This lesson discusses FAIR principles and methods currently in development for assessing FAIRness.
This lecture presents an overview of functional brain parcellations, as well as a set of tutorials on bootstrap agregation of stable clusters (BASC) for fMRI brain parcellation.
This lecture will provide an overview of neuroimaging techniques and their clinical applications.
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 provides an introduction to the course "Cognitive Science & Psychology: Mind, Brain, and Behavior".
This lecture covers the emergence of cognitive science after the Second World War as an interdisciplinary field for studying the mind, with influences from anthropology, cybernetics, and artificial intelligence.
This lecture covers different perspectives on the study of the mental, focusing on the difference between Mind and Brain.
This lecture outlines various approaches to studying Mind, Brain, and Behavior.
This lecture covers the history of behaviorism and the ultimate challenge to behaviorism.
This lecture covers various learning theories.
This lecture covers a lot of post-war developments in the science of the mind, focusing first on the cognitive revolution, and concluding with living machines.
In this lesson, you will learn about how genetics can contribute to our understanding of psychiatric phenotypes.