def main():
eeg_device, experiment, record_duration, save_fn = intro_prompt()
# run experiment
if experiment == 'visual-N170':
n170.present(duration=record_duration, eeg=eeg_device, save_fn=save_fn)
elif experiment == 'visual-P300':
p300.present(duration=record_duration, eeg=eeg_device, save_fn=save_fn)
elif experiment == 'visual-SSVEP':
ssvep.present(duration=record_duration,
eeg=eeg_device,
save_fn=save_fn)
elif experiment == 'auditory_oddball':
conditions_file = 'MUSE_conditions.mat'
F = h5py.File(conditions_file, 'r') #['museEEG']
highPE = np.squeeze(F['museEEG']['design']['highPE'][:]).astype(int)
lowPE = np.squeeze(F['museEEG']['design']['lowPE'][:]).astype(int)
inputs = np.squeeze(F['museEEG']['design']['inputs'][:]).astype(int)
oddball = np.squeeze(F['museEEG']['design']['oddball'][:]).astype(int)
oddball -= 1
stim_types = oddball
itis = np.ones_like(oddball) * 0.5
newAdditionalMarkers = []
for i in range(0, len(highPE)):
newAdditionalMarker = str(stim_types[i]) + str(highPE[i]) + str(
lowPE[i])
newAdditionalMarkers.append(newAdditionalMarker)
additional_labels = {'labels': newAdditionalMarkers}
auditoryaMMN.present(
record_duration=record_duration,
stim_types=stim_types,
itis=itis,
additional_labels={'labels': newAdditionalMarkers},
eeg=eeg_device,
save_fn=save_fn)
def run_experiment(experiment, record_duration, eeg_device, save_fn):
if experiment == "visual-N170":
n170.present(duration=record_duration, eeg=eeg_device, save_fn=save_fn)
elif experiment == "visual-P300":
p300.present(duration=record_duration, eeg=eeg_device, save_fn=save_fn)
elif experiment == "visual-SSVEP":
ssvep.present(duration=record_duration, eeg=eeg_device, save_fn=save_fn)
elif experiment == "auditory-SSAEP":
ssaep.present(duration=record_duration, eeg=eeg_device, save_fn=save_fn)
elif experiment == "auditory-oddball":
# conditions_file = os.path.join(eegnb_file, 'experiments', 'auditory-oddball', "MUSE_conditions.mat")
F = h5py.File(mcond_file, "r") # ['museEEG']
highPE = np.squeeze(F["museEEG"]["design"]["highPE"][:]).astype(int)
lowPE = np.squeeze(F["museEEG"]["design"]["lowPE"][:]).astype(int)
inputs = np.squeeze(F["museEEG"]["design"]["inputs"][:]).astype(int)
# based on inputs, creating oddball paradigms markers depending on "switch"
tonenums = maketonesnums(1800)
oddball3 = makeoddball(inputs, 3)
oddball4 = makeoddball(inputs, 4)
oddball5 = makeoddball(inputs, 5)
oddball6 = makeoddball(inputs, 6)
# modifying 0s in PE definitions of tones that represent markers to 3s to avoid loss of trials instead of ignoring them
for i in range(len(highPE)):
if highPE[i] == 0:
highPE[i] = 3
if lowPE[i] == 0:
lowPE[i] = 3
# 1 is standard/bottom, 2 is deviant/high, 3 is "baseline trial"
stim_types = inputs
itis = np.ones_like(inputs) * 0.5
newAdditionalMarkers = []
for i in range(0, len(highPE)):
newAdditionalMarker = (
str(oddball3[i])
+ str(oddball4[i])
+ str(oddball5[i])
+ str(oddball6[i])
+ str(highPE[i])
+ str(lowPE[i])
)
newAdditionalMarkers.append(newAdditionalMarker)
additional_labels = {"labels": newAdditionalMarkers}
aMMN.present(
record_duration=record_duration,
stim_types=stim_types,
itis=itis,
additional_labels={"labels": newAdditionalMarkers},
eeg=eeg_device,
save_fn=save_fn,
)
def run_experiment(experiment, record_duration, eeg_device, save_fn):
if experiment == 'visual-N170':
n170.present(duration=record_duration, eeg=eeg_device, save_fn=save_fn)
elif experiment == 'visual-P300':
p300.present(duration=record_duration, eeg=eeg_device, save_fn=save_fn)
elif experiment == 'visual-SSVEP':
ssvep.present(duration=record_duration,
eeg=eeg_device,
save_fn=save_fn)
def main():
eeg_device, experiment, record_duration, save_fn = intro_prompt()
# run experiment
if experiment == 'visual-N170':
n170.present(duration=record_duration, eeg=eeg_device, save_fn=save_fn)
elif experiment == 'visual-P300':
p300.present(duration=record_duration, eeg=eeg_device, save_fn=save_fn)
elif experiment == 'visual-SSVEP':
ssvep.present(duration=record_duration,
eeg=eeg_device,
save_fn=save_fn)
def run_experiment(experiment, record_duration, eeg_device, save_fn):
if experiment == 'visual-N170':
n170.present(duration=record_duration, eeg=eeg_device, save_fn=save_fn)
elif experiment == 'visual-P300':
p300.present(duration=record_duration, eeg=eeg_device, save_fn=save_fn)
elif experiment == 'visual-SSVEP':
ssvep.present(duration=record_duration, eeg=eeg_device, save_fn=save_fn)
elif experiment == 'auditory-SSAEP':
ssaepupdate.present(duration=record_duration, eeg=eeg_device, save_fn=save_fn)
elif experiment == 'auditory_oddball':
conditions_file = os.path.join(os.path.dirname(os.path.abspath("__file__")), "MUSE_conditions.mat")
F = h5py.File(conditions_file, 'r')#['museEEG']
highPE = np.squeeze(F['museEEG']['design']['highPE'][:]).astype(int)
lowPE = np.squeeze(F['museEEG']['design']['lowPE'][:]).astype(int)
inputs = np.squeeze(F['museEEG']['design']['inputs'][:]).astype(int)
#based on inputs, creating oddball paradigms markers depending on "switch"
tonenums = maketonesnums(1800)
oddball3 = makeoddball(inputs, 3)
oddball4 = makeoddball(inputs, 4)
oddball5 = makeoddball(inputs, 5)
oddball6 = makeoddball(inputs, 6)
#modifying 0s in PE definitions of tones that represent markers to 3s to avoid loss of trials instead of ignoring them
for i in range(len(highPE)):
if highPE[i] == 0:
highPE[i] = 3
if lowPE[i] == 0:
lowPE[i] = 3
#1 is standard/bottom, 2 is deviant/high, 3 is "baseline trial"
stim_types = inputs
itis = np.ones_like(inputs)*0.5
newAdditionalMarkers = [];
for i in range(0, len(highPE)):
newAdditionalMarker = str(oddball3[i]) + str(oddball4[i]) + str(oddball5[i]) + str(oddball6[i]) + str(highPE[i]) + str(lowPE[i])
newAdditionalMarkers.append(newAdditionalMarker)
additional_labels = {'labels' : newAdditionalMarkers}
auditoryaMMN.present(record_duration=record_duration,stim_types=stim_types,itis=itis, additional_labels = {'labels' : newAdditionalMarkers}, eeg=eeg_device, save_fn=save_fn)
# # Imports import os from eegnb import generate_save_fn from eegnb.devices.eeg import EEG from eegnb.experiments.visual_ssvep import ssvep # Define some variables board_name = "muse" experiment = "visual_ssvep" subject_id = 0 session_nb = 0 record_duration = 120 ################################################################################################### # Initiate EEG device # --------------------- # # Start EEG device eeg_device = EEG(device=board_name) # Create save file name save_fn = generate_save_fn(board_name, experiment, subject_id, session_nb) print(save_fn) ################################################################################################### # Run experiment # --------------------- # ssvep.present(duration=record_duration, eeg=eeg_device, save_fn=save_fn)