model.cfg /.para/.json

A design information file lists the onset/duration/type of all events or blocks in your experimental design, and other related information. 

These files can be stored in [.cfg] or [.json] format. 

Design information files may have a combination of the following fields:

             #onsets   : event onset times

Nx2 array (where N is the number of events/blocks modeled) with onset times and condition numbers for each event/block

Onset times (first column) are 0-based indexes to scan/acquisition numbers (when using 'scans' units) or relative times in seconds (when using 'secs' units)

Condition numbers (second column) are 1-based indexes to conditions (integers between 1 and M, where M is the total number of conditions)

             #durations: event durations

Nx1 array with duration of each event/block (alternatively, 1xM array with duration of each condition)

Duration values are specified as number of scans (when using 'scans' units) or durations in seconds (when using 'secs' units)

             #names    : condition (event-type) names

1xM list / cell-array of condition names

Condition names can include any alphanumeric characters except whitespaces

             #units       : units for onset/duration values 

scans / secs (default: scans)

         (optional fields for sparse sampling acquisitions)

              #scan_times  :  scan onset times

L x 1 array (where L is the number of scans/acquisitions) with times of each scan acquisition

Scan onset times  are specified in seconds from the beginning of each run/session (note: irrespective of #units field above)

Event-effects will be resampled at RT*fMRI_T0/fMRI_T after each individual scan onset

              #scan         :  scanner-noise

1/0 value indicating whether an explicit scanner-noise regressor should be included [0]

When set to 1 each scan/acquisition is modeled as an additional event/condition with duration TR. 

SPM effects are named scannernoise

          (optional fields for temporal modulation)

             #tmod     :  temporal modulation

1xM 1/0 array indicating whether condition M is modulated by time

When set to 1, in addition to (average) condition effects, the linear temporal modulation of condition effects is also modeled.

When set to a value greater than 1, higher-order polynomial temporal modulation effects up to the specified level are also included (e.g. 2 for quadratic effects)

SPM effects are named [condition_name]xtime, [condition_name]xtime^2, etc.

           (optional fields for parametric modulation)

             #pmod     : parametric modulation

KxM 1/0 array indicating whether condition M is modulated by covariate K

When set to 1, in addition to (average) condition effects, the condition-by-covariate interactions are also modeled. 

SPM effects are named [condition_name]x[covariate_name]

             #pmod_names  : parametric modulation covariate-names

1xK cell array of covariate names (note: covariate names cannot contain whitespace characters)

             #pmod_values : parametric modulation covariate-values

NxK matrix of covariate values (each covariate defines one value associated with each individual event, e.g. reaction time)

          (optional fields for parametric modulation when the same covariate affects several different conditions)

             #pmod_interaction : parametric modulation/interactions or main-effects only

1xK 1/0 array indicating whether to include condition-by-covariate interactions separately for each covariate

When set to 0, only common parametric covariate effects across all conditions are modeled (c.f. separate effects per condition) [1]

SPM effects are named [covariate_name]

          (optional fields for non-parametric modulation; estimation of individual trial-level effects)

             #npmod    : individual-trial/event effects 

1xM 1/0 array indicating whether condition M is broken down into individual-trial effects

When set to 1, condition effects are estimated separately for each trial. 

SPM effects are named [condition_name]_EVENT[event_number]

         (optional fields only applicable when multiple within-condition effects are estimated)

             #orth     :  orthogonalize within-condition measures

1/0 array indicating whether within-condition regressors should be GS orthogonalized [1]

designID.para example:

% onset_time (in scans units) / task_type

#onsets

0.00 1

4.00 2

8.00 1

13.00 1

16.00 1

20.00 1

24.00 1

30.00 1

36.00 2

42.00 2

45.00 2

48.00 1

52.00 1

55.00 2

60.00 2

65.00 2

70.00 1

75.00 2

79.00 1

82.00 1

85.00 2

88.00 1

94.00 1

97.00 1

104.00 1

107.00 2

111.00 2

115.00 2

120.00 2

126.00 1

131.00 2

134.00 2

138.00 2

143.00 1

147.00 2

153.00 2

160.00 2

163.00 1

166.00 1

172.00 2

% task names

#names

Speech NonSpeech

% task durations (in scans units)

#durations

3 3

% time units (scans/secs)

#units scans