# Pages in the category "example"

- Align EEG electrode positions to BEM headmodel
- Analysis of high-gamma band signals in human ECoG
- Analyze Steady-State Visual Evoked Potentials (SSVEPs)
- Analyzing NIRS data recorded during listening to and repeating speech
- Analyzing NIRS data recorded during unilateral finger- and foot-tapping
- Apply non-parametric statistics with clustering on TFRs of power that were computed with BESA
- BIDS - the brain imaging data structure
- Can I create an artificial CTF dataset using MATLAB?
- Check the quality of the anatomical coregistration
- Combine MEG with Eyelink eyetracker data
- Combined EEG and MEG source reconstruction
- Combining simultaneous recordings in BIDS
- Common filters in beamforming
- Compute EEG leadfields using a FEM headmodel
- Compute forward simulated data and apply a beamformer scan
- Compute forward simulated data and apply a dipole fit
- Compute forward simulated data using ft_dipolesimulation
- Compute forward simulated data with the low-level ft_compute_leadfield
- Computing and reporting the effect size
- Conditional Granger causality in the frequency domain
- Converting an example audio dataset for sharing in BIDS
- Converting an example behavioral dataset for sharing in BIDS
- Converting an example EEG dataset for sharing in BIDS
- Converting an example EMG dataset for sharing in BIDS
- Converting an example eyetracker dataset for sharing in BIDS
- Converting an example MEG dataset for sharing in BIDS
- Converting an example motion tracking dataset for sharing in BIDS
- Converting an example NIRS dataset for sharing in BIDS
- Converting an example video dataset for sharing in BIDS
- Converting the combined MEG/fMRI MOUS dataset for sharing in BIDS
- Correlation analysis of fMRI data
- Create MNI-aligned grids in individual head-space
- Creating a layout for plotting NIRS optodes and channels
- Cross-frequency analysis
- Defining electrodes as neighbours for cluster-level statistics
- Detect the muscle activity in an EMG channel and use that as trial definition
- Determine the filter characteristics
- Effect of SNR on Coherence
- Effects of tapering for power estimates
- Example analysis pipeline for Biosemi data
- Example MATLAB scripts
- Example real-time average
- Example real-time classification
- Example real-time power estimate
- Example real-time selective average
- Example real-time signal viewer
- Find the orientation of planar gradiometers
- Fit a dipole to the tactile ERF after mechanical stimulation
- Fitting a template MRI to the MEG Polhemus head shape
- Fitting oscillations and one-over-F (FOOOF)
- Fixing a missing channel
- Getting started with reading raw EEG or MEG data
- How to create a head model if you do not have an individual MRI
- How to import data from MNE-Python and FreeSurfer
- How to incorporate head movements in MEG analysis
- How to use ft_checkconfig
- Independent component analysis (ICA) to remove ECG artifacts
- Independent component analysis (ICA) to remove EOG artifacts
- Interpolating data from the CTF151 to the CTF275 sensor array using megrealign
- Irregular Resampling Auto-Spectral Analysis (IRASA)
- Localizing the sources underlying the difference in event-related fields
- Make MEG leadfields using different headmodels
- Making a synchronous movie of EEG or NIRS combined with video recordings
- Making your analysis pipeline reproducible using reproducescript
- Making your own trialfun for conditional trial definition
- Measuring the timing delay and jitter for a real-time application
- Perform modified Multiscale Entropy (mMSE) analysis on EEG/MEG/LFP data
- Plotting the result of source reconstruction on a cortical mesh
- Re-reference EEG and iEEG data
- Realtime neurofeedback application based on Hilbert phase estimation
- Simulate an oscillatory signal with phase resetting
- Source statistics
- Stratify the distribution of one variable that differs in two conditions
- Symmetric dipole pairs for beamforming
- Testing BEM created EEG lead fields
- The correct pipeline order for combining planar MEG channels
- Use denoising source separation (DSS) to remove ECG artifacts
- Use simulated ERPs to explore cluster statistics
- Use your own forward leadfield model in an inverse beamformer computation
- Using General Linear Modeling on time series data
- Using General Linear Modeling over trials
- Using GLM to analyze NIRS timeseries data
- Using reproducescript for a group analysis
- Using reproducescript on a full study
- Using simulations to estimate the sample size for cluster-based permutation test
- Using threshold-free cluster enhancement for cluster statistics