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.

This tutorial instructs users how to use MATLAB to programmatically convert data from cells to a matrix.

In this tutorial, users will learn how to identify and remove background noise, or "blur", an important step in isolating cell bodies from image data. 

This lesson teaches users how MATLAB can be used to apply image processing techniques to identify cell bodies based on contiguity.

This tutorial demonstrates how to extract the time course of calcium activity from each clusters of neuron somata, and store the data in a MATLAB matrix.

This lesson demonstrates how to use MATLAB to implement a multivariate dimension reduction method, PCA, on time series data.

This lecture covers infrared LED oblique illumination for studying neuronal circuits in in vitro block-preparations of the spinal cord and brain stem.

This lecture covers the application of diffusion MRI for clinical and preclinical studies.

This tutorial walks participants through the application of dynamic causal modelling (DCM) to fMRI data using MATLAB. Participants are also shown various forms of DCM, how to generate and specify different models, and how to fit them to simulated neural and BOLD data.

This lesson corresponds to slides 158-187 of the PDF below. 

This brief talk goes into work being done at The Alan Turing Institute to solve real-world challenges and democratize computer vision methods to support interdisciplinary and international researchers. 

This lightning talk describes the heterogeneity of the MR field regarding types of scanners, data formats, protocols, and software/hardware versions, as well as the challenges and opportunities for unifying these datasets in a common interface, MRdataset.

This brief talk covers an analysis technique for multi-band, multi-echo fMRI data, applying a denoising framework which can be used in an automated pipeline.