This lecture introduces you to the basics of the Amazon Web Services public cloud. It covers the fundamentals of cloud computing and goes through both the motivations and processes involved in moving your research computing to the cloud.

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 gives an overview of how to prepare and preprocess neuroimaging (EEG/MEG) data for use in TVB.  

This lecture covers the needs and challenges involved in creating a FAIR ecosystem for neuroimaging research.

This lecture covers the NIDM data format within BIDS to make your datasets more searchable, and how to optimize your dataset searches.

This lecture covers the processes, benefits, and challenges involved in designing, collecting, and sharing FAIR neuroscience datasets.

This lecture covers positron emission tomography (PET) imaging and the Brain Imaging Data Structure (BIDS), and how they work together within the PET-BIDS standard to make neuroscience more open and FAIR.

This lecture covers the benefits and difficulties involved when re-using open datasets, and how metadata is important to the process.

This lecture provides guidance on the ethical considerations the clinical neuroimaging community faces when applying the FAIR principles to their research. 

This lecture covers the ethical implications of the use of functional neuroimaging to assess covert awareness in unconscious patients and was part of the Neuro Day Workshop held by the NeuroSchool of Aix Marseille University.

This module covers many of the types of non-invasive neurotech and neuroimaging devices including electroencephalography (EEG), electromyography (EMG), electroneurography (ENG), magnetoencephalography (MEG), and more. 

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.

This lesson will go through the theory and practical techniques for implanting a GRIN lens for imaging in mice.

This lesson provides instruction on how to build a Miniscope and stream data, including an overview of the software involved.

This lecture discusses the the importance and need for data sharing in clinical neuroscience.

This lecture presents the Medical Informatic Platform's data federation for Traumatic Brain Injury.

This lecture gives insights into the Medical Informatics Platform's current and future data privacy model.

This lecture explains the concept of federated analysis in the context of medical data, associated challenges. The lecture also presents an example of hospital federations via the Medical Informatics Platform.