
[Illinois] MCB 529 BRH Reproductive Rhythms
07 Jan 2014  Online Presentations  Contributor(s): Megan Mahoney, Martha U. Gillette
http://nanohub.org/resources/20121

[Illinois] MCB 529 BRH Biological Rhythms in Health and Disease
30 Dec 2013  Courses  Contributor(s): Martha U. Gillette
Our major research thrusts are to understand: 1) signals that engage the circadian clockwork in the brain, 2) subcellular microenvironments that shape neuronal dendrites in development and...
http://nanohub.org/resources/20114

[Illinois] MCB 529 BRH Nocturnal and Diurnal Adaptations
30 Dec 2013  Online Presentations  Contributor(s): Rhanor Gillette, Martha U. Gillette
http://nanohub.org/resources/20117

[Illinois] MCB 529 BRH Circadian Control of Liver Function
30 Dec 2013  Online Presentations  Contributor(s): Shelley Tischkau, Martha U. Gillette
http://nanohub.org/resources/20118

[Illinois] MCB 529 BRH Drugs of Abuse and Circadian Rhythms
30 Dec 2013  Online Presentations  Contributor(s): Joshua M Gulley, Martha U. Gillette
http://nanohub.org/resources/20119

[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.
http://nanohub.org/resources/18834

[Illinois] MCB 493 Lecture 14: Future Directions in Neural Systems Modeling
30 Oct 2013  Online Presentations  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
http://nanohub.org/resources/18948

[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 handson experience in using computers to model neural systems. A neural system is a system of interconnected neural elements, or units....
http://nanohub.org/resources/16704

[Illinois] MCB 493 Lecture 11: TemporalDifference Learning and Reward Prediction
29 Oct 2013  Online Presentations  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.
http://nanohub.org/resources/18947

[Illinois]: Posterior target probability given singlesensory input (delta rule)
28 Jun 2013  Tools  Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node
Trains a single sigmoidal unit using the delta rule to estimate posterior target probability given sensory input of one modality (i.e., visual)
http://nanohub.org/resources/unisensorydelta

[Illinois]: Posterior probability of a target given singlesensory input (Bayes')
28 Jun 2013  Tools  Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node
Computes the posterior probability of a target given sensory input of one modality (i.e., visual)
http://nanohub.org/resources/unisensorybayes

[Illinois]: Posterior probability of a target given input for two senses (Bayes')
28 Jun 2013  Tools  Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node
Computes the posterior probability of a target given sensory input of two modalities (i.e., visual and auditory)
http://nanohub.org/resources/bisensorybayes

[Illinois]: Posterior probability of a target given input for two senses (delta)
28 Jun 2013  Tools  Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node
Trains a single sigmoidal unit using the delta rule to estimate posterior target probability given sensory input of two modalities (i.e., visual and auditory)
http://nanohub.org/resources/bisensorydelta

[Illinois]: Posterior probabilities of hypothetical fish classes
28 Jun 2013  Tools  Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node
Computes the posterior probabilities of each of three hypothetical fish classes using Bayes' rule
http://nanohub.org/resources/fishbayesrule

[Illinois]: Fish classification using backpropagation
28 Jun 2013  Tools  Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node
Trains a threelayered network of sigmoidal units using backpropagation to classify fish according to their lengths
http://nanohub.org/resources/fishbackprop

[Illinois]: Sigmoidal unit training with the delta rule
26 Jun 2013  Tools  Contributor(s): Lisa Sproat, NanoBio Node, Jessica S Johnson
Uses the delta rule to train a single sigmoidal unit with feedback to simulate the responses of neurons in the parabigeminal nucleus
http://nanohub.org/resources/pbndeltarule

[Illinois]: Predictorcorrector simulation of parabigeminal nucleus neural responses
24 Jun 2013  Tools  Contributor(s): Lisa Sproat, NanoBio Node, Jessica S Johnson
Implements a predictorcorrector simulation of the responses of neurons in the parabigeminal nucleus
http://nanohub.org/resources/pbnpredict

[Illinois]: Midbrain dopamine neuron responses to temporaldifference learning
21 Jun 2013  Tools  Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node
Simulates the responses of midbrain dopamine neurons using temporal difference learning
http://nanohub.org/resources/midbraindopamin

[Illinois]: Velocity storage and leakage
04 Jun 2013  Tools  Contributor(s): Lisa L Sproat, Jessica S Johnson, NanoBio Node
Implements the parallelpathway and positivefeedback models of velocity storage, and the negativefeedback model of velocity leakage
http://nanohub.org/resources/velstoreleak

Locustflight central pattern generator
06 Jun 2013  Tools  Contributor(s): Lisa L Sproat, NanoBio Node, Jessica S Johnson
Implements a linear version of Wilson's model of the locustflight central pattern generator
http://nanohub.org/resources/wilsoncpg