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.

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 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.

While the previous lesson in the Neuro4ML course dealt with the mechanisms involved in individual synapses, this lesson discusses how synapses and their neurons' firing patterns may change over time. 

In this lesson, you will learn about how machine learners and computational neuroscientists design and build models of neuronal synapses. 

This is an introductory lecture on whole-brain modelling, delving into the various spatial scales of neuroscience, neural population models, and whole-brain modelling. Additionally, the clinical applications of building and testing such models are characterized.