Tools (1-13 of 13)

1. [Illinois]: Posterior target probability given single-sensory input (delta rule)

   02 Jul 2013 | 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)

2. [Illinois]: Posterior probability of a target given single-sensory input (Bayes')

   Tools | 28 Jun 2013 | 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)

3. [Illinois]: Posterior probability of a target given input for two senses (Bayes')

   Tools | 28 Jun 2013 | 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)

4. [Illinois]: Posterior probability of a target given input for two senses (delta)

   Tools | 28 Jun 2013 | 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)

5. [Illinois]: Posterior probabilities of hypothetical fish classes

   Tools | 28 Jun 2013 | Contributor(s):: Lisa Sproat, Jessica S Johnson, NanoBio Node

   Computes the posterior probabilities of each of three hypothetical fish classes using Bayes' rule

6. [Illinois]: Fish classification using back-propagation

   Tools | 28 Jun 2013 | 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

7. [Illinois]: Sigmoidal unit training with the delta rule

   Tools | 26 Jun 2013 | 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

8. [Illinois]: Predictor-corrector simulation of parabigeminal nucleus neural responses

   Tools | 24 Jun 2013 | Contributor(s):: Lisa Sproat, NanoBio Node, Jessica S Johnson

   Implements a predictor-corrector simulation of the responses of neurons in the parabigeminal nucleus

9. [Illinois]: Midbrain dopamine neuron responses to temporal-difference learning

   Tools | 21 Jun 2013 | Contributor(s):: Lisa Sproat, Jessica S Johnson, NanoBio Node

   Simulates the responses of midbrain dopamine neurons using temporal difference learning

10. [Illinois]: Velocity storage and leakage

    Tools | 04 Jun 2013 | 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

11. Locust-flight central pattern generator

    Tools | 06 Jun 2013 | 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

12. Two-unit oculomotor integrator

    Tools | 04 Jun 2013 | Contributor(s):: Lisa L Sproat, Jessica S Johnson, NanoBio Node

    Implements the two-unit model of the integrator of the oculomotor system

13. [Illinois]: Two leaky integrators in series

    Tools | 31 May 2013 | 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