Table 2

The parameters for single dataset analysis

field name of cfg.

default value

input

description


surrogatetype (only in TEsurrogatestats.m)

'trialshuffling'

string

surrogate data for trial(n) will be created by replacing trial n of one channel:

'trialshuffling': trial(n+1)

'trialreverse': reverse of trial(n)

'blockresampling': cuts trial(n) at random point and resamples the trial

'blockreverse1': reverse after blockresampling

'blockreverse2': reverse first block after blockresam-pling

'blockreverse3': reverse second block after blockre-sampling


shifttest

'yes'

string

perform shift test to identify instantaneous mixing between the signal pairs. Values: 'yes' or 'no'


shifttesttype

'TE > TEshift'

string

The shift test can be calculated for the direction TE value of original data greater than the TE values of shifted data (value = 'TE > TEshift') or vice versa (value = 'TEshift > TE'). In this case the alpha level for the shift test is set to 0.1.


shifttype

'predicttime'

string

time shift used in shift test: 'onesample' - shift by one sample into the past; 'predicttime' - shift by the time specified in cfg.predicttime_u in TEprepare.m


permstatstype

'indepsamplesT'

string

'mean' to use the distribution of the mean differences and 'depsamplesT' or 'indepsamplesT' for distribution of the t-values.


numpermutation

190100

integer number

number of permutations in the permutation test


tail

2

integer number

1 or 2 tailed test of significance in the permutation test


alpha

.05

number

significance level for the permutation test


correctm

'FDR'

string

correction method used for correction of the multiple comparison problem - false discovery rate 'FDR' or Bonferroni correction 'BONF'


fileidout

string

the first part of the output filename


dim

optimal embedding dimension found in TEprepare

integer number

number of embedding dimensions; if not specified, the optimal dimension found in TEprepare will be used (recommended option!)


Both single subject analyses functions of TRENTOOL TEsurrogatestats.m and TEconditionstatssingle.m require the same input parameters for the input structure cfg. This table contains all possible parameters for the configuration structure cfg of these two functions (TRENTOOL Version 1.0)

For integer numbers no type casting has to be performed!

Lindner et al. BMC Neuroscience 2011 12:119   doi:10.1186/1471-2202-12-119

Open Data