This lecture provides an introduction to the study of eye-tracking in humans. 

This lecture provides an introduction to the application of genetic testing in neurodevelopmental disorders.

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.

This lesson continues with the second workshop on reproducible science, focusing on additional open source tools for researchers and data scientists, such as the R programming language for data science, as well as associated tools like RStudio and R Markdown. Additionally, users are introduced to Python and iPython notebooks, Google Colab, and are given hands-on tutorials on how to create a Binder environment, as well as various containers in Docker and Singularity.

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. 

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. 

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.

Maximize Your Research With Cloud Workspaces is a talk aimed at researchers who are looking for innovative ways to set up and execute their life science data analyses in a collaborative, extensible, open-source cloud environment. This panel discussion is brought to you by MetaCell and scientists from leading universities who share their experiences of advanced analysis and collaborative learning through the Cloud.

In this lesson, you will learn about data management within the Open Data Commons (ODC) framework, and in particular, how Spinal Cord Injury (SCI) data is stored, shared, and published. You will also hear about Frictionless Data, an open-source toolkit aimed at simplifying the data experience. 

This lesson provides an introduction the International Neuroinformatics Coordinating Facility (INCF), its mission towards FAIR neuroscience, and future directions. 

This talk describes the relevance and power of using brain atlases as part of one's data integration pipeline. 

In this talk, you will learn about the standardization schema for data formats among two of the US BRAIN Initiative networks: the Cell Census Network (BICCN) and the Cell Atlas Network (BICAN). 

This talk discusses what are usually considered successful outcomes of scientific research consortia, and how those outcomes can be translated into lasting impacts. 

This final lesson of the course consists of the panel discussion for Streamlining Cross-Platform Data Integration session during the first day of INCF's Neuroinformatics Assembly 2023. 

This brief talk goes into work being done at The Alan Turing Institute to solve real-world challenges and democratize computer vision methods to support interdisciplinary and international researchers. 

This brief talk describes the challenge of global data sharing and governance, as well as efforts of the the Brain Research International Data Governance & Exchange (BRIDGE) to develop ready-made workflows to share data globally. 

This lesson is the first part of a three-part series on the development of neuroinformatic infrastructure to ensure compliance with European data privacy standards and laws. 

In this hands-on session, you will learn how to explore and work with DataLad datasets, containers, and structures using Jupyter notebooks.