sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
962cc562885aff0a40cdbcd233e97bde5de7479c9cfad399b7bd0b009902aafb | MATLAB | 3,276 | 84 | %jds_periSuppressionRippleProbREM
%Peri-suppression cortical ripple probability during REM: histograms of
%chain REM cortical ripple times around PFC population-suppression
%troughs, compared against a 99% band from circular-shift shuffled
%suppression events (from jds_detectPopulationSuppressionREM output).
day = 1;
... |
f91d5c09cf806b5e3d60b108d4dea12afdb3607ed63dffba0bb8b17866728514 | MATLAB | 3,281 | 98 | function [R,eff] = randmio_dir_connected(R, ITER)
%RANDMIO_DIR_CONNECTED Random graph with preserved in/out degree distribution
%
% R = randmio_dir_connected(W, ITER);
% [R eff] = randmio_dir_connected(W, ITER);
%
% This function randomizes a directed network, while preserving the in-
% and out-degree... |
05ba7de32110f77d92564bfd93ee18810727c394c51f3cfd0716247db7794f23 | MATLAB | 3,282 | 92 | function Parcellate(data_dir,save_dir,parcellation,n_areas)
%
% Parcellate the neuroimaging data according to a given parcellation.
% Accepts only .nii files.
%
% INPUT:
% data_dir directory where the .1D files with the ABIDE data are
% stored
% save_dir directory to save the new data
% parcella... |
ab7a47d71af5bd8714728a7be88ef50081c183a166ffb7da5a7e97d917fac9cc | MATLAB | 3,288 | 89 | function newData = OverlapCalculation(data,OverlapPerc,minLocs,minArea)
wb = waitbar(0,['Calculating the percentage of overlap between the two channels per cluster of data set ' num2str(1) '/' num2str(length(data))]);
newData = cell(1,length(data));
for i = 1:length(data)
if ~isempty(data{i})
... |
a113a62d02825076492ac0daeaa995a62c4f0d1d3ea2b0dc4eae0eee38fa9956 | MATLAB | 3,297 | 80 | function [R, scale]=arqr(v, p, mcor)
%ARQR QR factorization for least squares estimation of AR model.
%
% [R, SCALE]=ARQR(v,p,mcor) computes the QR factorization needed in
% the least squares estimation of parameters of an AR(p) model. If
% the input flag mcor equals one, a vector of intercept terms is
% being fitt... |
10cd02c351c7f5e45d1431ccff8e39cc21a9a7b9e13451dcc440b2f6b28329e6 | MATLAB | 3,298 | 77 | function [trial_types, valid_responses, valid_correct_responses] = tc_get_events_from_trigger_values(all_trigger_values_vec, left_values, right_values, non_odd_ball_value, response_value, all_reaction_times, sampling_rate, stim_duration)
%% [trial_types, valid_responses] = tc_get_events_from_trigger_values(all_trigger_... |
85098500504abfac7185e384fdd5ba56db0daf248f7629dfc5596045822d276d | MATLAB | 3,301 | 78 | function image_average_filter(data)
figure()
set(gcf,'name','Average Filter','NumberTitle','off','color','w','units','normalized','position',[0.25 0.15 0.4 0.6],'menubar','none','toolbar','figure')
if length(data)>1
slider_step=[1/(length(data)-1),1];
slider_one = uicontrol('style','slider','units','... |
e5e13264556a3238ef430774645b50488fd8378cd1e949d9e29c5c6dcb67cd46 | MATLAB | 3,302 | 87 | function LEiDA_TransitionsK
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% LEADING EIGENVECTOR DYNAMICS ANALYSIS
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Function to compute the transition probability matrix for each sub... |
731499c424230611ea68a70a652eb9e35dc7c4daf6caae5b9cc168f8058dad8a | MATLAB | 3,307 | 82 | % This function returns the path to the DL+Direct output folder
% If the path doesn't exist or the folder is empty, it will create the path
% and run the algorithm.
% The name of the folder is always: DLdirect_output
function DLdirect_path = DLdirect_subject_space_Trento(data_path,varargin)
if nargin < 2
... |
fed5ec690096712bc7daf851e1aab68f86455810551a826b0a6d4034ec5ed7a5 | MATLAB | 3,310 | 88 | function [atlas_out, fc_out] = removeNetworks(atlas_in, net_names, name, fc_in)
%REMOVENETWORKS Remove given networks from a network atlas
% atlas_in: Input network atlas
% net_names: Networks to remove
% name: Name of modified atlas
% (Optional) fc_in: Functional connectivity to remove given networ... |
82611a822f02e5b5ca961727334f65c116f1d229d4f0cfbbeb1ab2a5417a6bcc | MATLAB | 3,325 | 160 | %% MAIN
clc
clear
format compact
format longG
load('waveforms_ripple_clusters_all.mat')
%save('waveforms_cluster2_rgs.mat','waveforms_cluster2_bp_rgs','waveforms_cluster2_raw_rgs','-v7.3');
%save('waveforms_cluster2_rgs.mat','waveforms_cluster2_bp_rgs','waveforms_cluster2_raw_rgs','-v7.3');
%save('waveforms_cluster2_r... |
cae5a904b179dc8ba0410d32ae674fcc26fb293d65ccef75dbb8ff9747b4aaae | MATLAB | 3,339 | 80 | function [I,Q,F]=motif3struct_wei(W)
%MOTIF3STRUCT_WEI Intensity and coherence of structural class-3 motifs
%
% [I,Q,F] = motif3struct_wei(W);
%
% Structural motifs are patterns of local connectivity in complex
% networks. Such patterns are particularly diverse in directed networks.
% The motif fre... |
88e4ff6631a80c46597baeab83eb4a08afcd92a6abeba28efc3e033a7464ec5c | MATLAB | 3,342 | 121 | function ri = rand_index(p1, p2, varargin)
%RAND_INDEX Computes the rand index between two partitions.
% RAND_INDEX(p1, p2) computes the rand index between partitions p1 and
% p2. Both p1 and p2 must be specified as N-by-1 or 1-by-N vectors in
% which each elements is an integer indicating which cluster the point... |
3aeb28822df0023a4c9f6f5d3931d57311d504a71d83f386fbd7c321005cd05f | MATLAB | 3,348 | 100 | function Plot_K_nodes_in_cortex(data_dir,save_dir,selectedK,parcellation)
%
% Plot the nodes with positive values in the vectors of the centroids red
% and the remaning nodes blue. Scale the size and transparency of the nodes
% according to their contribution.
%
% INPUT:
% data_dir directory where LEiDA results ar... |
da1fcccf030e3baab719a57e15f2fae67d0eb018abe431133390631fb1172618 | MATLAB | 3,373 | 110 | %jds_compareRippleModulationShifters
%Compares NREM ripple modulation (suppression index and ripple-aligned
%PSTH) of CA1 cells classified as REM theta-phase shifters vs nonshifters
%(rank-sum, boxplot, PSTH overlay).
clear
savedir = '/Volumes/JUSTIN/SingleDay/ProcessedDataREM/';
load([savedir 'CA1nremca1allripmodsigd... |
030f90ecaf53d9e9e52d7351bbdd30feafe2ca9755d0b9d31215dab7964ea630 | MATLAB | 3,377 | 112 | function extract_eye_trials(sj,blk)
piwd='/project/3018037.01/Experiment3.2_ERC/AnalysisFolder/rawData/';
%sj=[1 2 5:7 9:20];
% sj=9;
% blk=3;
pp=['S' num2str(sj)];
%if sj<21
hdrlines=43;
% else
% hdrlines=47;
% end
f=fopen([piwd pp filesep 'eyetrackerfiles' filesep pp '_B' num2str(blk) ' Samples.txt'])... |
5fa78d628d4484a2aa562a95b1b6679da65a40d341fe89338db585c93fef9180 | MATLAB | 3,384 | 86 | classdef DeglitchTest < 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(... |
10f83a2e289b3e8825f966cbcbdc71c4a592d86573aed5a52ef73873a44755ed | MATLAB | 3,385 | 96 | function surf = SurfStatWriteSurf1( filename, surf, ab );
%Writes coordinates and triangles to a single .obj or FreeSurfer file.
%
% Usage: surf = SurfStatWriteSurf1( filename, surf [,ab] );
%
% filename = .obj or FS file name. If extension=.obj, writes a .obj file
% (ASCII or binary), else write... |
ce8efb098e1b7825de24feccc051f9ec96d272a31f327662153a2ea59dbca094 | MATLAB | 3,400 | 96 | %% plot_fig5
%
% Reproduces all Fig. 5 panels
%
% Requires: shadedErrorBar.m (Mathworks File Exchange)
% 'Fig5_mua_sua.mat', 'Fig5_lfp_tf.mat'
% Author: moh3enparto@gmail.com
% Date: 08.08.2026
clear; close all;
set(groot, 'defaultAxesTickDir', 'out');
set(groot, 'defaultAxesTickDirMode', 'manual'... |
392b9d9643c6354f09104c28312608b1ffddb57cefcb3810a9fac68a51dcc32e | MATLAB | 3,401 | 107 | function [On,Wr] = reorder_mod(W,M)
%REORDER_MOD Reorder connectivity matrix by modular structure
%
% On = reorder_mod(W,M);
% [On Wr] = reorder_mod(W,M);
%
% This function reorders the connectivity matrix by modular structure and
% may consequently be useful in visualization of modular structure... |
9768e6c2998facd16992f106d7a35e0022bdc7bd5c1f67c539102ccbb463f3eb | MATLAB | 3,404 | 90 | function [anat_brain, mask] = spm_brain_extraction(structural)
%% STEP 3 -- Segmentation of coregistered structural image into GM, WM, CSF, etc
% (with implicit warping to MNI space, saving forward and inverse transformations)
[d, f, e] = fileparts(structural);
if exist([d filesep f '_brain.nii'],'file')
disp('... |
9cba91f062aacbdc3cdc0924fe876cc3194cf20d7a0c669ff09235cd8f31c645 | MATLAB | 3,418 | 141 | function newmap = bluewhitered_PD(m,x)
%BLUEWHITERED Blue, white, and red color map.
% BLUEWHITERED(M) returns an M-by-3 matrix containing a blue to white
% to red colormap, with white corresponding to the CAXIS value closest
% to zero. This colormap is most useful for images and surface plots
% with positiv... |
c5d7ce136659391033d6de42e7cf01d12af5f27943a18bf50bbc70942635174a | MATLAB | 3,421 | 115 | % CLIP_NII: Clip the NIfTI volume from any of the 6 sides
%
% Usage: nii = clip_nii(nii, [option])
%
% Inputs:
%
% nii - NIfTI volume.
%
% option - struct instructing how many voxel to be cut from which side.
%
% option.cut_from_L = ( number of voxel )
% option.cut_from_R = ( number of voxel )
% option... |
e9e22448095579ce740cdc438ecac637b2bc24e468414dc38cfd0704f7e4ef2a | MATLAB | 3,428 | 105 | %--------------------------------------------------------------------------
% Till Habersetzer, 05.07.2025
% Communication Acoustics, CvO University Oldenburg
% till.habersetzer@uol.de
%
% Description:
% Master script for running the 'complete' MEG-audio cross-correlation
% analysis pipeline (without plotting).
% ... |
60047e95719ed845b40103b6ad47d07528e4d05d85765a76fd3555351ca7d803 | MATLAB | 3,430 | 101 | % current working directory needs to be /path/to/scripts
mainpath = pwd;
addpath([mainpath filesep 'toolboxes' filesep 'OpenFmriAnalysis'])
addpath([mainpath filesep 'toolboxes' filesep 'tc_functions'])
addpath([mainpath filesep 'toolboxes' filesep 'spm12'])
tvm_installOpenFmriAnalysisToolbox
%%
freeSurferFolder = [... |
6453e3469fa2ce3d11cf6f98e3d797f00df96b34ddd20da5ef5624683e16cdce | MATLAB | 3,441 | 83 | function loc_list_clusters_data_table(data)
counter = 0;
for i = 1:length(data)
data_to = unique(data{i}.area);
if length(data_to)>1
counter = counter+1;
data_to_send{counter} = data{i};
end
end
if exist('data_to_send','var')
f = waitbar(0,'Extracting Data Table Information...'... |
4e1af71c1f19454ad8148cb47e18a1a123a741501854313fc04f31d6d179059b | MATLAB | 3,457 | 89 | function LEiDA_AnalysisCentroid
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% LEADING EIGENVECTOR DYNAMICS ANALYSIS
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Function to analyse one PL state from the set of K PL states c... |
a2f2e7ee3d1e6c8c9105188181457d79a6255b24e9bd04146af9db2ffca0e02f | MATLAB | 3,457 | 96 | function loc_list_break_data(data)
input_values = inputdlg({'X_axis Pile Size','Y_axis Pile Size'},'',1,{'10','10'});
if isempty(input_values)~=1
x_axis_pile_size = str2double(input_values{1,1});
y_axis_pile_size = str2double(input_values{2,1});
data_break = cell(1,length(data));
for i = 1:length(... |
eaaa694e5e00b95e4fb92aaaae1abeed649869a8e9f5ef7c7d0185a9f4cb6b87 | MATLAB | 3,459 | 78 | function varargout = nst_io_fetch_sample_data(data_label, confirm_download)
% Return file names of sample data. Download them if necessary.
%
% [NIRS_FILES, SUBJECT_NAMES] = NST_IO_FETCH_SAMPLE_DATA('template_group_tapping', CONFIRM_DOWNLOAD)
%
if nargin < 2
confirm_download = 1;
end
switch data_label
case 't... |
34a6279b1401235e9a25b7035e678e536634183aa51a85b5f3bb7ebcf0af16d9 | MATLAB | 3,461 | 105 | function Y_rand = spin_permutations(Y,spheres,n_rep,varargin)
% SPIN_PERMUTATIONS constructs null data through spin permutations.
%
% Y_rand = SPIN_PERMUTATIONS(Y,spheres,n_rep,varargin) performs spin
% permutations of n-by-m matrix Y, where n is number of vertices and m
% number of markers to perumute. Spheres... |
bd6fbe4a62f53aa4c19167d3f7f3f894cb032773d443cf0431992934526b26a4 | MATLAB | 3,467 | 88 | function [C, q]=core_periphery_dir(W,gamm,C)
%CORE_PERIPHERY_DIR Core/periphery structure and core-ness statistic
%
% C = core_periphery_dir(W)
% [C,q] = core_periphery_dir(W,gamm,C0)
%
% The optimal core/periphery subdivision is a partition of the network
% into two non-overlapping groups of nodes, a c... |
ba7ac591c7df2e247f7b25c7b5a6252750d7a5a44adb56f56ca8f41c6b813e10 | MATLAB | 3,477 | 106 | function Binned_y = Model_2State(parameter_guess, JumpProb, data_to_fit)
%MODEL_2STATE 2-state model, fixed localization error
LocError = data_to_fit.LocError;
dT = data_to_fit.dT;
HistVecJumps = data_to_fit.HistVecJumps;
dZ = data_to_fit.dZ;
HistVecJumpsCDF = data_to_fit.HistVecJumpsCDF;
ModelFit = data_to_fit.ModelF... |
b161c98e900b7efbbf862590e64122815b9a91ec97186894a6f5f88266539605 | MATLAB | 3,478 | 98 | function LEiDA_AnalysisK
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% LEADING EIGENVECTOR DYNAMICS ANALYSIS
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Function to analyse the PL states chosen according to the analysis fr... |
d748814d30b67455753c6c38c15cc40d2cd222d1ccf619b8030aa95176344185 | MATLAB | 3,484 | 107 | function P = morlet_transform(x,t,f,fc,FWHM_tc,squared)
% function P = morlet_transform(x,t,f,fc,FWHM_tc,squared)
%
% Applies complex Morlet wavelet transform to the timeseries stored in the
% matrix x with size (ntimeseries x ntimes). It returns a wavelet coefficient map (by default
% squared)
%
% INPUTS:
% ... |
3088b2740d5d04c9bec4046127d556a44a1bcf21e9716e7e55b41b1e3d0e74fb | MATLAB | 3,492 | 103 | function [b,idx,outliers] = deleteoutliers(a,alpha,rep);
% [B, IDX, OUTLIERS] = DELETEOUTLIERS(A, ALPHA, REP)
%
% For input vector A, returns a vector B with outliers (at the significance
% level alpha) removed. Also, optional output argument idx returns the
% indices in A of outlier values. Optional output argum... |
0c9df917f27bddc4afd49d79f69c22e4fe15483c16e4c257df04daea8339ffb9 | MATLAB | 3,495 | 87 | % COMPUTEMATCHEDFANOFACTOR Compute Fano Factor for matched distributions
%
% [FF, FF_SE] = computeMatchedFanoFactor(meanA, meanB, varA, varB, num_resampling)
% Computes the Fano Factor for two datasets with matched mean distributions
% through iterative resampling. The Fano Factor represents the slope of the... |
80f31e57c858bdc3a4883f72cbe075ff3d726bfd78e699f77abcc0bb3d77d839 | MATLAB | 3,503 | 84 | function [ResultMap1,ResultMap2,ResultMap3,ResultMap4,res]=restgca_coefficient_XQ(AROITimeCourse, ABrain4D,Order,theCovariables)
ResultMap1={};ResultMap2={};ResultMap3={};ResultMap4={};
nDim4 = size(AROITimeCourse,1);
% [nDim1, nDim2, nDim3, nDim4]=size(ABrain4D); % component by QX
% ... |
df91fc528147c12a028bf6c17383b31aa59291068ca904b69c13e7a2b1daff6b | MATLAB | 3,506 | 100 | function Y_rand = moran_randomization(Y,MEM,n_rep,varargin)
% MORAN_RANDOMIZATION Null model for spatially auto-correlated data.
% y_rand = MICA_MORAN_RANDOMIZATION(y,MEM,n_rep,varargin) computes
% random values x_rand with similar spatial properties as the input data
% x. x is a n-by-1 vector of observations, ... |
0faf43527d48fa8ae7853799e7f1735bfcb0b73f438e5c3e8fdbcf34d542b011 | MATLAB | 3,508 | 96 | function source_space_full_group_pipeline_V1()
% Example for the template- and surface-based full pipeline, using the
% function nst_ppl_1st_level_channel_V1.
%
% This script downloads some sample data of 10 "dummy" subjects (27 Mb)
% Total max amount of data to download: (TODO) Mb, the user is asked for download... |
33e0f1f90f5df7d4eca041cb0210c85dd72ab0c5d18b334ae89ccf60bd4713c8 | MATLAB | 3,509 | 101 | function FC_project = get_network(FC_project,network)
old_path = pwd;
switch FC_project.atlas
case 1
LN = [1,2,3,4,5,6,7,8,9,10,11,12,15,16,25,26,57,58,61,62,65,66,67,68,81,82,83,84,85,86,87,88,89,90];
SN = [33,34,147:152];
DAN = [1,2,5,6,51,52,61,62];
DMN = [19,20,25,26,3... |
e7801c04fdc20329eda09d80d9cffee4e7e96c5edbe0df68f83b6e84573ad6a0 | MATLAB | 3,510 | 100 | function [cmat, band_indexes] = nst_math_build_basis_dct(nsamples, sampling_rate, freq_ranges, ortho)
% build_basis_cosine - Build a Cosine basis within specific frequency
% ranges (or bands)
%
% Synopsis
% [cmat] = build_basis_cosine(nsamples, sampling_rate, freq_ranges)
%
% Description
% build an orthogonal matri... |
215b07a3f59611646aa240ee614cc76b4596faf0dd31c9fe887f4dd2fc925ca6 | MATLAB | 3,511 | 117 | function AS_ShowGCmatrixGUI
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;
SelMod.fig = figure('position',[MIDPOINT(1)-POSSIZE(1)/4,MIDPOINT(2)-POSSIZE(2)/4,P... |
054d0a8e847ee152efdd890ab6be13c759c4ea2bd3ad2e61837510436a9df080 | MATLAB | 3,513 | 109 | function [Rlatt,Rrp,ind_rp,eff] = latmio_und(R,ITER,D)
%LATMIO_UND Lattice with preserved degree distribution
%
% [Rlatt,Rrp,ind_rp,eff] = latmio_und(R,ITER,D);
%
% This function "latticizes" an undirected network, while preserving the
% degree distribution. The function does not preserve the strength
% d... |
ac740daa3873b74ea7aba5c842ccc0c7cba37c0245fb7214dd3f1abc99536dd9 | MATLAB | 3,513 | 134 | function varargout = fdr(varargin)
% Computes the FDR-threshold for a vector of p-values.
%
% Usage:
% [pthr,pcor,padj] = fdr(pvals)
% fdr(pval,q)
% fdr(pval,q,cV)
%
% Inputs:
% pvals = Vector of p-values.
% q = Allowed proportion of false positives (q-value).
% Defa... |
a68401db411727a1a9e79b2fd21ee520dbbb764477f91dd8eba3bfdf82ff6c1a | MATLAB | 3,514 | 44 | % SCHEMABALLUNIT Unit tests for schemaball.
classdef schemaballUnit < matlab.unittest.TestCase
methods (Test)
% Verify all errors
function verifyErrorsWarnings(tc)
tc.verifyError(@() schemaball([],[],[],[],[]) ,'MATLAB:TooManyInputs')
tc.verifyError(@... |
1f3145c7e643ec285015004c27db528aa987221f30cdbeb1c909032314555858 | MATLAB | 3,515 | 105 | function Binned_y = Model_2State_fitLocError(parameter_guess, JumpProb, data_to_fit)
%Model_2State_fitLocError 2-state model, fitted localization error
dT = data_to_fit.dT;
HistVecJumps = data_to_fit.HistVecJumps;
dZ = data_to_fit.dZ;
HistVecJumpsCDF = data_to_fit.HistVecJumpsCDF;
ModelFit = data_to_fit.ModelFit;
Z_co... |
134268950e137007fc95f1ca16fde6eb8baf7265020736c65c85639068d9c645 | MATLAB | 3,520 | 112 | function [sr, PL_bin, PL_wei, PL_dis, paths] = navigation_wu(L, D, max_hops)
% Navigation of connectivity length matrix L guided by nodal distance D
%
% % Navigation
% [sr, PL_bin, PL_wei] = navigation_wu(L,D);
% % Binary shortest path length
% sp_PL_bin = distance_bin(L);
% % Weighted shortest path length
% sp_PL_wei... |
05bb9c1070e20c81a4850745619584f94a2d4c9a4c5964521c11807b3082bd04 | MATLAB | 3,524 | 121 |
function [zmap]=stats_high_spec(freq1,freq2,w)
ntrials=size(freq1.powspctrm,1);
%Requires converting NaNs values into zeros.
no1=freq1.powspctrm;
no2=freq2.powspctrm;
no1(isnan(no1))=0;
no2(isnan(no2))=0;
%%
freq1.powspctrm=no1;
freq2.powspctrm=no2;
%% statistics via permutation testing
% p-value
pval = 0.05;
% con... |
26b117866c070147fcacf5e438871b3be5b2aac532ceb6b59ad8e7edb844d1f9 | MATLAB | 3,528 | 102 | function over_subject_results = i_make_t_stat_fmri_over_subjects(parameters, subjects, bad_subjects, models_to_use)
%% over_subject_results = i_make_t_stat_fmri_over_subjects(mainpath, subjects, bad_subjects, models_to_use)
%mainpath = '/project/3018037.01/Experiment3.2_ERC/AnalysisFolder/scripts/scriptTemplates/..';
t... |
8d1723ad5a2ab86f290276e28ff15c02ff1bcd898b5eab2b93074f3d613b4731 | MATLAB | 3,532 | 87 | function jds_chainIsolatedAssemblyStrengthREM(animalprefixlist,area,state)
%JDS_CHAINISOLATEDASSEMBLYSTRENGTHREM Assembly reactivation in chain vs isolated ripples.
% jds_chainIsolatedAssemblyStrengthREM(animalprefixlist,area,state)
% compares peak z-scored assembly reactivation strength within chain
% cortical r... |
739885c2ece065222469201e076eca710015d878264d60ab1d695cf4b4d43a7e | MATLAB | 3,534 | 97 | % Demonstrate how spin rotation works with a faked dataset in FreeSurfer fsaverage5
% Requires AxelRot.m (included in this directory) from file exchange,
% https://www.mathworks.com/matlabcentral/fileexchange/30864-3d-rotation-about-shifted-axis?focused=5191309&tab=function
% & installation of FreeSurfer Matlab toolbo... |
e9d4d83442b32adac6d0fff8d66dbbbdca7f7e96c3aaa17f156154bc7362e88d | MATLAB | 3,545 | 92 | function OUT = cluster_DTI_perm_2groups_3(S_fin)
%combining original and permuted clusters
%this function works in connection with the previous one
% Leonardo Bonetti, Aarhus, 22/12/2020
%indexing and loading permuting clusters
a = dir([S_fin.outdir '/' S_fin.analysis_name '_clust_perm*']);
if ~isempty(a) %if there ... |
d4a6e1653ee164d29cbd1c640ad64a57681df9ba54bef21b6fb600c392e20640 | MATLAB | 3,553 | 72 | classdef DiagnosticPlot < handle
properties
edge_test_options
network_test_options
edge_test_result
network_atlas
networkTestResult
end
methods
function obj = DiagnosticPlot(edge_test_options, network_test_options, edge_test_result, network_atlas, networkTes... |
309b4100c36ed9fbeb9be9e81dcd9e744c3d2f4ac3269f8f3ab469851701d35d | MATLAB | 3,557 | 121 | function [SPL,hops,Pmat] = distance_wei_floyd(D,transform)
% DISTANCE_WEI_FLOYD Distance matrix (Floyd-Warshall algorithm)
%
% [SPL,hops,Pmat] = distance_wei_floyd(D,transform)
%
% Computes the topological length of the shortest possible path
% connecting every pair of nodes in the network.
%
% Inputs:
%... |
0608d48391400cb69f7f10d5f7abadf636c542ac4b6ce8dfd6bf9709e64ff2de | MATLAB | 3,560 | 112 | %--------------------------------------------------------------------------
% Till Habersetzer, 05.07.2025
% Communication Acoustics, CvO University Oldenburg
% till.habersetzer@uol.de
%
% Description:
% Master script for running the complete MEG-audio neural decoding
% analysis pipeline (without plotting). It orc... |
7436e5fed90737c3a3aad7af95634a33f55a00d1bea33d109b985781f6f6a76e | MATLAB | 3,568 | 84 | % When you load any ANALYZE or NIfTI file with 'load_nii.m', and view
% it with 'view_nii.m', you may find that the image is L-R flipped.
% This is because of the confusion of radiological and neurological
% convention in the medical image before NIfTI format is adopted. You
% can find more details from:
%
%... |
1d73e814b3bbc0494921acced58fb16cf8e13d5ff7f0301648881eb058d4debb | MATLAB | 3,579 | 107 | function [R,eff] = randmio_und_connected(R, ITER)
%RANDMIO_UND_CONNECTED Random graph with preserved degree distribution
%
% R = randmio_und_connected(W,ITER);
% [R eff] = randmio_und_connected(W, ITER);
%
% This function randomizes an undirected network, while preserving the
% degree distribution. T... |
9465a7509d8227782bcc84f73d203f1a286fe9cf9b4f6f5c3bb14914e829fe61 | MATLAB | 3,583 | 86 | function [embedding, scaled_eigval] = diffusion_mapping(data, n_components, alpha, diffusion_time, random_state)
% DIFFUSION_MAPPING Diffusion mapping decomposition of input matrix.
% embedding = DIFFUSION_MAPPING(data,n_components,alpha,diffusion_time)
% computes the first n_components diffusion components of ma... |
76060c3c9d4813ea5c97b6b41d945bb11f9c3a3de6184f3d2fb377d019392ea9 | MATLAB | 3,587 | 106 | function run_permcp(tensorname,method,minF,maxF,nreps,shiftAmount)
%PERMCP Computes a permuted CP decomposition for several choices
% of the number of components (minF up to maxF) and a given
% number of repetitions using different random initializations.
% It assumes each fiber in the tensor is a flatt... |
cd8b2b3ae78d065bf1b8cefaac7ad5bc2c15a522e80a60068b5b69f89914081b | MATLAB | 3,588 | 93 | % Function to generate a p-value for the spatial correlation between two parcellated cortical surface maps,
% using a set of spherical permutations of regions of interest (which can be generated using the function "rotate_parcellation").
% The function performs the permutation in both directions; i.e.: by permute both... |
690065c59813a2a46bf4dc8ceb2299abc1d16c9a6b990556221b41dda11a63cb | MATLAB | 3,609 | 81 | function surface_template_full_group_pipeline_V1()
% Example for the template- and surface-based full pipeline, using the
% function NST_PPL_SURFACE_TEMPLATE_V1.
%
% This script downloads some sample data of 10 "dummy" subjects (27 Mb),
% as well as the Colin27_4NIRS template (19 Mb) if not available.
% For the ... |
b7e54804e4292454dc31c39b1d4baf94ec6263ba881f8e00161bdd96406d3906 | MATLAB | 3,610 | 73 | function ROI_final_pos = drawROIsOnCortex(ax, net_atlas, ctx, mesh_alpha, ROI_radius, view_pos, surface_parcels, color_mode, color_mat)
%DRAWROISONCORTEX Draw ROIs on cortex mesh
% net_atlas: relevant NetworkAtlas object
% ctx: MeshType object determining what mesh inflation value to use
% mesh_al... |
a75399d895cb83388ea21dc6b3f715642bbcde034a139302dc199e7c61b71d7d | MATLAB | 3,631 | 115 | %--------------------------------------------------------------------------
% Till Habersetzer, 20.06.2025
% Communication Acoustics, CvO University Oldenburg
% till.habersetzer@uol.de
%
% This script serves as a visualization tool for pre-computed Auditory
% Evoked Field (AEF) data, using the FieldTrip toolbox. It l... |
254656cb1f278f55ec205406302940e801f7b2490d075c4b21a8cb6ce53f0273 | MATLAB | 3,632 | 100 | function [B,E,K] = evaluate_generative_model(A,Atgt,D,modeltype,modelvar,params)
% EVALUATE_GENERATIVE_MODEL Generation and evaluation of synthetic networks
%
% [B,E,K] = EVALUATE_GENERATIVE_MODEL(A,Atgt,D,m,modeltype,modelvar,params)
%
% Generates synthetic networks and evaluates their energy function (see
% ... |
372cd94f4db2d820831109b9dc33b3ef238aca12f6b914c7574ae57e9befcf24 | MATLAB | 3,636 | 105 | function [Mreordered,Mindices,cost] = reorder_matrix(M1,cost,flag)
% REORDER_MATRIX Matrix reordering for visualization
%
% [Mreordered,Mindices,cost] = reorder_matrix(M1,cost,flag)
%
% This function rearranges the nodes in matrix M1 such that the matrix
% elements are squeezed along the main diagonal. T... |
558276fc32fbe4e65567ae80c075fd1a51547990fd15999e2a44f81238ef8ccc | MATLAB | 3,638 | 81 | classdef MultiLevel < nla.edge.permutationMethods.Base
%MULTILEVEL Multilevel permutation method
%
% multi-level strategy = multiLevel()
% multi-level strategy = the object which will be doing the permutations the data. The functional
% connectivity is permuted
%
% needed for methods:
... |
2ccf011de24db8d0e7e501668391074392fff4a306b3085a57974ded49740948 | MATLAB | 3,639 | 96 | function [info]=Getifh(filename)
%
% Program to read 4dfp image header.
%
% Yi Su, Jan 2011
info=[];
%Processing filename
[path,name1,ext1]=fileparts(filename);
[dum,name2,ext2]=fileparts(name1);
if (isempty(ext1))
name=[name1 '.4dfp.ifh'];
elseif (isempty(ext2)||~strcmp(ext2,'.4dfp')||~strcmp(ext1,'.ifh'))
... |
ccae76b39a48dc7490906f79b2f01f3808fbc54a79e225300771bf2848fd75c9 | MATLAB | 3,642 | 140 | function [Eres,prob_SPL] = resource_efficiency_bin(adj,lambda,SPL,M)
% RESOURCE_EFFICIENCY_BIN Resource efficiency and shortest-path probability
%
% [Eres,prob_SPL] = resource_efficiency_bin(adj,lambda,SPL,M)
%
% The resource efficiency between nodes i and j is inversly proportional
% to the amount of... |
059cbc5ffe166b8946200be5e4d173fc7aedcb0ca7a818b1c443b5a0fbdc4271 | MATLAB | 3,648 | 136 | function pval = computePVal(kA, muA, varA, kB, muB, varB)
% Compute the p-value for rnaseqdedemo.
pval = ones(size(kA));
p_A = muA ./varA;
r_A = (muA.^2)./(varA-muA);
p_B = muB./varB;
r_B = (muB.^2)./(varB-muB);
kS = kA + kB;
p_obs_0 = nbinpdf(kA, r_A, p_A) .* nbinpdf(kB, r_B, p_B);
nf_idx = isfinite(p_obs_0);
p_ob... |
e1cf20d5221c714272a4aab66d3c40595f51c48e5f5175d50d04e77e0fccaf0e | MATLAB | 3,656 | 75 | function j_check_voxel_neighborhood(mainpath, subjects, bad_subjects)
%% j_check_voxel_neighborhood(mainpath, save_dir, subjects, bad_subjects)
subject_counter = 0;
hemispheres = {'lh', 'rh'};
visual_areas = {'V1', 'V2', 'V3'};
perc_layers = [];
neighborhood = [];
num_voxel = [];
for subject = setdiff(subjects, bad_su... |
570d07f37a70034b7e0ff6434d74bd800d8ca5abf504cb8602dc8195e52297d7 | MATLAB | 3,659 | 106 | function [aligned, xfms] = procrustes_alignment(gradients,varargin)
% PROCRUSTES_ALIGNMENT Performs a Procrustes alignment between gradients.
%
% aligned = PROCRUSTES_ALIGNMENT(gradients,varargin) performs a singular
% value decomposition of the vectors in cell array gradients to align
% them. Valid name-value ... |
40b14954729117b9595bcb9cdeadffe8fb8f1f39c3836c54a850a832c5333df9 | MATLAB | 3,665 | 111 | function cluster_performance(data_dir)
%
% Compute the Dunn's index, Calinski-Harabasz (CH) index and average
% Silhouette coefficient for each value of K to assess clustering
% performance.
%
% INPUT:
% data_dir directory where the results from K-means are saved
%
% OUTPUT:
% dunn_score Dunn's index computed ... |
8e43c44c10831a850eda913db14e46827c6aead943af39d3aa8b7e18e0fe4794 | MATLAB | 3,668 | 176 | function [beta, tstr, ha] = mipp_resQ_plot(S, xps, h, h2, opt)
% function beta = resQ_plot(S, xps, h, h2, opt)
error('replaced by v2')
if (nargin < 3), h = gca; end
if (nargin < 4), h2 = []; end
if nargin < 5
opt = mdm_opt();
opt = resQ_opt(opt);
end
ind = ones(xps.n, 1, 'logical');
S = abs(S);
if ~isfiel... |
8480a4fcf39bc8f82bee478ab3b4db4454f1bbb86fa2eed5b18d4241dd7b4ce9 | MATLAB | 3,669 | 113 | function data = SurfStatReadData( filenames, dirname, maxmem )
%Reads data (e.g. thickness) from an array of .txt or FreeSurfer files.
%
% Usage: data = SurfStatReadData( filenames [, dirname [, maxmem ]] );
%
% filenames = .txt, .mgh or FS file name (n=1) or n x k cell array of file
% names. If t... |
dc8e77bdea3e5d7f9d8087604bc07c267ee6017a5936d5d4fd90f2cfa8f0b881 | MATLAB | 3,684 | 107 | function [ MATF ] = generalCoupling_prepareplotting_LBPD_D( POS, NEG, p_thresh, label_path, pos_lab_only )
% It creates an ROIs x ROIs matrix, ordering ROIs according to labels
% provided (example that I provide consists in AAL ordered like LRLRLR),
% showing the sum over time of significant connections between ROIs.
... |
408e018d656f0ec77a1dd37048532438c776cb106b8a465602ea352b4f56cdc4 | MATLAB | 3,697 | 72 | function O = GED_SingleSubjects(S)
O = [];
addpath('/projects/MINDLAB2017_MEG-LearningBach/scripts/Mattia')
comps2see = S.comps2see;
list = S.list;
shr = 0.01; % value between 0 and 1 (0 small perturbation, 1 big perturbation) - for Mattia regularisation (until 0.001 it works for restoring the full rank of th... |
65347be0def1bbb2bc032d719f75f3aa08245044c7f05554103cd2b4ea80cc2f | MATLAB | 3,697 | 70 | classdef StudentTTest < handle
%STUDENTTTESTs Student's t-test (t-test assuming normal distributions)
properties (Constant)
name = "students_t"
display_name = "Student's T-test"
statistics = ["t_statistic", "single_sample_t_statistic"]
ranking_statistic = "t_statistic"
al... |
238a7c85c98253c2aa5ed41d5bfe946ec5af21f46b40522ede9053c18f7589af | MATLAB | 3,698 | 148 | % Load NIFTI header extension after its header is loaded using load_nii_hdr.
%
% Usage: ext = load_nii_ext(filename)
%
% filename - NIFTI file name.
%
% Returned values:
%
% ext - Structure of NIFTI header extension, which includes num_ext,
% and all the extended header sections in the header extens... |
47f90bef5f0cd499e0945f97ebf6a904dd5107033fb8fff14869a02a6cda84fc | MATLAB | 3,707 | 105 | function PlotRadarGraph_multi(Data,seednum,maxpercent,Patchcolor,markersize,sepnum)
pathmfile = which('AS_WTA_GUI.m');
[pat nam ext] = fileparts(pathmfile);
load(fullfile(pat,'SEEDCOLOR.mat'))
load(fullfile(pat,'JETcode.mat'));
Hsize = get(0,'ScreenSize');
Bsize = min(Hsize(3),Hsize(4));
BsizeUsed = floor(Bsiz... |
76abef0641297cb9fbac378a110c0db6334ad301b33464e9fedd8f6557f82ac6 | MATLAB | 3,708 | 85 | classdef Base < nla.TestResult
%Base class of results of edge-level analysis
%
% :param size: The size of the Trimatrix being analyzed
% :param prob_max: The threshold for the p-value
properties
coeff % Fisher transformed r-value
prob
prob_sig
avg_prob_sig = NaN
... |
c68127f7935c6852cb1c59425b49ca061379e9f977c5844e94a036aa870ae64c | MATLAB | 3,719 | 97 | function varargout = process_nst_snap_montage( varargin )
% @=============================================================================
% This function is part of the Brainstorm software:
% http://neuroimage.usc.edu/brainstorm
%
% Copyright (c)2000-2016 University of Southern California & McGill University
% This ... |
0772d4b70df2a43c2573ef9be25995f5324e9da0dc6cfe69fd0c2773eb1d1dd1 | MATLAB | 3,720 | 176 | function [beta, tstr] = resQ_plot(S, xps, h, h2, opt)
% function beta = resQ_plot(S, xps, h, h2, opt)
if (nargin < 3), h = gca; end
if (nargin < 4), h2 = []; end
if nargin < 5
opt = mdm_opt();
opt = resQ_opt(opt);
end
ind = ones(xps.n, 1, 'logical');
ind(1:2) = 0;
S = abs(S);
if ~isfield... |
51a8577c883aea991c0933e8e1b47473cf1edd1f5b526400c4f4d4a4e90ce2b9 | MATLAB | 3,726 | 124 | %% read
prot=xlsread('L:\Elite\LARS\2014\mai\transfection 3rd paralell\TransFecMCR27logBm2withFugeneandControl.xlsx');
%% check normal ratio distribution
histfit(prot(prot(:,15)~=0,15)) % check for median ratios heavy normal to light normal
xlim([-3 3])
hist(prot(prot(:,15)~=0,15),[100]) % check for median rat... |
b874641ec395e9ce66b0fe64ac99d7acdc8f782b472c3893d04893e6137c0b23 | MATLAB | 3,726 | 90 | function model = nst_glm_apply_filter(model,filter_name, varargin )
%NST_GLM_APPLY_FILTER Apply filter on the regressor of the column matrix
%but only apply when it's ok to apply it (for exemple, we don't apply a
%high-pass filter on the constant regressor). Condition about what filter
%can be applied can be found in m... |
78000171865e0b2d45d78345ee96af0c1819f8cf2a84de655729092d633704b8 | MATLAB | 3,729 | 83 | % current working directory needs to be /path/to/scripts
mainpath = pwd;
addpath([mainpath filesep 'toolboxes' filesep 'OpenFmriAnalysis'])
addpath([mainpath filesep 'toolboxes' filesep 'spm12'])
tvm_installOpenFmriAnalysisToolbox;
%%
tic;disp('doing boundary registration...')
configuration = [];
configuration.i_Subje... |
9ad6914fc59f0ddb572266d322dcf6242b6efecdc49ace065c408245d4512d12 | MATLAB | 3,729 | 122 | function S2 = convert_surface(S,varargin)
% CONVERT_SURFACE Converts surfaces to MATLAB or SurfStat format and
% writes new surface files.
%
% S2 = CONVERT_SURFACE(S) converts surface S to SurfStat format. S can
% either be a file (.gii, .mat, .obj, Freesurfer), a loaded variable (in
% SurfSt... |
f89aa23e4d69f2491d4a284829e183b866d1e4ced24b2839c80d7e8e73a96679 | MATLAB | 3,732 | 91 | classdef RemoteDataTest < matlab.unittest.TestCase
properties
tmp_dir
end
methods(TestMethodSetup)
function create_tmp_dir(testCase)
tmpd = tempname;
mkdir(tmpd);
testCase.tmp_dir = tmpd;
end
end
methods(TestMethodTeardown)
... |
e29b2ecde4d5137a4d25532d87636c748ea93387b22455f79c65102959b7dffc | MATLAB | 3,735 | 114 | % Input an [x,y] list of localization positions and generate a mask image
% enclosing the area they comprise. The image can optionally be resized to
% obtain a desired pixel size
%
% Inputs
% xy - two-column matrix with x and y coordinates of localizations in
% presumed units are pixels, since this makes... |
55b4147a7cf8b850e94a957607490f4b0d53f41f006f24d38ec56b4d1c3f3555 | MATLAB | 3,741 | 136 |
function [zmap]=stats_high_granger(g2,g,i,j)
%ntrials=size(freq1.powspctrm,1);
a=[i j];
ntrials=size(g2, 5);
%Requires converting NaNs values into zeros.
no1=squeeze(g(a(1),a(2),:,:,:));
no2=squeeze(g2(a(1), a(2),:,:,:));
no1(isnan(no1))=0;
no2(isnan(no2))=0;
% replicating time frequency matrix ntrials time
%no1=r... |
445f22f713737ff97ccebd262c406fd3791c5b0f704f16dfc8295b07f50131ea | MATLAB | 3,763 | 109 | function t = term( x, str );
%Makes a vector, matrix or structure into a term in a linear model.
%
% Usage: t = term( x [, str] );
%
% Internally a term consists of a cell array of strings for the names of
% the variables in the term, and a matrix with one column for each name,
% which can be accessed by char ... |
44b8e5383e52bc2332b1011cf00cc5246a55f1d3d451ab9ed59c000e578f04fc | MATLAB | 3,788 | 116 | % This script loads 7 unweighted, undirected adjacency matrices
% corresponding to a clique, chain, ring, 1D lattice, star, rich-club, and
% bi-modular toy networks (all graphs have 50 nodes). The following
% efficiency measures are computed for each graph:
%
% - prob_SPL: probability of one particle traveling through... |
9f39925ca2a2212667edb046abba5221e2c6b8ca075c79656383578f6ebfc54a | MATLAB | 3,809 | 88 | function [f,F]=motif4funct_bin(A)
%MOTIF4FUNCT_BIN Frequency of functional class-4 motifs
%
% [f,F] = motif4funct_bin(A);
%
% *Structural motifs* are patterns of local connectivity in complex
% networks. In contrast, *functional motifs* are all possible subsets of
% patterns of local connectivity e... |
9f2b933e0e84647b6e7acd0219310d9e0703c80182dd52ce710ee0a961da7cfb | MATLAB | 3,812 | 76 | classdef WelchTTest < handle
%WELCHTTEST Welch's t-Test (t-test assuming normal distributions with unequal variances)
properties (Constant)
name = "welchs_t"
display_name = "Welch's T-test"
statistics = ["t_statistic", "single_sample_t_statistic"]
ranking_statistic = "t_statisti... |
77632bda4dd6c39ceb908064d7ba4a3c2f291eb37eb160aae7f20734bab0ddfd | MATLAB | 3,815 | 112 | function Plot_K_links_in_cortex(data_dir,save_dir,selectedK,parcellation)
%
% Plot the links between the areas with positive values in the vectors of
% the centroids in a glass cortex.
%
% INPUT:
% data_dir directory where LEiDA results are stored
% save_dir directory to save results for selected optimal K
% ... |
90c58a6285189e68f1bf86cdf9f64476dc03ace5909a74c6f40ab40635d7917c | MATLAB | 3,824 | 179 | function dFC_project = get_roi_lobe(dFC_project)
if dFC_project.atlas==1
ROI_location = {
'Frontal'
'Frontal'
'Frontal'
'Frontal'
'Frontal'
'Frontal'
'Frontal'
'Frontal'
'Frontal'
'Frontal'
'Frontal'
'Fro... |
100a13bc53903e4185451a912612c2a57fd48f0e39e4741c9019b2289d58a7d7 | MATLAB | 3,826 | 103 | classdef UnconstrainedBlocks < nla.helpers.stdError.AbstractSwEStdErrStrategy
properties (SetAccess = protected)
REQUIRES_GROUP = true;
end
methods
function contrastStdErr = calculate(obj, sweStdErrInput)
%rename variables for ... |
6a3d6f317c9d2f2b7c3ba5110de6bcc7b59644d774510531846dc2a03f4f6f17 | MATLAB | 3,829 | 145 | function [outpict inclass]=imcast(inpict,outclass)
% [OUTPICT INCLASS]=IMCAST(INPICT,OUTCLASS)
% Scale and recast image data and return class of input
% This is more succinct than using getrangefromclass()
% and im2double(), im2uint8(), etc.
%
% This is a convenience not only because it is suc... |
3605f0920a76a417edcd2ee2006e32e46a7d17e5c385f486413908d3789ee2ae | MATLAB | 3,833 | 85 | function Plot_K_overlap_yeo_nets(data_dir,save_dir,selectedK,parcellation)
%
% Compute the overlap between each PL state (1 to selectedK) and the RSNs
% defined in Yeo et al., (2011). Plot the overlap between each PL state and
% each of the Yeo RSNs.
%
% INPUT:
% data_dir directory where LEiDA results are stored
%... |
c01d301a8e33aecd3ff8de14222deea4c29c78bd9ef6c0f59a9674f657a31a62 | MATLAB | 3,838 | 167 | clear
maindir = 'D:\DATA_LOCAL\MIPCART pilot\Histology\Sorterad';
fnl = fix.findFiles(maindir, '*HE*.jpg');
% inam = {'Meningioma (Ref)', '102', '103', '105', '106', '12', '15', '3', '5', '8'};
inam = {'Ref. (meningioma)', 'Untreated (LNCaP)', ' ', ' ', ' ', 'Treated (LNCaP)', ' ', ' ', ' ', ' '};
ssf = [1 5 5 5 5 ... |
1625b22dc432d7cee54aec0a9a877d8b12a98a4545246ba90ba1044db338a349 | MATLAB | 3,854 | 142 | % PAD_NII: Pad the NIfTI volume from any of the 6 sides
%
% Usage: nii = pad_nii(nii, [option])
%
% Inputs:
%
% nii - NIfTI volume.
%
% option - struct instructing how many voxel to be padded from which side.
%
% option.pad_from_L = ( number of voxel )
% option.pad_from_R = ( number of voxel )
% option... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.