This lecture provides an introductory overview of some of the most important concepts in software engineering.

This lecture covers modeling the neuron in silicon, modeling vision and audition, and sensory fusion using a deep network. 

This lesson gives an overview of past and present neurocomputing approaches and hybrid analog/digital circuits that directly emulate the properties of neurons and synapses.

Presentation of the Brian neural simulator, where models are defined directly by their mathematical equations and code is automatically generated for each specific target.

This talk describes the NIH-funded SPARC Data Structure, and how this project navigates ontology development while keeping in mind the FAIR science principles. 

This lecture covers structured data, databases, federating neuroscience-relevant databases, and ontologies. 

This lecture covers FAIR atlases, including their background and construction, as well as how they can be created in line with the FAIR principles.

This lecture covers the description and characterization of an input-output relationship in a information-theoretic context. 

This lesson is part 1 of 2 of a tutorial on statistical models for neural data.

This lesson is part 2 of 2 of a tutorial on statistical models for neural data.

From the retina to the superior colliculus, the lateral geniculate nucleus into primary visual cortex and beyond, this lecture gives a tour of the mammalian visual system highlighting the Nobel-prize winning discoveries of Hubel & Wiesel.

From Universal Turing Machines to McCulloch-Pitts and Hopfield associative memory networks, this lecture explains what is meant by computation.

In this lesson you will learn about ion channels and the movement of ions across the cell membrane, one of the key mechanisms underlying neuronal communication. 

This lesson provides an overview of how to construct computational pipelines for neurophysiological data using DataJoint.

This lesson covers the ionic basis of the action potential, including the Hodgkin-Huxley model. 

This lesson provides an introduction to the myriad forms of cellular mechanisms whicn underpin healthy brain function and communication. 

In this lesson you will learn about the ionic basis of the action potential, including the Hodgkin-Huxley model. 

This lesson provides an introduction to the course Cellular Mechanisms of Brain Function.

This lesson covers membrane potential of neurons, and how parameters around this potential have direct consequences on cellular communication at both the individual and population level. 

This lesson covers the spatiotemporal dynamics of the membrane potential.