This lecture covers an introduction to neuroinformatics and its subfields, the content of the short course and future neuroinformatics applications.
This lecture covers modeling the neuron in silicon, modeling vision and audition and sensory fusion using a deep network.
Presentation 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 covers structured data, databases, federating neuroscience-relevant databases, ontologies.