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vb_set_bayes_parm

PURPOSE ^

Parameter setting of "bayes_parm" --- sample file

SYNOPSIS ^

function bayes_parm = vb_set_bayes_parm(proj_root)

DESCRIPTION ^

 Parameter setting of "bayes_parm" --- sample file
  bayes_parm = vb_set_bayes_parm(proj_root)
  
  You should copy 'vb_set_bayes_parm_test.m' to your local directory 
     and modify according to your environment.
  Alternately, you can make 'bayes_parm' parameter file using GUI.

 ------- Summary of bayes_parm --------
 proj_root : Root directory of your data files.
             All file names should be relative path from proj_root.
 
 Fields of 'bayes_parm'

 ***
 *** Basic Parameters
 ***
 ******************************
 - .megfile (.meg.mat)
     MEG data file to be analyzed. This is given by cell array of strings.
    e.g. megfile = {'SESSION1.meg.mat','SESSION2.meg.mat'}

 - .basisfile (.basis.mat)
     Lead field file for the high resolution model.
    e.g. megfile = {'SESSION1.basis.mat','SESSION2.basis.mat'}

 - .brainfile (.brain.mat)
     Brain file. 

 - .bayesfile (.bayes.mat)
     Result file. Estimated parameters will be saved into this file. 

 - .actfile (.act.mat)
    Activity map file. 

 - .areafile (.area.mat)
    Area file. 

 - .act_key
    ID of an activity map in .actfile. The specified activity map is 
   used as the prior information to VB variance estimation.

 - .area_key
    ID of an area in .areafile. Possible (focal) dipoles location are 
   restricted to the specified area. 

 - .twin_meg
    Time window of meg data in .megfile used for analysis. This window 
   is covered by several small time windows specfied by .Tperiod and
   .Tnext. It is specified by the start and end of the sampling frame, 
   not by the actual measurement time. 
   e.g. twin_meg = [1 600]  

 - .Tperiod
    Size of the small time windows. Its unit is the number of the
   sampling frames. .Tperiod and .Tnext mentioned below determine 
   small time windows for analysis.
   
 - .Tnext
   Moving steps of the small time window. If 100 sampling frames
   are covered by 19 small time windows with the size 10 frames,
   this parameter should be set to 5 (5x(19-1)+10=100). %

   e.g. Tperiod = 100, Tnext = 50  
               --> [1 100; 51 150; 101 200;...]
   e.g. Tperiod = [100 100 100], Tnext = [1 51 101] 
               --> [1 100; 51 150; 101 200;]

 - .soft_mode = 0;    % = 1: Soft normal constraint
    Soft normal constraint flag

 *** 
 *** Estimation Model Parameters 
 ***
 ********************************
   Specify estimation model by forward_model & noise_estimation_model

 - .forward_model
   -- 'focal' 
   -- 'focal+global' 

 - .noise_estimation_model
   How to estimate 
       sensor observation noise & brain background baseline activity
   
 *** The following fields are automatically set by noise_estimation_model
     You can change the time window for estimation

 - .twin_noise
   Time window (start and end) used for estimation 
   of the covariance of the observation noise

 - .twin_global
   Time window (start and end) used for estimation 
   of the baseline current activity

 - megnoisefile (.meg.mat)
   MEG data file for estimating the variance and covariance of 
   the observation noise.

 *** Do not modify the following fields directory

 - .noise_model
   Specifying noise model. 
   -- 1 spherical, same noise variance for all sensors
   -- 2 ellipsoidal, different noise variances but independent
   -- 3 full covariance, most general noise model 


 - .update_sx
   Specifying how to estimate the variance of the observation
   noise. 
   -- 0 Estimated from MEG data specified by
        bayes_parm.megnoisefile and bayes_parm.meg_noise. 
   -- 1 Estimated simultaneously with the variances of 'sparse'
        model. 

 - .update_v
   Specifying how to estimate the variance parameter of the 'iso'
   model.
   -- 0 Estimated from MEG data specified by
        bayes_parm.megbackfile and bayes_parm.meg_back. 
   -- 1 Estimated simultaneously with the variances of the high
        resolution model.
 
 ***
 *** Advanced parameters
 ***
 **********************************

 *** Global window  (default value)
 - .reduce_global (1)
    Rate to reduce the number of vertex points in global window. 
    This value must range from 0 to 1. 
 - .basisfile_global (.megfile)
 - .area_key_global  ('Cortex')
 - .Rfilt_global     (0)
   Radius (mm) of the smoothing filter along with the cortical
   surface for the low resolution model. 6mm (=6e-3) or 9mm is
   recommended. 

 *** Prior and VB estimation parameters (default value)
 - .a0 (1)
   Prior variance value corresponding to the minimum activity. 
 - .a0_act (1000) 
   Prior variance value corresponding to the maximum activity. 
 - .Ta0 (0)
   The confidence parameter of the prior variance for the high
   resolution estimation. This value is interpreted as a ratio to
   the sampling data number. That is, if it is set to 1, the prior
   is weighted equal to the estimated value based on the
   likelihood. 
 - .Tv0 (0)
   The confidence parameter of the prior variance for the low
   resolution estimation. This value is interpreted as a ratio to
   the sampling data number as in the case of bayes_parm.Ta0. 
 - .Ntrain (1000)
   Total number of parameter updates. 
 - .Npre_train (750)
   Number of parameter updates in the first stage by using VB-update rule. 
 - .skip (10)
   Number of iterations to calculate the free energy. 

 *** Optional parameters (default value)
 - .cont_pr (OFF)
   Flag whether initializing the prior parameters using estimated parameters
   of previous time window
 - .temporal_filter (OFF)
   Flag whether applying temporal smoothing filter to MEG data. 
 - .trial_average   (OFF) 
   Flag wheter applying trial average to MEG data.
 - .expand_spatial_filter  (ON)     
   Flag whether using expanding spatial filter 
 - .variance_orientation   (OFF) 
   Flag whether variance parameters have orientation

 - .cosval (-1)
   Orientation constraint for neighbour dipoles. A recommended
   value is 1 (=cos(pi)), which means no constraint. 
 - .Rfilt (6e-3)
   Radius (m) of the smoothing filter along with the cortical
   surface. 6mm (=6e-3) or 9mm is recommended. 
 - .noise_reg (0.1)
   Regularization parameter for the normalized covariance matrix
   of the additive noise. This value should be determined
   considering that the mean of the diagonal part of the
   normalized covariance matrix is 1.
 - .reduce (1)
    Rate to reduce the number of vertex points. This value must 
   range from 0 to 1. 
 - .Fdmin (1e-50)
   Criterion of convergence of the VB algorithm. 
 - .a_min (1e-6)
   Minimum value of alpha. 
 - .a_max (1e6)
   Maximum value of alpha. 


 ---------------------------------------------------------------

 ***
 *** File format of resultfile (.bayes.mat)
 ***
 ************************************************
 - bayes_parm
   Input parameters 
 - Model
   Estimated variance parameters 
 - Cov
   Additive noise covariance. 
 - Info
   Convergence information such as FE, Ev and Err ...
 - vb_parm 
   Parameters used in VB estimation
--- 
 
 2006/09/20 ver 0.5 by M. Sato
 2008-11-05 Taku Yoshioka

 Copyright (C) 2011, ATR All Rights Reserved.
 License : New BSD License(see VBMEG_LICENSE.txt)

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 function bayes_parm = vb_set_bayes_parm(proj_root)
0002 % Parameter setting of "bayes_parm" --- sample file
0003 %  bayes_parm = vb_set_bayes_parm(proj_root)
0004 %
0005 %  You should copy 'vb_set_bayes_parm_test.m' to your local directory
0006 %     and modify according to your environment.
0007 %  Alternately, you can make 'bayes_parm' parameter file using GUI.
0008 %
0009 % ------- Summary of bayes_parm --------
0010 % proj_root : Root directory of your data files.
0011 %             All file names should be relative path from proj_root.
0012 %
0013 % Fields of 'bayes_parm'
0014 %
0015 % ***
0016 % *** Basic Parameters
0017 % ***
0018 % ******************************
0019 % - .megfile (.meg.mat)
0020 %     MEG data file to be analyzed. This is given by cell array of strings.
0021 %    e.g. megfile = {'SESSION1.meg.mat','SESSION2.meg.mat'}
0022 %
0023 % - .basisfile (.basis.mat)
0024 %     Lead field file for the high resolution model.
0025 %    e.g. megfile = {'SESSION1.basis.mat','SESSION2.basis.mat'}
0026 %
0027 % - .brainfile (.brain.mat)
0028 %     Brain file.
0029 %
0030 % - .bayesfile (.bayes.mat)
0031 %     Result file. Estimated parameters will be saved into this file.
0032 %
0033 % - .actfile (.act.mat)
0034 %    Activity map file.
0035 %
0036 % - .areafile (.area.mat)
0037 %    Area file.
0038 %
0039 % - .act_key
0040 %    ID of an activity map in .actfile. The specified activity map is
0041 %   used as the prior information to VB variance estimation.
0042 %
0043 % - .area_key
0044 %    ID of an area in .areafile. Possible (focal) dipoles location are
0045 %   restricted to the specified area.
0046 %
0047 % - .twin_meg
0048 %    Time window of meg data in .megfile used for analysis. This window
0049 %   is covered by several small time windows specfied by .Tperiod and
0050 %   .Tnext. It is specified by the start and end of the sampling frame,
0051 %   not by the actual measurement time.
0052 %   e.g. twin_meg = [1 600]
0053 %
0054 % - .Tperiod
0055 %    Size of the small time windows. Its unit is the number of the
0056 %   sampling frames. .Tperiod and .Tnext mentioned below determine
0057 %   small time windows for analysis.
0058 %
0059 % - .Tnext
0060 %   Moving steps of the small time window. If 100 sampling frames
0061 %   are covered by 19 small time windows with the size 10 frames,
0062 %   this parameter should be set to 5 (5x(19-1)+10=100). %
0063 %
0064 %   e.g. Tperiod = 100, Tnext = 50
0065 %               --> [1 100; 51 150; 101 200;...]
0066 %   e.g. Tperiod = [100 100 100], Tnext = [1 51 101]
0067 %               --> [1 100; 51 150; 101 200;]
0068 %
0069 % - .soft_mode = 0;    % = 1: Soft normal constraint
0070 %    Soft normal constraint flag
0071 %
0072 % ***
0073 % *** Estimation Model Parameters
0074 % ***
0075 % ********************************
0076 %   Specify estimation model by forward_model & noise_estimation_model
0077 %
0078 % - .forward_model
0079 %   -- 'focal'
0080 %   -- 'focal+global'
0081 %
0082 % - .noise_estimation_model
0083 %   How to estimate
0084 %       sensor observation noise & brain background baseline activity
0085 %
0086 % *** The following fields are automatically set by noise_estimation_model
0087 %     You can change the time window for estimation
0088 %
0089 % - .twin_noise
0090 %   Time window (start and end) used for estimation
0091 %   of the covariance of the observation noise
0092 %
0093 % - .twin_global
0094 %   Time window (start and end) used for estimation
0095 %   of the baseline current activity
0096 %
0097 % - megnoisefile (.meg.mat)
0098 %   MEG data file for estimating the variance and covariance of
0099 %   the observation noise.
0100 %
0101 % *** Do not modify the following fields directory
0102 %
0103 % - .noise_model
0104 %   Specifying noise model.
0105 %   -- 1 spherical, same noise variance for all sensors
0106 %   -- 2 ellipsoidal, different noise variances but independent
0107 %   -- 3 full covariance, most general noise model
0108 %
0109 %
0110 % - .update_sx
0111 %   Specifying how to estimate the variance of the observation
0112 %   noise.
0113 %   -- 0 Estimated from MEG data specified by
0114 %        bayes_parm.megnoisefile and bayes_parm.meg_noise.
0115 %   -- 1 Estimated simultaneously with the variances of 'sparse'
0116 %        model.
0117 %
0118 % - .update_v
0119 %   Specifying how to estimate the variance parameter of the 'iso'
0120 %   model.
0121 %   -- 0 Estimated from MEG data specified by
0122 %        bayes_parm.megbackfile and bayes_parm.meg_back.
0123 %   -- 1 Estimated simultaneously with the variances of the high
0124 %        resolution model.
0125 %
0126 % ***
0127 % *** Advanced parameters
0128 % ***
0129 % **********************************
0130 %
0131 % *** Global window  (default value)
0132 % - .reduce_global (1)
0133 %    Rate to reduce the number of vertex points in global window.
0134 %    This value must range from 0 to 1.
0135 % - .basisfile_global (.megfile)
0136 % - .area_key_global  ('Cortex')
0137 % - .Rfilt_global     (0)
0138 %   Radius (mm) of the smoothing filter along with the cortical
0139 %   surface for the low resolution model. 6mm (=6e-3) or 9mm is
0140 %   recommended.
0141 %
0142 % *** Prior and VB estimation parameters (default value)
0143 % - .a0 (1)
0144 %   Prior variance value corresponding to the minimum activity.
0145 % - .a0_act (1000)
0146 %   Prior variance value corresponding to the maximum activity.
0147 % - .Ta0 (0)
0148 %   The confidence parameter of the prior variance for the high
0149 %   resolution estimation. This value is interpreted as a ratio to
0150 %   the sampling data number. That is, if it is set to 1, the prior
0151 %   is weighted equal to the estimated value based on the
0152 %   likelihood.
0153 % - .Tv0 (0)
0154 %   The confidence parameter of the prior variance for the low
0155 %   resolution estimation. This value is interpreted as a ratio to
0156 %   the sampling data number as in the case of bayes_parm.Ta0.
0157 % - .Ntrain (1000)
0158 %   Total number of parameter updates.
0159 % - .Npre_train (750)
0160 %   Number of parameter updates in the first stage by using VB-update rule.
0161 % - .skip (10)
0162 %   Number of iterations to calculate the free energy.
0163 %
0164 % *** Optional parameters (default value)
0165 % - .cont_pr (OFF)
0166 %   Flag whether initializing the prior parameters using estimated parameters
0167 %   of previous time window
0168 % - .temporal_filter (OFF)
0169 %   Flag whether applying temporal smoothing filter to MEG data.
0170 % - .trial_average   (OFF)
0171 %   Flag wheter applying trial average to MEG data.
0172 % - .expand_spatial_filter  (ON)
0173 %   Flag whether using expanding spatial filter
0174 % - .variance_orientation   (OFF)
0175 %   Flag whether variance parameters have orientation
0176 %
0177 % - .cosval (-1)
0178 %   Orientation constraint for neighbour dipoles. A recommended
0179 %   value is 1 (=cos(pi)), which means no constraint.
0180 % - .Rfilt (6e-3)
0181 %   Radius (m) of the smoothing filter along with the cortical
0182 %   surface. 6mm (=6e-3) or 9mm is recommended.
0183 % - .noise_reg (0.1)
0184 %   Regularization parameter for the normalized covariance matrix
0185 %   of the additive noise. This value should be determined
0186 %   considering that the mean of the diagonal part of the
0187 %   normalized covariance matrix is 1.
0188 % - .reduce (1)
0189 %    Rate to reduce the number of vertex points. This value must
0190 %   range from 0 to 1.
0191 % - .Fdmin (1e-50)
0192 %   Criterion of convergence of the VB algorithm.
0193 % - .a_min (1e-6)
0194 %   Minimum value of alpha.
0195 % - .a_max (1e6)
0196 %   Maximum value of alpha.
0197 %
0198 %
0199 % ---------------------------------------------------------------
0200 %
0201 % ***
0202 % *** File format of resultfile (.bayes.mat)
0203 % ***
0204 % ************************************************
0205 % - bayes_parm
0206 %   Input parameters
0207 % - Model
0208 %   Estimated variance parameters
0209 % - Cov
0210 %   Additive noise covariance.
0211 % - Info
0212 %   Convergence information such as FE, Ev and Err ...
0213 % - vb_parm
0214 %   Parameters used in VB estimation
0215 %---
0216 %
0217 % 2006/09/20 ver 0.5 by M. Sato
0218 % 2008-11-05 Taku Yoshioka
0219 %
0220 % Copyright (C) 2011, ATR All Rights Reserved.
0221 % License : New BSD License(see VBMEG_LICENSE.txt)
0222 
0223 % Set default parameter
0224 bayes_parm = vb_set_bayes_default_parameters; 
0225 
0226 % If 'proj_root' is not given, only default parameters are set
0227 if ~exist('proj_root', 'var'),     return; end;
0228 
0229 % --- Input file(relative path from proj_root)
0230 bayes_parm.brainfile = [];
0231 bayes_parm.areafile  = [];
0232 bayes_parm.actfile   = [];
0233 bayes_parm.megfile   = { [] };
0234 bayes_parm.basisfile = { [] };
0235 
0236 % --- Output file(relative path from proj_root)
0237 bayes_parm.bayesfile = '';
0238 
0239 % --- Specify current area and fMRI activity
0240 bayes_parm.area_key  = 'Cortex';
0241 bayes_parm.act_key   = {'Uniform'};
0242 
0243 % --- Specify time window by sample numbar
0244 bayes_parm.twin_meg  = []; % Time window for analysis
0245 bayes_parm.Tperiod   = []; % Time period for current estimation
0246 bayes_parm.Tnext     = []; % Time step for next period
0247 
0248 % --- Soft normal constraint flag
0249 bayes_parm.soft_mode = 0;    % = 1: Soft normal constraint
0250 
0251 % --- Estimation model
0252 bayes_parm.forward_model    = 'focal';  % 'focal' or 'focal+global'
0253 bayes_parm.noise_estimation_model = 1;  % 1, ..., 5
0254 
0255 % Extra dipole parameters
0256 bayes_parm.extra = []; 
0257 
0258 %
0259 % Noise estimation model
0260 %
0261 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0262 
0263 bayes_parm = vb_set_noise_estimation_model(bayes_parm, proj_root);

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