Code covered by the BSD License

Highlights from
Mass Univariate ERP Toolbox

EEG=bin_info2EEG(EEG_or_fname... bin_info2EEG() - Adds "bin" information to an EEGLAB EEG variable based on
GND=baselineGND(GND,bsln_wind... baselineGND() - Baseline the ERPs in a Mass Univariate ERP Toolbox GND
GND=bin_dif(GND,binA,binB,dif... bin_dif() - Computes the difference waves from two bins and stores the
GND=decimateGND(GND,decfactor... decimateGND() - Downsamples a set of ERPs to a lower sampling rate.
GND=erplab2GND(gui_infiles_or... erplab2GND() - Create a Mass Univariate ERP Toolbox GND struct variable from a set of
GND=sets2GND(gui_infiles_or_t... sets2GND() - Create a Mass Univariate ERP Toolbox GND struct variable from a set of
GNDorGRP=rm_bins(GNDorGRP,bin... rm_bins() - Removes bin from a Mass Univariate ERP Toolbox GND or GRP variable
GNDorGRP=rm_ttest(GNDorGRP,tt... rm_ttest() - Removes sets of t-test results from a GND or GRP variable
GRP=GNDs2GRP(gui_infiles_or_t... GNDs2GRP() - Creates a Mass Univariate ERP Toolbox GRP variable from a set
GRP=bin_opGRP(GRP,op,groupA,b... bin_opGRP() - Computes the difference waves from two bins or the mean of
VerbReport(report,verbtag,VER... VerbReport() - Outputs messages if they exceed a desired level of importance.
[GND, p_values, data_t, crit_... tfdrGND() - Tests the null hypothesis that the grand average voltage
[GND, prm_pval, data_t, crit_... tmaxGND() - Tests the null hypothesis that the grand average voltage
[GND, prm_pval, data_t]=clust... clustGND() - Tests the null hypothesis that the grand average voltage
[GRP, p_values, data_t, crit_... tfdrGRP() - Tests the null hypothesis that the grand average voltage
[GRP, prm_pval, data_t, crit_... tmaxGRP() - Tests the null hypothesis that the grand average voltage
[GRP, prm_pval, data_t]=clust... clustGRP() - Tests the null hypothesis that the grand average voltage
[bindesc, bintype]=read_bin_l... read_bin_list_file() - Extracts "bin" information from a text file called
[clust_membership, n_clust, u... find_clusters() - Given a 2D matrix of t-scores, this function bundles
[clust_membership, n_clust]=f... find_clusters() - Given a 2D matrix of t-scores, this function bundles
[h crit_p adj_p]=fdr_bh(pvals...
[h crit_p]=fdr_bky(p_values,q...
[justpath, justname]=pathNnam... function [justpath, justname]=pathNname(full_file)
[p_adj, p_raw, t_raw, seed_st... korn_fd1-Korn et al. (2004) permutation based procedure for
[p_values, t_scores, mn, stde... fast_t1 - Computes a 2D matrix of one sample/repeated measures t-tests
[p_values, t_scores, mn_dif, ... fast_t2 - Computes a 2D matrix of independent sample t-tests relatively
[pval, t_orig, clust_info, se... function [pval, t_orig, clust_info, seed_state, est_alpha]=clust_perm1(data,chan_hood,n_perm,fwer,tail,thresh_p,verblevel,seed_state,freq_domain)
[pval, t_orig, clust_info, se... [pval, t_orig, clust_info, seed_state, est_alpha]=clust_perm2(dataA,dataB,chan_hood,n_perm,fwer,tail,thresh_p,verblevel,seed_state,freq_domain)
[pval, t_orig, tmx_ptile, see... function [pval, t_orig, tmx_ptile, seed_state, est_alpha]=mxt_perm1(data,n_perm,alph,tail,verblevel,seed_state,freq_domain)
[pval, t_orig, tmx_ptile, see... function [pval, t_orig, tmx_ptile, seed_state, est_alpha]=mxt_perm1(data,n_perm,alph,tail,verblevel,seed_state,freq_domain)
[pval, t_orig, tmx_ptile, see... function [pval, t_orig, tmx_ptile, seed_state, est_alpha]=mxt_perm2(dataA,dataB,n_perm,alph,tail,verblevel,seed_state,freq_domain)
[pval, t_orig, tmx_ptile, see... function [pval, t_orig, tmx_ptile, seed_state, est_alpha]=mxt_perm2(dataA,dataB,n_perm,alph,tail,verblevel,seed_state,freq_domain)
[types type_count]=list_event... list_event_types() - Tallies the set of event "types" in an EEGLAB EEG
art_ics=remove_artifact_ics(b... remove_artifact_ics() - Removes the independent components (ICs) of an
chan_hood=spatial_nearest_nei... spatial_nearest_neighbors() - Given a set of electrode coordinates, this
chan_hood=spatial_neighbors(c... spatial_neighbors() - Given a set of electrode coordinates, this function
comp_struct(s1,s2,n1,n2,p,tol) check two structures for differances - i.e. see if strucutre s1 == structure s2
comp_struct_quiet(s1,s2,n1,n2... check two structures for differances - i.e. see if strucutre s1 == structure s2
erp_var=save_erps(erp_var,new... save_erps() - Saves a GND or GRP variable to disk using its current filename
griddata2(x,y,z,xi,yi,method,... GRIDDATA Data gridding and surface fitting.
gui_erp(cmnd_str,varargin) gui_erp() - Open a GUI for visualzing ERP butterfly plots and
headinfo(GND_GRP_or_fname) headinfo() - Displays channel, bin and t-test information about the data
img=sig_raster3(GND_GRP_specG... sig_raster() - Plots 2D (electrode x time/frequency) raster diagram of
infiles=get_set_infiles(gui_i... function infiles=get_set_infiles(gui_infiles_or_tmplt,sub_ids)
ord=orderofmag(val) function ord=orderofmag(val)
plot_wave(GND_GRP_or_fname,bi...
reject=is_art(label) isart() - Function for evaluating whether or not the text label of an
rounded_val=rnd_orderofmag(va... function rounded_val=rnd_orderofmag(val)
sbjct_info2set(in_setfile,sbj... % sbjct_info2set() - Imports information about a subject into the epochs
sig_topo(GND_GRP_specGND_or_f... sig_topo() - Plots scalp topographies of EEG efffects that have been
sig_wave(GND_GRP_specGND_or_f... sig_wave() - Illustrates results of a mass univariate t-test on a
textsc(x,y,txt); textsc() - places text in screen coordinates and places
topoplotMK(Values,loc_file,va... topoplotMK() - plot a topographic map of a scalp data field in a 2-D circular view
tpt=find_tpt(tme,tmes) function tpt=find_tpt(tme,tmes)
watchit(msg) function watchit(msg)
save_matmk.m
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Mass Univariate ERP Toolbox

by David Groppe

04 Nov 2010 (Updated 29 Mar 2013)

Functions for performing and visualizing mass univariate analyses of event-related potentials.

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File Information
Description	The Mass Univariate ERP Toolbox is a freely available set of MATLAB functions for performing mass univariate analyses of event-related potentials (ERPs), a noninvasive measure of neural activity popular in cognitive neuroscience. A mass univariate analysis is the analysis of a massive number of simultaneously measured dependent variables via the performance of univariate hypothesis tests (e.g., t-tests). Savvy corrections for multiple comparisons are applied to make spurious findings unlikely while still retaining a useful degree of statistical power. The advantages of mass univariate analyses include: reduced need for a priori defined time windows/regions of interest, discovery of unexpected effects even when a priori time windows/regions of interest are available, and greater spatial and temporal resolution than conventional mean time window analyses. The disadvantages of mass univariate analyses are that they lose some statistical power due to correction for multiple comparisons and some popular corrections for multiple comparisons are not guaranteed to work or may not provide the degree of certainty provided by selective analyses of a priori time windows/regions of interest. Currently the toolbox supports within-subject and between-subject t-tests with false discovery rate controls and control of the family-wise error rate via permutation tests. This toolbox was produced by members of the Kutaslab of the Department of Cognitive Science at the University of California, San Diego. If you use the toolbox to perform analyses or to produce figures used in a publication, please cite the following article: Groppe, D.M., Urbach, T.P., Kutas, M. (2011) Mass univariate analysis of event-related brain potentials/fields I: A critical tutorial review, Psychophysiology, 48(12) pp. 1711-1725, DOI: 10.1111/j.1469-8986.2011.01273.x. Documentation and a tutorial for using the code are available here: http://openwetware.org/wiki/Mass_Univariate_ERP_Toolbox
Acknowledgements	Compare Structures inspired this file.
Required Products	Statistics Toolbox
MATLAB release	MATLAB 7.8 (R2009a)
Other requirements	The toolbox relies on the following EEGLAB functions: cbar.m finputcheck.m icadefs.m readlocs.m

Tags for This File
Everyone's Tags	bonferroni, cluster, cognitive neuroscience, eeg, eeglab, erplab, erps, eventrelated potentials, false di, false dis, false discovery rate, gui, mass univariate analysis, massively univariate analysis, multiple comparison correction, multiple comparisons(2), neuroimaging, permutation test, statistics, tmax(2)
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Comments and Ratings (3)
01 Feb 2013	David Groppe	Could should now be compatible with Matlab R2012.
30 Jun 2012	David Groppe	Please note the updated code. I don't think Mathworks alerts "watchers" of this file when it is updated (only when people add comments).
10 May 2012	ahmed albakri	THANK YOU

Updates
10 Nov 2010	Unnecessary directory information removed from zip file.
15 Nov 2010	Function erplab2GND.m was added so that this code can be used with the ERPLAB MATLAB toolbox. A few minor modifications to other functions were made as well.
04 Dec 2010	sig_wave.m and plot_wave.m were added to toolbox to help data visualization. A few minor modifications to other functions were made as well.
10 Dec 2010	Due to rounding errors, mxt_perm1.m could produce inaccurate within-subject p-values for very small sample sizes (e.g., 3 participants). This has been fixed.
10 Mar 2011	Several minor bug fixes and bin_info2EEG.m can now operate on continuous data. See toolbox wiki for full details.
23 Mar 2011	decimateGND.m now works on non-Kutaslab data and has 'save_GND' option.
04 Apr 2011	All functions should now be compatible with Windows.
11 Apr 2011	save_matmk.m was accidentally omitted from the last update.
22 Apr 2011	bin_info2EEG.m can now work on EEG variables without an EEG.event(x).duration field. tfdrGND and tfdrGRP now stores FDR corrected p-values in GND and GRP variable for BH and BY FDR control algorithms.
24 May 2011	save_erp.m and save_matmk.m were not fully compatible with Windows but now should be (thanks Elisa Filevich!). bin_opGRP.m was not working properly for some group orderings and has been fixed.
26 Jun 2011	Cluster-based permutation tests added to toolbox. Function for GFWER control added.
06 Sep 2011	bin_info2EEG.m fixed. New 'bin*' elements of EEG.events had wrong bin #s and the function wouldn't work if EEG.epoch(#).eventtype was numeric. These problems should not have affected results from the toolbox since it ignores the EEG.events field.
12 Dec 2011	Cluster-based permutation tests made recursiveless and better able to handle many comparisons by Amy Guthormsen.
05 Mar 2012	sig_raster.m can now use a temperature scale to represent graded values of significance (in microvolts or t-scores).
26 Jun 2012	Function crashed or could assign incorrect EEG.epoch info (e.g. EEG.epoch(x).latency) to a bin event when run on epoched data with more than one event per epoch. Thanks to Clemens Maidhof for alerting me to this.
31 Jan 2013	topoplotMK.m modified to be compatible with Matlab R2012.
11 Mar 2013	spatial_neighbors.m updated to estimate head radius from electrode locations. This makes it easier to translate max_dist parameter for cluster-based tests into centimeters.
29 Mar 2013	Updated to be compatible with Matlab R2013a (thanks Aaron Newman) and minor gui_erp.m visualization bug fix.

Highlights from Mass Univariate ERP Toolbox

Mass Univariate ERP Toolbox

Highlights from
Mass Univariate ERP Toolbox