Pages tagged with "meg"
- Analysis of corticomuscular coherence
- Automatic artifact rejection
- Beamforming evoked fields and potentials in combined MEG/EEG data
- Beamforming oscillatory responses in combined MEG/EEG data
- Beamforming oscillatory responses in MEG data
- Can I create an artificial CTF dataset using MATLAB?
- Can I do combined EEG and MEG source reconstruction?
- Classification of event-related MEG data using MVPA-Light
- Cleaning artifacts using ICA
- Cluster-based permutation tests on event-related fields
- Cluster-based permutation tests on time-frequency data
- Combined EEG and MEG source reconstruction
- Common filters in beamforming
- Compute forward simulated data and apply a beamformer scan
- Computing and reporting the effect size
- Converting an example MEG dataset for sharing in BIDS
- Create MNI-aligned grids in individual head-space
- Creating a BEM volume conduction model of the head for source reconstruction of EEG data
- Creating a FEM volume conduction model of the head for source reconstruction of EEG data
- Creating a sourcemodel for source reconstruction of MEG or EEG data
- Creating a volume conduction model of the head for source reconstruction of MEG data
- Creation of headmodels and sourcemodels for source reconstruction
- Creation of headmodels and sourcemodels for source reconstruction
- Description of the auditory oddball MEG+EEG dataset
- Details of the MEG language dataset
- Dipole fitting of combined MEG/EEG data
- Event-related averaging and MEG planar gradient
- Extended analysis of sensor- and source-level connectivity
- FieldTrip beamformer demo
- FieldTrip connectivity demo
- FieldTrip course at the NatMEG in Stockholm
- FieldTrip stats demo
- FieldTrip Walkthrough
- FieldTrip workshop in Aarhus
- Fit a dipole to the tactile ERF after mechanical stimulation
- Fixing a missing channel
- Fourier analysis of neuronal oscillations and synchronization
- From raw data to ERP
- General instructions for MATLAB demo's
- Getting started with BabySQUID data
- Getting started with BTi/4D data
- Getting started with CTF data
- Getting started with FieldLine OPM data
- Getting started with LIMO MEEG
- Getting started with MNE(-python)
- Getting started with Neuromag/Elekta/Megin data
- Getting started with OPM data recorded at the FIL
- Getting started with reading raw EEG or MEG data
- Getting started with real-time head localization in MEG
- Getting started with Ricoh data
- Getting started with Yokogawa data
- Group analysis
- Group-level statistics with parametric and non-parametric methods
- How are electrodes, magnetometers or gradiometers described?
- How can I convert an anatomical MRI from DICOM into CTF format?
- How can I merge two datasets that were acquired simultaneously with different amplifiers?
- How can I monitor a subject's head position during a MEG session?
- How is the segmentation defined?
- How to coregister an anatomical MRI with the gradiometer or electrode positions?
- How to incorporate head movements in MEG analysis
- Importing your data
- 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
- Introduction on dealing with artifacts
- Introduction to the FieldTrip toolbox
- Localizing oscillatory sources using beamformer techniques
- Localizing visual gamma and cortico-muscular coherence using DICS
- Make leadfields using different headmodels
- MEG dataformats
- MEG-UK 2015 meeting
- Multimodal faces dataset
- Parametric and non-parametric statistics on event-related fields
- Preprocessing - Reading continuous EEG and MEG data
- Preprocessing - Segmenting and reading trial-based EEG and MEG data
- Preprocessing and event-related activity in combined MEG/EEG data
- Preprocessing raw data and computing ERPs/ERFs
- Reading in data and performing sensor-level ERF and TFR analyses
- Reconstructing source activity using beamformers
- Reconstructing source activity using beamformers
- References to implemented methods
- Sensor-level ERF, TFR and connectivity analyses
- Source reconstruction of event-related fields using minimum-norm estimation
- Source statistics
- Specifying the channel layout for plotting
- Speeding up your analysis using distributed computing with parfor
- Speeding up your analysis using distributed computing with qsub
- SPM DCM demo
- SPM Sensor-level stats demo
- SPM Source reconstruction demo
- Statistical analysis and multiple comparison correction for combined MEG/EEG data
- Time-frequency analysis of combined MEG/EEG data
- Time-frequency analysis using Hanning window, multitapers and wavelets
- Time-frequency analysis using Hanning window, multitapers and wavelets
- Time-frequency analysis using Hanning window, multitapers and wavelets
- Time-frequency analysis using Hanning window, multitapers and wavelets
- Use denoising source separation (DSS) to remove ECG artifacts
- Virtual channel analysis of epilepsy MEG data
- Visual artifact rejection
- What does the coilaccuracy parameter do?
- Which datasets are used in the documentation and where are they used?