You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: DEM_spatial_deconvolution.m
    path of file: ./repos/spm/toolbox/DEM
    
    the code of the file until where you have to start completion: function DEM_spatial_deconvolution
% FORMAT DEM_spatial_deconvolution
%--------------------------------------------------------------------------
% This (toy) demonstration routine illustrates spatiotemporal
% deconvolution of regional responses from imaging time-series.  The
% generative model assumes the data are generated by a small number of
% anatomical parcels that are smoothly displaced. The resulting data are
% then convolved spatially with a smoothly varying spatial kernel. The smooth
% displacement and dispersion are modelled in the usual way using discrete
% cosine basis set.  The model operates on reduced data features, using
% the eigenvariates of the original time-series - this supplements the
% implicit deconvolution with eigen-de-noising.  The ensuing estimates are
% anatomically informed because the generative model stars with a parcellation

    
function DEM_spatial_deconvolution
% FORMAT DEM_spatial_deconvolution
%--------------------------------------------------------------------------
% This (toy) demonstration routine illustrates spatiotemporal
% deconvolution of regional responses from imaging time-series.  The
% generative model assumes the data are generated by a small number of
% anatomical parcels that are smoothly displaced. The resulting data are
% then convolved spatially with a smoothly varying spatial kernel. The smooth
% displacement and dispersion are modelled in the usual way using discrete
% cosine basis set.  The model operates on reduced data features, using
% the eigenvariates of the original time-series - this supplements the
% implicit deconvolution with eigen-de-noising.  The ensuing estimates are
% anatomically informed because the generative model stars with a parcellation
% scheme.
%__________________________________________________________________________
 
% Karl Friston
% Copyright (C) 2008-2022 Wellcome Centre for Human Neuroimaging
 
 
% parcellation scheme (U) (make an atlas on the fly)
%==========================================================================
rng('default')

ATLAS = spm_conv(randn(64,16),6,6);
AP    = ATLAS;
a     = spm_vec(ATLAS);
[q,x] = hist(a,4);
A     = zeros(size(a));
for i = 1:length(x)
    A(:,i) = a < x(i);
    j      = find(A(:,i));
    a(j)   = Inf;
    AP(j)  = i;
end