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Tags: neuroscience

Resources (1-20 of 23)

  1. [Illinois]: Posterior target probability given single-sensory 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

  2. [Illinois]: Posterior probability of a target given single-sensory 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

  3. [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

  4. [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

  5. [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

  6. [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

    http://nanohub.org/resources/fishbackprop

  7. [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

  8. [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

    http://nanohub.org/resources/pbnpredict

  9. [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

    http://nanohub.org/resources/midbraindopamin

  10. [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

    http://nanohub.org/resources/velstoreleak

  11. 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

    http://nanohub.org/resources/wilsoncpg

  12. Two-unit oculomotor integrator

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

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

    http://nanohub.org/resources/twounitintegrat

  13. [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

    http://nanohub.org/resources/twoleakseries

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