FIX - typos

fieldtrip · Mar 8, 2024 · af2c89f · af2c89f
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diff --git a/assets/wordlist-ignore.txt b/assets/wordlist-ignore.txt
@@ -404,6 +404,9 @@ DICOM
 DICOMs
 DICS
 DIPFIT
+DK
+DKTatlas
+DL
 DLL
 DLLs
 DMA
@@ -598,6 +601,7 @@ FIXME's
 FIl
 FLTK
 FLxx
+FMRIB
 FNS
 FOOOF
 FOV
@@ -668,6 +672,7 @@ Freitas
 Friston
 Frontpanel
 Fs
+FsAverage
 FtBuffer
 Fz
 GAKL
@@ -862,6 +867,7 @@ IPv
 IRASA
 IRQ
 IRRAD
+Irv
 ISFINITE
 ISI
 ISOTRAK
@@ -1401,6 +1407,7 @@ OFA
 OGE
 OHBM
 OOP
+
 OPM
 OPMEG
 OPMs
@@ -1591,6 +1598,7 @@ RHJ
 RHS
 RIKEN
 RITMO
+RK
 RL
 RLTB
 RNet
@@ -2201,6 +2209,7 @@ anatonical
 andusing
 anims
 annd
+annot
 annnouncement
 anonimized
 anonimizing
@@ -2212,6 +2221,7 @@ anr
 anterio
 antomical
 anywave
+aparc
 apear
 apecific
 api
@@ -3250,7 +3260,9 @@ ftcolors
 ftgrid
 ftimwin
 ftmriN
+ftpath
 ftplotmesh
+ftver
 ftwiki
 ftx
 fuPpes
@@ -4255,6 +4267,7 @@ paramters
 paraview
 parcellated
 parcellation
+parcellations
 parfor
 paris
 parlour

diff --git a/template/atlas.md b/template/atlas.md
@@ -79,9 +79,9 @@ Besides the 'v17' version, the 'v18' is also supported.
 
 ## FreeSurfer FsAverage
 
-We often use [FreeSurfer](https://surfer.nmr.mgh.harvard.edu/fswiki/FreeSurferWiki) to extract cortical sheets which we use as the basis for a [source model](/tutorial/sourcemodel) or for the projection of [ECoG electrodes](/tutorial/human_ecog). FreeSurfer also comes with atlasses (or cortical parcellations), which can be used to label the vertices of the individual's cortical sheet.
+We often use [FreeSurfer](https://surfer.nmr.mgh.harvard.edu/fswiki/FreeSurferWiki) to extract cortical sheets which we use as the basis for a [source model](/tutorial/sourcemodel) or for the projection of [ECoG electrodes](/tutorial/human_ecog). FreeSurfer also comes with atlases (or cortical parcellations), which can be used to label the vertices of the individual's cortical sheet.
 
-The FreeSurfer atlasses are quite large and therefore not copied into FieldTrip, but you may have them on your local computer. There are multiple [parcellations available](https://surfer.nmr.mgh.harvard.edu/fswiki/CorticalParcellation):
+The FreeSurfer atlases are quite large and therefore not copied into FieldTrip, but you may have them on your local computer. There are multiple [parcellations available](https://surfer.nmr.mgh.harvard.edu/fswiki/CorticalParcellation):
 
 - Desikan-Killiany Atlas (?h.aparc.annot)
 - Destrieux Atlas (?h.aparc.a2009s.annot)
@@ -111,9 +111,9 @@ You can read the FsAverage parcellations per hemisphere like this:
 
 Following the segmentation and meshing of your individual participant with [recon-all](https://surfer.nmr.mgh.harvard.edu/fswiki/recon-all), you can find a similar `surf` and `label` directory for your participant. Reading the individual parcellation with the anatomical labels is therefore similar to reading them from the fsaverage template.
 
-## FSL atlasses
+## FSL atlases
 
-The [FMRIB Software Library](https://fsl.fmrib.ox.ac.uk/fsl/fslwiki) (FSL) release comes with a number of [atlasses](https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Atlases) that you can also read directly into FieldTrip.
+The [FMRIB Software Library](https://fsl.fmrib.ox.ac.uk/fsl/fslwiki) (FSL) release comes with a number of [atlases](https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/Atlases) that you can also read directly into FieldTrip.
 
     >> cd /opt/fsl/6.0.6/data/atlases  % or wherever your FSL is installed
     >> talairach = ft_read_atlas('Talairach.xml')
@@ -275,7 +275,7 @@ The atlas is described in:
 
 ## See also
 
-The **[ft_read_atlas](/reference/fileio/ft_read_atlas)** function can read geometrical information and anatomical labels from a variety of file formats, and can therefore also be used for other atlasses. You can find more atlases here:
+The **[ft_read_atlas](/reference/fileio/ft_read_atlas)** function can read geometrical information and anatomical labels from a variety of file formats, and can therefore also be used for other atlases. You can find more atlases here:
 - <https://www.loni.usc.edu/research/atlases>
 - <http://www.bmap.ucla.edu/portfolio/atlases>
 - <https://www.ebrains.eu/tools/human-brain-atlas>

diff --git a/tutorial/coregistration_opm.md b/tutorial/coregistration_opm.md
@@ -474,7 +474,7 @@ To facilitate later processing, we will assign a better defined coordinate syste
 _Figure: 3D scan with a coordinate system relating to the head and helmet._
 
 {% include markup/info %}
-As the ears are not visible, you have to click on dummy locations that appropriate the LPA and RPA points. Consequently, your coarse coregistration will be somewhat different from the one here in the tuturioal. In the subsequent code we will use some parameters (rotations, transloations) that depend on this initial coarse coregistration. To make sure that your subsequent results match what is presented here, you should download [example3_face_helmet_aligned.mat](https://download.fieldtriptoolbox.org/tutorial/coregistration_opm/example3_face_helmet_aligned.mat) and load it in MATLAB.
+As the ears are not visible, you have to click on dummy locations that appropriate the LPA and RPA points. Consequently, your coarse coregistration will be somewhat different from the one here in the tutorial. In the subsequent code we will use some parameters (rotations, translations) that depend on this initial coarse coregistration. To make sure that your subsequent results match what is presented here, you should download [example3_face_helmet_aligned.mat](https://download.fieldtriptoolbox.org/tutorial/coregistration_opm/example3_face_helmet_aligned.mat) and load it in MATLAB.
 
     load example3_face_helmet_aligned.mat  % this contains the aligned scan
 {% include markup/end %}

diff --git a/tutorial/mouse_eeg.md b/tutorial/mouse_eeg.md
@@ -314,7 +314,7 @@ FIXME insert figure (6 layout plot)
 
 If you think that some outlines (nose, eyes, head, whiskers and ears) are not necessary, you can pass without assigning any outline. Next step is zero point calibration for the bregma point. If you, however, use customized layout for single subject, you don't need to carry out next step.
 
-Coinsidering the mouse anatomy, the bregma point is located in the middle of the 4th layer of the anterior of the EEG array that it should be set (0, 0) because we follow the Paxinos coordinate system. To calibrate layout position, we just subtract the value of bregma on acquired layout from previous step.
+Considering the mouse anatomy, the bregma point is located in the middle of the 4th layer of the anterior of the EEG array that it should be set (0, 0) because we follow the Paxinos coordinate system. To calibrate layout position, we just subtract the value of bregma on acquired layout from previous step.
 
     bregma = [382, 280];
     layout.pos = layout.pos – repmat(bregma, size(layout.pos, 1), 1);
@@ -344,7 +344,7 @@ If you are satisfy with the result, you should save it to a MATLAB file. However
 
 ### Deal with differences in animal size
 
-The polyimide fiml from which the EEG array is made is not strechable. Each mouse, however, has a different head size depending on its strain, age, weight and sex. To deal with the different sizes, we use the distance between bregma and lambda and a reference scale of 4.2 mm. If you have a smaller mouse, and consequently a relatively wider spaced EEG array for that specific mouse, you can scale the layout to accommodate this. The approach here to deal with differences in the mouse brain size are very comparable to those adopted in the Talairach-Tournoux anatomical atlas of the human brain.
+The polyimide film from which the EEG array is made is not stretchable. Each mouse, however, has a different head size depending on its strain, age, weight and sex. To deal with the different sizes, we use the distance between bregma and lambda and a reference scale of 4.2 mm. If you have a smaller mouse, and consequently a relatively wider spaced EEG array for that specific mouse, you can scale the layout to accommodate this. The approach here to deal with differences in the mouse brain size are very comparable to those adopted in the Talairach-Tournoux anatomical atlas of the human brain.
 
 For example for a mouse with a bregma-lambda distance of 3.8, you can do the following.
 
@@ -405,7 +405,7 @@ Rather than plotting all ERPs on top of each other, we can also plot them accord
 
 FIXME insert figure (9 timelock plot)
 
-When you specify `cfg.interactive = 'no'` you can use the MATLAB zoom buttons. With `cfg.interactive = 'yes'` the zoom buttonsd don't work properly, but you can make a selection of channels and click in the selection, which causes them to be averaged and displayed in a single plot. In the single plot, you can again make a selection of time, which is subsequently averaged (for all channels) and shown as the interpolated topographic distribution of the potential.
+When you specify `cfg.interactive = 'no'` you can use the MATLAB zoom buttons. With `cfg.interactive = 'yes'` the zoom buttons don't work properly, but you can make a selection of channels and click in the selection, which causes them to be averaged and displayed in a single plot. In the single plot, you can again make a selection of time, which is subsequently averaged (for all channels) and shown as the interpolated topographic distribution of the potential.
 
 FIXME insert figure (singleplot)
 
@@ -454,7 +454,7 @@ The results of the time-frequency analysis can be plotted with **[ft_multiplotTF
 FIXME insert figure (10 ft_multiplotTFR)
 FIXME insert figure (11 ft_topoplotTFR)
 
-Again with `cfg.interactive = 'yes'`, which is the default, you can select one or multiple channels, click on them and get an average TFR over those channels,. In that average you can make a time and frequency selection, click in it, and get a spatial topopgraphy of the relative power over all channels in that fime-frequency range.
+Again with `cfg.interactive = 'yes'`, which is the default, you can select one or multiple channels, click on them and get an average TFR over those channels,. In that average you can make a time and frequency selection, click in it, and get a spatial topopgraphy of the relative power over all channels in that time-frequency range.
 
 If you did not construct a layout, you can visualize the TFRs sequentially over all channels. An advantage of this is that in contrast to the previous figure, channel VMP is now also plotted. There is no location for that channel in the layout contained in the `mouse_layout.mat` file.