def norm_timeseries(ts_list):
    '\n        ts_list    : list of timeseries arrays, each of shape (timepoints x regions)\n\n    returns:\n        norm_ts    : list of normalised timeseries arrays, same shape as ts_list\n    '
    norm_ts = []
    for ts in ts_list:
        norm_ts.append(nilearn.signal.clean(ts, detrend=False))
    return norm_ts
ts_list    : list of timeseries arrays, each of shape (timepoints x regions)

returns:
    norm_ts    : list of normalised timeseries arrays, same shape as ts_list
def norm_timeseries(ts_list):
    '\n        ts_list    : list of timeseries arrays, each of shape (timepoints x regions)\n\n    returns:\n        norm_ts    : list of normalised timeseries arrays, same shape as ts_list\n    '
    norm_ts = []
    for ts in ts_list:
        norm_ts.append(nilearn.signal.clean(ts, detrend=False))
    return norm_ts