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: demo_dcm_1region.m
    path of file: ./repos/PsPM/src/ext/VBA/subfunctions
    
    the code of the file until where you have to start completion: % Demo for 1-region DCM for fMRI.
% This demo inverts the DCM fo
    
function (not affected by stochastic
% innovations).

close all
clear variables

%-----------------------------------------------------------
%-------------- DCM model specification --------------------

%--- Basic settings
f_fname = @f_DCMwHRF;
g_fname = @g_HRF3;
TR = 1e0;                      % sampling period (in sec)
n_t = round(6e1/TR);            % number of time samples
dtU = 1;%round(2/TR)+1;           % input-on time interval
t0U = 1;%round(10/TR)+1;                  
microDT = 1e-1;               % micro-time resolution (in sec)
homogeneous = 1;              % params of g(x) homogeneous accross regions
lin = 0;
alpha = 1e2/TR;              % state noise precision
sigma = Inf;%1e2;              % measurement noise precision
stochastic = 0;

%--- Input
u = zeros(1,n_t);%zeros(2,n_t);
times = 2:2+16;
u(1,times) = 1;
% u(2,floor(n_t/2):n_t) = 1;
% % u(1,4*t0U:4*t0U+dtU) = 1;

%--- DCM structure
% invariant effective connectivity
A = [0];
nreg = size(A,1);
% modulatory effects
B{1} = 0;
B{2} = 0;
% input-state coupling
C = 1;%[1,0];
% gating (nonlinear) effects
D{1} = 0;

%--- Build options/dim structures for model inversion
thetaHRF = zeros(6,1); % use SPM prior mean for HRF parameters
phiHRF = zeros(2,1);
[options]           = prepare_fullDCM(A,B,C,D,TR,microDT,homogeneous);
dim.n_theta         = options.inF.ind5(end