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- About the FieldTrip project
 - Citations to the FieldTrip reference paper
 - Copyrights
 - Dataformats
 - Development
 - Accessing the FieldTrip source code through CVS
 - Accessing the FieldTrip source code through Git
 - Accessing the FieldTrip source code through SVN
 - Contribute
 - Data structures
 - Deprecated functions and options
 - Distributed computing
 - Forward and inverse computation of EEG/MEG data
 - Guidelines
 - Code guidelines
 - Communication guidelines
 - Documentation guidelines
 - Template guidelines
 - Website syntax and formatting
 - Integration between tools
 - Meetings
 - FieldTrip meeting - 20120822
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 - FieldTrip meeting - 20121024
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 - FieldTrip meeting - 20151130
 - FieldTrip meeting - 20151207
 - FieldTrip meeting - 20151214
 - FieldTrip meeting - 20160104
 - Modules
 - Connectivity estimates for EEG/MEG time series data
 - Distributed computing using a Linux compute cluster
 - Forward computation of EEG/MEG source models
 - Inverse source parameter estimates from EEG/MEG data
 - Plotting of channel-level, source-level and other geometrical data related to EEG/MEG
 - Preprocessing of EEG/MEG time series data
 - Reading and writing of EEG/MEG time series data
 - Spectral estimation of of EEG/MEG time series data
 - Project overview
 - A tutorial on forward modeling
 - Add stripped spm2 and other toolboxes as external dependencies
 - Add support for reading data from any file format supported by neuroshare
 - Add the spike functions from Martin
 - An alternative algorithm for constructing triangulated EEG-BEM head models
 - CSP for classification
 - Check the consistency between the documentation and the implementations
 - Check the correctness of the implementation of the algorithms
 - Clean up inside_vol and similar functions
 - Clean up the buffer implementation
 - Clean up the code of sourceanalysis, sourcedescriptives, freqdescriptives using checkdata
 - Clean up the documentation on head modeling, anatomical processing, etc.
 - Cleanup the functions in the private folders
 - Code coverage
 - Consistent flank detection for triggers
 - Create a forward solver for charges in an infinite halfspace
 - Create a headmodel for source reconstruction of MEG data
 - Create a tutorial on the processing of animal data
 - Create a volume conduction model of the head for source reconstruction of EEG data
 - Dealing with TMS-EEG datasets
 - Dealing with the geometry of the forward model
 - Developing the documentation of the source reconstruction methods
 - Document grad.tra, modifications to it, and effects on inverse
 - Ensemble methods
 - Ensure consistency of the documentation
 - Ensure consistent trial definition
 - Ensure consistent units throughout fieldtrip
 - Ensure that all website pages exist
 - Ensure that the compat directories are NOT called by FieldTrip itself
 - Explain how to create cfg.design for ft_xxxstatistics
 - FieldTrip from a software development perspective
 - FieldTrip/SIMBIO integration materials
 - FieldTrip/SIMBIO integration plan
 - FieldTrip/SIMBIO integration scenarios
 - Handling of continuous data
 - How to create a volumetric current density
 - How to deal with the forward model units?
 - Implement a common distributed computing backend
 - Implement a consistent way to spatially transform a grid or source model
 - Implement a function which computes a variety of bivariate coupling measures from the input data
 - Implement a function which computes an mvar-model based on the input data
 - Implement a graphical user interface as a "wizard" for certain analysis protocols
 - Implement function that checks consistency of cfgs
 - Implement online data processing and classification for BCI
 - Implement support for CTF synthetic gradiometers
 - Implement support for a separation of data into a signal and noise subspace
 - Implement trial selection option
 - Implementation of realistic electrode properties in forward volume conduction models
 - Import and export data to and from MNE-Python
 - Improve artifact handling
 - Improve integration with other toolboxes
 - Improve parallel computing under the hood
 - Improve regression testing
 - Infrastructure for testing
 - Integration with NUTMEG
 - Integration with SPM12
 - Integration with SPM8
 - Modularise ft_connectivityanalysis
 - Move internal fcdc documentation onto the website
 - NIRS development
 - Neighbour templates
 - Prefix all public functions with ft
 - Provide an interface to the FNS software for FDM modelling
 - Provide an interface to the OpenMEEG software for BEM modelling
 - Redesign and implement a common statistical backend for various data types
 - Redesign the interface to the read_fcdc_xxx functions
 - Refurbishing the FORWARD module
 - Reimplement the avg/cov/trial handling
 - Replicate functionality of MNE software
 - Restructure and rework all visualization functions
 - Restructure the directory layout
 - Switch from SPM2 to SPM8
 - Switch to using the preproc functions and phase out the old preprocessing code
 - Testing code quality
 - Testing minimum-norm estimate in FieldTrip and in MNE Suite
 - The rat beamformer
 - Visualization concept for 4D bivariate data
 - What is the best way to homogenize data using z-scores?
 - Write a tutorial on how to work with the MEGSIM data
 - source reconstruction using two dipoles
 - Real-time data processing
 - Closing the loop in a real-time BCI application
 - FieldTrip buffer C implementation
 - FieldTrip buffer C++ implementation
 - FieldTrip buffer Java interface
 - FieldTrip buffer MATLAB interface
 - FieldTrip buffer Python interface
 - FieldTrip buffer reference implementation
 - Low-level FieldTrip buffer TCP network protocol
 - Overview of the realtime buffer
 - Pipeline architecture
 - Realtime visualization of data from the FieldTrip buffer
 - Scratchpad for the realtime buffer interface
 - Specific software implementations for realtime EEG/MEG/fMRI/NIRS
 - Streaming realtime EEG data to and from Arduino
 - Streaming realtime data from ANT NeuroSDK
 - Streaming realtime data from Artinis Medical Systems
 - Streaming realtime data from BioSemi ActiveTwo EEG amplifier
 - Streaming realtime data from BrainVision Recorder Remote Data Access (RDA)
 - Streaming realtime data from CTF
 - Streaming realtime data from Emotiv neuroheadset
 - Streaming realtime data from Jinga-Hi
 - Streaming realtime data from Micromed
 - Streaming realtime data from Modular EEG (aka OpenEEG)
 - Streaming realtime data from Neuralynx
 - Streaming realtime data from Neuromag/Elekta/Megin
 - Streaming realtime data from Neurosky ThinkCap
 - Streaming realtime data from OpenBCI
 - Streaming realtime data from TMSI EEG amplifiers
 - Streaming realtime data from TOBI (Tools for Brain-Computer Interaction)
 - Streaming realtime data from Unicorn Hybrid Black
 - Streaming realtime data from and to BCI2000
 - Streaming realtime data from and to BrainStream
 - Streaming realtime data from soundcard using PortAudio
 - Suggested changes to the network protocol
 - Suggested changes to the reference implementation
 - Suggested improvements for compatibility across versions
 - Suggested improvements for handling header and chunks
 - Testing with sine waves and pre-recorded EEG data
 - Translating characters received on a serial port to FieldTrip events
 - Release and quality control
 - Reporting issues
 - Software architecture
 - Testing
 - Documentation
 - Download the FieldTrip toolbox
 - Email discussion list
 - Examples
 - Examples for plotting and visualization
 - Creating a layout for plotting NIRS optodes and channels
 - Making a synchronous movie of EEG or NIRS combined with video recordings
 - Plotting the result of source reconstruction on a cortical mesh
 - Examples for reading and preprocessing data
 - Combine MEG with Eyelink eyetracker data
 - Detect the muscle activity in an EMG channel and use that as trial definition
 - Determine the filter characteristics
 - Fixing a missing channel
 - Getting started with reading raw EEG or MEG data
 - Independent component analysis (ICA) to remove ECG artifacts
 - Independent component analysis (ICA) to remove EOG artifacts
 - Making your own trialfun for conditional trial definition
 - Rereference EEG and iEEG data
 - Use denoising source separation (DSS) to remove ECG artifacts
 - Examples for real-time analysis
 - Example real-time average
 - Example real-time classification
 - Example real-time power estimate
 - Example real-time selective average
 - Example real-time signal viewer
 - Measuring the timing delay and jitter for a real-time application
 - Realtime neurofeedback application based on Hilbert phase estimation
 - Examples for sensor-level analysis
 - Analyzing NIRS data recorded during listening to and repeating speech
 - Analyzing NIRS data recorded during unilateral finger- and foot-tapping
 - How to incorporate head movements in MEG analysis
 - Interpolating data from the CTF151 to the CTF275 sensor array using megrealign
 - The correct pipeline order for combining planar MEG channels
 - Examples for source reconstruction
 - Align EEG electrode positions to BEM headmodel
 - Can I create an artificial CTF dataset using MATLAB?
 - Check the quality of the anatomical coregistration
 - Combined EEG and MEG source reconstruction
 - Common filters in beamforming
 - Compute EEG leadfields using a BEM headmodel
 - Compute EEG leadfields using a FEM headmodel
 - Compute EEG leadfields using a concentric spheres 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
 - Create MNI-aligned grids in individual head coordinates
 - Create a template source model aligned to MNI space
 - Create atlas-based MNI-aligned grids in individual head coordinates
 - Fit a dipole to the tactile ERF after mechanical stimulation
 - Fitting a template MRI to the MEG Polhemus head shape
 - How to create a head model if you do not have an individual MRI
 - Localizing the sources underlying the difference in event-related fields
 - Make MEG leadfields using different headmodels
 - Read Neuromag .fif mri and create a MNI-aligned single-shell head model
 - Symmetric dipole pairs for beamforming
 - Testing BEM created EEG lead fields
 - Use an MNI-aligned grid with a FEM headmodel in individual head coordinates
 - Use your own forward leadfield model in an inverse beamformer computation
 - Examples for spectral analysis
 - Analysis of high-gamma band signals in human ECoG
 - Analyze steady-state visual evoked potentials (SSVEPs)
 - Conditional Granger causality in the frequency domain
 - Cross-frequency analysis
 - Effect of SNR on Coherence
 - Effects of tapering for power estimates
 - Fitting oscillations and one-over-F (FOOOF)
 - Fourier analysis of neuronal oscillations and synchronization
 - Interpolate the time axis of single-trial TFRs
 - Irregular resampling auto-spectral analysis (IRASA)
 - Simulate an oscillatory signal with phase resetting
 - Examples for statistical analysis
 - Apply non-parametric statistics with clustering on TFRs of power that were computed with BESA
 - Computing and reporting the effect size
 - Defining electrodes as neighbours for cluster-level statistics
 - Source statistics
 - Stratify the distribution of one variable that differs in two conditions
 - Use simulated ERPs to explore cluster statistics
 - Using general linear modeling on time series data
 - Using general linear modeling over trials
 - Using general linear modeling to analyze NIRS timeseries data
 - Using simulations to estimate the sample size for cluster-based permutation test
 - Using threshold-free cluster enhancement for cluster statistics
 - Various other examples
 - BIDS - the brain imaging data structure
 - Combining simultaneous recordings in BIDS
 - Converting an example EEG dataset for sharing in BIDS
 - Converting an example EMG dataset for sharing in BIDS
 - Converting an example MEG dataset for sharing in BIDS
 - Converting an example NIRS dataset for sharing in BIDS
 - Converting an example audio dataset for sharing in BIDS
 - Converting an example behavioral dataset for sharing in BIDS
 - Converting an example eyetracker dataset for sharing in BIDS
 - Converting an example motion tracking 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
 - Example analysis pipeline for BioSemi data
 - Find the orientation of planar gradiometers
 - How to import data from MNE-Python and FreeSurfer
 - How to use ft_checkconfig
 - Making your analysis pipeline reproducible using reproducescript
 - Perform modified multiscale entropy (mMSE) analysis on EEG/MEG/LFP data
 - Using reproducescript for a group analysis
 - Using reproducescript on a full study
 - External links
 - FieldTrip Walkthrough
 - FieldTrip workshops and courses
 - Advanced MEG/EEG toolkit at the Donders
 - Advanced MEG/EEG toolkit at the Donders
 - Advanced MEG/EEG toolkit at the Donders
 - Code of Conduct
 - Lessons learned
 - Preparation for the online toolkit
 - Test your MATLAB and FieldTrip installation in advance
 - Advanced MEG/EEG toolkit at the Donders
 - Advanced MEG/EEG toolkit at the Donders
 - Advanced MEG/EEG toolkit at the Donders
 - Advanced MEG/EEG toolkit at the Donders
 - Advanced MEG/EEG toolkit at the Donders
 - Advanced analysis and source modeling of EEG and MEG data
 - Advanced analysis and source modeling of EEG and MEG data
 - Advanced analysis and source modeling of EEG and MEG data
 - African Brain Data Network EEG workshop in Nigeria
 - Event-related potentials
 - Experimental design and presenting stimuli
 - Frequency analysis of resting state EEG data
 - Preprocessing of EEG data
 - Biomag 2016 satellite meeting - Seoul, Korea
 - Chengdu, China
 - ChildBrain pre-conference workshop in Leuven, Belgium
 - CuttingEEG X workshop at the Donders
 - ECoG/sEEG FieldTrip bootcamp at UC Davis
 - FieldTrip Workshop in Exeter, UK
 - FieldTrip Workshop in Guangzhou, China
 - FieldTrip Workshop in Göttingen in 2019
 - FieldTrip Workshop in London, UK
 - FieldTrip Workshop in Mannheim
 - FieldTrip Workshop in Marseille in January 2016
 - FieldTrip Workshop in Marseille in November 2016
 - FieldTrip Workshop in Tübingen, Germany
 - FieldTrip course at the NatMEG in Stockholm
 - FieldTrip tutorial at CuttingEEG 2021 in Aix-en-Provence
 - Convert the EEG language dataset for sharing in BIDS
 - Time-frequency analysis on short and long timescales
 - FieldTrip tutorial at WIRED 2024 in Paris
 - FieldTrip tutorial at the Donders Cognition Brain and Technology school
 - FieldTrip workshop Donostia
 - FieldTrip workshop at ESI/MPI Frankfurt, Germany
 - FieldTrip workshop at Universidad Católica del Maule, Chile
 - FieldTrip workshop at Washington University, St Louis
 - FieldTrip workshop in Aarhus
 - FieldTrip workshop in Barcelona
 - FieldTrip workshop in Bern, Switzerland
 - Preprocessing of EEG data
 - Solving the EEG forward problem using BEM and FEM
 - Solving the EEG inverse problem
 - FieldTrip workshop in Chieti
 - MEG virtual channels and seed-based connectivity
 - MEG whole-brain connectivity
 - Simulating and estimating, what about model (mis)match?
 - FieldTrip workshop in Coimbra, Portugal
 - FieldTrip workshop in Göttingen in 2014
 - FieldTrip workshop in Hamburg in 2012
 - FieldTrip workshop in Hamburg in 2013
 - FieldTrip workshop in Hamburg in 2023
 - FieldTrip workshop in Kiel, Germany
 - FieldTrip workshop in Krakow, Poland
 - FieldTrip workshop in Madrid
 - Cleaning and processing resting-state EEG
 - Cluster-based permutation tests on resting-state EEG power spectra
 - Convert the EEG sedation dataset for sharing in BIDS
 - Details on the resting-state EEG dataset recorded with different sedation levels
 - Getting started with EEG data, quality checks and ERPs
 - Time-frequency and spectral analysis
 - FieldTrip workshop in Oslo
 - Beamforming oscillatory responses in MEG data
 - Forward modeling for EEG source reconstruction
 - Preprocessing and event-related potentials in EEG data
 - Statistical analysis and multiple comparison correction for EEG data
 - Time-frequency analysis of EEG data
 - FieldTrip workshop in Parma
 - FieldTrip workshop in Salzburg, Austria
 - FieldTrip workshop in Salzburg, Austria
 - FieldTrip workshop in Singapore
 - Preprocessing of EEG and MEG data
 - Solving the EEG and MEG forward problem using the finite element method
 - Solving the EEG inverse problem
 - FieldTrip workshop in Sofia, Bulgaria
 - FieldTrip workshop in Stockholm
 - FieldTrip workshop in Trento, Italy
 - FieldTrip workshop in Zürich
 - Interactive Virtual Workshop organized by the Fetal, Infant, & Toddler Neuroimaging Group
 - Joint FieldTrip/MNE course at the NatMEG in Stockholm
 - M/EEG analysis workshop in Jyväskylä, Finland
 - MEG-UK 2015 meeting
 - FieldTrip beamformer demo
 - FieldTrip connectivity demo
 - FieldTrip stats demo
 - General instructions for MATLAB demo's
 - Multimodal faces dataset
 - SPM DCM demo
 - SPM Sensor-level stats demo
 - SPM Source reconstruction demo
 - MEG/EEG analysis and FieldTrip Workshop in Oxford, UK
 - MRC Partnership Grant FieldTrip workshop in Birmingham
 - Neuroimaging II - Electrophysiological Methods
 - Neuroimaging II - Electrophysiological Methods
 - SED1 - Statistical testing of electrophysiological data
 - SED2 - Statistical testing of electrophysiological data
 - SED3 - Statistical testing of electrophysiological data
 - SED4 - Statistical testing of electrophysiological data
 - SPED1 - Signal processing of electrophysiological data
 - SPED2 - Signal processing of electrophysiological data
 - SPED3 - Signal processing of electrophysiological data
 - SPED4 - Time-frequency analysis in practice using FieldTrip
 - SR1 - Source reconstruction
 - SR2 - Source reconstruction
 - SR3 - Source reconstruction
 - SR4 - Source reconstruction
 - SR5 - Source reconstruction
 - PracticalMEEG workshop at ICM in Paris
 - Creation of headmodels and sourcemodels for source reconstruction
 - From raw data to ERP
 - Group analysis
 - Instructions for the USB stick
 - Multimodal faces dataset
 - Reconstructing source activity using beamformers
 - Time-frequency analysis using Hanning window, multitapers and wavelets
 - PracticalMEEG workshop in Aix-en-Provence
 - Creation of headmodels and sourcemodels for source reconstruction
 - Dealing with artifacts
 - Group-level statistics with parametric and non-parametric methods
 - Multimodal faces dataset
 - Preprocessing raw data and computing ERPs/ERFs
 - Reconstructing source activity using beamformers
 - Time-frequency analysis using Hanning window, multitapers and wavelets
 - Realtime MEG BCI hands-on session in Nijmegen
 - Summerschool on brain networks
 - Toolkit of Cognitive Neuroscience - EEG/MEG
 - Workshop on FieldTrip, nonparametric statistics and connectivity
 - Workshop on analyzing intracranial data - spikes and fields
 - Workshop on the ECoG forward solution using FEMfuns in FieldTrip at the Donders
 - Frequently asked questions
 - Code and development questions
 - How are the various MATLAB data structures defined?
 - How can I debug my analysis script if a FieldTrip function gives an error?
 - How can I keep track of changes to the code?
 - What does a typical call to a FieldTrip function look like?
 - Why was FieldTrip maintained in SVN and not in Git?
 - Distributed computing questions
 - How can I distribute a batch of jobs?
 - How to compile MATLAB code into stand-alone executables?
 - How to get started with distributed computing using qsub?
 - How to get started with the MATLAB distributed computing toolbox?
 - What are the different approaches I can take for distributed computing?
 - Experimental questions
 - How can I change the head localization in a CTF dataset?
 - How can I monitor a subject's head position during a MEG session?
 - How can I use my MacBook Pro for stimulus presentation in the MEG lab?
 - How can I visualize the Neuromag head position indicator coils?
 - What kind of cable do I need for a serial port connection between two computers?
 - MATLAB questions
 - Can I prevent "external" toolboxes from being added to my MATLAB path?
 - Can I use FieldTrip without MATLAB license?
 - Can I use Octave instead of MATLAB?
 - How can I compile the mex files and command-line executable?
 - How can I compile the mex files on 64-bit Windows?
 - How can I compile the mex files on macOS?
 - How many lines of code does FieldTrip consist of?
 - How to select the correct SPM toolbox?
 - Installation and setting up the path
 - MATLAB complains about a missing or invalid mex file, what should I do?
 - MATLAB complains that mexmaci64 cannot be opened because the developer cannot be verified
 - MATLAB does not see the functions in the "private" directory
 - MATLAB version 7.3 (2006b) crashes when I try to do ...
 - Replacements for functions from MathWorks toolboxes
 - The databrowser crashes and destroys the whole MATLAB session, how can I resolve this?
 - What are the MATLAB and external requirements?
 - What are the MATLAB requirements for using FieldTrip?
 - Which external toolboxes are used by FieldTrip?
 - Why are so many of the interesting functions in the private directories?
 - Organizational questions
 - Can I get an offline version of the documentation on the website?
 - Can I use the FieldTrip logo on my poster?
 - How many people are subscribed to the email discussion list?
 - How should I refer to FieldTrip in my publication?
 - How should I share example data with the email list or developers?
 - How to ask good questions to the community?
 - I am having problems downloading
 - I am working at the Donders, should I also download FieldTrip?
 - Which version of FieldTrip should I download?
 - Why am I not allowed to post to the discussion list?
 - Why am I not receiving emails from the discussion list?
 - Why am I receiving warnings about too many bouncing emails?
 - Why is FieldTrip developed separately from EEGLAB?
 - Why is my message rejected from the email discussion list?
 - Plotting and visualization questions
 - How can I play back EEG/MEG and synchronous audio or video?
 - How can I visualize a localspheres volume conductor model?
 - How do I construct a layout file for the plotting functions?
 - I am getting strange artifacts in figures that use opacity
 - I am having problems printing figures that use opacity
 - What are the different Neuromag/Elekta/Megin and Yokogawa layouts good for?
 - What is a good way to save images for later processing in other software?
 - What is the format of the layout file which is used for plotting?
 - What is the plotting convention for anatomical MRIs?
 - Which colormaps are supported?
 - Why does my anatomical MRI show upside-down when plotting it with ft_sourceplot?
 - Questions about reading and preprocessing of data
 - How can I inspect the electrode impedances of my data?
 - How can I use the databrowser?
 - I used to work with trl-matrices that have more than 3 columns. Why is this not supported anymore?
 - Questions about artifacts
 - Do I need to resample my data, and if so, how is this to be done?
 - How can I consistently represent artifacts in my data?
 - How can I interpret the different types of padding in FieldTrip?
 - How does the filter padding in preprocessing work?
 - I used ICA on my MEG data from before 2012 and now FieldTrip crashes, why is that?
 - What kind of filters can I apply to my data?
 - Why does my ICA eyeblink component look strange?
 - Why does my ICA output contain complex numbers?
 - Why is there a residual 50Hz line-noise component after applying a DFT filter?
 - Questions about data handling
 - How can I append the files of two separate recordings?
 - How can I convert one dataformat into an other?
 - How can I merge two datasets that were acquired simultaneously with different amplifiers?
 - How can I preprocess a dataset that is too large to fit into memory?
 - How can I rename channels in my data structure?
 - Reading is slow, can I write my raw data to a more efficient file format?
 - What dataformats are supported?
 - Questions about specific data formats
 - How can I deal with a discontinuous Neuralynx LFP recording?
 - How can I extend the reading functions with a new dataformat?
 - How can I fix a corrupt CTF meg4 file?
 - How can I fix a corrupt CTF res4 header file?
 - How can I import my own data format?
 - How can I read EGI mff data without the JVM?
 - How can I read all channels from an EDF file that contains multiple sampling rates?
 - How can I read corrupted (unsaved) CTF data?
 - How does the CTF higher-order gradiometer work?
 - I am having problems reading the CTF .hc headcoordinates file
 - I have problems reading in NeuroScan .cnt files. How can I fix this?
 - Why are the fileio functions stateless, does the fseek not make them very slow?
 - Questions about trials, triggers and events
 - How can I check or decipher the sequence of triggers in my data?
 - How can I find out what eventvalues and eventtypes there are in my data?
 - How can I process continuous data without triggers?
 - How can I transform trigger values from bits to decimal representation with a trialfun?
 - Is it possible to keep track of trial-specific information in my analysis pipeline?
 - What is the relation between "events" (such as triggers) and "trials"?
 - Should I rereference prior to or after ICA for artifact removal?
 - Why should I set continuous to yes for CTF data?
 - Why should I start with rereferencing for BioSemi EEG data?
 - Real-time analysis questions
 - Does the FieldTrip realtime buffer only work with MATLAB?
 - How fast is the FieldTrip buffer for realtime data streaming?
 - How should I get started with the FieldTrip realtime buffer?
 - Source reconstruction questions
 - Can I do combined EEG and MEG source reconstruction?
 - Can I restrict the source reconstruction to the grey matter?
 - How are electrodes, magnetometers or gradiometers described?
 - How are the Left and Right Pre-Auricular (LPA and RPA) points defined?
 - How are the different head and MRI coordinate systems defined?
 - How can I check whether the grid that I have is aligned to the segmented volume and to the sensor gradiometer?
 - How can I convert an anatomical MRI from DICOM into CTF format?
 - How can I determine the anatomical label of a source or electrode?
 - How can I fine-tune my BEM volume conduction model?
 - How can I map source locations onto an anatomical label in an atlas?
 - How can I visualize the different geometrical objects that are needed for forward and inverse computations?
 - How do I install the OpenMEEG binaries
 - How do homogenous coordinate transformation matrices work?
 - How is anatomical, functional or statistical "volume data" described?
 - How is the segmentation defined?
 - How should I report the positions of the fiducial points on the head?
 - How should I specify the fiducials for electrode realignment?
 - How to change the MRI orientation, the voxel size or the field-of-view?
 - How to coregister an anatomical MRI with the gradiometer or electrode positions?
 - Is it OK for vertices/dipoles to stick out of the volume conductor?
 - Is it good or bad to have dipole locations outside of the brain for which the source reconstruction is computed?
 - Is it important to have accurate measurements of electrode locations for EEG source reconstruction?
 - My MRI is upside down, is this a problem?
 - Should I use a Polhemus or a Structure Sensor to record electrode positions?
 - What is the conductivity of the brain, CSF, skull and skin tissue?
 - What is the difference between the ACPC, MNI, SPM and TAL coordinate systems?
 - What kind of volume conduction models of the head (head models) are implemented?
 - What material is used for the flexible MEG headcasts?
 - Where can I find the dipoli command-line executable?
 - Where is the anterior commissure?
 - Why does my EEG headmodel look funny?
 - Why is the source model deformed or incorrectly aligned after warping template?
 - Why is there a rim around the brain for which the source reconstruction is not computed?
 - Why should I use an average reference for EEG source reconstruction?
 - Spectral analysis questions
 - Does it make sense to subtract the ERP prior to time frequency analysis, to distinguish evoked from induced power?
 - How can I compute inter-trial coherence?
 - How can I do time-frequency analysis on continuous data?
 - How does MTMCONVOL work?
 - How to interpret the sign of the phase slope index?
 - In what way can frequency domain data be represented in FieldTrip?
 - What are the differences between the old and the new implementation of 'mtmconvol' in ft_freqanalysis?
 - What are the differences between the old and the new implementation of 'mtmftt' in ft_freqanalysis?
 - What are the differences between the old and the new implementation of 'wavelet' (formerly 'wltconvol') in ft_freqanalysis?
 - What convention is used to define absolute phase in 'mtmconvol', 'wavelet' and 'mtmfft'?
 - What does "padding not sufficient for requested frequency resolution" mean?
 - What is meant by time-frequency trade off?
 - What is the difference between coherence and coherency?
 - Why am I not getting integer frequencies?
 - Why does my TFR contain NaNs?
 - Why does my TFR look strange (part I, demeaning)?
 - Why does my TFR look strange (part II, detrending)?
 - Why does my output.freq not match my cfg.foi when using 'mtmconvol' in ft_freqanalysis?
 - Why does my output.freq not match my cfg.foi when using 'mtmfft' in ft_freqanalysis
 - Why does my output.freq not match my cfg.foi when using 'wavelet' (formerly 'wltconvol') in ft_freqanalysis?
 - Why is the largest peak in the spectrum at the frequency which is 1/segment length?
 - Statistical questions
 - How NOT to interpret results from a cluster-based permutation test
 - How can I define neighbouring sensors?
 - How can I determine the onset of an effect?
 - How can I test for correlations between neuronal data and quantitative stimulus and behavioral variables?
 - How can I test whether a behavioral measure is phasic?
 - How can I use the ivar, uvar, wvar and cvar options to precisely control the permutations?
 - How does a difference in trial numbers per condition affect my statistical test
 - How does ft_prepare_neighbours work?
 - How to test an interaction effect using cluster-based permutation tests?
 - Should I use t or F values for cluster-based permutation tests?
 - What is the idea behind statistical inference at the second-level?
 - Why are there multiple neighbour templates for the Neuromag306 system?
 - Why should I use the cfg.correcttail option when using statistics_montecarlo?
 - Various other questions
 - Are the FieldTrip lectures available on video?
 - Can I compare EEG channels between different electrode caps?
 - Can I organize my own FieldTrip workshop?
 - How can I anonymize data processed in FieldTrip?
 - How can I anonymize or deidentify DICOM files?
 - How can I anonymize or deidentify a BrainVision dataset?
 - How can I anonymize or deidentify a CTF dataset?
 - How can I anonymize or deidentify an anatomical MRI?
 - How can I share my MEG data?
 - How do I prevent FieldTrip from printing the time and memory after each function call?
 - How should I prepare for the upcoming FieldTrip workshop?
 - How should I specify the coordinate systems in a BIDS dataset?
 - What are the units of the data and of the derived results?
 - Where can I find open access MEG/EEG data?
 - Which datasets are used in the documentation and where are they used?
 - Which methodological details should I report in an EEG/MEG manuscript?
 - Which version of FieldTrip should I download?
 - Getting started
 - Getting started with (data from) other software
 - Getting started with AnyWave
 - Getting started with BIDS
 - Getting started with BioImage Suite
 - Getting started with EEGLAB
 - Getting started with Homer
 - Getting started with LIMO MEEG
 - Getting started with LORETA
 - Getting started with MNE-Python
 - Getting started with MeshLab
 - Getting started with ParaView
 - Getting started with SPM
 - Getting started with Seg3D
 - Getting started with SimNIBS
 - Getting started with NIRS data
 - Getting started with Artinis NIRS data
 - Getting started with Hitachi NIRS data
 - Getting started with NIRx NIRS data
 - Getting started with SNIRF data
 - Getting started with Shimadzu NIRS data
 - Getting started with eyetracker data
 - Getting started with intracranial data
 - Getting started with Blackrock data
 - Getting started with Cyberkinetics data
 - Getting started with Neuralynx data
 - Getting started with Neuralynx data recorded at the Donders Institute
 - Getting started with Neurodata Without Borders (NWB) data
 - Getting started with Plexon data
 - Getting started with animal electrophysiology data, including spikes
 - Getting started with human ECoG data
 - Getting started with motion capture data
 - Getting started with other types of data
 - Getting started with audio data
 - Getting started with fMRI timeseries data
 - Getting started with video data
 - Getting started with particular EEG data types
 - Getting started with 20%, 10% and 5% electrode arrangements
 - Getting started with ABM's B-Alert EEG data
 - Getting started with ANT-Neuro, ASA and EEProbe data
 - Getting started with BESA data
 - Getting started with BioSemi BDF data
 - Getting started with BrainVision Analyzer and Easycap
 - Getting started with EDF (European Data Format) data
 - Getting started with EGI/Philips/Magstim data
 - Getting started with Nicolet data
 - Getting started with TMSi data
 - Getting started with particular MEG data types
 - Getting started with BTi/4D data
 - Getting started with BabySQUID data
 - Getting started with CTF data
 - Getting started with Cerca OPM data
 - Getting started with FieldLine OPM data
 - Getting started with Neuromag/Elekta/Megin data
 - Getting started with OPM data recorded at the FIL
 - Getting started with Ricoh data
 - Getting started with Yokogawa data
 - Getting started with real-time analysis
 - Importing your data
 - Index of all configuration options
 - Privacy Policy
 - Reference documentation
 - References to implemented methods
 - Review papers and teaching material
 - Search results
 - Support
 - Template models and data
 - Anatomical templates for visualizing source reconstructed activity
 - Template 2-D layouts for plotting
 - Template 3-D electrode sets
 - Template 3-D gradiometer descriptions
 - Template MEG dewar shapes
 - Template anatomical atlases and parcellation schemes
 - Template head models for EEG volume conduction modeling
 - Template models for source reconstruction
 - Templates for defining neighbouring channels
 - Tutorials
 - Details of the MEG language dataset
 - Details of the tMEG Motor task dataset
 - Details on the EEG language dataset
 - Details on the multimodal faces dataset
 - Tutorials on connectivity analysis
 - Analysis of corticomuscular coherence
 - Analysis of sensor- and source-level connectivity
 - Connectivity in auditory evoked responses
 - Extended analysis of sensor- and source-level connectivity
 - Whole brain connectivity and network analysis
 - Whole brain connectivity and network analysis
 - Whole brain connectivity and network analysis
 - Tutorials on making your analyses more efficient
 - Making a memory efficient analysis pipeline
 - Speeding up your analysis using distributed computing with parfor
 - Speeding up your analysis using distributed computing with qsub
 - Tutorials on plotting and visualization
 - Tutorials on reading and preprocessing of data
 - Automatic artifact rejection
 - Cleaning artifacts using ICA
 - Introduction on dealing with artifacts
 - Preprocessing - Reading continuous EEG and MEG data
 - Preprocessing - Segmenting and reading trial-based EEG and MEG data
 - Visual or manual artifact rejection
 - Tutorials on sensor-level analyses
 - Event-related averaging and MEG planar gradient
 - Extracting the brain state and events from continuous sleep EEG
 - Preprocessing and event-related activity in combined MEG/EEG data
 - Preprocessing of EEG data and computing ERPs
 - Preprocessing of Optically Pumped Magnetometer (OPM) data
 - Sensor-level ERF, TFR and connectivity analyses
 - Time-frequency analysis of combined MEG/EEG data
 - Time-frequency analysis using Hanning window, multitapers and wavelets
 - Tutorials on source reconstruction
 - Beamforming oscillatory responses in combined MEG/EEG data
 - Computation of virtual MEG channels in source-space
 - Coregistration of Optically Pumped Magnetometer (OPM) data
 - 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 source model for source reconstruction of MEG or EEG data
 - Creating a volume conduction model of the head for source reconstruction of MEG data
 - Dipole fitting of combined MEG/EEG data
 - EEG headmodels
 - Localizing electrodes using a 3D-scanner
 - Localizing oscillatory sources using beamformer techniques
 - Localizing sources using beamformer techniques
 - Localizing visual gamma and cortico-muscular coherence using DICS
 - Source reconstruction of event-related fields using minimum-norm estimation
 - Virtual channel analysis of epilepsy MEG data
 - Tutorials on statistical analysis
 - Classification of event-related MEG data using MVPA-Light
 - Cluster-based permutation tests on event-related fields
 - Cluster-based permutation tests on time-frequency data
 - Parametric and non-parametric statistics on event-related fields
 - Statistical analysis and multiple comparison correction for combined MEG/EEG data
 - Tutorials on the analysis of NIRS data
 - Preprocessing and averaging of multi-channel NIRS data
 - Preprocessing and averaging of single-channel NIRS data
 - Tutorials on the analysis of TMS data
 - Tutorials on the analysis of intracranial data
 - Analysis of human ECoG and sEEG recordings
 - Analysis of monkey ECoG recordings
 - Channel and source analysis of mouse EEG
 - ECoG tutorials
 - Preprocessing and analysis of spike and local field potential data
 - Preprocessing and analysis of spike-train data
 - Tutorials that introduce FieldTrip and MATLAB
 - Video lectures and tutorials
 - FieldTrip MEG/EEG workshop at NatMEG, Stockholm (October 2014)
 - FieldTrip workshop for the Human Connectome project at Washington University, St. Louis (2011)
 - FieldTrip/MNE workshop at NatMEG, Stockholm (January 2014)
 - Workshop at BRAMS Institute, Montreal (2012)
 - Website menu
 - Welcome to the FieldTrip website