2015-16: CCNS: Workshop on Optical Imaging Data Analysis: February 1-2, 2016


This workshop was held at SAMSI in RTP.  It was by invitation only.


Optical imaging is widely considered the most promising technology to achieve the aims of the BRAIN initiative. New indicators of neural activity are being developed every year, and imaging technology improves continually. These data will revolutionize neuroscience, just as microarrays revolutionized genomics, and should be similarly fruitful as a stimulus to innovation in statistics. Nevertheless there are almost no statisticians currently working with these data, both because these data are unfamiliar and are harder to access. This workshop would aim to introduce many statisticians to these data and present the major issues at present and expected in the near future.

The objectives are to introduce statisticians to the characteristics of optical technologies and to the kinds of statistical questions that are pressing now and may be appearing in the near future and to stimulate discussion about promising approaches to the largely unsolved statistical challenges of the new high-throughput optical data.

Questions: email CCNS@samsi.info

Schedule and Supporting Media

Participant List

Monday, February 1, 2016

Time Description Speaker Slides Videos
9:00-9:15 Opening Remarks Mark Reimers, Michigan State University
9:15-10:00 Neuroscience Questions Opened up by Optical Imaging Bruce McNaughton, University of California, Irvine
10:00-11:00 Session 1: Optical Technologies and Experiments Yiyang Gong, Duke University
10:40-11 Break
11:00-12:30 Session 1 (continued): Optical Technologies and Experiments, Strategies for Large-scale Calcium Imaging in the Mouse Brain Matthew Valley, Allen Institute for Brain Science and Dieter Jaeger, Emory University  
12:30-1:30 Lunch
1:30-3:00 Session 2: Pre-processing Issues
Part I: Calcium Imaging
Brief Reports and Issues
Dynamic Linear Models for Neuronal Optical Images
Traces from Calcium-sensitive Dyes
Can We Extract Neuropil Signal Automatically?
Eftychios Pnevmatikakis, Simons Foundation
Michael Lavine, University of Massachusetts, Amherst
Valentina Staneva, University of Washington
Pengcheng Zhou, Carnegie Mellon University
3:00-3:20 Break
3:20-5:00 Session 2: Pre-processing Issues (continued)
Part II: Voltage Imaging
Linear Model Decomposition for Voltage-sensitive Dye Imaging Signals: application on awake monkey
Brief Reports and Issues
Alexandre Reynaud, McGill University
Ming Yan, Michigan State University
Mark Reimers, Michigan State University
5:00-5:30 Working Groups
5:30-7:00 Reception (2nd Fl Commons) and Software Tutorials (Room 150)

Tuesday, February 2, 2016


Time Description Speaker Slides Videos
9:00-10:15 Session 3: Handling Big Data
Brief Reports and Issues
Challenges and Opportunities in Scalable Analysis of Neural Imaging Data
Jason Wittenbach, HHMI Janelia Farm
Ming Yan, Michigan State University
10:15-10:45 Break
10:45-12:15 Session 4: Network and Connectivity Analysis
Brief Reports and Issues
Yu Hu, Harvard University
Yuying Xie, Michigan State University
Mark Reimers, Michigan State University
12:15-1:15 Lunch
1:15-2:45 Space Dynamics
Brief Reports and Issues
Determining the Dimensionality of Brain-wide Activity from Calcium Imaging Data
Kathleen Champion, University of Washington
Mark Reimers, Michigan State University
Casey Diekman, New Jersey Institute of Technology
Grace Hong, Michigan State University
2:45-3:00 Break
3:00 Wrap-up Discussion
Note: Most sessions will begin with a 35-min talk with 10 min questions by a leading speaker, and continue with several 5-10 min brief reports, and selected discussion questions.