First and Second Level fMRI Analysis with SPM#
Author: Monika Doerig
Citation:
Wakeman, DG and Henson, RN (2021). Multisubject, multimodal face processing. OpenNeuro. [Dataset] doi: 10.18112/openneuro.ds000117.v1.0.5
Wakeman, D.G. & Henson, R.N. (2015). A multi-subject, multi-modal human neuroimaging dataset. Sci. Data 2:150001 doi: 10.1038/sdata.2015.1
Useful resources:
SPM Tutorial on event-related fMRI: https://www.fil.ion.ucl.ac.uk/spm/docs/tutorials/fmri/event/
SPM Manual, group face fMRI: https://www.fil.ion.ucl.ac.uk/spm/docs/manual/faces_group/face_group/#introduction
SPM Wikibooks, group analysis: https://en.wikibooks.org/wiki/SPM/Group_Analysis / https://www.fil.ion.ucl.ac.uk/spm/docs/wikibooks/Group_Analysis/
Nipype Documentation: fMRI: Famous vs non-famous faces in SPM: https://nipype.readthedocs.io/en/latest/users/examples/fmri_spm_face.html
Setup Neurodesk#
%%capture
import os
import sys
IN_COLAB = 'google.colab' in sys.modules
if IN_COLAB:
os.environ["LD_PRELOAD"] = "";
os.environ["APPTAINER_BINDPATH"] = "/content,/tmp,/cvmfs"
os.environ["MPLCONFIGDIR"] = "/content/matplotlib-mpldir"
os.environ["LMOD_CMD"] = "/usr/share/lmod/lmod/libexec/lmod"
!curl -J -O https://raw.githubusercontent.com/NeuroDesk/neurocommand/main/googlecolab_setup.sh
!chmod +x googlecolab_setup.sh
!./googlecolab_setup.sh
os.environ["MODULEPATH"] = ':'.join(map(str, list(map(lambda x: os.path.join(os.path.abspath('/cvmfs/neurodesk.ardc.edu.au/neurodesk-modules/'), x),os.listdir('/cvmfs/neurodesk.ardc.edu.au/neurodesk-modules/')))))
# Output CPU information:
!cat /proc/cpuinfo | grep 'vendor' | uniq
!cat /proc/cpuinfo | grep 'model name' | uniq
vendor_id : GenuineIntel
model name : Intel(R) Xeon(R) Gold 6126 CPU @ 2.60GHz
Introduction#
The fMRI dataset used for this example is part of a multi-subject, multi-modal (sMRI, fMRI, MEG, EEG) neuroimaging dataset on face processing. It contains data in BIDS format on sixteen healthy volunteers. The data was recoreded while the volunteers performed multiple runs of hundreds of trials of a simple perceptual task on pictures of familiar, unfamiliar and scrambled faces during two visits to the laboratory.
The facial stimuli consisted of two groups of 300 greyscale photos, half of which were of famous people and half of which were of non-famous people (unknown to the participants). Each scrambled face was created either from the famous face or the non-famous face of the same stimulus number. Additionally, each image was presented twice to the participants. The second presentation occurred either immediately after the first presentation (Immediate Repeats) or after 5–15 intervening stimuli (Delayed Repeats), with 50% of each type of repeat. To ensure that each stimulus received equal attention, participants were instructed to use their left or right index finger to press one of two keys (assignment counter-balanced across participants). They determined the symmetry of each image by pressing a key based on whether they perceived it to be ‘more’ or ‘less symmetric’ than average.
In the original paper (Wakeman & Henson, 2015), the repetition manipulation was not distinguished, meaning that initial and repeated presentations were treated identically without considering the timing of the repeats.
To illustrate the setup of a 3x2 factorial design analysis (familiar vs. unfamiliar vs. scrambled faces) x (1st vs. 2nd presentation) in an SPM Nipype workflow, the event files will be adapted accordingly. Each stimulus type will be labeled as either the first or second presentation. However, for simplicity, no distinction is made between immediate and delayed repetitions, resulting in 6 stimulus types (conditions): Familiar-Rep1 (F1), Familiar-Rep2 (F2), Unfamiliar-Rep1 (U1), Unfamiliar-Rep2 (U2), Scrambled-Rep1 (S1), and Scrambled-Rep2 (S2).
Examples of a familiar, unfamiliar and scrambled face:
PATTERN_STIMULI = "stimuli/func/*001.bmp"
!datalad install https://github.com/OpenNeuroDatasets/ds000117.git
!cd ds000117 && datalad get $PATTERN_STIMULI
action summary:
get (notneeded: 6)
import matplotlib.pyplot as plt
from matplotlib.image import imread
# Load the .bmp images
familiar = imread('ds000117/stimuli/func/f001.bmp')
unfamiliar = imread('ds000117/stimuli/func/u001.bmp')
scrambled = imread('ds000117/stimuli/func/s001.bmp')
# Create a Matplotlib figure with subplots
fig, axes = plt.subplots(1, 3, figsize=(12, 4))
# Plot each image on a subplot
axes[0].imshow(familiar, cmap='gray')
axes[0].set_title('Familiar face')
axes[0].axis('off')
axes[1].imshow(unfamiliar, cmap='gray')
axes[1].set_title('Unfamiliar face')
axes[1].axis('off')
axes[2].imshow(scrambled, cmap='gray')
axes[2].set_title('Scrambled face')
axes[2].axis('off')
plt.tight_layout()
plt.show()
Download Data and install Python modules#
# get func data of the mri session of 9 individuals
PATTERN = "sub-0*/ses-mri/func"
!datalad install https://github.com/OpenNeuroDatasets/ds000117.git
!cd ds000117 && datalad get $PATTERN
action summary:
get (notneeded: 9)
# get preprocessed normalized func images of 9 individuals
PATTERN_PREP = "sub-0*/ses-mri/func/*space-MNI152NLin6Asym_desc-smoothAROMAnonaggr_bold.nii.gz"
!datalad install https://github.com/OpenNeuroDerivatives/ds000117-fmriprep.git
!cd ds000117-fmriprep && datalad get $PATTERN_PREP
action summary:
get (notneeded: 81)
# Installations
!pip install nilearn pandas
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Load SPM and import Python and Nipype modules#
import lmod
await lmod.purge(force=True)
await lmod.load('spm12/r7771')
await lmod.list()
['spm12/r7771']
import pandas as pd
import numpy as np
from nilearn import plotting
import matplotlib.pyplot as plt
import json
import os
from os.path import join as opj
from scipy.io import loadmat
import nipype.algorithms.modelgen as model
from nipype.interfaces import spm
from nipype.interfaces.io import DataSink, DataGrabber
from nipype.interfaces.utility import IdentityInterface, Function
from nipype import Node, Workflow, MapNode
from nipype.algorithms.misc import Gunzip
import nipype
NIPYPE_VERSION = nipype.__version__
print(NIPYPE_VERSION)
1.8.6
if NIPYPE_VERSION <= '1.8.6':
print('Contrasts need to be defined manually and wont be computed automatically when they are defined in Level1Design using the factor_info parameter')
# starting in nipype version 1.8.7., when factor_info parameter is used in Level1design T and F contrasts (ess*, con*, spmF* and spmT* images)
# are created automatically by in EstimateModel by SPM
Contrasts need to be defined manually and wont be computed automatically when they are defined in Level1Design using the factor_info parameter
Analysis#
1. First Level Analysis#
Prepare Data Input#
#base directories
data_base_dir = os.getcwd()
experiment_dir = opj(data_base_dir, 'spm_analysis/') #where to store the working and datasink directories
#list of subject identifiers and runs
sub_list = ['01', '02', '03', '04', '05', '06', '07', '08', '09']
#only take run 1 and 2 for computational reasons
run_id = [1,2]
#TR of functional images
with open(opj(data_base_dir,'ds000117/task-facerecognition_bold.json'), 'rt') as fp:
task_info = json.load(fp)
TR = float(task_info['RepetitionTime'])
print('Repetition Time:', TR)
Repetition Time: 2.0
Start the workflow#
wf = Workflow(name='level1_spm', base_dir=experiment_dir)
wf.config["execution"]["crashfile_format"] = "txt"
Input stream#
infosource = Node(IdentityInterface(fields=["subject_id"]),
name="infosource")
infosource.iterables = [("subject_id", sub_list)]
SPM12 can accept NIfTI files as input, but only if they are not compressed (‘unzipped’). Use Gunzip node to unzip the files, before feeding them it to the model specification node.#
gunzip_func = MapNode(Gunzip(), name='gunzip_func', iterfield='in_file')
datagrabber = Node(interface=DataGrabber(
infields=["subject_id","run_id"], outfields=["func", "events"]
), name="datagrabber"
)
# Specify task names and return a sorted filelist to ensure to match files to correct runs
datagrabber.inputs.run_id = run_id
datagrabber.inputs.sort_filelist = True
datagrabber.inputs.template = "*"
datagrabber.inputs.base_directory = data_base_dir
# Define arguments fill the wildcards in the below paths
datagrabber.inputs.template_args = dict(
func=[["subject_id","subject_id","run_id"]],
events=[["subject_id","subject_id", "run_id"]]
)
datagrabber.inputs.field_template = dict(
func= "ds000117-fmriprep/sub-%s/ses-mri/func/sub-%s_ses-mri_task-facerecognition_run-%d_space-MNI152NLin6Asym_desc-smoothAROMAnonaggr_bold.nii.gz",
events="ds000117/sub-%s/ses-mri/func/sub-%s_ses-mri_task-facerecognition_run-0%d_events.tsv",
)
wf.connect([
(infosource, datagrabber, [("subject_id", "subject_id")])])
wf.connect([(datagrabber, gunzip_func, [('func', 'in_file')])])
First-level GLM#
The subsequent task involves obtaining information such as stimuli type, onset, duration, and other regressors for integration into the GLM model. To accomplish this, a helper function needs to be created, which will be referred to as subjectinfo.
A TSV file for each run looks like this:
!cat ds000117/sub-01/ses-mri/func/sub-01_ses-mri_task-facerecognition_run-01_events.tsv
onset duration circle_duration stim_type trigger button_pushed response_time stim_file
0 .908 .534 FAMOUS 5 4 2.158 func/f013.bmp
3.273 .962 .586 FAMOUS 6 4 1.233 func/f013.bmp
6.647 .825 .546 UNFAMILIAR 13 4 1.183 func/u014.bmp
9.838 .968 .597 UNFAMILIAR 14 4 .930 func/u014.bmp
12.978 .904 .415 UNFAMILIAR 13 7 1.068 func/u016.bmp
16.219 .859 .558 UNFAMILIAR 14 7 1.207 func/u016.bmp
19.443 .804 .585 UNFAMILIAR 13 4 1.286 func/u010.bmp
22.55 .879 .526 UNFAMILIAR 14 4 1.008 func/u010.bmp
25.606 .866 .416 SCRAMBLED 17 7 1.929 func/s002.bmp
28.697 .884 .461 SCRAMBLED 18 4 1.300 func/s002.bmp
31.319 20.000 20.000 n/a 999 20000 20.000 func/i999.bmp
51.898 .974 .543 FAMOUS 5 7 2.477 func/f004.bmp
55.173 .925 .534 SCRAMBLED 17 7 1.372 func/s008.bmp
58.313 .985 .439 UNFAMILIAR 13 4 1.431 func/u012.bmp
61.587 .862 .533 FAMOUS 5 4 1.086 func/f012.bmp
64.677 .869 .461 FAMOUS 6 4 1.018 func/f012.bmp
67.75 .804 .446 SCRAMBLED 17 7 1.267 func/s007.bmp
70.774 .873 .445 SCRAMBLED 17 7 1.211 func/s011.bmp
73.881 .983 .466 FAMOUS 7 7 1.203 func/f004.bmp
77.105 .998 .468 SCRAMBLED 17 7 1.240 func/s015.bmp
80.445 .833 .583 SCRAMBLED 19 7 1.379 func/s008.bmp
83.469 .940 .434 FAMOUS 5 7 1.637 func/f006.bmp
86.676 .813 .488 FAMOUS 6 7 1.209 func/f006.bmp
89.833 .994 .570 UNFAMILIAR 15 4 1.444 func/u012.bmp
93.19 .997 .594 FAMOUS 5 7 1.352 func/f009.bmp
96.448 .869 .491 FAMOUS 5 7 1.012 func/f005.bmp
99.655 .821 .571 SCRAMBLED 19 7 1.483 func/s007.bmp
102.695 .933 .437 FAMOUS 5 7 1.228 func/f002.bmp
105.869 .818 .481 FAMOUS 6 7 1.109 func/f002.bmp
108.942 .925 .487 SCRAMBLED 19 7 1.205 func/s011.bmp
111.615 20.000 20.000 n/a 999 20000 20.000 func/i999.bmp
132.144 .980 .498 FAMOUS 5 7 .898 func/f014.bmp
135.351 .833 .458 SCRAMBLED 19 n/a 0 func/s015.bmp
138.541 .999 .591 SCRAMBLED 17 4 1.940 func/s004.bmp
141.849 .868 .548 FAMOUS 5 4 1.366 func/f001.bmp
144.906 .832 .421 FAMOUS 6 4 1.433 func/f001.bmp
147.946 .897 .445 FAMOUS 7 7 .767 func/f009.bmp
151.186 .971 .575 UNFAMILIAR 13 7 1.604 func/u013.bmp
154.393 .978 .458 FAMOUS 7 7 1.137 func/f005.bmp
157.701 .984 .564 FAMOUS 5 7 1.248 func/f015.bmp
161.008 .900 .556 UNFAMILIAR 13 4 1.239 func/u011.bmp
164.265 .828 .594 UNFAMILIAR 14 4 1.269 func/u011.bmp
167.306 .830 .447 FAMOUS 7 7 1.116 func/f014.bmp
170.312 .992 .415 FAMOUS 5 7 1.806 func/f003.bmp
173.519 .942 .442 FAMOUS 6 7 1.361 func/f003.bmp
176.777 .874 .539 SCRAMBLED 19 4 1.363 func/s004.bmp
179.984 .845 .559 SCRAMBLED 17 4 1.131 func/s012.bmp
183.058 .981 .467 SCRAMBLED 17 7 .872 func/s001.bmp
186.365 .880 .559 SCRAMBLED 18 7 1.000 func/s001.bmp
189.422 .858 .414 UNFAMILIAR 15 4 1.095 func/u013.bmp
192.027 20.000 20.000 n/a 999 20000 20.000 func/i999.bmp
212.623 .873 .554 SCRAMBLED 17 4 1.718 func/s006.bmp
215.83 .863 .558 FAMOUS 7 7 1.115 func/f015.bmp
218.937 .984 .479 SCRAMBLED 17 7 1.449 func/s014.bmp
222.178 .873 .487 SCRAMBLED 18 7 .834 func/s014.bmp
225.452 .912 .536 UNFAMILIAR 13 4 1.099 func/u002.bmp
228.559 .952 .419 UNFAMILIAR 14 4 .915 func/u002.bmp
231.733 .891 .465 UNFAMILIAR 13 4 1.023 func/u004.bmp
234.89 .947 .496 UNFAMILIAR 14 4 .953 func/u004.bmp
238.164 .824 .560 SCRAMBLED 19 7 1.068 func/s012.bmp
241.187 .922 .425 FAMOUS 5 4 1.154 func/f011.bmp
244.478 .941 .593 SCRAMBLED 17 7 1.283 func/s005.bmp
247.668 .857 .482 SCRAMBLED 18 7 1.023 func/s005.bmp
250.825 .813 .524 SCRAMBLED 19 7 1.329 func/s006.bmp
253.849 .921 .450 FAMOUS 5 7 1.221 func/f007.bmp
257.072 .903 .528 SCRAMBLED 17 7 .788 func/s016.bmp
260.163 .969 .419 FAMOUS 5 4 1.369 func/f010.bmp
263.403 .892 .516 FAMOUS 6 4 1.183 func/f010.bmp
266.627 .950 .562 SCRAMBLED 17 7 1.326 func/s009.bmp
269.901 .935 .561 SCRAMBLED 18 7 1.010 func/s009.bmp
273.025 .896 .434 FAMOUS 7 7 1.431 func/f011.bmp
275.664 20.000 20.000 n/a 999 20000 20.000 func/i999.bmp
296.109 .895 .410 SCRAMBLED 17 4 1.541 func/s010.bmp
299.233 .908 .452 SCRAMBLED 18 4 1.010 func/s010.bmp
302.373 .866 .457 UNFAMILIAR 13 4 1.137 func/u008.bmp
305.53 .880 .519 FAMOUS 7 7 1.127 func/f007.bmp
308.588 .821 .417 SCRAMBLED 17 7 1.208 func/s003.bmp
311.594 .873 .403 SCRAMBLED 18 7 .965 func/s003.bmp
314.784 .967 .543 SCRAMBLED 19 7 1.126 func/s016.bmp
318.008 .913 .495 SCRAMBLED 17 4 1.137 func/s013.bmp
321.165 .957 .477 UNFAMILIAR 13 4 1.073 func/u007.bmp
324.423 .826 .534 UNFAMILIAR 14 4 .934 func/u007.bmp
327.479 .998 .457 UNFAMILIAR 13 4 1.293 func/u015.bmp
330.77 .981 .534 UNFAMILIAR 13 4 1.075 func/u009.bmp
334.011 .920 .491 UNFAMILIAR 15 4 1.075 func/u008.bmp
337.134 .967 .442 FAMOUS 5 7 .754 func/f008.bmp
340.425 .946 .552 FAMOUS 6 7 .917 func/f008.bmp
343.632 .870 .489 UNFAMILIAR 13 4 1.286 func/u003.bmp
346.839 .990 .552 UNFAMILIAR 14 4 1.141 func/u003.bmp
350.146 .937 .542 SCRAMBLED 19 4 1.334 func/s013.bmp
352.836 20.000 20.000 n/a 999 20000 20.000 func/i999.bmp
373.298 .816 .420 UNFAMILIAR 13 4 1.415 func/u001.bmp
376.455 .837 .577 UNFAMILIAR 14 4 1.247 func/u001.bmp
379.646 .825 .572 UNFAMILIAR 13 7 1.292 func/u006.bmp
382.786 .995 .540 UNFAMILIAR 15 4 1.003 func/u015.bmp
385.993 .976 .447 UNFAMILIAR 13 7 1.536 func/u005.bmp
389.3 .906 .558 UNFAMILIAR 15 4 1.078 func/u009.bmp
392.508 .957 .526 FAMOUS 5 7 1.223 func/f016.bmp
395.264 .012 0 n/a 999 0 0 func/Circle.bmp
As mentioned in the introduction, these event files will be adapted in the function ‘subjectinfo’ to demonstrate the setup of a 3x2 factorial design analysis. The original stimulus types (stim_types) FAMOUS, NONFAMILIAR, SCRAMBLED will be replaced with F1 (first presentation of an image of a famous face)/ F2 (second presentation of image), U1/U2 and S1/S1 due to the first or second occurance of the respective stimulus file (stim_file). In addition, stimuli of stimulus type n/a are deleted.
# Get the subject information: to create a GLM model, Nipype needs a list of Bunch objects per run (session)
def subjectinfo(events):
# packages need to be imported within the function for node to work (function is executed in a standalone environment)
from nipype.interfaces.base import Bunch
import pandas as pd
from collections import OrderedDict
trialinfo = pd.read_table(events)
# Filter out rows where stim_type does not contain 'FAMOUS', 'UNFAMILIAR', or 'SCRAMBLED' --> n/a
trialinfo = trialinfo[trialinfo['stim_type'].isin(['FAMOUS', 'UNFAMILIAR', 'SCRAMBLED'])].reset_index(drop=True)
# Create a dictionary to store the count of occurrences for each stim_file
stim_file_count = {}
# Iterate over each row in the dataframe
for index, row in trialinfo.iterrows():
# Get the stim_file value for the current row
stim_file = row['stim_file']
# If the stim_file is not in the stim_file_count dictionary, add it with count 1
if stim_file not in stim_file_count:
stim_file_count[stim_file] = 1
else:
# Increment the count for the stim_file and update the dictionary
stim_file_count[stim_file] += 1
# Get the count of occurrences for the current stim_file
count = stim_file_count[stim_file]
# Determine the new stim_type based on the stim_file and its count
if 'FAMOUS' in row['stim_type']:
new_stim_type = f'F{count}'
elif 'UNFAMILIAR' in row['stim_type']:
new_stim_type = f'U{count}'
else:
# If it's not 'FAMOUS' or 'UNFAMILIAR', it must be 'SCRAMBLED'
new_stim_type = f'S{count}'
# Update the stim_type in the dataframe
trialinfo.at[index, 'stim_type'] = new_stim_type
# Define the custom sorting order (instead of an alphabetic ordering F1, F2, S1, S2, U1, U2
sorting_order = OrderedDict([('F1', 1), ('F2', 2), ('U1', 3), ('U2', 4), ('S1', 5), ('S2', 6)])
conditions = []
onsets = []
durations = []
# Group trialinfo by 'stim_type' and iterate over groups
grouped_trials = trialinfo.groupby('stim_type')
for group_key in sorting_order.keys(): # Use keys() to iterate over keys
group_data = grouped_trials.get_group(group_key)
conditions.append(group_key)
onsets.append(group_data['onset'].tolist())
durations.append(group_data['duration'].tolist())
subject_info = Bunch(conditions=conditions,
onsets=onsets,
durations=durations)
return subject_info
getsubjectinfo = MapNode(Function(input_names=['events'],
output_names=['subject_info'],
function=subjectinfo),
name='getsubjectinfo', iterfield=['events'])
wf.connect(datagrabber, 'events', getsubjectinfo, 'events')
modelspec = Node(model.SpecifySPMModel(concatenate_runs=True,
input_units = 'secs',
output_units = 'secs',
time_repetition= TR,
high_pass_filter_cutoff=128), #in secs, slow signal drifts with a period > 128 will be removed
name='modelspec')
wf.connect(getsubjectinfo, 'subject_info', modelspec,'subject_info')
wf.connect(gunzip_func, 'out_file', modelspec, 'functional_runs')
Level1Design: canonical HRF#
The design matrix will be constructed without including derivatives of the hemodynamic response function (HRF) and therefore assumes a constant delay and dispersion for the hemodynamic response.
Starting in nipype version 1.8.7., when factor_info parameter is used in Level1design, T and F contrasts (ess*, con*, spmF* and spmT* images) are created automatically in EstimateModel by SPM. They need to be connected directly to a data output module#
The following lines automatically inform SPM to create a default set of contrats for a factorial design.
# Level1Design - Generates an SPM design matrix
level1design = Node(spm.Level1Design(bases={'hrf':{'derivs': [0,0]}}, # no derivatives
timing_units='secs',
interscan_interval=TR,
microtime_onset=8, #The onset/time-bin in seconds for alignment
microtime_resolution=16, #Number of time-bins per scan in secs
mask_threshold=0.8,
global_intensity_normalization='none',
volterra_expansion_order=1, #do not model interactions
model_serial_correlations='AR(1)'), # serial correlations --> autoregressive AR(1) model during Classical (ReML) parameter estimation
name='level1design')
if NIPYPE_VERSION > '1.8.6':
# Factors need to match conditions: product of levels (here 6) needs to match number of condition names --> F1, F2, U1, U2, S1, S2
level1design.inputs.factor_info = [dict(name = 'Face', levels = 3),
dict(name = 'Rep', levels = 2)]
wf.connect(modelspec,'session_info', level1design, 'session_info')
# EstimateModel - estimate the parameters of the model
level1estimate = Node(spm.EstimateModel(estimation_method={'Classical':1}), #EstimateModel2
name='level1estimate')
wf.connect(level1design, 'spm_mat_file', level1estimate, 'spm_mat_file')
Specify GLM contrast for nipype<=1.8.6#
Contrasts need to be set up manually as they are not created automatically in EstimateModel when factor_info parameter is used in Level1Design.
condition_names = ['F1', 'F2', 'U1', 'U2', 'S1', 'S2'] #The condition names must match the names listed in the subjectinfo function described above.
cond1 = ('Positive effect of condition', 'T', condition_names, [1, 1, 1, 1, 1, 1])
# positive effect face
face1 = ('Positive effect of Face_1', 'T', condition_names, [1, 1, -1, -1, 0, 0])
face2 = ('Positive effect of Face_2', 'T', condition_names, [0, 0, 1, 1, -1, -1])
# rep1 > rep2
rep1 = ('Positive effect of Rep', 'T', condition_names, [1, -1, 1, -1, 1, -1])
# positive interaction face x rep
int1 = ('Positive interaction of Face x Rep1', 'T', condition_names, [1, -1, -1, 1, 0, 0])
int2 = ('Positive interaction of Face x Rep2', 'T', condition_names, [0, 0, 1, -1, -1, 1])
contf1 = ['Average effect condition', 'F', [cond1]]
contf2 = ['Main effect Face', 'F', [face1, face2]]
contf3 = ['Main effect Rep', 'F', [rep1]]
contf4 = ['Interaction: Face x Rep', 'F', [int1, int2]]
contrasts = [contf1, contf2, contf3, contf4, cond1, face1, face2, rep1, int1, int2]
# EstimateContrast - explicit contrast estimation with nipype version <= 1.8.6 with the defined contrast list
if NIPYPE_VERSION <= '1.8.6':
level1conest = Node(spm.EstimateContrast(),
name='level1conest')
level1conest.inputs.contrasts = contrasts
wf.connect([(level1estimate, level1conest, [('spm_mat_file','spm_mat_file'),
('beta_images','beta_images'),
('residual_image','residual_image')])])
Output stream#
# save all results into one
datasink = Node(DataSink(), name='sinker')
datasink.inputs.base_directory=opj(experiment_dir, "level1_spm_results")
wf.connect(infosource, 'subject_id', datasink, 'container')
if NIPYPE_VERSION <= '1.8.6':
wf.connect([(level1conest, datasink, [('spm_mat_file', '1stLevel.@spm_mat'),
('spmT_images', '1stLevel.@T'),
('con_images', '1stLevel.@con'),
('spmF_images', '1stLevel.@F'),
('ess_images', '1stLevel.@ess')]),
])
# starting in nipype version 1.8.7., when factor_info parameter is used in Level1Design T and F contrasts (ess*, con*, spmF* and spmT* images)
# are created automatically by SPM in EstimateModel
else:
wf.connect(level1design, 'spm_mat_file', datasink, '1stLevel.@spm_mat')
wf.connect([(level1estimate, datasink, [
('spmT_images', '1stLevel.@T'),
('con_images', '1stLevel.@con'),
('spmF_images', '1stLevel.@F'),
('ess_images', '1stLevel.@ess')]),
])
subFolders = [('%s/1stLevel' % s, 'sub-%s/' % s)
for s in sub_list]
subFolders1 = [('_subject_id_%s'%(s), '')
for s in sub_list]
subFolders.extend(subFolders1)
datasink.inputs.substitutions = subFolders
# Create 1st-level analysis output graph
wf.write_graph(graph2use='colored', format='png', simple_form=True)
# Visualize the graph
from IPython.display import Image
Image(filename=opj(wf.base_dir, wf.name, 'graph.png'))
240613-06:39:48,46 nipype.workflow INFO:
Generated workflow graph: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/graph.png (graph2use=colored, simple_form=True).
wf.run(plugin="MultiProc") #will use all CPUs
#ca. 10 min
240613-06:39:48,76 nipype.workflow INFO:
Workflow level1_spm settings: ['check', 'execution', 'logging', 'monitoring']
240613-06:39:48,125 nipype.workflow INFO:
Running in parallel.
240613-06:39:48,128 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 9 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:39:48,700 nipype.workflow INFO:
[Node] Setting-up "level1_spm.datagrabber" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/datagrabber".
240613-06:39:48,703 nipype.workflow INFO:
[Node] Setting-up "level1_spm.datagrabber" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/datagrabber".
240613-06:39:48,702 nipype.workflow INFO:
[Node] Setting-up "level1_spm.datagrabber" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/datagrabber".
240613-06:39:48,704 nipype.workflow INFO:
[Node] Setting-up "level1_spm.datagrabber" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/datagrabber".
240613-06:39:48,705 nipype.workflow INFO:
[Node] Setting-up "level1_spm.datagrabber" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/datagrabber".
240613-06:39:48,712 nipype.workflow INFO:
[Node] Setting-up "level1_spm.datagrabber" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/datagrabber".
240613-06:39:48,717 nipype.workflow INFO:
[Node] Executing "datagrabber" <nipype.interfaces.io.DataGrabber>
240613-06:39:48,715 nipype.workflow INFO:
[Node] Setting-up "level1_spm.datagrabber" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/datagrabber".
240613-06:39:48,715 nipype.workflow INFO:
[Node] Setting-up "level1_spm.datagrabber" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/datagrabber".
240613-06:39:48,715 nipype.workflow INFO:
[Node] Setting-up "level1_spm.datagrabber" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/datagrabber".
240613-06:39:48,719 nipype.workflow INFO:
[Node] Executing "datagrabber" <nipype.interfaces.io.DataGrabber>
240613-06:39:48,720 nipype.workflow INFO:
[Node] Executing "datagrabber" <nipype.interfaces.io.DataGrabber>
240613-06:39:48,720 nipype.workflow INFO:
[Node] Executing "datagrabber" <nipype.interfaces.io.DataGrabber>
240613-06:39:48,722 nipype.workflow INFO:
[Node] Executing "datagrabber" <nipype.interfaces.io.DataGrabber>
240613-06:39:48,723 nipype.workflow INFO:
[Node] Finished "datagrabber", elapsed time 0.001618s.
240613-06:39:48,724 nipype.workflow INFO:
[Node] Executing "datagrabber" <nipype.interfaces.io.DataGrabber>
240613-06:39:48,724 nipype.workflow INFO:
[Node] Finished "datagrabber", elapsed time 0.001625s.
240613-06:39:48,725 nipype.workflow INFO:
[Node] Executing "datagrabber" <nipype.interfaces.io.DataGrabber>
240613-06:39:48,725 nipype.workflow INFO:
[Node] Finished "datagrabber", elapsed time 0.001606s.
240613-06:39:48,724 nipype.workflow INFO:
[Node] Executing "datagrabber" <nipype.interfaces.io.DataGrabber>
240613-06:39:48,727 nipype.workflow INFO:
[Node] Finished "datagrabber", elapsed time 0.001663s.
240613-06:39:48,727 nipype.workflow INFO:
[Node] Finished "datagrabber", elapsed time 0.001644s.
240613-06:39:48,728 nipype.workflow INFO:
[Node] Executing "datagrabber" <nipype.interfaces.io.DataGrabber>
240613-06:39:48,729 nipype.workflow INFO:
[Node] Finished "datagrabber", elapsed time 0.001556s.
240613-06:39:48,730 nipype.workflow INFO:
[Node] Finished "datagrabber", elapsed time 0.001585s.
240613-06:39:48,732 nipype.workflow INFO:
[Node] Finished "datagrabber", elapsed time 0.00274s.
240613-06:39:48,733 nipype.workflow INFO:
[Node] Finished "datagrabber", elapsed time 0.001423s.
240613-06:39:50,130 nipype.workflow INFO:
[Job 0] Completed (level1_spm.datagrabber).
240613-06:39:50,134 nipype.workflow INFO:
[Job 1] Completed (level1_spm.datagrabber).
240613-06:39:50,136 nipype.workflow INFO:
[Job 2] Completed (level1_spm.datagrabber).
240613-06:39:50,137 nipype.workflow INFO:
[Job 3] Completed (level1_spm.datagrabber).
240613-06:39:50,138 nipype.workflow INFO:
[Job 4] Completed (level1_spm.datagrabber).
240613-06:39:50,140 nipype.workflow INFO:
[Job 5] Completed (level1_spm.datagrabber).
240613-06:39:50,141 nipype.workflow INFO:
[Job 6] Completed (level1_spm.datagrabber).
240613-06:39:50,142 nipype.workflow INFO:
[Job 7] Completed (level1_spm.datagrabber).
240613-06:39:50,144 nipype.workflow INFO:
[Job 8] Completed (level1_spm.datagrabber).
240613-06:39:50,145 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 18 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:39:52,129 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 36 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:39:52,266 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/gunzip_func/mapflow/_gunzip_func1".
240613-06:39:52,266 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/gunzip_func/mapflow/_gunzip_func0".
240613-06:39:52,267 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:52,267 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:52,278 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/gunzip_func/mapflow/_gunzip_func0".
240613-06:39:52,279 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/gunzip_func/mapflow/_gunzip_func1".
240613-06:39:52,289 nipype.workflow INFO:
[Node] Executing "_gunzip_func0" <nipype.algorithms.misc.Gunzip>
240613-06:39:52,290 nipype.workflow INFO:
[Node] Executing "_gunzip_func1" <nipype.algorithms.misc.Gunzip>
240613-06:39:52,290 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo0" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:52,290 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo1" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:52,289 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:52,304 nipype.workflow INFO:
[Node] Executing "_gunzip_func1" <nipype.algorithms.misc.Gunzip>
240613-06:39:52,297 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:52,306 nipype.workflow INFO:
[Node] Executing "_gunzip_func0" <nipype.algorithms.misc.Gunzip>
240613-06:39:52,306 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/gunzip_func/mapflow/_gunzip_func1".
240613-06:39:52,305 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/gunzip_func/mapflow/_gunzip_func0".
240613-06:39:52,316 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo0" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:52,307 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/gunzip_func/mapflow/_gunzip_func0".
240613-06:39:52,307 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:52,306 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:52,354 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo1" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:52,309 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:52,360 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:52,361 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/gunzip_func/mapflow/_gunzip_func1".
240613-06:39:52,361 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/gunzip_func/mapflow/_gunzip_func0".
240613-06:39:52,308 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/gunzip_func/mapflow/_gunzip_func1".
240613-06:39:52,348 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:52,383 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo1" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:52,372 nipype.workflow INFO:
[Node] Executing "_gunzip_func0" <nipype.algorithms.misc.Gunzip>
240613-06:39:52,383 nipype.workflow INFO:
[Node] Executing "_gunzip_func1" <nipype.algorithms.misc.Gunzip>
240613-06:39:52,388 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:52,389 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/gunzip_func/mapflow/_gunzip_func0".
240613-06:39:52,361 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/gunzip_func/mapflow/_gunzip_func1".
240613-06:39:52,347 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:52,383 nipype.workflow INFO:
[Node] Executing "_gunzip_func0" <nipype.algorithms.misc.Gunzip>
240613-06:39:52,390 nipype.workflow INFO:
[Node] Executing "_gunzip_func1" <nipype.algorithms.misc.Gunzip>
240613-06:39:52,388 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:52,428 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo1" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:52,427 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:52,361 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/gunzip_func/mapflow/_gunzip_func0".
240613-06:39:52,428 nipype.workflow INFO:
[Node] Executing "_gunzip_func0" <nipype.algorithms.misc.Gunzip>
240613-06:39:52,410 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/gunzip_func/mapflow/_gunzip_func1".
240613-06:39:52,389 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/gunzip_func/mapflow/_gunzip_func1".
240613-06:39:52,454 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo1" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:52,451 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:52,363 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:52,482 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo0" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:52,481 nipype.workflow INFO:
[Node] Executing "_gunzip_func0" <nipype.algorithms.misc.Gunzip>
240613-06:39:52,476 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo0" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:52,499 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo0" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:52,488 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo0" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:52,506 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo1" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:52,507 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo1" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:52,482 nipype.workflow INFO:
[Node] Executing "_gunzip_func1" <nipype.algorithms.misc.Gunzip>
240613-06:39:52,507 nipype.workflow INFO:
[Node] Executing "_gunzip_func1" <nipype.algorithms.misc.Gunzip>
240613-06:39:52,545 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo0" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:52,347 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:52,347 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/gunzip_func/mapflow/_gunzip_func0".
240613-06:39:52,611 nipype.workflow INFO:
[Node] Executing "_gunzip_func1" <nipype.algorithms.misc.Gunzip>
240613-06:39:52,589 nipype.workflow INFO:
[Node] Executing "_gunzip_func0" <nipype.algorithms.misc.Gunzip>
240613-06:39:52,628 nipype.workflow INFO:
[Node] Executing "_gunzip_func0" <nipype.algorithms.misc.Gunzip>
240613-06:39:52,646 nipype.workflow INFO:
[Node] Executing "_gunzip_func1" <nipype.algorithms.misc.Gunzip>
240613-06:39:52,666 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo0" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:52,666 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo1" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:52,900 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo0", elapsed time 0.581607s.
240613-06:39:52,917 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo1", elapsed time 0.595812s.
240613-06:39:53,117 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo1", elapsed time 0.740315s.
240613-06:39:53,238 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo1", elapsed time 0.830323s.
240613-06:39:53,211 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo1", elapsed time 0.717004s.
240613-06:39:53,647 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo0", elapsed time 1.140628s.
240613-06:39:53,674 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo1", elapsed time 1.091297s.
240613-06:39:53,686 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo0", elapsed time 1.157195s.
240613-06:39:53,743 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo0", elapsed time 1.22757s.
240613-06:39:53,915 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo0", elapsed time 1.159781s.
240613-06:39:54,153 nipype.workflow INFO:
[Job 74] Completed (_getsubjectinfo0).
240613-06:39:54,212 nipype.workflow INFO:
[Job 75] Completed (_getsubjectinfo1).
240613-06:39:54,213 nipype.workflow INFO:
[Job 79] Completed (_getsubjectinfo1).
240613-06:39:54,214 nipype.workflow INFO:
[Job 95] Completed (_getsubjectinfo1).
240613-06:39:54,161 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo0", elapsed time 1.517694s.
240613-06:39:54,215 nipype.workflow INFO:
[Job 98] Completed (_getsubjectinfo0).
240613-06:39:54,216 nipype.workflow INFO:
[Job 99] Completed (_getsubjectinfo1).
240613-06:39:54,217 nipype.workflow INFO:
[Job 102] Completed (_getsubjectinfo0).
240613-06:39:54,218 nipype.workflow INFO:
[Job 103] Completed (_getsubjectinfo1).
240613-06:39:54,146 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo1", elapsed time 1.514954s.
240613-06:39:54,161 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo1", elapsed time 1.584535s.
240613-06:39:54,255 nipype.workflow INFO:
[MultiProc] Running 24 tasks, and 7 jobs ready. Free memory (GB): 214.68/219.48, Free processors: 8/32.
Currently running:
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _getsubjectinfo0
* _gunzip_func1
* _gunzip_func0
* _getsubjectinfo1
* _getsubjectinfo0
* _gunzip_func1
* _gunzip_func0
* _getsubjectinfo1
* _getsubjectinfo0
* _gunzip_func1
* _gunzip_func0
* _getsubjectinfo1
* _getsubjectinfo0
* _gunzip_func1
* _gunzip_func0
* _getsubjectinfo0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
240613-06:39:54,307 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo0", elapsed time 1.6459190000000001s.
240613-06:39:54,505 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo0", elapsed time 1.696907s.
240613-06:39:54,613 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo1", elapsed time 1.8154249999999998s.
240613-06:39:55,99 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/gunzip_func/mapflow/_gunzip_func0".
240613-06:39:55,107 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/gunzip_func/mapflow/_gunzip_func1".
240613-06:39:55,110 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:55,107 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:55,126 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo0" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:55,134 nipype.workflow INFO:
[Node] Executing "_gunzip_func1" <nipype.algorithms.misc.Gunzip>
240613-06:39:55,149 nipype.workflow INFO:
[Node] Executing "_gunzip_func0" <nipype.algorithms.misc.Gunzip>
240613-06:39:55,158 nipype.workflow INFO:
[Node] Executing "_getsubjectinfo1" <nipype.interfaces.utility.wrappers.Function>
240613-06:39:55,143 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:55,153 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:55,162 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:55,204 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo0" - collecting precomputed outputs
240613-06:39:55,204 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo0" - collecting precomputed outputs
240613-06:39:55,211 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo0" - collecting precomputed outputs
240613-06:39:55,212 nipype.workflow INFO:
[Node] "_getsubjectinfo0" found cached.
240613-06:39:55,226 nipype.workflow INFO:
[Node] "_getsubjectinfo0" found cached.
240613-06:39:55,230 nipype.workflow INFO:
[Node] "_getsubjectinfo0" found cached.
240613-06:39:55,231 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:55,251 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:55,271 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo0", elapsed time 0.111534s.
240613-06:39:55,247 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:55,284 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo1" - collecting precomputed outputs
240613-06:39:55,285 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo1" - collecting precomputed outputs
240613-06:39:55,276 nipype.workflow INFO:
[Node] Finished "_getsubjectinfo1", elapsed time 0.102113s.
240613-06:39:55,298 nipype.workflow INFO:
[Node] "_getsubjectinfo1" found cached.
240613-06:39:55,298 nipype.workflow INFO:
[Node] "_getsubjectinfo1" found cached.
240613-06:39:55,298 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo1" - collecting precomputed outputs
240613-06:39:55,328 nipype.workflow INFO:
[Node] "_getsubjectinfo1" found cached.
240613-06:39:56,135 nipype.workflow INFO:
[Job 78] Completed (_getsubjectinfo0).
240613-06:39:56,141 nipype.workflow INFO:
[Job 82] Completed (_getsubjectinfo0).
240613-06:39:56,142 nipype.workflow INFO:
[Job 83] Completed (_getsubjectinfo1).
240613-06:39:56,147 nipype.workflow INFO:
[Job 86] Completed (_getsubjectinfo0).
240613-06:39:56,148 nipype.workflow INFO:
[Job 87] Completed (_getsubjectinfo1).
240613-06:39:56,149 nipype.workflow INFO:
[Job 90] Completed (_getsubjectinfo0).
240613-06:39:56,150 nipype.workflow INFO:
[Job 91] Completed (_getsubjectinfo1).
240613-06:39:56,150 nipype.workflow INFO:
[Job 94] Completed (_getsubjectinfo0).
240613-06:39:56,153 nipype.workflow INFO:
[Job 10] Completed (level1_spm.getsubjectinfo).
240613-06:39:56,162 nipype.workflow INFO:
[Job 22] Completed (level1_spm.getsubjectinfo).
240613-06:39:56,164 nipype.workflow INFO:
[Job 24] Completed (level1_spm.getsubjectinfo).
240613-06:39:56,165 nipype.workflow INFO:
[Job 106] Completed (_getsubjectinfo0).
240613-06:39:56,166 nipype.workflow INFO:
[Job 107] Completed (_getsubjectinfo1).
240613-06:39:56,167 nipype.workflow INFO:
[MultiProc] Running 18 tasks, and 6 jobs ready. Free memory (GB): 215.88/219.48, Free processors: 14/32.
Currently running:
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
240613-06:39:56,626 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:56,648 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:56,645 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:56,652 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:56,664 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:56,670 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo0" - collecting precomputed outputs
240613-06:39:56,684 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo0" - collecting precomputed outputs
240613-06:39:56,689 nipype.workflow INFO:
[Node] "_getsubjectinfo0" found cached.
240613-06:39:56,670 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo0" - collecting precomputed outputs
240613-06:39:56,683 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo0" - collecting precomputed outputs
240613-06:39:56,691 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:56,689 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo0" - collecting precomputed outputs
240613-06:39:56,700 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo1" - collecting precomputed outputs
240613-06:39:56,699 nipype.workflow INFO:
[Node] "_getsubjectinfo0" found cached.
240613-06:39:56,690 nipype.workflow INFO:
[Node] "_getsubjectinfo0" found cached.
240613-06:39:56,703 nipype.workflow INFO:
[Node] "_getsubjectinfo0" found cached.
240613-06:39:56,702 nipype.workflow INFO:
[Node] "_getsubjectinfo0" found cached.
240613-06:39:56,703 nipype.workflow INFO:
[Node] "_getsubjectinfo1" found cached.
240613-06:39:56,707 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:56,703 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/getsubjectinfo/mapflow/_getsubjectinfo0".
240613-06:39:56,708 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:56,711 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:56,710 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:56,716 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo1" - collecting precomputed outputs
240613-06:39:56,724 nipype.workflow INFO:
[Node] "_getsubjectinfo1" found cached.
240613-06:39:56,724 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo1" - collecting precomputed outputs
240613-06:39:56,724 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo1" - collecting precomputed outputs
240613-06:39:56,732 nipype.workflow INFO:
[Node] "_getsubjectinfo1" found cached.
240613-06:39:56,727 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo1" - collecting precomputed outputs
240613-06:39:56,728 nipype.workflow INFO:
[Node] "_getsubjectinfo1" found cached.
240613-06:39:56,737 nipype.workflow INFO:
[Node] "_getsubjectinfo1" found cached.
240613-06:39:56,737 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo0" - collecting precomputed outputs
240613-06:39:56,747 nipype.workflow INFO:
[Node] "_getsubjectinfo0" found cached.
240613-06:39:56,766 nipype.workflow INFO:
[Node] Setting-up "_getsubjectinfo1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/getsubjectinfo/mapflow/_getsubjectinfo1".
240613-06:39:56,783 nipype.workflow INFO:
[Node] Cached "_getsubjectinfo1" - collecting precomputed outputs
240613-06:39:56,787 nipype.workflow INFO:
[Node] "_getsubjectinfo1" found cached.
240613-06:39:58,137 nipype.workflow INFO:
[Job 12] Completed (level1_spm.getsubjectinfo).
240613-06:39:58,144 nipype.workflow INFO:
[Job 14] Completed (level1_spm.getsubjectinfo).
240613-06:39:58,146 nipype.workflow INFO:
[Job 16] Completed (level1_spm.getsubjectinfo).
240613-06:39:58,147 nipype.workflow INFO:
[Job 18] Completed (level1_spm.getsubjectinfo).
240613-06:39:58,149 nipype.workflow INFO:
[Job 20] Completed (level1_spm.getsubjectinfo).
240613-06:39:58,150 nipype.workflow INFO:
[Job 26] Completed (level1_spm.getsubjectinfo).
240613-06:39:58,153 nipype.workflow INFO:
[MultiProc] Running 18 tasks, and 0 jobs ready. Free memory (GB): 215.88/219.48, Free processors: 14/32.
Currently running:
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
240613-06:40:15,638 nipype.workflow INFO:
[Node] Finished "_gunzip_func0", elapsed time 23.128215s.
240613-06:40:16,142 nipype.workflow INFO:
[Job 100] Completed (_gunzip_func0).
240613-06:40:16,160 nipype.workflow INFO:
[MultiProc] Running 17 tasks, and 0 jobs ready. Free memory (GB): 216.08/219.48, Free processors: 15/32.
Currently running:
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
* _gunzip_func1
* _gunzip_func0
240613-06:40:32,632 nipype.workflow INFO:
[Node] Finished "_gunzip_func0", elapsed time 40.132508s.
240613-06:40:32,698 nipype.workflow INFO:
[Node] Finished "_gunzip_func1", elapsed time 40.383246s.
240613-06:40:32,915 nipype.workflow INFO:
[Node] Finished "_gunzip_func0", elapsed time 40.566017s.
240613-06:40:33,174 nipype.workflow INFO:
[Node] Finished "_gunzip_func1", elapsed time 38.021523s.
240613-06:40:33,667 nipype.workflow INFO:
[Node] Finished "_gunzip_func1", elapsed time 41.115592s.
240613-06:40:33,770 nipype.workflow INFO:
[Node] Finished "_gunzip_func1", elapsed time 41.066139s.
240613-06:40:33,800 nipype.workflow INFO:
[Node] Finished "_gunzip_func1", elapsed time 41.185805s.
240613-06:40:33,806 nipype.workflow INFO:
[Node] Finished "_gunzip_func0", elapsed time 41.052042s.
240613-06:40:33,807 nipype.workflow INFO:
[Node] Finished "_gunzip_func1", elapsed time 41.348077s.
240613-06:40:33,865 nipype.workflow INFO:
[Node] Finished "_gunzip_func1", elapsed time 41.102108s.
240613-06:40:33,915 nipype.workflow INFO:
[Node] Finished "_gunzip_func0", elapsed time 41.452969s.
240613-06:40:33,928 nipype.workflow INFO:
[Node] Finished "_gunzip_func0", elapsed time 41.216404s.
240613-06:40:33,947 nipype.workflow INFO:
[Node] Finished "_gunzip_func1", elapsed time 41.647503s.
240613-06:40:33,963 nipype.workflow INFO:
[Node] Finished "_gunzip_func0", elapsed time 41.661571s.
240613-06:40:34,1 nipype.workflow INFO:
[Node] Finished "_gunzip_func1", elapsed time 41.555917s.
240613-06:40:34,124 nipype.workflow INFO:
[Node] Finished "_gunzip_func0", elapsed time 38.961281s.
240613-06:40:34,158 nipype.workflow INFO:
[Job 72] Completed (_gunzip_func0).
240613-06:40:34,159 nipype.workflow INFO:
[Job 73] Completed (_gunzip_func1).
240613-06:40:34,160 nipype.workflow INFO:
[Job 76] Completed (_gunzip_func0).
240613-06:40:34,161 nipype.workflow INFO:
[Job 77] Completed (_gunzip_func1).
240613-06:40:34,162 nipype.workflow INFO:
[Job 80] Completed (_gunzip_func0).
240613-06:40:34,162 nipype.workflow INFO:
[Job 81] Completed (_gunzip_func1).
240613-06:40:34,163 nipype.workflow INFO:
[Job 85] Completed (_gunzip_func1).
240613-06:40:34,164 nipype.workflow INFO:
[Job 88] Completed (_gunzip_func0).
240613-06:40:34,165 nipype.workflow INFO:
[Job 89] Completed (_gunzip_func1).
240613-06:40:34,166 nipype.workflow INFO:
[Job 92] Completed (_gunzip_func0).
240613-06:40:34,167 nipype.workflow INFO:
[Job 93] Completed (_gunzip_func1).
240613-06:40:34,167 nipype.workflow INFO:
[Job 96] Completed (_gunzip_func0).
240613-06:40:34,168 nipype.workflow INFO:
[Job 97] Completed (_gunzip_func1).
240613-06:40:34,168 nipype.workflow INFO:
[Job 101] Completed (_gunzip_func1).
240613-06:40:34,169 nipype.workflow INFO:
[Job 104] Completed (_gunzip_func0).
240613-06:40:34,170 nipype.workflow INFO:
[Job 105] Completed (_gunzip_func1).
240613-06:40:34,172 nipype.workflow INFO:
[MultiProc] Running 1 tasks, and 8 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.
Currently running:
* _gunzip_func0
240613-06:40:34,266 nipype.workflow INFO:
[Node] Finished "_gunzip_func0", elapsed time 41.81803s.
240613-06:40:34,498 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/gunzip_func/mapflow/_gunzip_func0".
240613-06:40:34,498 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/gunzip_func/mapflow/_gunzip_func0".
240613-06:40:34,498 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/gunzip_func/mapflow/_gunzip_func0".
240613-06:40:34,498 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/gunzip_func/mapflow/_gunzip_func0".
240613-06:40:34,498 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/gunzip_func/mapflow/_gunzip_func0".
240613-06:40:34,493 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/gunzip_func/mapflow/_gunzip_func0".
240613-06:40:34,499 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/gunzip_func/mapflow/_gunzip_func0".
240613-06:40:34,498 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/gunzip_func/mapflow/_gunzip_func0".
240613-06:40:34,500 nipype.workflow INFO:
[Node] Cached "_gunzip_func0" - collecting precomputed outputs
240613-06:40:34,501 nipype.workflow INFO:
[Node] Cached "_gunzip_func0" - collecting precomputed outputs
240613-06:40:34,502 nipype.workflow INFO:
[Node] "_gunzip_func0" found cached.
240613-06:40:34,502 nipype.workflow INFO:
[Node] "_gunzip_func0" found cached.
240613-06:40:34,501 nipype.workflow INFO:
[Node] Cached "_gunzip_func0" - collecting precomputed outputs
240613-06:40:34,502 nipype.workflow INFO:
[Node] Cached "_gunzip_func0" - collecting precomputed outputs
240613-06:40:34,503 nipype.workflow INFO:
[Node] Cached "_gunzip_func0" - collecting precomputed outputs
240613-06:40:34,503 nipype.workflow INFO:
[Node] Cached "_gunzip_func0" - collecting precomputed outputs
240613-06:40:34,503 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/gunzip_func/mapflow/_gunzip_func1".
240613-06:40:34,503 nipype.workflow INFO:
[Node] "_gunzip_func0" found cached.
240613-06:40:34,503 nipype.workflow INFO:
[Node] "_gunzip_func0" found cached.
240613-06:40:34,503 nipype.workflow INFO:
[Node] Cached "_gunzip_func0" - collecting precomputed outputs
240613-06:40:34,504 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/gunzip_func/mapflow/_gunzip_func1".
240613-06:40:34,504 nipype.workflow INFO:
[Node] "_gunzip_func0" found cached.
240613-06:40:34,505 nipype.workflow INFO:
[Node] Cached "_gunzip_func0" - collecting precomputed outputs
240613-06:40:34,505 nipype.workflow INFO:
[Node] Cached "_gunzip_func1" - collecting precomputed outputs
240613-06:40:34,506 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/gunzip_func/mapflow/_gunzip_func1".
240613-06:40:34,504 nipype.workflow INFO:
[Node] "_gunzip_func0" found cached.
240613-06:40:34,508 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/gunzip_func/mapflow/_gunzip_func1".
240613-06:40:34,509 nipype.workflow INFO:
[Node] "_gunzip_func1" found cached.
240613-06:40:34,509 nipype.workflow INFO:
[Node] "_gunzip_func0" found cached.
240613-06:40:34,509 nipype.workflow INFO:
[Node] Cached "_gunzip_func1" - collecting precomputed outputs
240613-06:40:34,508 nipype.workflow INFO:
[Node] "_gunzip_func0" found cached.
240613-06:40:34,510 nipype.workflow INFO:
[Node] Cached "_gunzip_func1" - collecting precomputed outputs
240613-06:40:34,510 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/gunzip_func/mapflow/_gunzip_func1".
240613-06:40:34,520 nipype.workflow INFO:
[Node] "_gunzip_func1" found cached.
240613-06:40:34,521 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/gunzip_func/mapflow/_gunzip_func1".
240613-06:40:34,523 nipype.workflow INFO:
[Node] "_gunzip_func1" found cached.
240613-06:40:34,527 nipype.workflow INFO:
[Node] Cached "_gunzip_func1" - collecting precomputed outputs
240613-06:40:34,521 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/gunzip_func/mapflow/_gunzip_func1".
240613-06:40:34,520 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/gunzip_func/mapflow/_gunzip_func1".
240613-06:40:34,536 nipype.workflow INFO:
[Node] "_gunzip_func1" found cached.
240613-06:40:34,529 nipype.workflow INFO:
[Node] Cached "_gunzip_func1" - collecting precomputed outputs
240613-06:40:34,537 nipype.workflow INFO:
[Node] Cached "_gunzip_func1" - collecting precomputed outputs
240613-06:40:34,537 nipype.workflow INFO:
[Node] Cached "_gunzip_func1" - collecting precomputed outputs
240613-06:40:34,537 nipype.workflow INFO:
[Node] Cached "_gunzip_func1" - collecting precomputed outputs
240613-06:40:34,538 nipype.workflow INFO:
[Node] "_gunzip_func1" found cached.
240613-06:40:34,538 nipype.workflow INFO:
[Node] "_gunzip_func1" found cached.
240613-06:40:34,538 nipype.workflow INFO:
[Node] "_gunzip_func1" found cached.
240613-06:40:34,545 nipype.workflow INFO:
[Node] "_gunzip_func1" found cached.
240613-06:40:36,159 nipype.workflow INFO:
[Job 84] Completed (_gunzip_func0).
240613-06:40:36,160 nipype.workflow INFO:
[Job 9] Completed (level1_spm.gunzip_func).
240613-06:40:36,161 nipype.workflow INFO:
[Job 11] Completed (level1_spm.gunzip_func).
240613-06:40:36,162 nipype.workflow INFO:
[Job 13] Completed (level1_spm.gunzip_func).
240613-06:40:36,163 nipype.workflow INFO:
[Job 17] Completed (level1_spm.gunzip_func).
240613-06:40:36,164 nipype.workflow INFO:
[Job 19] Completed (level1_spm.gunzip_func).
240613-06:40:36,165 nipype.workflow INFO:
[Job 21] Completed (level1_spm.gunzip_func).
240613-06:40:36,166 nipype.workflow INFO:
[Job 23] Completed (level1_spm.gunzip_func).
240613-06:40:36,167 nipype.workflow INFO:
[Job 25] Completed (level1_spm.gunzip_func).
240613-06:40:36,175 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 9 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:40:36,334 nipype.workflow INFO:
[Node] Setting-up "level1_spm.modelspec" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/modelspec".
240613-06:40:36,334 nipype.workflow INFO:
[Node] Setting-up "level1_spm.modelspec" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/modelspec".
240613-06:40:36,334 nipype.workflow INFO:
[Node] Setting-up "level1_spm.modelspec" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/modelspec".
240613-06:40:36,349 nipype.workflow INFO:
[Node] Setting-up "level1_spm.modelspec" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/modelspec".
240613-06:40:36,349 nipype.workflow INFO:
[Node] Setting-up "level1_spm.modelspec" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/modelspec".
240613-06:40:36,349 nipype.workflow INFO:
[Node] Setting-up "level1_spm.modelspec" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/modelspec".
240613-06:40:36,348 nipype.workflow INFO:
[Node] Setting-up "level1_spm.modelspec" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/modelspec".
240613-06:40:36,348 nipype.workflow INFO:
[Node] Setting-up "level1_spm.modelspec" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/modelspec".
240613-06:40:36,368 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/gunzip_func/mapflow/_gunzip_func0".
240613-06:40:36,370 nipype.workflow INFO:
[Node] Executing "modelspec" <nipype.algorithms.modelgen.SpecifySPMModel>
240613-06:40:36,370 nipype.workflow INFO:
[Node] Executing "modelspec" <nipype.algorithms.modelgen.SpecifySPMModel>
240613-06:40:36,369 nipype.workflow INFO:
[Node] Executing "modelspec" <nipype.algorithms.modelgen.SpecifySPMModel>
240613-06:40:36,370 nipype.workflow INFO:
[Node] Executing "modelspec" <nipype.algorithms.modelgen.SpecifySPMModel>
240613-06:40:36,370 nipype.workflow INFO:
[Node] Executing "modelspec" <nipype.algorithms.modelgen.SpecifySPMModel>
240613-06:40:36,369 nipype.workflow INFO:
[Node] Executing "modelspec" <nipype.algorithms.modelgen.SpecifySPMModel>
240613-06:40:36,371 nipype.workflow INFO:
[Node] Cached "_gunzip_func0" - collecting precomputed outputs
240613-06:40:36,372 nipype.workflow INFO:
[Node] Executing "modelspec" <nipype.algorithms.modelgen.SpecifySPMModel>
240613-06:40:36,373 nipype.workflow INFO:
[Node] "_gunzip_func0" found cached.
240613-06:40:36,373 nipype.workflow INFO:
[Node] Executing "modelspec" <nipype.algorithms.modelgen.SpecifySPMModel>
240613-06:40:36,374 nipype.workflow INFO:
[Node] Setting-up "_gunzip_func1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/gunzip_func/mapflow/_gunzip_func1".
240613-06:40:36,388 nipype.workflow INFO:
[Node] Cached "_gunzip_func1" - collecting precomputed outputs
240613-06:40:36,390 nipype.workflow INFO:
[Node] "_gunzip_func1" found cached.
240613-06:40:36,402 nipype.workflow INFO:
[Node] Finished "modelspec", elapsed time 0.029773s.
240613-06:40:36,403 nipype.workflow INFO:
[Node] Finished "modelspec", elapsed time 0.031097s.
240613-06:40:36,404 nipype.workflow INFO:
[Node] Finished "modelspec", elapsed time 0.03211s.
240613-06:40:36,417 nipype.workflow INFO:
[Node] Finished "modelspec", elapsed time 0.031377s.
240613-06:40:36,404 nipype.workflow INFO:
[Node] Finished "modelspec", elapsed time 0.031388s.
240613-06:40:36,418 nipype.workflow INFO:
[Node] Finished "modelspec", elapsed time 0.044186s.
240613-06:40:36,420 nipype.workflow INFO:
[Node] Finished "modelspec", elapsed time 0.046569s.
240613-06:40:36,428 nipype.workflow INFO:
[Node] Finished "modelspec", elapsed time 0.039876s.
240613-06:40:38,159 nipype.workflow INFO:
[Job 15] Completed (level1_spm.gunzip_func).
240613-06:40:38,164 nipype.workflow INFO:
[Job 27] Completed (level1_spm.modelspec).
240613-06:40:38,171 nipype.workflow INFO:
[Job 28] Completed (level1_spm.modelspec).
240613-06:40:38,172 nipype.workflow INFO:
[Job 29] Completed (level1_spm.modelspec).
240613-06:40:38,173 nipype.workflow INFO:
[Job 31] Completed (level1_spm.modelspec).
240613-06:40:38,174 nipype.workflow INFO:
[Job 32] Completed (level1_spm.modelspec).
240613-06:40:38,175 nipype.workflow INFO:
[Job 33] Completed (level1_spm.modelspec).
240613-06:40:38,176 nipype.workflow INFO:
[Job 34] Completed (level1_spm.modelspec).
240613-06:40:38,177 nipype.workflow INFO:
[Job 35] Completed (level1_spm.modelspec).
240613-06:40:38,179 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 9 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:40:38,331 nipype.workflow INFO:
[Node] Setting-up "level1_spm.modelspec" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/modelspec".
240613-06:40:38,332 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1design" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/level1design".
240613-06:40:38,333 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1design" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/level1design".
240613-06:40:38,333 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1design" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/level1design".
240613-06:40:38,341 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1design" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/level1design".
240613-06:40:38,340 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1design" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/level1design".
240613-06:40:38,358 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1design" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/level1design".
240613-06:40:38,358 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1design" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/level1design".
240613-06:40:38,360 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1design" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/level1design".
240613-06:40:38,385 nipype.workflow INFO:
[Node] Executing "level1design" <nipype.interfaces.spm.model.Level1Design>
240613-06:40:38,393 nipype.workflow INFO:
[Node] Executing "level1design" <nipype.interfaces.spm.model.Level1Design>
240613-06:40:38,393 nipype.workflow INFO:
[Node] Executing "level1design" <nipype.interfaces.spm.model.Level1Design>
240613-06:40:38,393 nipype.workflow INFO:
[Node] Executing "level1design" <nipype.interfaces.spm.model.Level1Design>
240613-06:40:38,395 nipype.workflow INFO:
[Node] Executing "level1design" <nipype.interfaces.spm.model.Level1Design>
240613-06:40:38,396 nipype.workflow INFO:
[Node] Executing "level1design" <nipype.interfaces.spm.model.Level1Design>
240613-06:40:38,397 nipype.workflow INFO:
[Node] Executing "level1design" <nipype.interfaces.spm.model.Level1Design>
240613-06:40:38,404 nipype.workflow INFO:
[Node] Executing "level1design" <nipype.interfaces.spm.model.Level1Design>
240613-06:40:38,530 nipype.workflow INFO:
[Node] Executing "modelspec" <nipype.algorithms.modelgen.SpecifySPMModel>
240613-06:40:38,563 nipype.workflow INFO:
[Node] Finished "modelspec", elapsed time 0.028673s.
240613-06:40:40,159 nipype.workflow INFO:
[Job 30] Completed (level1_spm.modelspec).
240613-06:40:40,161 nipype.workflow INFO:
[MultiProc] Running 8 tasks, and 1 jobs ready. Free memory (GB): 217.88/219.48, Free processors: 24/32.
Currently running:
* level1_spm.level1design
* level1_spm.level1design
* level1_spm.level1design
* level1_spm.level1design
* level1_spm.level1design
* level1_spm.level1design
* level1_spm.level1design
* level1_spm.level1design
240613-06:40:40,322 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1design" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/level1design".
240613-06:40:40,382 nipype.workflow INFO:
[Node] Executing "level1design" <nipype.interfaces.spm.model.Level1Design>
240613-06:40:42,198 nipype.workflow INFO:
[MultiProc] Running 9 tasks, and 0 jobs ready. Free memory (GB): 217.68/219.48, Free processors: 23/32.
Currently running:
* level1_spm.level1design
* level1_spm.level1design
* level1_spm.level1design
* level1_spm.level1design
* level1_spm.level1design
* level1_spm.level1design
* level1_spm.level1design
* level1_spm.level1design
* level1_spm.level1design
240613-06:41:42,353 nipype.workflow INFO:
[Node] Finished "level1design", elapsed time 63.956473s.
240613-06:41:43,926 nipype.workflow INFO:
[Node] Finished "level1design", elapsed time 65.499334s.
240613-06:41:43,926 nipype.workflow INFO:
[Node] Finished "level1design", elapsed time 65.532317s.
240613-06:41:43,990 nipype.workflow INFO:
[Node] Finished "level1design", elapsed time 63.605568s.
240613-06:41:43,991 nipype.workflow INFO:
[Node] Finished "level1design", elapsed time 65.580354s.
240613-06:41:43,991 nipype.workflow INFO:
[Node] Finished "level1design", elapsed time 65.593839s.
240613-06:41:44,72 nipype.workflow INFO:
[Node] Finished "level1design", elapsed time 65.676236s.
240613-06:41:44,91 nipype.workflow INFO:
[Node] Finished "level1design", elapsed time 65.695045s.
240613-06:41:44,93 nipype.workflow INFO:
[Node] Finished "level1design", elapsed time 65.665607s.
240613-06:41:44,225 nipype.workflow INFO:
[Job 36] Completed (level1_spm.level1design).
240613-06:41:44,226 nipype.workflow INFO:
[Job 37] Completed (level1_spm.level1design).
240613-06:41:44,227 nipype.workflow INFO:
[Job 38] Completed (level1_spm.level1design).
240613-06:41:44,228 nipype.workflow INFO:
[Job 40] Completed (level1_spm.level1design).
240613-06:41:44,229 nipype.workflow INFO:
[Job 41] Completed (level1_spm.level1design).
240613-06:41:44,230 nipype.workflow INFO:
[Job 42] Completed (level1_spm.level1design).
240613-06:41:44,231 nipype.workflow INFO:
[Job 43] Completed (level1_spm.level1design).
240613-06:41:44,232 nipype.workflow INFO:
[Job 44] Completed (level1_spm.level1design).
240613-06:41:44,233 nipype.workflow INFO:
[Job 39] Completed (level1_spm.level1design).
240613-06:41:44,235 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 9 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:41:44,402 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/level1estimate".
240613-06:41:44,417 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/level1estimate".
240613-06:41:44,402 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/level1estimate".
240613-06:41:44,425 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/level1estimate".
240613-06:41:44,402 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/level1estimate".
240613-06:41:44,437 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/level1estimate".
240613-06:41:44,441 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/level1estimate".
240613-06:41:44,449 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/level1estimate".
240613-06:41:44,454 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/level1estimate".
240613-06:41:44,500 nipype.workflow INFO:
[Node] Executing "level1estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:41:44,517 nipype.workflow INFO:
[Node] Executing "level1estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:41:44,506 nipype.workflow INFO:
[Node] Executing "level1estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:41:44,507 nipype.workflow INFO:
[Node] Executing "level1estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:41:44,521 nipype.workflow INFO:
[Node] Executing "level1estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:41:44,521 nipype.workflow INFO:
[Node] Executing "level1estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:41:44,521 nipype.workflow INFO:
[Node] Executing "level1estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:41:44,521 nipype.workflow INFO:
[Node] Executing "level1estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:41:44,521 nipype.workflow INFO:
[Node] Executing "level1estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:41:46,225 nipype.workflow INFO:
[MultiProc] Running 9 tasks, and 0 jobs ready. Free memory (GB): 217.68/219.48, Free processors: 23/32.
Currently running:
* level1_spm.level1estimate
* level1_spm.level1estimate
* level1_spm.level1estimate
* level1_spm.level1estimate
* level1_spm.level1estimate
* level1_spm.level1estimate
* level1_spm.level1estimate
* level1_spm.level1estimate
* level1_spm.level1estimate
240613-06:43:36,646 nipype.workflow INFO:
[Node] Finished "level1estimate", elapsed time 112.114152s.
240613-06:43:37,402 nipype.workflow INFO:
[Node] Finished "level1estimate", elapsed time 112.870713s.
240613-06:43:37,645 nipype.workflow INFO:
[Node] Finished "level1estimate", elapsed time 113.118144s.
240613-06:43:37,690 nipype.workflow INFO:
[Node] Finished "level1estimate", elapsed time 113.146s.
240613-06:43:37,706 nipype.workflow INFO:
[Node] Finished "level1estimate", elapsed time 113.169625s.
240613-06:43:37,739 nipype.workflow INFO:
[Node] Finished "level1estimate", elapsed time 113.207248s.
240613-06:43:37,831 nipype.workflow INFO:
[Node] Finished "level1estimate", elapsed time 113.287801s.
240613-06:43:37,844 nipype.workflow INFO:
[Node] Finished "level1estimate", elapsed time 113.307623s.
240613-06:43:37,845 nipype.workflow INFO:
[Node] Finished "level1estimate", elapsed time 113.313924s.
240613-06:43:38,283 nipype.workflow INFO:
[Job 45] Completed (level1_spm.level1estimate).
240613-06:43:38,285 nipype.workflow INFO:
[Job 46] Completed (level1_spm.level1estimate).
240613-06:43:38,287 nipype.workflow INFO:
[Job 47] Completed (level1_spm.level1estimate).
240613-06:43:38,288 nipype.workflow INFO:
[Job 48] Completed (level1_spm.level1estimate).
240613-06:43:38,289 nipype.workflow INFO:
[Job 49] Completed (level1_spm.level1estimate).
240613-06:43:38,290 nipype.workflow INFO:
[Job 50] Completed (level1_spm.level1estimate).
240613-06:43:38,291 nipype.workflow INFO:
[Job 51] Completed (level1_spm.level1estimate).
240613-06:43:38,293 nipype.workflow INFO:
[Job 52] Completed (level1_spm.level1estimate).
240613-06:43:38,294 nipype.workflow INFO:
[Job 53] Completed (level1_spm.level1estimate).
240613-06:43:38,296 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 9 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:43:38,502 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1conest" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/level1conest".
240613-06:43:38,504 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1conest" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/level1conest".
240613-06:43:38,538 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1conest" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/level1conest".
240613-06:43:38,548 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1conest" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/level1conest".
240613-06:43:38,540 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1conest" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/level1conest".
240613-06:43:38,595 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1conest" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/level1conest".
240613-06:43:38,603 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1conest" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/level1conest".
240613-06:43:38,577 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1conest" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/level1conest".
240613-06:43:38,606 nipype.workflow INFO:
[Node] Setting-up "level1_spm.level1conest" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/level1conest".
240613-06:43:38,675 nipype.workflow INFO:
[Node] Executing "level1conest" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:43:38,682 nipype.workflow INFO:
[Node] Executing "level1conest" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:43:38,711 nipype.workflow INFO:
[Node] Executing "level1conest" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:43:38,711 nipype.workflow INFO:
[Node] Executing "level1conest" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:43:38,713 nipype.workflow INFO:
[Node] Executing "level1conest" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:43:38,715 nipype.workflow INFO:
[Node] Executing "level1conest" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:43:38,715 nipype.workflow INFO:
[Node] Executing "level1conest" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:43:38,716 nipype.workflow INFO:
[Node] Executing "level1conest" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:43:38,723 nipype.workflow INFO:
[Node] Executing "level1conest" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:43:40,284 nipype.workflow INFO:
[MultiProc] Running 9 tasks, and 0 jobs ready. Free memory (GB): 217.68/219.48, Free processors: 23/32.
Currently running:
* level1_spm.level1conest
* level1_spm.level1conest
* level1_spm.level1conest
* level1_spm.level1conest
* level1_spm.level1conest
* level1_spm.level1conest
* level1_spm.level1conest
* level1_spm.level1conest
* level1_spm.level1conest
240613-06:44:06,134 nipype.workflow INFO:
[Node] Finished "level1conest", elapsed time 27.402464s.
240613-06:44:06,139 nipype.workflow INFO:
[Node] Finished "level1conest", elapsed time 27.449268s.
240613-06:44:06,141 nipype.workflow INFO:
[Node] Finished "level1conest", elapsed time 27.417092s.
240613-06:44:06,159 nipype.workflow INFO:
[Node] Finished "level1conest", elapsed time 27.435406s.
240613-06:44:06,161 nipype.workflow INFO:
[Node] Finished "level1conest", elapsed time 27.437036s.
240613-06:44:06,172 nipype.workflow INFO:
[Node] Finished "level1conest", elapsed time 27.458638s.
240613-06:44:06,181 nipype.workflow INFO:
[Node] Finished "level1conest", elapsed time 27.467807s.
240613-06:44:06,182 nipype.workflow INFO:
[Node] Finished "level1conest", elapsed time 27.457296s.
240613-06:44:06,195 nipype.workflow INFO:
[Node] Finished "level1conest", elapsed time 27.504365s.
240613-06:44:06,286 nipype.workflow INFO:
[Job 54] Completed (level1_spm.level1conest).
240613-06:44:06,288 nipype.workflow INFO:
[Job 55] Completed (level1_spm.level1conest).
240613-06:44:06,289 nipype.workflow INFO:
[Job 56] Completed (level1_spm.level1conest).
240613-06:44:06,289 nipype.workflow INFO:
[Job 57] Completed (level1_spm.level1conest).
240613-06:44:06,290 nipype.workflow INFO:
[Job 58] Completed (level1_spm.level1conest).
240613-06:44:06,292 nipype.workflow INFO:
[Job 59] Completed (level1_spm.level1conest).
240613-06:44:06,293 nipype.workflow INFO:
[Job 60] Completed (level1_spm.level1conest).
240613-06:44:06,293 nipype.workflow INFO:
[Job 61] Completed (level1_spm.level1conest).
240613-06:44:06,294 nipype.workflow INFO:
[Job 62] Completed (level1_spm.level1conest).
240613-06:44:06,296 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 9 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:44:06,480 nipype.workflow INFO:
[Node] Setting-up "level1_spm.sinker" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_01/sinker".
240613-06:44:06,505 nipype.workflow INFO:
[Node] Setting-up "level1_spm.sinker" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_03/sinker".
240613-06:44:06,511 nipype.workflow INFO:
[Node] Setting-up "level1_spm.sinker" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_06/sinker".
240613-06:44:06,501 nipype.workflow INFO:
[Node] Setting-up "level1_spm.sinker" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_02/sinker".
240613-06:44:06,528 nipype.workflow INFO:
[Node] Setting-up "level1_spm.sinker" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_08/sinker".
240613-06:44:06,511 nipype.workflow INFO:
[Node] Setting-up "level1_spm.sinker" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_04/sinker".
240613-06:44:06,526 nipype.workflow INFO:
[Node] Setting-up "level1_spm.sinker" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_07/sinker".
240613-06:44:06,539 nipype.workflow INFO:
[Node] Setting-up "level1_spm.sinker" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_09/sinker".
240613-06:44:06,535 nipype.workflow INFO:
[Node] Setting-up "level1_spm.sinker" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm/_subject_id_05/sinker".
240613-06:44:06,577 nipype.workflow INFO:
[Node] Executing "sinker" <nipype.interfaces.io.DataSink>
240613-06:44:06,577 nipype.workflow INFO:
[Node] Executing "sinker" <nipype.interfaces.io.DataSink>
240613-06:44:06,577 nipype.workflow INFO:
[Node] Executing "sinker" <nipype.interfaces.io.DataSink>
240613-06:44:06,578 nipype.workflow INFO:
[Node] Executing "sinker" <nipype.interfaces.io.DataSink>
240613-06:44:06,578 nipype.workflow INFO:
[Node] Executing "sinker" <nipype.interfaces.io.DataSink>
240613-06:44:06,579 nipype.workflow INFO:
[Node] Executing "sinker" <nipype.interfaces.io.DataSink>
240613-06:44:06,579 nipype.workflow INFO:
[Node] Executing "sinker" <nipype.interfaces.io.DataSink>
240613-06:44:06,579 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///SPM.mat
240613-06:44:06,579 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///SPM.mat
240613-06:44:06,580 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///SPM.mat
240613-06:44:06,587 nipype.workflow INFO:
[Node] Executing "sinker" <nipype.interfaces.io.DataSink>
240613-06:44:06,587 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///spmF_0001.nii
240613-06:44:06,598 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///spmF_0001.nii
240613-06:44:06,598 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmF_0001.nii
240613-06:44:06,598 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///SPM.mat
240613-06:44:06,598 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///SPM.mat
240613-06:44:06,598 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///SPM.mat
240613-06:44:06,598 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///SPM.mat
240613-06:44:06,599 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///SPM.mat
240613-06:44:06,599 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///spmF_0002.nii
240613-06:44:06,600 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmF_0002.nii
240613-06:44:06,600 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///spmF_0002.nii
240613-06:44:06,600 nipype.workflow INFO:
[Node] Executing "sinker" <nipype.interfaces.io.DataSink>
240613-06:44:06,601 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///spmF_0001.nii
240613-06:44:06,603 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///spmF_0001.nii
240613-06:44:06,603 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmF_0001.nii
240613-06:44:06,601 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///spmF_0001.nii
240613-06:44:06,603 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmF_0003.nii
240613-06:44:06,603 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///spmF_0003.nii
240613-06:44:06,603 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/08/1stLevel/_subject_id_08/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-08///spmF_0003.nii
240613-06:44:06,603 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///spmF_0001.nii
240613-06:44:06,603 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///spmF_0002.nii
240613-06:44:06,604 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmF_0002.nii
240613-06:44:06,604 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///spmF_0002.nii
240613-06:44:06,604 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///spmF_0002.nii
240613-06:44:06,604 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///spmF_0004.nii
240613-06:44:06,605 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmF_0003.nii
240613-06:44:06,604 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmF_0004.nii
240613-06:44:06,605 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///SPM.mat
240613-06:44:06,605 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/spmF_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///spmF_0002.nii
240613-06:44:06,605 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///spmF_0003.nii
240613-06:44:06,606 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/09/1stLevel/_subject_id_09/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-09///spmF_0003.nii
240613-06:44:06,605 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/03/1stLevel/_subject_id_03/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-03///spmF_0003.nii
240613-06:44:06,607 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/spmT_0005.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///spmT_0005.nii
240613-06:44:06,607 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/04/1stLevel/_subject_id_04/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-04///spmF_0004.nii
240613-06:44:06,607 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/05/1stLevel/_subject_id_05/spmF_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-05///spmF_0001.nii
240613-06:44:06,607 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/01/1stLevel/_subject_id_01/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-01///spmF_0004.nii
240613-06:44:06,608 nipype.interface INFO:
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sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/07/1stLevel/_subject_id_07/ess_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-07///ess_0002.nii
240613-06:44:06,663 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///ess_0003.nii
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240613-06:44:06,669 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/06/1stLevel/_subject_id_06/ess_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-06///ess_0004.nii
240613-06:44:06,669 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/spmF_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///spmF_0004.nii
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240613-06:44:06,671 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/ess_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///ess_0001.nii
240613-06:44:06,671 nipype.workflow INFO:
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240613-06:44:06,672 nipype.interface INFO:
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240613-06:44:06,671 nipype.workflow INFO:
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240613-06:44:06,678 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/02/1stLevel/_subject_id_02/ess_0004.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level1_spm_results/sub-02///ess_0004.nii
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[Job 63] Completed (level1_spm.sinker).
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[MultiProc] Running 0 tasks, and 0 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
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<networkx.classes.digraph.DiGraph at 0x7fd2be527810>
Visualize design matrix and list contrasts#
spmmat = loadmat(opj(experiment_dir, 'level1_spm_results/sub-01/SPM.mat'), struct_as_record=False)
designMatrix = spmmat['SPM'][0][0].xX[0][0].X
names =[i[0] for i in spmmat['SPM'][0][0].xX[0][0].name[0]]
names_contrast = [spmmat['SPM'][0][0].xCon[0][i].name[0] for i in range(spmmat['SPM'][0][0].xCon.shape[1])]
normed_design=designMatrix / np.abs(designMatrix).max(axis=0)
fig,ax = plt.subplots(figsize=(8,8))
plt.imshow(normed_design, aspect='auto', cmap='gray')
ax.set_ylabel('Volume id')
ax.set_xticks(np.arange(len(names)))
ax.set_xticklabels(names, rotation=90);
data = []
xCon_array = spmmat['SPM'][0][0].xCon[0]
# Iterate over each struct in the xCon array, nested loop, iterate over Vspm and Vcon to get filenames
for struct in xCon_array:
name = struct.name[0]
stat = struct.STAT[0]
c = struct.c.flatten().tolist()
vspm = struct.Vspm[0]
vcon = struct.Vcon[0]
for st in vspm:
vspm_name = st.fname[0]
for s in vcon:
vcon_name = s.fname[0]
data.append({"Name": name, "STAT": stat, "c": c, "spm_file": vspm_name, "con_file": vcon_name})
df = pd.DataFrame(data)
df_string = df.to_string(index=False)
print(df_string)
Name STAT c spm_file con_file
Average effect condition F [1, 1, 1, 1, 1, 1, 0, 0] spmF_0001.nii ess_0001.nii
Main effect Face F [1, 0, 1, 0, -1, 1, -1, 1, 0, -1, 0, -1, 0, 0, 0, 0] spmF_0002.nii ess_0002.nii
Main effect Rep F [1, -1, 1, -1, 1, -1, 0, 0] spmF_0003.nii ess_0003.nii
Interaction: Face x Rep F [1, 0, -1, 0, -1, 1, 1, -1, 0, -1, 0, 1, 0, 0, 0, 0] spmF_0004.nii ess_0004.nii
Positive effect of condition T [1, 1, 1, 1, 1, 1, 0, 0] spmT_0005.nii con_0005.nii
Positive effect of Face_1 T [1, 1, -1, -1, 0, 0, 0, 0] spmT_0006.nii con_0006.nii
Positive effect of Face_2 T [0, 0, 1, 1, -1, -1, 0, 0] spmT_0007.nii con_0007.nii
Positive effect of Rep T [1, -1, 1, -1, 1, -1, 0, 0] spmT_0008.nii con_0008.nii
Positive interaction of Face x Rep1 T [1, -1, -1, 1, 0, 0, 0, 0] spmT_0009.nii con_0009.nii
Positive interaction of Face x Rep2 T [0, 0, 1, -1, -1, 1, 0, 0] spmT_0010.nii con_0010.nii
2. Second Level Analysis#
For a factorial design with 2 factors there are 4 effects to test for: an overall effect, 2 main effects and one two-way interaction:
To test (1) the overall effect, use a [1 1 1 1 1 1] contrast for each subject and take the resulting con images of all subjects into a one-sample t-test at the second level. Then specify a [1] F-contrast (at the second level) to test for significantly non-zero BOLD responses related to the paradigm.
To test for (2) the main effect of Factor Repetition (two levels), use a [1 -1 1 -1 1 -1] contrast for each subject and take the resulting con images into a one-sample t-test at the second level.
To test for (3) the main effect of Factor Face (three levels), use two contrasts per subject [1 1 -1 -1 0 0] and [0 0 1 1 -1 -1] and take all resulting con images (two per subject) into a two-sample t-test design at the second level. Then, use a [1 0; 0 1] F-contrast to test for this main effect.
To test for (4) the interaction between Factors Face and Rep, use two contrasts per subject [1 -1 -1 1 0 0] and [0 0 1 -1 -1 1] and take all resulting con images (two per subject) into a two-sample t-test design at the second level. Use then a [1 0; 0 1] F-contrast to test for this interaction effect.
2.1 One Sample T-Test: Overall effect, main effect of repetition#
Test for significantly non-zero BOLD responses over all subjects.
con_0005: Positive effect
con_0006: Positive Effect F>S
con_0007: Positive Effect S>U
con_0008: Positive Effect of rep1>rep2
con_0009: Positive Interaction Face (F/S) x Rep
con_0010: Positive Interaction Face (S/U) x Rep
wf_2ndlevel_onesample = Workflow(name='level2_spm_1sample', base_dir=experiment_dir)
wf_2ndlevel_onesample.config["execution"]["crashfile_format"] = "txt"
contrast_id = [5, 6, 7, 8, 9, 10] #contrasts con_0005 to con_0010
l2source = Node(DataGrabber(infields= ['con'], outfields=['contrasts']), name='l2source')
l2source.inputs.sort_filelist = True
l2source.inputs.base_directory = opj(experiment_dir, 'level1_spm_results')
l2source.inputs.template = '*'
l2source.inputs.field_template = dict(
contrasts = '*/con_%04d.nii'
)
# iterate over all contrast images
l2source.iterables = [('con', contrast_id)]
# OneSampleTTest Design
onesamplettestdes = Node(interface=spm.OneSampleTTestDesign(), name="onesampttestdes")
wf_2ndlevel_onesample.connect([(l2source, onesamplettestdes, [('contrasts', 'in_files')])])
# EstimateModel - estimates the model
l2estimate = Node(spm.EstimateModel(estimation_method={'Classical':1}), name='level2estimate')
# EstimateContast - estimates group contrast
l2conestimate = Node(spm.EstimateContrast(group_contrast=True), name = 'level2conestimate')
con_1= ['Group', 'T', ['mean'], [1]]
#con_2= ['Group', 'F', [con_1]] # if an F contrast is also wanted
l2conestimate.inputs.contrasts = [con_1] # con_2, include in list if wanted
# Threshold - thresholds contrasts
level2thresh = Node(spm.Threshold(contrast_index=1,# which contrast in the SPM.mat to use --> here set for con_1: T stat
use_topo_fdr=True, # whether to use FDR over cluster extent probabilities
use_fwe_correction=False, # whether to use FWE (Bonferroni) correction for initial threshold
extent_threshold=0, # minimum cluster size in voxels
height_threshold=0.005, # value for initial thresholding (defining clusters) - voxelwise
height_threshold_type='p-value',
extent_fdr_p_threshold=0.05), # p threshold on FDR corrected cluster size probabilities
name='level2thresh')
wf_2ndlevel_onesample.connect([(onesamplettestdes, l2estimate, [('spm_mat_file', 'spm_mat_file')]),
(l2estimate, l2conestimate, [('spm_mat_file', 'spm_mat_file'),
('beta_images', 'beta_images'),
('residual_image', 'residual_image')]),
(l2conestimate, level2thresh, [('spm_mat_file', 'spm_mat_file'),
('spmT_images', 'stat_image')])
])
datasink_2nd = Node(DataSink(), name='datasink_2nd')
datasink_2nd.inputs.base_directory=opj(experiment_dir, 'level2_spm_results_1sample')
wf_2ndlevel_onesample.connect([(l2conestimate, datasink_2nd, [('spm_mat_file', '2ndLevel.@spm_mat'),
('spmT_images', '2ndLevel.@T'),
('con_images', '2ndLevel.@con')]),
(level2thresh, datasink_2nd, [('thresholded_map',
'2ndLevel.@threshold')])
])
#replace _con_ with con
subFolders = [('2ndLevel/', '')]
subFolders1 = [('_con_', 'con')]
subFolders.extend(subFolders1)
datasink_2nd.inputs.substitutions = subFolders
from IPython.display import Image
wf_2ndlevel_onesample.write_graph(graph2use='colored', format='png', simple_form=True)
Image(filename=opj(wf_2ndlevel_onesample.base_dir, wf_2ndlevel_onesample.name, 'graph.png'))
240613-06:44:11,680 nipype.workflow INFO:
Generated workflow graph: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/graph.png (graph2use=colored, simple_form=True).
wf_2ndlevel_onesample.run(plugin="MultiProc")
# 2min
240613-06:44:11,692 nipype.workflow INFO:
Workflow level2_spm_1sample settings: ['check', 'execution', 'logging', 'monitoring']
240613-06:44:11,713 nipype.workflow INFO:
Running in parallel.
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240613-06:44:12,343 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.l2source" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_5/l2source".
240613-06:44:12,343 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.l2source" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_6/l2source".
240613-06:44:12,344 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.l2source" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_7/l2source".
240613-06:44:12,345 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.l2source" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_8/l2source".
240613-06:44:12,352 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.l2source" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_9/l2source".
240613-06:44:12,353 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.l2source" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_10/l2source".
240613-06:44:12,364 nipype.workflow INFO:
[Node] Executing "l2source" <nipype.interfaces.io.DataGrabber>
240613-06:44:12,364 nipype.workflow INFO:
[Node] Executing "l2source" <nipype.interfaces.io.DataGrabber>
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[Node] Executing "l2source" <nipype.interfaces.io.DataGrabber>
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[Node] Executing "l2source" <nipype.interfaces.io.DataGrabber>
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[Node] Executing "l2source" <nipype.interfaces.io.DataGrabber>
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[Node] Executing "l2source" <nipype.interfaces.io.DataGrabber>
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240613-06:44:14,242 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.onesampttestdes" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_5/onesampttestdes".
240613-06:44:14,242 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.onesampttestdes" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_6/onesampttestdes".
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[Node] Setting-up "level2_spm_1sample.onesampttestdes" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_10/onesampttestdes".
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[Node] Setting-up "level2_spm_1sample.onesampttestdes" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_9/onesampttestdes".
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[Node] Setting-up "level2_spm_1sample.onesampttestdes" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_8/onesampttestdes".
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[Node] Setting-up "level2_spm_1sample.onesampttestdes" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_7/onesampttestdes".
240613-06:44:14,319 nipype.workflow INFO:
[Node] Executing "onesampttestdes" <nipype.interfaces.spm.model.OneSampleTTestDesign>
240613-06:44:14,319 nipype.workflow INFO:
[Node] Executing "onesampttestdes" <nipype.interfaces.spm.model.OneSampleTTestDesign>
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[Node] Executing "onesampttestdes" <nipype.interfaces.spm.model.OneSampleTTestDesign>
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[Node] Executing "onesampttestdes" <nipype.interfaces.spm.model.OneSampleTTestDesign>
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[Node] Executing "onesampttestdes" <nipype.interfaces.spm.model.OneSampleTTestDesign>
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[Node] Executing "onesampttestdes" <nipype.interfaces.spm.model.OneSampleTTestDesign>
240613-06:44:15,716 nipype.workflow INFO:
[MultiProc] Running 6 tasks, and 0 jobs ready. Free memory (GB): 218.28/219.48, Free processors: 26/32.
Currently running:
* level2_spm_1sample.onesampttestdes
* level2_spm_1sample.onesampttestdes
* level2_spm_1sample.onesampttestdes
* level2_spm_1sample.onesampttestdes
* level2_spm_1sample.onesampttestdes
* level2_spm_1sample.onesampttestdes
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[Node] Finished "onesampttestdes", elapsed time 19.307692s.
240613-06:44:33,718 nipype.workflow INFO:
[Job 7] Completed (level2_spm_1sample.onesampttestdes).
240613-06:44:33,720 nipype.workflow INFO:
[Job 8] Completed (level2_spm_1sample.onesampttestdes).
240613-06:44:33,721 nipype.workflow INFO:
[Job 9] Completed (level2_spm_1sample.onesampttestdes).
240613-06:44:33,722 nipype.workflow INFO:
[Job 10] Completed (level2_spm_1sample.onesampttestdes).
240613-06:44:33,723 nipype.workflow INFO:
[Job 11] Completed (level2_spm_1sample.onesampttestdes).
240613-06:44:33,724 nipype.workflow INFO:
[MultiProc] Running 1 tasks, and 5 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.
Currently running:
* level2_spm_1sample.onesampttestdes
240613-06:44:33,891 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_6/level2estimate".
240613-06:44:33,892 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_8/level2estimate".
240613-06:44:33,892 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_7/level2estimate".
240613-06:44:33,893 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_9/level2estimate".
240613-06:44:33,894 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_10/level2estimate".
240613-06:44:33,902 nipype.workflow INFO:
[Node] Executing "level2estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:44:33,902 nipype.workflow INFO:
[Node] Executing "level2estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:44:33,903 nipype.workflow INFO:
[Node] Executing "level2estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:44:33,903 nipype.workflow INFO:
[Node] Executing "level2estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:44:33,907 nipype.workflow INFO:
[Node] Executing "level2estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:44:33,916 nipype.workflow INFO:
[Node] Finished "onesampttestdes", elapsed time 19.58191s.
240613-06:44:35,719 nipype.workflow INFO:
[Job 6] Completed (level2_spm_1sample.onesampttestdes).
240613-06:44:35,721 nipype.workflow INFO:
[MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 218.48/219.48, Free processors: 27/32.
Currently running:
* level2_spm_1sample.level2estimate
* level2_spm_1sample.level2estimate
* level2_spm_1sample.level2estimate
* level2_spm_1sample.level2estimate
* level2_spm_1sample.level2estimate
240613-06:44:35,922 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_5/level2estimate".
240613-06:44:35,938 nipype.workflow INFO:
[Node] Executing "level2estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:44:37,722 nipype.workflow INFO:
[MultiProc] Running 6 tasks, and 0 jobs ready. Free memory (GB): 218.28/219.48, Free processors: 26/32.
Currently running:
* level2_spm_1sample.level2estimate
* level2_spm_1sample.level2estimate
* level2_spm_1sample.level2estimate
* level2_spm_1sample.level2estimate
* level2_spm_1sample.level2estimate
* level2_spm_1sample.level2estimate
240613-06:44:53,77 nipype.workflow INFO:
[Node] Finished "level2estimate", elapsed time 19.161336s.
240613-06:44:53,723 nipype.workflow INFO:
[Job 17] Completed (level2_spm_1sample.level2estimate).
240613-06:44:53,725 nipype.workflow INFO:
[MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 218.48/219.48, Free processors: 27/32.
Currently running:
* level2_spm_1sample.level2estimate
* level2_spm_1sample.level2estimate
* level2_spm_1sample.level2estimate
* level2_spm_1sample.level2estimate
* level2_spm_1sample.level2estimate
240613-06:44:53,959 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2conestimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_10/level2conestimate".
240613-06:44:53,973 nipype.workflow INFO:
[Node] Executing "level2conestimate" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:44:54,127 nipype.workflow INFO:
[Node] Finished "level2estimate", elapsed time 20.220956s.
240613-06:44:54,263 nipype.workflow INFO:
[Node] Finished "level2estimate", elapsed time 20.357547s.
240613-06:44:54,353 nipype.workflow INFO:
[Node] Finished "level2estimate", elapsed time 20.448029s.
240613-06:44:54,574 nipype.workflow INFO:
[Node] Finished "level2estimate", elapsed time 20.667891s.
240613-06:44:55,724 nipype.workflow INFO:
[Job 13] Completed (level2_spm_1sample.level2estimate).
240613-06:44:55,725 nipype.workflow INFO:
[Job 14] Completed (level2_spm_1sample.level2estimate).
240613-06:44:55,726 nipype.workflow INFO:
[Job 15] Completed (level2_spm_1sample.level2estimate).
240613-06:44:55,727 nipype.workflow INFO:
[Job 16] Completed (level2_spm_1sample.level2estimate).
240613-06:44:55,729 nipype.workflow INFO:
[MultiProc] Running 2 tasks, and 4 jobs ready. Free memory (GB): 219.08/219.48, Free processors: 30/32.
Currently running:
* level2_spm_1sample.level2conestimate
* level2_spm_1sample.level2estimate
240613-06:44:55,869 nipype.workflow INFO:
[Node] Finished "level2estimate", elapsed time 19.928532s.
240613-06:44:55,890 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2conestimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_6/level2conestimate".
240613-06:44:55,890 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2conestimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_7/level2conestimate".
240613-06:44:55,891 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2conestimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_8/level2conestimate".
240613-06:44:55,892 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2conestimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_9/level2conestimate".
240613-06:44:55,903 nipype.workflow INFO:
[Node] Executing "level2conestimate" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:44:55,903 nipype.workflow INFO:
[Node] Executing "level2conestimate" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:44:55,904 nipype.workflow INFO:
[Node] Executing "level2conestimate" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:44:55,905 nipype.workflow INFO:
[Node] Executing "level2conestimate" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:44:57,730 nipype.workflow INFO:
[Job 12] Completed (level2_spm_1sample.level2estimate).
240613-06:44:57,732 nipype.workflow INFO:
[MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 218.48/219.48, Free processors: 27/32.
Currently running:
* level2_spm_1sample.level2conestimate
* level2_spm_1sample.level2conestimate
* level2_spm_1sample.level2conestimate
* level2_spm_1sample.level2conestimate
* level2_spm_1sample.level2conestimate
240613-06:44:57,877 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2conestimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_5/level2conestimate".
240613-06:44:57,893 nipype.workflow INFO:
[Node] Executing "level2conestimate" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:44:59,725 nipype.workflow INFO:
[MultiProc] Running 6 tasks, and 0 jobs ready. Free memory (GB): 218.28/219.48, Free processors: 26/32.
Currently running:
* level2_spm_1sample.level2conestimate
* level2_spm_1sample.level2conestimate
* level2_spm_1sample.level2conestimate
* level2_spm_1sample.level2conestimate
* level2_spm_1sample.level2conestimate
* level2_spm_1sample.level2conestimate
240613-06:45:17,883 nipype.workflow INFO:
[Node] Finished "level2conestimate", elapsed time 23.894972s.
240613-06:45:19,725 nipype.workflow INFO:
[Node] Finished "level2conestimate", elapsed time 23.819495s.
240613-06:45:19,728 nipype.workflow INFO:
[Job 23] Completed (level2_spm_1sample.level2conestimate).
240613-06:45:19,730 nipype.workflow INFO:
[MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 218.48/219.48, Free processors: 27/32.
Currently running:
* level2_spm_1sample.level2conestimate
* level2_spm_1sample.level2conestimate
* level2_spm_1sample.level2conestimate
* level2_spm_1sample.level2conestimate
* level2_spm_1sample.level2conestimate
240613-06:45:19,835 nipype.workflow INFO:
[Node] Finished "level2conestimate", elapsed time 23.929947s.
240613-06:45:19,863 nipype.workflow INFO:
[Node] Finished "level2conestimate", elapsed time 23.956484s.
240613-06:45:19,913 nipype.workflow INFO:
[Node] Finished "level2conestimate", elapsed time 24.005406s.
240613-06:45:19,905 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2thresh" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_10/level2thresh".
240613-06:45:19,944 nipype.workflow INFO:
[Node] Executing "level2thresh" <nipype.interfaces.spm.model.Threshold>
240613-06:45:21,728 nipype.workflow INFO:
[Job 19] Completed (level2_spm_1sample.level2conestimate).
240613-06:45:21,730 nipype.workflow INFO:
[Job 20] Completed (level2_spm_1sample.level2conestimate).
240613-06:45:21,731 nipype.workflow INFO:
[Job 21] Completed (level2_spm_1sample.level2conestimate).
240613-06:45:21,732 nipype.workflow INFO:
[Job 22] Completed (level2_spm_1sample.level2conestimate).
240613-06:45:21,734 nipype.workflow INFO:
[MultiProc] Running 2 tasks, and 4 jobs ready. Free memory (GB): 219.08/219.48, Free processors: 30/32.
Currently running:
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2conestimate
240613-06:45:21,912 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2thresh" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_7/level2thresh".
240613-06:45:21,912 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2thresh" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_8/level2thresh".
240613-06:45:21,912 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2thresh" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_9/level2thresh".
240613-06:45:21,937 nipype.workflow INFO:
[Node] Finished "level2conestimate", elapsed time 24.03745s.
240613-06:45:21,938 nipype.workflow INFO:
[Node] Executing "level2thresh" <nipype.interfaces.spm.model.Threshold>
240613-06:45:21,937 nipype.workflow INFO:
[Node] Executing "level2thresh" <nipype.interfaces.spm.model.Threshold>
240613-06:45:21,938 nipype.workflow INFO:
[Node] Executing "level2thresh" <nipype.interfaces.spm.model.Threshold>
240613-06:45:21,911 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2thresh" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_6/level2thresh".
240613-06:45:21,968 nipype.workflow INFO:
[Node] Executing "level2thresh" <nipype.interfaces.spm.model.Threshold>
240613-06:45:23,728 nipype.workflow INFO:
[Job 18] Completed (level2_spm_1sample.level2conestimate).
240613-06:45:23,730 nipype.workflow INFO:
[MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 218.48/219.48, Free processors: 27/32.
Currently running:
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
240613-06:45:23,932 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.level2thresh" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_5/level2thresh".
240613-06:45:23,945 nipype.workflow INFO:
[Node] Executing "level2thresh" <nipype.interfaces.spm.model.Threshold>
240613-06:45:25,729 nipype.workflow INFO:
[MultiProc] Running 6 tasks, and 0 jobs ready. Free memory (GB): 218.28/219.48, Free processors: 26/32.
Currently running:
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
240613-06:45:33,655 nipype.workflow INFO:
[Node] Finished "level2thresh", elapsed time 13.708427s.
240613-06:45:33,729 nipype.workflow INFO:
[Job 29] Completed (level2_spm_1sample.level2thresh).
240613-06:45:33,731 nipype.workflow INFO:
[MultiProc] Running 5 tasks, and 1 jobs ready. Free memory (GB): 218.48/219.48, Free processors: 27/32.
Currently running:
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
240613-06:45:33,894 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.datasink_2nd" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_10/datasink_2nd".
240613-06:45:33,906 nipype.workflow INFO:
[Node] Executing "datasink_2nd" <nipype.interfaces.io.DataSink>
240613-06:45:33,909 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_10/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con10/SPM.mat
240613-06:45:33,910 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_10/spmT_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con10/spmT_0001.nii
240613-06:45:33,911 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_10/con_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con10/con_0001.nii
240613-06:45:33,912 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_10/spmT_0001_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con10/spmT_0001_thr.nii
240613-06:45:33,914 nipype.workflow INFO:
[Node] Finished "datasink_2nd", elapsed time 0.004923s.
240613-06:45:35,729 nipype.workflow INFO:
[Job 35] Completed (level2_spm_1sample.datasink_2nd).
240613-06:45:35,731 nipype.workflow INFO:
[MultiProc] Running 5 tasks, and 0 jobs ready. Free memory (GB): 218.48/219.48, Free processors: 27/32.
Currently running:
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
* level2_spm_1sample.level2thresh
240613-06:45:35,938 nipype.workflow INFO:
[Node] Finished "level2thresh", elapsed time 13.997871s.
240613-06:45:35,976 nipype.workflow INFO:
[Node] Finished "level2thresh", elapsed time 14.035477s.
240613-06:45:35,975 nipype.workflow INFO:
[Node] Finished "level2thresh", elapsed time 14.003737s.
240613-06:45:36,79 nipype.workflow INFO:
[Node] Finished "level2thresh", elapsed time 14.138397s.
240613-06:45:37,729 nipype.workflow INFO:
[Job 25] Completed (level2_spm_1sample.level2thresh).
240613-06:45:37,731 nipype.workflow INFO:
[Job 26] Completed (level2_spm_1sample.level2thresh).
240613-06:45:37,732 nipype.workflow INFO:
[Job 27] Completed (level2_spm_1sample.level2thresh).
240613-06:45:37,734 nipype.workflow INFO:
[Job 28] Completed (level2_spm_1sample.level2thresh).
240613-06:45:37,736 nipype.workflow INFO:
[MultiProc] Running 1 tasks, and 4 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.
Currently running:
* level2_spm_1sample.level2thresh
240613-06:45:37,771 nipype.workflow INFO:
[Node] Finished "level2thresh", elapsed time 13.824073s.
240613-06:45:37,904 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.datasink_2nd" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_8/datasink_2nd".
240613-06:45:37,904 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.datasink_2nd" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_7/datasink_2nd".
240613-06:45:37,905 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.datasink_2nd" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_9/datasink_2nd".
240613-06:45:37,905 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.datasink_2nd" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_6/datasink_2nd".
240613-06:45:37,918 nipype.workflow INFO:
[Node] Executing "datasink_2nd" <nipype.interfaces.io.DataSink>
240613-06:45:37,918 nipype.workflow INFO:
[Node] Executing "datasink_2nd" <nipype.interfaces.io.DataSink>
240613-06:45:37,918 nipype.workflow INFO:
[Node] Executing "datasink_2nd" <nipype.interfaces.io.DataSink>
240613-06:45:37,920 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_7/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con7/SPM.mat
240613-06:45:37,920 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_8/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con8/SPM.mat
240613-06:45:37,921 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_9/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con9/SPM.mat
240613-06:45:37,921 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_7/spmT_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con7/spmT_0001.nii
240613-06:45:37,921 nipype.workflow INFO:
[Node] Executing "datasink_2nd" <nipype.interfaces.io.DataSink>
240613-06:45:37,922 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_9/spmT_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con9/spmT_0001.nii
240613-06:45:37,922 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_8/spmT_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con8/spmT_0001.nii
240613-06:45:37,922 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_7/con_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con7/con_0001.nii
240613-06:45:37,923 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_9/con_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con9/con_0001.nii
240613-06:45:37,923 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_8/con_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con8/con_0001.nii
240613-06:45:37,924 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_6/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con6/SPM.mat
240613-06:45:37,924 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_9/spmT_0001_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con9/spmT_0001_thr.nii
240613-06:45:37,924 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_7/spmT_0001_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con7/spmT_0001_thr.nii
240613-06:45:37,925 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_8/spmT_0001_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con8/spmT_0001_thr.nii
240613-06:45:37,925 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_6/spmT_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con6/spmT_0001.nii
240613-06:45:37,925 nipype.workflow INFO:
[Node] Finished "datasink_2nd", elapsed time 0.005013s.
240613-06:45:37,926 nipype.workflow INFO:
[Node] Finished "datasink_2nd", elapsed time 0.00601s.
240613-06:45:37,926 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_6/con_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con6/con_0001.nii
240613-06:45:37,926 nipype.workflow INFO:
[Node] Finished "datasink_2nd", elapsed time 0.006461s.
240613-06:45:37,928 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_6/spmT_0001_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con6/spmT_0001_thr.nii
240613-06:45:37,929 nipype.workflow INFO:
[Node] Finished "datasink_2nd", elapsed time 0.005159s.
240613-06:45:39,729 nipype.workflow INFO:
[Job 24] Completed (level2_spm_1sample.level2thresh).
240613-06:45:39,731 nipype.workflow INFO:
[Job 31] Completed (level2_spm_1sample.datasink_2nd).
240613-06:45:39,732 nipype.workflow INFO:
[Job 32] Completed (level2_spm_1sample.datasink_2nd).
240613-06:45:39,733 nipype.workflow INFO:
[Job 33] Completed (level2_spm_1sample.datasink_2nd).
240613-06:45:39,734 nipype.workflow INFO:
[Job 34] Completed (level2_spm_1sample.datasink_2nd).
240613-06:45:39,735 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:45:39,888 nipype.workflow INFO:
[Node] Setting-up "level2_spm_1sample.datasink_2nd" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_1sample/_con_5/datasink_2nd".
240613-06:45:39,895 nipype.workflow INFO:
[Node] Executing "datasink_2nd" <nipype.interfaces.io.DataSink>
240613-06:45:39,921 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_5/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con5/SPM.mat
240613-06:45:39,923 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_5/spmT_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con5/spmT_0001.nii
240613-06:45:39,924 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_5/con_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con5/con_0001.nii
240613-06:45:39,925 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/2ndLevel/_con_5/spmT_0001_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_1sample/con5/spmT_0001_thr.nii
240613-06:45:39,927 nipype.workflow INFO:
[Node] Finished "datasink_2nd", elapsed time 0.005705s.
240613-06:45:41,730 nipype.workflow INFO:
[Job 30] Completed (level2_spm_1sample.datasink_2nd).
240613-06:45:41,732 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 0 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
<networkx.classes.digraph.DiGraph at 0x7fd2bd8695d0>
2.1 Two Sample T-Test: Main effect of face, Interaction Face x Repetition#
Main effect of face: enter the following 2 contrasts per subject into a two-sample t-test and use 1 0, 0 1 F contrast
con_0006: Positive Effect F>S
con_0007: Positive Effect S>U
Interaction Face x Rep: enter the following 2 contrasts per subject into a two-sample t-test and use 1 0, 0 1 F contrast
con_0009: Positive Interaction Face (F/S) x Rep
con_0010: Positive Interaction Face (S/U) x Rep
wf_2ndlevel_twosample = Workflow(name='level2_spm_2sample', base_dir=experiment_dir)
wf_2ndlevel_twosample.config["execution"]["crashfile_format"] = "txt"
contrast_id_1 = [6] #con_0006
contrast_id_2 = [7] #con_0007
l2source2 = Node(DataGrabber(outfields=["group_1", "group_2"]), name='l2source')
l2source2.inputs.sort_filelist = True
l2source2.inputs.contrast_id_1 = contrast_id_1
l2source2.inputs.contrast_id_2 = contrast_id_2
l2source2.inputs.base_directory = opj(experiment_dir, 'level1_spm_results')
l2source2.inputs.template = '*'
l2source2.inputs.template_args = dict(
group_1=[["contrast_id_1"]],
group_2=[["contrast_id_2"]])
l2source2.inputs.field_template = dict(
group_1 = "*/con_%04d.nii",
group_2 ="*/con_%04d.nii",
)
# SecondLevelDesign - TwoSampleTTestDesign bases Factorial Design
twosamplettestdes = Node(interface=spm.TwoSampleTTestDesign(), name="twosampttestdes")
twosamplettestdes.inputs.dependent = False # measurements dependent between levels
twosamplettestdes.inputs.unequal_variance = True # equal or unequal between groups
wf_2ndlevel_twosample.connect([(l2source2, twosamplettestdes, [('group_1', 'group1_files')]),
(l2source2, twosamplettestdes, [('group_2', 'group2_files')])])
l2estimate2 = Node(spm.EstimateModel(estimation_method={'Classical':1}), name='level2estimate')
# EstimateContast - estimates group contrast
l2conestimate2 = Node(spm.EstimateContrast(group_contrast=True), name = 'level2conestimate')
con_1 = ('Pos effect level 1','T', ['Group_{1}', 'Group_{2}'],[1, 0])
con_2 = ('Pos effect level 2','T', ['Group_{1}', 'Group_{2}'],[0, 1])
con_3 = ('Main effect', 'F', [con_1, con_2]) # main effect of face
l2conestimate2.inputs.contrasts = [con_1, con_2, con_3]
# Threshold - thresholds contrasts
level2thresh2 = MapNode(spm.Threshold(contrast_index=3,# which contrast in the SPM.mat to use --> here set for con_3: main effect
use_topo_fdr=True, # whether to use FDR over cluster extent probabilities
use_fwe_correction=False, # whether to use FWE (Bonferroni) correction for initial threshold
extent_threshold=0, # minimum cluster size in voxels
height_threshold=0.005, # value for initial thresholding (defining clusters) - voxelwise
height_threshold_type='p-value',
extent_fdr_p_threshold=0.05), # P threshold on FDR corrected cluster size probabilities
iterfield=['stat_image'],
name='level2thresh')
wf_2ndlevel_twosample.connect([(twosamplettestdes, l2estimate2, [('spm_mat_file', 'spm_mat_file')]),
(l2estimate2, l2conestimate2, [('spm_mat_file', 'spm_mat_file'),
('beta_images', 'beta_images'),
('residual_image', 'residual_image')]),
(l2conestimate2, level2thresh2, [('spm_mat_file', 'spm_mat_file'),
('spmT_images', 'stat_image')])
])
datasink_2nd_2 = Node(DataSink(), name='datasink_2nd_2')
datasink_2nd_2.inputs.base_directory=opj(experiment_dir, 'level2_spm_results_2sample')
wf_2ndlevel_twosample.connect([(l2conestimate2, datasink_2nd_2, [('spm_mat_file', '2ndLevel.@spm_mat'),
('spmT_images', '2ndLevel.@T'),
('con_images', '2ndLevel.@con')]),
(level2thresh2, datasink_2nd_2, [('thresholded_map',
'2ndLevel.@threshold')])
])
subFolders = [('2ndLevel/', 'MainEffectFace/')]
subFolders1 = [('_con_', 'con')]
subFolders2 = [('_level2thresh0', 'thresh_con1')]
subFolders3 = [('_level2thresh1', 'thresh_con2')]
subFolders4 = [('_level2thresh2', 'thresh_con3')]
subFolders.extend(subFolders1)
subFolders.extend(subFolders2)
subFolders.extend(subFolders3)
subFolders.extend(subFolders4)
datasink_2nd_2.inputs.substitutions = subFolders
from IPython.display import Image
wf_2ndlevel_twosample.write_graph(graph2use='colored', format='png', simple_form=True)
Image(filename=opj(wf_2ndlevel_twosample.base_dir, wf_2ndlevel_twosample.name, 'graph.png'))
240613-06:45:44,410 nipype.workflow INFO:
Generated workflow graph: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/graph.png (graph2use=colored, simple_form=True).
wf_2ndlevel_twosample.run(plugin="MultiProc")
240613-06:45:44,421 nipype.workflow INFO:
Workflow level2_spm_2sample settings: ['check', 'execution', 'logging', 'monitoring']
240613-06:45:44,427 nipype.workflow INFO:
Running in parallel.
240613-06:45:44,429 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:45:44,938 nipype.workflow INFO:
[Node] Setting-up "level2_spm_2sample.l2source" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/l2source".
240613-06:45:44,946 nipype.workflow INFO:
[Node] Executing "l2source" <nipype.interfaces.io.DataGrabber>
240613-06:45:44,952 nipype.workflow INFO:
[Node] Finished "l2source", elapsed time 0.00239s.
240613-06:45:46,432 nipype.workflow INFO:
[Job 0] Completed (level2_spm_2sample.l2source).
240613-06:45:46,436 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:45:46,685 nipype.workflow INFO:
[Node] Setting-up "level2_spm_2sample.twosampttestdes" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/twosampttestdes".
240613-06:45:46,697 nipype.workflow INFO:
[Node] Executing "twosampttestdes" <nipype.interfaces.spm.model.TwoSampleTTestDesign>
240613-06:45:48,430 nipype.workflow INFO:
[MultiProc] Running 1 tasks, and 0 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.
Currently running:
* level2_spm_2sample.twosampttestdes
240613-06:46:02,47 nipype.workflow INFO:
[Node] Finished "twosampttestdes", elapsed time 15.346838s.
240613-06:46:02,431 nipype.workflow INFO:
[Job 1] Completed (level2_spm_2sample.twosampttestdes).
240613-06:46:02,433 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:46:02,580 nipype.workflow INFO:
[Node] Setting-up "level2_spm_2sample.level2estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2estimate".
240613-06:46:02,590 nipype.workflow INFO:
[Node] Executing "level2estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:46:04,432 nipype.workflow INFO:
[MultiProc] Running 1 tasks, and 0 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.
Currently running:
* level2_spm_2sample.level2estimate
240613-06:46:22,491 nipype.workflow INFO:
[Node] Finished "level2estimate", elapsed time 19.898428s.
240613-06:46:24,433 nipype.workflow INFO:
[Job 2] Completed (level2_spm_2sample.level2estimate).
240613-06:46:24,435 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:46:24,580 nipype.workflow INFO:
[Node] Setting-up "level2_spm_2sample.level2conestimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2conestimate".
240613-06:46:24,595 nipype.workflow INFO:
[Node] Executing "level2conestimate" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:46:26,434 nipype.workflow INFO:
[MultiProc] Running 1 tasks, and 0 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.
Currently running:
* level2_spm_2sample.level2conestimate
240613-06:46:41,400 nipype.workflow INFO:
[Node] Finished "level2conestimate", elapsed time 16.802565s.
240613-06:46:42,435 nipype.workflow INFO:
[Job 3] Completed (level2_spm_2sample.level2conestimate).
240613-06:46:42,437 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:46:44,435 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 3 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:46:44,580 nipype.workflow INFO:
[Node] Setting-up "_level2thresh0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh0".
240613-06:46:44,581 nipype.workflow INFO:
[Node] Setting-up "_level2thresh1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh1".
240613-06:46:44,582 nipype.workflow INFO:
[Node] Setting-up "_level2thresh2" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh2".
240613-06:46:44,592 nipype.workflow INFO:
[Node] Executing "_level2thresh0" <nipype.interfaces.spm.model.Threshold>
240613-06:46:44,592 nipype.workflow INFO:
[Node] Executing "_level2thresh1" <nipype.interfaces.spm.model.Threshold>
240613-06:46:44,592 nipype.workflow INFO:
[Node] Executing "_level2thresh2" <nipype.interfaces.spm.model.Threshold>
240613-06:46:46,440 nipype.workflow INFO:
[MultiProc] Running 3 tasks, and 0 jobs ready. Free memory (GB): 218.88/219.48, Free processors: 29/32.
Currently running:
* _level2thresh2
* _level2thresh1
* _level2thresh0
240613-06:46:56,734 nipype.workflow INFO:
[Node] Finished "_level2thresh1", elapsed time 12.139144s.
240613-06:46:56,789 nipype.workflow INFO:
[Node] Finished "_level2thresh0", elapsed time 12.19431s.
240613-06:46:56,825 nipype.workflow INFO:
[Node] Finished "_level2thresh2", elapsed time 12.230605s.
240613-06:46:58,442 nipype.workflow INFO:
[Job 6] Completed (_level2thresh0).
240613-06:46:58,444 nipype.workflow INFO:
[Job 7] Completed (_level2thresh1).
240613-06:46:58,445 nipype.workflow INFO:
[Job 8] Completed (_level2thresh2).
240613-06:46:58,446 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:46:58,601 nipype.workflow INFO:
[Node] Setting-up "_level2thresh0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh0".
240613-06:46:58,606 nipype.workflow INFO:
[Node] Cached "_level2thresh0" - collecting precomputed outputs
240613-06:46:58,608 nipype.workflow INFO:
[Node] "_level2thresh0" found cached.
240613-06:46:58,609 nipype.workflow INFO:
[Node] Setting-up "_level2thresh1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh1".
240613-06:46:58,611 nipype.workflow INFO:
[Node] Cached "_level2thresh1" - collecting precomputed outputs
240613-06:46:58,612 nipype.workflow INFO:
[Node] "_level2thresh1" found cached.
240613-06:46:58,614 nipype.workflow INFO:
[Node] Setting-up "_level2thresh2" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh2".
240613-06:46:58,616 nipype.workflow INFO:
[Node] Cached "_level2thresh2" - collecting precomputed outputs
240613-06:46:58,617 nipype.workflow INFO:
[Node] "_level2thresh2" found cached.
240613-06:47:00,443 nipype.workflow INFO:
[Job 4] Completed (level2_spm_2sample.level2thresh).
240613-06:47:00,445 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:47:00,588 nipype.workflow INFO:
[Node] Setting-up "level2_spm_2sample.datasink_2nd_2" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/datasink_2nd_2".
240613-06:47:00,602 nipype.workflow INFO:
[Node] Executing "datasink_2nd_2" <nipype.interfaces.io.DataSink>
240613-06:47:00,604 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/SPM.mat
240613-06:47:00,605 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/spmT_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/spmT_0001.nii
240613-06:47:00,606 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/spmT_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/spmT_0002.nii
240613-06:47:00,607 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/spmF_0003.nii
240613-06:47:00,608 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/con_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/con_0001.nii
240613-06:47:00,610 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/con_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/con_0002.nii
240613-06:47:00,610 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/ess_0003.nii
240613-06:47:00,612 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/_level2thresh0/spmT_0001_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/thresh_con1/spmT_0001_thr.nii
240613-06:47:00,613 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/_level2thresh1/spmT_0002_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/thresh_con2/spmT_0002_thr.nii
240613-06:47:00,614 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/_level2thresh2/spmF_0003_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/MainEffectFace/thresh_con3/spmF_0003_thr.nii
240613-06:47:00,615 nipype.workflow INFO:
[Node] Finished "datasink_2nd_2", elapsed time 0.011128s.
240613-06:47:02,443 nipype.workflow INFO:
[Job 5] Completed (level2_spm_2sample.datasink_2nd_2).
240613-06:47:02,445 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 0 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
<networkx.classes.digraph.DiGraph at 0x7fd3533c5f10>
contrast_id_1 = [9] #con_0009
contrast_id_2 = [10] #con_0010
l2source2.inputs.contrast_id_1 = contrast_id_1
l2source2.inputs.contrast_id_2 = contrast_id_2
subFolders = [('2ndLevel/', 'InteractionFace_Repetition/')]
subFolders.extend(subFolders1)
subFolders.extend(subFolders2)
subFolders.extend(subFolders3)
subFolders.extend(subFolders4)
datasink_2nd_2.inputs.substitutions = subFolders
wf_2ndlevel_twosample.run(plugin="MultiProc")
240613-06:47:04,529 nipype.workflow INFO:
Workflow level2_spm_2sample settings: ['check', 'execution', 'logging', 'monitoring']
240613-06:47:04,536 nipype.workflow INFO:
Running in parallel.
240613-06:47:04,538 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:47:04,680 nipype.workflow INFO:
[Node] Outdated cache found for "level2_spm_2sample.l2source".
240613-06:47:05,42 nipype.workflow INFO:
[Node] Setting-up "level2_spm_2sample.l2source" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/l2source".
240613-06:47:05,46 nipype.workflow INFO:
[Node] Outdated cache found for "level2_spm_2sample.l2source".
240613-06:47:05,57 nipype.workflow INFO:
[Node] Executing "l2source" <nipype.interfaces.io.DataGrabber>
240613-06:47:05,75 nipype.workflow INFO:
[Node] Finished "l2source", elapsed time 0.002216s.
240613-06:47:06,547 nipype.workflow INFO:
[Job 0] Completed (level2_spm_2sample.l2source).
240613-06:47:06,552 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:47:06,796 nipype.workflow INFO:
[Node] Outdated cache found for "level2_spm_2sample.twosampttestdes".
240613-06:47:06,802 nipype.workflow INFO:
[Node] Setting-up "level2_spm_2sample.twosampttestdes" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/twosampttestdes".
240613-06:47:06,806 nipype.workflow INFO:
[Node] Outdated cache found for "level2_spm_2sample.twosampttestdes".
240613-06:47:06,813 nipype.workflow INFO:
[Node] Executing "twosampttestdes" <nipype.interfaces.spm.model.TwoSampleTTestDesign>
240613-06:47:08,539 nipype.workflow INFO:
[MultiProc] Running 1 tasks, and 0 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.
Currently running:
* level2_spm_2sample.twosampttestdes
240613-06:47:22,398 nipype.workflow INFO:
[Node] Finished "twosampttestdes", elapsed time 15.58235s.
240613-06:47:22,539 nipype.workflow INFO:
[Job 1] Completed (level2_spm_2sample.twosampttestdes).
240613-06:47:22,541 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:47:22,685 nipype.workflow INFO:
[Node] Outdated cache found for "level2_spm_2sample.level2estimate".
240613-06:47:22,690 nipype.workflow INFO:
[Node] Setting-up "level2_spm_2sample.level2estimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2estimate".
240613-06:47:22,694 nipype.workflow INFO:
[Node] Outdated cache found for "level2_spm_2sample.level2estimate".
240613-06:47:22,704 nipype.workflow INFO:
[Node] Executing "level2estimate" <nipype.interfaces.spm.model.EstimateModel>
240613-06:47:24,541 nipype.workflow INFO:
[MultiProc] Running 1 tasks, and 0 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.
Currently running:
* level2_spm_2sample.level2estimate
240613-06:47:42,212 nipype.workflow INFO:
[Node] Finished "level2estimate", elapsed time 19.50542s.
240613-06:47:42,541 nipype.workflow INFO:
[Job 2] Completed (level2_spm_2sample.level2estimate).
240613-06:47:42,543 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:47:42,685 nipype.workflow INFO:
[Node] Outdated cache found for "level2_spm_2sample.level2conestimate".
240613-06:47:42,691 nipype.workflow INFO:
[Node] Setting-up "level2_spm_2sample.level2conestimate" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2conestimate".
240613-06:47:42,696 nipype.workflow INFO:
[Node] Outdated cache found for "level2_spm_2sample.level2conestimate".
240613-06:47:42,705 nipype.workflow INFO:
[Node] Executing "level2conestimate" <nipype.interfaces.spm.model.EstimateContrast>
240613-06:47:44,542 nipype.workflow INFO:
[MultiProc] Running 1 tasks, and 0 jobs ready. Free memory (GB): 219.28/219.48, Free processors: 31/32.
Currently running:
* level2_spm_2sample.level2conestimate
240613-06:47:59,416 nipype.workflow INFO:
[Node] Finished "level2conestimate", elapsed time 16.708273s.
240613-06:48:00,543 nipype.workflow INFO:
[Job 3] Completed (level2_spm_2sample.level2conestimate).
240613-06:48:00,545 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:48:02,543 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 3 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:48:02,691 nipype.workflow INFO:
[Node] Outdated cache found for "_level2thresh0".
240613-06:48:02,694 nipype.workflow INFO:
[Node] Outdated cache found for "_level2thresh1".
240613-06:48:02,696 nipype.workflow INFO:
[Node] Outdated cache found for "_level2thresh2".
240613-06:48:02,696 nipype.workflow INFO:
[Node] Setting-up "_level2thresh0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh0".
240613-06:48:02,701 nipype.workflow INFO:
[Node] Outdated cache found for "_level2thresh0".
240613-06:48:02,698 nipype.workflow INFO:
[Node] Setting-up "_level2thresh1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh1".
240613-06:48:02,700 nipype.workflow INFO:
[Node] Setting-up "_level2thresh2" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh2".
240613-06:48:02,709 nipype.workflow INFO:
[Node] Outdated cache found for "_level2thresh1".
240613-06:48:02,711 nipype.workflow INFO:
[Node] Outdated cache found for "_level2thresh2".
240613-06:48:02,714 nipype.workflow INFO:
[Node] Executing "_level2thresh0" <nipype.interfaces.spm.model.Threshold>
240613-06:48:02,716 nipype.workflow INFO:
[Node] Executing "_level2thresh1" <nipype.interfaces.spm.model.Threshold>
240613-06:48:02,718 nipype.workflow INFO:
[Node] Executing "_level2thresh2" <nipype.interfaces.spm.model.Threshold>
240613-06:48:04,544 nipype.workflow INFO:
[MultiProc] Running 3 tasks, and 0 jobs ready. Free memory (GB): 218.88/219.48, Free processors: 29/32.
Currently running:
* _level2thresh2
* _level2thresh1
* _level2thresh0
240613-06:48:14,610 nipype.workflow INFO:
[Node] Finished "_level2thresh1", elapsed time 11.89035s.
240613-06:48:14,622 nipype.workflow INFO:
[Node] Finished "_level2thresh0", elapsed time 11.904817s.
240613-06:48:14,731 nipype.workflow INFO:
[Node] Finished "_level2thresh2", elapsed time 12.0103s.
240613-06:48:16,544 nipype.workflow INFO:
[Job 6] Completed (_level2thresh0).
240613-06:48:16,546 nipype.workflow INFO:
[Job 7] Completed (_level2thresh1).
240613-06:48:16,546 nipype.workflow INFO:
[Job 8] Completed (_level2thresh2).
240613-06:48:16,547 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:48:16,695 nipype.workflow INFO:
[Node] Outdated cache found for "level2_spm_2sample.level2thresh".
240613-06:48:16,706 nipype.workflow INFO:
[Node] Outdated cache found for "level2_spm_2sample.level2thresh".
240613-06:48:16,723 nipype.workflow INFO:
[Node] Setting-up "_level2thresh0" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh0".
240613-06:48:16,727 nipype.workflow INFO:
[Node] Cached "_level2thresh0" - collecting precomputed outputs
240613-06:48:16,728 nipype.workflow INFO:
[Node] "_level2thresh0" found cached.
240613-06:48:16,729 nipype.workflow INFO:
[Node] Setting-up "_level2thresh1" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh1".
240613-06:48:16,731 nipype.workflow INFO:
[Node] Cached "_level2thresh1" - collecting precomputed outputs
240613-06:48:16,732 nipype.workflow INFO:
[Node] "_level2thresh1" found cached.
240613-06:48:16,734 nipype.workflow INFO:
[Node] Setting-up "_level2thresh2" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/level2thresh/mapflow/_level2thresh2".
240613-06:48:16,737 nipype.workflow INFO:
[Node] Cached "_level2thresh2" - collecting precomputed outputs
240613-06:48:16,738 nipype.workflow INFO:
[Node] "_level2thresh2" found cached.
240613-06:48:18,544 nipype.workflow INFO:
[Job 4] Completed (level2_spm_2sample.level2thresh).
240613-06:48:18,547 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 1 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
240613-06:48:18,693 nipype.workflow INFO:
[Node] Outdated cache found for "level2_spm_2sample.datasink_2nd_2".
240613-06:48:18,698 nipype.workflow INFO:
[Node] Setting-up "level2_spm_2sample.datasink_2nd_2" in "/mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_2sample/datasink_2nd_2".
240613-06:48:18,703 nipype.workflow INFO:
[Node] Outdated cache found for "level2_spm_2sample.datasink_2nd_2".
240613-06:48:18,709 nipype.workflow INFO:
[Node] Executing "datasink_2nd_2" <nipype.interfaces.io.DataSink>
240613-06:48:18,712 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/SPM.mat -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/SPM.mat
240613-06:48:18,713 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/spmT_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/spmT_0001.nii
240613-06:48:18,714 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/spmT_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/spmT_0002.nii
240613-06:48:18,716 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/spmF_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/spmF_0003.nii
240613-06:48:18,717 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/con_0001.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/con_0001.nii
240613-06:48:18,718 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/con_0002.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/con_0002.nii
240613-06:48:18,719 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/ess_0003.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/ess_0003.nii
240613-06:48:18,720 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/_level2thresh0/spmT_0001_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/thresh_con1/spmT_0001_thr.nii
240613-06:48:18,721 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/_level2thresh1/spmT_0002_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/thresh_con2/spmT_0002_thr.nii
240613-06:48:18,722 nipype.interface INFO:
sub: /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/2ndLevel/_level2thresh2/spmF_0003_thr.nii -> /mnt/neurodesktop-storage/Examples_neurodesk/spm_analysis/level2_spm_results_2sample/InteractionFace_Repetition/thresh_con3/spmF_0003_thr.nii
240613-06:48:18,724 nipype.workflow INFO:
[Node] Finished "datasink_2nd_2", elapsed time 0.011743s.
240613-06:48:20,545 nipype.workflow INFO:
[Job 5] Completed (level2_spm_2sample.datasink_2nd_2).
240613-06:48:20,547 nipype.workflow INFO:
[MultiProc] Running 0 tasks, and 0 jobs ready. Free memory (GB): 219.48/219.48, Free processors: 32/32.
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
stty: 'standard input': Inappropriate ioctl for device
<networkx.classes.digraph.DiGraph at 0x7fd3533b13d0>
Results#
The group analysis was only done on N=9 subjects, a voxel-wise threshold of p<0.005 was chosen and a cluster-wise FDR threshold of p<0.05 to correct for multiple comparisons.
Look at the positive effect using the plot_stat_map plotting method of nilearn#
plotting.plot_stat_map(opj(experiment_dir, 'level2_spm_results_1sample/con5/spmT_0001_thr.nii'), title='Positive Effect', dim=1, display_mode='y', cut_coords=(-45, -30, -15, 0, 15), threshold=2, vmax=8, cmap='viridis');
/opt/conda/lib/python3.11/site-packages/nilearn/plotting/img_plotting.py:1317: UserWarning: Non-finite values detected. These values will be replaced with zeros.
safe_get_data(stat_map_img, ensure_finite=True),
Look at the results using the glass brain plotting method of nilearn#
plotting.plot_glass_brain(opj(experiment_dir, 'level2_spm_results_1sample/con5/spmT_0001_thr.nii'),
colorbar=True, threshold=2, display_mode='lyrz', black_bg=True, vmax=10, title='Positive effect');
plotting.plot_glass_brain(opj(experiment_dir, 'level2_spm_results_1sample/con6/spmT_0001_thr.nii'),
colorbar=True, threshold=2, display_mode='lyrz', black_bg=True, vmax=10, title='Positive effect Famous>Unfamiliar');
plotting.plot_glass_brain(opj(experiment_dir, 'level2_spm_results_1sample/con7/spmT_0001_thr.nii'),
colorbar=True, threshold=2, display_mode='lyrz', black_bg=True, vmax=10, title='Positive effect Unfamiliar>Scambled');
plotting.plot_glass_brain(opj(experiment_dir, 'level2_spm_results_1sample/con8/spmT_0001_thr.nii'),
colorbar=True, threshold=2, display_mode='lyrz', black_bg=True, vmax=10, title='Positive Effect of rep1>rep2');
plotting.plot_glass_brain(opj(experiment_dir, 'level2_spm_results_1sample/con9/spmT_0001_thr.nii'),
colorbar=True, threshold=2, display_mode='lyrz', black_bg=True, vmax=10, title='Positive Interaction Face (Famous/Unfamiliar) x Rep');
plotting.plot_glass_brain(opj(experiment_dir, 'level2_spm_results_1sample/con10/spmT_0001_thr.nii'),
colorbar=True, threshold=2, display_mode='lyrz', black_bg=True, vmax=10, title='Positive Interaction Face (Unfamiliar/Scrambled) x Rep');
/opt/conda/lib/python3.11/site-packages/nilearn/plotting/img_plotting.py:1471: UserWarning: Non-finite values detected. These values will be replaced with zeros.
safe_get_data(stat_map_img, ensure_finite=True),
/opt/conda/lib/python3.11/site-packages/nilearn/plotting/displays/_slicers.py:308: UserWarning: empty mask
ims = self._map_show(img, type="imshow", threshold=threshold, **kwargs)
Visualize main effects face and interaction face x repetition#
plotting.plot_glass_brain(opj(experiment_dir, 'level2_spm_results_2sample/MainEffectFace/thresh_con3/spmF_0003_thr.nii'),
colorbar=True, display_mode='lyrz', black_bg=True, vmax=10, title='Main effect face');
plotting.plot_glass_brain(opj(experiment_dir, 'level2_spm_results_2sample/InteractionFace_Repetition/thresh_con3/spmF_0003_thr.nii'),
colorbar=True, display_mode='lyrz', black_bg=True, vmax=10, title='Interaction face x repetition');
