This lecture covers visualizing extracellular neurotransmitter dynamics
This lecture covers the linking neuronal activity to behavior using AI-based online detection.
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 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.
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.
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.
This brief video provides an introduction to the third session of INCF's Neuroinformatics Assembly 2023, focusing on how to streamling cross-platform data integration in a neuroscientific context.
This talk describes the challenges to sustained operability and success of consortia, why many of these groups flounder after just a few years, and what steps can be taken to mitigate such outcomes.
This talk discusses the BRAIN Initiative Cell Atlas Network (BICAN), taking a look specifically at how this network approaches the design, development, and maintenance of specimen and sequencing library portals.
In this talk, you will hear about the challenges and costs of being FAIR in the many scientific fields, as well as opportunities to transform the ecology of the academic crediting system.
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 talk describes how to use DataLad for your data management and curation techniques when dealing with animal datasets, which often contain several disparate types of data, including MRI, microscopy, histology, electrocorticography, and behavioral measurements.
This brief talk covers an analysis technique for multi-band, multi-echo fMRI data, applying a denoising framework which can be used in an automated pipeline.
This lesson gives a quick introduction to the rest of this course, Research Workflows for Collaborative Neuroscience.
This lesson provides an overview of how to conceptualize, design, implement, and maintain neuroscientific pipelines in via the cloud-based computational reproducibility platform Code Ocean.
This lesson provides an overview of how to construct computational pipelines for neurophysiological data using DataJoint.
This talk describes approaches to maintaining integrated workflows and data management schema, taking advantage of the many open source, collaborative platforms already existing.