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

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. 

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

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

In this hands-on session, you will learn how to explore and work with DataLad datasets, containers, and structures using Jupyter notebooks. 

This talk describes the challenges in sharing personal, and in particular, health data, such as data anonymization and maintaining GDPR compliance. 

Video coming soon. 

This talk covers the differences between applying HED annotation to fMRI datasets versus other neuroimaging practices, and also introduces an analysis pipeline using HED tags.