This talk presents state-of-the-art methods for ensuring data privacy with a particular focus on medical data sharing across multiple organizations.
This lecture talks about the usage of knowledge graphs in hospitals and related challenges of semantic interoperability.
In this lesson, users will learn about human brain signals as measured by electroencephalography (EEG), as well as associated neural signatures such as steady state visually evoked potentials (SSVEPs) and alpha oscillations.
This is a continuation of the talk on the cellular mechanisms of neuronal communication, this time at the level of brain microcircuits and associated global signals like those measureable by electroencephalography (EEG). This lecture also discusses EEG biomarkers in mental health disorders, and how those cortical signatures may be simulated digitally.
This lecture gives an overview of how to prepare and preprocess neuroimaging (EEG/MEG) data for use in TVB.
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.
This lesson gives an overview of the Brainstorm package for analyzing extracellular electrophysiology, including preprocessing, spike sorting, trial alignment, and spectrotemporal decomposition.
This lesson provides an overview of the CaImAn package, as well as a demonstration of usage with NWB.
This lesson gives an overview of the SpikeInterface package, including demonstration of data loading, preprocessing, spike sorting, and comparison of spike sorters.
In this lesson, users will learn about the NWBWidgets package, including coverage of different data types, and information for building custom widgets within this framework.