CCN 2023 Workshop on Calcium & Voltage Imaging Analysis

Date & Time

Workshop Description

New imaging modalities – including endoscopic and multiphoton calcium imaging, and single and multiphoton voltage imaging, among others – have granted unprecedented access to the activity of large neuronal populations with high temporal resolution.  As such, those methods have been instrumental in obtaining new neurobiological insights inaccessible to other recording modalities. However, the barrier to establishing reproducible and efficient computational pipelines for imaging datasets, along with the difficulty of integrating this technology into real-time experiments, have substantially slowed progress in neuroscience and represent a significant opportunity cost for many laboratories.

CaImAn is an open-source software platform that provides optimized and scalable routines to process imaging data with the goal of extracting the activity of each neuron. CaImAn handles multiple imaging modalities (voltage, calcium, endoscopic, multiphoton, volumetric) and analysis settings (batch/offline vs online/real-time). Mesmerize is a new organizational and visualization framework that allows for efficient and streamlined analysis using CaImAn algorithms, and enables users with minimal programming experience to use CaImAn effectively. CaImAn is very popular among neuroscientists world-wide, but its widespread dissemination, the efficient use of its routines, and the opportunities provided by Mesmerize, require access to training opportunities. We will address this challenge by establishing a workshop at the Flatiron Institute, Simons Foundation.

The free workshop will be of interest to imaging researchers at many levels of experience. It will provide a unique opportunity to directly learn from lead developers of both CaImAn and Mesmerize for analysis of calcium and voltage data. Attendees will receive:

  • Tutorials on cutting edge calcium and voltage imaging analysis tools.
  • Hands-on training with real data sets and practical code examples that they will be able to use with their own data.
  • Receive training on the new Mesmerize framework for batch analysis and data organization enabling streamlined use of CaImAn algorithms.
  • Training on the mesmerize-viz and fastplotlib libraries for very fast visualization or large-scale datasets in Jupyter notebooks.
  • More experienced users and developers will have the opportunity to participate in a hackathon, make contributions to the core packages, and become active contributors to these tools moving forward.
  • Training in DataJoint: data organization and infrastructure with the help of a database server.

There is no charge to attend the workshop. Each day, meals will be provided for attendees, and accommodations will be provided for non-local participants. Travel grants will be offered to individuals whose participation furthers the goal to promote diversity in systems and computational neuroscience, in particular among populations underrepresented in the scientific workforce as defined by NIH (including but not limited to racially underrepresented individuals, women, individuals with disabilities and individuals from disadvantaged backgrounds).

To see the schedule/website for a previous iteration of the workshop, held in June 2022, see: 

Learning Objectives

  • Learn the fundamentals of the calcium/voltage imaging analysis package CaImAn
    • Background and principles, including:
      • PCA
      • Nonnegative matrix factorization
      • Optimization
    • How to install and use the software with a provided data set
  • Learn Mesmerize, a batch management framework for CaImAn algorithms
    • Batch processing to maximize efficiency by automating parameter search
    • Motion correction and CNMF using Mesmerize’s pandas extensions
    • fastplotlib and mesmerize-viz for fast interactive visualization within jupyter notebooks
    • We will be using the new Mesmerize framework in jupyter notebooks, not the older Mesmerize desktop application.
  • Practical data analysis with users’ own data
    • Half-day “bring your own data” session for hands-on experience
  • Learn to adapt Mesmerize and CaImAn to individual researcher needs
    • Instructions on how to use Github to contribute
    • Half-day hackathon for hands-on experience making contributions
  • For More information on the packages see their GitHub repos:

* Note that we will not cover the older Mesmerize desktop application which is now treated as legacy software.

Target Attendees:

  • Researchers with some programming experience who want to enhance their understanding of the CaImAn and Mesmerize software packages, and the underlying theory behind them.
  • Users with their own calcium/voltage imaging data that they want help analyzing.
  • Ideally 10 or more attendees (out of 30) that are interested in contributing to the packages.


To apply, please visit:

Application Deadlines

Workshop attendance will be capped at 30 attendees. In the event that there are over 30 applications, participation will be restricted to one applicant per lab.  Applications to attend the workshop will be accepted through midnight on Sunday, November 6, and admitted attendees will be notified by Friday, November 18; persons who applied for travel grants will also be notified by November 18.

If your application is accepted, you will be required to submit your intent to attend by Tuesday, November 22 to help ensure full attendance and to allow time for travel arrangements.

The event will also be recorded as a reference for attendees, and for those who are unable to attend.


  • Dr. Mitya Chklovskii, Group Leader, Neural Circuits and Algorithms Group, CCN
  • Dr. Johannes Friedrich, Associate Research Scientist, Neural Circuits and Algorithms Group, CCN
  • Dr. Andrea Giovannucci
  • Pat Gunn, Senior Software Engineer, Flatiron Institute, SCC
  • Kushal Kolar, Doctoral Candidate in Neuroscience, University of North Carolina at Chapel Hill
  • Dr. Eric Thomson, Bioinformatics Scientist, National Institutes of Health

Teaching Assistants

  • Caitlin Lewis, Research Assistant, Statistics and Computer Science degree candidate, University of North Carolina at Chapel Hill
  • Changjia Cai, Doctoral Candidate in Biomedical Engineering, University of North Carolina at Chapel Hill
  • Arjun Putcha, Doctoral Candidate in Biomedical Engineering, University of North Carolina at Chapel Hill
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