Overview of Day 2 of this course.
This talk compares various sensors and resolutions for in vivo neural recordings.
This hands-on tutorial explains how to run your own Minion session in the MetaCell cloud using jupityr notebooks.
In this hands-on analysis tutorial, users will mimic a kernel crash and learn the steps to restore inputs in such a case.
This lesson will go through how to extract cells from video that has been cleaned of background noise and motion.
This final hands-on analysis tutorial walks users through the last visualization steps in the cellular data.
This lecture covers visualizing extracellular neurotransmitter dynamics
This lecture covers infrared LED oblique illumination for studying neuronal circuits in in vitro block-preparations of the spinal cord and brain stem.
This lecture provides an introduction to the study of eye-tracking in humans.
This lecture covers the application of diffusion MRI for clinical and preclinical studies.
This lecture provides an introduction to the application of genetic testing in neurodevelopmental disorders.
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 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 hands-on tutorial walks you through DataJoint platform, highlighting features and schema which can be used to build robost neuroscientific pipelines.
In this hands-on session, you will learn how to explore and work with DataLad datasets, containers, and structures using Jupyter notebooks.
This video shows how to use the brainlife.io interface to edit the participants' info file. This file is the ParticipantInfo.json file of the Brain Imaging Data Structure (BIDS).
This quick video presents some of the various visualizers available on brainlife.io
This video demonstrates each required step for preprocessing T1w anatomical data in brainlife.io.
This lecture focuses on how the immune system can target and attack the nervous system to produce autoimmune responses that may result in diseases such as multiple sclerosis, neuromyelitis, and lupus cerebritis manifested by motor, sensory, and cognitive impairments. Despite the fact that the brain is an immune-privileged site, autoreactive lymphocytes producing proinflammatory cytokines can cause active brain inflammation, leading to myelin and axonal loss.