sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
47d28f89aaed48736486e597d103ba5358e1272ba87014020d8e494688dcf89f | MATLAB | 16,804 | 481 | function boolAddedEpoch = ETC_AddPupilEpoch(hObject,eventdata,strType)
%globals
global sFigETC;
global sETC;
%get temporary epoch
sEpoch = sFigETC.sEpochTemp;
%hTemp=figure;
%get modifier
boolControlPressed = getAsyncKeyState(VirtualKeyCode.VK_CONTROL);
boolAltPressed = getAsyncKeyState(VirtualKeyCode.VK_MENU... |
3a0753ff7eae9e0609fd164c2b73127b08d4d4f90ecebb79a77485459382596e | MATLAB | 16,819 | 527 | zef.h_find_synthetic_source_legacy = figure(...
'PaperUnits','inches',...
'Units','normalized',...
'Position',[0.565833333333333 1.10641025641026 0.176388888888889 0.3],...
'Visible',get(0,'defaultfigureVisible'),...
'Color',get(0,'defaultfigureColor'),...
'IntegerHandle','off',...
'Colormap... |
3654f1574fb9578a41897e3c92e399d64b9baa1fd75236917af101c2eaede209 | MATLAB | 16,841 | 396 | function [h_old,h_new] = vis_artifacts(new,old,varargin)
% vis_artifacts(NewEEG,OldEEG,Options...)
% Display the artifact rejections done by any of the artifact cleaning functions.
%
% Keyboard Shortcuts:
% [n] : display just the new time series
% [o] : display just the old time series
% [b] : display both time s... |
317c3b114f77b5dcc8bde41606d3735e63e3bbd065435fe515185189352a4b6b | MATLAB | 16,908 | 550 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [L_eit, bg_data, dof_positions, dof_directions, dof_ind, dof_count] = lead_field_eit_fem( ...
zef, ...
nodes, ...
elements, ...
sigma, ...
electrodes, ...
p_nearest_nei... |
8218e83a02d7e9020f45b381fe7f7738d225bbac0e22767a121c933c6475b3b9 | MATLAB | 16,908 | 380 | function nse_field = zef_nse_haemodynamic_response_solver(zef, nse_field,nodes,tetra,domain_labels,mvd_length)
%Output:
%nse_field.bf_capillaries
%nse_field.bp_vessels
%nse_field.bf_capillary_node_ind
%nse_field.bp_vessel_node_ind
%Input:
%nse_field.artery_domain_ind
%nse_field.capillary_domain_ind
%nse_field.total_f... |
d588dda89fe364e09a6e8f747dfee1aa4f8263bf79b5b9641c6e38a95e30c7a5 | MATLAB | 16,965 | 360 | function detection = bodizs_spindle_detection(C3nrem,O1nrem,C3,fs)
% BODIZS Detect sleep spindles using the Bodizs algorithm.
% R. Bodizs et al. "The individual adjustment method of sleep spindle
% analysis: Methodological improvements and roots in the fingerprint
% paradigm", J Neuro Method 178, 2009, pp 205-213
%
% F... |
1c5b418e2d2abc82f3abb90d1e28ba004713dbe058445c0b52266da9b850dfdc | MATLAB | 17,002 | 398 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function zef = zef_import_segmentation_legacy(zef, file_name, folder_name)
void = [];
if nargin == 0
zef = evalin('base','zef');
end
if eval('zef.use_display')
if nargin < 2
[file_na... |
7e5ae1fbf01da1e8d6733792c83dfd0932e0bdb576387b29669f935e0fd71c72 | MATLAB | 17,132 | 368 | classdef zef_segmentation_tool_app_exported < matlab.apps.AppBase
% Properties that correspond to app components
properties (Access = public)
h_zeffiro_window_main matlab.ui.Figure
h_set_position matlab.ui.control.Button
h_segmentation_tool_toggle matlab.... |
9c9309dddb404c338b564b2f2a75aa143be06ac25db4b16332e355b635fd5479 | MATLAB | 17,336 | 466 |
%open source simulation tool and select the correct source
%
%check the noise like below and update the values
%check max data without noise
%max(abs(zef.measurements),[],'all')
meg_max=0.0078; %%%%%%%%%%%%%%%%%%%%
eeg_max=0.6928; %%%%%%%%%%%
% eegnode=zef.dataBank.tree.node_1_1;
% megnode=zef.dataBank.tree.node_2... |
2cc83b82d35585322f8d1fc2eee7956b1698f34f5074f376ee72dcf079615f0a | MATLAB | 17,365 | 519 |
%signal_pos=[-16, 56.5, 41.6];
p='p1';
load(strcat(p, '_resectionStuff.mat'));
A=alphaShape(res_zef(:,1), res_zef(:,2), res_zef(:,3),3.4);
[AF, AP]=alphaTriangulation(A);
%%
signal_pos=res_zef;
alpha = str2num(evalin('base','zef.GMM.parameters.Values{6}'))/100;
r = sqrt(chi2inv(alpha,3));
SNR=[-30 -25 -20 -15 -10 ... |
b600e22f91ca53f2330309d18ab0767fe9eddddf3d588d62b8107787af907477 | MATLAB | 17,433 | 413 | function sFile = getEyeTrackerChecker(sFile,strTempPath)
%getEyeTrackerChecker Check eye-tracking quality
% sFile = getEyeTrackerChecker(sFile,strTempPath)
%% globals
global sFigETC;
global sETC;
sFigETC = [];
sETC = [];
%% find minivid
strMiniVidFile = sFile.sPupil.sPupil.strMiniVidFile;
strMiniVidPath... |
97f5e5b107219d47b50d18bd74ef22cbb3acfd9fb12a98f0e681937e0cee5f50 | MATLAB | 17,872 | 393 | function [P,VAL,M,Hss_single]=bsliang_CNLRplots_re(data_in,issham,rmnan,is_stat,perDISRIB,data_in_mask)
% issham == 1, add sham, iTBS cTBS sham
% issham == 0. dont add sham, usually iTBS=iTBS-sham, cTBS=cTBS-sham
% is_stat: ÊÇ·ñ½øÐÐͳ¼Æ¼ìÑé
P=[]; VAL=[]; M=[];
data=data_in(:,2:end);... |
51a209afea4b3338308602c090e6120645c6c5a7cfcac030304781751e7b0b76 | MATLAB | 17,907 | 431 | function pl = boxplot_LT(x,varargin) ;
% Boxplot function. By default will plot a boxplot with points next to it
% representing each data point.
%
% BASIC PLOTTING -----------
% Inputs:
% - x: Data to be plotted. This can be a column vector of all points, or a
% NxM matrix. I... |
aeb8257a126ae47ba728955fcab9861c3966cd4b5d4ff528be16efb52e14b4ce | MATLAB | 18,027 | 376 | %file_name = 'training_dataset_p1_10dB.mat';
examples.studies.decision_making.zef_parameters_focal_epilepsy;
training_data = struct;
if not(exist('zef','var'))
zef = zeffiro_interface('start_mode','nodisplay','open_project',project_file_name);
end
zef_start_dataBank;
waitbar_counter = 0;
h_waitbar = zef_waitbar(... |
0c07a69b69576729fa70c05e828c54e6453e170abf0f9086ef4c91998718cbde | MATLAB | 18,075 | 465 |
clcl
%%% decoding analysis from the paper
for file_load=1;
%
files={''}; %%put _28hz at the end!
end
limtrials1=10; %limit the number of trials analysed for each stimulus type(control/redundandt/deviant).
baseBEGIN=1; baseEND=12; %what you call the baseline
BEGINo=14; ENDo=28; %these are the analysis windows. note: ... |
7aa07089e313c37bd05e5cb459905b8af1b26b21f832dfc2b696f93a380ed892 | MATLAB | 18,418 | 455 | function [hmm, Gamma, Xi, vpath, GammaInit, residuals, fehist, feterms, rho] = ...
hmmmar (data,T,options)
% Main function to train the HMM-MAR model, compute the Viterbi path and,
% if requested, obtain the cross-validated sum of prediction quadratic errors.
%
% INPUT
% data observations; either a struct ... |
2b6b21c01a1183a8c9337948279a929c19436d7fd03010dca3ddf741264bea05 | MATLAB | 18,458 | 565 |
%signal_pos=[-16, 56.5, 41.6];
p='p1';
load(strcat(p, '_resectionStuff.mat'));
A=alphaShape(res_zef(:,1), res_zef(:,2), res_zef(:,3),3.4);
[AF, AP]=alphaTriangulation(A);
%%
signal_pos=res_zef;
alpha = str2num(evalin('base','zef.GMM.parameters.Values{6}'))/100;
r = sqrt(chi2inv(alpha,3));
SNR=[-30 -25 -20 -15 -10 ... |
26dba916d3c4d0a9177cfd0809a275db2776040dd5f321d7f757f3439f61e79f | MATLAB | 18,522 | 576 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
if zef.w_on
zef.enable_str = 'on';
else
zef.enable_str = 'off';
end;
set(zef.h_edit9001, 'enable', zef.enable_str);
set(zef.h_edit29, 'enable', zef.enable_str);
set(zef.h_edit70, 'enable', zef... |
ba9fad1e9aef03c90d6b5fb694c4233e66f7e219278a91a72c9c899ea3f4a101 | MATLAB | 18,581 | 536 | function h1 = zef_mne_tool_export()
% This is the machine-generated representation of a Handle Graphics object
% and its children. Note that handle values may change when these objects
% are re-created. This may cause problems with any callbacks written to
% depend on the value of the handle at the time the object was... |
b2fb314657f03225bc71ddc8797cdac4396be26e051ca494774e13ecd1c2b41a | MATLAB | 18,590 | 437 | function [Pss_single,Pss_compare,Hss_single,Dss_single,Dss_compare]=bsliang_CNLRplots_re(data_in,issham,rmnan,perDISRIB,data_in_mask)
% issham == 1, add sham, larynx tongue sham
% issham == 0. dont add sham, usually larynx=larynx-sham, tongue=tongue-sham
data=data_in(:,2:end);
data_mask=data_i... |
0796d608abf08616c1b8b2c07cb86bc7d2c80ca7832520592966f50d5c544348 | MATLAB | 18,609 | 529 | function [Ep,Cp,Eh,Ch,F] = variational_laplace(M,U,Y)
% Variational Laplace scheme.
%
% Fits any model to data and returns a posterior density over the
% parameters N(Ep,Cp), a posterior density over the hyperparameters
% governing the noise N(Eh,Ch), and an approximation of the log model
% evi... |
7fbe2b2e13ead385d20ad16e5494a4bf13c0b69c184c86aeab2dcbea567fcb23 | MATLAB | 18,787 | 419 | % look at CF trends
clear all
Analyze_dates = [{'09.16.18'},{'09.20.18'},{'09.21.18'},{'10.01.18'},{'10.12.18'}];
addpath('../../Neuron Analysis Functions')
addpath('/media/ravinderjit/Data_Drive/Data/AuditoryNerve/DynBin')
Screen_pixelLocs = [1986 1 1855 1001]; %makes figure the size of my second screen at Lyle ... ... |
cea1ac92881cb0a44a781fceef8b3ccce9352476ef876ee4c56c99e54b794017 | MATLAB | 18,873 | 551 | % Code used in Vidaurre et al. (2018) Nature Communications
%
% Detailed documentation and further examples can be found in:
% https://github.com/OHBA-analysis/HMM-MAR
% This pipeline must be adapted to your particular configuration of files.
%%%%%%%%%%%%%%%%%%%%%%%%%
%% SETUP THE MATLAB PATHS AND FILE NAMES
% ... |
d20dc50556d7f4cac739d1ec422e0dd231436caa14e56ffc3bdbdcbc0f96e6b8 | MATLAB | 18,894 | 301 | function [net, info] = QuickNAT_Train(imdb, netF, inpt, varargin)
% some common options
trainer = @cnn_train_dag_seg;
opts.train.extractStatsFn = @extract_stats_segmentation_Mod;
opts.train.batchSize = 4;
opts.train.numEpochs = 15;
opts.train.continue = true ;
opts.train.gpus = [2] ;
opts.train.learningRate =... |
7c8448d9fea496fdbd300a7fe11b5d6643385eb2dec652dfc68717a7f89be2a7 | MATLAB | 18,913 | 418 | % look at CF trends
clear all
Analyze_dates = [{'09.16.18'},{'09.20.18'},{'09.21.18'},{'10.01.18'},{'10.12.18'}];
%Analyze_dates = [{'09.20.18'},{'09.21.18'},{'10.01.18'},{'10.12.18'}];
fig_loc = '/media/ravinderjit/Data_Drive/Data/Figures/DynBin/Nerve';
addpath('../../Neuron Analysis Functions')
addpath('/media/ravi... |
feab1557ff7e6700266ef2c5ee4c396679299c480609a3092b8c088667e778ee | MATLAB | 18,972 | 241 |
set(groot,'defaultFigureVisible','off')
zef_data = zef_menu_tool_app_exported;
zef_data.h_zeffiro_menu.Visible = zef.use_display;
set(groot,'defaultFigureVisible','on')
zef.fieldnames = fieldnames(zef_data);
for zef_i = 1:length(zef.fieldnames)
zef.(zef.fieldnames{zef_i}) = zef_data.(zef.fieldnames{zef_i});
end
s... |
063ff00927d5df56ebf5a915e1779d5e97d12b8b5373dd66c0a3ee5f20480f30 | MATLAB | 19,014 | 733 | function sigma_out = zef_nse_sigma(nse_field, nodes, tetra, domain_labels, sigma_in, s_interp_ind, singular_threshold)
%
% zef_nse_sigma
%
% Computes conductivities for the different brain compartments or tetrahedra
% in the finite element mesh, based on the capillary blood flow in those
% compartments.
%
% NOTE: this ... |
d1bfae318d4c4a346a830957bf27c1339308c59593320328d0f51bcf1754597e | MATLAB | 19,257 | 265 |
%--------------------------------------------------------------------------------
% fig3.m
%
% This analysis is included in
% Experimental validation of the free-energy principle with in vitro neural networks
% Takuya Isomura, Kiyoshi Kotani, Yasuhiko Jimbo, Karl Friston
%
% Copyright (C) 2022 Takuya Isomura
% (RIKEN ... |
c273af13fda073110cd6cf2ec32a90b711e1da2822919c2c6d9bbc103b331cec | MATLAB | 19,287 | 763 | function zef = zef_strip_tool_window(zef)
h1 = figure(...
'PaperUnits',get(0,'defaultfigurePaperUnits'),...
'Units','normalized',...
'Position',[0.43 0.52 0.35 0.45],...
'Visible',get(0,'defaultfigureVisible'),...
'Color',get(0,'defaultfigureColor'),...
'IntegerHandle','off',...
'Colormap',[0 0 0.5625;0 0 0.625;0 0 0.... |
f6273b5d1996d32014a0d52adfaadcad20aef71d5874b2e4235436d35529850d | MATLAB | 19,296 | 303 | function opts = trainingOptions2(solverName, varargin)
% ======================================================
% dir : C:\Program Files\MATLAB\R2019a\toolbox\nnet\cnn
% ======================================================
% trainingOptions Options for training a neural network
%
% options = trainingOptio... |
a270003025cb8144a21ca8933c7c888a1b067b38233ac6bbcd75bf70780887aa | MATLAB | 19,298 | 304 | function opts = trainingOptions2(solverName, varargin)
% ======================================================
% dir : C:\Program Files\MATLAB\R2019b\toolbox\nnet\cnn
% ======================================================
% trainingOptions Options for training a neural network
%
% options = trainingOpt... |
f1998ca080efaeca6b247275e5e298fca74d5a004e5c19b5ac2321e6ff2897f8 | MATLAB | 19,360 | 673 | function h_waitbar = zef_waitbar(varargin)
%
% zef_waitbar
%
% A function that either creates a new Zeffiro Interface waitbar with a
% certain title, updates an existing waitbar while keeping the title the same,
% or updates a waitbar while also updating the title.
%
% Inputs: a varargin cell array with either 3 or 4 e... |
9626cc53f0b8d33165ae42e87502c122554fdaaf28a680062f3cd1a5121ff72a | MATLAB | 19,384 | 476 | function fcn_hcp_meg_process_rest(hcp_dir, subjList, badChannels, reports_dir)
% hcp_meg_process: Script to process Resting-state MEG data from Human
% Connectime Project
%
% Modified from Brainstorm online tutorials:
% https://neuroimage.usc.edu/brainstorm/Tutorials/HCP-MEG
%
% Inputs:
% hcp_dir: Directory wit... |
7576ffd0e9cbadd9a718dd2274d29ba0dfaa723fa056fe97b0cd53e09c953079 | MATLAB | 19,477 | 618 | function [Ep,Cp,Eh,F,L,dFdp,dFdpp,Ch] = spm_nlsi_GN(M,U,Y)
% Bayesian inversion of nonlinear models - Gauss-Newton/Variational Laplace
% FORMAT [Ep,Cp,Eh,F] = spm_nlsi_GN(M,U,Y)
%
% [Dynamic] MIMO models
%__________________________________________________________________________
% M.G - or
% M.IS - function name f(P,M... |
5be09089102d20ec4e57f7c649fddc0a2d19bee0971fd61cba702ab5f4e72233 | MATLAB | 19,554 | 568 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [L_meg, dipole_locations, dipole_directions] = lead_field_meg_fem( ...
zef, ...
nodes, ...
elements, ...
sigma, ...
sensors, ...
p_nearest_neighbour_inds, ...
varar... |
2748759387545b622eb132f5409adacf1aa39f0e1ea63d9a44f6ff1e973b7dff | MATLAB | 19,791 | 498 | function plt = plot(obj,param,varargin)
% Visualize microstate data and statistics
if nargin == 1
param = 'data' ;
end
% ensure plotting functions are on path
mspath = microstate.functions.toolbox_path ;
addpath(fullfile(mspath,'+external','brewermap'))
switch param... |
a1b34ae2a7931dd443b242c05f3572ed1d970c0c9a645f3a828bdaef00ea2487 | MATLAB | 19,869 | 718 | zef.h_find_synthetic_source_ROI = figure(...
'PaperUnits','inches',...
'Units','normalized',...
'Position',[0.565833333333333 1.10641025641026 0.176388888888889 2*0.3],...
'Visible',get(0,'defaultfigureVisible'),...
'Color',get(0,'defaultfigureColor'),...
'IntegerHandle','off',...
'Colormap'... |
12e8f0fa8a737c5920faf091e1289ce26f250a0d5cf800a8c0e07f6af544e610 | MATLAB | 19,883 | 474 | function [FrEn,avLL] = evalfreeenergy(X,T,Gamma,Xi,hmm,residuals,XX,todo)
% Computes the Free Energy of an HMM depending on observation model
%
% INPUT
% X observations
% T length of series
% Gamma probability of states conditioned on data
% Xi joint probability of past and future... |
b7989bda88a73f4dfbc2dfc5d988a463997f1be384508d19ef3244bf73bbde7a | MATLAB | 20,086 | 545 |
%function structMP = RunReceptiveFieldMapping
%8 seconds per trial
%8 trial types (max 64 seconds per rep)
%10 repetitions = 11 minutes
%80 trials in total
%% suppress m-lint warnings & clear all variables except RunExperiment inputs
%#ok<*MCCD,*NASGU,*ASGLU,*CTCH>
clearvars -except sStimPresets sStimParamsSettings s... |
3b13b3a6761b0049cb40941b30793276e90c9b4ddd35b588af0460691889e34f | MATLAB | 20,175 | 549 | function [rip]=sw_detect_ripple(dat,opt)
%% ------------------------------------------------------------------------
% [rip,cscx,csc,cts]=sw_detect_ripple(dat,opt)
%
% Function to detect ripple events in a lfp trace.
%
% The input signal is an envelope of power (raw signal is zscored -mean removed,
% divided b... |
7f77e6a44bb1e0499545d229e30a64f690b46af47820108cf09d82d7f02fac8a | MATLAB | 20,353 | 334 | function zef = zef_nse_tool_window(zef)
zef_data = zef_nse_app;
zef = zef_nse_tool_init(zef);
zef.nse_field.reconstruction_type_list = cell(0);
zef.nse_field.reconstruction_type_list{1} = [1 2 3 6 7 8 9 10 11 12 13 14];
zef.nse_field.reconstruction_type_list{2} = [4 5 15 16 17];
zef.nse_field.h_plot_sphere = zef_... |
47f6815c6283b9d2bb856e4c1cd4872f6edcdbaaf6a231945ac2c5ac235a35f0 | MATLAB | 20,392 | 629 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [eit_data_vec] = zef_compute_eit_data(nodes,elements,sigma,electrodes,varargin)
N = size(nodes,1);
if iscell(elements)
tetrahedra = elements{1};
prisms = [];
K2 = size(tetrahedra... |
b020d4d660387a72b17c38d6075d41048f9213703851f8f4132b4cb39c80a417 | MATLAB | 20,471 | 426 | function bsliang_TMS_main
% Öظ´ÑéÖ¤¼ÆË㣺Ö÷³ÌÐò
clear all
close all
addpath('global');
addpath(genpath('D:\ÖØÒª×ÊÁÏ_20190604\²©Ò»ÏÂѧÆÚ\ÄÔµç\˼ӰÄÔµç20200720\siyingEEGT_20200720\6EEGT_day1\toolboxes\eeglab14_1_1b\eeglab14_1_1b'))
% ÊäÈëһЩ²ÎÊý£º
IDsteps=5;
rawIDs... |
b8b62c34aa06871aa857ee83d1aeca2904f152ed61bdf4f15c2256db6d144ecc | MATLAB | 20,580 | 480 | classdef Ising < BCFWObjective
% Ising BCFW interface for Ising models.
properties (Dependent)
% Flat vector interface for the BatchFW routine. The vectorization
% format is
% x = vertcat(vec(TN'), vec(TE')) = vectorizeNE(TN, TE)
x
end
properties
% vector... |
a0a89b168c91b65d77875e51d987645a7b94ff73d64adf696935f8d1b88d46f2 | MATLAB | 21,006 | 678 | function varargout = runEyeTracker(varargin)
%runEyeTracker Acquire eye-tracking video while performing detection
%
%This GUI interfaces with SpikeGLX to enable automatic cross-platform
%synchronization. It can run online pupil tracking and allows you to
%set a reasonable estimate for the parameters requires for a... |
7199fe53c4ce50daf7f1885120588cbef87afa96b151bf83f164e2195f78a70f | MATLAB | 21,166 | 260 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
%if zef.h_segmentation_tool_toggle == 1
% zef.size_temp = [zef.segmentation_tool_default_position(1) + 0.505*zef.segmentation_tool_default_position(3), ...
% zef.segmentation_tool_default_... |
5d5e2ec3a36731aad88caa6242610e62051307ab0363f875815a5729ece48251 | MATLAB | 21,298 | 640 |
h1 = figure(...
'PaperUnits',get(0,'defaultfigurePaperUnits'),...
'Units','normalized',...
'Position',[0.576388888888889 0.375555555555556 0.247222222222222 0.655555555555556],...
'Visible',get(0,'defaultfigureVisible'),...
'Color',get(0,'defaultfigureColor'),...
'CloseRequestFcn',get(0,'defau... |
ee202772e40b609684aa42d00e2662a74e845bb1b9667ff768c9032b3debb80d | MATLAB | 21,326 | 588 | function [spin]=sw_detect_spindle(dat,opt)
%% ------------------------------------------------------------------------
% [spin,dat,dat,dat.ts]=sw_detect_spindle(dat,opt)
%
% Function to detect spindle events in a lfp trace.
%
% The input signal is an envelope of power (raw signal is zscored -mean removed,
% div... |
0bd6eceb0985c630ab96cb2a569c47302dd0323436f37525ccdcc916bd044594 | MATLAB | 21,367 | 532 | function [x, cost, info, options] = rlbfgs(problem, x0, options)
% Riemannian limited memory BFGS solver for smooth objective functions.
%
% function [x, cost, info, options] = rlbfgs(problem)
% function [x, cost, info, options] = rlbfgs(problem, x0)
% function [x, cost, info, options] = rlbfgs(problem, x0, options)
%... |
25d86925da6dedddeddeeb4ee628436269cd8375e9bd6d2044354571d4085b72 | MATLAB | 21,391 | 404 | function state = asr_calibrate(X,srate,cutoff,blocksize,B,A,window_len,window_overlap,max_dropout_fraction,min_clean_fraction)
% Calibration function for the Artifact Subspace Reconstruction (ASR) method.
% State = asr_calibrate(Data,SamplingRate,Cutoff,BlockSize,FilterB,FilterA,WindowLength,WindowOverlap,MaxDropoutF... |
343b3de7198e341235b93d756e629a1dca89f0f19495fc2b443c9a800280449c | MATLAB | 21,470 | 407 | function state = asr_calibrate_r(X,srate,cutoff,blocksize,B,A,window_len,window_overlap,max_dropout_fraction,min_clean_fraction)
% Calibration function for the Artifact Subspace Reconstruction (ASR) method.
% State = asr_calibrate(Data,SamplingRate,Cutoff,BlockSize,FilterB,FilterA,WindowLength,WindowOverlap,MaxDropou... |
52b632b38c56e9cdbeebf6edf8a0fba9fbd6ea1165f1cc7e5edf8a2153cda90d | MATLAB | 21,991 | 446 | classdef zef_mesh_visualization_tool_app_exported < matlab.apps.AppBase
% Properties that correspond to app components
properties (Access = public)
h_mesh_visualization_tool matlab.ui.Figure
h_pushbutton31 matlab.ui.control.Button
h_pushbutton20 m... |
097c5b233247441c36658bf9588f61caa7d84013cfab8f6b06985b16cf131dbb | MATLAB | 22,057 | 620 | %% testing for lognormal fit
% this script fits your data visually to a lognormal distribution, and
% gathers statistical parameters that will be used for a statistical
% analysis in a different script
% for the statisticial analysis, refer to "stat_analysis_lognormal_data"
% clear all variables and spaces bef... |
9573cd38611596656820b828e1460250deb3e443f0de63f1088d642b588420c2 | MATLAB | 22,211 | 521 | function nse_field = zef_nse_poisson_dynamic(nse_field,nodes,tetra,domain_labels,mvd_length)
h_waitbar = zef_waitbar(0,1,'NSE solver: pressure');
if not(isfield(nse_field,'nse_type'))
nse_field.nse_type = 1;
end
if nse_field.time_integration == 1
n_q_steps = 1;
elseif nse_field.time_integration == 2
n_q_... |
cc113d2a7612708947a00c45d324442ccade12ff101b7e9f154c82aafea63dda | MATLAB | 22,356 | 495 | #if defined(OS_MACOS)
#pragma clang diagnostic push
#pragma clang diagnostic ignored "-Wdeprecated-declarations"
#include <CoreFoundation/CFBundle.h>
#include <ApplicationServices/ApplicationServices.h>
#include <Foundation/NSUserDefaults.h>
#include <AppKit/NSScreen.h>
#include <CoreFound... |
db6e201d8a4edec9afe9a3a6bba5c18fa2bb8671f838a71352326559175f8dd8 | MATLAB | 22,867 | 525 | classdef cohort
%% ------ PROPERTIES -------
properties
individual = [] ; % Array of microstate.individual objects representing each individual in the cohort
condition (:,1) double {mustBeReal, mustBeFinite} = [] ; % Array of integers labelling the condition corresponding to each individual... |
f51c6ff59abd53a645ef4947c52438fa82e7e1d257da08c3ebe9cd7877fdb31d | MATLAB | 22,970 | 508 | function [IMAGE,LABEL] = fun_small_multi_num_pos_noise_L8_backNoise_pos(num_train,num_valid,num_test,redim,max_Amp,pos_noise,dist2cen)
XTrain = loadMNISTImages('DATASET_ori\MNIST\train-images-idx3-ubyte');
XTest = loadMNISTImages('DATASET_ori\MNIST\t10k-images-idx3-ubyte');
YTrain = loadMNISTLabels('DATASET_ori\... |
c35ee8a59eb63e2a08e5863e4575395d7770786b0fe67ee0d3c2044fb6bfd3c9 | MATLAB | 23,041 | 650 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [L_meg, dipole_locations, dipole_directions] = lead_field_meg_grad_fem( ...
zef, ...
nodes, ...
elements, ...
sigma, ...
sensors, ...
p_nearest_neighbour_inds, ...
... |
a49d3fef2974b5fb0c94eeb1d402831e00a6d422a62e49306bc2a286070de7ad | MATLAB | 23,287 | 598 | function [S,NlogL,optimInfo]...
=AdvGMModeling4Rec(X,weight,k,start,reps, CovType,SharedCov, RegV, options,probtol)
%GMCLUSTER Gaussian mixture fit.
% S = GMCLUSTER(X,K) fits a K-component Gaussian mixture model to the
% data. The fit maximizes the log-likelihood of the data using
% Expectation Maximization ... |
c1947a1fbaf6e3a7d73c1d99f229c471419cdcb39c3d224d83c35670a903cb45 | MATLAB | 23,608 | 555 | function [options,data] = checkoptions (options,data,T,cv)
% Basic checks
if nargin<4, cv = 0; end
if isempty(strfind(which('pca'),matlabroot))
error(['Function pca() seems to be other than Matlab''s own - you need to rmpath() it. ' ...
'Use ''rmpath(fileparts(which(''pca'')))'''])
end
if ~isfield(options,... |
8828b746e0077d24dfd66a20bb9c117dc6d7c7bfc8e472de5f7e10b41de29661 | MATLAB | 23,709 | 621 | function [delta]=sw_detect_delta(dat,opt)
% function to detect delta waves in lfp:
% inputs:
% - fn0: string argument with filename incl path
% eg : fn0='E:\data\xyz.ncs'
% - opt: structure array with options:
% opt.filetype: filetype of raw data file:
% can be: 'ncs' - ... |
e66f3b0160fea69399d27bc81aa8b9a4fa57e72eecc8c9afc7f3afbbb2734f3a | MATLAB | 23,748 | 655 | function zef = zef_parcellation_tool_window(zef)
h1 = figure(...
'PaperUnits','inches',...
'Units','normalized',...
'Position',[0.544444444444445 1.125 0.251388888888889 0.822222222222222],...
'Visible',get(0,'defaultfigureVisible'),...
'Color',get(0,'defaultfigureColor'),...
'CloseRequestFcn',... |
cbcf7be9ed9a27d8db4a622ccd20651d91e077ec49d643eef301863981c5b54a | MATLAB | 23,844 | 650 | function [eout,thresh,gv_45,gh_135,matGrad] = getEdge(varargin)
%GETEDGE Find edges in intensity image.
% EDGE takes an intensity or a binary image I as its input, and returns a
% binary image BW of the same size as I, with 1's where the function
% finds edges in I and 0's elsewhere.
%
% EDGE supports six diffe... |
b401ee2d509b3c5c7dc8d7c794cfaa437a12082aa5e0435067fd614e7fdc4e41 | MATLAB | 23,907 | 598 | function [z,Var_loc] = MUSIC_iteration
h = zef_waitbar(0,1,['MUSIC.']);
[s_ind_1] = unique(evalin('base','zef.source_interpolation_ind{1}'));
n_interp = length(s_ind_1);
snr_val = evalin('base','zef.inv_snr');
std_lhood = 10^(-snr_val/20);
lambda_L = evalin('base','zef.MUSIC_leadfield_lambda');
sampling_freq = evalin(... |
e089e1edd1f64b2d3f1651099e640a71b4818ce63781abba4e22c823488fe521 | MATLAB | 24,081 | 662 | function [result] = inverse_SESAME(full_data, leadfield, sourcespace, cfg)
% inverse_SESAME samples the posterior distribution of a
% multi-dipole Bayesian model and provides an estimate of the number of
% dipoles and of the dipole locations and time courses; in addition, it
% provides uncertainty quantification in te... |
7d229301cf2f54c3290d1c6e3e0c7b138e22be84281024b5ed0f1cb0a74eb09b | MATLAB | 24,154 | 597 | clcl
for stiminduced_power=1;
load erspsV1_control
load erspsV1_exp
load time1
load basetime1
load basetime2
load basetime0
load time2
load time3
load t_sG1_cnoEEG
load f_sG1_cnoEEG
t_sG1=t_sG1_cnoEEG;
f_sG1=f_sG1_cnoEEG;
%the final stats are in a screenshot of an S... |
616e4650a075a4f3ea2b05ee7e375933d28c4d792c2331954230776fb283e62a | MATLAB | 24,467 | 528 | classdef zef_menu_tool_app_exported < matlab.apps.AppBase
% Properties that correspond to app components
properties (Access = public)
h_zeffiro_menu matlab.ui.Figure
h_menu_project matlab.ui.container.Menu
h_menu_new matlab.ui.conta... |
2f295aa2a9c9cdc2d319e01a09b084c0424a75beba6425392a02a46cb9a1e94e | MATLAB | 24,494 | 528 | % v4 trims duration to ~20 minutes,
% backwards from treatment time
% forwards after treatment delay
% production straight to table with all four data sets, hardcoded to _4
% 20260406 updated to export filtfilt in addition to prctfilt and movmin
version_suffix = "4v4"; % bumping this is the single point of change f... |
ee30de93ecd4f805974cdbb837475fe9f489db5710602af56f1598888c7da2b4 | MATLAB | 24,586 | 560 | function [IMAGE,LABEL] = fun_load_sameSmnist_diffPos_posNoise(num_train,num_valid,num_test,redim, pos_noise, max_Amp)
XTrain = loadMNISTImages('DATASET_ori\MNIST\train-images-idx3-ubyte');
XTest = loadMNISTImages('DATASET_ori\MNIST\t10k-images-idx3-ubyte');
YTrain = loadMNISTLabels('DATASET_ori\MNIST\train-label... |
c13c88e51f48c7cee4eec4395b2c48b16c62f4ffdd47ab28f29fb5314fdeed6a | MATLAB | 25,237 | 708 | function [Ypk,Xpk,Wpk,Ppk,wxPk] = findpeaksTD(Yin,varargin)
%FINDPEAKS Find local peaks in data
% PKS = FINDPEAKS(Y) finds local peaks in the data vector Y. A local peak
% is defined as a data sample which is either larger than the two
% neighboring samples or is equal to Inf.
%
% [PKS,LOCS] = FINDPEAKS(Y) also... |
dcd885349af511b75fd0e370ed0eabe406daeb4874293a9f0cf91e925e94606d | MATLAB | 25,740 | 809 | function m = meshLoadGmsh4( fileName )
%
% m = meshLoadGmsh4(fileName)
%
% Load a Gmsh mesh file (binary or ASCII) into a MATLAB
% struct called m. This file was copied from
%
% https://github.com/simnibs/simnibs/blob/master/simnibs/matlab_tools/mesh_load_gmsh4.m
%
% at 2025-11-17, renamed and updated to support more... |
fa97f45192b2816e255c6baad2c20486a405860c80e2c346c1af449e5d5c08a8 | MATLAB | 26,275 | 923 |
function varargout=xhtmlgr(task,varargin)
varargout={};
if 0
tic
px=pwd;
ht=xhtmlgr('copyhtml','s' ,which('formgr.html'),'t',fullfile(px,'summary.html'));
xhtmlgr('study','page',ht,'study',px);
xhtmlgr('timer','page',ht,'start',datestr(now));
xhtmlgr('show','page',ht);
... |
2c01eafbfce20ac4ad74b2c1a06e6d5dfd318f04ff6d397d0be8627d6b6e4476 | MATLAB | 26,460 | 864 | function zef = zef_ias_map_estimation_roi_window(zef)
h1 = figure(...
'PaperUnits',get(0,'defaultfigurePaperUnits'),...
'Units','normalized',...
'Position',[0.4325 0.333418803418803 0.254166666666667 0.692222222222222],...
'Visible',get(0,'defaultfigureVisible'),...
'Color',get(0,'defaultfigureColo... |
8b192b6a3a956510e06c400d089842cb3d7c3eced2e61b7c31a672a534888840 | MATLAB | 26,855 | 606 | function nse_field = zef_nse_poisson_dynamic(nse_field,nodes,tetra,domain_labels,mvd_length)
h_waitbar = zef_waitbar(0,1,'NSE solver: pressure');
if not(isfield(nse_field,'nse_type'))
nse_field.nse_type = 1;
end
if nse_field.time_integration == 1
n_q_steps = 1;
elseif nse_field.time_integration == 2
n_q_... |
4bfe11cc449a6fdee1c3acc7f37bcae0a1c3aaa041c410a9c11c452b92d25e3d | MATLAB | 26,875 | 568 | %% Nat Comms Ictogenesis Figure 6
clear
load('20230127_PooledData.mat');
%% Process DTW
DIST_DIST = [ ...
"seizureN_seizureKL"
"seizureN_seizure"
"seizureN_evolving"
"seizureN_flat"
"seizureKL_seizure"
"seizureKL_seizureKL"
"seizure_seizure"
"seizureKL_evolving"
... |
9fbe0621bb317c2b988853c80d309a0f777937ba49ba59f2cd7380148f135e3d | MATLAB | 26,982 | 571 | function [z,Var_loc,reconstruction_information] = zef_beamformer(zef)
h = zef_waitbar(0,1,['Beamformer.']);
[procFile.s_ind_1] = unique(eval('zef.source_interpolation_ind{1}'));
n_interp = length(procFile.s_ind_1);
snr_val = eval('zef.inv_snr');
std_lhood = 10^(-snr_val/20);
lambda_cov = eval('zef.inv_cov_lambda');
la... |
b08ae175485eb88ceb7d3af3454e20e9f11c1d00e78022c04df66e14b8392aa8 | MATLAB | 29,519 | 805 | function [VE1, ME1, HE1, NE1, KO1, NAI1, OO1, S1, X1, ISYN1, VE2, ME2, HE2, NE2, KO2, NAI2, OO2, S2, X2, ISYN2, t, options] = HHWUIS_solver_NCexamples_RK4(options)
ve1 = squeeze(options.InitialConditions.VE1(end, :)).';
me1 = squeeze(options.InitialConditions.ME1(end, :)).';
he1 = squeeze(options.Initial... |
419754cb9b7c40810165a4ec7238182d75c9e5aac7dbcfea81d26d1dadd6e8de | MATLAB | 29,535 | 506 | function R = weightedcorrs(Y, w)
%
% WEIGHTEDCORRS returns a symmetric matrix R of weighted correlation
% coefficients calculated from an input T-by-N matrix Y whose rows are
% observations and whose columns are variables and an input T-by-1 vector
% w of weights for the observations. This function may be a val... |
eaf696ead8113edba7f02d9eab3a4cff5cdebec7c84c978738d42d7ebb3d4802 | MATLAB | 30,369 | 602 | %% Nat Comms Ictogenesis Figure S8
clear
load('20230127_PooledData.mat');
%% DTW analysis
DIST_DIST = [ ...
"seizureN_seizureKL"
"seizureN_seizure"
"seizureN_evolving"
"seizureN_flat"
"seizureKL_seizure"
"seizureKL_seizureKL"
"seizure_seizure"
"seizureKL_evolving"
... |
7e631b7f6e20f4f2a7d3108350d38cc803206b772f356d604239a52efa6f1a46 | MATLAB | 31,285 | 1,065 | function run(segmentation_output_folder, recon_all_output_folder, kwargs)
%
% fs2zef.run (segmentation_output_folder, recon_all_output_folder, kwargs)
%
% Uses the external program FreeSurfer version 8.1.0 to generate a segmentation,
% that can then be imported to Zeffiro interface. Optionally, a [FreeSurfer]
% reconst... |
ff27ba8bf4c7560151a688c24542dc4adc6d76a96702039aec9a38094faad384 | MATLAB | 31,296 | 498 |
if isequal(zef.h_eit_sensitivity_tool_distribution.Value,zef.h_eit_sensitivity_tool_distribution.Items{1})
%Sigma 1
i%f isequal(questdlg(['Apply: ' zef.h_eit_sensitivity_tool_distribution.Items{1} '?']),'Yes')
zef.sigma(zef.brain_ind,1) = 1/4*(zef.eit_sensitivity_tool_data.avg(zef.source_interpolation_ind... |
06153af6aedec2f008a500fbe9a9677f3192f905554939525dcc5281fe0d8a5c | MATLAB | 31,386 | 612 | function zef = zef_import_segmentation(zef, file_name, folder_name)
if nargin == 0
zef = evalin('base','zef');
end
domain_label_counter = 0;
atlas_on = 0;
if nargin < 3
if zef.use_display
[file_name, folder_name] = uigetfile({'*.zef;*.mat'},'Segmentation data file and folder',eval('zef.save_file_path'... |
bb4f48b565e42ee1511ec38be9f207fab4073f9ce3a09ff260399ed68fda632c | MATLAB | 33,370 | 1,008 | function varargout = venn (varargin)
%VENN Plot 2- or 3- circle area-proportional Venn diagram
%
% venn(A, I)
% venn(Z)
% venn(..., F)
% venn(..., 'ErrMinMode', MODE)
% H = venn(...)
% [H, S] = venn(...)
% [H, S] = venn(..., 'Plot', 'off')
% S = venn(..., 'Plot', 'off')
% [...] = venn(..., P1, V1, P2, V2, .... |
596377f7b4ad2ad202b20561bea1c7db5d6894f040b53fb54bf5919704f3db57 | MATLAB | 33,419 | 789 | function [trainedNet, info] = trainNetwork2(varargin)
% ========================================================
% dir = C:\Program Files\MATLAB\R2019a\toolbox\nnet\cnn
% ========================================================
% trainNetwork Train a neural network
%
% trainedNet = trainNetwork(imds, laye... |
e9859136d4f5d32b316a7cc7cbf924dd92fe8ba2d52aca17e42b6c6467e0819b | MATLAB | 33,419 | 789 | function [trainedNet, info] = trainNetwork2(varargin)
% ========================================================
% dir = C:\Program Files\MATLAB\R2019b\toolbox\nnet\cnn
% ========================================================
% trainNetwork Train a neural network
%
% trainedNet = trainNetwork(imds, laye... |
31a1e308abbdeb93495ff00b4d23153e970e4bf67b6f62baf2ac2d31b0e79d7e | MATLAB | 33,586 | 974 |
clcl
rednumber=4; %redundant to analyse. i used 4 for main fig; 4 is the "third" in the sequence
limtrials=10; %limit trials in all conditions to this. if 0, it wont do it;
for fileload=1;
matchy=0;
files1={''};
files2={'';};%;
end
%% do control
for makematrices=1;
erspsV1=[];
itcsV1=[];
... |
c154fb1e3490f299115288d0e2045d2b8b1e87617a06bf3810d7d641a3b26416 | MATLAB | 33,776 | 831 | function sSynthesis = getPreProSynthesis(sFile,sRP)
%% show msg
ptrMsg = dialog('Position',[600 400 250 50],'Name','Source synthesis');
ptrText = uicontrol('Parent',ptrMsg,...
'Style','text',...
'Position',[20 00 210 40],...
'FontSize',11,...
'String','Loading clustered data...');
movegui(ptrMsg,'center')... |
9eb0f86065ced66de012018d9c5560e5520c95729bafc18a45c3198f439ed430 | MATLAB | 33,869 | 686 | function Fun_SpectralAnalysisTC(Path, Subject, NumberOfFilesPerSubject,...
FileNamesForSubjects, NumberOfEpochs, NumberOfSpectrumValues,...
SpectraTC, ScoringTC, NumOfTimePoints, TimeBin, Frequencies,...
DeltaThetaLimits, NumOfScoringsForSpectra, ScoringMappingForSpectra)
%% Written and upda... |
c04af13d739716d6a51ca497c70c7f6f15e2bad1cc908913efa49ae65b53ae61 | MATLAB | 35,226 | 810 | function [x, cost, info, options] = trustregions(problem, x, options)
% Riemannian trust-regions solver for optimization on manifolds.
%
% function [x, cost, info, options] = trustregions(problem)
% function [x, cost, info, options] = trustregions(problem, x0)
% function [x, cost, info, options] = trustregions(problem,... |
485f07e1962c3279a2244986b658e108c11e71618cd6ed0e9489a4ef05e9f765 | MATLAB | 38,076 | 977 |
clcl
clear all
rednumber=4; % the number redundant to analyse
limtrials=10; %liman it trial is in all conditions to this. if 0, dont do it
dopowstandardize=0; %this is for standardizing the data for assessing baseline power. it takes time, so only do it when youre going to analyse power.
docontrol=0; % 1 = cno only.... |
902c279b2f2b87f62e9ea2a79601f8802f9dd9c790f3cf49b2228c76762ba998 | MATLAB | 40,149 | 1,158 |
% xQAregistration: calculate registration-based quality metric (standard-space comparison)
% -this procedure evaluates the animal registration quality to standard space
% -the [gm]-approach: the gray-matter compartement is warped to standard-space and compared with
% the gray matter image of the template (metric... |
0d94afa4ec6031ffa561aebe9fce1d546d991ad0984d6826f184d7ccdae074e3 | MATLAB | 43,896 | 1,009 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function zef_plot_volume(varargin)
zef = evalin('base','zef');
f_ind = 1;
cdata_counter = 1;
if isfield(zef,[zef.current_sensors '_get_functions'])
zef = zef_fix_sensors_get_functions_array_size(zef... |
f0ad77a0424a0a897ddebbbd343ddc7bc0132ea46c00426142b2270cd177316f | MATLAB | 44,840 | 947 | classdef individual
%% ------ PROPERTIES -------
properties
data double % Number of samples x number of channels (or ROIs) array of MEG/EEG/source/amplitude envelope time courses
time (1,:) double {mustBeReal} % 1 x number of samples array containing the time axis
sample (1,:) doub... |
601e7e9e96854946cbacd52057d4fc8dd2ac5fb2c5a119365bdf27491007ef7e | MATLAB | 47,473 | 1,023 | tic,
%%%%%%%%%%%%%%%%%%%%%%%%%% Fig.2 %%%%%%%%%%%%%%%%%%%%%%%%%%
Vm_p = linspace(-2,2.5,500);
k1p = 2.088; k1m = 0.01479; k2p = 0.7648; k2m = 8.54e-05;
k3p = 0.2698; k3m = 1.472; k4p = 3.129e-08; k4m = 0.0971;
k0d_Nao = 0.4982; k0d_Nai = 5.034; k0d_Ko = 0.6084; k0d_Ki = 0.6787;
k0d_Csi = 9.0; kd_... |
2057cb99c321f41df283c59d3adec8c6d231b2a758fb5485593a0826deddad80 | MATLAB | 49,050 | 1,001 | %%% opto
clear all
for file_load=1;
%pre
files = {'';};%
% % %post
files = {'';};%
end
limtrials1=10; %limit the number of trials analysed for each stimulus type(control/redundandt/deviant).
baseBEGIN=1; baseEND=12; %what you call the baseline
BEGINo=14; ENDo=28; %these are the analysis window... |
59bfb4ca517a28b6370bb3c5140634096a2ede44f3a3ebd20485c7c397ced226 | MATLAB | 51,067 | 1,163 |
function [streams,fileheader] = load_xdf(filename,varargin)
% Import an XDF file.
% [Streams,FileHeader] = load_xdf(Filename, Options...)
%
% This is a MATLAB importer for multi-stream XDF (Extensible Data Format) recordings. All
% information covered by the XDF 1.0 specification is imported, plus any additional meta-... |
0d88fe8b31166cfb85a0d418038c75288a3b15fcd8ac07a7a591b9588f2d67ea | MATLAB | 60,290 | 1,447 | function [rew,raw]=mcdcov(x,varargin);
%MCDCOV computes the MCD estimator of a multivariate data set. This
% estimator is given by the subset of h observations with smallest covariance
% determinant. The MCD location estimate is then the mean of those h points,
% and the MCD scatter estimate is their covariance matr... |
cd4fb5923ee4252d2bccf64f49f2f8635a793389abdc7d946d50a937a01831ee | MATLAB | 61,847 | 1,701 | % License & disclaimer.
% ------------------------------------------------------------------------------
% Copyright 2019 Dumoncel Jean
% Modified by Edwin de Jager (2023)
% ------------------------------------------------------------------------------
%
% IMPORTANT
% If you use this program for your publ... |
98a9743a0fcc55bbfd547c835554f61c66985d7d172afef3a6a1cd46f1cbbbb0 | MATLAB | 63,293 | 1,266 | %Copyright © 2018- Sampsa Pursiainen & ZI Development Team
%See: https://github.com/sampsapursiainen/zeffiro_interface
function [void] = zef_plot_meshes(~)
zef = evalin('base','zef');
f_ind = 1;
cdata_counter = 1;
if isfield(zef,[zef.current_sensors '_get_functions'])
zef = zef_fix_sensors_get_functions_array_size(z... |
64afe1fcf0f817727b6b909bfc6a391eb776c0be79fa7b6b7058bcf93a57584c | MATLAB | 70,189 | 1,452 |
clcl
for file_load=1;
files = {''}; %%
end
%run "forOSI.m" first
limtrials1=10; %limit the number of trials analysed for each stimulus type(control/redundandt/deviant).
baseBEGIN=1; baseEND=12; %what you call the baseline
BEGINo=14; ENDo=28; %these are the analysis windows. note: stimulus starts at 14 and finishes at... |
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