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

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

This lecture picks up from the previous lesson, providing an overview of neuroimaging techniques and their clinical applications.

Difficulty level: Beginner
Duration: 41:00
Speaker: : Dafna Ben Bashat

This lesson discusses both state-of-the-art detection and prevention schema in working with neurodegenerative diseases. 

Difficulty level: Beginner
Duration: 1:02:29
Speaker: : Nir Giladi

This lesson provides a basic introduction to clinical presentation of schizophrenia, its etiology, and current treatment options.

Difficulty level: Beginner
Duration: 51:49

This lecture focuses on the rationale for employing neuroimaging methods for movement disorders.

Difficulty level: Beginner
Duration: 1:04:04
Speaker: : Bogdan Draganski

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 lesson gives an introductory presentation on how data science can help with scientific reproducibility.

Difficulty level: Beginner
Duration:
Speaker: : Michel Dumontier

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 how to make modeling workflows FAIR by working through a practical example, dissecting the steps within the workflow, and detailing the tools and resources used at each step.

Difficulty level: Beginner
Duration: 15:14

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

In response to a growing need in the neuroscience community for concrete guidance concerning ethically sound and pragmatically feasible open data-sharing, the CONP has created an ‘Ethics Toolkit’. These documents (links found below in 'Documents' section) are meant to help researchers identify key elements in the design and conduct of their projects that are often required for the open sharing of neuroscience data, such as model consent language and approaches to de-identification.

This guidance is the product of extended discussions and careful drafting by the CONP Ethics and Governance Committee that considers both Canadian and international ethical frameworks and research practice. The best way to cite these resources is with their associated Zenodo DOI:

zenodo.5655350

Difficulty level: Beginner
Duration:
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Open Brain Consent is an international initiative aiming to address the challenge of creating participant consent language that will promote the open sharing of data, protect participant privacy, and conform to legal norms and institutional review boards.

Open Brain Consent addresses the aforementioned difficulties in neuroscience research with human participants by collecting:

  • widely acceptable consent forms (with various translations) allowing deposition of anonymized data to public data archives
  • collection of tools/pipelines to help anonymization of neuroimaging data making it ready for sharing
Difficulty level: Beginner
Duration:
Speaker: :