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[Illinois] MCB 493 Neural Systems Modeling
29 Oct 2013 | Courses | Contributor(s): Thomas J. Anastasio
The purpose of this independent study is to give students hands-on experience in using computers to model neural systems. A neural system is a system of interconnected neural elements, or units. Students will use existing computer programs which will simulate real neural systems. They will...
[Illinois] MCB 493 Lecture 9: Probability Estimation and Supervised Learning
30 Oct 2013 | Online Presentations | Contributor(s): Thomas J. Anastasio
Supervised learning algorithms can train neural units and networks to estimate probabilities and simulate the responses of neurons to multisensory stimulation.
[Illinois] MCB 493 Lecture 8: Information Transmission and Unsupervised Learning
29 Oct 2013 | Online Presentations | Contributor(s): Thomas J. Anastasio
Unsupervised learning algorithms can train neural networks to increase the amount of information they contain about their inputs and simulate the properties of sensory neurons.
[Illinois] MCB 493 Lecture 7: Reinforcement Learning and Associative Conditioning
Reinforcement learning algorithms can simulate certain types of associative conditioning and train neural networks to form non-uniform distributed representations.
[Illinois] MCB 493 Lecture 6: Supervised Learning and Non-Uniform Representations
Supervised learning algorithms can train neural networks to associate patterns and simulate the non-uniform distributed representations found in many brain regions.
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