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