Attendees of this talk will learn aobut computational imaging systems and associated pipelines, as well as open-source software solutions supporting miniscope use.

This lecture introduces neuroscience concepts and methods such as fMRI, visual respones in BOLD data, and the eccentricity of visual receptive fields. 

This tutorial walks users through the creation and visualization of activation flat maps from fMRI datasets. 

This talk covers the present state and future directions of calcium imaging data analysis, particularly in the context of one-photon vs two-photon approaches. 

This tutorial demonstrates to users the conventional preprocessing steps when working with BOLD signal datasets from fMRI. 

In this tutorial, users will learn how to create a trial-averaged BOLD response and store it in a matrix in MATLAB. 

This tutorial teaches users how to create animations of BOLD responses over time, to allow researchers and clinicians to visualize time-course activity patterns.

This tutorial demonstrates how to use MATLAB to create event-related BOLD time courses from fMRI datasets. 

In this tutorial, users learn how to compute and visualize a t-test on experimental condition differences.

In this talk, results from rodent experimentation using in vivo imaging are presented, demonstrating how the monitoring of neural ensembles may reveal patterns of learning during spatial tasks.

How to start processing the raw imaging data generated with a Miniscope, including developing a usable pipeline and demoing the Minion pipeline.

The direction of miniature microscopes, including both MetaCell and other groups.

Overview of the content for Day 2 of this course.

Summary and closing remarks for this three-day course.

This hands-on tutorial explains how to run your own Minion session in the MetaCell cloud using jupityr notebooks.

In this hands-on analysis tutorial, users will mimic a kernel crash and learn the steps to restore inputs in such a case.

This lesson introduces various methods in MATLAB useful for dealing with data generated by calcium imaging. 

This lesson will go through how to extract cells from video that has been cleaned of background noise and motion.

This tutorial demonstrates how to use MATLAB to generate and visualize animations of calcium fluctuations over time. 

This final hands-on analysis tutorial walks users through the last visualization steps in the cellular data.