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## [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)

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#### Abstract

FIGURE 9.11 depicts a single, sigmoidal unit used to simulate a bisensory neuron in the superior colliculus. The unit y receives inputs X1 and x2 and a bias b. The weight matrix V is a row vector containing the weights of the three connections to y from x1, x2, and b. The unit computes the weighted sum of its inputs and passes the result through the sigmoidal squashing function (see Chapter 6). Inputs x1 and x2 could represent visual and auditory inputs, respectively, and the bias could represent constant influences on the firing rate of the collicular neuron.

This tool is built from the MATLAB scripts for Tutorial on Neural Systems Modeling by Thomas J. Anastasio.

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