This code implements the simulation results reported in:

M. W. Spratling (2016) A neural implementation of Bayesian inference based on predictive coding. Connection Science, 28(4):346-83.

Please cite this paper if this code is used in, or to motivate, any publications.

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USAGE

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This code was tested with MATLAB Version 8.3.0.532 (R2014a).

Some functions make use of the nansuite toolbox by Jan Glaescher, available at http://www.mathworks.com/matlabcentral/fileexchange/6837. These functions should thus be installed somewhere on your matlab path. Alternatively, the Statistics Toolbox can be used.

To use this software:

    start matlab 
    move to the directory containing this code 
    run one of the functions with the name pcbc_prob_*

Each of the pcbc_prob_* functions runs an experiment reported in the above publication. The following table gives details of which MATLAB function produces each figure in this article.

Figure	MATLAB Function
2b-e	pcbc_prob_1gaussian (Figs. 1, 2, 4, & 5)
3	pcbc_prob_1gaussian_width_height (Figs. 1, 2, 5, 6, 11, 12, 15 & 16)
4	pcbc_prob_Ngaussian
5b-e	pcbc_prob_1gaussian_prior (Figs. 1 to 4)
6	pcbc_prob_2integrate (Figs. 1, 2, 5, & 6)
7	pcbc_prob_3integrate (Figs. 1, 2, 5, & 6)
8	pcbc_prob_2integrate_prior (Figs. 1, 2, 5, & 6)
9	pcbc_prob_2integrate (Figs. 3 & 4)
10a	pcbc_prob_2integrate_segregate (Fig. 9)
10b	as Fig8a but requires value of "stdInputs" to be modified in the code
11	pcbc_prob_3basis
12	pcbc_prob_4basis (Figs. 1-4, 8-11)
14a-g	pcbc_prob_image_orientation (Figs. 1-7)
14h-i	pcbc_prob_image_orientation_prior (Figs. 1-2)
15a	pcbc_prob_image_orientation (Fig. 8)
15b	pcbc_prob_image_orientation(1) (Fig. 8)
Result not shown in paper:
sec 3.5	pcbc_prob_4basis_hierarchical.m