Makes a model specification
To see optional arguments SpecifyModel().inputs_help()
Inputs:
[Mandatory]
functional_runs : (a list of items which are an existing file name or an existing file name)
Data files for model. List of 4D files or list oflist of 3D files per session
input_units : ('secs' or 'scans')
Units of event onsets and durations (secs or scans)
output_units : ('secs' or 'scans')
Units of design event onsets and durations (secs or scans)
subject_id : (a string or an integer)
Subject identifier used as a parameter to the subject_info_func.
subject_info : (a list of items which are any value)
List subject specific condition information
time_repetition : (a float)
Time between the start of one volume to the start of the next image volume.
[Optional]
concatenate_runs : (a boolean)
Concatenating all runs to look like a single session.
high_pass_filter_cutoff : (a float)
High-pass filter cutoff in secs
is_sparse : (a boolean)
indicates whether paradigm is sparse
model_hrf : (a boolean)
model sparse events with hrf
outlier_files : (an existing file name)
Files containing scan outlier indices that should be tossed
realignment_parameters : (an existing file name)
Realignment parameters returned by motion correction algorithm
scan_onset : (a float)
Start of scanning relative to onset of run in secs
stimuli_as_impulses : (a boolean)
Treat each stimulus to be impulse like.
time_acquisition : (a float)
Time in seconds to acquire a single image volume
volumes_in_cluster : (an integer >= 0)
Number of scan volumes in a cluster
Outputs:
session_info session info for level1designs