updated tags

_data/tag/artifact.yml

@@ -1,3 +1,6 @@
+- name:  Use denoising source separation (DSS) to remove ECG artifacts
+  link:  /example/dss_ecg
+
 - name:  How to incorporate head movements in MEG analysis
   link:  /example/headmovement_meg
 
@@ -10,9 +13,6 @@
 - name:  Combine MEG with Eyelink eyetracker data
   link:  /example/meg_eyelink
 
-- name:  Use denoising source separation (DSS) to remove ECG artifacts
-  link:  /example/use_denoising_source_separation_dss_to_remove_ecg_artifacts
-
 - name:  How can I interpret the different types of padding in FieldTrip?
   link:  /faq/artifact_padding
 

_data/tag/cluster.yml

@@ -1,6 +1,3 @@
-- name:  Apply non-parametric statistics with clustering on TFRs of power that were computed with BESA
-  link:  /example/apply_clusterrandanalysis_on_tfrs_of_power_that_were_computed_with_besa
-
 - name:  Computing and reporting the effect size
   link:  /example/effectsize
 
@@ -11,7 +8,10 @@
   link:  /example/samplesize
 
 - name:  Use simulated ERPs to explore cluster statistics
-  link:  /example/use_simulated_erps_to_explore_cluster_statistics
+  link:  /example/simulateddata_clusterstats
+
+- name:  Apply non-parametric statistics with clustering on TFRs of power that were computed with BESA
+  link:  /example/stats_besa
 
 - name:  Why should I use the cfg.correcttail option when using statistics_montecarlo?
   link:  /faq/clusterstats_correcttail

_data/tag/coherence.yml

@@ -2,7 +2,7 @@
   link:  /example/coherence_snr
 
 - name:  Correlation analysis of fMRI data
-  link:  /example/correlation_analysis_in_fmri_data
+  link:  /example/fmri_correlationanalysis
 
 - name:  What is the difference between coherence and coherency?
   link:  /faq/coherence_coherency
@@ -17,7 +17,7 @@
   link:  /faq/phaseslopeindex
 
 - name:  References to implemented methods
-  link:  /references_to_implemented_methods
+  link:  /references_methods
 
 - name:  Localizing visual gamma and cortico-muscular coherence using DICS
   link:  /tutorial/beamformingextended

_data/tag/connectivity.yml

@@ -2,7 +2,7 @@
   link:  /development/module/connectivity
 
 - name:  Conditional Granger causality in the frequency domain
-  link:  /example/connectivity_conditional_granger
+  link:  /example/granger_conditional
 
 - name:  In what way can frequency domain data be represented in FieldTrip?
   link:  /faq/datatype_freq

_data/tag/ct.yml

@@ -1,3 +1,6 @@
+- name:  Use denoising source separation (DSS) to remove ECG artifacts
+  link:  /example/dss_ecg
+
 - name:  How to incorporate head movements in MEG analysis
   link:  /example/headmovement_meg
 
@@ -10,9 +13,6 @@
 - name:  Combine MEG with Eyelink eyetracker data
   link:  /example/meg_eyelink
 
-- name:  Use denoising source separation (DSS) to remove ECG artifacts
-  link:  /example/use_denoising_source_separation_dss_to_remove_ecg_artifacts
-
 - name:  How can I interpret the different types of padding in FieldTrip?
   link:  /faq/artifact_padding
 

_data/tag/ctf.yml

@@ -14,7 +14,7 @@
   link:  /example/megrealign
 
 - name:  Can I create an artificial CTF dataset using MATLAB?
-  link:  /example/writing_simulated_data_to_a_ctf_dataset
+  link:  /example/simulateddata_ctf
 
 - name:  How can I convert an anatomical MRI from DICOM into CTF format?
   link:  /faq/anat_dicom2ctf

_data/tag/dataformat.yml

@@ -8,7 +8,7 @@
   link:  /example/biosemi
 
 - name:  Can I create an artificial CTF dataset using MATLAB?
-  link:  /example/writing_simulated_data_to_a_ctf_dataset
+  link:  /example/simulateddata_ctf
 
 - name:  How can I convert an anatomical MRI from DICOM into CTF format?
   link:  /faq/anat_dicom2ctf

_data/tag/dipole.yml

@@ -1,18 +1,18 @@
-- name:  Compute forward simulated data using ft_dipolesimulation
-  link:  /example/compute_forward_simulated_data
-
-- name:  Compute forward simulated data and apply a beamformer scan
-  link:  /example/compute_forward_simulated_data_and_apply_a_beamformer_scan
-
-- name:  Compute forward simulated data and apply a dipole fit
-  link:  /example/compute_forward_simulated_data_and_apply_a_dipole_fit
-
 - name:  Compute forward simulated data with the low-level ft_compute_leadfield
   link:  /example/compute_leadfield
 
 - name:  Fit a dipole to the tactile ERF after mechanical stimulation
   link:  /example/dipolefit_somatosensory_erf
 
+- name:  Compute forward simulated data using ft_dipolesimulation
+  link:  /example/simulateddata
+
+- name:  Compute forward simulated data and apply a beamformer scan
+  link:  /example/simulateddata_beamformer
+
+- name:  Compute forward simulated data and apply a dipole fit
+  link:  /example/simulateddata_dipolefit
+
 - name:  Dipole fitting of combined MEG/EEG data
   link:  /workshop/natmeg2014/dipolefitting
 

_data/tag/eeg.yml

@@ -1,17 +1,14 @@
 - name:  Streaming realtime data from Modular EEG (aka OpenEEG)
   link:  /development/realtime/modulareeg
 
-- name:  Example analysis pipeline for Biosemi data
-  link:  /example/biosemi
-
-- name:  Combined EEG and MEG source reconstruction
-  link:  /example/combined_eeg_and_meg_source_reconstruction
+- name:  Use your own forward leadfield model in an inverse beamformer computation
+  link:  /example/beamformer_ownforward
 
-- name:  Compute forward simulated data using ft_dipolesimulation
-  link:  /example/compute_forward_simulated_data
+- name:  Testing BEM created EEG lead fields
+  link:  /example/bem_evaluation
 
-- name:  Compute forward simulated data and apply a dipole fit
-  link:  /example/compute_forward_simulated_data_and_apply_a_dipole_fit
+- name:  Example analysis pipeline for Biosemi data
+  link:  /example/biosemi
 
 - name:  Compute forward simulated data with the low-level ft_compute_leadfield
   link:  /example/compute_leadfield
@@ -25,23 +22,26 @@
 - name:  Compute EEG leadfields using a FEM headmodel
   link:  /example/fem
 
-- name:  Getting started with reading raw EEG or MEG data
-  link:  /example/getting_started_with_reading_raw_eeg_or_meg_data
-
 - name:  Using General Linear Modeling on time series data
   link:  /example/glm_timeseries
 
 - name:  Using General Linear Modeling over trials
   link:  /example/glm_trials
 
+- name:  Getting started with reading raw EEG or MEG data
+  link:  /example/raw_meeg
+
 - name:  Re-reference EEG and iEEG data
   link:  /example/rereference
 
-- name:  Testing BEM created EEG lead fields
-  link:  /example/testing_bem_created_leadfields
+- name:  Compute forward simulated data using ft_dipolesimulation
+  link:  /example/simulateddata
 
-- name:  Use your own forward leadfield model in an inverse beamformer computation
-  link:  /example/use_your_own_forward_leadfield_model_in_an_inverse_beamformer_computation
+- name:  Compute forward simulated data and apply a dipole fit
+  link:  /example/simulateddata_dipolefit
+
+- name:  Combined EEG and MEG source reconstruction
+  link:  /example/sourcerecon_meeg
 
 - name:  Making a synchronous movie of EEG or NIRS combined with video recordings
   link:  /example/video_eeg
@@ -128,7 +128,7 @@
   link:  /reading_data
 
 - name:  References to implemented methods
-  link:  /references_to_implemented_methods
+  link:  /references_methods
 
 - name:  Template 2-D layouts for plotting
   link:  /template/layout

_data/tag/emg.yml

@@ -2,7 +2,7 @@
   link:  /example/bids_emg
 
 - name:  Detect the muscle activity in an EMG channel and use that as trial definition
-  link:  /example/detect_the_muscle_activity_in_an_emg_channel_and_use_that_as_trial_definition
+  link:  /example/trialdef_emg
 
 - name:  Analysis of corticomuscular coherence
   link:  /tutorial/coherence

_data/tag/filter.yml

@@ -1,5 +1,5 @@
 - name:  Determine the filter characteristics
-  link:  /example/determine_the_filter_characteristics
+  link:  /example/filter_characteristics
 
 - name:  How can I interpret the different types of padding in FieldTrip?
   link:  /faq/artifact_padding

_data/tag/fixme.yml

@@ -2,7 +2,7 @@
   link:  /development/guideline/code
 
 - name:  Common filters in beamforming
-  link:  /example/common_filters_in_beamforming
+  link:  /example/beamformer_commonfilter
 
 - name:  Fit a dipole to the tactile ERF after mechanical stimulation
   link:  /example/dipolefit_somatosensory_erf

_data/tag/fmri.yml

@@ -2,7 +2,7 @@
   link:  /development/realtime/fmri
 
 - name:  Correlation analysis of fMRI data
-  link:  /example/correlation_analysis_in_fmri_data
+  link:  /example/fmri_correlationanalysis
 
 - name:  Getting started with fMRI timeseries data
   link:  /getting_started/fmri

_data/tag/freq.yml

@@ -1,30 +1,30 @@
-- name:  Apply non-parametric statistics with clustering on TFRs of power that were computed with BESA
-  link:  /example/apply_clusterrandanalysis_on_tfrs_of_power_that_were_computed_with_besa
+- name:  Common filters in beamforming
+  link:  /example/beamformer_commonfilter
 
 - name:  Effect of SNR on Coherence
   link:  /example/coherence_snr
 
-- name:  Common filters in beamforming
-  link:  /example/common_filters_in_beamforming
-
-- name:  Conditional Granger causality in the frequency domain
-  link:  /example/connectivity_conditional_granger
-
-- name:  Correlation analysis of fMRI data
-  link:  /example/correlation_analysis_in_fmri_data
-
 - name:  Cross-frequency analysis
   link:  /example/crossfreq
 
 - name:  Effects of tapering for power estimates
   link:  /example/effects_of_tapering
 
+- name:  Correlation analysis of fMRI data
+  link:  /example/fmri_correlationanalysis
+
+- name:  Conditional Granger causality in the frequency domain
+  link:  /example/granger_conditional
+
 - name:  Simulate an oscillatory signal with phase resetting
   link:  /example/phase_reset
 
 - name:  Analyze Steady-State Visual Evoked Potentials (SSVEPs)
   link:  /example/ssvep
 
+- name:  Apply non-parametric statistics with clustering on TFRs of power that were computed with BESA
+  link:  /example/stats_besa
+
 - name:  How can I test whether a behavioral measure is phasic?
   link:  /faq/behavior_cosinefit
 
@@ -89,7 +89,7 @@
   link:  /reference
 
 - name:  References to implemented methods
-  link:  /references_to_implemented_methods
+  link:  /references_methods
 
 - name:  Localizing oscillatory sources using beamformer techniques
   link:  /tutorial/beamformer

_data/tag/granger.yml

@@ -1,5 +1,5 @@
 - name:  Conditional Granger causality in the frequency domain
-  link:  /example/connectivity_conditional_granger
+  link:  /example/granger_conditional
 
 - name:  Analysis of sensor- and source-level connectivity
   link:  /tutorial/connectivity

_data/tag/headmodel.yml

@@ -1,8 +1,5 @@
-- name:  Combined EEG and MEG source reconstruction
-  link:  /example/combined_eeg_and_meg_source_reconstruction
-
-- name:  Compute forward simulated data using ft_dipolesimulation
-  link:  /example/compute_forward_simulated_data
+- name:  Testing BEM created EEG lead fields
+  link:  /example/bem_evaluation
 
 - name:  Compute forward simulated data with the low-level ft_compute_leadfield
   link:  /example/compute_leadfield
@@ -14,17 +11,20 @@
   link:  /example/fem
 
 - name:  Make MEG leadfields using different headmodels
-  link:  /example/make_leadfields_using_different_headmodels
+  link:  /example/headmodel_various
+
+- name:  Compute forward simulated data using ft_dipolesimulation
+  link:  /example/simulateddata
 
 - name:  Create MNI-aligned grids in individual head-space
   link:  /example/sourcemodel_aligned2mni
 
+- name:  Combined EEG and MEG source reconstruction
+  link:  /example/sourcerecon_meeg
+
 - name:  Fitting a template MRI to the MEG Polhemus head shape
   link:  /example/sphere_fitting
 
-- name:  Testing BEM created EEG lead fields
-  link:  /example/testing_bem_created_leadfields
-
 - name:  How to coregister an anatomical MRI with the gradiometer or electrode positions?
   link:  /faq/anat_coreg
 
@@ -83,7 +83,7 @@
   link:  /reference
 
 - name:  References to implemented methods
-  link:  /references_to_implemented_methods
+  link:  /references_methods
 
 - name:  Template head models for EEG volume conduction modeling
   link:  /template/headmodel

_data/tag/ica.yml

@@ -1,12 +1,12 @@
+- name:  Use denoising source separation (DSS) to remove ECG artifacts
+  link:  /example/dss_ecg
+
 - name:  Independent component analysis (ICA) to remove ECG artifacts
   link:  /example/ica_ecg
 
 - name:  Independent component analysis (ICA) to remove EOG artifacts
   link:  /example/ica_eog
 
-- name:  Use denoising source separation (DSS) to remove ECG artifacts
-  link:  /example/use_denoising_source_separation_dss_to_remove_ecg_artifacts
-
 - name:  The databrowser crashes and destroys the whole MATLAB session, how can I resolve this?
   link:  /faq/databrowser_crash
 

_data/tag/literature.yml

@@ -5,8 +5,8 @@
   link:  /citations
 
 - name:  References to implemented methods
-  link:  /references_to_implemented_methods
+  link:  /references_methods
 
 - name:  References to review papers and teaching material
-  link:  /references_to_review_papers_and_teaching_material
+  link:  /references_papers
 

_data/tag/meg-removal.yml

@@ -1,9 +1,9 @@
+- name:  Use denoising source separation (DSS) to remove ECG artifacts
+  link:  /example/dss_ecg
+
 - name:  Independent component analysis (ICA) to remove ECG artifacts
   link:  /example/ica_ecg
 
-- name:  Use denoising source separation (DSS) to remove ECG artifacts
-  link:  /example/use_denoising_source_separation_dss_to_remove_ecg_artifacts
-
 - name:  Which datasets are used in the documentation and where are they used?
   link:  /faq/datasets