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 lecture provides an introduction to optogenetics, a biological technique to control the activity of neurons or other cell types with light.
This primer on optogenetics primer discusses how to manipulate neuronal populations with light at millisecond resolution and offers possible applications such as curing the blind and "playing the piano" with cortical neurons.
This lecture covers visualizing extracellular neurotransmitter dynamics
This lecture consists of the second half of the introduction to signal transduction, here focusing on cell receptors and signalling cascades.
In this lesson, you will learn about GABAergic interneurons and local inhibition on the circuit level.
The "connectome" is a term, coined in the past decade, that has been used to describe more than one phenomenon in neuroscience. This lecture explains the basics of structural connections at the micro-, meso- and macroscopic scales.
EyeWire is a game to map the brain. Players are challenged to map branches of a neuron from one side of a cube to the other in a 3D puzzle. Players scroll through the cube and reconstruct neurons with the help of an artificial intelligence algorithm developed at Seung Lab in Princeton University. EyeWire gameplay advances neuroscience by helping researchers discover how neurons connect to process visual information.
This module explains how neurons come together to create the networks that give rise to our thoughts. The totality of our neurons and their connection is called our connectome. Learn how this connectome changes as we learn, and computes information.
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.