In this lesson you will learn about fundamental neural phenomena such as oscillations and bursting, and the effects these have on cortical networks. 

This lesson continues discussing properties of neural oscillations and networks. 

In this lecture, you will learn about rules governing coupled oscillators, neural synchrony in networks, and theoretical assumptions underlying current understanding.

This lesson provides a continued discussion and characterization of coupled oscillators. 

This lesson gives an overview of modeling neurons based on firing rate. 

This lesson characterizes the pattern generation observed in visual system hallucinations.

This lesson gives an introduction to stability analysis of neural models.

This lesson continues from the previous lectures, providing introduction to stability analysis of neural models.

In this lesson, you will learn about phenomena of neural populations such as synchrony, oscillations, and bursting.

This lesson continues from the previous lecture, giving an overview of various neural phenomena such as oscillations and bursting. 

This lesson provides more context around weakly coupled oscillators.

This lesson builds upon previous lectures in this series, providing an overview of coupled oscillators.

In this lesson, you will learn about neuronal models based on their spike rate. 

In this lesson, you will learn about neural activity pattern generation in visual system hallucinations.

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.

This lesson describes how DataLad allows you to track and mange both your data and analysis code, thereby facilitating reliable, reproducible, and shareable research.

This lecture provides an introduction to the Brain Imaging Data Structure (BIDS), a standard for organizing human neuroimaging datasets.

This tutorial covers the fundamentals of collaborating with Git and GitHub.

This lecture and tutorial focuses on measuring human functional brain networks, as well as how to account for inherent variability within those networks. 

This lesson provides an overview of Jupyter notebooks, Jupyter lab, and Binder, as well as their applications within the field of neuroimaging, particularly when it comes to the writing phase of your research.