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robertoostenveld committed Jan 30, 2023
1 parent a4bdb17 commit f170dbf
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8 changes: 4 additions & 4 deletions template/headmodel.md
Original file line number Diff line number Diff line change
Expand Up @@ -21,9 +21,9 @@ You can load and visualize it with

headmodel =
struct with fields:
bnd: [1×3 struct]
bnd: [1x3 struct]
cond: [0.3300 0.0041 0.3300]
mat: [3000×3000 double]
mat: [3000x3000 double]
type: 'dipoli'
unit: 'mm'
Expand All @@ -50,8 +50,8 @@ You can load and visualize it with
mri =
struct with fields:
dim: [181 217 181]
anatomy: [181×217×181 uint8]
transform: [4×4 double]
anatomy: [181x217x181 uint8]
transform: [4x4 double]
unit: 'mm'
coordsys: 'spm'

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26 changes: 13 additions & 13 deletions tutorial/headmodel_eeg_bem.md
Original file line number Diff line number Diff line change
Expand Up @@ -61,10 +61,10 @@ Then, you can read in the anatomical MRI data.

disp(mri)
dim: [256 256 256]
anatomy: [256×256×256 int16]
hdr: [1×1 struct]
transform: [4×4 double]
fid: [1×1 struct]
anatomy: [256x256x256 int16]
hdr: [1x1 struct]
transform: [4x4 double]
fid: [1x1 struct]
unit: 'mm'
coordsys: 'ctf'

Expand Down Expand Up @@ -214,11 +214,11 @@ We can change the segmentation from the probabilistic (or in this case Boolean)

disp(segmentedmri_indexed)
dim: [256 256 256]
transform: [4×4 double]
transform: [4x4 double]
coordsys: 'ctf'
unit: 'mm'
cfg: [1×1 struct]
tissue: [256×256×256 double]
cfg: [1x1 struct]
tissue: [256x256x256 double]
tissuelabel: {'scalp' 'skull' 'brain'}
After adding the anatomical data to the segmentation, we can plot them together.
Expand Down Expand Up @@ -352,11 +352,11 @@ There are many EEG manufacturers and almost as many EEG electrode placement syst
elec = ft_read_sens('standard_1020.elc');

disp(elec)
chanpos: [97×3 double]
chantype: {97×1 cell}
chanunit: {97×1 cell}
elecpos: [97×3 double]
label: {97×1 cell}
chanpos: [97x3 double]
chantype: {97x1 cell}
chanunit: {97x1 cell}
elecpos: [97x3 double]
label: {97x1 cell}
type: 'eeg1010'
unit: 'mm'

Expand Down Expand Up @@ -466,7 +466,7 @@ The headshape method is easiest for the pre-auricular points, as you can regogni
20.4483 67.4268 3.3728
16.4416 -70.3234 2.5651
disp(fiducials.label)
4×1 cell array
4x1 cell array
{'nas'}
{'ini'}
{'lpa'}
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