sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
d31df15174d778ed7445e8a5ebfcab21f37e8c0cd3f671d316c910fae03e8d5f | MATLAB | 9,357 | 222 | classdef NetworkAtlas < nla.inputField.InputField
%NETWORKATLAS Network atlas, contains network + ROI details
properties (Constant)
name = 'net_atlas'
disp_name = 'Network atlas';
end
properties
net_atlas = false
end
properties (Access = protected)
butto... |
494b62311d063d90ed88ad575178bd0852c0d3f330d7cfd263121b47157b8da1 | MATLAB | 9,385 | 272 | function varargout = process_nst_glm_group_ttest( varargin )
% process_nst_compute_group_ttest
% Compute a t-test using mixed effects
%
% @=============================================================================
% This function is part of the Brainstorm software:
% http://neuroimage.usc.edu/brainstorm
%
% Copyrig... |
b79cec68eee8f6c89f4b1d2d79c77a2886a8121e157670440072f88eb0c49184 | MATLAB | 9,389 | 206 | function jds_sleepStateVelTDComparison(animalprefixlist, varargin)
% Compare velocity and theta/delta ratio (TD) across NREM and REM sleep.
%
% INPUT
% animalprefixlist : cell array of animal ID strings
% varargin : optional name-value pairs
%
% The function produces:
% • Box-plots of velocity and TD (z-s... |
dc655012cba7ced7fc6ddf3fbf998db172a881e69a9c8f0d24d75f28ef64c4c1 | MATLAB | 9,395 | 197 | classdef MontageTest < matlab.unittest.TestCase
properties
tmp_dir
end
methods(TestMethodSetup)
function setup(testCase)
tmpd = tempname;
mkdir(tmpd);
testCase.tmp_dir = tmpd;
utest_bst_setup();
end
end
methods(T... |
42f7bc034ffbb7826a3b7ff67691eed2dda047bbbba579b5704b68cbf56b0840 | MATLAB | 9,400 | 284 | function OCDdraw_m21_plot26()
%% =========================================
% M21: beta distribution plot (70 x 26 mm)
% Revised version (fix overlap of "median estimate" with left panel):
% 1) Fix left-panel XTick to [0 0.05]
% 2) Narrow the right subject-level panel
% 3) Keep the right panel right-aligned
% ... |
b872c1f2bd51393818972f9bacbb1995008b7112514b6a1db04c6ada6ccfdc3d | MATLAB | 9,404 | 286 | % Save NIFTI dataset. Support both *.nii and *.hdr/*.img file extension.
% If file extension is not provided, *.hdr/*.img will be used as default.
%
% Usage: save_nii(nii, filename, [old_RGB])
%
% nii.hdr - struct with NIFTI header fields (from load_nii.m or make_nii.m)
%
% nii.img - 3D (or 4D) matrix of NIFTI... |
f1eb03400349abd826b95b4b58018e421331be4f26feec96525a11fffacaebdb | MATLAB | 9,404 | 254 | function jds_thetaPhaseLockingPFCRipplesShifters(animalprefixlist)
%JDS_THETAPHASELOCKINGPFCRIPPLESSHIFTERS Theta phase locking around PFC ripple chains.
% jds_thetaPhaseLockingPFCRipplesShifters(animalprefixlist) measures CA1
% cell spike phase locking to theta within +/-2 s of REM cortical
% ripple-chain midpoi... |
a10512d91c149b69903bc9ba9efafdfb13ddd8f1b38aeeac578f23089d18e08d | MATLAB | 9,424 | 225 | function BCCT_ShowFCmatrixGUI_GCA
Hsize = get(0,'screensize');
MIDPOINT = [Hsize(3)/2,Hsize(4)/2];
Asize = [100*3,100+40];
MaxSIZE = [Hsize(3) Hsize(4)]*0.4;
factor = MaxSIZE./Asize;
factornew = min(factor);
POSSIZE = Asize*factornew;
Hshow.fig = figure('position',[MIDPOINT(1)-POSSIZE(1)/2,MIDPOINT(2)-POSSIZE(2)/2,POSS... |
abe4595c07f7f7793aec6215663a2d9a358da0237b248e19f1596a06e02aff65 | MATLAB | 9,452 | 243 | function BCCT_MOD_Surf_compute_freesurfer(Parameter)
mfilenam = which('BCCT.m');
[pat nam ext] = fileparts(mfilenam);
Outputdir = Parameter.Outdir;
Indir = Parameter.Indir;
marker = Parameter.markerdir;
Marker = {marker,['r',marker(2:end)]};
FSlab = Parameter.FSlabs;
if FSlab(1)
FStype = 'fsaverage';
el... |
3d0086617da40ebab2c496fe2e9bdbe9fc6b68d01d6e4d383de17786c439b5c9 | MATLAB | 9,485 | 226 | function shape_classification_plot(data)
clf(figure())
set(gcf,'name','Shape Classification','NumberTitle','off','color','w','units','normalized','position',[0.3 0.2 0.4 0.6],'menubar','none','toolbar','none')
file_menu = uimenu('Text','File');
uimenu(file_menu,'Text','Send Data to Workspace','Callback',@send_dat... |
d42ed8e7335260f511c09e70de2c16ec9ec02d557bf2286ca2d282bb51e687b6 | MATLAB | 9,497 | 227 | % internal function
% - Jimmy Shen (jimmy@rotman-baycrest.on.ca)
function save_nii_hdr(hdr, fid)
if ~exist('hdr','var') | ~exist('fid','var')
error('Usage: save_nii_hdr(hdr, fid)');
end
if ~isequal(hdr.hk.sizeof_hdr,348),
error('hdr.hk.sizeof_hdr must be 348.');
end
... |
345f616e0ab6216f99c5f67cf56bf32dceb4c62b92570b72ad5d892bff2b44a2 | MATLAB | 9,514 | 261 |
%
% current working directory needs to be /path/to/scripts
mainpath = pwd;
addpath([mainpath filesep 'toolboxes' filesep 'fieldtrip'])
addpath([mainpath filesep 'toolboxes' filesep 'tc_functions'])
addpath([mainpath filesep 'scriptTemplates'])
ft_defaults
parameterSettings=tc_ws2struct('base','MaxVarSize',16484,'Excl... |
5c4efb670f9ec980f3f3b9b0b8723a0ba5bddac073bab093587c0e07f25b6f55 | MATLAB | 9,525 | 276 | %--------------------------------------------------------------------------
% Till Habersetzer, 15.07.2025
% Communication Acoustics, CvO University Oldenburg
% till.habersetzer@uol.de
%
% Description:
% Pre-processes OLSA sentence stimuli by computing their auditory
% envelopes. This script applies the same resam... |
aabebf4dbd05f78f7b9000460bd50956b88cf9eb1c0143e2cfdcc6187ada7c2e | MATLAB | 9,528 | 228 | function spt_parabolic_fit(data)
input_values = inputdlg({'percentage of data to fit:'},'',1,{'25'});
if isempty(input_values)==1
return
else
percentage=str2double(input_values{1});
for i=1:length(data)
[data{i}.a,data{i}.c,data{i}.r2] = msd_fit_parabolic_msd_inside(data{i}.msd,percentage... |
920fea7ec0a7ca6e9eb1047142c3fbcbfb6ff52c669cfbc5780ed5c6f1dddeaa | MATLAB | 9,553 | 214 | function colocalization_module()
figure()
set(gcf,'name','Colocalization Module','NumberTitle','off','color','k','units','normalized','position',[0.25 0.2 0.5 0.6],'menubar','none','toolbar','figure')
global data listbox
uicontrol('style','pushbutton','units','normalized','position',[0,0.95,0.2,0.05],'string','Set ... |
e3878a4327cab9e5e837bd257b9f6efdf017bbfc247cd926b5e81c2dbd3bf262 | MATLAB | 9,558 | 200 | function eps2pdf(source, dest, crop, append, gray, quality, gs_options)
%EPS2PDF Convert an eps file to pdf format using ghostscript
%
% Examples:
% eps2pdf source dest
% eps2pdf(source, dest, crop)
% eps2pdf(source, dest, crop, append)
% eps2pdf(source, dest, crop, append, gray)
% eps2pdf(source, de... |
35d447f8ee3197a4bc280566dc04871684ccd8dc144b09efac736a60ef2485a2 | MATLAB | 9,587 | 241 | function [FCpre,pred_data,Fcorr] = generate_fc(SC,beta,ED,pred_var,model,FC)
% GENERATE_FC Generation of synthetic functional connectivity matrices
%
% [FCpre,pred_data,Fcorr] = generate_fc(SC,beta,ED,{'SPLwei_log','SIwei_log'},FC)
% [FCpre,pred_data] = generate_fc(SC,beta,[],{'SPLwei_log','SIwei_log'})
%
% ... |
aa9d161481c965e27b24e4e7074204b0096ace9b5663faa9c11d7fe56123642d | MATLAB | 9,597 | 368 | function [Beta,res,Z] = fMRI_multitrial_GLMs(S);
% Matlab function to return single-trial Betas from GLM using LSA, LSS or L2-regularised LSA
% fit to fMRI timeseries from a scan x ROI data matrix, given onsets and durations of events
%
% rik.henson@mrc-cbu.cam.ac.uk, 2017 (see Abdulrahman & Henson, 2016, Neuroim... |
8d3a05de6fe88f902f8c290d1c5b70ac279863b46788d50698ce531ab0d56bee | MATLAB | 9,600 | 204 | function jds_detectPopulationSuppressionREM(animalprefixlist,area)
%JDS_DETECTPOPULATIONSUPPRESSIONREM Detect population-activity suppression events.
% jds_detectPopulationSuppressionREM(animalprefixlist,area) detects
% transient drops in smoothed, normalized population firing (z-scored,
% below threshold, 0.3-0.... |
21532cd1161632627bfb0e8f7bff18428abd16cf4f2868980f4daee78ff74cd7 | MATLAB | 9,613 | 207 | function [ data ] = ps_preparedata_spmobj_LBPD_D( S )
% It extracts data from SPM objects (in one or more datasets) in the
% requested time-range(s).
% It computes the source leakage correction (by orthogonalisation, removing
% zero-lag correlations) and calculates the envelope.
% Currently, it is designed to extract... |
926de06a8cced877a9e289c18bb2e3e28cb9f82c9ce065f594bfea71b6b9c5a5 | MATLAB | 9,631 | 209 | classdef FilterTableTest < matlab.unittest.TestCase
properties
acq_table
end
methods(TestMethodSetup)
function setup(testCase)
s_table(1).subject_id = 1;
s_table(1).period = 'pre';
s_table(1).acq_date = '2017/05/23';
s_table(1).age = ... |
aa8f52e2865043d1827bfa8aa0e96b3c4ca27699d694b331b06deeec2ee9b4bf | MATLAB | 9,641 | 244 | %jds_sleepStateRipplePrediction
%Decodes ripple type (REM vs noncoordinated NREM cortical ripple) from
%CA1 per-ripple spike-count vectors with a linear classifier (10-fold
%cross validation, repeated over 10 random ripple-count-matched splits),
%against a row-shuffled control. Reports accuracy, precision, recall,
%and... |
4c830f96c20715a583ddd07e0ef5818b08fcf54bdbcb2fb5240134dc9ee267e9 | MATLAB | 9,665 | 265 | %% cue-locked
%% step 1: source estimation: ERP-based source activity (to ft)
clear all; close all; clc
dbstop if error
% Add FieldTrip path
addpath('D:\MATLAB oolbox\fieldtrip-20211209\fieldtrip-20211209'); % Make sure the path is correct
ft_defaults;
% Set data path
path = 'G:\MT\reference\rename\cue_epoch\out_p... |
343d64dfc4e8c46da12dfd8967f23b830401e5e69ab4538a7ad654ed22adb802 | MATLAB | 9,667 | 279 | % SFig 2A (activation density vs distance from stim site at 4 uA)
% Build weekDensityData from populationDistances
dDiv = 7; % days per week
targetCurrents = [4,5];
C = numel(targetCurrents);
min_neurons = 1;
num_shells = 20;
shell_width = 0.05; % mm (50 µm)
num_shells = 8;
shell_width = 0.1; % mm (100 ... |
f0de5ec7eef43af9666ea388d38d3e0142f984a560f8e5f3d74512881fdf2517 | MATLAB | 9,690 | 286 | % Save NIFTI dataset. Support both *.nii and *.hdr/*.img file extension.
% If file extension is not provided, *.hdr/*.img will be used as default.
%
% Usage: save_nii(nii, filename, [old_RGB])
%
% nii.hdr - struct with NIFTI header fields (from load_nii.m or make_nii.m)
%
% nii.img - 3D (or 4D) matrix o... |
15c09f3df400784fd8e47e661eab2c8c0efc5b791bcb7e3cb37b647b02b4e908 | MATLAB | 9,732 | 204 | function jds_rippleTriggeredAssemblyStrengthREMxVal(animalprefixlist,area,state)
%JDS_RIPPLETRIGGEREDASSEMBLYSTRENGTHREMXVAL Cross-validated assembly sequence around ripple chains.
% jds_rippleTriggeredAssemblyStrengthREMxVal(animalprefixlist,area,state)
% randomly splits REM ripple-chain onsets into two halves, al... |
c3b06991063b05f1442979a7071021fce114da51d192d792079dd58d18448540 | MATLAB | 9,753 | 275 | function freezeColors(varargin)
% freezeColors Lock colors of plot, enabling multiple colormaps per figure. (v2.3)
%
% Problem: There is only one colormap per figure. This function provides
% an easy solution when plots using different colomaps are desired
% in the same figure.
%
% freezeColors freeze... |
d82570dc5a840b4c9af4302787c13dc18670c969bdee3ed5f18ef8845d10dfea | MATLAB | 9,772 | 322 | %ARDEM Demonstrates modules of the ARfit package.
% Revised: 30-Dec-99 Tapio Schneider
% 01-Dec-10 (added example with multiple realizations)
format short
format compact
echo on
clc
% ARfit is a collection of Matlab modules for the modeling of
% multivariate time series with autoregressive (AR) mode... |
b82f4fe9562b82fcc1fc1fd13368a4df1383499e85b148ce551d754ba436a836 | MATLAB | 9,815 | 206 | function [ ] = GT_modul_plot_LBPD( S )
% It plots intra and inter subnetworks connectivity (after finding ideal
% subnetworks; e.g. using modularity algorithms).
% INPUT: -S.intra_con: 1 for connectivity intra subnetwork; 0 otherwise
% -S.inter_con: 1 for connectivity inter subnetwork... |
0d2ff850aa68530ce66376df9c7b01d53468aa893afd95d4529e40279350ce17 | MATLAB | 9,824 | 255 | classdef SandwichEstimator < nla.edge.BaseTest
%SANDWICHESTIMATOR Summary of this class goes here
% Detailed explanation goes here
properties
name = "Sandwich Estimator"
coeff_name = 'SwE Contrast T-value'
end
properties
% test specific properties go here (things that ... |
5dc4024f1fd0ad1c2a5cd61a15886e5b5e4257dd9a5a19d41ff25511c3971e0a | MATLAB | 9,864 | 218 | function [ ] = sources_3D_plot_LBPD( S )
% Plotting in 3D space neural signal over MEG sensors and in brain sources.
% If you do not provide information about the head model and MEG sensors
% position, previously computed structural/topologic data will be shown.
% For now, the function works in 8mm MNI152-T1 space, b... |
802d0da12fa609e3c423bfcfca9a271bc4f24d6a85c936a2032e5f68d0502a73 | MATLAB | 9,870 | 237 | function stat = pl_permtestcluster(data, varargin)
%
% Performs cluster-size statistical inference on 'data' for difference against 0.
% For a difference against any mean value m, use input data - m.
%
% Data from each observation are randomly multiplied by +-1 to create permutation samples.
% Statistical maps ... |
ba09c5fafe4ce4f17c8eb0354e77e152443d1b54e57f0f15b9e4b36c92591ff8 | MATLAB | 9,905 | 274 | function [result, problem] = optimize(varargin)
% Script that optimizes an MR gradient waveform subject to a number of constraints.
% In particular it maximizes the b-value of a diffusion encoding
% pulse sequence subject to constraints on power, maximum gradient and maximum slew rate.
%
% If you use this in your resea... |
24cdd18a4eeeafe92287caae6bdc1762c8dbb5e79ba3581048a24855120a7928 | MATLAB | 9,920 | 259 | function jds_thetaPhaseShiftersREM(animalprefixlist)
%JDS_THETAPHASESHIFTERSREM Classify CA1 cells as REM theta-phase shifters.
% jds_thetaPhaseShiftersREM(animalprefixlist) computes each CA1 cell's
% preferred theta phase during run (theta periods) and during REM, and
% classifies cells whose preferred phase shi... |
20bbc89e361d601437e952523624f814773fcf6daca9ad94bff095f3ccc69ec5 | MATLAB | 9,941 | 346 | function slm = SurfStatLinMod( Y, M, surf, niter, thetalim, drlim );
%Fits linear mixed effects models to surface data and estimates resels.
%
% Usage: slm = SurfStatLinMod( Y, M [,surf [,niter [,thetalim [,drlim]]]]);
%
% Y = n x v or n x v x k matrix of surface data, v=#vertices;
% n=#observ... |
8f4f4c22eb8a8c79c6b0f3484a723aadca3d8fc87a4dc77a864bc8b48ff14f7c | MATLAB | 9,971 | 212 | function [] = waveform_plotting_local_v2(S)
% It plots waveform for multiple conditions (one group of participants).
% Typically used for plotting time series of MEG channel/source, locally.
% INPUTS:
% -S.data: Data that you want to plot
% ROIs (s... |
14716ea7a477ddd65fd8caf1c9bca88f3f00540e2cbac53d0e1104fdbf17d907 | MATLAB | 10,009 | 256 | function preprocessing_audiobooks(settings)
%--------------------------------------------------------------------------
% Till Habersetzer, 05.07.2025
% Communication Acoustics, CvO University Oldenburg
% till.habersetzer@uol.de
%
% Description:
% Prepares audiobook stimuli for a neural decoding analysis by converti... |
b6673b367de074bdb3f24d667890c5bbb7ec58c4781db744e870ee42ed6d3da9 | MATLAB | 10,017 | 327 | function BCCT_ShowGCMap_GUI_coef
D.fig = figure('Name','Showing Coef-based GCA maps',...
'units','normalized',...
'menubar','none',...
'numbertitle','off',...
'color',[0.95 0.95 0.95],...
'position',[0.2 0.3 0.6 0.4]);
movegui(D.fig,'center');
dires = which('BCCT_Show... |
fbdf258c945f755e4a2c8e661b14a57a3c13d4acb8082508b43a4070e6a420f5 | MATLAB | 10,032 | 226 | % .HACKED, some minor modifications by PKR, UPENN, September 2018
% Function that iteratively identifies thresholds for Voronoi Areas given
% an input of Voronoi areas from data and from a Monte Carlo simulation
%
% input is intended to be the output from the associated function:
% VoronoiMonteCarlo_JO.m
%
%... |
8b188c9e639610b35f866e7b2f0a74f6b0336f72f21ddaa321ec5480a788a9a4 | MATLAB | 10,085 | 335 | function BCCT_ShowGCMap_GUI_res
D.fig = figure('Name','Showing Res-based GCA maps',...
'units','normalized',...
'menubar','none',...
'numbertitle','off',...
'color',[0.95 0.95 0.95],...
'position',[0.2 0.3 0.6 0.4]);
movegui(D.fig,'center');
dires = which('BCCT_ShowGC... |
c8a699c59884b1470760177be82e3442057884ef260d3fbfe150718c5da777e6 | MATLAB | 10,097 | 266 | function varargout = process_nst_dOD( varargin )
% @=============================================================================
% This software is part of the Brainstorm software:
% http://neuroimage.usc.edu/brainstorm
%
% Copyright (c)2000-2013 Brainstorm by the University of Southern California
% This software is... |
b5ce20593c9a641d5b3d4a1a4ca59228ae62e49ff34dc26e99cdefd2676f6408 | MATLAB | 10,138 | 321 | % The basic application of the 'reslice_nii.m' program is to perform
% any 3D affine transform defined by a NIfTI format image.
%
% In addition, the 'reslice_nii.m' program can also be applied to
% generate an isotropic image from either a NIfTI format image or
% an ANALYZE format image.
%
% The resliced N... |
831617545ef88f8fe5c8a63f86ffed36f28f2c1507cc121bb890608d9882272a | MATLAB | 10,148 | 279 | %%
% current working directory needs to be /path/to/scripts
mainpath= pwd;
addpath([mainpath filesep 'toolboxes' filesep 'tc_functions'])
addpath([mainpath filesep 'fmriRegAnalysis'])
addpath([mainpath filesep 'toolboxes' filesep 'fieldtrip'])
addpath([mainpath filesep 'toolboxes' filesep 'OpenFmriAnalysis'])
tvm_inst... |
143b558a12e7c06ebda4c046e5cf09274a1fcd5166501bd8f1bd8dc859938ec3 | MATLAB | 10,174 | 255 | function defaults = tc_make_reg_analysis_defaults(mainpath, subject, varargin)
%% defaults = tc_make_reg_analysis_defaults(mainpath, subject, dir_for_computation)
%
% creates default parameter set for EEG-fMRI regression analysis
basic_only = false;
if ~isempty(varargin)
dir_for_computation = {1};
if length(var... |
67d326bfd06b499a3666013f2dfa4336bdc166e17e4d7c217a727af0a6e15fa4 | MATLAB | 10,189 | 326 | % RUN_SPATIAL_SPIN_CORRELATION_TEST
%
% This script tests spatial correlations between parcel-wise
% structure-function coupling (SFC) and cortical maps while accounting for
% spatial autocorrelation using spin permutations.
%
% The script was written for surface-based cortical data with separate left
% and right hemis... |
0adc1ff3da2e1640802ada03734aa7a550480abb9cd4f13479a6fbc1abf4fddf | MATLAB | 10,209 | 249 | function stat = pl_permtestcluster2(data1, data2, varargin)
%
% Performs 2-sample cluster-size statistical inference on 'data1' and 'data2' for difference against 0.
% For a difference against any mean value m, use input data - m.
%
%
% stat = pl_permclustertest2(data1,data2) uses default values
%
% stat = ... |
498e734d7d691902ae363ebb0c6f1a86c0b3b28fd854063a881863808c226ec2 | MATLAB | 10,242 | 280 | % internal function
% - Jimmy Shen (jimmy@rotman-baycrest.on.ca)
function [hdr, filetype, fileprefix, machine] = load_nii_hdr(fileprefix)
if ~exist('fileprefix','var'),
error('Usage: [hdr, filetype, fileprefix, machine] = load_nii_hdr(filename)');
end
machine = 'ieee-le';
new_ext = 0;... |
77993efbb572cb36320aa3c5858a50ca29e066be0437c7e10d113e1b7efb77eb | MATLAB | 10,311 | 280 | % internal function
% - Jimmy Shen (jimmy@rotman-baycrest.on.ca)
function [hdr, filetype, fileprefix, machine] = load_nii_hdr(fileprefix)
if ~exist('fileprefix','var'),
error('Usage: [hdr, filetype, fileprefix, machine] = load_nii_hdr(filename)');
end
machine = 'ieee-le';
new_ext = 0;... |
145f40d9b431e48c724fc0436c52d3b6a09aef99cfcabb0adc6dce606ae2b0b3 | MATLAB | 10,354 | 296 | function dFC_project = compute_variability(dFC_project)
method_choices = {
'Zhang et al. Formula'
'Standard deviation'
};
if ~isfield(dFC_project,'var_method')
[method,tf] = listdlg('SelectionMode','single','ListString',method_choices);
if tf==0
method=1;
end
else
me... |
94576473ff3c0ae14d6556fa5ee81d6ae66fc095d42e0d17325701be99838b2e | MATLAB | 10,357 | 268 | function [data_path,movement_par,varargout] = Realign_func(functional4D,pre_proc,all_slices,aux_folder)
if strcmp(pre_proc,'none')
data_path = functional4D;
movement_par = [];
if nargout > 2
varargout{1} = [];
end
return;
end
% if realigned functional data already exist, check realignmen... |
3eae7e76dfe5252f7c3d1d07d812968d2b4d7fc056f65595aa2dc226bc803103 | MATLAB | 10,457 | 246 | function image_plot(data)
figure()
set(gcf,'name','Image Toolbox','NumberTitle','off','color','w','units','normalized','position',[0.35 0.25 0.4 0.6],'menubar','none','toolbar','figure')
if length(data)>1
slider_step=[1/(length(data)-1),1/(length(data)-1)];
slider_one = uicontrol('style','slider','un... |
aed793db0a44d11fe5abec69f348c3eecc1b548492382d536b6627a997b8fd5e | MATLAB | 10,461 | 385 | function varargout = boundedline(varargin)
%BOUNDEDLINE Plot a line with shaded error/confidence bounds
%
% [hl, hp] = boundedline(x, y, b)
% [hl, hp] = boundedline(x, y, b, linespec)
% [hl, hp] = boundedline(x1, y1, b1, linespec1, x2, y2, b2, linespec2)
% [hl, hp] = boundedline(..., 'alpha')
% [hl, hp] = boundedline(... |
4651b5579eb9972a83e9334069cb579e4d7a4398904d8fe27af9c6a80c2424ea | MATLAB | 10,477 | 261 | function [A, bcol] = print2array(fig, res, renderer, gs_options)
%PRINT2ARRAY Exports a figure to an image array
%
% Examples:
% A = print2array
% A = print2array(figure_handle)
% A = print2array(figure_handle, resolution)
% A = print2array(figure_handle, resolution, renderer)
% A = print2array(figur... |
9c07ac0784ddbe236e18b061f2e8151c158f1966d9733c28e5798fb82b7b7bf0 | MATLAB | 10,508 | 175 | classdef NetworkResultPlotParameterTestCase < matlab.unittest.TestCase
properties
root_path
network_atlas
edge_test_options
network_test_options
edge_test_result
network_test_result
permutation_results
tests
end
methods (TestMethodSetup)
... |
095d48f862cab1ad31101afc8a15a6bf60da2851d97ed0cdcc2647da9d2bcf76 | MATLAB | 10,526 | 283 | function [ARA_table,tableRowInds] = getAllenStructureList(varargin)
% Download the list of adult mouse structures from the Allen API.
%
% function ARA_table = getAllenStructureList('param1',val1,...)
%
%
% Purpose
% Make an API query to read in the Allen Reference Atlas (ARA) brain area
% list. All areas and d... |
6b488c09fe942eef4775b0b0e88f37c5d1fc6870a12224a8cf28420d313da8a1 | MATLAB | 10,530 | 215 | function h = schemaball_modularity_LBPD(r, lbls, modul, COL, perc_intra, perc_inter, limitt)
% Plots modularity of graphs (such as brain networks) in schemaball.
% This work is based on the brilliant function "schemaball" created by Oleg
% Komarov (oleg.komarov@hotmail.it), even though the codes here have been
% ... |
dc6c4c80d8d0f1078275960204515c5bf9858c3df7c3bb4600b7f897805903c1 | MATLAB | 10,569 | 199 | function O = InducedResponses_Morlet_Coords_AALROIs_LBPD_D( S )
O = [];
% It computes time-frequency analysis (induced responses) using Morlet
% wavelet.
% It computes Morlet wavelet transform independently on each voxel and each
% trial of the provided data. Then, it averages the results over voxels and trials.
% It... |
09b50b2c0f66288ddd3be1fc23ac980af7200ca459a445b1551f6cf036a765e8 | MATLAB | 10,576 | 236 | %% ============================================================
% Combined Motivational Go/NoGo Task Behaviour (HC & OCD)
% [Final Adjustment: Vertical Gap Increased by 2mm]
% - Layout: 50mm width per panel, 2 rows (HC/OCD)
% - Vertical Gap: Increased from 3.2 to 3.4 cm (+2mm)
% - Figure Height: Increased from 13.... |
55855f59cfa4c0fe8e04c2c7864fbc32b26ad5b235a8c625fe8bcce0117241d6 | MATLAB | 10,578 | 263 | %% Plot and count Fig 3 J, L, M, N
% Requires fig3_final_results or fig3def_plot_data loaded
if ~exist('DATA_ROOT','var'), run(fullfile(pwd, 'matlab', 'config.m')); end
if ~exist('mergedDFF', 'var')
load(fullfile(DATA_ROOT, 'fig3def_plot_data.mat'));
end
subset_idx = subsetMerged == 1;
remaining_idx = subsetMerge... |
9ed30bcfdae057a2c4c6f3fbf98886ccc78da062bda6a34ce5d36be12f49bc3d | MATLAB | 10,608 | 263 | function AS_WTA_MapShow
[pat nam ext] = fileparts(which('AS_WTA_MapShow.m'));
backgroundmap = fullfile(pat,'mni_icbm152_t1_tal_nlin_asym_09a.nii');
indir = uigetdir(pwd,'Result of WTA');
outdir = uigetdir(pwd,'Pic Out Dir');
[vbg dbg] = Dynamic_read_dir_NIFTI(backgroundmap);
dbgre = reshape(dbg,vbg.dim(1),vbg.dim... |
8d378f27752998e771dbad73bb5055cfcef9645f14ed15df4a64e2f520bfc81f | MATLAB | 10,650 | 301 | %jds_rippleBurstingREM
%Bursting probability and first-spike latency of CA1 theta-phase shifter
%vs nonshifter cells within isolated (non-chain) REM cortical ripples.
%Compares the two groups (rank-sum, bar/boxplots) and relates bursting and
%latency to phase-shift magnitude by quartile.
clear all;
close all;
animalpr... |
f3a6beb38a834175a86fcd5d9e1a08df84c7a33ff42b41b989d586ec63b9b810 | MATLAB | 10,663 | 239 | function data = spt_plot(data)
for i = 1:length(data)
if isfield(data{i},'msd') ~= 1
f = waitbar(0,'calculating msd');
for j = 1:length(data{i}.tracks)
waitbar(j/length(data{i}.tracks),f,['calculating msd ',num2str(j),'/',num2str(length(data{i}.tracks))]);
if size(dat... |
a85f4e7e9eb282ab331e2e5de23185d6b61a2931edfb8ccf2f940d28989cd5d2 | MATLAB | 10,739 | 312 | function jds_CA1PFCRippleCoactivityREMDeltaFR(animalprefixlist)
%JDS_CA1PFCRIPPLECOACTIVITYREMDELTAFR CA1 firing-rate change vs REM ripple cofiring.
% jds_CA1PFCRippleCoactivityREMDeltaFR(animalprefixlist) computes each CA1
% cell's mean z-scored cofiring with PFC cells in REM chain cortical
% ripples, along with... |
01ae88dac9d0c54f1233df8a0b2876ee75c00bfae2dd7db71ca03b5ad165107b | MATLAB | 10,882 | 208 | function [ PP ] = BrainSources_MonteCarlosim_3D_LBPD_D( S )
% It identifies 3D spatial clusters (by using islands3D_LBPD_D.m) on a binarized
% 3D matrix and then computes Monte Carlo simulation for testing the significance of the
% clusters in the original data. The clusters always refer to only one direction of the
%... |
0d5b6cade09eae58c0a0368c1b68a13ff11f4dea204c68a8b8d6a9583045993a | MATLAB | 10,941 | 309 | function SurfStatView1(struct, surf, varargin );
%Viewer for surface and/or volume data or P-value or Q-value structures.
%
% Usage: SurfStatView( struct, surf, ... );
%
% struct = 1 x v vector of data, v=#vertices,
% or one of the following structures:
% P-value structure:
% struct.P... |
54eae374d923ae77fd42a243ca4ff0ba8d7f62af252db31cae3069907ecdde59 | MATLAB | 11,015 | 299 | function Plot_C_summary(data_dir,save_dir,selectedK,centroid,parcellation)
%
% Plot the centroids in 3D glass brain, in vector format and the boxplots
% of the fractional occupancy and dwell time value
%
% INPUT:
% data_dir directory where LEiDA results are stored
% save_dir directory to save results for sele... |
a2fff3b41c891deda8ce85d707ef72c8782711a1144eecefaf23dae9f9799353 | MATLAB | 11,015 | 285 | %jds_phaseAmpCouplingREMShuffle
%Shuffle control for jds_phaseAmpCouplingREM: computes the theta-phase to
%gamma/ripple-amplitude comodulogram during phasic REM alongside a
%circular-shift shuffle of the phase/amplitude time series, and compares
%real vs shuffled modulation indices for gamma and ripple bands.
animalpr... |
efd5c5b9f010a3ffff66f604e8a3980297c3898fbd853fa05b38ea3ecdc9d12f | MATLAB | 11,071 | 315 | function dFC_project = compute_TF_comm_struct_v4(dFC_project, condition)
% condition = 1;
nsub = size(dFC_project.dFC,5);
% nsub = 1;
TF = zeros(nsub,1);
mean_duration = zeros(nsub,1);
time_in_state = zeros(nsub,1);
mean_in_state_dFC = zeros(nsub,1);
mean_out_of_state_dFC = zeros(nsub,1);
mean_dFC = ze... |
8f184f4d69ef4dad3d82bccfe2187dadf823290b0a5c39034c082248cacccbcf | MATLAB | 11,076 | 208 | function [cfg] = ft_topoplotER(cfg, varargin)
% FT_TOPOPLOTER plots the topographic distribution over the head
% of a 2-dimensional data representations such as the event-related
% fields or potentials or the power- or coherence spectrum.
%
% Use as
% ft_topoplotER(cfg, timelock)
% or
% ft_topoplotER(cfg, freq)
%
... |
f5b76dc69abcd339941bf54bb2ec4cad50b016a56d73fe179a9ed0b5d1144efa | MATLAB | 11,080 | 268 | function AS_WTA_MapShow_inFun(inmixdir,outdir,extendfactor1,extendfactor2,extendfactor3)
[pat nam ext] = fileparts(which('AS_WTA_MapShow.m'));
backgroundmap = fullfile(pat,'mni_icbm152_t1_tal_nlin_asym_09a.nii');
% indir = uigetdir(pwd,'Result of WTA');
% outdir = uigetdir(pwd,'Pic Out Dir');
[vbg dbg] = Dynamic_r... |
045c0ea1342e7d4b7090b0ef4fe241af64a24077bf155538eccb77e82b549f0e | MATLAB | 11,112 | 389 | function [actmap,aoff]=activationmapoff(pix,framerate,images,mask,velalgo,before,tfilt,usespline,splineN,repolap,inoff);
% Function for creating activation map from an image stack.
% This version also outputs the offset
% Chris O'Shea and Ting Yue Yu, University of Birmingham
% Maintained by Chris O'Shea - Email... |
b42cf333bfb9a8e58e059455419d87abfdb07bbbefc2db1b191f9e0c1f9eff81 | MATLAB | 11,121 | 258 | function Plot_DwellTime(data_dir)
%
% Plot the results from the hypothesis tests obtained from comparing the
% mean dwell time between conditions
%
% INPUT:
% data_dir directory where the results from running the hypothesis
% tests on the dwell time of PL states
%
% OUTPUT:
% Fig1 plot of th... |
d892d90376fe86a4aac58149552635b82091aceeaa55e4944ca5910fd88e5b15 | MATLAB | 11,176 | 294 |
% calculate trace means and stds
% TODO - report baseline trace means over each session, i.e. see if there is a drifting baseline in each session or for each roi
allROI2Comp = cell(3,1);
allDays = cell(3,1);
for animal = 1:3
if(animal==1)
icms = 'ICMS92';
files2Load = {'Z:\xl_stimulation\ICM... |
fe5e27bd22666a70a8f75a2e62e93a0ca21f142b91cc160067a1bb5caa3dea7e | MATLAB | 11,176 | 238 | function [ ] = MEG_sensors_MCS_plottingclusters_LBPD_D( S )
% It plots topoplots for gradiometers and magnetometers clusters (given the
% cluster ID that you want to plot).
% Magnetometers positive and negative are plotted together, assuming that
% user is providing cluster IDs that are compatible. In other words,
% ... |
cd7d8f20af4d221417bc0babe59b7ea70435cd28cbde9d940f24f50c792068f0 | MATLAB | 11,177 | 226 | function shape_classification_ellipses_plot(data)
number_of_classes = size(data.classes,1);
answer = inputdlg({'Classes to Plot:','Radius of Ellipses:','Scatter Clusters in Class (1 or 0):','Show Error Bar (0 or1):','Show Data Table (0 or 1):','Weight for Total Number of Clusters (0 or 1):'},'Input',[1 50],{['1:',num... |
3ace22db7a70786daf433a9ee9741e49f3fb01ff60333c2ec542ad3e4d5c7f0d | MATLAB | 11,196 | 308 | function preprocessing_crosscorr(subject,settings)
%--------------------------------------------------------------------------
% Till Habersetzer, 05.07.2025
% Communication Acoustics, CvO University Oldenburg
% till.habersetzer@uol.de
%
% Description:
% Performs subject-level preprocessing for a cross-correlation a... |
b604d64b505811e2250208f3c967d10541fa3fd7dd9433acc57416a5de80fe74 | MATLAB | 11,210 | 338 | function [model,code,message] = nst_glm_add_regressors(model,Regressor_type,varargin)
% Call exemple
% model = add_regressors(Model, "event", Events, basis_choice, hrf_duration)
% model = add_regressors(Model, "external_input", external_input)
% model = add_regressors(Model, "channel",sFile,criteria,params,types)
% mo... |
fa829e0e4b8cd3b1a28b043f538d16fbb78d4eb8da910a725b3af4993ca29abc | MATLAB | 11,222 | 258 | function Plot_FracOccup(data_dir)
%
% Plot the results from the hypothesis tests obtained from comparing the
% mean fractional occupancy between conditions
%
% INPUT:
% data_dir directory with the results from running the hypothesis
% tests on the mean fractional occupancy of PL states
%
% OUTPUT:
% ... |
3abfcde12bf61dc53795a4939ce03332554183c2e50aa9b4f4e6fa41c4dab64f | MATLAB | 11,251 | 233 | function loc_list_clusters_remove_outliers_updated(data)
%-------------------------------------------------------------------------
f = waitbar(0,'Exracting Clusters from Image(s)...');
for k = 1:length(data)
clusters{k} = loc_list_extract_clusters_from_data(data{k});
names{k} = data{k}.name;
waitbar... |
1e51886749cd92a763bb33d470d35d50ad6f5be935ff5c3f8db7511771b8ffa4 | MATLAB | 11,289 | 268 | function AS_WTA_MapShow_inFunZspec(inmixdir,outdir,width,lenth)
[pat nam ext] = fileparts(which('AS_WTA_MapShow.m'));
backgroundmap = fullfile(pat,'mni_icbm152_t1_tal_nlin_asym_09a.nii');
% indir = uigetdir(pwd,'Result of WTA');
% outdir = uigetdir(pwd,'Pic Out Dir');
[vbg dbg] = Dynamic_read_dir_NIFTI(backgroundm... |
d5f5e0b01bda98191665176ebd16a33ed00dbe2a744bbaca9db332498d938ed9 | MATLAB | 11,307 | 223 | function AS_WTA_Stat_main(Parameter)
% Face a problem for the number of connects
% In later version, we would like to deal with it for the small ROM
% computer.
Outdir = Parameter.Outdir;
Indir1 = Parameter.Input1;
Indir2 = Parameter.Input2;
Incalmat1 = load(fullfile(Indir1,'SetUpparameter.mat'));
Incalmat2 = ... |
c870e19a57ef12452ed4200af275c13a53010a18017e00090de5e5e10e8e7eeb | MATLAB | 11,318 | 268 | function AS_WTA_MapShow_inFunX(inmixdir,outdir,extendfactor1)
[pat nam ext] = fileparts(which('AS_WTA_MapShow.m'));
backgroundmap = fullfile(pat,'mni_icbm152_t1_tal_nlin_asym_09a.nii');
% indir = uigetdir(pwd,'Result of WTA');
% outdir = uigetdir(pwd,'Pic Out Dir');
[vbg dbg] = Dynamic_read_dir_NIFTI(backgroundmap... |
a77bde8289e2c1f325f3dd72e5b11759840bcab859d7a685938df5c35ae118d1 | MATLAB | 11,319 | 268 | function AS_WTA_MapShow_inFunY(inmixdir,outdir,extendfactor2)
[pat nam ext] = fileparts(which('AS_WTA_MapShow.m'));
backgroundmap = fullfile(pat,'mni_icbm152_t1_tal_nlin_asym_09a.nii');
% indir = uigetdir(pwd,'Result of WTA');
% outdir = uigetdir(pwd,'Pic Out Dir');
[vbg dbg] = Dynamic_read_dir_NIFTI(backgroundmap... |
9b858039eb85135441b8385954224d8df623822e6c638ae1b1c1e48d18a04234 | MATLAB | 11,342 | 345 | function [y,index_ab_unique]=abnorm_detect(x1,label_index,detect_label)
% detect_label=1 3sigma detect_label=2 ËÄ·Öλ detect_label=3 zscore
% detect_label=4 ¹ÂÁ¢ÉÁÖ
rng(1)
x=zscore(x1); %¶¼ÏȽøÐбê×¼»¯´¦Àí
if detect_label==1
figure
index_ab_all=[];
for i=1:size(x,2)
x_mean=mean(x(:,i));
x_std=s... |
10dd978e9e6e4149219cea43ed48ce8134663b320268fcee6b1fbb18f869c297 | MATLAB | 11,345 | 268 | function AS_WTA_MapShow_inFunZ(inmixdir,outdir,extendfactor1,extendfactor2,extendfactor3)
[pat nam ext] = fileparts(which('AS_WTA_MapShow.m'));
backgroundmap = fullfile(pat,'mni_icbm152_t1_tal_nlin_asym_09a.nii');
% indir = uigetdir(pwd,'Result of WTA');
% outdir = uigetdir(pwd,'Pic Out Dir');
[vbg dbg] = Dynamic_... |
87a11f362d7e14828638527459ce77b899028fb683d2c64f56665e1c2895c94d | MATLAB | 11,351 | 255 | % Load source EEG data and convert to BIDS format
%
% Project: Song Familiarity
% Other m-files required: EEGLAB with bids-matlab-tools extensions
% bids-matlab toolbox (https://github.com/bids-standard/bids-matlab)
% Other files required: dmlab32.locs
% Author: Cameron Hassall, Department of Psychology, MacEwan Unive... |
2f1e7a0cc94b228a4a3d2c587e997afcfb877f138c9e747efa2786d75a045f79 | MATLAB | 11,357 | 368 | %% Relation midfrontal theta power and Pavlovian-Instrumental conflict (FINAL)
clear; clc; close all;
% =============================
% 0) Global style (Arial 9pt, no bold)
% =============================
set(groot, 'defaultAxesFontName', 'Arial');
set(groot, 'defaultTextFontName', 'Arial');
set(groot, 'defaultAxe... |
d7bf5f9b85621aaadfa38708916c6301413e370db8fdd77b4fb75b30607dc430 | MATLAB | 11,358 | 345 |
function [apd,tau,DI,ttp,maxvelup] = segapd(apdopt,tauopt,DIopt,ttpopt,maxupvelopt,Fluo,framerate,f,before,after,tfilt,t,startopt,apdblopt,apdblnum,tstar,tend);
% Function for doing analysis of paramaters measured in single file analysis GUI
% Chris O'Shea and Ting Yue Yu, University of Birmingham
% Maintained by... |
2ef5ded45a2a98a8cdfb65e85b2262e5ab2599f322df8e0d3ec878431749731d | MATLAB | 11,361 | 308 | function varargout = process_nst_wmne( varargin )
% @=============================================================================
% This software is part of the Brainstorm software:
% http://neuroimage.usc.edu/brainstorm
%
% Copyright (c)2000-2013 Brainstorm by the University of Southern California
% This software i... |
d684ed6503b63f89a51b073c58109a0e15921930e1abfbd8f95f8a6b48cf11af | MATLAB | 11,417 | 361 | function [X, SPM]=batch_spm_anova(S)
% A general function for N-way mixed (within+between subjects) ANOVAs in SPM5/SPM8
% (though assumes same number of conditions per group)
% R Henson Oct 2006
%
% The only required argument in S is:
% imgfiles ... |
bc2cee7667d9d086b16264d5cd06b3be3c00e9f13dfb6edc76f84a0c42832614 | MATLAB | 11,483 | 276 | function R_all_blocks = a_confound_and_task_regressors(parameters, delete_files)
%% R_out = a_confound_and_task_regressors(mainpath, subject, delete_files)
% mainpath = '/project/3018037.01/Experiment3.2_ERC/AnalysisFolder/scripts/scriptTemplates/..';
tc_struct2ws('caller', parameters.main);
%% setup parameters
tc_st... |
9da3ccda85a03f72250d2bd4bbac8f38938a62112319c7ba1fd8020629e96a34 | MATLAB | 11,494 | 314 | function preprocessing_audiobooks_decoding(subject,settings)
%--------------------------------------------------------------------------
% Till Habersetzer, 05.07.2025
% Communication Acoustics, CvO University Oldenburg
% till.habersetzer@uol.de
%
% Description:
% Performs subject-level preprocessing for a neural de... |
ab92db27fe6c34e2d318545220ea768660f07b881d84cdbc0add7d08a7a159d8 | MATLAB | 11,516 | 299 | %--------------------------------------------------------------------------
% Till Habersetzer, 23.06.2025
% Communication Acoustics, CvO University Oldenburg
% till.habersetzer@uol.de
%
% This script automates the creation and visual validation of individual
% headmodels and sourcemodels for MEG source analysis. It... |
6e669ba75e57ad78c264363cad5fb9863fbb9664c8c5084eea3d331fbdbddb0a | MATLAB | 11,558 | 317 | %--------------------------------------------------------------------------
% Till Habersetzer, 19.06.2025
% Communication Acoustics, CvO University Oldenburg
% till.habersetzer@uol.de
%
% This script performs a complete Auditory Evoked Field (AEF) analysis on
% MEG data using the FieldTrip toolbox. For a list of sub... |
edc90d0d23550075bdc917267cfe285c8db16803cd562575a37c5c23ca401e51 | MATLAB | 11,569 | 264 | function [ P_pos_fin, P_neg_fin, PM ] = diff_conditions_matr_couplingROIs_MCS_LBPD_D( a, b, ROI_lab, X, permut, threshMC, plot_label )
% It calculates the difference between two conditions of strength of the significant
% coupling between each couple of ROIs. Then, it calculates Monte Carlo
% simulations to assess the... |
30327b18f861bcbbf3d6079643f84f9a68955b4514ba02e99b1db3bf8c42bf4a | MATLAB | 11,640 | 374 | %% Overview
% The main goal of this pipeline is perform source estimation using the
% processed data from the main pipelines (OPM_CFA_correction_Pilot_study.m
% and Comparative_analysis_with_ICA.m need to have created the required
% data objects.
%% Parameter settings
spm_path = 'C:\Users\swoelk\Documents\MATLAB\spm\... |
7c8ebdb85eabbbf01ff7c05e9cc459ae59e2bbff2141afe4dd61b6012b300b44 | MATLAB | 11,683 | 261 | function drawChord(ax, ax_width, net_atlas, sig_mat, color_map, sig_type, chord_type, coeff_min, coeff_max, representative)
%DRAWCHORD display chord plot
% ax: axes to plot on, should be square
% ax_width: width (assumed to equal height) of axes
% net_atlas: respective NetworkAtlas object
% ... |
92664f79cf91bac15d0056496ed89dbbea1b3320fc8cea27b8a04c8427c177de | MATLAB | 11,713 | 297 | %% define parameter sets for analysis
if ~(exist('mainpath','var') && exist('thisSubject','var'))
clearvars
% current working directory needs to be /path/to/scripts
mainpath = pwd;
thisSubject = 'S1';
else
clearvars -except mainpath thisSubject
end
load([mainpath filesep '..' filesep 'subjectData' ... |
0347f1858aab74bd83516b10e2f993a67e015931a9cda3986eebc7769a837610 | MATLAB | 11,833 | 291 | % This script concatenates all the processed data contained in the
% allCTX and allCA1 mat files in Matlab arrays to make the plots of the
% individual statistics of the events (Fig. S1 in the manuscript) and the
% correlation curves of Fig. 3
% --- Load data --------------------------------------------------------... |
3482c5115eda0b660e9918bdcd9a18d8c3ad0e824d78fbd1023f2eb0a99c6910 | MATLAB | 11,844 | 327 | function varargout = process_nst_cmem( varargin )
% @=============================================================================
% This software is part of the Brainstorm software:
% http://neuroimage.usc.edu/brainstorm
%
% Copyright (c)2000-2013 Brainstorm by the University of Southern California
% This software i... |
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