os.makedirs(dr, exist_ok=True)
for task in contrasts:
task_dr = os.path.join(dr, task)
os.makedirs(task_dr, exist_ok=True)
cs = contrasts[task]
# Save activation maps
activation_dr = os.path.join(task_dr, 'Activations')
os.makedirs(activation_dr, exist_ok=True)
scale = scales[task]
cortical_data, subcortical_data, _, _ = get_data(task=task,
cs=cs,
scale=scale)
for cort, subcort, contrast in zip(cortical_data, subcortical_data, cs):
# Cast to nifti & save cort
cort_lh = nib.Nifti1Image(cort[0].reshape((163842, 1, 1)),
affine=np.eye(4))
cort_rh = nib.Nifti1Image(cort[1].reshape((163842, 1, 1)),
affine=np.eye(4))
nib.save(cort_lh, os.path.join(activation_dr, contrast + '_lh.nii.gz'))
nib.save(cort_rh, os.path.join(activation_dr, contrast + '_rh.nii.gz'))
# Save subcort
nib.save(subcort,
os.path.join(activation_dr, contrast + '_subcort.nii.gz'))
def plot_mid(plot=True):
task = 'MID'
plot = True
scale = .98
figure = plt.figure(figsize=(20, 10))
outer_grid =\
gridspec.GridSpec(nrows=2, ncols=6,
wspace=None, hspace=None,
width_ratios=[.35, 1, 1, 1, 1, .1],
height_ratios=None)
text_ax = figure.add_subplot(outer_grid[0, 0])
text_ax.text(0, 1, 'MID', fontsize=NAME_SIZE, weight="bold")
text_ax.text(0, .75, 'a)\nCortical\nactivation', fontsize=TITLE_SIZE)
text_ax.text(0, .12, 'b)\nSubcortical\nactivation', fontsize=TITLE_SIZE)
text_ax.set_axis_off()
text_ax2 = figure.add_subplot(outer_grid[1, 0])
text_ax2.text(0, .75, '\nCortical\nactivation', fontsize=TITLE_SIZE)
text_ax2.text(0, .12, '\nSubcortical\nactivation', fontsize=TITLE_SIZE)
text_ax2.set_axis_off()
# Contrasts to plot
contrasts = [
'Antic._large_reward_vs._neutral', 'Antic._large_loss_vs._neutral',
'Reward_pos._vs._neg._feedback', 'Loss_pos._vs._neg._feedback',
'Antic._large_vs._small_reward', 'Antic._large_vs._small_loss'
]
# Load data
cortical_data, subcortical_data, vmin, vmax =\
get_data(task, contrasts, scale=scale)
# Plot data
smfs, cnt, cnt2 = [], 0, 0
for i, contrast in enumerate(contrasts):
# For plotting in columns
if cnt == 4:
cnt2 += 1
cnt = 0
# Clean contrast name
contrast = contrast.replace('_', ' ')
# Plot
smfs.append(
fill_spot(figure,
contrast,
outer_grid,
cnt2,
cnt + 1,
cortical_data[i],
subcortical_data[i],
cmap='cold_hot',
vmin=vmin,
vmax=vmax,
threshold=.2,
plot=plot))
cnt += 1
# Add color bar
colorbar_ax = figure.add_subplot(outer_grid[0, 5])
colorbar_ax.set_axis_off()
add_collage_colorbar(figure=figure,
ax=colorbar_ax,
smfs=smfs,
vmax=vmax,
vmin=vmin,
multicollage=True,
cbar_shrink=1,
cbar_aspect=30,
cbar_pad=0,
cmap='cold_hot',
threshold=.2,
nb_ticks=5,
round_dec=2)
# Add reliability
bot_outer_grid = gridspec.GridSpecFromSubplotSpec(
nrows=2,
ncols=2,
subplot_spec=outer_grid[1:, 3:],
width_ratios=[0.01, 2],
height_ratios=[1, .025])
# Load reliability
cort_rely, subcort_rely = load_rely(task, contrasts)
# Add plot
rely1_ax = figure.add_subplot(bot_outer_grid[0, 1])
make_plot(rely1_ax,
'c) Reproducibility',
list(zip(cort_rely, subcort_rely)),
contrasts,
sz=6,
legend_alpha=.5,
low_val=-.2,
yticks=[0, .2, .4, .6, .8, 1.0],
x_lim=(-10, 2500),
cspaces=13,
sspaces=11)
#figure.savefig('Figures/mid.png', dpi=500, bbox_inches='tight')
figure.savefig('Figures/mid.tiff',
bbox_inches='tight',
dpi=500,
transparent=False)
plt.close(figure)
def plot_sst(plot=True):
scale = .99
task = 'SST'
figure = plt.figure(figsize=(20, 10))
# Top grid
grid = gridspec.GridSpec(nrows=2,
ncols=6,
wspace=None,
hspace=.1,
width_ratios=[3.5, 10, 10, 10, 1, 10],
height_ratios=None)
text_ax = figure.add_subplot(grid[0, 0])
text_ax.text(0, 1, 'SST', fontsize=NAME_SIZE, weight="bold")
text_ax.text(0, .75, 'a)\nCortical\nactivation', fontsize=TITLE_SIZE)
text_ax.text(0, .12, 'b)\nSubcortical\nactivation', fontsize=TITLE_SIZE)
text_ax.set_axis_off()
bot_text_ax = figure.add_subplot(grid[1, 0])
bot_text_ax.text(0, .75, 'c)\nCortical\ncorrelation', fontsize=TITLE_SIZE)
bot_text_ax.text(0,
.12,
'd)\nSubcortical\ncorrelation',
fontsize=TITLE_SIZE)
bot_text_ax.set_axis_off()
# Plot these contrasts
contrasts = [
'Correct_stop_vs._correct_go', 'Incorrect_stop_vs._correct_go',
'Correct_stop_vs._incorrect_stop'
]
# Load the base activation maps
cortical_data, subcortical_data, vmin, vmax =\
get_data(task, contrasts, scale=scale)
# Plot the base activations
smfs, cnt = [], 1
for i, contrast in enumerate(contrasts):
# Replace name
contrast = contrast.replace('_', ' ')
smfs.append(
fill_spot(figure,
contrast,
grid,
0,
cnt,
cortical_data[i],
subcortical_data[i],
cmap='cold_hot',
vmin=vmin,
vmax=vmax,
threshold=.2,
plot=plot))
cnt += 1
# Add colorbar
colorbar_ax = figure.add_subplot(grid[0, 4])
colorbar_ax.set_axis_off()
add_collage_colorbar(figure=figure,
ax=colorbar_ax,
smfs=smfs,
vmax=vmax,
vmin=vmin,
multicollage=True,
cbar_shrink=1,
cbar_aspect=30,
cbar_pad=0,
cmap='cold_hot',
threshold=.2)
# Load corr data
cortical_perf, subcortical_perf, vmin, vmax =\
get_corr_data(task, contrasts, 'tfmri_sst_all_beh_total_meanrt')
# Plot performance corrs
smfs, cnt = [], 1
for i, contrast in enumerate(contrasts):
# Clean name
contrast = contrast.replace('_', ' ')
smfs.append(
fill_spot(figure,
'',
grid,
1,
cnt,
cortical_perf[i],
subcortical_perf[i],
cmap='seismic',
vmin=vmin,
vmax=vmax,
threshold=.000001,
label=" Correlation with SSRT",
plot=plot))
cnt += 1
# Add the performance contrast color bar
bot_colorbar_ax = figure.add_subplot(grid[1, 4])
bot_colorbar_ax.set_axis_off()
add_collage_colorbar(figure=figure,
ax=bot_colorbar_ax,
smfs=smfs,
vmax=vmax,
vmin=vmin,
multicollage=True,
cbar_shrink=1,
cbar_aspect=30,
cbar_pad=0,
cmap='seismic',
threshold=None)
# Plot reliability
rely_grid =\
gridspec.GridSpecFromSubplotSpec(nrows=5, ncols=2,
subplot_spec = grid[:,5],
hspace=0,
height_ratios=[.05, 1, .5, 1, .13],
width_ratios=[0.175, 1])
# Load rely + perf rely
cort_rely, subcort_rely = load_rely(task, contrasts)
cort_p_rely, subcort_p_rely =\
load_perf_rely(task, contrasts, 'tfmri_sst_all_beh_total_meanrt')
# Plot base rely + legend
rely1_ax = figure.add_subplot(rely_grid[1, 1])
make_plot(rely1_ax,
'e) Reproducibility',
list(zip(cort_rely, subcort_rely)),
contrasts,
sz=7,
legend_alpha=.5,
legend_loc=(-.66, -.4),
xlabel=None,
x_lim=(-10, 2500),
cspaces=10,
sspaces=8,
special=True,
yticks=[0, .1, .2, .3, .4, .5, .6, .7, 0.8, 0.9, 1.0],
ylabel='Correlation for activation maps')
# Plot performance rely
rely2_ax = figure.add_subplot(rely_grid[3, 1])
make_plot(rely2_ax,
'',
list(zip(cort_p_rely, subcort_p_rely)),
contrasts,
sz=6,
ylabel='Correlation for performance maps',
low_val=0,
yticks=[0, .1, .2, .3, .4, .5, .6, .7, 0.8, 0.9, 1.0],
x_lim=(-10, 2500),
legend=False)
# Save
#figure.savefig('Figures/sst.png', bbox_inches='tight', dpi=500)
figure.savefig('Figures/sst.tiff',
bbox_inches='tight',
dpi=500,
transparent=False)
plt.close(figure)
def plot_nback2(plot=True):
scale = .98
task = 'nBack'
figure = plt.figure(figsize=(20, 10))
outer_grid = gridspec.GridSpec(nrows=2,
ncols=8,
wspace=None,
hspace=None,
width_ratios=[.75, 1, .1, .3, 1, 1, .1, .1],
height_ratios=None)
text_ax = figure.add_subplot(outer_grid[0, 0])
text_ax.text(0, 1, 'N-Back', fontsize=NAME_SIZE, weight="bold")
text_ax.text(0, .75, 'a)\nCortical\nactivation', fontsize=TITLE_SIZE)
text_ax.text(0, .12, 'b)\nSubcortical\nactivation', fontsize=TITLE_SIZE)
text_ax.text(0, -.5, 'Cortical\nactivation', fontsize=TITLE_SIZE)
text_ax.set_axis_off()
# The contrasts to plot
contrasts = [
'Face_vs._places', 'Negface_vs._neutface', 'Posface_vs._neutface'
]
# Loads faces vs. places seperate
cortical_data1, subcortical_data1, vmin1, vmax1 =\
get_data(task, [contrasts[0]], scale=scale)
cortical_data2, subcortical_data2, vmin2, vmax2 =\
get_data(task, contrasts[1:], scale=scale)
# Plot faces vs places
smfs = []
smfs.append(
fill_spot(figure,
contrasts[0].replace('_', ' '),
outer_grid,
0,
1,
cortical_data1[0],
subcortical_data1[0],
cmap='cold_hot',
vmin=vmin1,
vmax=vmax1,
threshold=.2,
plot=plot))
# Add colorbar
colorbar_ax = figure.add_subplot(outer_grid[0, 2])
colorbar_ax.set_axis_off()
add_collage_colorbar(figure=figure,
ax=colorbar_ax,
smfs=smfs,
vmax=vmax1,
vmin=vmin1,
multicollage=True,
cbar_shrink=1,
cbar_aspect=30,
cbar_pad=0,
cmap='cold_hot',
threshold=.2)
# Plot rest of contrasts
smfs = []
cnt = 4
for i, contrast in enumerate(contrasts[1:]):
contrast = contrast.replace('_', ' ')
smfs.append(
fill_spot(figure,
contrast,
outer_grid,
0,
cnt,
cortical_data2[i],
subcortical_data2[i],
cmap='seismic',
vmin=vmin2,
vmax=vmax2,
threshold=.00000001,
plot=plot))
cnt += 1
# Add seperate color bar
colorbar_ax2 = figure.add_subplot(outer_grid[0, 6])
colorbar_ax2.set_axis_off()
add_collage_colorbar(figure=figure,
ax=colorbar_ax2,
smfs=smfs,
vmax=vmax2,
vmin=vmin2,
multicollage=True,
cbar_shrink=1,
cbar_aspect=30,
cbar_pad=0,
cmap='seismic',
threshold=.00000001)
# Add reliability plots
bot_outer_grid = gridspec.GridSpecFromSubplotSpec(
nrows=1,
ncols=4,
subplot_spec=outer_grid[1, :],
width_ratios=[0.0675, .95, 1.05, .05])
# Load rely
cort_rely, subcort_rely = load_rely(task, contrasts)
rely1_ax = figure.add_subplot(bot_outer_grid[2])
make_plot(rely1_ax,
'c) Reproducibility',
list(zip(cort_rely, subcort_rely)),
contrasts,
sz=6,
legend_alpha=.5,
low_val=-.1,
yticks=[0, .2, .4, .6, .8, 1.0],
x_lim=(-10, 2500),
cspaces=3,
sspaces=1,
ylabel='Correlation for activation maps')
# Add extra cortical view
sml_grid = gridspec.GridSpecFromSubplotSpec(nrows=1,
ncols=2,
subplot_spec=bot_outer_grid[1],
wspace=-.5)
fvp = cortical_data1[0]
fs_avg = nilearn.datasets.fetch_surf_fsaverage(mesh='fsaverage')
# Lh view
lh_ax = figure.add_subplot(sml_grid[0], projection='3d')
plot_surf(fs_avg.infl_left,
fvp[0],
threshold=.2,
view='posterior',
cmap='cold_hot',
vmin=vmin1,
vmax=vmax1,
bg_map=fs_avg.sulc_left,
dist=6,
alpha=1,
bg_on_data=True,
axes=lh_ax)
# Rh view
rh_ax = figure.add_subplot(sml_grid[1], projection='3d')
plot_surf(fs_avg.infl_right,
fvp[1],
threshold=.2,
view='posterior',
cmap='cold_hot',
vmin=vmin1,
vmax=vmax1,
bg_map=fs_avg.sulc_right,
dist=6,
alpha=1,
bg_on_data=True,
axes=rh_ax)
# Set alpha to 0
lh_ax.patch.set_alpha(0)
rh_ax.patch.set_alpha(0)
# Add text
t_ax = figure.add_subplot(sml_grid[0])
t_ax.text(.585, -.12, "Cohen's d map", fontsize=LABEL_SIZE)
t_ax.set_axis_off()
# Save
#figure.savefig('Figures/nback2.png', dpi=500, bbox_inches='tight')
figure.savefig('Figures/nback2.tiff',
bbox_inches='tight',
dpi=500,
transparent=False)
plt.close(figure)
def plot_nback1(plot=True):
scale = .98
task = 'nBack'
figure = plt.figure(figsize=(20, 10))
# Top grid
grid = gridspec.GridSpec(nrows=2,
ncols=6,
wspace=None,
hspace=.1,
width_ratios=[3.5, 10, 10, 10, 1, 10],
height_ratios=None)
# Add side text
text_ax = figure.add_subplot(grid[0, 0])
text_ax.text(0, 1, 'N-Back', fontsize=NAME_SIZE, weight="bold")
text_ax.text(0, .75, 'a)\nCortical\nactivation', fontsize=TITLE_SIZE)
text_ax.text(0, .12, 'b)\nSubcortical\nactivation', fontsize=TITLE_SIZE)
text_ax.set_axis_off()
# Contrasts to plot
contrasts = [
'0-back vs. fixation', '2-back vs. fixation', '2-back_vs._0-back'
]
cortical_data, subcortical_data, vmin, vmax =\
get_data(task, contrasts, scale=scale)
# Plot the base activations
smfs, cnt = [], 1
for i, contrast in enumerate(contrasts):
# Replace name
contrast = contrast.replace('_', ' ')
smfs.append(
fill_spot(figure,
contrast,
grid,
0,
cnt,
cortical_data[i],
subcortical_data[i],
cmap='cold_hot',
vmin=vmin,
vmax=vmax,
threshold=.2,
plot=plot))
cnt += 1
# Add colorbar axis
colorbar_ax = figure.add_subplot(grid[0, 4])
colorbar_ax.set_axis_off()
add_collage_colorbar(figure=figure,
ax=colorbar_ax,
smfs=smfs,
vmax=vmax,
vmin=vmin,
multicollage=True,
cbar_shrink=1,
cbar_aspect=30,
cbar_pad=0,
anchor='W',
cmap='cold_hot',
threshold=.2,
nb_ticks=5,
round_dec=2)
# Add side text
bot_text_ax = figure.add_subplot(grid[1, 0])
bot_text_ax.text(0, .75, 'c)\nCortical\ncorrelation', fontsize=TITLE_SIZE)
bot_text_ax.text(0,
.12,
'd)\nSubcortical\ncorrelation',
fontsize=TITLE_SIZE)
bot_text_ax.set_axis_off()
# Load the performance correlation data
# First with just one 0 back
d0_cortical_data, d0_subcortical_data, d0_vmin, d0_vmax =\
get_corr_data(task, [contrasts[0]], 'dprime_0back')
# Last 2 with 2back
d2_cortical_data, d2_subcortical_data, d2_vmin, d2_vmax =\
get_corr_data(task, contrasts[1:], 'dprime_2back')
# Get performance vmin / vmax
vmin = np.min([d0_vmin, d2_vmin])
vmax = np.max([d0_vmax, d2_vmax])
if np.abs(vmin) > vmax:
vmax = np.abs(vmin)
else:
vmin = -vmax
# Plot the performance contrasts
smfs = []
# 0back w/ 0-back d'
smfs.append(
fill_spot(figure,
'',
grid,
1,
1,
d0_cortical_data[0],
d0_subcortical_data[0],
cmap='seismic',
vmin=vmin,
vmax=vmax,
threshold=.000001,
label=" Correlation with 0-back D'",
plot=plot))
# 2'back with 2-back d' and 2back - 0 back
for i in range(2):
smfs.append(
fill_spot(figure,
'',
grid,
1,
2 + i,
d2_cortical_data[i],
d2_subcortical_data[i],
cmap='seismic',
vmin=vmin,
vmax=vmax,
threshold=.000001,
label=" Correlation with 2-back D'",
plot=plot))
# Add the performance contrast color bar
bot_colorbar_ax = figure.add_subplot(grid[1, 4])
bot_colorbar_ax.set_axis_off()
add_collage_colorbar(figure=figure,
ax=bot_colorbar_ax,
smfs=smfs,
vmax=vmax,
vmin=vmin,
multicollage=True,
cbar_shrink=1,
cbar_aspect=30,
cbar_pad=0,
anchor='W',
cmap='seismic',
threshold=None,
nb_ticks=5,
round_dec=2)
# Add Reliability Plots
rely_grid =\
gridspec.GridSpecFromSubplotSpec(nrows=5, ncols=2,
subplot_spec = grid[:,5],
hspace=0,
height_ratios=[.05, 1, .5, 1, .13],
width_ratios=[0.175, 1])
# Load rely
cort_rely, subcort_rely = load_rely(task, contrasts)
# Load perf rely
cort_p_rely1, subcort_p_rely1 =\
load_perf_rely(task, [contrasts[0]], 'dprime_0back')
cort_p_rely2, subcort_p_rely2 =\
load_perf_rely(task, contrasts[1:], 'dprime_2back')
cort_p_rely = cort_p_rely1 + cort_p_rely2
subcort_p_rely = subcort_p_rely1 + subcort_p_rely2
# Plot base rely + legend
rely1_ax = figure.add_subplot(rely_grid[1, 1])
make_plot(rely1_ax,
'e) Reproducibility',
list(zip(cort_rely, subcort_rely)),
contrasts,
sz=6,
legend_alpha=.5,
legend_loc=(-.5, -.43),
xlabel=None,
x_lim=(-10, 2500),
cspaces=5,
sspaces=2,
yticks=[0, .1, .2, .3, .4, .5, .6, .7, 0.8, 0.9, 1.0],
ylabel='Correlation for activation maps')
# Plot performance rely
rely2_ax = figure.add_subplot(rely_grid[3, 1])
make_plot(rely2_ax,
'',
list(zip(cort_p_rely, subcort_p_rely)),
contrasts,
sz=6,
ylabel='Correlation for performance maps',
low_val=0,
yticks=[0, .1, .2, .3, .4, .5, .6, .7, 0.8, 0.9, 1.0],
x_lim=(-10, 2500),
legend=False)
#figure.savefig('Figures/nback1.png', bbox_inches='tight', dpi=500)
figure.savefig('Figures/nback1.tiff',
bbox_inches='tight',
dpi=500,
transparent=False)
plt.close(figure)