Skip to main content

This lesson gives an in-depth introduction of ethics in the field of artificial intelligence, particularly in the context of its impact on humans and public interest. As the healthcare sector becomes increasingly affected by the implementation of ever stronger AI algorithms, this lecture covers key interests which must be protected going forward, including privacy, consent, human autonomy, inclusiveness, and equity. 

Difficulty level: Beginner
Duration: 1:22:06
Speaker: : Daniel Buchman

This lesson describes a definitional framework for fairness and health equity in the age of the algorithm. While acknowledging the impressive capability of machine learning to positively affect health equity, this talk outlines potential (and actual) pitfalls which come with such powerful tools, ultimately making the case for collaborative, interdisciplinary, and transparent science as a way to operationalize fairness in health equity. 

Difficulty level: Beginner
Duration: 1:06:35
Speaker: : Laura Sikstrom

This lesson contains both a lecture and a tutorial component. The lecture (0:00-20:03 of YouTube video) discusses both the need for intersectional approaches in healthcare as well as the impact of neglecting intersectionality in patient populations. The lecture is followed by a practical tutorial in both Python and R on how to assess intersectional bias in datasets. Links to relevant code and data are found below. 

Difficulty level: Beginner
Duration: 52:26

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. 

Difficulty level: Beginner
Duration: 1:15:12
Speaker: : Abhi Pratap

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.

Difficulty level: Beginner
Duration: 2:24:35

This lecture will provide an overview of neuroimaging techniques and their clinical applications.

Difficulty level: Beginner
Duration: 45:29
Speaker: : Dafna Ben Bashat

This lecture provides an overview of depression (epidemiology and course of the disorder), clinical presentation, somatic co-morbidity, and treatment options.

Difficulty level: Beginner
Duration: 37:51

This lecture provides an overview of some of the essential concepts in neuropharmacology (e.g. receptor binding, agonism, antagonism), an introduction to pharmacodynamics and pharmacokinetics, and an overview of the drug discovery process relative to diseases of the central nervous system. 

Difficulty level: Beginner
Duration: 45:47

This lecture gives an introduction to the types of glial cells, homeostasis (influence of cerebral blood flow and influence on neurons), insulation and protection of axons (myelin sheath; nodes of Ranvier), microglia and reactions of the CNS to injury.

Difficulty level: Beginner
Duration: 40:32

This lesson discusses FAIR principles and methods currently in development for assessing FAIRness.

Difficulty level: Beginner
Duration:
Speaker: : Michel Dumontier

The lecture provides an overview of the core skills and practical solutions required to practice reproducible research.

Difficulty level: Beginner
Duration: 1:25:17
Speaker: : Fernando Perez

This lecture covers FAIR atlases, including their background and construction, as well as how they can be created in line with the FAIR principles.

Difficulty level: Beginner
Duration: 14:24
Speaker: : Heidi Kleven

This lecture covers the biomedical researcher's perspective on FAIR data sharing and the importance of finding better ways to manage large datasets.

Difficulty level: Beginner
Duration: 10:51
Speaker: : Adam Ferguson

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

Difficulty level: Beginner
Duration: 12:26
Speaker: : Camille Maumet

This lecture covers multiple aspects of FAIR neuroscience data: what makes it unique, the challenges to making it FAIR, the importance of overcoming these challenges, and how data governance comes into play.

Difficulty level: Beginner
Duration: 14:56
Speaker: : Damian Eke

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

Difficulty level: Beginner
Duration: 12:33
Speaker: : David Keator

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

Difficulty level: Beginner
Duration: 11:35

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.

Difficulty level: Beginner
Duration: 12:06
Speaker: : Melanie Ganz

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

Difficulty level: Beginner
Duration: 11:20
Speaker: : Elizabeth DuPre

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

Difficulty level: Beginner
Duration: 13:11
Speaker: : Gustav Nilsonne