snpm_defaults.m

%
% FORMAT spm_defaults
%_______________________________________________________________________
%
% This file is intended to be customised for the site.
% Individual users can make copies which can be stored in their own
% matlab subdirectories. If ~/matlab is ahead of the SnPM directory
% in the MATLABPATH, then the users own personal defaults are used.
%
% Care must be taken when modifying this file
%_______________________________________________________________________
% Copyright (C) 2013 The University of Warwick
% Id: snpm_defaults.m  SnPM13 2013/10/12
% Thomas Nichols

global SnPMdefs

% Spatial extent threshold parameters
%------------------------------------------------------------------------
SnPMdefs.STalpha = 0.01; % T values above this sig are save for ST analysis
SnPMdefs.STprop  = 0.10; % 100*(1-STprop)%ile of observed Psuedo T values saved
                         % Default cluster-forming threshold set pre-analysis
SnPMdefs.ST_U    = spm_invNcdf(1-0.001);

% Work in "high memory" mode?
%------------------------------------------------------------------------
SnPMdefs.bVolm = 1; % Default to volumetric if less than this many scans

% When to work volumetrically?
%------------------------------------------------------------------------
SnPMdefs.nMax4DefVol = 16; % Default to volumetric if less than this many scans

% Variance smoothing?
%------------------------------------------------------------------------
SnPMdefs.vFWHM = [0 0 0 ]; 

% Default number of permutations
%------------------------------------------------------------------------
SnPMdefs.nPerm = 5000; % Default to volumetric if less than this many scans

% Statistics
%------------------------------------------------------------------------
SnPMdefs.FWElevel = 0.05;  % Default FWE level
SnPMdefs.FDRlevel = 0.05;  % Default FDR level

% Covariate option
%------------------------------------------------------------------------
SnPMdefs.CovVals = { 
    '1'
    '0'
    };

% If true, shuffles the seed of the random number generator to get 
% different results every time. Use false, if you want to specify your own 
% seed, for instance to insure that results can be replicated or when using 
% a high performance cluster.
%------------------------------------------------------------------------
SnPMdefs.shuffle_seed = true; 

% Reporting options for tabular listing of maximum
%------------------------------------------------------------------------
SnPMdefs.Results_distmin = 8;   % Minimum distance between peaks
SnPMdefs.Results_nbmax   = 3;   % Maximum number secondary peaks

% In Paired T test plugin, maximum number of subjects for which exhustive
% computation of permutations can be conducted.
%------------------------------------------------------------------------
SnPMdefs.pi_PairT_MaxExh = 25;