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: spm_dem_search_trajectory.m
    path of file: ./repos/bspm/thirdparty/spm12/toolbox/DEM
    
    the code of the file until where you have to start completion: function spm_dem_search_trajectory(DEM)
% plots visual search in extrinsic and intrinsic coordinates
% FORMAT spm_dem_search_trajectory(DEM)
%
% DEM - {DEM} structures from visual search simulations
%
% hidden causes and states
%==========================================================================
% x    - hidden states:
%   o(1) - oculomotor angle
%   o(2) - oculomotor angle
%   x(1) - relative amplitude of visual hypothesis 1
%   x(2) - relative amplitude of visual hypothesis 2
%   x(3) - ...
%
% v    - hidden causes
%
% g    - sensations:
%   g(1) - oculomotor angle (proprioception - x)
%   g(2) - oculomotor angle (proprioception - y)
%   g(3) - retinal input - channel 1
%   g(4) - retinal input - channel 2
%   g(5) - ...
%__________________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
 
% Karl Friston
% $Id: spm_dem_search_trajectory.m 4595 2011-12-19 13:06:22Z karl $
 
 
% Preliminaries
%--------------------------------------------------------------------------
clf, global STIM
N  = length(DEM);
S  = spm_read_vols(STIM.U);
 
% Stimulus
%======================================================================
Dx = STIM.U.dim(1)/2;
Dy = STIM.U.dim(2)/2;
a  = [];
q  = [];
c  = [];

subplot(2,2,1); hold off
image((S + 1)*32), axis image, hold on
 
for i = 1:N
    
    % i-th saccade - position
    %----------------------------------------------------------------------
    pU = DEM{i}.pU.x{1}(1:2,:)*16;

    
function spm_dem_search_trajectory(DEM)
% plots visual search in extrinsic and intrinsic coordinates
% FORMAT spm_dem_search_trajectory(DEM)
%
% DEM - {DEM} structures from visual search simulations
%
% hidden causes and states
%==========================================================================
% x    - hidden states:
%   o(1) - oculomotor angle
%   o(2) - oculomotor angle
%   x(1) - relative amplitude of visual hypothesis 1
%   x(2) - relative amplitude of visual hypothesis 2
%   x(3) - ...
%
% v    - hidden causes
%
% g    - sensations:
%   g(1) - oculomotor angle (proprioception - x)
%   g(2) - oculomotor angle (proprioception - y)
%   g(3) - retinal input - channel 1
%   g(4) - retinal input - channel 2
%   g(5) - ...
%__________________________________________________________________________
% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging
 
% Karl Friston
% $Id: spm_dem_search_trajectory.m 4595 2011-12-19 13:06:22Z karl $
 
 
% Preliminaries
%--------------------------------------------------------------------------
clf, global STIM
N  = length(DEM);
S  = spm_read_vols(STIM.U);
 
% Stimulus
%======================================================================
Dx = STIM.U.dim(1)/2;
Dy = STIM.U.dim(2)/2;
a  = [];
q  = [];
c  = [];

subplot(2,2,1); hold off
image((S + 1)*32), axis image, hold on
 
for i = 1:N
    
    % i-th saccade - position
    %----------------------------------------------------------------------
    pU = DEM{i}.pU.x{1}(1:2,:)*16;
    T  = length(pU);
    
    % eye movements in extrinsic coordinates
    %======================================================================
    subplot(2,2,1)
    plot(pU(2,:) + Dy,pU(1,:) + Dx,'r-','LineWidth',2)
    plot(pU(2,T) + Dy,pU(1,T) + Dx,'ro','MarkerSize',16)
    
    % Free energy
    %======================================================================
    F(i) = DEM{i}.F;
    
end