This lecture describes how to build research workflows, including a demonstrate using DataJoint Elements to build data pipelines.
This lecture discusses how FAIR practices affect personalized data models, including workflows, challenges, and how to improve these practices.
This lecture covers how to make modeling workflows FAIR by working through a practical example, dissecting the steps within the workflow, and detailing the tools and resources used at each step.
Serving as good refresher, this lesson explains the maths and logic concepts that are important for programmers to understand, including sets, propositional logic, conditional statements, and more.
This compilation is courtesy of freeCodeCamp.
This lesson provides a useful refresher which will facilitate the use of Matlab, Octave, and various matrix-manipulation and machine-learning software.
This lesson was created by RootMath.
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 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 lesson discusses a gripping neuroscientific question: why have neurons developed the discrete action potential, or spike, as a principle method of communication?
This lesson provides an overview of Neurodata Without Borders (NWB), an ecosystem for neurophysiology data standardization. The lecture also introduces some NWB-enabled tools.
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.