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_cost_SHC_fx.m
    path of file: ./repos/spm12/toolbox/DEM
    
    the code of the file until where you have to start completion: function [f] = spm_cost_SHC_fx(x,v,P)
% equations of motion for foraging problem using SHCs
% problem
% FORMAT [f] = spm_cost_SHC_fx(x,v,P)
%
% x   - hidden states (x.x, x.v x.q and x.a)
% v   - exogenous inputs
% P   - parameters
%
% The parameters associate increases in some physiological states x.q with 
% positions in physical space, encoded by radial basis functions x.a
%__________________________________________________________________________
% Copyright (C) 2010 Wellcome Trust Centre for Neuroimaging
 

    
function [f] = spm_cost_SHC_fx(x,v,P)
% equations of motion for foraging problem using SHCs
% problem
% FORMAT [f] = spm_cost_SHC_fx(x,v,P)
%
% x   - hidden states (x.x, x.v x.q and x.a)
% v   - exogenous inputs
% P   - parameters
%
% The parameters associate increases in some physiological states x.q with 
% positions in physical space, encoded by radial basis functions x.a
%__________________________________________________________________________
% Copyright (C) 2010 Wellcome Trust Centre for Neuroimaging
 
% Karl Friston
% $Id: spm_cost_SHC_fx.m 3757 2010-03-08 11:41:53Z guillaume $
 
 
 
% location and radius of attractors A
%--------------------------------------------------------------------------
global A; X   = A.x;
 
% gradient of Hamiltonian (G) is determined by the attractor state x.a
%--------------------------------------------------------------------------
[m,i] = max(x.a);
G     = x.x - X(:,i);
 
% motion of physical states
%--------------------------------------------------------------------------
f   = x;
f.x = x.v;
f.v = -G*8 - x.v*4;
 
% motion of physiological states (using basis functions of position)
%--------------------------------------------------------------------------
for i = 1:size(X,2)
    b(i,1) = norm(x.x - X(:,i)) < A.d;
end