This lesson discusses FAIR principles and methods currently in development for assessing FAIRness.
In this lesson, while learning about the need for increased large-scale collaborative science that is transparent in nature, users also are given a tutorial on using Synapse for facilitating reusable and reproducible research.
This lesson contains the first part of the lecture Data Science and Reproducibility. You will learn about the development of data science and what the term currently encompasses, as well as how neuroscience and data science intersect.
The lecture provides an overview of the core skills and practical solutions required to practice reproducible research.
This lecture provides an introduction to reproducibility issues within the fields of neuroimaging and fMRI, as well as an overview of tools and resources being developed to alleviate the problem.
This lecture provides a historical perspective on reproducibility in science, as well as the current limitations of neuroimaging studies to date. This lecture also lays out a case for the use of meta-analyses, outlining available resources to conduct such analyses.
This lecture covers the history of behaviorism and the ultimate challenge to behaviorism.
This lecture discusses how to standardize electrophysiology data organization to move towards being more FAIR.
Overview of the content for Day 1 of this course.
Best practices: the tips and tricks on how to get your Miniscope to work and how to get your experiments off the ground.
This talk delves into challenges and opportunities of Miniscope design, seeking the optimal balance between scale and function.
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 introductory lesson welcomes users to the virtual learning series, explaining some of the background behind open-source miniscopes, as well as outlining the rest of the lessons in this course.
This lesson provides an overview of the Miniscope project, explaining the motivation behind the how and why of Miniscope development, why Miniscopes may be useful for researchers, and the differences between previous and current versions.