def preprocessing_raw(fpath, subj):
# load data and read event channels
rawlist = []
evelist = []
# extracting bdf filenames into bdfs
bdfs = fnmatch.filter(os.listdir(fpath), subj + '_ITD*.bdf')
if len(bdfs) >= 1:
for k, bdf in enumerate(bdfs):
rawtemp, evestemp = bs.importbdf(fpath + bdf)
rawlist += [rawtemp,]
evelist += [evestemp,]
else:
RuntimeError("No bdf files found!")
raw, eves = mne.concatenate_raws(rawlist, events_list = evelist)
# Things to try if data are too noisy
# raw.info['bads'] += ['A20'] # if A7, A6, A24 have been rejected a lot, they can be added manually
# raw.set_eeg_reference(ref_channels = ['Average']) # referencing to the average of all channels, do this if channels are too noisy
# the returned eves has three columns: sample number, value of onset, value of offset.
eves2 = eves.copy()
eves2[:, 1] = np.mod(eves2[:, 1], 256)
eves2[:, 2] = np.mod(eves2[:, 2], 256)
# raw.plot(events=eves2)
raw.filter(l_freq = 1, h_freq=50) # if channels are noisy, adjust the filter parameters, high-pass frequency is better set at 1 compared to 0.5 Hz, to get rid of low-frequency drift
# SSP for blinks
blinks = find_blinks(raw, ch_name = ['A1',], l_trans_bandwidth=0.5,
l_freq=1.0) # A1 is the closest electrode to eyebrow, raw.plot(events=blinks) shows the lines at eye blinks, 998 is default event_id
epochs_blinks = mne.Epochs(raw, blinks, 998, tmin = -0.25, tmax = 0.25,
proj = False, baseline = (-0.25, 0),
reject=dict(eeg=500e-6))
n_eeg = 4
blink_projs = compute_proj_epochs(epochs_blinks, n_grad=0,
n_mag=0, n_eeg=n_eeg,
verbose='DEBUG')
if subj in ['S025', 'S031', 'S046', 'S117', 'S123', 'S127', 'S128', 'S132', 'S133', 'S143', 'S149', 'S051', 'S183', 'S185', 'S187', 'S189', 'S193', 'S195', 'S196', 'S043', 'S072', 'S078', 'S191', 'S129', 'S141', 'S190', 'S194']:
#raw.add_proj(blink_projs) # adding all projections
#raw.del_proj()
#raw.plot_projs_topomap()
raw.add_proj([blink_projs[0], blink_projs[2]])
elif subj in ['S135', 'S192', 'S197', 'S199', 'S216', 'S218']:
raw.add_proj([blink_projs[0], blink_projs[1]])
elif subj in ['S084', 'S075']:
raw.add_proj([blink_projs[0]])
return raw, eves2
blinks = find_blinks(data_eeg,
ch_name=['A1'],
thresh=100e-6,
l_trans_bandwidth=0.5,
l_freq=1.0)
blink_epochs = mne.Epochs(data_eeg,
blinks,
998,
tmin=-0.25,
tmax=0.25,
proj=False,
baseline=(-0.25, 0),
reject=dict(eeg=500e-6))
Projs = compute_proj_epochs(blink_epochs,
n_grad=0,
n_mag=0,
n_eeg=8,
verbose='DEBUG')
if subject == 'S207':
ocular_projs = [Projs[0], Projs[2]]
elif subject == 'S228':
ocular_projs = [Projs[0], Projs[2]]
elif subject == 'S236':
ocular_projs = [Projs[0]]
elif subject == 'S238':
ocular_projs = [Projs[0], Projs[2]]
elif subject == 'S239':
ocular_projs = [Projs[0], Projs[2]]
elif subject == 'S246':
ocular_projs = [Projs[0], Projs[2]]
],
l_trans_bandwidth='auto')
blinkname = (fpath + subj + '_' + para + '_blinks_erp' + ssstag +
'-eve.fif')
mne.write_events(blinkname, blinks)
epochs_blinks = mne.Epochs(raw,
blinks,
998,
tmin=-0.25,
tmax=0.25,
proj=True,
baseline=(-0.25, 0),
reject=dict(grad=8000e-13, mag=8e-12))
blink_projs = compute_proj_epochs(epochs_blinks,
n_grad=2,
n_mag=2,
n_eeg=0,
verbose='DEBUG')
raw.add_proj(blink_projs)
# SSP for cardiac artifact
if ('ECG063' in raw.ch_names) and ekg:
qrschan = 'ECG063'
thresh = 20e-6
else:
qrschan = 'MEG1711'
thresh = 1e-12
qrs = find_blinks(raw,
ch_name=[
qrschan,
],
tmin=-0.25,
tmax=0.25,
proj=False,
baseline=(-0.25, 0),
reject=dict(eeg=500e-6))
blinkITD_epochs = mne.Epochs(ITD_eeg,
blinks_ITD,
998,
tmin=-0.25,
tmax=0.25,
proj=False,
baseline=(-0.25, 0),
reject=dict(eeg=500e-6))
Projs_IAC = compute_proj_epochs(blinkIAC_epochs,
n_grad=0,
n_mag=0,
n_eeg=8,
verbose='DEBUG')
Projs_ITD = compute_proj_epochs(blinkITD_epochs,
n_grad=0,
n_mag=0,
n_eeg=8,
verbose='DEBUG')
if Subject == 'S211':
eye_projsIAC = [Projs_IAC[0], Projs_IAC[2]]
eye_projsITD = [Projs_ITD[0], Projs_ITD[2]]
elif Subject == 'S203':
eye_projsIAC = [Projs_IAC[0], Projs_IAC[1]]
eye_projsITD = [Projs_ITD[0], Projs_ITD[1]]
elif Subject == 'S204':
tmin=-0.25,
tmax=0.25,
proj=False,
baseline=(-0.25, 0),
reject=dict(eeg=500e-6))
blinkITD_epochs = mne.Epochs(ITD_eeg,
blinks_ITD,
998,
tmin=-0.25,
tmax=0.25,
proj=False,
baseline=(-0.25, 0),
reject=dict(eeg=500e-6))
Projs_IAC = compute_proj_epochs(blinkIAC_epochs,
n_grad=0,
n_mag=0,
n_eeg=5)
Projs_ITD = compute_proj_epochs(blinkITD_epochs,
n_grad=0,
n_mag=0,
n_eeg=5)
if Subject == 'S211':
eye_projsIAC = [Projs_IAC[0], Projs_IAC[1]]
eye_projsITD = [Projs_ITD[0], Projs_IAC[1]]
elif Subject == 'S203':
eye_projsIAC = [Projs_IAC[0], Projs_ITD[1]]
eye_projsITD = [Projs_ITD[0], Projs_ITD[1]]
elif Subject == 'S204':
eye_projsIAC = [Projs_IAC[0], Projs_ITD[1]]
eye_projsITD = [Projs_ITD[0], Projs_ITD[1]]
#%% Load data and filter
datapath = os.path.join(data_loc, subject)
data_eeg,data_evnt = EEGconcatenateFolder(datapath+'/',nchans,refchans,exclude)
data_eeg.filter(l_freq=1,h_freq=600)
#%% Remove bad channels
#%% Blink Removal
blinks = find_blinks(data_eeg,ch_name = ['A1'],thresh = 100e-6, l_trans_bandwidth = 0.5, l_freq =1.0)
blink_epochs = mne.Epochs(data_eeg,blinks,998,tmin=-0.25,tmax=0.25,proj=False,
baseline=(-0.25,0),reject=dict(eeg=500e-6))
Projs = compute_proj_epochs(blink_epochs,n_grad=0,n_mag=0,n_eeg=8)
if subject == 'S211':
ocular_projs = [Projs[0]] #not using Projs[2] for now
data_eeg.add_proj(ocular_projs)
data_eeg.plot_projs_topomap()
#data_eeg.plot(events=blinks,show_options=True)
del blinks, blink_epochs, Projs,ocular_projs
#%% Plot data
fs = data_eeg.info['sfreq']
reject = dict(eeg=1000e-6)
epochs = mne.Epochs(data_eeg,data_evnt,1,tmin=-0.3,tmax=np.ceil(mseq.size/fs)+0.4, reject = reject, baseline=(-0.1,0.))
def processing(stimulus, subj, fpath):
# load data and read event channels
rawlist = []
evelist = []
# extracting bdf filenames into bdfs
if stimulus == 'ITD':
bdfs = fnmatch.filter(os.listdir(fpath), subj + '_ITD*.bdf')
elif stimulus == 'Atten':
bdfs = fnmatch.filter(os.listdir(fpath), subj + '_Atten*.bdf')
if len(bdfs) >= 1:
for k, bdf in enumerate(bdfs):
rawtemp, evestemp = bs.importbdf(fpath + bdf)
rawlist += [rawtemp,]
evelist += [evestemp,]
else:
RuntimeError("No bdf files found!")
# the returned eves has three columns: sample number, value of onset, value of offset.
raw, eves = mne.concatenate_raws(rawlist, events_list = evelist)
# Things to try if data are too noisy
# raw.info['bads'] += ['A7', 'A6', 'A24'] # if A7, A6, A24 have been rejected a lot, they can be added manually
# raw.set_eeg_reference(ref_channels=['Average']) # referencing to the average of all channels, do this if channels are too noisy
eves2 = eves.copy()
# the eves are in 16 bits originally, so this operation only looks at the lower 8 bits. higher 8 bits are always
# high, representing button box condition. If interested in what's happening at button press, do np.floor(eves2[:,1]/256)
eves2[:, 1] = np.mod(eves2[:, 1], 256)
eves2[:, 2] = np.mod(eves2[:, 2], 256)
if stimulus == 'ITD' or stimulus == 'Atten':
raw.filter(l_freq = 1, h_freq=50) # if channels are noisy, adjust the filter parameters
# raw.plot(events=eves2)
# SSP for blinks
blinks = find_blinks(raw, ch_name = ['A1',], l_trans_bandwidth=0.5,
l_freq=1.0) # A1 is the closest electrode to eyebrow
# blink and eves2 triggers can be combined using np.concatenate((eves2, blinks), axis = 0)
# raw.plot(events=blinks) shows the lines at eye blinks
# the trigger for blinks can be chosen to be starting from 1000, just to make sure it doesn't collide with the triggers for conditions
epochs_blinks = mne.Epochs(raw, blinks, 998, tmin = -0.25, tmax = 0.25,
proj = False, baseline = (-0.25, 0),
reject=dict(eeg=500e-6))
# evoked_blinks = epochs_blinks.average()
# evoked_blinks_data = evoked_blinks.data[np.arange(32),:]
# PCA is only applied to the epochs around eye blinks. Since the eye blinks are
# contributing the most to the variance within this chunk of window,
# the first PCA (first eigenvector) is going to be due to the eye blink
# for sure and removed. If the PCA was performed on the whole samples, we wouldn't
# know which vector is going to be linked to the eye blink
# for "n_eeg", it's recommended to remove only the biggest projection, which is eye blinks in this case
# greater n_eeg removes more nueral data, which is not favorable
n_eeg = 4
blink_projs = compute_proj_epochs(epochs_blinks, n_grad=0,
n_mag=0, n_eeg=n_eeg,
verbose='DEBUG')
projN = np.zeros(2)
if subj in ['S025', 'S031', 'S046', 'S117', 'S123', 'S127', 'S128', 'S132', 'S133', 'S143', 'S149', 'S051', 'S183', 'S185', 'S187', 'S189', 'S193', 'S195', 'S196', 'S043', 'S072', 'S075', 'S078', 'S191', 'S129', 'S141', 'S190', 'S021', 'S024', 'S028', 'S083', 'S119', 'S121', 'S122', 'S139', 'S140', 'S142', 'S144', 'S145']:
#raw.add_proj(blink_projs) # adding all projections
raw.add_proj([blink_projs[0], blink_projs[2]]) # raw.del_proj()
projN = [1, 3]
elif subj in ['S135', 'S192', 'S194', 'S197', 'S199', 'S216', 'S218']:
raw.add_proj([blink_projs[0], blink_projs[1]]) # raw.del_proj()
projN = [1, 2]
elif subj in ['S084']:
raw.add_proj([blink_projs[0]]) # raw.del_proj()
projN = [1, 0]
# raw.plot_projs_topomap() shows the 4 max PCAs (eigenvectors)
# raw.plot(events = blinks, show_options = True) could show the options for applying different projections
# if channels are too noisy, play with n_eeg, if the second variance is acting more than
# the first, that means the channels are contaminated not just by the eye blinks, but also
# from other sources
# MANUALLY SELECT PROJECTIONS BY PLOTTING raw.plot_projs_topomap
# REMOVE EXTRA PROJS USING raw.del_proj -- Remember index starts at 0
return raw, eves2, projN
proj=False, # why is proj true is we havent generated one yet?
baseline=(-0.25, 0), # what is point of baseline correction for blinks
reject=dict(eeg=500e-6))
epochs_blinksRS = mne.Epochs(
rawRS,
blinksRS,
998,
tmin=-0.25,
tmax=0.25,
proj=False, # why is proj true is we havent generated one yet?
baseline=(-0.25, 0), # what is point of baseline correction for blinks
reject=dict(eeg=500e-6))
blink_projsHB = compute_proj_epochs(epochs_blinksHB,
n_grad=0,
n_mag=0,
n_eeg=6,
verbose='DEBUG')
blink_projsRS = compute_proj_epochs(epochs_blinksRS,
n_grad=0,
n_mag=0,
n_eeg=6,
verbose='DEBUG')
#All_projs = mne.compute_proj_raw(raw,start=0,stop=None,duration=None,n_grad=0,n_mag=0,n_eeg=10,reject=dict(eeg=500e-6),verbose = 'DEBUG')
#ica = mne.preprocessing.ICA()
#ica.fit(raw)
blink_projsHB = [blink_projsHB[0], blink_projsHB[2]]
blink_projsRS = [blink_projsRS[0], blink_projsRS[1]]
#eog_events = mne.preprocessing.find_eog_events(raw,ch_name='EXG5')
#eog_epochs = mne.preprocessing.create_eog_epochs(raw,ch_name='EXG5')
from mne.preprocessing.ssp import compute_proj_epochs
epochs_blinks = mne.Epochs(
raw,
blinks,
998,
tmin=-0.25,
tmax=0.25,
proj=False, # why is proj true is we havent generated one yet?
baseline=(-0.25, 0), # what is point of baseline correction for blinks
reject=dict(eeg=500e-6))
blink_projs = compute_proj_epochs(
epochs_blinks,
n_grad=0,
n_mag=0,
n_eeg=8, #n_eeg = 2 b/c blinks and horizontal movements
verbose='DEBUG')
blink_projs = [blink_projs[0], blink_projs[2]]
raw.add_proj(blink_projs) #how much do we affect the neural data with this
raw.plot_projs_topomap()
raw.plot(events=blinks, scalings=scalings, show_options=True)
epochsAll = mne.Epochs(raw,
eves, [1, 2, 3],
tmin=-0.4,
tmax=4.4,
proj=False,
#eog_epochs = mne.preprocessing.create_eog_epochs(raw,ch_name='EXG5')
from mne.preprocessing.ssp import compute_proj_epochs
epochs_blinks = mne.Epochs(
raw,
blinks,
998,
tmin=-0.25,
tmax=0.25,
proj=False, # why is proj true is we havent generated one yet?
baseline=(-0.25, 0), # what is point of baseline correction for blinks
reject=dict(eeg=500e-6))
blink_projs = compute_proj_epochs(epochs_blinks,
n_grad=0,
n_mag=0,
n_eeg=6,
verbose='DEBUG')
#All_projs = mne.compute_proj_raw(raw,start=0,stop=None,duration=None,n_grad=0,n_mag=0,n_eeg=10,reject=dict(eeg=500e-6),verbose = 'DEBUG')
#ica = mne.preprocessing.ICA()
#ica.fit(raw)
#blink_projs = [blink_projs[0], blink_projs[2]] <- use this for subject HB
blink_projs = [blink_projs[0], blink_projs[1]]
raw.add_proj(blink_projs)
#raw.add_proj(All_projs)
raw.plot_projs_topomap()
raw.plot(events=blinks, scalings=scalings, show_options=True)
