Computational Models of Aphasia

Welcome to Computational Models of Aphasia at the University of California, Irvine's Auditory & Language Neuroscience Lab!
This site draws much of its inspiration from the Aphasia Modeling Project.

This website provides statistical methods for applying the two-step, interactive model of lexical access to picture naming responses (Foygel & Dell, 2000).
Users may enter naming response frequencies to obtain Bayesian point and interval estimates of the S-weight and P-weight parameter values with the best fit, or users may enter S-weight and P-weight parameter values to obtain naming response probabilities.

Fit Data

This website uses a Metropolis-Hastings sampling algorithm to approximate the posterior distribution of weight parameters in a lexical network given data.
Weight parameters are assumed to lie on the interval [0, 0.04].

The sampling procedure can take up to 30 seconds to fit the data.

Please enter the observed counts of each response type:

Correct Semantic Formal Mixed Unrelated Nonword

Fitting Parameters Other Parameters
Random Seed Steps
Jump Sigma .05 Decay
Chains 2 Intrinsic Noise
Samples 50 Activation Noise
Burnin 20 Initial Activation
Jolt Activation
20% Mixed Error Opportunities

Run Model

This website uses numerical approximation of integrals to calculate response probabilities given lexical network parameters.

Please modify the parameters you wish, and select Run!
Note: Weight parameter values of 0.04 simulate the "normal" or "healthy" lexical network, and lower values simulate damage.

Weight Parameters Other Parameters
S-weight Steps
P-weight Decay
Intrinsic Noise
Activation Noise
Initial Activation
Jolt Activation
20% Mixed Error Opportunities


The SP Model Bayesian SP Model


Please contact Grant M. Walker for questions or comments regarding the model or the theory behind it.

Please contact Grant M. Walker for technical questions about the model's implementation, or to report a problem with this web page.

Webmaster: Grant M. Walker <>
Last modified: Wed Aug 23 2017