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Functions are organised in three groups:

Admin functions: eeglab() and its menu functions.

Interactive pop-functions: Matlab functions with pop-up graphic interface windows called from the EEGLAB menu. These functions can be used from the Matlab commandline or in Matlab scripts and macro functions. They provide an EEGLAB graphic interface to the signal processing functions.

Study functions: Matlab functions for processing studies. Some of these function have pop-up graphic interfaces and may be called from the EEGLAB menu

Signal-processingfunctions: Matlab functions called by the EEGLAB graphic interface. Experienced Matlab users can call them directly from scripts or the Matlab

Admin functions

eeg_checkset	check the consistency of the fields of an EEG dataset Also: See EEG dataset structure field descriptions below.
eeg_eval	apply eeglab function to a collection of input datasets
eeg_global	declare global eeglab variables. These variables are used only as global by the main function eeglab, the function pop_rejmenu and the history eegh function.
eeg_helpadmin	Help file for eeglab
eeg_helphelp	How to use eeglab help.
eeg_helpmenu	Call the help file for eeglab menus
eeg_helppop	Help file for eeglab
eeg_helpsigproc	Help file for eeglab
eeg_helpstudy	Help file for eeglab
eeg_hist	history for eeglab dataset.
eeg_options	eeglab option script
eeg_optionsbackup	eeglab option script
eeg_readoptions	Read eeglab memory options file (eeg_options) into a structure variable (opt).
eeg_retrieve	Retrieve an EEG dataset from the variable containing all datasets (standard: ALLEEG).
eeg_store	store specified EEG dataset(s) in the ALLEG variable containing all current datasets, after first checking dataset consistency using eeg_checkset.
eegh	history function.
eeglab_error	generate an eeglab error.
eeglab_exec	apply eeglab function to a dataset and perform appropriate checks.
eeglab_options	handle eeglab options. This script (not function) set the various options in the eeg_options file.
errordlg2	Makes a popup dialog box with the specified message and (optional) title.
finputcheck	check Matlab function {'key','value'} input argument pairs
gethelpvar	convert a Matlab m-file help-message header into out variables
getkeyval	get variable value from a 'key', 'val' sequence string.
gettext	This function prints a dialog box on screen and waits for the user to enter a string. There is a cancel button which returns a value of [].
inputdlg2	inputdlg function clone with coloring and help for eeglab.
inputgui	A comprehensive gui automatic builder. This function helps to create GUI very quickly without bothering about the positions of the elements. After creating a geometry, elements just place themselves in the predefined locations. It is especially useful for figures in which you intend to put text buttons and descriptions.
is_sccn	returns 1 if computer is located at SCCN (Swartz Center for computational Neuroscience) and 0 otherwise
listdlg2	listdlg function clone with coloring and help for eeglab.
pop_delset	Delete a dataset from the variable containing all datasets.
pop_editoptions	Edit memory-saving eeglab options. These are stored in a file 'eeg_options.m'. With no argument, pop up a window to allow the user to set/unset these options. Store user choices in a new 'eeg_options.m' file in the working directory.
pop_rejmenu	Main menu for rejecting trials in an EEG dataset
pop_stdwarn	check memory options and issue warning for studies.
pophelp	Same as matlab hthelp but does not crash under windows.
questdlg2	questdlg function clone with coloring and help for eeglab.
supergui	a comprehensive gui automatic builder. This function help to create GUI very fast without bothering about the positions of the elements. After creating a geometry, elements just place themselves into the predefined locations. It is especially usefull for figure where you intend to put text button and descriptions.
vararg2str	transform arguments into string for evaluation using the eval() command
warndlg2	same as warndlg for eeglab

Interactive pop_functions

eeg_amplitudearea	Resamples an ERP average using spline interpolation at a new sample rate (resrate) in Hz to get the exact limits of the window of integration. Finely samples the window and adds together very narrow rectangles capped by right-angled triangles under the window. Output is in uV. Trade-off between speed and number of resamples and number of channels selected occurs.
eeg_chantype	Returns the channel indices of the desired channel type(s).
eeg_context	returns (in output 'delays') a matrix giving, for each event of specified ("target") type(s), the latency (in ms) to the Nth preceding and/or following urevents (if any) of specified ("neighbor") type(s). Return the target event and urevent numbers, the neighbor urevent numbers, and the values of specified urevent field(s) for each of the neighbor urevents. Uses the EEG.urevent structure, plus EEG.event().urevent pointers to it. If epoched data, also uses the EEG.epoch structure. For use in event-handling scripts and functions.
eeg_eegrej	reject porition of continuous data in an eeglab dataset
eeg_emptyset	Initialize an EEG dataset structure with default values.
eeg_epochformat	Convert the epoch information of a dataset from struct to array or vice versa.
eeg_eventformat	Convert the event information of a dataset from struct to array or vice versa.
eeg_eventhist	return or plot histogram of event or urevent field values. If NO output args, plots the histogram. If the field values are not numbers or strings, no histogram is computed.
eeg_eventtypes	return a list of event or urevent types in a dataset and the respective number of events of each type. Ouput event or urevent types are sorted in reverse order of their number. If no outputs, print this list on the commandline instead.
eeg_getepochevent	Return dataset event field values for all events of one or more specified types
eeg_getica	get ICA component activation. Recompute if necessary. >> mergelocs = eeg_getica(EEG, comp);
eeg_insertbound	insert boundary event in an EEG event structure.
eeg_interp	interpolate data channels
eeg_lat2point	convert latencies in time units relative to the time locking event of an eeglab data epoch to latencies in data points (assuming concatenated epochs).
eeg_matchchans	find closest channels in a larger eeglab chanlocs structure to channels in a smaller chanlocs structure
eeg_mergechan	merge channel structure while preserving channel order >> mergelocs = eeg_mergechan(locs1, locs2);
eeg_mergelocs	merge channel structure while preserving channel order >> mergedlocs = eeg_mergelocs(loc1, loc2, loc3, ...);
eeg_multieegplot	Produce an eegplot of a the average of an epoched dataset (with optional pre-labelling of specific trials).
eeg_oldica	report, return or add to oldicaweights and oldicasphere stored in cell arrays in EEG.etc of an eeglab dataset
eeg_point2lat	convert latency in data points to latency in ms relative to the time locking. Used in eeglab.
eeg_pv	Compute EEG.data 'percent variance ' (pv) of the whole EEG data versus the projections of specified components. Can omit specified components and channels from the computation. Can draw a plot of the scalp distribution of pv, or progressively compute the pv for comps 1:k, where k = 1 -> the total number of components. Note: pv's of spatially non-orthogonal independent components may not add to 100%, and individual component pv could be < 0%.
eeg_pvaf	Compute EEG.data 'percent variance accounted for' (pvaf) by specified components. Can omit specified components and channels from the computation. Can draw a plot of the scalp distribution of pvaf, or progressively compute the pvaf for comps 1:k, where k = 1 -> the total number of components. Note: pvaf's of spatially non-orthogonal independent components may not add to 100%, and individual component pvaf could be < 0%.
eeg_rejmacro	Internal eeglab macro for all pop_ functions that perform data rejection.
eeg_rejsuperpose	superpose rejections of a EEG dataset.
eeg_urlatency	find the real latency of an event in the continuous data.
getchanlist	Obtain indices of specified channel types.
importevent	Import experimental events from data file or Matlab array into a structure.
pop_averef	Convert an EEG dataset to average reference. This function is obsolete. See pop_reref instead.
pop_biosig	import data files into eeglab using BIOSIG toolbox
pop_chancenter	recenter cartesian X,Y,Z channel coordinates
pop_chancoresp	define correspondances between two channel locations structures (EEG.chanlocs) automatically (by matching channel labels) else using a user input gui.
pop_chanedit	Edit channel locations structure of an eeglab dataset, EEG.chanlocs. For EEG channel location structure and file formats, see >> help readlocs
pop_chanevent	import event latencies from the rising and/or falling 'edge' latencies of a specified event-marker channel in EEG.data
pop_chansel	pop up a graphic interface to select channels
pop_comments	edit comments
pop_compareerps	Compare the (ERP) averages of two datasets.
pop_comperp	Compute the grand average ERP waveforms of multiple datasets currently loaded into eeglab, with optional ERP difference-wave plotting and t-tests. Creates a plotting figure.
pop_copyset	Copy the current EEG dataset into another dataset.
pop_crossf	Return estimates and plots of event-related spectral coherence
pop_editeventfield	Add/remove/rename/modify a field in the event structure of an EEG dataset. Can also be used to append new events to the end of the event structure or to delete all current events. If the dataset is the only input, a window pops up to ask for relevant parameter values.
pop_editeventvals	Edit events contained in an EEG dataset structure. If the dataset is the only input, a window pops up allowing the user to insert the relevant parameter values.
pop_editset	Edit EEG dataset structure fields.
pop_eegfilt	interactively filter EEG dataset data using eegfilt
pop_eegplot	Visually inspect EEG data using a scrolling display. Perform rejection or marking for rejection of visually (and/or previously) selected data portions (i.e., stretches of continuous data or whole data epochs).
pop_eegthresh	reject artifacts by detecting outlier values. This has long been a standard method for selecting data to reject. Applied either for electrode data or component activations.
pop_envtopo	Plot envelope of an averaged EEG epoch, plus scalp maps of specified or largest contributing components referenced to their time point of maximum variance in the epoch or specified sub-epoch. Calls envtopo. When nargin < 3, a query window pops-up to allow additional arguments.
pop_epoch	Convert a continuous EEG dataset to epoched data by extracting data epochs time locked to specified event types or event indices. May also sub-epoch an already epoched dataset (if sub-epochs are same size or smaller). This pop_function calls epoch.
pop_erpimage	draw an ERP-image plot of a given EEG channel or independent component. Uses a pop-up window if less than three (or four in one condition) input arguments are supplied. Calls erpimage. For futher details see >> help erpimage
pop_eventstat	Computes and plots statistical characteristics of an EEG event, including the data histogram, a fitted normal distribution, a normal ditribution fitted on trimmed data, a boxplot, and the QQ-plot. The estimates value are printed in a panel and can be read as output. NaNs are omitted. See signalstat.
pop_expica	export ICA weights or inverse matrix
pop_export	export EEG dataset
pop_headplot	plot one or more spherically-splined EEG field maps using a semi-realistic 3-D head model. Requires a spline file, which is created first if not found. This may take some time, but does not need to be done again for this channel locations montage. A wait bar will pop up to indicate how much time remains.
pop_icathresh	main menu for choosing threshold for component rejection in EEGLAB.
pop_importdata	import data from a Matlab variable or disk file by calling importdata().
pop_importepoch	Export epoch and/or epoch event information to the event structure array of an EEG dataset. If the dataset is the only input, a window pops up to ask for the relevant parameter values.
pop_importevent	Import events into an EEG dataset. If the EEG dataset is the only input, a window pops up to ask for the relevant parameter values.
pop_importpres	append Presentation event file information into an eeglab dataset The Presentation stimulus presentation program outputs an ascii log file. This function merges existing EEG dataset events with additional field information (fields) about those events contained in the logfile.
pop_jointprob	reject artifacts in an EEG dataset using joint probability of the recorded electrode or component activities observed at each time point. e.g., Observing large absoluate values at most electrodes or components is improbable and may well mark the presence of artifact.
pop_loadbci	import a BCI2000 ascii file into eeglab
pop_loadcnt	load a neuroscan CNT file (pop out window if no arguments).
pop_loaddat	merge a neuroscan DAT file with input dataset (pop out window if no arguments).
pop_loadeeg	load a Neuroscan .EEG file (via a pop-up window if no arguments). Calls loadeeg.
pop_loadset	load an EEG dataset. If no arguments, pop up an input window.
pop_mergeset	Merge two or more datasets. If only one argument is given, a window pops up to ask for more arguments.
pop_newcrossf	Return estimates and plots of event-related spectral coherence
pop_newset	Edit/save EEG dataset structure information.
pop_newtimef	Returns estimates and plots of event-related (log) spectral perturbation (ERSP) and inter-trial coherence (ITC) changes timelocked to a set of input events in one data channel.
pop_plotdata	Plot average of EEG channels or independent components in a rectangular array. Else, (over)plot single trials.
pop_plottopo	plot one or more concatenated multichannel data epochs in a topographic array format using plottopo
pop_prop	plot the properties of a channel or of an independent component.
pop_read_erpss	interactively import an uncompressed ERPSS-format data file (.RAW or .RDF) using read_erpss
pop_readbdf	obsolete function, use the function pop_biosig instead
pop_readegi	load a EGI EEG file (pop out window if no arguments).
pop_readlocs	load a EGI-format EEG file (pop up an interactive window if no arguments).
pop_readsegegi	load a segmented EGI EEG file. Pop up query window if no arguments.
pop_rejepoch	Reject pre-labeled trials in a EEG dataset. Ask for confirmation and accept the rejection
pop_rejkurt	rejection of artifact in a dataset using kurtosis of activity (i.e. to detect peaky distribution of activity).
pop_rejspec	rejection of artifact in a dataset using thresholding of frequencies in the data.
pop_rejtrend	Measure linear trends in EEG data; reject data epochs containing strong trends.
pop_reref	Convert an EEG dataset to average reference or to a new common reference channel (or channels). Calls reref.
pop_resample	resample dataset (pop up window).
pop_rmbase	remove channel baseline means from an epoched or continuous EEG dataset. Calls rmbase.
pop_runica	Run an ICA decomposition of an EEG dataset using runica, binica, or another ICA or other linear decomposition.
pop_saveh	save the eeglab session command history stored in ALLCOM or in the 'history' field of the current dataset
pop_saveset	save one or more EEG dataset structures
pop_select	given an input EEG dataset structure, output a new EEG data structure retaining and/or excluding specified time/latency, data point, channel, and/or epoch range(s).
pop_selectcomps	Display components with button to vizualize their properties and label them for rejection.
pop_selectevent	Find events in an EEG dataset. If the dataset is the only input, a window pops up to ask for the relevant parameter values.
pop_signalstat	Computes and plots statistical characteristics of a signal, including the data histogram, a fitted normal distribution, a normal ditribution fitted on trimmed data, a boxplot, and the QQ-plot. The estimates value are printed in a panel and can be read as output. See SIGNALSTAT.
pop_snapread	load an EEG SnapMaster file (pop out window if no arguments).
pop_spectopo	Plot spectra of specified data channels or components. Show scalp maps of power at specified frequencies. Calls spectopo.
pop_subcomp	remove specified components from an EEG dataset. and subtract their activities from the data. Else, remove components already marked for rejection.
pop_timef	Returns estimates and plots of event-related (log) spectral perturbation (ERSP) and inter-trial coherence (ITC) changes timelocked to a set of input events in one data channel.
pop_timtopo	call the timtopo function for epoched EEG datasets. Plots the epoch mean for each channel on a single axis, plus scalp maps of the data at specified latencies.
pop_topoplot	Plot scalp map(s) in a figure window. If number of input arguments is less than 3, pop up an interactive query window. Makes (possibly repeated) calls to topoplot.
pop_writelocs	load a EGI EEG file (pop out window if no arguments).

Study processing functions

compute_ersp_times	computes the widest possible ERSP/ITC time window, which depends on requested ERSP/ITC parameters such as epoch limits, frequency range, wavelet parameters, sampling rate and frequency resolution that are used by timef(). This helper function is called by pop_preclust & std_ersp.
neural_net	computes clusters using Matlab Neural Net toolbox. Alternative clustering algorithm to kmeans(). This is a helper function called from pop_clust.
pop_chanplot	graphic user interface (GUI)-based function with plotting options for visualizing. Only channel measures (e.g., spectra, ERPs, ERSPs, ITCs) that have been computed and saved in the study EEG datasets can be visualized. These can be computed using the GUI-based pop_precomp.
pop_clust	select and run a clustering algorithm on components from an eeglab STUDY structure of EEG datasets. Clustering data should be prepared beforehand using pop_preclust and/or eeg_preclust(). The number of clusters must be specified in advance. If called in gui mode, the pop_clustedit window appears when the clustering is complete to display clustering results and allow the user to review and edit them.
pop_clustedit	graphic user interface (GUI)-based function with editing and plotting options for visualizing and manipulating an input STUDY structure. Only component measures (e.g., dipole locations, scalp maps, spectra, ERPs, ERSPs, ITCs) that have been computed and saved in the study EEG datasets can be visualized. These can be computed during pre-clustering using the GUI-based function pop_preclust or the equivalent command line functions eeg_createdata() and eeg_preclust(). To use dipole locations for clustering, they must first be stored in the EEG dataset structures using dipfit(). Supported cluster editing functions include new cluster creation, cluster merging, outlier rejection, and cluster renaming. Components can also be moved from one cluster to another or to the outlier cluster.
pop_erpparams	Set plotting and statistics parameters for cluster ERP plotting
pop_erspparams	Set plotting and statistics parameters for computing and plotting STUDY mean (and optionally single-trial) ERSP and ITC measures and measure statistics. Settings are stored within the STUDY structure (STUDY.etc.erspparams) which is used whenever plotting is performed by the function std_specplot.
pop_loadstudy	load an existing eeglab STUDY set of EEG datasets plus its corresponding ALLEEG structure. Calls std_loadalleeg.
pop_preclust	prepare STUDY components' location and activity measures for later clustering. Collect information in an interactive pop-up query window. To pre-cluster from the commandline, use std_preclust. After data entry into the pop window, selected measures (one or more from options: ERP, dipole locations, spectra, scalp maps, ERSP, and ITC) are computed for each dataset in the STUDY set, unless they already present. After all requested measures are computed and saved in the STUDY datasets, a PCA matrix (by runica with 'pca' option) is constructed (this is the feature reduction step). This matrix will be used as input to the clustering algorithm in pop_clust. pop_preclust allows selection of a subset of components to cluster. This subset may either be user-specified, all components with dipole model residual variance lower than a defined threshold (see dipfit()), or components from an already existing cluster (for hierarchical clustering). The EEG datasets in the ALLEEG structure are updated; then the updated EEG sets are saved to disk. Calls std_preclust.
pop_precomp	precompute measures (spectrum, ERP, ERSP) for a collection of data channels. Calls std_precomp.
pop_savestudy	save a STUDY structure to a disk file
pop_specparams	Set plotting and statistics parameters for computing STUDY component spectra.
pop_study	create a new STUDY set structure defining a group of related EEG datasets. The STUDY set also contains information about each of the datasets: the subject code, subject group, experimental condition, and session. This can be provided interactively in a pop-up window or be automatically filled in by the function. Defaults: Assume a different subject for each dataset and only one condition; leave subject group and session fields empty. Additional STUDY information about the STUDY name, task and miscellaneous notes can also be saved in the STUDY structure.
robust_kmeans	an extension of Matlab kmeans() that removes outlier components from all clusters. This is a helper function called from pop_clust.
ss_std_envtopo	Creates an envtopo image for a STUDY set, uses cluster contributions instead of individual components. Plots the envelope of a data epoch, plus envelopes and average scalp maps for specified or largest-contributing clusters for each condition. Click on individual axes to examine them in detail (using axcopy. See envtopo for further details.
std_centroid	compute cluster centroid in eeglab dataset STUDY. Compute and store the centroid(s) (i.e., mean(s)) for some combination of six measures on specified clusters in a STUDY. Possible measures include: scalp maps, ERPs, spectra, ERSPs, ITCs, dipole_locations
std_changroup	Create channel groups for plotting.
std_chaninds	look up channel indices in a STUDY
std_chantopo	plot ERP/spectral/ERSP topoplot at a specific latency/frequency.
std_checkset	check STUDY set consistency
std_clustread	load one or more requested measures ['erp'|'spec'|'ersp'|'itc'|'dipole'|'map'] for all components of a specified cluster. Calls std_readerp, std_readersp, etc.
std_comppol	inverse component polarity in a component cluster
std_createclust	dreate a new empty cluster. After creation, components may be (re)assigned to it using std_movecomp.
std_dipplot	Commandline function to plot cluster component dipoles. Dipoles for each named cluster is displayed in a separate figure. To view all the clustered components in the STUDY on the same figure (in a separate subplot), all STUDY clusters must be requested. To visualize dipoles, they first must be stored in the EEG dataset structures using dipfit(). Only components that have dipole locations will be displayed, along with the cluster mean dipole (in red).
std_editset	modify a STUDY set structure.
std_envtopo	Creates an envtopo image for a STUDY set, uses cluster contributions instead of individual components. Plots the envelope of a data epoch, plus envelopes and average scalp maps for specified or largest-contributing clusters for each condition. Click on individual axes to examine them in detail (using axcopy. See envtopo for further details.
std_erp	Constructs and returns channel or ICA activation ERPs for a dataset. Saves the ERPs into a Matlab file, [dataset_name].icaerp, for data channels or [dataset_name].icaerp for ICA components, in the same directory as the dataset file. If such a file already exists, loads its information.
std_erpplot	Command line function to plot STUDY cluster component ERPs. Either displays grand mean ERPs for all requested clusters in the same figure, with ERPs for different conditions (if any) plotted in different colors. Else, displays ERP for each specified cluster in separate figures (per condition), each containing the cluster component ERPs plus the grand mean cluster ERP (in bold). ERPs can be plotted only if component ERPs were computed and saved in the STUDY EEG datasets. These can be computed during pre-clustering using the gui-based function pop_preclust or the equivalent command line functions eeg_createdata() and eeg_preclust(). Called by pop_clustedit. and std_propplot.
std_ersp	Compute ERSP and/or ITC transforms for ICA components or data channels of a dataset. Save results into Matlab float files. When these output files already exist, loads the ERSP/ITC information from them unless the requested flag '??' specifies differently. If so, a query window pops up??. Also updates the EEG structure in the calling % Matlab environment?? and saves the modified dataset to disk??
std_erspplot	plot STUDY cluster ERSPs. Displays either mean cluster ERSPs, or else all cluster component ERSPs plus the mean cluster ERSP in one figure per condition. The ERSPs can be plotted only if component ERSPs were computed and saved in the EEG datasets in the STUDY. These may either be computed during pre-clustering using the gui-based function pop_preclust, or via the equivalent commandline functions eeg_createdata() and eeg_preclust(). Called by pop_clustedit.
std_filecheck	Check if ERSP or spec file contain specific parameters. This file must contain a Matlab structure with a field named 'parameter'. The content of this field will be compared to the 'params' input. If they are identical the output flag will indicate that recomputing this file is not necessary. If they are different, the user is queried ('guion' option) to see if he wishes to use the new parameters and recompute the file (not done in this function) or if he wishes to use the parameters of the file on disk.
std_findoutlierclust	determine whether an outlier cluster already exists for a specified cluster. If so, return the outlier cluster index. If not, return zero. This helper function is called by pop_clustedit, std_moveoutlier, std_renameclust.
std_interp	interpolate, if needed, a list of named data channels for all datasets included in a STUDY. Currently assumes that all channels have uniform locations across datasets.
std_itcplot	Commandline function to plot cluster ITCs. Either displays mean cluster ITCs, or else all cluster component ITCs, plus the mean cluster ITC, in one figure per cluster and condition. ITCs can be visualized only if component ITCs were calculated and saved in the STUDY EEG datasets. These can be computed during pre-clustering using the gui-based function pop_preclust, or via the equivalent commandline functions eeg_createdata() and eeg_preclust(). Called by pop_clustedit.
std_loadalleeg	constructs an ALLEEG structure, given the paths and file names of all the EEG datasets that will be loaded into the ALLEEG structure. The EEG datasets may be loaded without their EEG.data (see the pop_editoptions function), so many datasets can be loaded simultaneously. The loaded EEG datasets have dataset information and a (filename) pointer to the data.
std_mergeclust	Commandline function, to merge several clusters.
std_movecomp	Move ICA component(s) from one cluster to another.
std_moveoutlier	Commandline function, to reassign specified outlier component(s) from a cluster to its outlier cluster.
std_plot	plot ERP/spectral traces or ERSP/ITC images a component or channel cluster in a STUDY. Also allows plotting scalp maps.
std_plotcurve	plot ERP/spectral traces of a component or channel cluster in a STUDY.
std_plottf	plot ERSP/ITC images a component or channel cluster in a STUDY. Also allows plotting scalp maps.
std_preclust	prepare STUDY component location and activity measures for later clustering. Selected measures (one or more from options: ERPs, dipole locations, spectra, scalp maps, ERSPs, and ITCs) are computed for each dataset in the STUDY set, unless they already present. After all requested measures are computed and saved in the STUDY datasets, each feature dimension is reduced by computing a PCA decomposition. These PCA matrices (one per measure) are concatenated and used as input to the clustering algorithm in pop_clust. std_preclust allows selection of a subset of components to use in the clustering. This subset may be a user-specified component subset, components with dipole model residual variance lower than a defined threshold (see dipfit()), or components from an already existing cluster (for hierarchical clustering). The EEG datasets in the ALLEEG structure are updated. If new measures are added, the updated EEG sets are also saved to disk. Called by pop_preclust. Follow with eeg_clust() or pop_clust. See Example below.
std_precomp	Precompute measures (ERP, spectrum, ERSP, ITC) for channels in a study. If channels are interpolated before computing the measures, the updated EEG datasets are also saved to disk. Called by pop_precomp. Follow with pop_plotstudy(). See Example below.
std_propplot	Command line function to plot component cluster properties for a STUDY set. Displays mean cluster scalp map, ERP, ERSP; dipole model, spectrum, and ITC in one figure per cluster. Only meaasures computed during pre-clustering (by pop_preclust or std_preclust) are plotted. Called by pop_clustedit. Leaves the plotted grand mean cluster measures in STUDY.cluster for quick replotting.
std_readdata	load one or more requested measures ['erp'|'spec'|'ersp'|'itc'|'dipole'|'map'] for all components of a specified cluster. Called by cluster plotting functions: std_envtopo, std_erpplot, std_erspplot, ...
std_readerp	returns the ERP for an ICA component in an epoched dataset. The ERPs of the dataset ICA components are assumed to have been saved in a Matlab file, [dataset_name].icaerp, in the same directory as the dataset file. If this file doesn't exist, use std_erp to create it, else use a pre-clustering function that calls it: pop_preclust or std_preclust
std_readersp	Returns the equal-log-frequency spaced mean event-related spectral perturbation(s) (ERSP(s)) for a requested ICA component. The ERSP is assumed to have been saved in a Matlab file, [dataset_name].icaersp in the same folder as the dataset file. If this file does not exist, use std_ersp to create it, else use a pre-clustering function: pop_preclust or std_preclust, that calls it. Interpretation of the ERSP requires some input variables used to compute it: frequency range, window width, resolution, probability threshold, and wavelet type (FFT or wavelet_cycles). See >> timef help and >> timef details
std_readitc	returns the log-frequency inter-trial coherence (ITC) for a specified ICA component. The component ITCs for the dataset are assumed to have been saved in a Matlab file, [dataset_)name].icaitc, in the same directory as the dataset. If no such file exists, use std_ersp to create it, else the pre-clustering functions that call it: pop_preclust, std_preclust. The input variables used to compute the ITC are returnsd: frequency_range, time_range, resolution, probability_threshold, and wavelet type (FFT | wavelet cycles). See timef() for details.
std_readspec	returns the stored mean power spectrum for an ICA component in a specified dataset. The spectrum is assumed to have been saved in a Matlab file, "[dataset_name].icaspec", in the same directory as the dataset file. If this file doesn't exist, use std_spec to create it or a pre-clustering function (pop_preclust or std_preclust) that calls it.
std_readtopo	returns the scalp map of a specified ICA component, assumed to have been saved in a Matlab file, [dataset_name].icatopo, in the same directory as the dataset file. If this file does not exist, use std_topo to create it, else a pre-clustering function that calls it: pop_preclust or eeg_preclust().
std_readtopoclust	Command line function to read cluster component and scalp maps. This function automatically invert the polarity of scalp maps so they best match the polarity of the mean scalp map.
std_rejectoutliers	Commandline function, to reject outlier component(s) from clusters. Reassign the outlier component(s) to an outlier cluster specific to each cluster.
std_renameclust	Commandline function, to rename clusters using specified (mnemonic) names.
std_savedat	save measure for computed data
std_selcomp	Helper function for std_erpplot, std_specplot and std_erspplot to select specific components prior to plotting.
std_selsubject	Helper function for std_erpplot, std_specplot and std_erspplot to select specific subject when plotting channel data.
std_spec	Returns the ICA component spectra for a dataset. Updates the EEG structure in the Matlab environment and in the .set file as well. Saves the spectra in a file.
std_specplot	plot STUDY component cluster spectra, either mean spectra for all requested clusters in the same figure, with spectra for different conditions (if any) plotted in different colors, or spectra for each specified cluster in a separate figure for each condition, showing the cluster component spectra plus the mean cluster spectrum (in bold). The spectra can be plotted only if component spectra have been computed and saved with the EEG datasets in Matlab files "[datasetname].icaspec" using pop_preclust or std_preclust. Called by pop_clustedit. Calls std_readspec and internal function std_plotcompspec()
std_stat	compute statistics for ERP/spectral traces or ERSP/ITC images of a component or channel cluster in a STUDY.
std_topo	uses topoplot to get the interpolated Cartesian grid of the specified component topo maps. The topo map grids are saved into a (.icatopo) file and a pointer to the file is stored in the EEG structure. If such a file already exists, loads the information from it. Returns the topo map grids of all the requested components. Also returns the EEG sub-structure etc (i.e EEG.etc), which is modified with a pointer to the float file and some information about the file.
std_topoplot	Command line function to plot cluster component and mean scalp maps. Displays either mean cluster/s scalp map/s, or all cluster/s components scalp maps with the mean cluster/s scsalp map in one figure. The scalp maps can be visualized only if component scalp maps were calculated and saved in the EEG datasets in the STUDY. These can be computed during pre-clustering using the GUI-based function pop_preclust or the equivalent commandline functions eeg_createdata() and eeg_preclust(). A pop-function that calls this function is pop_clustedit.
toporeplot	re-plot a saved topoplot output image (a square matrix) in a 2-D circular scalp map view (as looking down at the top of the head). May also be used to re-plot a mean topoplot map for a number of subjects and/or components without all the constitutent maps having the same channel montage. Nose is at top of plot. Left = left. See topoplot.

Signal processing functions

acsobiro	A.C.'s Robust second-order blind identification (SOBI) by joint
adjustlocs	read neuroscan polar location file (.asc)
angtimewarp	Given two event marker vectors, computes a warping of the input angular time series so that its evlatencies match newlatencies. Values of the warped timeserie that falls between two frames in the original timeserie will be linearly interpolated under the assumption that phase change is minimal between two successive time points.
anova1_cell	compute F-values in cell array using ANOVA.
anova2_cell	compute F-values in cell array using ANOVA.
axcopy	Copy a Matlab figure axis and its graphic objects to a new pop-up window using the left mouse button.
binica	Run stand-alone binary version of runica from the Matlab command line. Saves time and memory relative to runica. If stored in a float file, data are not read into Matlab, and so may be larger than Matlab can handle owing to memory limitations.
biosig2eeglabevent	convert biosig events to eeglab event structure
blockave	make block average of concatenated data sets of same size Each data set is assumed to be of size (chans,frames).
cart2topo	convert xyz-cartesian channel coordinates to polar topoplot coordinates. Input data are points on a sphere centered at (0,0,0) or at optional input 'center'. This function is now DEPRECATED! See Important warning below.
cbar	Display full or partial color bar
celltomat	convert cell array to matrix
chancenter	recenter cartesian X,Y,Z channel coordinates
changeunits	Takes one or more points in one axes and gives its position in another axes. Useful for drawing lines between sbplots (see sbplot.
compvar	project selected components and compute the variance of the original signal they account for.
condstat	accumulate surrogate data for comparing two data conditions
convertlocs	Convert electrode locations between coordinate systems using the EEG.chanlocs structure.
copyaxis	helper function for axcopy
coregister	Co-register measured or template electrode locations with a a reference channel locations file. For instance if you want to perform dipole modeling you have to coregister (align) your channel electrodes with the model (and the easiest way to do that is to coregister your channel electrodes with the electrodes file associated with the model. To use coregister, one may for instance use the default MNI head and 10-5 System locations from Robert Oostenveld, used in the dipfit2() dipole modeling function as a reference. Use coregister to linearly align or nonlinearly warp subsequently recorded or nominally identified (e.g., 'Cz') sets of channel head locations to the reference locations. Both channel locations and/or fiducial (non-electrode) locations can then be used by coregister to linearly align or nonlinearly warp a given or measured montage to the reference locations. In its (default) manual mode, coregister produces an interactive gui showing the imported and reference channel locations on the imported head mesh (if any), allowing the user to make additional manual adjustments using gui text entry boxes, and to rotate the display using the mouse.
eegfilt	(high|low|band)-iass filter data using two-way least-squares FIR filtering. Multiple data channels and epochs supported. Requires the MATLAB Signal Processing Toolbox.
eegfiltfft	(high|low|band)-pass filter data using inverse fft (without using the Matlab signal processing toolbox)
eegplot	Scroll (horizontally and/or vertically) through multichannel data. Allows vertical scrolling through channels and manual marking and unmarking of data stretches or epochs for rejection.
eegplot2event	convert eegplot rejections into events compatible with eeglab format for continuous datasets.
eegplot2trial	convert eegplot rejections into trial and electrode rejections compatible with eeglab format.
eegrej	reject/excise arbitrary periods from continuous EEG data (e.g., EEG.data).
eegthresh	classical trial rejection rejection using a threshold on the raw signal
entropy_rej	calculation of entropy of a 1D, 2D or 3D array and rejection of odd last dimension values of the input data array using the discrete entropy of the values in that dimension (and using the probability distribution of all columns).
env	return envelope of rows of a data matrix, or optionally of the data interpolated to a different sampling rate.
envtopo	Plot the envelope of a multichannel data epoch, plus envelopes and scalp maps of specified or largest-contributing components. If a 3-D input matrix, operates on the mean of the data epochs. Click on individual axes to examine them in detail. The black lines represent the max and min values across all channels at each time point. The blue shading represents the max and min contributions of the selected components tothose channels. The paired colored lines represent the max and min contributions of the indicated component across all channels.
epoch	Extract epochs time locked to specified events from continuous EEG data.
erpimage	Plot a colored image of a collection of single-trial data epochs, optionally sorted on and/or aligned to an input sorting variable and smoothed across trials with a moving-average. (To return event-aligned data without plotting, use eegalign()). Optionally sort trials on value, amplitude or phase within a specified latency window. Optionally plot the ERP mean and std. dev.and moving-window spectral amplitude and inter-trial coherence at aselected or peak frequency. Optionally 'time warp' the single trial time-domain (potential) or power data to align the plotted data to a series of events with varying latencies that occur in each trial. Click on individual figures parts to examine them separately and zoom (using axcopy.
eventalign	function called by pop_importevent to find the best sampling rate ratio to align 2 arrays of data events.
eventlock	DEPRECATED: Please use eegalign() instead.
eyelike	calculate a permutation matrix P and a scaling (diagonal) maxtrix S such that S*P*E is eyelike (so permutation acts on the rows of E). E must be a square matrix.
fastif	fast if function.
floatread	Read matrix from float file ssuming four byte floating point number Can use fseek() to read an arbitary (continguous) submatrix.
floatwrite	Write data matrix to float file.
forcelocs	rotate location in 3-D so specified electrodes match specified locations. CAUTION: Only for use on electrodes in and remaining in the upper spherical hemisphere, otherwise it will work improperly. Written primarily for adjusting all electrodes homogenously with Cz.
headplot	plot a spherically-splined EEG field map on a semi-realistic 3-D head model. Can 3-D rotate the head image using the left mouse button.
icaact	compute ICA activation waveforms = weights*sphere*(data-meandata)
icadefs	function to read in a set of eeglab system-wide (i.e. lab-wide) or working directory-wide constants and preferences. Change the way these are defined in the master icadefs.m file (usually in dir eeglab/functions/sigprocfunc) or make a custom copy of the icadefs.m file in a project directory. Then, calling functions that call icadefs from an eeglab session in that working directory will read the local copy, which may set preferences different from the system-wide copy.
icaproj	project ICA component activations through the associated weight matrices to reconstitute the observed data using only the selected ICA components.
icavar	project ICA component activations through the ICA weight matrices to reconstitute the observed data using selected ICA components. Returns time course of variance on scalp for each component.
imagesctc	DEPRECATED. never completed or documented.
jader	blind separation of real signals using JADE (v1.5, Dec. 1997).
jointprob	rejection of odd columns of a data array using joint probability of the values in that column (and using the probability distribution of all columns).
kurt	return kurtosis of input data distribution
loadavg	loading eeg average data file from Neuroscan into matlab.
loadcnt	Load a Neuroscan continuous signal file.
loaddat	loading neuroscan format data file into matlab.
loadeeg	load a binary data file in Neuroscan .eeg file format.
loadtxt	load ascii text file into numeric or cell arrays
matsel	select rows, columns, and epochs from given multi-epoch data matrix
mattocell	convert matrix to cell array
metaplottopo	plot concatenated multichannel data epochs in a topographic or rectangular array. Uses a channel location file with the same format as topoplot, or else plots data on a rectangular grid.
movav	Perform a moving average of data indexed by xvals. Supports use of a moving non-rectangular window. Can be used to resample a data matrix to any size (see xadv NOTE below) and to regularize sampling of irregularly sampled data.
moveaxes	move, resize, or copy Matlab axes using the mouse
nan_mean	Average, not considering NaN values
openbdf	Opens an BDF File (European Data Format for Biosignals) in MATLAB (R)
parsetxt	parse text input into cell array
phasecoher	Implements inter-trial amp/coherence using Gaussian wavelets. Returns same data length as input frames. Plots results when nargin>6. Outputs have flat ends at data indices [1:halfwin] and [frames-halfwin:frames].
plotchans3d	Plots the 3-D configuration from a Polhemus ELP file. The axes of the Cartesian coordinate system are plotted. The nose is plotted as a bold red segment.
plotcurve	plot curve(s) with optional significance highlighting.
plotdata	plot concatenated multichannel data epochs in two-column format
ploterp	plot a selected multichannel data epoch on a common timebase
plotmesh	plot mesh defined by faces and vertex
plotsphere	only keep the biggest surface
plottopo	plot concatenated multichannel data epochs in a topographic or rectangular array. Uses a channel location file with the same format as topoplot, or else plots data on a rectangular grid. If data are all positive, they are assumed to be spectra.
posact	Make runica activations all RMS-positive. Adjust weights and inverse weight matrix accordingly.
projtopo	plot projections of one or more ICA components along with the original data in a 2-d topographic array. Returns the data plotted. Click on subplot to examine separately.
qqdiagram	Empirical quantile-quantile diagram.
quantile	computes the quantiles of the data sample from a distribution X
read_erpss	read an compressed and uncompressed ERPSS file formats (.RAW or .RDF)
readbdf	Loads selected Records of an EDF or BDF File (European Data Format for Biosignals) into MATLAB
readedf	read eeg data in EDF format.
readeetraklocs	read 3-D location files saved using the EETrak digitizing software.
readegi	read EGI Simple Binary datafile (versions 2,3,4,5,6,7). Return header info, EEG data, and any event data.
readegihdr	read header information from EGI (versions 2,3,4,5,6,7) data file.
readelp	read electrode locations from an .elp (electrode positions) file as generated, for example, by a Polhemus tracking device
readlocs	read electrode location coordinates and other information from a file. Several standard file formats are supported. Users may also specify a custom column format. Defined format examples are given below (see File Formats).
readneurodat	read neuroscan location file (.dat)
readneurolocs	read neuroscan polar location file (.asc)
realproba	compute the effective probability of the value in the sample.
rejkurt	calculation of kutosis of a 1D, 2D or 3D array and rejection of outliers values of the input data array using the discrete kutosis of the values in that dimension.
rejstatepoch	reject bad eeg trials based a statistical measure. Can be applied either to the raw eeg data or the ICA component activity. This is an interactive function.
rejtrend	detect linear trends in EEG activity and reject the epoched trials based on the accuracy of the linear fit.
reref	convert common reference EEG data to some other common reference or to average reference
rmbase	subtract basevector channel means from multi-epoch data matrix
runica	Perform Independent Component Analysis (ICA) decomposition of input data using the logistic infomax ICA algorithm of Bell & Sejnowski (1995) with the natural gradient feature of Amari, Cichocki & Yang, or optionally the extended-ICA algorithm of Lee, Girolami & Sejnowski, with optional PCA dimension reduction. Annealing based on weight changes is used to automate the separation process.
runica_ml	Perform Independent Component Analysis (ICA) decomposition of input data using the logistic infomax ICA algorithm of Bell & Sejnowski (1995) with the natural gradient feature of Amari, Cichocki & Yang, or optionally the extended-ICA algorithm of Lee, Girolami & Sejnowski, with optional PCA dimension reduction. Annealing based on weight changes is used to automate the separation process.
runica_ml2	Perform Independent Component Analysis (ICA) decomposition of input data using the logistic infomax ICA algorithm of Bell & Sejnowski (1995) with the natural gradient feature of Amari, Cichocki & Yang, or optionally the extended-ICA algorithm of Lee, Girolami & Sejnowski, with optional PCA dimension reduction. Annealing based on weight changes is used to automate the separation process.
runica_mlb	Perform Independent Component Analysis (ICA) decomposition of input data using the logistic infomax ICA algorithm of Bell & Sejnowski (1995) with the natural gradient feature of Amari, Cichocki & Yang, or optionally the extended-ICA algorithm of Lee, Girolami & Sejnowski, with optional PCA dimension reduction. Annealing based on weight changes is used to automate the separation process.
sbplot	create axes in arbitrary subplot grid positions and sizes
sdfopen	Opens EDF/GDF/SDF files for reading and writing. The EDF format is specified in [1], GDF in [2]. SDF is the SIESTA convention (see [3], pp.8-9); SDF uses the EDF format.
sdfread	Reads selected seconds of an EDF File (European Data Format for Biosignals) The EDF data and header format is specified in [1].
shuffle	shuffle a given dimension in an array
signalstat	Computes and plots statistical characteristics of a signal, including the data histogram, a fitted normal distribution, a normal ditribution fitted on trimmed data, a boxplot, and the QQ-diagram. The estimates value are printed in a panel and can be read as output. Optionally, a topographic map (see TOPOPLOT) can be plotted. The boxplot and the Kolmogorov-Smirnov test require the MATLAB Statistics Toolbox.
slider	add slider to a figure
snapread	Read data in Snap-Master Standard Binary Data File Format Reads Snap-Master header and data matrix (nchans,nframes). Ref: Users Guide, Snap-Master for Windows (1997) p. 4-19
sobi	Second Order Blind Identification (SOBI) by joint diagonalization of correlation matrices. THIS CODE ASSUMES TEMPORALLY CORRELATED SIGNALS, and uses correlations across times in performing the signal separation. Thus, estimated time delayed covariance matrices must be nonsingular for at least some time delays.
spec	power spectrum. This function replaces psd() function if the signal processing toolbox is not present. It uses the timef() function.
spectopo	Plot the mean log spectrum of a set of data epochs at all channels as a bundle of traces. At specified frequencies, plot the relative topographic distribution of power. If available, uses pwelch() from the Matlab signal processing toolbox, else the eeglab spec function. Plots the mean spectrum for all of the supplied data, not just the pre-stimulus baseline.
sph2topo	Convert from a 3-column headplot file in spherical coordinates to 3-column topoplot locs file in polar (not cylindrical) coords. Used for topoplot and other 2-D topographic plotting programs. Assumes a spherical coordinate system in which horizontal angles have a range [-180,180] deg, with zero pointing to the right ear. In the output polar coordinate system, zero points to the nose. See >> help readlocs
spher	return the sphering matrix for given input data
spherror	chancenter sub function to compute minimum distance of Cartesian coordinates to a sphere
statcond	compare two or more data conditions statistically using standard parametric or nonparametric permutation-based ANOVA (1-way or 2-way) or t-test methods. Parametric testing uses fcdf() from the Matlab Statistical Toolbox. Use of up to 4-D data matrices speeds processing.
strmultiline	format a long string as a multi-line string.
textsc	places text in screen coordinates and places a title at the top of the figure.
timefdetails	details of the timef() function for time/frequency analysis of multiple epochs of single-channel event-related data.
timewarp	Given two event marker vectors, computes a matrix that can be used to warp a time series so that its evlatencies match newlatencies. Values of the warped timeserie that falls between two frames in the original timeserie will be linear interpolated.
timtopo	plot all channels of a data epoch on the same axis and map its scalp map(s) at selected latencies.
topo2sph	convert a topoplot style 2-D polar-coordinate channel locations file to a 3-D spherical-angle file for use with headplot
topoplot	plot a topographic map of a scalp data field in a 2-D circular view (looking down at the top of the head) using interpolation on a fine cartesian grid. Can also show specified channnel location(s), or return an interpolated value at an arbitrary scalp location (see 'noplot'). By default, channel locations below head center (arc_length 0.5) are shown in a 'skirt' outside the cartoon head (see 'plotrad' and 'headrad' options below). Nose is at top of plot; left is left; right is right. Using option 'plotgrid', the plot may be one or more rectangular grids.
transformcoords	Select nazion and inion in anatomical MRI images.
trial2eegplot	convert eeglab format to eeplot format of rejection window
uigetfile2	same as uigetfile but remember folder location.
uiputfile2	same as uigputfile but remember folder location.
writecnt	Write a Neuroscan continuous signal file.
writelocs	write a file containing channel location, type and gain information

Other functions not accessible using the GUI

abspeak	find peak amps/latencies in each row of a single-epoch data matrix
arrow	Draw a line with an arrowhead.
averef	convert common-reference EEG data to average reference
caliper	Measure a set of spatial components of a given data epoch relative to a reference epoch and decomposition.
chanproj	make a detailed plot of data returned from plotproj for given channel. Returns the data plotted.
compdsp	Display standard info figures for a data decomposition Creates four figure windows showing: Component amplitudes, scalp maps, activations and activation spectra.
compheads	plot multiple topoplot maps of ICA component topographies
compmap	Plot multiple topoplot maps of ICA component topographies Click on an individual map to view separately.
compplot	plot a data epoch and maps its scalp topography at a given time
compsort	reorder ICA components, first largest to smallest by the size of their maximum variance in the single-component projections, then (if specified) the nlargest component projections are reordered by the (within-epoch) time point at which they reach their max variance.
convolve	convolve two matrices (normalize by the sum of convolved elements to compensate for border effects).
covary	For vectors, covary(X) returns the variance of X. For matrices, covary(X)is a row vector containing the variance of each column of X.
crossfold	Returns estimates and plot of event-related coherence (ERC) changes between data from two input channels. The lower panel gives the coherent phase difference between the processes. In this panel, for Ex. -90 degrees (blue) means xdata leads ydata by a quarter cycle. 90 degrees (orange) means ydata leads xdata by a quarter cycle. Click on each subplot to view separately and zoom in/out.
datlim	return min and max of a matrix
del2map	compute the discrete laplacian of an EEG distribution.
difftopo	compute and plot component decomposition for the difference ERP between two EEG datasets. Plots into the current axis (gca); plot into a new empty figure as below.
eeg_ms2f	convert epoch latency in ms to nearest epoch frame number
eeg_regepochs	Convert a continuous dataset into consecutive epochs of a specified regular length by adding dummy events of type 'X' and epoching the data around these events. The mean of each epoch (or if min epochlimits arg < 0, the mean of the pre-0 baseline) is removed from each epoch. May be used to split up continuous data for artifact rejection followed by ICA decomposition. The computed EEG.icaweights and EEG.icasphere matrices may then be exported to the continuous dataset and/or to its epoched descendents.
eeg_time2prev	returns a vector giving, for each event of specified ("target") type(s), the delay (in ms) since the preceding event (if any) of specified ("previous") type(s). Requires the EEG.urevent structure, plus EEG.event().urevent pointers to it. NOW SUPERCEDED BY eeg_context
eegdraw	subroutine used by eegplotold to plot data.
eegdrawg	subroutine used by eegplotgold to plot data.
eegmovie	Compile and view a Matlab movie. Uses scripts eegplotold and topoplot. Use seemovie to display the movie.
eegplotgold	display EEG data in a clinical format
eegplotold	display data in a horizontal scrolling fashion with (optional) gui controls (version 2.3)
eegplotsold	display data in a clinical format without scrolling
envproj	plot envelopes of projections of selected ICA component projections against envelope of the original data
gabor2d	generate a two-dimensional gabor matrice.
gauss	return a smooth Gaussian window
gauss2d	generate a 2-dimensional gaussian matrix
getallmenus	get all submenus of a window or a menu and return a tree.
gradmap	compute the gradient of an EEG spatial distribution.
gradplot	Compute the gradient of EEG scalp map(s) on a square grid
headmovie	Record a Matlab movie of scalp data. Use seemovie to display the movie.
help2html	Convert a Matlab m-file help-message header into an .html help file
hungarian	Solve the assignment problem using the Hungarian method.
icademo	a sample ICA analysis script using the ICA/ERP package of Matlab functions distributed via http://www.sccn.ucsd.edu/eeglab
imagescloglog	make an imagesc(0) plot with log y-axis and x-axis values
imagesclogy	make an imagesc(0) plot with log y-axis values (ala semilogy())
laplac2d	generate a 2 dimensional gaussian matrice
lapplot	Compute the discrete laplacian of EEG scalp distribution(s)
loadelec	Load electrode names file for eegplot
loc_subsets	Separate channels into maximally evenly-spaced subsets. This is achieved by exchanging channels between subsets so as to increase the sum of average of distances within each channel subset.
logimagesc	make an imagesc(0) plot with log y-axis values (ala semilogy())
loglike	log likehood function to estimate dependence between components
logspec	plot mean log power spectra of submitted data on loglog scale using plotdata or plottopo formats
makeelec	subroutine to make electrode file in eegplot
makehtml	generate .html function-index page and function help pages composed automatically from formatted Matlab function help messages
matcorr	Find matching rows in two matrices and their corrs. Uses the Hungarian (default), VAM, or maxcorr assignment methods. (Follow with matperm to permute and sign x -> y).
matperm	transpose and sign rows of x to match y (run after matcorr )
nan_std	std, not considering NaN values
numdim	estimate a lower bound on the (minimum) number of discrete sources in the data via their second-order statistics.
pcexpand	expand data using Principal Component Analysis (PCA) returns data expanded from a principal component subspace [compare pcsquash]
pcsquash	compress data using Principal Component Analysis (PCA) into a principal component subspace. To project back into the original channel space, use pcexpand
perminv	returns the inverse permutation vector
plotproj	plot projections of one or more ICA components along with the original data (returns the data plotted)
promax	perform Promax oblique rotation after orthogonal Varimax rotation of the rows of the input data. A method for linear decomposition by "rotating to simple structure."
qrtimax	perform Quartimax rotation of rows of a data matrix.
read_RDF	read RDF-formatted EEG files.
readlocsold	Read electrode locations file in style of topoplot or headplot. Output channel information is ordered by channel numbers.
rmart	Remove eye artifacts from EEG data using regression with multiple time lags. Each channel is first made mean-zero. After JL Kenemans et al., Psychophysiology 28:114-21, 1991.
rmsave	return the RMS in each channel, epoch
runicatest	Perform Independent Component Analysis (ICA) decomposition using natural-gradient infomax - the infomax ICA algorithm of Bell & Sejnowski (1995) with the natural gradient method of Amari, Cichocki & Yang, the extended-ICA algorithm of Lee, Girolami & Sejnowski, PCA dimension reduction, and/or specgram() preprocessing (suggested by M. Zibulevsky).
runpca	perform principal component analysis (PCA) using singular value decomposition (SVD) using Matlab svd() or svds() >> inv(eigvec)*data = pc;
seemovie	see an EEG movie produced by eegmovie
shortread	Read matrix from short file.
testica	Test the runica function's ability to separate synthetic sources. Use the input variables to estimate the (best) decomposition accuracy for a given data set size.
textgui	make sliding vertical window. This window contain text with optional function calls at each line.
tftopo	Generate a figure showing a selected or representative image (e.g., an ERSP, ITC or ERP-image) from a supplied set of images, one for each scalp channel. Then, plot topoplot scalp maps of value distributions at specified (time, frequency) image points. Else, image the signed (selected) between-channel std(). Inputs may be outputs of timef(), crossf(), or erpimage.
timefrq	progressive Power Spectral Density estimates on a single EEG channel using out-of-bounds and muscle activity rejection tests. Uses Matlab FFT-based psd().
topoimage	plot concatenated multichannel time/frequency images in a topographic format Uses a channel location file with the same format as topoplot or else plots data on a rectangular grid of axes. Click on individual images to examine separately.
tree	Make a hierarchical (tree-diagram) component plot. Use successive calls to this function to build the full plot.
tutorial	Bring up the ICA / electrophysiology toolbox tutorial in a browser window (see docopt.m in the toolbox dir). Tutorial URL: http://www.sccn.ucsd.edu/tutorial/ Download: See http://www.sccn.ucsd.edu/ica.html
varimax	Perform orthogonal Varimax rotation on rows of a data matrix.
varsort	reorder ICA components, largest to smallest, by the size of their MEAN projected variance across all time points
vectdata	vector data interpolation with optional moving average.
zica	Z-transform of ICA activations; useful for studying component SNR