will be limited to a small group of participants. Participants will be provided funds to cover travel, accommodations, and meals.

We encourage applications from female scientists and those belonging to underrepresented minorities.

The 2019 workshop was held at Columbia University's Jerome L Greene Science Center.

The 2020 workshop was hosted by the University of Houston at the BioScience Research Collaborative.

Workshop Schedule for 2020.

Organizers: Krešimir Josić and Harel Shouval

Questions? Email

Visitors Program

This program supports researchers from academic institutions outside the NYC area (NYC visitors are welcome but do not require support) to visit the Theory Hub. These visitors may be theorists or experimentalists looking to learn new techniques or to collaborate in analyzing and modeling data. To participate, please email Stefano Fusi and Allison Ong with your research interests.


Neuroscience Cloud Analysis As a Service

NeuroCAAS is an open-source scientific resource that uses cloud computing to run powerful modern data analyses. It packages these analyses into fully portable descriptions called blueprints, which can be deployed to analyze data on demand and automatically. Analyzing data with NeuroCAAS
does not require any hardware purchases, installation, or dependency management. The scientific user is only responsible for two things: 1) their data, and 2) a configuration file containing analysis parameters. We provide these services to any interested researcher free of charge.

Access the NeuroCAAS site here


A collection of links to code for analysis and modeling developed by members of the Center.


Calcium imaging analysis

CalmAn, a package for analysis of large-scale calcium imaging data, now maintained by members of the Flatiron Institute (see Pnevmatikakis et al. 2016github)

CNMF-E, Constrained nonnegative matrix factorization for microendoscopic data (see Zhou et al. 2018github)


Population analyses for neural recordings

Cunningham lab (github)

Tensor maximum entropy method (see Elsayed & Cunningham 2017github)

LFADS, Latent factor analysis via dynamical systems (see Pandarinath et al. 2018github)

Page Last Updated: 8/7/2020