Documentation

Paradigm


Paradigm_MI
paradigm of Motor imagery
input: {'exp_type',-1; 'trig_port','D010'; 'tcpip_port',3000; 'screen_num',2; 'screen_size','full'; 'num_trial',50; 'class',{'right','left'}; 'time_sti','4'; 'time_cross',2.5; 'time_blank', 3; 'rs_time',60}
output: psychotoolbox screen

Analysis


Analysis_MI
analysis of motor imagery
input: file, band, fs, interval,{'nClass',2;'channel',channel_index}
output: [LOSS,CSP,LDA]

preprocessing

prep_selectChannels
select channels with index or name
input: CNT,{'Index',channel_index});
output: CNT
property
      index: input with index number vector
      name: input with name of channels vector

prep_filter
band-pass filter
input: CNT, {'frequency', [8 13]}
output: CNT
Properties
    frequency: frequency band of min and max values

prep_segmentation
segmentation of continuous signals
input: CNT, {'interval', [750 3500]}
output: SMT
properties
     interval: interval time of starting and ending from trigger

training

func_csp
excuting CSP
input: SMT_tr,{'nPatterns',[3]}
output: [SMT_tr_csp,W,D]

func_featureExtraction
input: SMT_tr_csp,{'feature','logvar'}
output: FT_tr

func_train
input: FT_tr,{'classifier','LDA'}
output: CF_PARAM

performance evaluation

func_projection
input: SMT_te, W
output: SMT_te_csp

func_featureExtraction
input: SMT_te_csp,{'feature','logvar'}
output: FT_te

func_predict
input: FT_te, CF_PARAM
output: cf_out

eval_calLoss
input: SMT_te.y_logic, cf_out
output: loss

Visualization


vis_scalpPlot
input: SMT, {'Interval',var_ival; 'Baseline', var_baseline; 'Channels', var_chan; 'ERDERSRange', var_erders_range; 'TimePlot','on'; 'ErspPlot',on; 'ErdPlot','on'}
output: figure with plotting