
[Illinois] MCB 493 Lecture 13: PredictorCorrector Models and Probabilistic Inference
30 Oct 2013   Contributor(s):: Thomas J. Anastasio

[Illinois] MCB 493 Lecture 10: Time Series Learning and Nonlinear Signal Processing
30 Oct 2013   Contributor(s):: Thomas J. Anastasio

[Illinois] MCB 493 Lecture 14: Future Directions in Neural Systems Modeling
30 Oct 2013   Contributor(s):: Thomas J. Anastasio
In the future, neural systems models will become increasingly complex and will span levels from molecular interactions within neurons to interactions between networks

[Illinois] MCB 493 Lecture 9: Probability Estimation and Supervised Learning
30 Oct 2013   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 11: TemporalDifference Learning and Reward Prediction
29 Oct 2013   Contributor(s):: Thomas J. Anastasio
Temporaldifference learning can train neural networks to estimate the future value of a current state and simulate the responses of neurons involved in reward processing.

Neural Systems Modeling Ch1013 Master Tool
02 Aug 2013   Contributor(s):: Jessica S Johnson, NanoBio Node
Combination of all tools used in Chapters 1013 of Neural Systems Modeling by Anastasio

[Illinois]: Neural Systems Modeling Ch 69 Master Tool
26 Jul 2013   Contributor(s):: Jessica S Johnson, NanoBio Node
Combination of all tools used in Chapters 69 of Neural Systems Modeling by Anastasio

[Illinois]: Error Gradient Estimations Due to Parallel Perturbation of Weights
07 Jul 2013   Contributor(s):: AbderRahman N Sobh, Jessica S Johnson, NanoBio Node
This tool trains twolayered networks of sigmoidal units to associate patterns using simultaneous perturbation of weights.

[Illinois]: Perturbative Reinforcement Learning to Develop Distributed Representations
10 Jul 2013   Contributor(s):: AbderRahman N Sobh, Jessica S Johnson, NanoBio Node
This tool trains threelayered networks of sigmoidal units to associate patterns.

[Illinois]: Perturbative Reinforcement Learning Using Directed Drift
10 Jul 2013   Contributor(s):: AbderRahman N Sobh, Jessica S Johnson, NanoBio Node
This tool trains twolayered networks of sigmoidal units to associate patterns using a realvalued adaptation of the directed drift algorithm.

[Illinois]: Error Gradient Estimations Due to Perturbation of One Weight at a Time
29 Jun 2013   Contributor(s):: AbderRahman N Sobh, Jessica S Johnson, NanoBio Node
This tool trains twolayered networks of sigmoidal units to associate patterns using perturbation of one weight at a time.

[Illinois]: Avoidance Learn Simulation with 'Call' Neuron
25 Jun 2013   Contributor(s):: AbderRahman N Sobh, NanoBio Node, Jessica S Johnson
This script simulates avoidance learning as a reinforcement learning with two upper motoneurons (sumo and fumo) and one "call" neuron.

[Illinois]: Avoidance Learn Simulation
20 Jun 2013   Contributor(s):: AbderRahman N Sobh, NanoBio Node, Jessica S Johnson
This script simulates avoidance conditioning as reinforcement learning with two upper motoneurons (SUMO and FUMO).

[Illinois]: Optimize Connectivity Profile of ActivityBubble Network
25 Jun 2013   Contributor(s):: Jessica S Johnson, NanoBio Node
Use genetic algorithm with binary chromosomes to optimize activitybubble network.