sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
f75293fdad33b2660d38c7a46790c3ecc7c4a50f0a15955e644fbc659c627b0b | MATLAB | 9,064 | 181 | % hMRI processing
%
% Computation of quantitative maps from acquired MPMs. The script is
% based on the batch GUI of the SPM12 toolbox. To run the script, both the
% hMRI and SPM12 have to be installed. The script gets the root directory
% of the SPM12 toolbox from the matlab search path. All input files are
% define... |
0aedd8d8718131af8902b86f45ea57c0221ff48a944186a5489bab4adc2ae099 | MATLAB | 9,065 | 241 | function [mainNBSPredict] = get_NBSPredictInput(NBSPredict)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% get_NBSPredictInput checks NBSPredict structure provided and set default
% parameters if no provided. It also loads correlation matrices using
% a directory containing correlation ma... |
11827c34ea3261d984dac371cf931d880de35c05999f5ff62acb31843afee574 | MATLAB | 9,073 | 66 | function map = viridis(N)
% Perceptually uniform sequential colormap from MatPlotLib.
%
% Copyright (c) 2017-2020 Stephen Cobeldick
%
%%% Syntax:
% map = viridis
% map = viridis(N)
%
% Colormap designed by Eric Firing, Nathaniel J. Smith, and Stefan van der Walt.
%
% For MatPlotLib 2.0 improved colormaps were created... |
c9e70af1f300fa22337059294dcd1c045ba66755cfb8b43643d270262a3466d8 | MATLAB | 9,078 | 220 | % POP_IMPORTGROUPVAR - import a group variable from a ASCII file and
% manual entry.
%
% Usage:
% >>
%
% Inputs:
%
% Outputs:
%
% See also:
% pop_studydesign,
%
% Author: Ramon Martinez-Cancino, SCCN, 2014
%
% Copyright (C) 2014 Ramon Martinez-Cancino,
%
% This file is part of EEGLAB, see http://www.eeglab... |
36a4e8056128390871329a4317c4f4e2be29a6fb2fb1c45dac61a3d8d2553456 | MATLAB | 9,083 | 274 | clc;
clear;
addpath('/cbica/home/lihon/code/Download/cifti-matlab-master');
res_dir = '/cbica/home/lihon/comp_space_recover/ABCD_comp/dl_prediction/pred_res_cog_abcc_bl_cv/non_dl_pnc_res';
dat_dir = '/cbica/home/lihon/comp_space_recover/ABCD_comp/dl_prediction/data_cog_pnc_cv';
num_r = 400;
ro_covars = 1; % 0: ba... |
232537c835305c9fe69b7faecbe2ae3a1fe91614c8c903bf074242762d0c9624 | MATLAB | 9,084 | 217 | function c = tapas_hgf_binary_pu_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the Hierarchical Gaussian Filter (HGF)
% for binary inputs in the *presence* of perceptual uncertainty.
%
% The HGF is the model introduced in
... |
b360c3c6aa5c95b90dc7fb525290bd5c218540aeac748931f2532b72a014aa47 | MATLAB | 9,086 | 199 | function [MRSCont] = osp_saveLCM(MRSCont)
%% [MRSCont] = osp_saveLCM(MRSCont)
% This function writes all MRS data loaded by OspreyLoad to separate
% LCModel .RAW files.
%
% One .RAW file is produced for unedited MRS data
% (PRESS, sLASER, etc.), four .RAW files are produced for MEGA-edited
% data (A, B, su... |
d2f126e3e806ac090a548e8c1ff338822180e703203d4908db9eb6ccd42b7aab | MATLAB | 9,088 | 217 | function c = tapas_ehgf_binary_pu_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the Hierarchical Gaussian Filter (HGF)
% for binary inputs in the *presence* of perceptual uncertainty.
%
% The HGF is the model introduced in ... |
58b70fa25ec07858b50574ef6cf8ab5f58d28f264f7e91ed831a8a0261433dba | MATLAB | 9,090 | 226 | % LOC_SUBSETS - Separate channels into maximally evenly-spaced subsets.
% This is achieved by exchanging channels between subsets so as to
% increase the sum of average of distances within each channel subset.
% Usage:
% >> subset = loc_subsets(chanlocs, nchans); % select an evenl... |
e76c1403dbcb523fb562f03040d83170c8ceed05df6401f11f8a38043425f9a1 | MATLAB | 9,099 | 191 | %% AFM_RegionAnalysis_Mapping.m by Julia Becker, 14/10/2021
% This script combines data about analysed AFM measurements from an
% experiment into a big table ('data'). It checks for several measurements
% at the same x/y coordinates and only keeps one (duplicate removal). It
% will also check how the actua... |
cfd5462ed60b650e697d10ffbc28cffde28ab9abb2610be75012ac86028d1097 | MATLAB | 9,103 | 266 | % (C) Copyright 2020 CPP visual motion localizer developpers
function [cfg] = setParameters()
%
% Initialize the parameters and general configuration variables
cfg = struct();
cfg.subject.askGrpSess = [false true];% this stops the GUI input for subject group. comment it if you want to ask for subje... |
a913ab0ce0c36957f21876ab5b20bcc2c02247920759a8ba6682200377c4a96c | MATLAB | 9,105 | 320 | %% script to generate channel reductions for the EGI 257 layout
%% load layouts
egi=ft_prepare_layout(struct('layout','conf/layouts/GSN-HydroCel-257-layout.mat'));
eeg1020=ft_prepare_layout(struct('layout','EEG1020'));
eeg1010=ft_prepare_layout(struct('layout','EEG1010'));
% now plot
figure
hold on
scatter(eeg101... |
5fcbb609686108f8b5f05558d61cb1a6eecf4bfe1bea1d49e09bfaeb9643e707 | MATLAB | 9,109 | 206 | function [varargout] = likGaussWarp(warp, hyp, y, mu, varargin)
% likGaussWarp - Warped Gaussian likelihood for regression.
% The expression for the likelihood is
% likGaussWarp( y | t ) = likGauss( g(y) | t ) * g'(y),
% where likGauss is the Gaussian likelihood and g is the warping function.
%
% The hyperparamete... |
d9c5f021e643c1e43f197fadf316c8e87c9dda1e8949a0402c375356bb7359e5 | MATLAB | 9,109 | 201 | function [x_data,xxline] = fg_bootstrap_two_groups(fig_num,B_L,group_1_data,group_2_data,group_1_counter,group_2_counter,log_scale,frequencies,CIU,CIL,freq_lims)
%Use bootstrapping for statistic of power spectra
%output gives the coordinates for points of significant difference
%input is figure number, the number of... |
ba318047023ea92a06dfe53f69c8e11f50c16762d62a8a6a878d7d7c9c0f503f | MATLAB | 9,123 | 200 | %% ########################################################################
% demo_analysis_1_1_detect_ripples_1_f
% #########################################################################
%
% Main analyses on simulated data. Yields plots utilized in Fig. 1.
%
% -----------------------------------------------------... |
d4eaf4616c87519047dc9eb44e4f818157f318b190358d22c53cc1c6e0c71026 | MATLAB | 9,127 | 243 | function [Y,motion_corr] = rigid_motion_correction(data_path,varargin)
% modified from NoRMCorre demo-1p
% https://github.com/flatironinstitute/NoRMCorre
% ZZ 2022
% applying the NoRMCorre motion correction algorithm on
% 1-photon widefield imaging data
% input:
% data_path: folder of a pre-processed data fil... |
89f27c7909249bb98cde23aeefd239f8f07e76cc4ab0e7018f220b6434c298d3 | MATLAB | 9,128 | 273 | function plotFigure2_muscimol(processedMuscimolPath, behaviorPath)
% Plot Figure 2. Muscimol data and inference model with lapse parameter.
% YOU MUST RUN processMuscimolData BEFORE RUNNING THIS FUNCTION
%INPUTS:
% muscimolPath = Local path to muscimol data downloaded from Zenodo.
% Folder contains the subfo... |
941bfce0a7a17a61939ca72d227408aa30a8e44095361ef1959977f7a701df1a | MATLAB | 9,130 | 242 | classdef tapas_Huge
%% tapas_Huge Hierarchical Unsupervised Generative Embedding
% This class implements the HUGE model. HUGE stands for Hierarchical
% Unsupervised Generative Embedding. It is a generative model for
% (task-based) fMRI data from heterogeneous cohorts. For more details on
% the theory behind the... |
3f287774f4a259a9cfb7e3345585c4743231c4e043d5ba83efb145991b902091 | MATLAB | 9,132 | 267 | classdef Layer < handle
%LAYER Base class for a network layer in a DagNN
properties (Access = public, Hidden, Transient)
net
layerIndex
end
methods
function outputs = forward(obj, inputs, params)
%FORWARD Forward step
% OUTPUTS = FORWARD(OBJ, INPUTS, PARAMS) takes the layer object OBJ
... |
60b81596d8c7794be71af05ca811e459d88e0f4d53dc93be720b2bdcd6353c5d | MATLAB | 9,135 | 278 | function plotbehav(T, depVar, outdir, pairwiseResults)
if nargin<3||isempty(outdir), outdir=pwd; end
if ~exist(outdir,'dir'), mkdir(outdir); end
if isstring(depVar), depVar=char(depVar); end
cstr = string(T.Condition);
cstr(cstr=="1")="Congruent"; cstr(cstr=="2")="Incongruent";
[chosenEffect, pcol] = chooseEf... |
a1823fa3ced2739cbee6ad40e1a66ef82e7e415d8d89907e362a572dbc47487f | MATLAB | 9,137 | 224 | function [Wrr,Wrf,outdegreeEE,outdegreeIE,outdegreeEI,outdegreeII,outdegreeEX,outdegreeIX,seqindX,seqindE,seqindI,presynIDE,presynIDI,presynIDX] = ...
generate_weights_broad_indegree(Ne,Ni,Nx,sigmaRX,sigmaRR,Prr,Prx,P_ts,TS_th,b1,varargin)
% GENERATE_WEIGHTS_BROAD_INDEGREE Connectivity with broad (Gamma-like) inde... |
c837af5ae3e4fc4d0e07b317492970bfddcc1717422185f2ec4b73fe873519bb | MATLAB | 9,143 | 267 | classdef Layer < handle
%LAYER Base class for a network layer in a DagNN
properties (Access = {?dagnn.DagNN, ?dagnn.Layer}, Hidden, Transient)
net
layerIndex
end
methods
function outputs = forward(obj, inputs, params)
%FORWARD Forward step
% OUTPUTS = FORWARD(OBJ, INPUTS, PARAMS) takes th... |
cfb37f42230ec3a284af0f7033fef69cca4b97e9cb5555b3fcf1432ec8e63a62 | MATLAB | 9,161 | 159 | %% Script to plot brain maps of cortical MIND associations.
% 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 so... |
1ab43f1522dd0fcce454141744764e6d3d278a1dce0ff3a3ea24d90916b23f22 | MATLAB | 9,176 | 299 | function OUT = get_contrast_indicator(DB,testfield,varargin)
% OUT = get_contrast_indicator(DB,testfield,varargin)
% OUT = get_contrast_indicator(DB,'Method','create')
% OUT = get_contrast_indicator(DB,'valence','load',OUT)
% OUT = get_contrast_indicator(DB,'valence','create',[],{'pos' 'neg'})
% OUT = get_contrast_indi... |
b2d6cc9c0984fa9e6528629ffd8a1ac062c684a6cf7dfa1decc2617daa3b1f31 | MATLAB | 9,180 | 246 | % ANOVA2_CELL - compute F-values in cell array using ANOVA.
%
% Usage:
% >> [FC FR FI dfc dfr dfi] = anova2_cell( data );
%
% Inputs:
% data = data consisting of PAIRED arrays to be compared. The last
% dimension of the data array is used to compute ANOVA.
% Outputs:
% FC - F-value for c... |
cfd679ece888423834b64adfbe12c87b424458879c53e6454388e6dba3b35e40 | MATLAB | 9,184 | 207 | function [data, settings, version] = readHD5(F)
% F: Key structure or full filename including path (for example '/path/Patchfile10.h5')
%
% data: all variables extracted from file
% settings: settings telegraphs from NPI amp
% ver: file version
if isstruct(F)
if count(experiment.ScanBehaviorFile & F)
F = f... |
907a7086697cc14c5e12fe0f5f25c1a24d44e6c93e56977f7d83a09e55e5086a | MATLAB | 9,185 | 207 | function plot(segStream, cfg, varargin)
% Plot the contents of a McsSegmentStream object with averages.
%
% function plot(segStream,cfg,varargin)
%
% Produces for each average object on overlay plot of the averages
%
% Input:
%
% segStream - A McsSegmentStream object
%
% cfg - Either em... |
b826e4aefa4a6b71474a7eef649bfdcfcd94a6dae8ae6b45f60ecc6b5853a569 | MATLAB | 9,187 | 242 | % sourceReconstruction_p.m
% source reconstruction of preprocessed MEG data using LCMV beamformer
settings.target_fs = 600; %sampling frequency
settings.lcmv_reg = 0.05;
settings.fres = settings.target_fs;
settings.smoothcortex = 0.3; %less smoothing
% epoch length
settings.winlength = 2*settings.target_fs;
% model or... |
fedb8e41dc67a3dfa40f8eefbdc2c3d7b047a2c1ce9e6f7db47f98459a469ad7 | MATLAB | 9,188 | 176 | 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... |
f1b26536aa7852a2f8fd91f4a0f018524a79377334054d047da1c92eeb9c5025 | MATLAB | 9,192 | 260 | function [newnode,newelem,newface]=meshrefine(node,elem,varargin)
%
% [newnode,newelem,newface]=meshrefine(node,elem,face,opt)
%
% refine a tetrahedral mesh by adding new nodes or constraints
%
% author: Qianqian Fang, <q.fang at neu.edu>
%
% input parameters:
% node: existing tetrahedral mesh node list
% ele... |
4bfce13a8f8e1835faf9ae2dcf1f1441ee3bd2d14177550c3c12a662a6e6142e | MATLAB | 9,193 | 246 | function [distmat,cfg] = mahal_iem_mds_xgen(dat,theta,task,cfg)
% [distmat,cfg] = mahal_iem_mds_xgen(dat,theta,task,cfg)
if nargin < 3
help mahal_iem_mds_xgen
error('missing input arguments!')
end
ntrl = size(dat,1); % number of timepoints
nsens = size(dat,2); % number of M/EEG sensors
... |
bd6ebde24281ab0c8827930644d87e6db346f9489149914514cd2f1ca9b50de0 | MATLAB | 9,194 | 223 | function varargout = check_logs_ui(varargin)
% CHECK_LOGS_UI MATLAB code for check_logs_ui.fig
% CHECK_LOGS_UI, by itself, creates a new CHECK_LOGS_UI or raises the existing
% singleton*.
%
% H = CHECK_LOGS_UI returns the handle to a new CHECK_LOGS_UI or the handle to
% the existing singleton*.
%
% ... |
56c2e38ee6a2acbe4956c0f4330f8c3d4a00964755538887f3c80004da291c69 | MATLAB | 9,199 | 212 | % pop_dipplot() - plot dipoles.
%
% Usage:
% >> pop_dipplot( EEG ); % pop up interactive window
% >> pop_dipplot( EEG, comps, 'key1', 'val1', 'key2', 'val2', ...);
%
% Graphic interface:
% "Components" - [edit box] enter component number to plot. By
% all the localized components are plotted. Comma... |
6b42c2c1acadbeaf012e6c9b925fd7fd71c64800588ac631ace1a1c177d9130b | MATLAB | 9,201 | 248 | % Prepare power data for statistical analysis and plotting the results including cortical and hippocampal PSD,
% and cortical region-wise Power differences between AD and control groups.
resultsDir = [main_path 'Results/source/'];
% Get a list of all subjects in the directory0
subjectFiles = dir(fullfile(resultsDir... |
2103cecde6f94ec1cdbb6e9b19f421f2f3bd0f6ca5692f571e343ef36cdc0820 | MATLAB | 9,203 | 254 | addpath(genpath(pwd));
% load data
load(fullfile('data', 'doseResponseData.mat'));
% define the curve type
[rowTotal, colTotal, ~] = size(conc);
maskPlot = SetCurveType(rowTotal, colTotal); % manually define the type of the dose-response curves
% set up the fitting
hillEq = @(a, b, c, x) a./(1+ exp(-b*(x-c)));
ft ... |
1d493a5891e0108e19796bc5578d404fd17339773e68ccab57b312ffbbfc3b79 | MATLAB | 9,206 | 220 | %% extract the beta parameters from ROIS
%from peak coordinates or centre of individual ROIs
% TACTILE MOTION LOCALIZER
% across two runs
clear all
%% from peak cooridinates
%get roi coordinates
r=readtable('/Volumes/IqraMacFmri/visTac/fMRI_analysis/code/roi/coordinates4.xlsx');
% check the roi label order
roiLabels =... |
7e816280d3b83e43a77da57033bbada5e19ea418ee8c4f95076a1a1157ebbf7e | MATLAB | 9,217 | 212 | function c = tapas_hgf_binary_pu_tbt_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the Hierarchical Gaussian Filter (HGF) for binary inputs in the
% *presence* of perceptual uncertainty with the additional twist that percep... |
b22c9ef60ddc9f7576f6bc2eec9b4786165ffe4ffc87aba8c7baa3e92970fe79 | MATLAB | 9,217 | 257 | function [J,Jfd,CRLB] = fit_Osprey_CRLB(dataToFit, basisSet, minKnotSpacingPPM, fitRangePPM,fitParams,refShift);
j = sqrt(-1); % i
nMets = basisSet.nMets;
nMM = basisSet.nMM;
nBasisFcts = nMets + nMM; % number of basis functions
lineShape = fitParams.lineShape;
ph0 = fitParams.ph0 * pi/180; %... |
3d556ffd533fa72f6399acd15dbd04804d5b5961fc4997d4d3083df45bea12a5 | MATLAB | 9,222 | 238 | %% fitglm_allpredictors_network.m
clear; close all; clc; warning('off');
scriptName = mfilename;
%% Ensure workers can see current code path (parfor safety)
p = gcp('nocreate');
if isempty(p); p = parpool; end
% Replicate current path on workers
pctRunOnAll addpath(genpath(pwd));
%% ---- Inputs (same dialog as before... |
af81405c13f5e6f67f8cc268a9bc0ad7a32a51b158c2168f73f1b14dfb708f6f | MATLAB | 9,223 | 205 | % op_preref.m
% USAGE:
% [refShift_ind_ini]=op_preref(in);
%
% DESCRIPTION:
% We will use a frequency cross-correlation approach on the
% Choline and Creatine singlets to generate a robust initial
% frequency guess for the robust spectral registration. This is
% especially useful for data with heavy frequency drift. T... |
b5f109ab435f4550ce007f0d1abf0f2ffe1c54af44cc8c2ee9da44146fa40e01 | MATLAB | 9,225 | 156 |
% Clear all variables
clear all
% Initialise SPM with fMRI defaults
spm('Defaults', 'fMRI');
% Initialise cfg_util configuration and set path accordingly
spm_jobman('initcfg');
% Define the directory for TPM files
tpm_dir = '/Users/az/Documents/MATLAB/spm12/tpm';
% Define the preprocessing directory
prepro_dir... |
de8be091a80e9ba5b66ef03d33f424eec78096d917d55131b58ef3be8339a494 | MATLAB | 9,234 | 205 | function c = tapas_hgf_ar1_binary_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the Hierarchical Gaussian Filter (HGF) for AR(1) processes
% for binary inputs in the absence of perceptual uncertainty.
%
% The HGF is the mod... |
ed82129e0b17308613ae0443b3fad00fa5c19c04a9405010532d3754e88cd013 | MATLAB | 9,241 | 276 | function [cfg] = checkParameters(cfg)
%
% Check that all parameters are sets. If not it uses the defaults.
%
% ``cfg.design.localizer``: switching this to ``MT`` (default) or ``MT_MST``
%
% - ``MT``: translational motion on the whole screen
%
% - alternates static and motion (left or r... |
e891baa5330894c9e81aa8143f9aec19b116adb7299e79313ab4616494b1500e | MATLAB | 9,242 | 237 | %% fitglm_allpredictors_network.m
clear; close all; clc; warning('off');
scriptName = mfilename;
%% Ensure workers can see current code path (parfor safety)
p = gcp('nocreate');
if isempty(p); p = parpool; end
% Replicate current path on workers
pctRunOnAll addpath(genpath(pwd));
%% ---- Inputs (same dialog as before... |
05eb7006e75e3605fea2f273b078043516c07da470ed3b23a1454469ceaf3910 | MATLAB | 9,243 | 210 | %*************************************************************************%
%*************************************************************************%
%fitTemplates: Detect spike and calculate the templates
%Simplified and commented by Madeny belkhiri 30/01/18.
%********************************************************... |
989102370da20c079933ec38503d6b76837313f86e52c0060bd998c1ac35b8bc | MATLAB | 9,245 | 261 | function SOMResults = Meta_Multivariate(MC_Setup,DB,nSOM,nIter,varargin)
% SOMResults = Meta_Multivariate(MC_Setup,DB,nSOM,nIter,[additional args])
%
% Additional args:
% 'mask', then mask image name
% 'data', followed by data matrix
%
% This is a clearing-house function to run multivariate-... |
ed4baea84b130f2093be9776a248614a96810f911cf0f545b2241725313f7d31 | MATLAB | 9,246 | 203 | classdef McsTimeStampStream < McsHDF5.McsStream
% Holds the contents of an TimeStampStream
%
% Fields:
% TimeStamps - (1xn) cell array, each cell holding a (1 x timestamps)
% vector of time stamps for each time stamp entity.
%
% The Info field and the other attributes provide general info... |
83de92ebcde050d0a5fde0b8ffdac0ccdd57755eb03f7266fd7ef6939456439c | MATLAB | 9,248 | 263 | function SuppFigure_V1(varargin)
%SUPPFIGURE_V1 Generate supplementary figure showing V1 experimental data analysis
%
% Purpose:
% Creates a three-panel figure showing V1 experimental data including
% normalization index distribution, correlation analysis, and tuning
% similarity control analysis.
%
% Inputs:
% ... |
b284bda315597ff8c9c54e53d9664ebb7e405f75efea62c781343f707555a7f8 | MATLAB | 9,256 | 216 | classdef StoreDB < handle_light
% The StoreDB class is a handle class to manage caching in Manopt.
%
% To create an object, call: storedb = StoreDB();
% Alternatively, call: storedb = StoreDB(storedepth); to instruct
% the database to keep at most storedepth stores in its history.
% (Note that clean up only happens whe... |
54bc3dd09743bfeca4a2ecbf695e877258b25f07252c2bc9da66c4c46581c83f | MATLAB | 9,257 | 239 | function this = MrDimInfo_split(this, testVariantsDimInfoSplit)
% Unit test for MrDimInfo split
%
% Y = MrUnitTest()
% run(Y, 'MrDimInfo_split')
%
% This is a method of class MrUnitTest.
%
% IN
%
% OUT
%
% EXAMPLE
% MrDimInfo_split
%
% See also MrUnitTest
% Author: Saskia Bollmann
% Created: 2018-02-14
% Co... |
9c4f8e28c074ac6d6a0cb6200d153bc29b444d1cab881c8ed1fbe127cc7998cd | MATLAB | 9,257 | 225 | function [data, beta, popt] = parse_data_from_mysql(S, varargin)
%concatenate data over days.
data.date = [];
data.trainingstage = [];
data.nic = [];
data.catch = [];
data.prob_catch = [];
data.adapt_block = [];
data.test_block = [];
data.reward = [];
data.reward_delay = [];
data.block = [];
data.hits = [];
data.vios =... |
a37973cbfd4a23f2716abffaad44a05c8a92298ca0734d46c96fa74063fac38a | MATLAB | 9,257 | 226 | % POP_READEGI - load a EGI EEG file (pop out window if no arguments).
%
% Usage:
% >> EEG = pop_readegi; % a window pops up
% >> EEG = pop_readegi( filename );
% >> EEG = pop_readegi( filename, datachunks, forceversion, fileloc);
%
% Inputs:
% filename - EGI file name
% datachunks - desi... |
5de3799119a96841a9872a5c8050e58e215bf36f45bb4e0c457b52dfa81c78be | MATLAB | 9,259 | 304 | function turnDistribution = RadialMazeTurns(data,mode)
%RadialMazeTurns - Compute distribution of successive turn angles in radial maze.
%
% In order to detect stereotypic egocentric strategies that a rat could employ to
% solve a radial maze task, this function determines the distribution (over trials)
% of success... |
77c204fcf9bbd23225a7b6e9f4bc5e4d0e82a0a39303f29ca9844d4033785a55 | MATLAB | 9,264 | 264 | clear all;
close all;
clc;
warning('off')
scriptName = mfilename;
%% Ensure workers can see current code path (parfor safety)
p = gcp('nocreate');
if isempty(p); p = parpool; end
% Replicate current path on workers
pctRunOnAll addpath(genpath(pwd));
% ---------------- I/O and paths ----------------
fullpath = mfilena... |
40af601e77745154ee23da851b5d7184ea694adb6793d026b22a9a1a4a6fbd20 | MATLAB | 9,269 | 201 | function data = placefields2(data,bins,method,varargin)
% Take a dataset and detect whether each cell in this dataset has a place
% field defined by the following criteria based on the dFoY traces. For
% analysis of significance, the dF values in one bin are compared to the
% distribution of dF values in the 20% bi... |
43411f18e7fef334083177d8692cc7fdc0059fc23f4be66556607f9cc9bcf575 | MATLAB | 9,275 | 328 | function coactPaper_figureS14()
labelWeight=true;
labelCase=false;
labelSize=9;
letGapX=5;
letGapY=6;
fontsize=6;
close all
fh=initFig('width',18.6,'height',4,'font','Arial','fontsize',fontsize);
x=15;y=7;
panel_01_02(x,y,fontsize);
panelLetter2(x-letGapX-3,y-letGapY+1,alphabet(1,labelCase),'fontSize',labelSize,'isB... |
e4c3fbe4773b8b99349749b7fa8b5000acc51fbdb4a4d95814a12db31f165155 | MATLAB | 9,285 | 245 | function [x, info, options] = stochasticgradient(problem, x, options)
% Stochastic gradient (SG) minimization algorithm for Manopt.
%
% function [x, info, options] = stochasticgradient(problem)
% function [x, info, options] = stochasticgradient(problem, x0)
% function [x, info, options] = stochasticgradient(problem, x0... |
3412e28e815052beb49ac3baba927ed544a10d761e585779857b0147caaf7fec | MATLAB | 9,288 | 226 | function [data, beta, popt] = parse_data_from_mysql(S, varargin)
%concatenate data over days.
data.date = [];
data.trainingstage = [];
data.nic = [];
data.catch = [];
data.prob_catch = [];
data.adapt_block = [];
data.test_block = [];
data.reward = [];
data.reward_delay = [];
data.block = [];
data.hits = [];
data.vios =... |
4e0300dd358f29d338d2e1546742f048f5b7b480da1d4ff65119fc75c8c7eb0f | MATLAB | 9,289 | 227 | % POP_EXPORT - export EEG dataset
%
% Usage:
% >> com = pop_export(EEG); % a window pops up
% >> com = pop_export(EEG, filename, 'key', 'val', ... );
%
% Inputs:
% EEG - eeglab dataset
% filename - file name
%
% Optional inputs:
% 'ica' - ['on'|'off'] export ICA activities (or ERP)... |
290185562f6f4b33907909ac845ea21961ecc65caabd1bb5b52e87998310f2ce | MATLAB | 9,292 | 188 | %% [chi] = Wrapper_QSM_LSQRandHEIDI(localField,mask,matrixSize,voxelSize,algorParam, headerAndExtraData)
%
% Input
% --------------
% localField : local field map (tissue fields), in Hz
% mask : signal mask
% matrixSize : size of the input image
% voxelSize : spatial resolution of each dimension of t... |
65dacc4fc3143ec398aa24153214003dd7ae6e95b1d7bd806d0ff960925aa818 | MATLAB | 9,293 | 270 | function run_lassoglm_grid_a1(param1Name, param1Vals, param2Name, param2Vals, seeds, outdir)
% RUN_LASSOGLM_GRID Sweep two parameters and seeds, run full pipeline, aggregate metrics.
% Positional args:
% run_lassoglm_grid_a1(param1Name, param1Vals, param2Name, param2Vals, seeds, outdir)
% Example:
% run_lassoglm_gri... |
0775326e836b7877da2a5df2fabb311ffabf76792825c0ba9674edbd31130b2f | MATLAB | 9,303 | 302 | function ch2roi_plot_stackFreq(GRUP, groupInfo)
% groups channels into defined ROIs (anatomic areas), averages & plots
% FIG:
% - subplots = freqBands x ROIs
% - 1 subplot = 1 class imagesc of stacked FB (y-axis) x time (x-axis) x activations (c-vals)
% based on the following criteria:
% - selected anatomical ar... |
2e57f5bf5be07c31d853ead914b0a40a876c458c0c6c3a85aeb30876c29ca905 | MATLAB | 9,305 | 183 | function [status, res] = BF_TiseanSystem(tiseanCommand, timeoutSecs)
% BF_TiseanSystem Run a TISEAN command-line call with a bounded timeout.
%
% All TISEAN-based operations shell out to a compiled binary via system().
% Verified empirically that these binaries do not always error on a bad
% invocation: false_nearest... |
375ed8ebf360749cffe3c2b0035760fe1979926591080a4da809141321759c3a | MATLAB | 9,307 | 244 | function [odm,clusters] = i_density_diff(XYZ,XYZ2,radius,niterations,varargin)
% function [odm,clusters] = i_density_diff(XYZ,XYZ2,radius,niterations,[resume at iteration])
%
% iterated density algorithm, to mask out significant areas from
% density analysis and re-run on remaining points, until convergence
% this is... |
b71011ba5df26c87febe1dcfc509e7e0c247a10ab04b4e55ae350deffb4e1eef | MATLAB | 9,307 | 343 | function [U,S,V,bnd,j] = lansvd(varargin)
%LANSVD Compute a few singular values and singular vectors.
% LANSVD computes singular triplets (u,v,sigma) such that
% A*u = sigma*v and A'*v = sigma*u. Only a few singular values
% and singular vectors are computed using the Lanczos
% bidiagonalization algorithm... |
fc263f4a0eacd31fdaa172701fde80768db6fa13c9ef48d3932d91748a6b531e | MATLAB | 9,310 | 268 | function [t,p,ci,stats,dist] = permuttest(x,m,varargin)
%PERMUTTEST One-sample and paired-sample permutation-based t-test.
% T = PERMUTTEST(X) performs a one-sample permutation test based on the
% t-statistic of the hypothesis that the data in X come from a
% distribution with mean zero, and returns the test sta... |
d1f35c8b15f146150fb4c0f3b538a21906501a077706a9fa83c1f262bf45691a | MATLAB | 9,311 | 231 | % POP_CROSSF - Return estimates and plots of event-related spectral coherence
%
% Usage:
% >> pop_crossf(EEG, typeproc, num1, num2, tlimits,cycles,
% 'key1',value1,'key2',value2, ... );
% Inputs:
% INEEG - Input EEG dataset
% typeproc - Type of processing:
%... |
7934fa00c7a620acbb4451c4055e6c0668a80300fd85d17628547c91ea80af6e | MATLAB | 9,322 | 223 | function c = tapas_hgf_ar1_mab_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the Hierarchical Gaussian Filter (HGF) for AR(1)
% processes in multi-armed bandit situations. The template for such
% a situation is the task from... |
24cfa1c11eafbaa818a521f9e32a08c7b029dcc7579d585ffe37ef8cafa16856 | MATLAB | 9,328 | 259 | % Script demo_dim_info
% Exemplifies creation and usage of MrDimInfo class for retrieving and
% manipulating indices of multi-dimensional array
%
% demo_dim_info
%
%
% See also MrDimInfo
% Author: Saskia Bollmann & Lars Kasper
% Created: 2016-01-23
% Copyright (C) 2016 Institute for Biomedical Engineering
% ... |
d52bababe5394e03da1ea27b7fbf2811c49b749b591c08c68041052e27d8513d | MATLAB | 9,334 | 264 | function [r,p,ci,stats,dist] = permucorr(x,varargin)
%PERMUCORR Linear or rank permutation-based correlation.
% R = PERMUCORR(X) returns a matrix containing the pairwise linear
% correlation coefficients between each pair of columns in X based on
% Pearson's r. For nonlinear correlations, the raw data may be
% ... |
9695f7ae34c11aab69f8a3142ad2e99ecc2bfe647283c43aaac38f87006da77d | MATLAB | 9,345 | 218 | function r = tapas_simModel(inputs, prc_model, prc_pvec, varargin)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% This is the main function for simulating responses (or only perceptual states) from a combination
% of perceptual and observation models, given para... |
ab0688dc39c0e4c1da69013ae496582c70c2d4a5c18adf2f3a364dc81299396c | MATLAB | 9,348 | 275 | %__________________________________________________________________________
% violin.m - Simple violin plot using matlab default kernel density estimation
% Last update: 10/2015
%__________________________________________________________________________
% This function creates violin plots based on kernel density estim... |
a8f8cba49b15ec53f97ca690172e4208107ee5ea287a6e7267a69493f103525d | MATLAB | 9,349 | 283 | %
% 'overseer' function for performing & logging subtraction in a tapered
% approach.
%
% [data,cfg]=m_do_taperedhann(data,cfg)
function [data,cfg]=m_do_taperedhann(data,cfg)
% this code needs some severe cleanup.
% several variables are unused, and some matrices could be defined as a bit
% smaller.
% verbose=0;... |
f892ad3b03258831165fe2b50e103ac54469b02cac9ced95f50ceb3db1587e1d | MATLAB | 9,351 | 347 | function str=struct2string(stuct_to_be_formatted)
% EXAMPLE USE WITH ARGUMENTS
% struct2stringstuct_to_be_formatted - use 1
%
% HELP
% This function takes a sturcture or an object and goes transform all the fields into strings in the recursive manner. Fields with big arrays are not processed - instead the size and a ty... |
243b10cdf3b4b6d6ede8857a92b65081ed40b975fe4aba80e695e354ed586e0a | MATLAB | 9,352 | 228 | function [X, maxdot] = packing_on_the_sphere(d, n, epsilon, X0)
% Return a set of points spread out on the sphere.
%
% function [X, maxdot] = packing_on_the_sphere(d, n, epsilon, X0)
%
% Using optimization on the oblique manifold, that is, the product of
% spheres, this function returns a set of n points with unit norm... |
3499a902458ece0a6da1910a91b3ed8719f6a59ea2fd8d8b8f1bb70801a075d4 | MATLAB | 9,358 | 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, dest, crop... |
7e53f811eea6f50e718c14ba8983f1bf78dd7014b9ba253d14753c69224c97f7 | MATLAB | 9,360 | 213 | function c = tapas_ehgf_binary_pu_tbt_config
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Contains the configuration for the *enhanced* Hierarchical Gaussian Filter (HGF) for binary inputs in the
% *presence* of perceptual uncertainty with the additional twist... |
764a4c9b05ba9633fb19060b6701c207225a07d1abfb7e019ab0bab05983c714 | MATLAB | 9,363 | 239 | % POP_IMPORTERPLAB - import ERPLAB event list file and bin file into
% EEGLAB event structure for use in STUDY processing
%
% Usage:
% >> OUTEEG = pop_sample( INEEG, file1, file2);
%
% Inputs:
% INEEG - input EEG dataset
% file1 - ERPLAB event list text file
% file2 - ERPLAB bin file... |
26d80d88141575ce5e1865195fb4bf77f630820f9dc7d4968199aa82dfc25a4d | MATLAB | 9,367 | 206 | function [realignedImage, realignmentParameters] = realign(this, varargin)
% Realigns n-dimensional image according to representative derived 4D image(s),
% and applies resulting realignment parameters to respective subsets of the
% n-d image
%
% Y = MrImage()
% rY = Y.realign('representationIndexArray', representa... |
88054e148e64860bebf4a5d64c90bca9e71dab6e130e854444c83bbb79463640 | MATLAB | 9,368 | 271 | clear all
close all
clc
% Calculates subspace generalization between simulated voxels.
% Each voxel is an average over simulated grid cells. Cells are sampled
% randomly. This script examine the signal as a function of the numer of
% voxels per module.
% noise is added to the voxels' activity map.
global cells_in_vox... |
7932e2d548db90fc82cd4e4fc536d284410c7706c397f8fd7eb142750d403da2 | MATLAB | 9,371 | 166 | function AFI_OptimizeSmoothing(MyelinInput, AFIVolume, TRone, TRtwo, TargFlipAngle, LeftPial, LeftMidthick, LeftWhite, RightPial, RightMidthick, RightWhite, SmoothLower, SmoothUpper, LeftVolROI, RightVolROI, GroupCorrected, Output)
%take all numbers as strings, for unified compiled/interpreted handling
TRo... |
59aea262312b9a194472c4544266093b578557d08a8669b844e77b419d4eb180 | MATLAB | 9,372 | 254 | %% cell_selectivity_and_population_plots.m
%NOTE THIS IS USED TO AUTOMATICALLY SELECTING PHENOTYPE SPECIFIC NEURONS,
%EXCLUSIVE FROM OTHER PHENOTYPES
% Reads:
% Calcium.xlsx -> rows = timepoints (~3000 for 10 min @ 5Hz), cols = cells
% Behavior.xlsx -> 6 sheets, each sheet = [start, stop] times in seconds... |
bb9e97bb4580ef5665dab3116b4861a9228414aac14e486630f4b6646f674ac1 | MATLAB | 9,380 | 222 | % Copyright 2025 Laura Schmid
% Permission is hereby granted, free of charge, to any person obtaining a
% copy of this software and associated documentation files (the
% “Software”), to deal in the Software without restriction, including
% without limitation the rights to use, copy, modify, merge, publish,
% distribut... |
55a4783a383c3dda3cc9a62d9321d3235427ebbb3e083d6a4fa6a5f210e4aa37 | MATLAB | 9,382 | 301 | function Fig4Sup1_DecoyTitrations(varargin)
% Fig4Sup1_DecoyTitrations
% Plots EC50 dose-response curves for GABA and various decoy ligands.
% Reads XLS/CSV files from current directory, fits 4-parameter sigmoid,
% and saves figure + EC50 table.
%
% USAGE:
% Fig4Sup1_DecoyTitrations() % process all XLS/CSV fil... |
2a8ea05605bdf5b90227aa38d854a7781a2c83141ca931fc6e9e2a2985e12599 | MATLAB | 9,386 | 258 | function [celldata] = plot_2E(all_unitinfo, all_ps, all_etas, all_etas_imperm_boot, all_etas_qperm_boot, level)
% plot_2E Generate boxplot visualization of partial eta squared values
%
% plot_2E creates a figure displaying the distribution of partial eta squared
% values across different effect types (stimulus, contex... |
7a873611ced0c9c36c1e63e740b957fa4ddd414ee54347d761c1bc81995b2570 | MATLAB | 9,393 | 285 | % ########## This function is deprecated. Use eegmovie instead. ##########
%
% HEADMOVIE - Record a Matlab movie of scalp data.
% Use SEEMOVIE to display the movie.
%
% Usage: >> [Movie,Colormap] = headmovie(data,elec_loc,spline_file);
% >> [Movie,Colormap,minc,maxc] = headmovie(data,elec_loc,sp... |
a42eba1b1764036465a967a4f7eb76d02c7dd48f166b2d103fb79a32afa4bc85 | MATLAB | 9,396 | 246 | function varargout = run_oopsi(F,V,P)
% this function runs our various oopsi filters, saves the results, and
% plots the inferred spike trains. make sure that fast-oopsi and
% smc-oopsi repository are in your path if you intend to use them.
%
% to use the code, simply provide F, a vector of fluorescence observations,
... |
d3ede634092a4b252f979929948f5fe2451ca4e17bbe7a9b3bb1de038b4d9302 | MATLAB | 9,398 | 230 | function [K,dK,D2] = covMaha(mode, par, k, dk, hyp, x, z)
% COVMAHA Mahalanobis distance-based covariance function.
%
% Report number of hyperparameters
% s = COVMAHA (mode)
% s = COVMAHA (mode, par)
% s = COVMAHA (mode, par, k)
% s = COVMAHA (mode, par, k, dk)
% s = COVMAHA (mode, par, k, dk, hyp)
%
% E... |
5cfde84845576e9915215da21ee036c554aa1dbd1154d5eaac683b1629cf25e4 | MATLAB | 9,399 | 295 | function [f,G,H,evidence,penalty,f_offset] = nll_poiss(st,c,stim,ops,trial_id)
%calcs neg. log-likelihood and gradient, hessian
%for glm with parametrized spike history filter and multiple filtered stimuli
%
%
%Inputs:
%st: either i) [nt,ns] matrix of spike times, nt=# time points,ns=# samples
% or ii) [nt x ns,... |
5368fd95acb4e2423c5593b0ec5e231d8fb098159925a6267fdaf2389bdb55bb | MATLAB | 9,400 | 217 | % function poolSubjects_brain3D_activity(params, groupInfo)
% plots 3D brain & activations (ERP + freq.band + spectra)
% pools together subject processed by a given job
% settings (subjects, directory names, ...) are stored in 'params'
% (c) Jiri, Apr18
disp('Plotting channels: 3D brain & activations ...');
%% came... |
215e5ffbfa1a71d87b7983472df19b6a77adca0f4e0cd2faeb6933a3b40e63ad | MATLAB | 9,408 | 257 | function [varargout] = gen_synthData(varargin)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% gen_synthData generates synthetic network data and embed contrast of
% interest in a given number of edges. Using this function scale-free,
% small-world and random networks can be generated. It ... |
8104fb1083573b476b4b54fb4fdc877669b0df21c1cdbbb7e29eda18874339de | MATLAB | 9,422 | 252 | clear all
close all
clc
% Calculates subspace generalization between simulated voxels.
% Each voxel is an average over simulated grid cells. Fraction of cells are selected
% according to their phase such that grid cells with closer phases are averaged within the same voxels
% and fraction that is selected randomly.
% ... |
ee6661ef634309fdd7987112860bb5c119463444a7c404f724797052ab22e63f | MATLAB | 9,426 | 267 | % TESTICA - Test the RUNICA function's ability to separate synthetic sources.
% Use the input variables to estimate the (best) decomposition accuracy
% for a given data set size.
% Usage:
% >> testica(channels,frames); % No return variable -> plot results
% >> [testresult] = test... |
80234dabf8ab2062537b555d7f3852f42ea1de4edc35c95110acad5c19774d5a | MATLAB | 9,430 | 305 | function ht = plotsign2 (h,s,Opt);
% ht = plotsign2 (h,s,[Opt]);
% h is the figure handle, if you need to specify a subplot within the figure
% pass the figure handle and the subplot number in h, like: [1 213]
% or [1 2 1 3]
% s is the text string, if s is not supplied, a default string is used
% the default i... |
6f32140a4cc7f765c1ab92b6d20158268689468ff6feed7c8fff2fcc4c414b9b | MATLAB | 9,435 | 220 | %specify clusters to load
clear inx
Cluster1 = 3;
Cluster2 = 19;
% inx1 = find(rez.st(:,end)==Cluster1); inx1 = inx1(inxT1);
% inx2 = find(rez.st(:,end)==Cluster1); inx2 = inx2(inxTO1);
% inx{1} = inx1;
% inx{2} = inx2;
inx1 = find(rez.st(:,4) >= 0);
inx2 = find(rez.st(:,4) >= 0);
inx{1} = intersect(find(rez.st(:,e... |
ca0ecb1b1c643b422910000993cf60214eb19f4f9d079ad9a6cb3900c540c5d2 | MATLAB | 9,435 | 206 | % fit_Osprey.m
% Georg Oeltzschner, Johns Hopkins University 2019.
%
% USAGE:
% [fitParams] = fit_Osprey(dataToFit, resBasisSet, fitOpts);
%
% DESCRIPTION:
% This is the function describing the Osprey fitting model, which is
% performed with the resampled basis set resBasisSet on the data contained
% in the FID-A data... |
9dcfeda871798732f9fa398ae75691ed532fc6560e05292c2706372ae9981461 | MATLAB | 9,443 | 233 | % POP_READLOCS - load channel location file (pop up an interactive window
% if no arguments).
%
% Usage:
% >> chanlocs = pop_readlocs; % a window pops up
% >> chanlocs = pop_readlocs( filename, 'key', val, ...); % no window
%
% Inputs:
% filename - Electrode loc... |
f39d7b88e88a832782cff7e96aea13f15fcb5d62c9c12df9c4bc864cbad2afe1 | MATLAB | 9,443 | 200 | % STD_FILECHECK - Check if ERSP or SPEC file contain specific parameters.
% This file must contain a Matlab structure with a field
% named 'parameter'. The content of this field will be
% compared to the 'params' input. If they are identical
% the out... |
109efd3346491ae93ff271726c25f51d337d0d644c40e293689a9009a07349b3 | MATLAB | 9,450 | 258 | % BIOSIG2EEGLAB - convert BIOSIG structure to EEGLAB structure
%
% Usage:
% >> OUTEEG = pop_biosig2eeglab(hdr, data, interval);
%
% Inputs:
% hdr - BIOSIG header
% data - BIOSIG data array
%
% Optional input:
% interval - BIOSIG does not remove event which are outside of
% the data range when im... |
315abc7bd150689047c2ffcef6080b4f60f48d0429519bc9a2e2500b2ca359b8 | MATLAB | 9,451 | 213 | % POP_ENVTOPO - Plot envelope of an averaged EEG epoch, plus scalp maps
% of specified or largest contributing components referenced
% to their time point of maximum variance in the epoch or specified
% sub-epoch. Calls ENVTOPO. When nargin < 3, a query window
% ... |
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