Hi! I would like to ask how you got datast structure like in adhd200_sample from nilearn.datasets. That would help me very much to perform some academic tasks on this code:
#Using a filter to extract the regions time series
from nilearn import input_data
masker = input_data.NiftiMapsMasker(components_img, smoothing_fwhm=6,
standardize=False, detrend=True,
t_r=2.5, low_pass=0.1,
high_pass=0.01)
#Computing the regions signals and extracting the phenotypic information of interest
subjects = []
adhds = []
sites = []
labels = []
for func_file, confound_file, phenotypic in zip(
adhd_data.func, adhd_data.confounds, adhd_data.phenotypic):
time_series = masker.fit_transform(func_file, confounds=confound_file)
subjects.append(time_series)
print(adhd_data.confounds)
is_adhd = phenotypic[‘adhd’]
if is_adhd == 1:
adhds.append(time_series)
sites.append(phenotypic[‘site’])
labels.append(phenotypic[‘adhd’])
This code needs the regressors files which I can not find in other fMRI dataset structures like full ADHD-200
‘/home/milan/nilearn_data/adhd/data/0010042/0010042_regressors.csv’,
‘/home/milan/nilearn_data/adhd/data/0010064/0010064_regressors.csv’,
‘/home/milan/nilearn_data/adhd/data/0010128/0010128_regressors.csv’,
‘/home/milan/nilearn_data/adhd/data/0021019/0021019_regressors.csv’,
‘/home/milan/nilearn_data/adhd/data/0023008/0023008_regressors.csv’,