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.
How does the brain learn? This lecture discusses the roles of development and adult plasticity in shaping functional connectivity.
This lesson goes into the mechanisms behind changes in synaptic function created by learning.