Restructuring courses page

Author: oliviakowalczyk

docs/courses/eeg_meg/index.md

@@ -0,0 +1,3 @@
+# SPM Course - EEG & MEG
+
+

docs/courses/fmri_vbm/index.md

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+# SPM Course - fMRI & VBM
+
+!!! info inline end "Course recordings"
+    Recordings of course lectures are available [here](./recordings/).
+    
+This three-day course introduces the analysis of neuroimaging data, including Magnetic Resonance Imaging (MRI) and functional MRI (fMRI). It covers:
+
+- Experimental design
+- Pre-processing brain images
+- Quantifying structural changes in the brain (Voxel-Based Morphometry, VBM)
+- Quantifying brain function (using the General Linear Model, GLM)
+- Statistics for neuroimaging (frequentist and Bayesian)
+- Connectivity analysis (Dynamic Causal Modelling, DCM)
+
+The course is divided into theoretical and practical sessions, in which the SPM software package is used to analyse exemplar data sets. The SPM course is taught by an international faculty of neuroimaging experts from the Functional Imaging Laboratory (FIL) and collaborators. 
+
+The course is suitable for beginners and more advanced users.
+
+Please [contact us](mailto:[email protected]) if you have any questions.

docs/courses/fmri_vbm/bayesian_inference.md renamed to docs/courses/fmri_vbm/recordings/bayesian_inference.md

@@ -1,5 +1,8 @@
 # SPM Course
 
+!!! info inline end "Course recordings"
+    Recordings of course lectures from the fMRI & VBM course are available [here](./recordings/).
+
 The FIL SPM course on using Statistical Parametric Mapping for neuroimaging is held each May and October as part of the [Institute of Neurology's short course programme](https://www.ucl.ac.uk/ion/education).
 
-Since 2010, we provide two separate SPM courses reflecting the different imaging modalities. There is a three-day course on SPM for EEG/MEG followed by the long-established three-day course on SPM for fMRI/VBM. Both courses are suitable for beginners and more advanced users. We advise students to gain at least some minimal familiarity with the methodology, for example, from reading introductory articles available from the SPM webpage or by following data analysis examples in the [SPM tutorials](../tutorials/index.md).
+Since 2010, we provide two separate SPM courses reflecting the different imaging modalities. There is a three-day course on SPM for EEG/MEG followed by the long-established three-day course on [SPM for fMRI/VBM](./fmri_vbm/index.md). Both courses are suitable for beginners and more advanced users. We advise students to gain at least some minimal familiarity with the methodology, for example, from reading introductory articles available from the SPM webpage or by following data analysis examples in the [SPM tutorials](../tutorials/index.md).

docs/courses/fmri_vbm/contrasts_classical_inference.md renamed to docs/courses/fmri_vbm/recordings/contrasts_classical_inference.md

@@ -67,18 +67,19 @@ nav:
     - 'Octave':       'installation/octave.md'
   - 'Courses':
     - 'courses/index.md'
-    - 'fMRI/VBM':
-      - 'Spatial preprocessing':            'courses/fmri_vbm/preprocessing.md'
-      - 'General linear model':             'courses/fmri_vbm/glm.md'
-      - 'Contrasts & classical inference':  'courses/fmri_vbm/contrasts_classical_inference.md'
-      - 'Group analysis':                   'courses/fmri_vbm/group_analysis.md'
-      - 'Random field theory':              'courses/fmri_vbm/random_field_theory.md'
-      - 'Voxel-based morphometry':          'courses/fmri_vbm/vbm.md'
-      - 'Experimental design':              'courses/fmri_vbm/experimental_design.md'
-      - 'Event-related fMRI':               'courses/fmri_vbm/event_related_fmri.md'
-      - 'Bayesian inference':               'courses/fmri_vbm/bayesian_inference.md'
-      - 'Introduction to DCM':              'courses/fmri_vbm/dcm_introduction.md'
-      - 'DCM: Testing hypotheses':          'courses/fmri_vbm/dcm_hypothesis_testing.md'
+    - 'fMRI/VBM': 
+      - 'courses/fmri_vbm/index.md'
+      - 'Spatial preprocessing':            'courses/fmri_vbm/recordings/preprocessing.md'
+      - 'General linear model':             'courses/fmri_vbm/recordings/glm.md'
+      - 'Contrasts & classical inference':  'courses/fmri_vbm/recordings/contrasts_classical_inference.md'
+      - 'Group analysis':                   'courses/fmri_vbm/recordings/group_analysis.md'
+      - 'Random field theory':              'courses/fmri_vbm/recordings/random_field_theory.md'
+      - 'Voxel-based morphometry':          'courses/fmri_vbm/recordings/vbm.md'
+      - 'Experimental design':              'courses/fmri_vbm/recordings/experimental_design.md'
+      - 'Event-related fMRI':               'courses/fmri_vbm/recordings/event_related_fmri.md'
+      - 'Bayesian inference':               'courses/fmri_vbm/recordings/bayesian_inference.md'
+      - 'Introduction to DCM':              'courses/fmri_vbm/recordings/dcm_introduction.md'
+      - 'DCM: Testing hypotheses':          'courses/fmri_vbm/recordings/dcm_hypothesis_testing.md'
   - 'Tutorials':
     - 'tutorials/index.md'
     - 'fMRI':