Data Science for Large-Scale Imaging of Neuronal Activity


Suzhou, China 

August 16 - 30, 2026

Application Deadline: May 31, 2026



Organized by:

Mark Reimers, Michigan State University

Jennifer SunUniversity College London



COURSE DESCRIPTION


See the roll of honor - who's taken the course in the past


This course will introduce students to the statistical and computational techniques needed for processing and analyzing the population ecording data now being generated with high-throughput calcium imaging techniques in behaving experimental animals. These state-of-the-art technologies include in vivo two-photon, mini-scope, wide field, and lightsheet imaging. The course will first address advantage and specific pre-processing issues related to each imaging techniques, and then discuss the analytical methods for population activity, especially multivariate methods for finding low-dimensional representations that correlates with animal behavior or experimental stimulus. We will also discuss several emerging topics in neural population analysis, such as network analysis and inter regional communication.



2026 FACULTY ROSTER


Mikio Aoi, University of California San Diego

Hadas Ben-Esti, Technion - Israel Institute of Technology

Kenneth Harris, University College London 

Xiaoxuan Jia, Tsinghua University

Abhilasha Joshi, National Center for Biological Sciences, Bangalore

Jaekyung Kim, Korea Advanced Institute of Science and Technology

Yu Mu, Institute of Neuroscience, CAS

Mark Reimers, Michigan State University

Jennifer SunUniversity College London

Quan Wen, University of Science and Technology of China  

Jiamin Wu, Tsinghua University

Chris Xu, Cornell University



2026 PRICING (INCLUDING TUITION, BOARD AND LODGING): 1400 USD


No payment is due until the selection decisions are made, but any applicant requiring financial support (i.e. stipends) should make that request in written form during the online application. The admissions process is need-blind, your financial situation will not be considered before admission decisions are made.