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

Difficulty level: Beginner
Duration:
Speaker: : Michel Dumontier

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

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

Difficulty level: Beginner
Duration:
Speaker: : Michel Dumontier

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

The state of the field regarding the diagnosis and treatment of major depressive disorder (MDD) is discussed. Current challenges and opportunities facing the research and clinical communities are outlined, including appropriate quantitative and qualitative analyses of the heterogeneity of biological, social, and psychiatric factors which may contribute to MDD.

Difficulty level: Beginner
Duration: 1:29:28

This lesson delves into the opportunities and challenges of telepsychiatry. While novel digital approaches to clinical research and care have the potential to improve and accelerate patient outcomes, researchers and care providers must consider new population factors, such as digital disparity. 

Difficulty level: Beginner
Duration: 1:20:28
Speaker: : Abhi Pratap

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 provides an introduction to the principal of anatomical organization of neural systems in the human brain and spinal cord that mediate sensation, integrate signals, and motivate behavior.

Difficulty level: Beginner
Duration: 59:57

This lecture focuses on the comprehension of nociception and pain sensation, highlighting how the somatosensory system and different molecular partners are involved in nociception.

Difficulty level: Beginner
Duration: 28:09
Speaker: : Serena Quarta

In this lesson, you will learn about how genetics can contribute to our understanding of psychiatric phenotypes.

Difficulty level: Beginner
Duration: 55:15
Speaker: : Sven Cichon

In this lesson, you will learn about the current challenges facing the integration of machine learning and neuroscience. 

Difficulty level: Beginner
Duration: 5:42
Speaker: : Dan Goodman

This lesson provides a brief overview of the Python programming language, with an emphasis on tools relevant to data scientists.

Difficulty level: Beginner
Duration: 1:16:36
Speaker: : Tal Yarkoni

This lecture covers the description and brief history of data science and its use in neuroinformatics.

Difficulty level: Beginner
Duration: 11:15
Speaker: : Ariel Rokem

This lesson provides an overview of self-supervision as it relates to neural data tasks and the Mine Your Own vieW (MYOW) approach.

Difficulty level: Beginner
Duration: 25:50
Speaker: : Eva Dyer

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 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 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:
Speaker: :