In this lecture, the speaker demonstrates Neurokernel's module interfacing feature by using it to integrate independently developed models of olfactory and vision LPUs based upon experimentally obtained connectivity information.
In this talk the speakers will give a brief introduction of the Fenix Infrastructure and Service Offering, before focusing on Data Safety. The speaker will take the participants through the ETHZ-CSCS offering for EBRAINS and all the HBP Communities highlighting the Infrastructure role in a service implementation in respect of Security. Particular attention will be on showing what tools ETHZ-CSCS provides to a Portal/Service provider such as EBRAINS, MIP/HIP, TVB, NRP amongst others. Finally there will be given a quick glimpse into the future and the role that “multi-tenancy” will play.
This lecture goes into detailed description of how to process workflows in the virtual research environment (VRE), including approaches for standardization, metadata, containerization, and constructing and maintaining scientific pipelines.
This video will document the process of creating a pipeline rule for batch processing on brainlife.
This video will document the process of launching a Jupyter Notebook for group-level analyses directly from brainlife.
This lecture introduces you to the basics of the Amazon Web Services public cloud. It covers the fundamentals of cloud computing and goes through both the motivations and processes involved in moving your research computing to the cloud.
This lesson provides an overview of the current status in the field of neuroscientific ontologies, presenting examples of data organization and standards, particularly from neuroimaging and electrophysiology.
This lesson continues from part one of the lecture Ontologies, Databases, and Standards, diving deeper into a description of ontologies and knowledg graphs.
This lecture focuses on ontologies for clinical neurosciences.
Learn how to create a standard extracellular electrophysiology dataset in NWB using Python.
Learn how to create a standard calcium imaging dataset in NWB using Python.
In this tutorial, you will learn how to create a standard intracellular electrophysiology dataset in NWB using Python.
In this tutorial, you will learn how to use the icephys-metadata extension to enter meta-data detailing your experimental paradigm.
This lesson provides instructions on how to build and share extensions in NWB.
Learn how to build custom APIs for extension.
This lesson provides instruction on advanced writing strategies in HDF5 that are accessible through PyNWB.
In this tutorial, users learn how to create a standard extracellular electrophysiology dataset in NWB using MATLAB.
Learn how to create a standard calcium imaging dataset in NWB using MATLAB.
Learn how to create a standard intracellular electrophysiology dataset in NWB.
This lesson provides a tutorial on how to handle writing very large data in MatNWB.