As the previous lesson of this course described how researchers acquire neural data, this lesson will discuss how to go about interpreting and analysing the data.
In this lesson you will learn about the motivation behind manipulating neural activity, and what forms that may take in various experimental designs.
In this lesson, you will learn about one particular aspect of decision making: reaction times. In other words, how long does it take to take a decision based on a stream of information arriving continuously over time?
In this lesson, you will hear about some of the open issues in the field of neuroscience, as well as a discussion about whether neuroscience works, and how can we know?
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 introduction to modeling single neurons, as well as stability analysis of neural models.
This lesson continues a thorough description of the concepts, theories, and methods involved in the modeling of single neurons.
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.