Calculate ERSP for cortical current.
(VBMEG public function)
This function calculates event-related spectral perturbation (ERSP;
Delorme and Makeig, 2004) for cortical current. The value is
baseline-normalized and its unit is dB (10log10). Analyses can be done
on the original subject's cortex or on the other subject's cortex
(commonly template cortical model like fsaverage).
[syntax]
vb_job_ersp(proj_root,tf_parm)
[input]
proj_root: <<string>> VBMEG project root directory.
tf_parm : <<struct>> Parameters for time-frequency analysis
--- fields of fs_parm
curr_file : <<string>> Cortical current file.
curr_file_base: <optional> <<string>> Cortical current files from
which baseline current amplitude is calculated. If not
given, curr_file is used to calculate baseline.
brain_file : <<string>> Cortical surface model file on which
cortical current was calculated (subject's brain).
key : <<string>> ID of coregistration matrix for each subjects
corresponding to brain files. In common, coregistration
matrix from the subject to a template cortical model is
specified.
tbrain_file : <<string>> Cortical surface model filename of template
brain. This file is used to reduce the number of
vertices.
reduce : <<int or double>> Vertex reduction ratio
(@see reducepatch).
fmin : <<double>> Minimum frequency.
fmax : <<double>> Maximum frequency.
baseline : <<double vector>> Start and end of baseline time window
in millisecond.
elim_time : <optional> <<double>> In order to eliminate edge
effect, time points with length (elim_time)*(original
time length) are eliminated from start and end of data
after time-frequency decomposition (wavelet). Default
value is 0.05.
tf_file_out : <<string>> Output filename.
timefreq_parm : <optional> <<struct>> EEGLAB timefreq parameters. If
this parameter is given, elim_time is ignored.
--- fields of timefreq_parm
cycles : <<scalar or vector>> Parameter of timefreq function.
winsize : <<scalar>> Parameter of timefreq function.
padratio : <<scalar>> Parameter of timefreq function.
ntimesout : <<int>> Parameter of timefreq function.
nfreqs : <<int>> Parameter of timefreq function.
ntimesout_base: <<int>> Parameter of timefreq function for baseline.
---
---
[output]
TimeFrequency file (.tf.mat) is created. This file has the following
variables:
data : <<matrix>> Time-frequency data. F-by-T-by-I matrix, where F, T,
I are number of frequency bins (=length(TFinfo.freq), time
window length (=length(TFinfo.Tmsec) and the number of vertices
(=length(TFinfo.ix_act)), respectively.
TFinfo: <<struct>> Information of time-frequency data.
--- fields of TFinfo
tf_type : <<string>> Set to 'ERSP'.
Tsample : <<vector>> Timepoint indices of the original data.
Pretrigger: <<int>> Pretrigger period (timepoints).
SampleFreq: <<float>> Sampling frequency of the original data.
Tmsec : <<vector>> Actual time of each timepoints in msec
(length(Tsample) = length(Tmsec)).
Ntrial : <<vector>> Number of trials of each current data.
freq : <<vector>> Frequency vector [Hz]. Each row of
'data(:,f,:)' has frequency TFinfo.freq(f).
ix_act : <<int vector>> Vertex indices on which time-frequency data
is calculated.
Wact : <<double matrix>> Smoothing filter matrix. The size of
smoothing filter is automatically determined from mean
distance between vertices after reduction
(tf_parm.reduce). This matrix will be used for displaying
purpose.
ix_act_ex : <<int vector>> Vertex indices corresponding to the row of
the smoothing matrix TFinfo.Wact.
base : <<double matrix>> Baseline at each frequency and
vertex. It is temporal average of the baseline ERSP.
---
[example]
The following code is an example to calculate ERSP on template cortical
surface model.
>> tf_parm.curr_file = './subjects/0001/result/0001_LR.curr.mat';
>> tf_parm.curr_file_base = tf_parm.curr_file;
>> tf_parm.brain_file = './subjects/0001/brain/0001.brain.mat';
>> tf_parm.key = 'fsaverage.sphere.reg';
>> tf_parm.tbrain_file ...
= './subjects/fsaverage/brain/fsaverage.brain.mat';
>> tf_parm.reduce = 0.2;
>> tf_parm.fmin = 2.0;
>> tf_parm.baseline = [-300 0];
>> tf_parm.tf_file_out ...
= './subjects/fsaverage/result/fsaverage_LR_ERSP.tf.mat';
>> vb_job_ersp(proj_root,tf_parm);
[history]
2011-01-02 Taku Yoshioka
2011-01-25 taku-y
[enhancement] EEGLAB timefreq function supported.
2011-02-03 taku-y
[trivial] Baseline ERSP 'base' added to TFinfo.
2011-02-28 taku-y
[debug] [0 fmax] -> [fmin fmax] in timefreq().
2011-07-01 taku-y
[minor] vb_disp() was replaced by vb_disp_nonl() for displaying
progress messages.
Copyright (C) 2011, ATR All Rights Reserved.
License : New BSD License(see VBMEG_LICENSE.txt)0001 function vb_job_ersp(proj_root,tf_parm) 0002 % Calculate ERSP for cortical current. 0003 % (VBMEG public function) 0004 % 0005 % This function calculates event-related spectral perturbation (ERSP; 0006 % Delorme and Makeig, 2004) for cortical current. The value is 0007 % baseline-normalized and its unit is dB (10log10). Analyses can be done 0008 % on the original subject's cortex or on the other subject's cortex 0009 % (commonly template cortical model like fsaverage). 0010 % 0011 % [syntax] 0012 % vb_job_ersp(proj_root,tf_parm) 0013 % 0014 % [input] 0015 % proj_root: <<string>> VBMEG project root directory. 0016 % tf_parm : <<struct>> Parameters for time-frequency analysis 0017 % --- fields of fs_parm 0018 % curr_file : <<string>> Cortical current file. 0019 % curr_file_base: <optional> <<string>> Cortical current files from 0020 % which baseline current amplitude is calculated. If not 0021 % given, curr_file is used to calculate baseline. 0022 % brain_file : <<string>> Cortical surface model file on which 0023 % cortical current was calculated (subject's brain). 0024 % key : <<string>> ID of coregistration matrix for each subjects 0025 % corresponding to brain files. In common, coregistration 0026 % matrix from the subject to a template cortical model is 0027 % specified. 0028 % tbrain_file : <<string>> Cortical surface model filename of template 0029 % brain. This file is used to reduce the number of 0030 % vertices. 0031 % reduce : <<int or double>> Vertex reduction ratio 0032 % (@see reducepatch). 0033 % fmin : <<double>> Minimum frequency. 0034 % fmax : <<double>> Maximum frequency. 0035 % baseline : <<double vector>> Start and end of baseline time window 0036 % in millisecond. 0037 % elim_time : <optional> <<double>> In order to eliminate edge 0038 % effect, time points with length (elim_time)*(original 0039 % time length) are eliminated from start and end of data 0040 % after time-frequency decomposition (wavelet). Default 0041 % value is 0.05. 0042 % tf_file_out : <<string>> Output filename. 0043 % timefreq_parm : <optional> <<struct>> EEGLAB timefreq parameters. If 0044 % this parameter is given, elim_time is ignored. 0045 % --- fields of timefreq_parm 0046 % cycles : <<scalar or vector>> Parameter of timefreq function. 0047 % winsize : <<scalar>> Parameter of timefreq function. 0048 % padratio : <<scalar>> Parameter of timefreq function. 0049 % ntimesout : <<int>> Parameter of timefreq function. 0050 % nfreqs : <<int>> Parameter of timefreq function. 0051 % ntimesout_base: <<int>> Parameter of timefreq function for baseline. 0052 % --- 0053 % --- 0054 % 0055 % [output] 0056 % TimeFrequency file (.tf.mat) is created. This file has the following 0057 % variables: 0058 % data : <<matrix>> Time-frequency data. F-by-T-by-I matrix, where F, T, 0059 % I are number of frequency bins (=length(TFinfo.freq), time 0060 % window length (=length(TFinfo.Tmsec) and the number of vertices 0061 % (=length(TFinfo.ix_act)), respectively. 0062 % TFinfo: <<struct>> Information of time-frequency data. 0063 % --- fields of TFinfo 0064 % tf_type : <<string>> Set to 'ERSP'. 0065 % Tsample : <<vector>> Timepoint indices of the original data. 0066 % Pretrigger: <<int>> Pretrigger period (timepoints). 0067 % SampleFreq: <<float>> Sampling frequency of the original data. 0068 % Tmsec : <<vector>> Actual time of each timepoints in msec 0069 % (length(Tsample) = length(Tmsec)). 0070 % Ntrial : <<vector>> Number of trials of each current data. 0071 % freq : <<vector>> Frequency vector [Hz]. Each row of 0072 % 'data(:,f,:)' has frequency TFinfo.freq(f). 0073 % ix_act : <<int vector>> Vertex indices on which time-frequency data 0074 % is calculated. 0075 % Wact : <<double matrix>> Smoothing filter matrix. The size of 0076 % smoothing filter is automatically determined from mean 0077 % distance between vertices after reduction 0078 % (tf_parm.reduce). This matrix will be used for displaying 0079 % purpose. 0080 % ix_act_ex : <<int vector>> Vertex indices corresponding to the row of 0081 % the smoothing matrix TFinfo.Wact. 0082 % base : <<double matrix>> Baseline at each frequency and 0083 % vertex. It is temporal average of the baseline ERSP. 0084 % --- 0085 % 0086 % [example] 0087 % The following code is an example to calculate ERSP on template cortical 0088 % surface model. 0089 % >> tf_parm.curr_file = './subjects/0001/result/0001_LR.curr.mat'; 0090 % >> tf_parm.curr_file_base = tf_parm.curr_file; 0091 % >> tf_parm.brain_file = './subjects/0001/brain/0001.brain.mat'; 0092 % >> tf_parm.key = 'fsaverage.sphere.reg'; 0093 % >> tf_parm.tbrain_file ... 0094 % = './subjects/fsaverage/brain/fsaverage.brain.mat'; 0095 % >> tf_parm.reduce = 0.2; 0096 % >> tf_parm.fmin = 2.0; 0097 % >> tf_parm.baseline = [-300 0]; 0098 % >> tf_parm.tf_file_out ... 0099 % = './subjects/fsaverage/result/fsaverage_LR_ERSP.tf.mat'; 0100 % >> vb_job_ersp(proj_root,tf_parm); 0101 % 0102 % [history] 0103 % 2011-01-02 Taku Yoshioka 0104 % 2011-01-25 taku-y 0105 % [enhancement] EEGLAB timefreq function supported. 0106 % 2011-02-03 taku-y 0107 % [trivial] Baseline ERSP 'base' added to TFinfo. 0108 % 2011-02-28 taku-y 0109 % [debug] [0 fmax] -> [fmin fmax] in timefreq(). 0110 % 2011-07-01 taku-y 0111 % [minor] vb_disp() was replaced by vb_disp_nonl() for displaying 0112 % progress messages. 0113 % 0114 % Copyright (C) 2011, ATR All Rights Reserved. 0115 % License : New BSD License(see VBMEG_LICENSE.txt) 0116 0117 vb_disp('--- ERSP calculation'); 0118 0119 % 0120 % Verbose level 0121 % 0122 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 0123 const = vb_define_verbose; 0124 vb_struct2vars(const,{'VERBOSE_LEVEL_NONE','VERBOSE_LEVEL_EMERGENCY', ... 0125 'VERBOSE_LEVEL_WARNING','VERBOSE_LEVEL_NOTICE', ... 0126 'VERBOSE_LEVEL_INFO','VERBOSE_LEVEL_DEBUG'}); 0127 VERBOSE_LEVEL_DEBUG = const.VERBOSE_LEVEL_DEBUG; 0128 0129 % 0130 % Input arguments 0131 % 0132 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 0133 vb_struct2vars(tf_parm,{'curr_file','brain_file','key', ... 0134 'tf_file_out','tbrain_file','reduce','fmin','fmax', ... 0135 'baseline','elim_time','curr_file_base', ... 0136 'timefreq_parm'}); 0137 0138 if isempty(curr_file_base), curr_file_base = curr_file; end 0139 if isempty(elim_time), elim_time = 0.05; end 0140 0141 % 0142 % Check arguments 0143 % 0144 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 0145 % Sampling frequency 0146 Jinfo1 = vb_load_current_info(curr_file); 0147 Jinfo2 = vb_load_current_info(curr_file_base); 0148 if Jinfo1.SampleFreq~=Jinfo2.SampleFreq, 0149 error(['Sampling frequencies of current file and baseline ' ... 0150 'current file must be the same.']); 0151 end 0152 0153 % 0154 % Preparation of cortical dipole indices 0155 % 0156 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 0157 % Number of dipoles on which TF analysis conducted. 0158 if ~isempty(key), % use template brain 0159 % note: consistency check between tbrain_file and key{1} is required, 0160 % but postponed. (7 Dec. 2010, taku-y) 0161 brain_file_tmp = tbrain_file; 0162 else % single subject analysis 0163 brain_file_tmp = brain_file; 0164 end 0165 0166 % Reduce vertex of the cortical model 0167 V = vb_load_cortex(brain_file_tmp); 0168 ix_act = vb_reduce_cortex(brain_file_tmp,1:size(V,1),reduce); 0169 I = length(ix_act); 0170 clear V; 0171 0172 % For single subject analysis, find overlap between ix_act and 0173 % Jinfo.ix_act_ex. ix_act is replaced by it and I is overwritten. 0174 if isempty(key), % single subject analysis 0175 Jinfo = vb_load_current_info(curr_file); 0176 [tmp,ixx] = intersect(Jinfo.ix_act_ex,ix_act); 0177 ix_act = Jinfo.ix_act_ex(ixx); 0178 I = length(ix_act); 0179 Wact = Jinfo.Wact(ixx,:); 0180 end 0181 0182 % Calculate mean distance between reduced vertices to determine smoothing 0183 % filter size 0184 R = 0.0; 0185 N = 0; 0186 [nextDD,nextIX] = vb_load_cortex_neighbour(brain_file_tmp); 0187 for i=1:length(ix_act) 0188 [tmp,ixx] = union(nextIX{ix_act(i)},ix_act); 0189 R = R+sum(nextDD{ix_act(i)}(ixx)); 0190 N = N+length(ixx); 0191 end 0192 R = R/N; 0193 0194 % Calculate smoothing filter. It will be used for displaying purpose, not 0195 % affect further analysis. 0196 V = vb_load_cortex(brain_file_tmp); 0197 [W,ix_act_ex] ... 0198 = vb_spatial_gauss_filter(brain_file_tmp,R,2*R,ix_act,1,-1,1); 0199 W = W./repmat(sum(W,2),[1 size(W,2)]); 0200 TFinfo.Wact = W; 0201 TFinfo.ix_act_ex = ix_act_ex; 0202 clear V; 0203 0204 % 0205 % Preparation of variables time-frequency data stored 0206 % 0207 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 0208 if isempty(timefreq_parm), % wavelet() parameters 0209 % Number of timepoints 0210 Jinfo = vb_load_current_info(curr_file); 0211 T = length(Jinfo.Tmsec); % time points 0212 DJ = 0.25; % scale of time points spacing 0213 DT = 1/(Jinfo.SampleFreq); % original time points spacing 0214 S0 = 2*DT; % smallest freq. scale 0215 0216 % Number of frequency bins 0217 [tmp,period,coi] = wavelet(randn(1,T),DT,1,DJ); 0218 TFinfo.freq = 1./period; 0219 ix_freq = find(TFinfo.freq>=fmin); 0220 TFinfo.freq = TFinfo.freq(ix_freq); 0221 F = length(TFinfo.freq); 0222 0223 % Eliminate start and end time points 0224 t_elim = ceil(T*elim_time); 0225 ix_time = (t_elim+1):(T-t_elim); 0226 Tmsec = Jinfo.Tmsec(ix_time); 0227 T = length(Tmsec); 0228 0229 % Whole data 0230 data = zeros(F,T,I); 0231 0232 % Baseline 0233 if ~isempty(baseline), 0234 Jinfo_base = vb_load_current_info(curr_file_base); 0235 Tbase = length(Jinfo_base.Tmsec); 0236 t_elim_base = ceil(Tbase*elim_time); 0237 ix_time_base = (t_elim_base+1):(Tbase-t_elim_base); 0238 Tmsec_base = Jinfo_base.Tmsec(ix_time_base); 0239 Tbase = length(Tmsec_base); 0240 base = zeros(F,Tbase,I); 0241 Ntrial_base = Jinfo_base.Ntrial; 0242 else 0243 Tbase = []; 0244 end 0245 else % timefreq() parameters 0246 vb_struct2vars(timefreq_parm,{'cycles','winsize','padratio', ... 0247 'ntimesout','nfreqs','ntimesout_base'}); 0248 0249 % Number of timepoints and frequency bins 0250 Jinfo = vb_load_current_info(curr_file); 0251 frames = length(Jinfo.Tmsec); 0252 tlimits = [min(Jinfo.Tmsec) max(Jinfo.Tmsec)]; 0253 srate = Jinfo.SampleFreq; 0254 if isempty(fmax), 0255 fmax = srate/2; 0256 end 0257 0258 [tmp,freqs,Tmsec] ... 0259 = timefreq(randn(frames,1),srate,'cycles',cycles, ... 0260 'freqs',[fmin fmax],'padratio',padratio, ... 0261 'winsize',winsize,'tlimits',tlimits, ... 0262 'ntimesout',ntimesout,'nfreqs',nfreqs, ... 0263 'verbose','off'); 0264 0265 T = length(Tmsec); 0266 ix_time = 1:length(Tmsec); 0267 TFinfo.freq = freqs; 0268 ix_freq = find(TFinfo.freq>=fmin); 0269 TFinfo.freq = TFinfo.freq(ix_freq); 0270 F = length(TFinfo.freq); 0271 0272 % Whole data 0273 data = zeros(F,T,I); 0274 0275 % Baseline 0276 if ~isempty(baseline), 0277 Jinfo_base = vb_load_current_info(curr_file_base); 0278 frames_base = length(Jinfo_base.Tmsec); 0279 tlimits_base = [min(Jinfo.Tmsec) max(Jinfo.Tmsec)]; 0280 0281 [tmp,freqs_base,Tmsec_base] ... 0282 = timefreq(randn(frames_base,1),srate,'cycles',cycles, ... 0283 'freqs',[fmin fmax],'padratio',padratio, ... 0284 'winsize',winsize,'tlimits',tlimits_base, ... 0285 'ntimesout',ntimesout_base,'nfreqs',nfreqs, ... 0286 'verbose','off'); 0287 0288 Tbase = length(Tmsec_base); 0289 ix_time_base = 1:Tbase; 0290 base = zeros(F,Tbase,I); 0291 Ntrial_base = Jinfo_base.Ntrial; 0292 else 0293 Tbase = []; 0294 end 0295 end 0296 0297 vb_disp(['Number of frequency bins : ' num2str(F)]); 0298 vb_disp(['Number of timepoints : ' num2str(T)]); 0299 vb_disp(['Number of vertices : ' num2str(I)]); 0300 0301 if ~isempty(Tbase), 0302 vb_disp(['Number of timepoints (baseline): ' num2str(Tbase)]); 0303 end 0304 0305 % 0306 % Main routine 0307 % 0308 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 0309 Jinfo = vb_load_current_info(curr_file); 0310 Ntrial = Jinfo.Ntrial; 0311 0312 if ~isempty(key), % use template brain 0313 C = vb_load_cortex_pmat(brain_file,key); 0314 0315 if strcmp(Jinfo.curr_type,'Z-current'), 0316 CW = sparse(C(ix_act,Jinfo.ix_act_ex)*Jinfo.Wact); 0317 else 0318 CW = sparse(C(ix_act,Jinfo.ix_act_ex)); 0319 end 0320 else % single subject analysis 0321 CW = Wact; 0322 end 0323 0324 prg = 0; 0325 prg_all = Ntrial; 0326 prg_str = sprintf('Current : %d%% processed',0); 0327 vb_disp_nonl(prg_str); 0328 0329 for j=1:Ntrial % trial loop 0330 [tmp,Z] = vb_load_current(curr_file,Jinfo.curr_type,false,j); 0331 0332 for k=1:I % vertex loop 0333 ix = find(abs(CW(k,:))>0); 0334 J = CW(k,ix)*Z(ix,:); % J-current at ix_act-th dipole 0335 0336 if isempty(timefreq_parm), 0337 wave = wavelet(J,DT,1,DJ); 0338 else 0339 wave = timefreq(J',srate,'cycles',cycles, ... 0340 'freqs',[fmin fmax],'padratio',padratio, ... 0341 'winsize',winsize,'tlimits',tlimits, ... 0342 'ntimesout',ntimesout,'nfreqs',nfreqs, ... 0343 'verbose','off'); 0344 end 0345 0346 wave = wave(ix_freq,ix_time); 0347 data(:,:,k) = data(:,:,k)+abs(wave).^2; 0348 end 0349 0350 % progress message 0351 prg = prg+1; 0352 for ii=1:length(prg_str); vb_disp_nonl(sprintf('\b')); end 0353 prg_str = sprintf('Current : %d%% processed',ceil(100*(prg/prg_all))); 0354 vb_disp_nonl(prg_str); 0355 end 0356 0357 for ii=1:length(prg_str); vb_disp_nonl(sprintf('\b')); end 0358 vb_disp('Current : finished'); 0359 0360 % Baseline 0361 Jinfo_base = vb_load_current_info(curr_file_base); 0362 Ntrial = Jinfo_base.Ntrial; 0363 0364 if ~isempty(key), % use template brain 0365 C = vb_load_cortex_pmat(brain_file,key); 0366 0367 if strcmp(Jinfo_base.curr_type,'Z-current'), 0368 CW = sparse(C(ix_act,Jinfo_base.ix_act_ex)*Jinfo_base.Wact); 0369 else 0370 CW = sparse(C(ix_act,Jinfo_base.ix_act_ex)); 0371 end 0372 else % single subject analysis 0373 CW = Wact; 0374 end 0375 0376 prg = 0; 0377 prg_all = Ntrial_base; 0378 prg_str = sprintf('Baseline: %d%% processed',0); 0379 vb_disp_nonl(prg_str); 0380 0381 for j=1:Ntrial_base % trial loop 0382 [tmp,Z] = vb_load_current(curr_file_base, ... 0383 Jinfo_base.curr_type,false,j); 0384 0385 for k=1:I % vertex loop 0386 ix = find(abs(CW(k,:))>0); 0387 J = CW(k,ix)*Z(ix,:); % J-current at ix_act-th dipole 0388 if isempty(timefreq_parm), 0389 wave = wavelet(J,DT,1,DJ); 0390 else 0391 wave = timefreq(J',srate,'cycles',cycles, ... 0392 'freqs',[fmin fmax],'padratio',padratio, ... 0393 'winsize',winsize,'tlimits',tlimits_base, ... 0394 'ntimesout',ntimesout_base,'nfreqs',nfreqs, ... 0395 'verbose','off'); 0396 end 0397 0398 wave = wave(ix_freq,ix_time_base); 0399 base(:,:,k) = base(:,:,k)+abs(wave).^2; 0400 end 0401 0402 % progress message 0403 prg = prg+1; 0404 for ii=1:length(prg_str); vb_disp_nonl(sprintf('\b')); end 0405 prg_str = sprintf('Baseline: %d%% processed',ceil(100*(prg/prg_all))); 0406 vb_disp_nonl(prg_str); 0407 end 0408 0409 for ii=1:length(prg_str); vb_disp_nonl(sprintf('\b')); end 0410 vb_disp('Baseline: finished'); 0411 0412 % Normalization 0413 [tmp,ix_base_start] = min(abs(Tmsec_base-tf_parm.baseline(1))); 0414 [tmp,ix_base_end] = min(abs(Tmsec_base-tf_parm.baseline(2))); 0415 ix_base = ix_base_start:ix_base_end; 0416 data = data./Ntrial; 0417 base = base./Ntrial_base; 0418 data = 10*log10(data./repmat(mean(base(:,ix_base,:),2),[1 T 1])); 0419 0420 % 0421 % Make struct 'TFinfo' 0422 % 0423 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 0424 Jinfo = vb_load_current_info(curr_file); 0425 0426 TFinfo.tf_type = 'ERSP'; 0427 TFinfo.Tmsec = Tmsec; 0428 TFinfo.Ntrial = Ntrial; 0429 TFinfo.ix_act = ix_act; 0430 TFinfo.base = mean(base(:,ix_base,:),2); 0431 0432 if isempty(timefreq_parm), 0433 TFinfo.Tsample = Jinfo.Tsample(ix_time); 0434 TFinfo.Pretrigger = Jinfo.Pretrigger-t_elim; 0435 TFinfo.SampleFreq = Jinfo.SampleFreq; 0436 TFinfo.freq_scale = 'log'; % for wavelet() 0437 else 0438 Tmsec = TFinfo.Tmsec; 0439 [tmp,TFinfo.Pretrigger] = min(abs(Tmsec(:))); 0440 TFinfo.SampleFreq = ((Tmsec(end)-Tmsec(1))./1000)./length(Tmsec); 0441 TFinfo.freq_scale = 'linear'; 0442 end 0443 0444 % 0445 % Save result 0446 % 0447 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 0448 vb_fsave(tf_file_out,'tf_parm','data','TFinfo'); 0449 0450 % 0451 % Save project file 0452 % 0453 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 0454 proj_file = get_project_filename; 0455 if isempty(proj_file), 0456 return; 0457 end 0458 0459 project_file_mgr('load', proj_file); 0460 project_file_mgr('add', 'tf_parm', tf_parm); 0461 0462 return;