sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
50a4ca170b677adc331cd7121754bd1dafd5946de0437b1f7cb05f60701a3dc3 | MATLAB | 15,601 | 520 | function M = fixedranktensorembeddedfactory(tensor_size, tensor_rank)
% Manifold of tensors with fixed multilinear rank in Tucker format
% as a submanifold of a Euclidean space.
%
% function M = fixedranktensorembeddedfactory(tensor_size, tensor_rank)
%
% NOTE: Tensor Toolbox version 2.6 or higher is required for this ... |
edc589dd63dcfc2353ebced94ef13a7b0a4935ea20786d21c012695493802ad9 | MATLAB | 15,612 | 335 | function files_out = bids_spreadsheet2participants(varargin)
% routine to takes an spreadsheet file (e.g. excel) as input and export as participants.tsv
% and participants.json
%
% FORMAT files_out = bids_spreadsheet2participants(file_in,'ignore','field1','filed2',...)
%
% INPUTS if empty user is prompted
% fi... |
0b5cc9ec726027723009cd313fa388802d65aa4c4c9549d8a64fd8b1de690cc1 | MATLAB | 15,630 | 342 | function TS_ClassifyLowDim(whatData,cfnParams,numPCs,doComputeAtMaxInSample)
% TS_ClassifyLowDim compare performance of reduced PCs from the data matrix
%-------------------------------------------------------------------------------
% 'whatData', HCTSA data file (or structure).
% 'cfnParams', parameters of the classif... |
8d254d18978df7b44861d8a553df78da51831b8a5ade490d4727308d8144a7c1 | MATLAB | 15,645 | 268 | function TOL_main
% TOL_main, main code for Duvelle and Grieves (2026)
% Code to plot figures for: Duvelle and Grieves (2026) Tolman's Sunburst Maze 80
% years on: A meta-analysis reveals poor replicability and little evidence for
% shortcutting. European Journal of Neuroscience. DOI:
% https://doi.org/10.1111/ejn.7... |
8afb7da3d69d345a6849aec5bb2f061125f9b534b39759c69a9ac54cb689555b | MATLAB | 15,646 | 570 | %% Part 1 : Single Neuron
close all
clear all
rng(1)
load('Z:\CLOOSE benchmark tests\Various_BCI_approaches\DF_062624_NDNF_07_000_009.mat');
load('Z:\BCI\Data\NDNF_Opto\NDNF_07\062624_NDNF_07\Baseline\baselineMask_2.mat')
load('Z:\CLOOSE benchmark tests\Various_BCI_approaches\ROIS_062624_NDNF_07_000_009.mat')
figure... |
1a7d4fbd2abb6ef842dde6e0f5def429679f372de67da7d67df2bec6e40555f5 | MATLAB | 15,655 | 391 | % STD_SPECGRAM - Returns the ICA component or channel spectrogram for a dataset.
% Saves the spectra in a file.
% Usage:
% >> [spec freqs] = std_specgram(EEG, 'key', 'val', ...);
%
% Inputs:
% EEG - a loaded epoched EEG dataset structure.
%
% Optional inputs:
% 'components' - [numeri... |
58d9fae950dab09531371d5466a9c2744ac08e22ea47588de6aa8e0f18c7097b | MATLAB | 15,662 | 352 | function outputFileName = TS_Normalize(normFunction,filterOptions,fileName_HCTSA,classVarFilter,keepCalcTime)
% TS_Normalize Trims and normalizes data from an hctsa analysis.
%
% Reads in data from HCTSA.mat, writes a trimmed, normalized version to HCTSA_N.mat
% For many normalization settings, each feature is normali... |
abe370a30cbbd8e2216dc02e1394f670e476abdaf1b1792372c1bc54e5773fb0 | MATLAB | 15,665 | 268 | function [cm_data]=magma(m)
cm = [[ 1.46159096e-03, 4.66127766e-04, 1.38655200e-02],
[ 2.25764007e-03, 1.29495431e-03, 1.83311461e-02],
[ 3.27943222e-03, 2.30452991e-03, 2.37083291e-02],
[ 4.51230222e-03, 3.49037666e-03, 2.99647059e-02],
[ 5.94976987e-03, 4.84285000e-03, 3.71296... |
9d6d82e54a8eb936cd183004e8a9de1684632b23394aa5aec2bd0cc3909aa303 | MATLAB | 15,667 | 389 | Skip to content
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Join GitHub today
GitHub is home to over 28 million developers working together to host and review code, manage projects, and... |
18e20b1a881386c7473f3f8b0f0b367d356e3a61ba61de0c6948490c88a2a622 | MATLAB | 15,668 | 271 | function [cm_data]=magma(m)
cm = [[ 1.46159096e-03, 4.66127766e-04, 1.38655200e-02],
[ 2.25764007e-03, 1.29495431e-03, 1.83311461e-02],
[ 3.27943222e-03, 2.30452991e-03, 2.37083291e-02],
[ 4.51230222e-03, 3.49037666e-03, 2.99647059e-02],
[ 5.94976987e-03, 4.84285000e-03, 3.7129... |
4781d926e89a18d422c80dc28219142a36d975e5e6f5c607c71bc0f9985823f5 | MATLAB | 15,687 | 129 | %EEGLAB group processing (STUDY) functions (studyfunc folder):
% <a href="matlab:helpwin compute_ersp_times">compute_ersp_times</a> - Computes the widest possible ERSP/ITC time window,...
% <a href="matlab:helpwin eeglabciplot">eeglabciplot</a> - Eeglabciplot(lower,upper)...
% <a href="matlab:helpwin extra... |
58a0caeecca5ad37ab5b33720dd90159db4da9cf0454385accdda6cb5fcbf800 | MATLAB | 15,692 | 346 | function runStimDetectionApp(MEANAPapp)
%RUNSTIMDETECTIONAPP Summary of this function goes here
% Detailed explanation goes here
% MEANAPapp : app object
% Main MEANAP application object, to sync settings / parameters across
% these two apps
stimDetectionAppObj = stimDetectionApp;
stimDetectionAppObj.UIFigure.Name ... |
f618520605de21e6b8fbee1c6c8642ed78519a8fb83e5e5977cc6aab9bf81569 | MATLAB | 15,692 | 341 | %% =====================================================================
% GROUP‑LEVEL ERP ANALYSIS & N1 EXTRACTION
% ---------------------------------------------------------------------
% Author : Suong Welp
% Date : 2025-07-24
% Loads all *_ERP.mat files created by preprocessing2ERP_final.m,
% build... |
d7029eee45f5ae34908bdce42b95912f1cffbfb40a742e48c7e420cf450c9751 | MATLAB | 15,696 | 503 | function coactPaper_figure05()
labelWeight=true;
labelCase=false;
labelSize=9;
letGapX=5;
letGapY=6;
fontsize=6;
close all
fh=initFig('width',18.6,'height',3,'font','Arial','fontsize',fontsize);
x=14;
y=6-4;
panel_01(x,y,fontsize)
panelLetter2(x-letGapX-6,y-letGapY+2+4,alphabet(1,labelCase),'fontSize',labelSize,'isB... |
7bb7bba7152e6e8e35d61d460fe20de7b42b03852d6b81ebe52832942aa41ec2 | MATLAB | 15,714 | 445 | %{
Once you have your results, time for plotting and making the graphs
look beautiful already in Matlab! Rather than prettifying your plots
in Illustrator, I highly recommend doing as much as possible already
in Matlab. Chances that you'll have to regenerate the figures at some
point (because you decide to change one s... |
2eebc56d7bbb3cdbbb2d1a93f62b4edb594119fe2f3791b135dc12b3def75430 | MATLAB | 15,723 | 396 | clear all; close all; clc;
warning('off');
% ---------------- I/O and paths ----------------
fullpath = mfilename('fullpath');
if isempty(fullpath)
fullpath = matlab.desktop.editor.getActiveFilename;
end
[scriptFolder, scriptName, ~] = fileparts(fullpath);
parentFolder = fileparts(scriptFolder);
dataPath = full... |
e43c9b1818ee86616ab1693c8cee7a3c406f239e38a25af958b74118fa99a8c0 | MATLAB | 15,725 | 318 | %% h = sepia_handle_panel_utility_get_header(hParent,hFig,h,position)
%
% Input
% --------------
% hParent : parent handle of this panel
% hFig : handle of the GUI
% h : global structure contains all handles
% position : position of this panel
%
% Output
% --------------
% h ... |
0f6ce1d43315d3b8cc999cdfa10be1217ecedc778570329a0a815ed66966a6cb | MATLAB | 15,732 | 302 | % SHOW FIGURES OF MAIN FMRI RESULTS AND CALCULATE EFFECT SIZES FROM BETAS
function master_fMRI_showResults
%
% js 2019-2024
% general settings
panLetterFontSize = 28;
sliceFontSize = 18;
labelFontSize = 16;
LMMcoeffBarColor = [.8 .8 .8];
tFlg = 0; % if 1, adds text title to panels
figName1 = 'Figure 4 - fMRIresults';
... |
0749ffe7fb2a5c3e44f7c73f3e83c0b2aa159bedb670cd50f10145e6b9b33fe0 | MATLAB | 15,733 | 344 | function fh = plot4D(this, varargin)
%plots an MR image per slice
%
% Y = MrImage
% fh = Y.plot4D('ParameterName', ParameterValue)
%
% IN
% varargin 'ParameterName', 'ParameterValue'-pairs for the following
% properties:
% 'plotType' Type of plot that is created
% ... |
0aeb6b2c140e6251801698dd855088568d2e47e4e935e67d466c53e0d4dc98da | MATLAB | 15,762 | 357 | function [A, bcol, alpha] = print2array(fig, res, renderer, gs_options)
%PRINT2ARRAY Exports a figure to a bitmap RGB image array
%
% Examples:
% A = print2array
% A = print2array(figure_handle)
% A = print2array(figure_handle, resolution)
% A = print2array(figure_handle, resolution, renderer)
% A = ... |
af8080d219c5239c5f1fd3ed899656313630c5a319eeba8aa502926418b2d6dc | MATLAB | 15,821 | 400 | function m = hlp_serialize(v)
% Convert a MATLAB data structure into a compact byte vector.
% Bytes = hlp_serialize(Data)
%
% The original data structure can be recovered from the byte vector via hlp_deserialize.
%
% In:
% Data : some MATLAB data structure
%
% Out:
% Bytes : a representation of the original data as... |
fb020eb7fb0785cfc6b01b27a6ee011545befc278806c0b675a4ab3c542da60c | MATLAB | 15,829 | 515 | function ss=FscatJit2(identifiers, data, varargin)
% Plots data as both jittered points and an error bar, in the
% order the identifiers are passed to it. It preserves whatever order
% was in the fbmm structure. Also includes the option to define the circle
% size or use a default. Also allows someone to add bars to ... |
2b436a0d9be1da675d1e1a5eb4c8283215d5ba92481313ff1a199cf5e006f5db | MATLAB | 15,858 | 517 | function Answer=APinputdlg(Prompt, Title, NumLines, DefAns, Resize)
%INPUTDLG Input dialog box.
% ANSWER = INPUTDLG(PROMPT) creates a modal dialog box that returns user
% input for multiple prompts in the cell array ANSWER. PROMPT is a cell
% array containing the PROMPT strings.
%
% INPUTDLG uses UIWAIT to suspend ... |
00d962d20d14c367f1b0d1102180dd114bb14fd2581479d9487aef9ebc9c6e98 | MATLAB | 15,864 | 291 | % CROSSFREQ - compute cross-frequency coherences. Power of first input
% correlation with phase of second.
%
% Usage:
% >> crossfreq(x,y,srate);
% >> [coh,timesout,freqsout1,freqsout2,cohboot] ...
% = crossfreq(x,y,srate,'key1', 'val1', 'key2', val2' ...);
% Inputs:
% x = ... |
04710d406778e6bd53ff99b6ea8358bcd22efdee4f31261bba5d754386551d68 | MATLAB | 15,886 | 461 | function res = vl_contrib(command, module, varargin)
%VL_CONTRIB Contribution modules management
% VL_CONTRIB is a tool to download, set up and compile external
% contribution modules for MatConvNet. It downloads the list of available
% modules from a dedicated repository and uses GIT (if present) or ZIP
% file... |
f09ac36c2e22e381a25e2231651920532f1fe7d563a07f8454c07bd606f68f03 | MATLAB | 15,900 | 447 | clear all
close all
clc
n_track = 1;
step_time = 10;
step_avg = 200;
peak_lap = 0.2;
threshold_norm = 0.2;
threshold_burst_cp = 10;
file_names = dir('*.csv');
for q = 1:length(file_names)
input = readtable(file_names(q).name);
time = table2array(input(:,1));
signal = table2array(input(:,n... |
9df41c6809b5650911c5d4e5515fd3a1e149a017199ce4c966b61794e6fd5776 | MATLAB | 15,901 | 595 | function pp = splinefit(varargin)
%SPLINEFIT Fit a spline to noisy data.
% PP = SPLINEFIT(X,Y,BREAKS) fits a piecewise cubic spline with breaks
% (knots) BREAKS to the noisy data (X,Y). X is a vector and Y is a vector
% or an ND array. If Y is an ND array, then X(j) and Y(:,...,:,j) are
% matched. Use PPVA... |
d254c7b2e7e35fb803f6dea431a99f4f78ac95badbc0b7b9d8c5dd5b3944ac57 | MATLAB | 15,963 | 338 | % STD_TOBIDS - From a STUDY rename files if needed, sort folders, and export metadata
% following the BIDS specification
%
% FORMAT STUDY = std_tobids(STUDY,options)
% options are: 'export_dir' followed by the path
% 'keep_files' being 'yes' (default) or 'no'
% ... |
29a29aa0e8f25c74e593536fe70eab3c8b2e710a459e6ecb85f36d2be084d3d9 | MATLAB | 15,980 | 404 | function m = std_serialize(v)
% Convert a MATLAB data structure into a compact byte vector. This function
% is identical to hlp_serialise (as of 2015). It bears a different name
% so as to avoid conflict.
%
% Bytes = std_serialize(Data)
%
% The original data structure can be recovered from the byte vector via hlp_dese... |
7d67ffaaf120fc8400825fbfffa9ae8df991016e53f5bd4bede13bf722ab8b32 | MATLAB | 15,991 | 400 | function [] = StandardisedNetworkPlotNodeCartography(adjM, coords, edge_thresh, ...
NdCartDiv, plotType, FN, pNum, Params, lagval, e, figFolder, oneFigureHandle, suffix)
%
% script to plot the graph network for node cartography
%
% Parameters
% ----------
% adjM : double array
% adjacency matri... |
21ee423feb95b7fffde82878c80539c472ac38b92433f5b37469424759ec7daa | MATLAB | 16,024 | 349 | function [trl,dataselep] = iEEG_func_detectRipples_detector5(fsettings,data)
%% ########################################################################
% [trl,dataselep] = iEEG_func_detectRipples_detector5(fsettings,data)
% #########################################################################
%
% Ripple detection... |
e5f2c6119ad6ae52c064d3064b043a507be1856e9f69ea1643546d4d4aa3b428 | MATLAB | 16,034 | 411 | function TS_FeatureSummary(opID,whatData,doViolin,doInspect,annotateParams,customAnnotation)
% TS_FeatureSummary How a given feature behaves across a time-series dataset
%
% Plots the distribution of outputs of an operation across the given dataset
% and allows the user to annotate time series onto the plot to visual... |
61a50cfa9b952369326fc2e3d2ae4cc1e247d220d7d78e95c5029c7c31db22c5 | MATLAB | 16,047 | 356 | %************************************************************************************%
%************************************************************************************%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%Master file for D.sort%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%**********************************************************... |
90c61eddbeeaf0b447d21234b71f048ac42739f8042d2d8e436249f947cebb23 | MATLAB | 16,051 | 483 | function [VOLLOCS, LOCS, verbose] = ...
tapas_physio_create_scan_timing_from_gradients_auto_philips(log_files, ...
scan_timing, verbose)
% Automatically extracts slice/volume scan events from gradient timecourse
% SCANPHYSLOG file
%
% [VOLLOCS, LOCS, verbose] = ...
% tapas_physio_create_scan_timing_from_gra... |
e6d86f256ccbb61a1879986b629a933ff8473ba7ef3333119e5d100d8c997e00 | MATLAB | 16,061 | 590 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MakingSubcorMORDensity
% Setup
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Add paths
baseloc="C:\Users\dk818\OneDrive - Imperial College London\NCORE\miFCdFC";
% For outputs
str='\Outputs';
outputpath=strcat(baseloc,str);
a... |
37362a7650081571fbca8cbf48db2047ddfac7e946911200ba1751e52b4b99e8 | MATLAB | 16,066 | 442 | function ccainf(N,Ny,Nx,Nz,Nw,Npca,dist_parm,sig,nR,nP,deconf_meth,use_nullspace,seed0)
% Monte Carlo evaluation of CCA inference
% ccainf(N,Ny,Nx,Nz,Nw,Npca,dist_parm,sig,nR,nP,deconf_meth,seed0)
%
% N : Number of subjects
% Ny : Number of variables in Y
% Nx : Number of variables in X
% Nz... |
4ba9531ea6bde7c925e87217a008e9da8a5efa26e89b7380dc6e29ed31e9bd41 | MATLAB | 16,083 | 392 | % EEGLAB_UPDATE - assess if EEGLAB new updating and ask user to install
% new version
%
% Usage:
% >> eeglab_update
%
% Authors: Arnaud Delorme, SCCN/INC/UCSD, 2019
% Copyright (C) 2019 Arnaud Delorme, SCCN/INC/UCSD
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentatio... |
646d8abf22013ec130da85ac1ee39f75c5933ce43003af1ef5ff198111e2018d | MATLAB | 16,098 | 394 | function [x, cost, info, options] = arc(problem, x, options)
% Adaptive regularization by cubics (ARC) minimization algorithm for Manopt
%
% function [x, cost, info, options] = arc(problem)
% function [x, cost, info, options] = arc(problem, x0)
% function [x, cost, info, options] = arc(problem, x0, options)
% function ... |
c7297ebcb354bbe1e8b315529473237b5a96943dc20096829d5386cdd98b7b5c | MATLAB | 16,098 | 419 | function CellsortICAplot(mode, ica_filters, ica_sig, f0, tlims, dt, ratebin, plottype, ICuse, spt, spc)
% CellsortICAplot(mode, ica_filters, ica_sig, f0, tlims, dt, ratebin, plottype, ICuse, spt, spc)
%
% Display the results of ICA analysis in the form of paired spatial filters
% and signal time courses
%
% Inputs:
% ... |
0b5aea6876fd4d690b253721230f1fa2d22d27e4fbd34eb4b4d58e73c67f7a92 | MATLAB | 16,119 | 459 | load('pooldata_ComboStim.mat')
stimInd = [1,2,3];
SpikeCount_Twindow = 1; % compute spike count in 1 sec time window following IgnoreTimeWindow
StimTimeIndv = 1; % duration of each stimulus is 2 sec
IgnoreTimeWindow = 0; % ignore first 0 sec response
%% spike counnt in 1 sec bin
clear spikecount num
for k1 = 1:size(p... |
21931ddcaad328a2f8196169980f2197397cc17cf524aad2944a7cca0c138e67 | MATLAB | 16,121 | 414 | function [ subject ] = nmri_read_markers( subject, params )
%[ subject ] = nmri_read_markers( subject, params )
% Will check spike/event markers and put into subject struct
% call the subject and params include
nmri_include_read_ps
%% Get the modality-specific analysis params
if isfield(subject,'dataset_mapping')
... |
bfd5edeb7925a444b189162510097e77717539534b92816a2ba9b60b6b99f04c | MATLAB | 16,121 | 433 | function [anstime, answer] = PresentStimulus(signal, refdirection, signaldirection, leng, display, jitter, depthorder, ped, peddisp, disparitydiff, task, contr, contrsign);
%% Inputs
% signal is given in proportion -- this represents the coherence of the
% stimulus.
signal = signal/100;
%% Initialize these v... |
405d5ae4b6c358efa3700d077cb2414d34f318425a0b824786a53b70bfe10377 | MATLAB | 16,139 | 460 | function varargout = DensityMap(x, y, varargin)
%DensityMap - colormap equivalent of the dotplot produced by PlotXY
%
% This funtion produces a colormap equivalent of the dotplot producesd by
% PlotXY. Provide two vectors x and y (of equal lengths) to get a map with
% values of x varying in different columns (absciss... |
be9b7cbc4bb1d8c97700febf3e57c19eea3fe1636c377c35aecb58849ea1b60e | MATLAB | 16,160 | 375 | function [] = load_params
%%load_params: Load parameters for assays
global info
%% Import general experimental information
% These values will be common across all assay types
disp('Reading data from file....');
% Detect names of tabs in excel spreadsheet
[~, info.sheets] = xlsfinfo(info.calledfile);
alphabet = ['A... |
40eeab82150be8f285e152adbc0af1d47bf1b9ce6b9b48d19884ee16d2ce6eac | MATLAB | 16,166 | 422 | function varargout = dataset_select(varargin)
% DATASET_SELECT MATLAB code for dataset_select.fig
% DATASET_SELECT, by itself, creates a new DATASET_SELECT or raises the existing
% singleton*.
%
% H = DATASET_SELECT returns the handle to a new DATASET_SELECT or the handle to
% the existing singleton... |
22bc2690e33f8ee709173e4293f89fc10af624471c89c52ff599625551a91740 | MATLAB | 16,171 | 369 | classdef Population
% evolvable population of reservoir objects.
properties
% User-modifiable properties:
Size = 100; % number of reservoirs
Env = 'Lorenz'; % reservoir environment
T = struct('spinu... |
912228bafc4ce247e41bdfb9ed35860327c3d66d41eebd97ab60eba7bba93c57 | MATLAB | 16,174 | 416 | function out = NL_LargestLyap(y, Nref, maxtstep, past, NNR, embedParams)
% NL_LargestLyap Largest Lyapunov exponent of a time series.
%
% ---INPUTS:
% y, the time series to analyze
% Nref, number of randomly-chosen reference points (-1 == all). Accepted for
% backwards compatibility but no longer affects the co... |
ed70e8107443fa288df29ebbb8691c77d73a9f1996975d7a85de6f42d9a32e8c | MATLAB | 16,176 | 496 | function data = loadjson(fname,varargin)
%
% data=loadjson(fname,opt)
% or
% data=loadjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% author: Qianqian Fang, <q.fang at neu.edu>
% created on 2011/09/09, including previous works from
%
% Nedialk... |
e62c33d18dedb04c40ccd1d4aaf5401ef27d65a53662a6f9517887855adabfea | MATLAB | 16,178 | 493 | function varargout = colorspace(Conversion,varargin)
%COLORSPACE Transform a color image between color representations.
% B = COLORSPACE(S,A) transforms the color representation of image A
% where S is a string specifying the conversion. The input array A
% should be a real full double array of size Mx3 or MxN... |
b7c4200d14184a530ec329883cbaf96405254832452aec9ce3c3b3f0df735b7e | MATLAB | 16,215 | 404 | function ft_fmri_preprocessing(img_input, slice_params, field_params, ...
realign_params, outlier_params)
% FMRI preprocessing
%
% ft_fmri_preprocessing(img_input, slice_params, field_params, ...
% realign_params, outlier_params)
%
% Inputs:
% input - cell array of filenames of input time series.
% ... |
bcbf3903082ed4131661121ba39a0ad079e223d1595ce86433a4badb37bfe57f | MATLAB | 16,219 | 372 | %Axon analysis and quantification code associated with Gutman-Wei et al.,
%2025 - function for initial processing of reconstruction
% Returns reconstruction with WM axon and small branches removed, and a
% series of indices matching each xyz value of reconstruction with point
% type, height, layer identity, and other... |
6526029df9140500ee259bde58bb6ad53616a323377a307583dfd4bba5a6917c | MATLAB | 16,241 | 481 | % This demo script provides data description and analysis demonstration
% Data for each section can be accessed in each corresponding subfolder directly or via
% external link
% Call functions from #functions#
% Contact Dr Ye Tian, yetianmed@gmail.com
%% 1.Compute subcortex-to-subcortex similarity matrix
addp... |
526698651327f7edb7b2b58500253ee8569739111474f8735329f28772cf083f | MATLAB | 16,267 | 447 | function han = showsurface3(vertices, faces, para, varargin);
% plots volume conductor/cortex as surfaces
% eventually plus sources/dipoles
% usage: showsurface(vc,para,source1,source2,....);
%
%
% vc is a structure with two fields:
% vc.tri is Nx3 matrix of integers where each
% column denotes the indic... |
0249d0f7b4f83e420afe8abb6d8d383bf84a5f5fdb75175ffefb93e2b6b9d4a4 | MATLAB | 16,271 | 494 | function varargout = Meta_cluster_tools(meth,varargin)
% varargout = Meta_cluster_tools(meth,varargin)
%
% This function contains multiple tools for working with clusters
% derived from Meta_Activation_FWE and Meta_SOM tools
%
%
% ------------------------------------------------------
% extract data and print a table f... |
b7d749b507c0c440bef0938139e9c6f3573ba076a84a2f23103950d86aac221b | MATLAB | 16,284 | 484 | function generateFigure6()
% GENERATEFIGURE6_REVISED Generate Figure 6 for the normalization paper
%
% Purpose:
% Creates a multi-panel figure comparing default and in-degree matched conditions:
% - Normalization index distributions
% - Fisher Information scaling for contrast and orientation
% - Neural manifold... |
25c33e9cd5084f2f3d744f0b0e552258896235f33bc749ead6d381afe98e7472 | MATLAB | 16,285 | 354 | %% Script to compute HC and SSD MIND edges and degrees.
% Copyright (C) 2026 University of Seville
% Written by Natalia García San Martín (ngarcia1@us.es)
% This file is part of Hierarchy Longitudinal MIND Gradients Psychosis toolkit.
%
% Hierarchy Longitudinal MIND Gradients Psychosis toolkit is free softwa... |
57935c0179eda70c2c41995b5bfa3958ec0af92367f144b785fd350612a93cca | MATLAB | 16,299 | 436 | function out = DN_OutlierInclude(y, thresholdHow, inc, fixedThresh)
% DN_OutlierInclude How statistics depend on distributional outliers.
%
% Measures a range of different statistics about the time series as more and
% more outliers are included in the calculation according to a specified rule,
% of outliers being ... |
6d67ef85b36808eb6feaec51035354da68073afa40e5eb2b2d264469a4b7a4d9 | MATLAB | 16,301 | 410 | function [x, cost, info, options] = conjugategradient(problem, x, options)
% Conjugate gradient minimization algorithm for Manopt.
%
% function [x, cost, info, options] = conjugategradient(problem)
% function [x, cost, info, options] = conjugategradient(problem, x0)
% function [x, cost, info, options] = conjugategradie... |
d52fa421ae9b50fd5cf63a6c857d8c749cdeab4f3835dadef354183b4625d9bf | MATLAB | 16,314 | 580 | function exportfig(varargin)
%EXPORTFIG Export a figure to Encapsulated Postscript.
% EXPORTFIG(H, FILENAME) writes the figure H to FILENAME. H is
% a figure handle and FILENAME is a string that specifies the
% name of the output file.
%
% EXPORTFIG(...,PARAM1,VAL1,PARAM2,VAL2,...) specifies
% parameters th... |
8d6fbacd7049536949f7bba5f0e62cf4368b6762ea6c4c4ebe8a15315c7f7122 | MATLAB | 16,318 | 409 | function results = runnsdbehavioralanalysis(filename,expectedframes,expectedduration,nsdexpfile,choicebuttons);
% function results = runnsdbehavioralanalysis(filename,expectedframes,expectedduration,nsdexpfile,choicebuttons);
%
% <filename> is the .mat file saved from runnsd.m
% <expectedframes> is the expected number... |
df797c06031a08b8cde10541d1e51778b9836c4e862e01a5518484fb926411a1 | MATLAB | 16,356 | 385 | set_up_paths_and_data_directories;
bold_suffix = 'space-MNI_desc-ppres_bold.nii';
tr_length = 1.3;
stim_names = {
'After_The_Rain', 'Between_Viewings', 'Big_Buck_Bunny', 'Chatter', 'Damaged_Kung_Fu', ...
'First_Bite', 'Lesson_Learned', 'Payload', 'Riding_The_Rails', 'Sintel', 'Spaceman', ...
'Superhero', 'Tears_of_St... |
8e5a807230a9bdabaf58f5cb375f618ee05b59d3d03f6ee793335365056ba6bf | MATLAB | 16,358 | 341 | function plot_communication_subspace_prediction_ablation
close all
clear all
clc
% Plot prediction performance by reduced-rank regression after ablation.
% Select a folder containing data.
folder_name = uigetdir;
cd(folder_name)
% Ablation dimensionality.
ablated_dim_num = 2; % 1, 2 or 3.
load('population_regressio... |
529363e4f07a4866c874aabd8598472db5b086f1fb91d4aad10cde1c0b893437 | MATLAB | 16,363 | 455 | function [] = tapas_uniqc_view3d(img, voxelSizeRatio)
% Display 3D matrices along their 3 dimensions.
%
% [] = tapas_uniqc_view3d(img)
%
% IN
% img arbitrary matrix (can be complex)
% voxelSizeRatio allows display of non-isotropic voxel size
% default: [1 1 1] for isotropic display
... |
1c2a5873cce32120ffcbf6f2680d80646bc1e69d16240a60247c9edb04ca6f23 | MATLAB | 16,372 | 407 | % EEG_INTERP - interpolate data channels
%
% Usage: EEGOUT = eeg_interp(EEG, badchans, method, t_range);
%
% Inputs:
% EEG - EEGLAB dataset
% badchans - [integer array] indices of channels to interpolate.
% For instance, these channels might be bad.
% [chanlocs structure] cha... |
cff5127b03001fe41925a87c5ddcaa9f53e18e744f281c39f999fefb16d92fd0 | MATLAB | 16,376 | 435 | function [basefun] = chooseBasis(type,tmesh,params)
%CHOOSEBASIS: create basis functions for spike and stimulus filters
%
%
%input:
% %type: a handle to decide which basis to use
%tmesh: vector of time points. just needs to be 1:numel(tmesh)
%params: the importnat parameters for each model. if not
% ... |
c52563593b29ffc2c841907f517ef05025ee198b1f082a39b5dfe95722813068 | MATLAB | 16,379 | 358 | close all;
clear all;
clc;
ForderName=['PAG/BadMood'];
Monkey_name='all'; % 'c' 'k' 'all'
Num_context=4;
Num_probability=3;
POP_foldapath=['POP_Correlation/PavFo4C4S/ALL/',ForderName];
POP_allfolda=dir([POP_foldapath,'/*.mat']);
load(['Labnote/Labnote.mat']);
load(['Labnote/Labnote_RAW.mat']);
u=1;
for POP_i=1:length(P... |
f1b64c970a5926627915b790f3af0db43031ad08177549992d18acdd30ba314b | MATLAB | 16,401 | 338 | function env_showmenu(varargin)
% Links the BCILAB menu into another menu, or creates a new root menu if necessary.
% env_showmenu(Options...)
%
% In:
% Options... : optional name-value pairs; names are:
% 'parent': parent menu to link into
%
% 'shortcuts': whether to enable keyboard s... |
d34e590a715a672e04dffbf283a126c279bac320a46c2ad29f4cf529db8f83de | MATLAB | 16,419 | 456 | function [grad, elec] = mne2grad(hdr, dewar, coilaccuracy, coildeffile)
% MNE2GRAD converts a header from a fif file that was read using the MNE toolbox into
% a gradiometer structure that can be understood by the FieldTrip low-level forward
% and inverse routines.
%
% Use as
% [grad, elec] = mne2grad(hdr, dewar, co... |
ebaf8eb48497d554b7932a6ec9de114120d4ae9f3a8ac0d5728ac24f84a99bef | MATLAB | 16,432 | 269 | function [cm_data]=inferno(m)
cm = [[ 1.46159096e-03, 4.66127766e-04, 1.38655200e-02],
[ 2.26726368e-03, 1.26992553e-03, 1.85703520e-02],
[ 3.29899092e-03, 2.24934863e-03, 2.42390508e-02],
[ 4.54690615e-03, 3.39180156e-03, 3.09092475e-02],
[ 6.00552565e-03, 4.69194561... |
042cd589bd82c14d039bd1f61d9709b20b20b881cb24ab8ad3a7479ff2262f1d | MATLAB | 16,433 | 270 | function cm_data=plasma(m)
cm = [[ 5.03832136e-02, 2.98028976e-02, 5.27974883e-01],
[ 6.35363639e-02, 2.84259729e-02, 5.33123681e-01],
[ 7.53531234e-02, 2.72063728e-02, 5.38007001e-01],
[ 8.62217979e-02, 2.61253206e-02, 5.42657691e-01],
[ 9.63786097e-02, 2.51650976e-0... |
129960b2e003266f8687f9f751523587cf6f7b7c60b750596ca971f95b931f1d | MATLAB | 16,433 | 410 | function M = fixedrankembeddedfactory(m, n, k)
% Manifold struct to optimize fixed-rank matrices w/ an embedded geometry.
%
% function M = fixedrankembeddedfactory(m, n, k)
%
% Manifold of m-by-n real matrices of fixed rank k. This follows the
% embedded geometry described in Bart Vandereycken's 2013 paper:
% "Low-rank... |
d990518624b416476469e530bcb2f0dcf9c2685ee2f459c6fe46e84a9da9d563 | MATLAB | 16,434 | 432 | function [center, Cn, PNR] = initComponents_residual_parallel(obj, K, save_avi, use_parallel, min_corr, min_pnr, seed_method)
%% initializing spatial/temporal components for the residual video
%% input:
% K: scalar, maximum number of neurons
% frame_range: 1 X 2 vector indicating the starting and ending frames
% ... |
cb0614ce21933b20e5968fe0de64cb6eda7f57dc28950c1f4e7a97f529fa8d75 | MATLAB | 16,446 | 530 | function json=saveubjson(rootname,obj,varargin)
%
% json=saveubjson(rootname,obj,filename)
% or
% json=saveubjson(rootname,obj,opt)
% json=saveubjson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a Universal
% Binary JSON (UBJSON) binary string
%
% author... |
a7fe789b19041587ca541ae933596819fd874d0ccdb496a0eb7a71406725599c | MATLAB | 16,449 | 416 | function data = besa2fieldtrip(varargin)
% BESA2FIELDTRIP reads and converts various BESA datafiles into a FieldTrip
% data structure, which subsequently can be used for statistical analysis
% or other analysis methods implemented in Fieldtrip.
%
% Use as
% [output] = besa2fieldtrip(input)
% where the input should b... |
cad8de8450696474e6a053b4b694b91fafddd19568eb5b81b0a1a6fc926a725d | MATLAB | 16,450 | 386 | function [ avw, machine ] = avw_hdr_read(fileprefix, machine, verbose)
% avw_hdr_read - read Analyze format data header (*.hdr)
%
% [ avw, machine ] = avw_hdr_read(fileprefix, [machine], [verbose])
%
% fileprefix - string filename (without .hdr); the file name
% can be given as a full path or relative to ... |
0f5786f8555ed446f123b619b8cc32658d79584f33a88f4150a693c70bd9429a | MATLAB | 16,452 | 341 | %% ms SEI: job - functional connectivity (FC) between 2 selected AAs (DMN & DAN)
% figs = msSEI_FC_DTF_fig_v2_selCh.m
% (c) Jiri, Oct23
%% settings: v1 - relaxed conditions (p-level, length of significance, ...)
dirSuffix = '_msFig_AA_v1_relaxCond';
t_sel = [-1.0, 2.0]; % the true sel time will be cut by 1 s on ed... |
d2429134c40006283a211eecb33499fdabf6ba41092058f61f7c70d5782ac83d | MATLAB | 16,468 | 456 | function [MRSCont] = OspreyLoad(MRSCont)
%% [MRSCont] = OspreyLoad(MRSCont)
% This function loads the raw MRS data from all major vendors.
% Data is read from the provided input filenames. It is shaped according
% to the type of sequence (un-edited data, MEGA-edited (ON/OFF),
% HERMES/HERCULES (A/B/C/D), etc.).... |
535e64fd85e0f833c437f24ed5d9f4dfbaeb934ef8e9642c2bd592d4e516c751 | MATLAB | 16,510 | 372 | function [trl,dataselep] = iEEG_func_detectRipples_detector4(fsettings,data)
%% ########################################################################
% [trl,dataselep] = iEEG_func_detectRipples_detector4(fsettings,data)
% #########################################################################
%
% Ripple detection... |
420edccf8994c849956f0787bbba92d333820366e7bb2ec48290bc05deab35db | MATLAB | 16,555 | 421 | function [fitParamsStep1] = fit_Osprey_PrelimReducedMM(dataToFit, basisSet, minKnotSpacingPPM, fitRangePPM)
%% [fitParamsStep1] = fit_Osprey_PrelimReduced(dataToFit, basisSet, minKnotSpacingPPM, fitRangePPM)
% Performs the first step of the LCModel preliminary analysis
% analogous to the LCModel algorithm. The algo... |
262e7b7043535e6cbd29f981a2bd7fd5f1c0c25a38fce77388b1a9f723541583 | MATLAB | 16,563 | 395 | function [C2,cfg] = mahal_iem_trialwise_xgen(dat,theta,task,cfg)
% [distmat,cfg] = mahal_iem_trialwise_xgen(dat,theta,task,cfg)
if nargin < 3
help mahal_iem_trialwise_xgen
error('missing input arguments!')
end
%set options
if (nargin < 3) || (isempty(cfg))
cfg = struct;
end
ntrl = ... |
f36248aa5157da81ecef79bff6d644b7d77ba4a3c4731ad2181f927adf8f9185 | MATLAB | 16,596 | 353 | function poolSubjects_signifActivTimes(params, AA_type, SA_params)
% plots histograms of times of significant activations in anatomical areas
% activation time = when activations in given freq. band were significantly different
% !!! works for only 2 classes !!!
% pools together subject processed by a given job
% sett... |
cec352eca6c25e321ce87194080148b8f2a74682df07569f8b9b8f1b957798ff | MATLAB | 16,610 | 505 | clear % Clears workspace
clc % Clears history
clf % Clears figure window
Nx = 101; % Defines the no. of x grid points
Ny = 101; % Defines the no. of y grid points
px = 0; % Sets the lower end of the domain x
qx = 1; % Sets the upper end of the domain x
py = 0; % Sets the lower end of the domain y
qy = 1; % ... |
41e5e60adb59f9514bc9cb70493ed4067270a9ada75b611433cdefe147993e23 | MATLAB | 16,623 | 337 | %% jobSDAT.m
% This function describes an Osprey job defined in a MATLAB script.
%
% A valid Osprey job contains four distinct classes of items:
% 1. basic information on the MRS sequence used
% 2. several settings for data handling and modeling
% 3. a list of MRS (and, optionally, structural imag... |
bd1ecf6b5a120f49c866e2297430dd13ed11b618de508480797f2a9dce1b4cfa | MATLAB | 16,625 | 358 | function [trl,dataselep] = iEEG_func_detectRipples_detector1(fsetup,data)
%% ########################################################################
% [trl,dataselep] = iEEG_func_detectRipples_detector1(fsetup,data)
% #########################################################################
%
% Ripple detection. Func... |
b7ba3d911dc12150b4750215d42ae54798f8fb4c0854b88eb7b0b5e2d1ce234b | MATLAB | 16,655 | 347 | %% h = sepia_handle_panel_utility_get_header(hParent,hFig,h,position)
%
% Input
% --------------
% hParent : parent handle of this panel
% hFig : handle of the GUI
% h : global structure contains all handles
% position : position of this panel
%
% Output
% --------------
% h ... |
a66c6f947e1b045e378c15a8aadfde5b1bd98f21f22a2264755105fdcb27e938 | MATLAB | 16,664 | 334 | %% jobP.m
% This function describes an Osprey job defined in a MATLAB script.
%
% A valid Osprey job contains four distinct classes of items:
% 1. basic information on the MRS sequence used
% 2. several settings for data handling and modeling
% 3. a list of MRS (and, optionally, structural imaging... |
0c707a211fc679312d51c0fb725d3f52132f6add7086b0c32db9059edf483ebe | MATLAB | 16,693 | 449 |
addpath '/slow-scratch/erfan/brainstorm3/' % add brainstorm to path
fs_folder = '/slow-scratch/erfan/freesurfer/subjects/'; % FreeSurfer folder setup
BrainstormDbDir = '/slow-scratch/erfan/brainstorm_db/'; % Brainstorm database folder setup
AD_dir = main_path; % main project directory
fig_folder = [AD_dir '/Resu... |
0f0187d41ac159ed5f07a253aa7761fcb85ebe93dd62f8920211d1f02790f18d | MATLAB | 16,704 | 617 | %%
clear;
working_dir = 'G:\CEST-fMRI'; % the actual directory to put the codes
SPM_modified_path = [working_dir,'\scripts\SPM_modified'];
addpath(SPM_modified_path);
BM_sim_path = [working_dir,'\scripts\simulation\CEST_coef'];
addpath(BM_sim_path);
ds_dir = [working_dir,'\datasets\sim\exp1\result']; % dir... |
454454c416f2a2c291e90e538d116530709028c1dde5518009788f48e4fd2885 | MATLAB | 16,707 | 591 | % op_robustSpecReg.m
% Georg Oeltzschner, Johns Hopkins University 2019.
% Mark Mikkelsen, Johns Hopkins University 2019.
%
% USAGE:
% [out,fs,phs] = op_robustSpecReg(in, seqType, echo, F0, noAlign);
%
% DESCRIPTION:
% Perform robust spectral registration in the time domain to correct frequency and
% phase drifts.
%
% ... |
3ec7d9479cfb860df85277af6dc87517060132602fa0cafbd18f06546615f272 | MATLAB | 16,721 | 497 | function [conn, nlags] = data2spwctrgc(data, fres, nlags, cond, nboot, maxfreq, output, verbose)
% Epoched time series data to spectral pairwise-conditional time-reversed Granger causality
% and other useful quantities (cross-spectrum, (time reversed) directed
% transfer function, (time reversed) partial directed coher... |
7e770be743cf969971898cec0b8de9fc65e8217b67ed73c38ed7662db901e0e4 | MATLAB | 16,722 | 489 | function data = multiEventLockKinematics(R, M, eventNames, preT, postT, tBase, lags, varargin)
% data = multiEventLockKinematics(R, eventName, tPts, ...)
%
% Repair, smooth, and time-lock video tracking data from DeepLabCut (3D
% version) from an R struct produced by mergeDLC3R.
%
% Smooth: Use either Savitsky-Golay (d... |
7d587db4d3057bd9864be058fd14139b046a0a96664007417126856508b41269 | MATLAB | 16,724 | 471 | %% Figure 3, co-written with Luca Cecchetti
%% 1.1 Prepare the training and test sets: IRI-PT, IRI-EC, and PCL-R F1
% (and PCL-R total score, for the supplement)
clc; clear; close all
load data
% Select variables of interest
dataNonSA = data(:, {'URSI' 'IRI_PT' 'IRI_EC' 'PCL_Total' 'PCL_Factor1' 'Age' 'IQ' 'eTIV'}... |
82dad40ec617960b827c65858c511ece45952e26997a9524094e56ba8e6a9387 | MATLAB | 16,746 | 442 | function M = fixedrankfactory_tucker_preconditioned(tensor_size, tensor_rank)
% Manifold of fixed multilinear rank tensors in Tucker format.
%
% function M = fixedrankfactory_tucker_preconditioned(tensor_size, tensor_rank)
%
% n1 = tensor_size(1);
% n2 = tensor_size(2);
% n3 = tensor_size(3);
% r1 = tensor_rank(1);
% r... |
7f3f976786c36dea7b97f2d346409f2c3268c9de0d4b65097e118f748cd39375 | MATLAB | 16,805 | 406 | % STATCONDFILEDTRIP - same as statcond except that it uses the fieldtrip
% statistical functions. This is useful to perform
% a wider variety of corrections for multiple
% comparisons for instance.
% Usage:
% >> [stats, df, pvals, surrog] =... |
8bea5ad683415390ead7cd0693894c748bfc47217b098763c3317f3cae7cfb22 | MATLAB | 16,822 | 393 | function plot(str, cfg, varargin)
% plot function for a McsCmosSpikeSorterSource object
%
% function plot(str, cfg, varargin)
%
% Produces an intensity map with colorbar and a list of all units. Units
% can be selected from the list or from the map and detailed Information
% about them is displayed in a separat... |
d16d13e6bf24f503d6dc8bd784367d10fd19ac62dd665d83f6cd70906e5cdbaf | MATLAB | 16,825 | 428 | % pop_leadfield - compute Leadfield Matrix
%
% Usage:
% EEG = pop_leadfield(EEG, 'key', 'val', ...);
%
% Inputs:
% EEG - EEGLAB dataset
%
% Required inputs:
% 'sourcemodel' - [string] source model file
%
% Optional inputs:
% 'sourcemodel2mni' - [9x float] homogeneous transformation matrix to convert
% ... |
dd2c42a964ed1167ae7dcc4311a9cb4e00f8bf165381149caa5868bfc050646f | MATLAB | 16,825 | 540 | function Answer=inputdlgcol(Prompt, Title, NumLines, DefAns,Resize,NumCols)
%INPUTDLGCOL Input dialog box.
% Answer = INPUTDLGCOL(Prompt) creates a modal dialog box that returns
% user input for multiple prompts in the cell array Answer. Prompt
% is a cell array containing the Prompt strings.
%
% INPUTDLGCOL uses ... |
fd8e3c5afa247fb5533268b1db98322f7d1a1b9becf8a7add89b348ab41de340 | MATLAB | 16,842 | 338 | %% jobSDAT.m
% This function describes an Osprey job defined in a MATLAB script.
%
% A valid Osprey job contains four distinct classes of items:
% 1. basic information on the MRS sequence used
% 2. several settings for data handling and modeling
% 3. a list of MRS (and, optionally, structural imag... |
107dc6e34660a4c09ea1f8bea8801c98f730e61c22c45f045362f901efc4b899 | MATLAB | 16,879 | 465 | function [anstime, answer] = PresentStimulus(signalD, signalGP, signaldirection, leng, display,depthorder, task, contr, contrsign);
%% Inputs
% signalD, signalGP given in proportion -- this represents the coherence of
% the disparity and GP aspects of the stimulus
answer = [];
anstime = [];
%% Initialize ... |
d731e864ec241ceb811086c51a68471c70e74a660abf2528f0556f93eab9009e | MATLAB | 16,882 | 337 | %% jobRDA.m
% This function describes an Osprey job defined in a MATLAB script.
%
% A valid Osprey job contains four distinct classes of items:
% 1. basic information on the MRS sequence used
% 2. several settings for data handling and modeling
% 3. a list of MRS (and, optionally, structural imagi... |
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