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.
Following the previous lesson on neuronal structure, this lesson discusses neuronal function, particularly focusing on spike triggering and propogation.
This lesson introduces the practical exercises which accompany the previous lessons on animal and human connectomes in the brain and nervous system.
This lesson discusses a gripping neuroscientific question: why have neurons developed the discrete action potential, or spike, as a principle method of communication?
This lecture covers NeuronUnit, a library that builds upon SciUnit and integrates with several existing neuroinformatics resources to support validating single-neuron models using data gathered by neurophysiologists.
This lesson provides an introduction to the NeuroElectro project, which aims to organize information on cellular neurophysiology.
This lesson covers simultaneously recorded neurons in non-human primates coordinate their spiking activity in a sequential manner that mirrors the dominant wave propagation directions of the local field potentials.
This talk covers statistical analysis of spike train data, the modeling approach GLM, and the problem of assessing neural synchrony.
This talk covers statistical methods for characterizing neural population responses and extracting structure from high-dimensional neural data.
This presentation discusses research aimed at understanding the activity of single neurons and populations of neurons in the visual system.
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.