[Illinois]: Neural Systems Modeling Ch 1-5 Master Tool
24 Jul 2013 | Tools | Contributor(s): Jessica S Johnson, Nahil Sobh, NanoBio Node
Combination of all tools used in Chapters 1-5 of Neural Systems Modeling by Anastasio
Neural Systems Modeling Ch10-13 Master Tool
02 Aug 2013 | Tools | Contributor(s): Jessica S Johnson, NanoBio Node
Combination of all tools used in Chapters 10-13 of Neural Systems Modeling by Anastasio
[Illinois]: Neural Systems Modeling Ch 6-9 Master Tool
26 Jul 2013 | Tools | Contributor(s): Jessica S Johnson, NanoBio Node
Combination of all tools used in Chapters 6-9 of Neural Systems Modeling by Anastasio
[Illinois]: Velocity storage and leakage
04 Jun 2013 | Tools | Contributor(s): Lisa L Sproat, Jessica S Johnson, NanoBio Node
Implements the parallel-pathway and positive-feedback models of velocity storage, and the negative-feedback model of velocity leakage
[Illinois]: Midbrain dopamine neuron responses to temporal-difference 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
[Illinois]: Two leaky integrators in series
31 May 2013 | Tools | Contributor(s): Lisa L Sproat, John Feser, Jessica S Johnson, NanoBio Node
Implements a model having two units (leaky integrators) in series, each with recurrent, excitatory self-connections allowing the units to exert positive feedback on themselves
[Illinois]: Avoidance Learn Simulation
20 Jun 2013 | Tools | 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).
Locust-flight 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 locust-flight central pattern generator
[Illinois]: Fish classification using back-propagation
28 Jun 2013 | Tools | Contributor(s): Lisa Sproat, Jessica S Johnson, NanoBio Node
Trains a three-layered network of sigmoidal units using back-propagation to classify fish according to their lengths
[Illinois]: Gill withdrawal habituation
13 May 2013 | Tools | Contributor(s): John Feser, Jessica S Johnson, NanoBio Node
A very simple simulation of habituation of the Aplysia gill withdrawal reflex.
[Illinois]: Kohonen self-organizing map (SOM) algorithm
19 Jun 2013 | Tools | Contributor(s): Bara Saadah, John Feser, NanoBio Node, Jessica S Johnson
This too implements the Kohonen self-organizing map (SOM) algorithm
[Illinois]: Predictor-corrector simulation of parabigeminal nucleus neural responses
24 Jun 2013 | Tools | Contributor(s): Lisa Sproat, NanoBio Node, Jessica S Johnson
Implements a predictor-corrector simulation of the responses of neurons in the parabigeminal nucleus
[Illinois] A Response of a Single Neuron with Positive Feedback
09 Jul 2013 | Tools | Contributor(s): Bara Saadah, Nahil Sobh, Jessica S Johnson, NanoBio Node
This tool stimulates the pulse or step response of a single neuron with positive feedback
[Illinois]: BUTDprobInference
17 Jul 2013 | Tools | Contributor(s): Bara Saadah, Jessica S Johnson, NanoBio Node
This tool stimulates bottom-up/top-down processing in the visual system using probabilistic inference.
[Illinois]: Optimize Connectivity Profile of Activity-Bubble Network
25 Jun 2013 | Tools | Contributor(s): Jessica S Johnson, NanoBio Node
Use genetic algorithm with binary chromosomes to optimize activity-bubble network.
[Illinois]: Avoidance Learn Simulation with 'Call' Neuron
25 Jun 2013 | Tools | 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]: Posterior target probability given single-sensory input (delta rule)
Trains a single sigmoidal unit using the delta rule to estimate posterior target probability given sensory input of one modality (i.e., visual)
[Illinois] KohonenSOM
This tool implements the Kohonen self-organizing map (SOM) algorithm
[Illiniois]: SynchUp
16 Jul 2013 | Tools | Contributor(s): Bara Saadah, Nahil Sobh, AbderRahman N Sobh, Jessica S Johnson, NanoBio Node
This tool computes synchronous updates of autoassociative networks.
[Illinois]: Posterior probability of a target given input for two senses (Bayes')
Computes the posterior probability of a target given sensory input of two modalities (i.e., visual and auditory)
[Illinois]: Perturbative Reinforcement Learning to Develop Distributed Representations
10 Jul 2013 | Tools | Contributor(s): AbderRahman N Sobh, Jessica S Johnson, NanoBio Node
This tool trains three-layered networks of sigmoidal units to associate patterns.
Two-unit oculomotor integrator
Implements the two-unit model of the integrator of the oculomotor system
[Illinois]: Posterior probabilities of hypothetical fish classes
Computes the posterior probabilities of each of three hypothetical fish classes using Bayes' rule
[Illinois]: Posterior probability of a target given single-sensory input (Bayes')
Computes the posterior probability of a target given sensory input of one modality (i.e., visual)
[Illinois]: Posterior probability of a target given input for two senses (delta)
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)