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Lesson type

Lesson title:

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

Difficulty level: Beginner
Duration: 1:32:17
Speaker: : Shih-Chii Liu
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Presentation of a simulation software for spatial model neurons and their networks designed primarily for GPUs.

Difficulty level: Beginner
Duration: 21:15
Speaker: : Tadashi Yamazaki
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Presentation of past and present neurocomputing approaches and hybrid analog/digital circuits that directly emulate the properties of neurons and synapses.

Difficulty level: Beginner
Duration: 41:57
Speaker: : Giacomo Indiveri
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Presentation of the Brian neural simulator, where models are defined directly by their mathematical equations and code is automatically generated for each specific target.

Difficulty level: Beginner
Duration: 20:39
Speaker: : Giacomo Indiveri
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The lecture covers a brief introduction to neuromorphic engineering, some of the neuromorphic networks that the speaker has developed, and their potential applications, particularly in machine learning.

Difficulty level: Intermediate
Duration: 19:57
Lesson title:

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.

Difficulty level: Beginner
Duration: 1:13:16
Speaker: : Clay Reid
Lesson title:

How does the brain learn? This lecture discusses the roles of development and adult plasticity in shaping functional connectivity.

Difficulty level: Beginner
Duration: 1:08:45
Speaker: : Clay Reid