sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
06a1ea4678d22523bf825831ee1b0dc74c85f1be666083ccc092aaa36344d443 | MATLAB | 11,767 | 240 | clear all
close all
target= '151008';
if ispc
home = 'C:\'; %[getenv('HOMEDRIVE') getenv('HOMEPATH')];
pat = [home 'Analysis\AssemblyAnalysis\raw\KDE_bins'];
separator='\';
elseif ismac
path(path,'/Users/aleksanderdomanski/Documents/Bristol_work/assembly_analysis/MichalDataAna')
home = gete... |
6c77c4a01050c974b049d7627b3d0572edddec07263555ae937ca06c9e6bd2d2 | MATLAB | 11,807 | 271 | % ----------------------------------------------------------------------
% [staircase, stairParams]=usePalamedes(stairParams,response)
% ----------------------------------------------------------------------
% Purpose: Initialize and update adaptive procedures.
% This function simply calls the Palamedes too... |
3e3d678113c86b5c9d4eec2d27423f2d8bf78f0648cc974a8a60d321665f7066 | MATLAB | 11,816 | 340 | % PURPOSE : Marking epochs containing activity above an upper threshold and below a lower threshold
%
% FORMAT :
%
% >> EEG = pop_artextval(EEG, parameters);
%
% INPUTS :
%
% EEG - input dataset
%
% The available parameters are as follows:
%
% 'Twindow' - time period (in ms) to apply ... |
54134cbe7291110853f2f8ce0b9d5cfc5fb30d800423b7c8af35200f5e68db1d | MATLAB | 11,826 | 352 | %This is a program that plots different response categories in the two eye
%experiment. data is in TwoEyeAnalysis/ISI20/LXLXCXCX. Created by Haleh
%Fotowat
close all
clearvars
path=uigetdir;
cd(path)
load('Peaks_EXPFits_ClustsNew_LXLXCXCX_v2.mat')
%% generate bar plot for all dimming responsive neurons
eye1=[0,1,2,3]... |
47a2b4e97451233bf8bb45e3a1d1ac66c36ce80d73f8f293bda45a601555212e | MATLAB | 11,881 | 597 | function EuclideanDistancePopulationDecoder
% Try out Euclidean Distance Classifier: Spike Train
% Created 08/22/17
clear all
close all
clc
tic
%---Initiate Path---%
if( isunix )
Path = '/Volumes/JUSTIN EXHD/DataStore/';
else
Path = 'E:\DataStore\';
end
%---FLAG---%
Save = 1;
option = 1; %---0: All... |
0939db160d98a6c1bd74cba546b2785c3ddc64386cffea81ed4e2e206198a5c4 | MATLAB | 11,889 | 201 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Analysis of time spent in vigilance states
% Script written: Lukas B Krone 2021 based on previous scripts from the Vyazovskiy lab
%
% INPUT:
% - "-VSspec" files for one EEG channel for each date with a different injection condition (... |
8838eb52d1026825fb51a6577217a548e789591bf35bd5f4dcb8dfa3d546257b | MATLAB | 11,890 | 262 | function [Jx_bar, Jy_bar] = solveClosureProblem(problem, Edir, boundary_type, skin_map)
% This function takes an input problem (specified in the traditional
% 'problem' format used by the monodomain solver code) and solves the
% steady-state diffusion problem with no reaction term, but subject to an
% external electric... |
f0bebdfc6e0f7886664a3d774a92c246512ab4f7b900b017fd86bc4bf3bdf53b | MATLAB | 11,925 | 391 | %% BCI dataset, Ulster University
% Pipeline_correlation analysis
% Writtern by Vahab Youssof Zadeh
% Update: 08/10/2022
clear, close all
%% Initial settings
%- Brainstorm dir
bsdir = '/data/MEG/Research/BCI_Ulster/BCI5';
bs_path = '/opt/matlab_toolboxes/brainstorm3';
addpath ./functions
addpath ./data
ft_path = '/o... |
d836650f40f01703304eb3b6ea9409274ad2eb972f0b27a3df52d2e234d83226 | MATLAB | 11,935 | 358 | % PURPOSE : Create BEST (.mat) file for the loaded subject bin-epoched (.set) file for decoding analyses.
%
% FORMAT :
%
% >> [BEST] = pop_extractBEST(ALLEEG,parameters);
%
% INPUTS :
%
% EEG or ALLEEG - input EEG dataset
%
% The available input parameters are as follows:
%
% 'DSindex' -... |
0876e8cdd6f7dc2b14109d2843b796ad6ebe1ff7618927e9736d3776aa6b16ef | MATLAB | 11,939 | 290 | %% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Delays__ = {'4s','8s','16s'};
Target = 'LONG';
RunErrors = false;
tlimsAll = [0 5];
tlimsShort=[0 4];
tlimsMedium=[0 8];
tlimsLong=[0 16];
shift = 0;
plotOnline = false;
bw = 0.05;
Nbs = 500;
tbShort=tlimsShort(1):bw:tlimsShort(2);
tbMedium=tli... |
587293b5e8a13d775c2bfc1831bc509914eaf7e2488cc0eae72742ba874248c7 | MATLAB | 11,947 | 276 | %%
% Compares continuous L/R discrimination during the delay period,
% calcluated on short/medium/long delay trials independently
%% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Delays__ = {'4s','8s','16s'};
DelaysDur = [4,8,16];
Target = 'LONG';
tlimsAll = [-30 30];
tlimsTrials = [... |
e4f2f679cf3ad0b778beb008a0e9d1be36750dbd6258ede52df8b8e0260cf930 | MATLAB | 11,957 | 326 | % PURPOSE: Creates a text version of the ERPLAB's EVENTLIST structure
%
% FORMAT:
%
% [EEG EVENTLIST] = creaeventlist(EEG, EVENTLIST, lfname, wf)
%
% Inputs:
%
% EEG - input dataset
% EVENTLIST - ERPLAB's EVENTLIST structure
% lfname - full filename of EventList file to save (*.txt)
% wf - write... |
b1850188e08b0db21a3504bafafff43b43b3b6f39674f72c1b2aae6f18f2661a | MATLAB | 11,962 | 363 |
function scatter_colormap_lin_fit(data_struct, varargin)
% Plot data points from different groups.
% cfr scatter_with_colormap
% used in test_SO_inference (colormap) and CN_analyze_ratings (lin fits).
%
% data_struct
% Structure array with one entry per group of data, which will be
% associated with a mar... |
56bb25b54e672f1a467bb9fd5ba052eba13586e4add475e58b57711afb0a3b1e | MATLAB | 11,966 | 316 | classdef Grid < uix.Box
%uix.Grid Grid
%
% b = uix.Grid(p1,v1,p2,v2,...) constructs a grid and sets parameter
% p1 to value v1, etc.
%
% A grid lays out contents from top to bottom and left to right.
%
% See also: uix.HBox, uix.VBox, uix.GridFlex
% Copyright 2009... |
00e6db94fa0dedb3b608d56ff643f370e05086a341fbd27688b7096d379de276 | MATLAB | 11,975 | 286 | %%
clear all
close all
run(['..' filesep 'def_local'])
addpath(genpath(path_mTRF))
%%
allfiles={'405','406','407','408','409','410','411','412','413','414','415','416','417','418','419','420','421','422','423'};
StimProfiles_freq=([2 8]);
all_Rec=[];
all_Cond=[];
all_Samples=[];
all_Types=[];
all_CodeStim=[];
directi... |
10e99ae8487909bb681c872c6b7ca6f7e05b7dd7cb8f38704442b486364cb8b9 | MATLAB | 11,995 | 281 | classdef Model
%MODEL Summary of this class goes here
% Detailed explanation goes here
properties(SetAccess=immutable)
nerveModel char
electrodeType char
electrodePlacement char
paramSet char
baseName char % Name WITHOUT paramSet
fullName cha... |
253aaca24dca9da279a0bbdd8c17d329d00cbca14ba745a3b98185d7df06f102 | MATLAB | 12,009 | 376 | classdef ConfidenceScorer < DeepActionProject
properties
Method
Temperature
end
methods
function self = ConfidenceScorer(project, method)
self = self@DeepActionProject(project.ProjectPath)
self.Network = project.Network;
self.Method = method;
... |
6990902039a61d2dc96ad876f2ca92620eaaf1221843c1cf9aa662be373c48dd | MATLAB | 12,019 | 358 | % PURPOSE : Loads ERPset(s)
%
% FORMAT :
%
% ERP = pop_loaderp(parameters);
%
% PARAMETERS :
%
% 'filename' - ERPset filename
% 'filepath' - ERPset's filepath
% 'overwrite' - overwrite current erpset. 'on'/'off'
% 'Warning' - 'on'/'off'
% 'multiload' - load multiple ERPset usin... |
ff78af4e63bb1d9f163a1f2f99a910918b611d6176cf0474e58c935d61f9654c | MATLAB | 12,057 | 604 | function CorrCoefPopulationDecoder
% Try out Correlation-based Classifier: Spike Train
% Created 08/18/17
clear all
close all
clc
tic
%---Initiate Path---%
if( isunix )
Path = '/Volumes/JUSTIN EXHD/DataStore/';
else
Path = 'E:\DataStore\';
end
%---FLAG---%
Save = 1;
option = 1; %---0: All units; 1:... |
7e6ab7e8386050f08f252bc3c8dd55fec32aaf68acdba9040bbb1095edd9e37b | MATLAB | 12,078 | 393 | function varargout = gexf(filename,A,L,S,options)
% [filename] = gexf(filename,A,[L],[S],[options])
%
% Writes a formatted XML file for use with Gephi.
%
% Complies with GEXF 1.2draft format: https://gephi.org/gexf/1.2draft/gexf-12draft-primer.pdf
%
% Only the adjacency matrix, A is required. All other fields have de... |
c51fa778a51fc8f53db30991d249f072205efce5a3a301da2699bc31e0726553 | MATLAB | 12,116 | 389 | function varargout = Appetitive_detection_GUI_v2(varargin)
% GUI for appetitive detection task
%
%To do:
%Add trial order control (ascending, descending, shuffled)
%Add bandwidth cutoffs
%
%
%Written by ML Caras Jun 10, 2015
%Updated Apr 26, 2016
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_Sta... |
52d0371fa0c8d62ab34319d88dddedbe64fa207bd22c8737e511ae6e06ecd5ae | MATLAB | 12,120 | 502 | clear all;
% Gives me: X (labels), Y (data), time, label
tmp = load('../data/testdata_orientation.mat');
Y = tmp.Y; % Y: features x time x trials
X = tmp.X';
time = tmp.time;
label = tmp.label;
phi = X * (180/8); % Presented orientation in degrees
numF = size(Y, 1);
numT = size(Y, 2);
numN = size(... |
a6a2e732d168922c474a19c29f83536d4b19d2d78d8ebe31ccb08a40439dabfd | MATLAB | 12,125 | 278 | function result=psignifit(data,options)
% main function for fitting psychometric functions
%function result=psignifit(data,options)
% This function is the user interface for fitting psychometric functions to
% data.
%
% pass your data in the n x 3 matrix of the form:
% [x-value, number correct, number of trials]
... |
4b33e10e354351dc6ed1980553a0f8ab35ecdcdd3a217158d267b74e42bb23e5 | MATLAB | 12,137 | 406 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
%% setup vars
thr_vals = [ 0 0.05 0.1 0.15 ] ;
filename = [ DD_INTERM '/' OUTSTR '_divergences_n_outlierdetect.mat' ] ;
divo = load(filename) ;
ff = [ PROJ_DIR '/reports/lab_meeting/... |
33c6408242698f9ccda6b8ea29f916fb52aa4b012c4c51b7048c6ae2c44a3557 | MATLAB | 12,167 | 252 | clear all
close all
target= 'Task';
if ispc
home = 'C:\'; % [getenv('HOMEDRIVE') getenv('HOMEPATH')];
pat = [home 'Analysis\AssemblyAnalysis\Sleep'];
separator='\';
elseif ismac
path(path,'/Users/aleksanderdomanski/Documents/Bristol_work/assembly_analysis/MichalDataAna')
home = getenv('HOME... |
10179d9526c87f89f0cda168e7e65c1c11d3ef24c6249ca477f451f18c470dba | MATLAB | 12,168 | 334 | function big_brain_maps_AAL116
%
% Function to make fig1 for the test retest paper
%
%
% Fran Hancock
% Aug 2021
% fran.hancock@kcl.ac.uk
%
% This function needs plot_nodes_in_cortex and
% MNI152_T1_10mm_brain_mask.nii aal_cog_txt
%
%%%%%%%
%
% Set up the paths to the functions, libraries etc
%
%
PROJECT = '/Users/HDF... |
e6ffdeb898b59c6df17f0972cc438faa1fdd09b907e861ce06c19fb5737646c6 | MATLAB | 12,204 | 295 | %% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Delays__ = {'4s','8s','16s'};
Target = 'LONG';
RunErrors = false;
tlimsAll = [0 5];
tlimsShort=[0 4];
tlimsMedium=[0 8];
tlimsLong=[0 16];
shift = 0;
plotOnline = false;
bw = 0.05;
Nbs = 500;
tbShort=tlimsShort(1):bw:tlimsShort(2);
tbMedium=tli... |
caacc4ad1d4216168a9a6c652455318edd9dbe0b42ecad858a616e7f4eb54b61 | MATLAB | 12,238 | 320 | % Fig8_b and Suppl.Fig_6
% Code to generate behavioral analysis for detection task with optogenetic stimulation
% load data
addpath data
load('Fig8_b_data','tr', 'sessionIDs')
%% recalculate the correct fals alarm rate
[ out, tr ] = recalcFalseAlarms( tr );
%% collect trial outcomes per condition
sessionSelection = ... |
1eb98b5c90c2123ad0cc0a730d2037e537804ca734dc97ccc578b139bf9804bf | MATLAB | 12,284 | 269 | %% Determine a participant's steady-state performance in OH/OHA/TOH/TOA
% Automatically detects three phases of task performance (early/easy,
% at-limit, and overwhelmed) and calculates some phase-related statistics.
% Copyright (C) 2022 Richard Hugh Moulton
%
% This program is free software: you can redistribute ... |
efef39821c5d4bd63aa35e269ceda13385dadbc8dc37acc5c9b5c8cff6de9e60 | MATLAB | 12,286 | 315 | %%
clearvars
close all
clc
for well_num = 1:42
get_wells = strcat('*COMPLETED_Rat_MEA2Pharma_DIV22_raster_3D*');
filelist = {dir(get_wells).name};
numoffiles = length(filelist);
for i=1:numoffiles
load(filelist{i});
if size(actual_contribution,1)>=1
% for valid file, extrac... |
4e104feaffd510a09b6af293601835e71c22749931112daf41fec2f12c3c8461 | MATLAB | 12,292 | 319 | function map=pmkmp_new(n,scheme)
% PMKMP Returns perceptually balanced colormaps with rainbow-like colors
% PMKMP(N,SCHEME) returns an Nx3 colormap.
% usage: map=pmkmp(n,scheme);
%
% JUSTIFICATION: rainbow, or spectrum color schemes are considered a poor
% choice for scientific data display by many in the scientif... |
00959eb6ee386b041a67bbb2626238226faa710ba13c9d2955a86f53d34a890a | MATLAB | 12,302 | 309 | function [A,B,C,Init_dim,SET] = func_Prepare_Data(Parm)
%Prepare_Data with DeepInsight
%
%Description of Datasets
% 1. dataset1.mat is RNA-seq (1.5GB)
% 2. dataset2.mat is ringnorm-DELVE (560KB)
% 3. dataset3.mat is vowels (3.6MB)
% 4. dataset4.mat is Madelon (2.1MB)
% 5. dataset5.mat is Relathe (696KB)
if Parm.SnowF... |
b3f05ecb385787208c9e1401055af326d05c5962e60a8630bf649e742907d924 | MATLAB | 12,305 | 296 | %Author: Guanghui ZHANG--zhang.guanghui@foxmail.com
%Center for Mind and Brain
%University of California, Davis
%Davis, CA, USA
%Feb. 2022
% ERPLAB Studio
function varargout = f_ERP_history_GUI(varargin)
global observe_ERPDAT;
addlistener(observe_ERPDAT,'Count_currentERP_change',@Count_currentERPChanged);
addlistener... |
6147e0f1c1a82a7bb09404bbc868c2592410e7f17076b7f66089ce68f323abb4 | MATLAB | 12,369 | 517 | clear all;
% Add the toolbox
addpath('../');
% Gives me: X (labels), Y (data), time, label
tmp = load('../data/testdata_orientation.mat');
Y = tmp.Y; % Y: features x time x trials
X = tmp.X';
time = tmp.time;
label = tmp.label;
phi = X * (180/8); % Presented orientation in degrees
numF = size(Y, ... |
9e6b708ab5956d3b8a97da0f769c69545ffc9fa77f6aa870d147c6cf633a02df | MATLAB | 12,390 | 306 | %% demo_006 additonal functionality
% This demo shows some convenience functions we added, which are not
% directly used for the final fitting of psychometric functions.
% We will need some fitted function for illustration. Thus we first fit our
% standard data from demo_001.m again:
data = [...
0.0010, 45.0... |
093dd5e7c14eb198a25bfd633a2ab8de1458fe81b9eb67e49716e95c2ea12682 | MATLAB | 12,423 | 252 | restoredefaultpath
clc; clear; close all force;
data_name='PPMI';
base_path = fullfile('C:\Users\Vincent\Desktop\scratch');
out_path = fullfile(base_path, 'output'); addpath(out_path);
codes_dir = fullfile(base_path, 'ET_biomarker', 'tab_data');
sub_list_file = fullfile(codes_dir, [data_name,'_subjects.list']); % re... |
7af204faec6c4d897b06d295e38015a868ffc2fb81a125e605d37f772d9ab509 | MATLAB | 12,434 | 354 | function varargout = gui_erplabShiftEventCodes(varargin)
% GUI_ERPLABSHIFTEVENTCODES MATLAB code for gui_erplabShiftEventCodes.fig
% GUI_ERPLABSHIFTEVENTCODES, by itself, creates a new GUI_ERPLABSHIFTEVENTCODES or raises the existing
% singleton*.
%
% H = GUI_ERPLABSHIFTEVENTCODES returns the handle to a... |
e467daa4bc15301099cace3834e00f2faf06727e2a7eda9441845f080b64ea3c | MATLAB | 12,435 | 322 | function DB_CreateDatabase(name)
% DB_CreateDatabase(name)
%
% Use to create all tables for a new database with the name of the input
% parameter NAME.
%
% DJS 2013
dbs = dblist;
if any(strcmpi(dbs,name))
% fprintf(['A database called "%s" already exists on the server ', ...
% '..... |
5addd997a3e6941e8a8de86c6c6e3ed8d084196138641ad8dff596f9d72390c0 | MATLAB | 12,469 | 512 | setUpPaths
%%
for len=1:length(fileNames)
processData
%%
if Nexps ==4
ExpCond=3;
else
ExpCond=5;
end
%%
clear ExpectMeaned Sig
for expect =1:3
if expect ==1
trials =(RandTrials);
elseif expect ==2
trials=StoreType==1 & NewSupriseSt... |
130955458a5117e0dab99094c51280c78a94a561b763328b05b905d164c98fc2 | MATLAB | 12,501 | 391 | %
% Author: Javier Lopez-Calderon & Steven Luck
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% ERPLAB Toolbox
% Copyright © 2007 The Regents of the University of California
% Created by Javier Lopez-Calderon and St... |
50948318e598af088188d0298278ae0ccc3358a544b6dceacb30d458c56ca659 | MATLAB | 12,519 | 352 | %
% Author: Javier Lopez-Calderon & Steven Luck
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% ERPLAB Toolbox
% Copyright © 2007 The Regents of the University of California
% Created by Javier Lopez-Calderon and St... |
aa25d140fffd8a5e17842d64198bae3b70f47a779ccde6326cd7dd099ad5f486 | MATLAB | 12,537 | 574 | % Spike-count and Spike-timing coding strategies of neurons
% Analysis Parameters
analysiswin = [0 0.65];
nReps = 500;
gw_durations = 2.^(0:7); % gaussian window duration (ms)
binsize = 0.001; % ensure binsize is small enough so that only one spike per bin
% 1/24414 = 4e-5
DB = 'ds_a1_aaf_mod_mgb';
... |
3defc8e8c0c07ed59ed1fc20fdf0eceb4a0a01328d9b5871d36de10415c6342f | MATLAB | 12,539 | 308 | %% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Delays__ = {'4s','8s','16s'};
Target = 'LONG';
shift = 0;
plotOnline = false;
bw=0.05;
Nbs = 500;
warning ('off')
if ispc
pat = 'C:\Analysis\AssemblyAnalysis\raw\';
else
pat = '/Volumes/HDD2/DNMTP/raw/';
end
cd(pat)
fileLis... |
d85a16ecb7868560be1870c054f4de7555c62ffa6f54e0124725efb4b83c5857 | MATLAB | 12,602 | 423 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
%% setup vars
thr_vals = [ 0 0.05 0.1 0.15 ] ;
filename = [ DD_INTERM '/' OUTSTR '_divergences_n_outlierdetect.mat' ] ;
divo = load(filename) ;
ff = [ PROJ_DIR '/reports/lab_meeting/... |
c8686fa033e03f11936bd31928ca0aff4b08f5b55ceff6a380644327f9fe3c29 | MATLAB | 12,609 | 445 | function A = set_up_C_matrix(G, mesh, c_idx)
%set_up_C_matrix Set up matrix for the finite difference equations
% for the concentrations (part that do not depend on phi)
% Load parameters
N = G.N;
Nx = G.Nx;
Ny = G.Ny;
dt = G.dt;
D_func = G.D_func;
% Load grid point mesh
e_lsw = mesh.e_lsw;
e_lse = mesh.e_lse;
e_lnw... |
220587f83ac72d5e55d8430690871df15ad34dd715f151e517169edb358f5cb0 | MATLAB | 12,632 | 312 | %% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Delays__ = {'4s','8s','16s'};
Target = 'LONG';
shift = 0;
minTrialCount = 3;
subsampleTrials = false;
BootstrapCI_TS = true;
nDrawsTrials = 50;
Nbs = 500;
bw=0.05;
tlimsAll = [-5 5];
tbAll = tlimsAll(1):bw:tlimsAll(2);%0:bw:2*sum(abs(tlimsAll));
cl... |
b5332036c59ae8cb0e5242fc7a01f0d846bafebc0eb333c167c7880bc74c76d4 | MATLAB | 12,693 | 626 | function SVMPopulationDecoder
% Try out Support Vector Machine (SVM): Spike Train
% Created 08/14/17
clear all
close all
clc
tic
%---Initiate Path---%
if( isunix )
Path = '/Volumes/JUSTIN EXHD/DataStore/';
else
Path = 'E:\DataStore\';
end
%---FLAG---%
Save = 1;
option = 1; %---0: All units; 1: Kmea... |
e624f3950a0c7855384a414aa96dd03b528092ca091c8fd845bde933f7d837aa | MATLAB | 12,734 | 486 | function [smooth_f, df, disc_f, optimal_alpha, noise_power, acc_power] = ...
extractSmoothDerivative(noisy_f, sampling_frequency, hardThres, plotFlag)
%
%
% [smooth_f, df, disc_f] = ...
% extractSmoothDerivative (noisy_f, sampling_frequency)
%
% Goal:
% 1. Given 1d noisy (temporal) signal, estimate its... |
4b364fa8b82c805eea77d52194c82fc1f4da4eaf3d9dd06ab7700d19f09194a6 | MATLAB | 12,750 | 335 | function sif_generator_grad(name,project_path,bodies,mat1,mat2,nboundaries,boundary1,boundary2,boundary3,temp1,temp2,temp3)
%bodies can be 1 or 2 1-->99 2--> 56 and 78
%boundaries goes from 1 to 3
%mat1 and mat2 are the material heat conductivities (1 or 0)
lb = sprintf('\n');
%generat... |
e3d64681aeec9ab8467b5c2b8eea06d325eb1a791834e90691242677983aafb1 | MATLAB | 12,750 | 335 | function sif_generator_flux(name,project_path,bodies,mat1,mat2,nboundaries,boundary1,boundary2,boundary3,temp1,temp2,temp3)
%bodies can be 1 or 2 1-->99 2--> 56 and 78
%boundaries goes from 1 to 3
%mat1 and mat2 are the material heat conductivities (1 or 0)
lb = sprintf('\n');
%generat... |
302e17d08ebd206a715c59b16778f1c758db8ae18eb00ecebb750bb8363cbeb0 | MATLAB | 12,778 | 309 | clear all
close all
target= 'physostigmine';
if ispc
home = 'C:\'; % [getenv('HOMEDRIVE') getenv('HOMEPATH')];
pat = [home 'Analysis\AssemblyAnalysis\raw\KDE_binsTaskonly\'];
pat_ = [home 'Analysis\AssemblyAnalysis\raw\'];
elseif ismac
% path(path,'/Users/aleksanderdomanski/Documents/Bristol_wor... |
9d55f3896c7e36fe7c94170a3cceab45d963e788cf6a6a5fd620b59fe44410ba | MATLAB | 12,783 | 434 | %
% Author: Javier Lopez-Calderon & Steven Luck & Guanghui ZHANG
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009 & 2022
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% Copyright (C) 2008 Javier Lopez-Calderon & Steven Luck,
% Center for Mind and Brain, Univer... |
6b3fbcae1b0e71722a7aaf4d40b36b653e8beafc5b16206bc00764bf72a07cd4 | MATLAB | 12,809 | 409 | function varargout = Appetitive_detection_GUI_v2(varargin)
% GUI for appetitive detection task
%
%To do:
%Add trial order control (ascending, descending, shuffled)
%Add bandwidth cutoffs
%
%
%Written by ML Caras Jun 10, 2015
%Updated Apr 26, 2016
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_Sta... |
fd522a7b96586dbec4154a409fa550a93fbc292546300b4d19f61db2594daba0 | MATLAB | 12,837 | 377 | function [] = plot_heatmap_insets(fig_name, x_vec, y_vec, all_data, cmap, ...
label_str, y_label, x_label, x_vec_R, mean_R, std_R, x_vec_T, mean_T, std_T, ...
varargin)
% Display a colormap with Right and Top insets.
%
% x_vec_R, mean_R, std_R: data for the Right inset.
% x_vec_T, mean_T, std_T: data for... |
333fc115e73fb8fca51f7090131660f3fb4b704b265155ba6e3c83663c652e2d | MATLAB | 12,865 | 401 | function varargout = mvpa_save_multi_file(varargin)
% MVPA_SAVE_MULTI_FILE MATLAB code for mvpa_save_multi_file.fig
% MVPA_SAVE_MULTI_FILE, by itself, creates a new MVPA_SAVE_MULTI_FILE or raises the existing
% singleton*.
%
% H = MVPA_SAVE_MULTI_FILE returns the handle to a new MVPA_SAVE_MULTI_FILE or t... |
1219d2a8ea0367d7bf5f633138c579c12b3f193c8df058bce965cfaba24dd986 | MATLAB | 12,869 | 287 | function testlat(input_folder,output_folder)
%
% testlat -- test laterality
% ==========================
%
%
% JOURNAL ARTICLE
%
% Civier O, Sourty M, Calamante F (2023) MFCSC: Novel method to calculate mismatch between functional and structural brain connectomes,
% and its a... |
232bb53eee880d48152326ad379c7deebac00475f628d8be6f66dbffa91d247e | MATLAB | 12,877 | 349 | %% Compares performance in two tasks on a "per-subject" basis
% Given two tasks, this script compares them by analysing the performance
% of subjects who performed both tasks. The user has the option of
% comparing this performance between all aligned pairs of trials for
% subjects, or only each subject's first pai... |
c0a49c1e9f221719efc04f0586ea886ff4aa2acf5563eda604485d0db0bc9c34 | MATLAB | 12,898 | 380 | %% CONN Pipeline
% Preprocess data using CONN toolbox according to a predefined parameters.
%
% Directory/file scheme:
% root dir: .\SUBJECTS\{Subject Name}\
% T1: .\{PROTOCOL}\mSUBJECTNAME_T1.nii
% T2*: .\{PROTOCOL}\mSUBJECTNAME_PROTOCOL.nii
% FieldMap Phase: .\COMMON\SUBJECTNAME_FM_... |
347783cb504ca861df8a8d1947444cf9f40dbf45ca42e55bacc1dae032dc0b6f | MATLAB | 12,915 | 418 | function varargout = tuning_harmonics_gui(varargin)
% BASIC_CHARACTERIZATION MATLAB code for basic_characterization.fig
% BASIC_CHARACTERIZATION, by itself, creates a new BASIC_CHARACTERIZATION or raises the existing
% singleton*.
%
% H = BASIC_CHARACTERIZATION returns the handle to a new BASIC_CHARACTER... |
86fb5987ea6ca3a74a28549a8138ed27306c3ab61aca9be4789f879b19b1ae51 | MATLAB | 12,919 | 378 | function bestThreshPerASPerParam = plot_comparison(varargin)
p = inputParser;
addOptional(p,'modelNames',[]);
addParameter(p,'mode','rel');
addParameter(p,'thresh',[]);
addParameter(p,'mean',false);
addParameter(p,'plotPath',[]);
addParameter(p,'modelValues',[]);
addParameter(p,'xLabel','Model');
addParameter(... |
df8e672c321aa2695458b1bfa8b0f4a226b81ccdf74f77928b25232c2deea54f | MATLAB | 12,921 | 380 | %BLP_rev_Fig1_FreezingCalc
clear all
for animalN = 1:7; %1-7, blpretroarch 1,2,3,4,6,7,9
FC = 0; % 0:Retrieval; 1:FC;
%Thres=6200000;
%Thres=0.05;
%load Thres
switch animalN
case 1 %blpretroarch1
if FC == 1
cd('.\Data\blpretroarch1\blpretroarch1_s01_fc_opto\video\')
folderN='blpretroarch1_s01... |
0c79935271fe3398ada48f0549b73a9b8ca135a20ba43d120f5bab7aaf250b65 | MATLAB | 12,936 | 527 | function configFileParams = ParseConfigFile(self)
contents = fileread(self.FilePath);
lines = strsplit(contents, '\n', 'CollapseDelimiters', false);
sectionTitles = ["[Project]", "[Stream]", "[Features]", "[Annotations]",...
"[Classifier]", "[TrainingOptions]", "[Evaluation]", ...
"[ConfidenceScoring]"];
sta... |
a620cbef7744b0d24e3bbb930b023697cadb60ae8ac248205c58283d6e56469e | MATLAB | 12,939 | 344 | function plot_waveforms( spikes, show, colormode,issubtree)
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% plot_waveforms - display waveforms for a collection of spikes
%
% Usage:
% plot_waveforms( spikes, show, colormode,issubtree)
%
% Description:
% This function displays a co... |
da38684d5c83a47495469bf4f51912080356feba53a081803fd817e4e49badb8 | MATLAB | 12,964 | 327 | function plot_elec_placements(iSubject, placements, customASOrder, varargin)
%PLOT_ELECTRODES Summary of this function goes here
% Basic use is 'plot_elec_placements(iSubject)', all other parameters
% are optional.
% 'placements' is optional, if omitted all placements are plot
% Examples:
% - plot_elec_... |
e22d29e7caebc558387d80296eab5922f32a51e30ab2ceb9a02afd33cb241983 | MATLAB | 12,973 | 335 | function [corrval,pval] = plotMainFig(mainFigDat,eigDat)
%% Rename everything
mainFigP = mainFigDat.mainFigP;
dataMPC = mainFigDat.dataMPC;
M = mainFigDat.M;
dataA = mainFigDat.dataA;
k2plt = mainFigP.k2plt;
ii2plt = mainFigP.ii2plt;
r = eigDat.r;
compDimP = eigDat.compDimP;
... |
6fb30068b3363d56c8d40ca5452241cd51e680ca5859aac97a04a154fce7a14b | MATLAB | 12,995 | 390 | function [stats] = plotMUAV1V6mean_ksTest( fullSessionName, aMU1eS, aMU6eS, preT, postT, xlimPl, Fs, msSmooth)
% plots mean MUA psth across channels and makes ks test to find significantly modulated
% channels
sessionNr = 564;
mapnames = {'V1_1A'; 'V1_1B'; 'V6_1A'; 'V6_1B'; 'V6_2A'; 'V6_2B'};
%% identify responsive ... |
d016c0c9f7120bc6fb9a2f76ee270e47ebe7e20ad4b7024c004de967f48c676f | MATLAB | 13,013 | 362 | %
% Author: Aaron Matthew Simmons & Steven Luck
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% ERPLAB Toolbox
% Copyright © 2007 The Regents of the University of California
% Created by Javier Lopez-Calderon and St... |
fc81e5f4cdd45733432ba54a1872d3890f225911abff0b411351d4569ca941d7 | MATLAB | 13,016 | 356 | % PURPOSE : Marking epochs containing step-like activity that is greater than a given threshold.
%
% FORMAT :
%
% >> EEG = pop_artstep(EEG, parameters);
%
% INPUTS :
%
% EEG - input dataset
%
% The available parameters are as follows:
%
% 'Twindow' - time period (in ms) to apply this ... |
7c7b00acc4f36971b3c6145c32a4d0bc0342eb00557dfa4d3cbf21a0d4f14493 | MATLAB | 13,038 | 375 | function [] = catScatterplot(X, varargin)
% function [] = categoricalscatterplot()
%
% Based on 'categoricalscatterplot.m' from Dinesh Natesan. Modified and
% extended by Patrick Jendritza 2022
%
% A replacement for the traditional box and whisker plots provided in
% MATLAB (command boxplot). The categorical sca... |
94a53be24e7c55ecc7f79266130768575205404440882c9432553d615a088cc1 | MATLAB | 13,041 | 355 | % PURPOSE : Marking epochs containing peak to peak activity, within a moving window, that is greater than a given threshold.
%
% FORMAT :
%
% >> EEG = pop_artmwppth(EEG, parameters);
%
% INPUTS :
%
% EEG - input dataset
%
% The available parameters are as follows:
%
% 'Twindow' - time... |
593d09a0264e90016709091fa57ce4ef22bdd22473bbe78f5e626c53b42378b0 | MATLAB | 13,064 | 362 | %
% Author: Aaron Matthew Simmons & Steven Luck
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% ERPLAB Toolbox
% Copyright © 2007 The Regents of the University of California
% Created by Javier Lopez-Calderon and St... |
247d287d79c8f5e3248497fcc4c463f6e5ce0b83b2bd401e1b1a545165295787 | MATLAB | 13,065 | 397 | function writeTIFstack(data, path, threshold, options)
% threshold: threshold in TIFF file size (provided as bytes) above which
% big TIFF mode will be used
% options.color
% : true or FALSE
% : If this is true, third dimension should be 3 and the data is saved as a color image.
% options.com... |
fbcef1142a22e20e3b9bb90fc04d94e33f90d638b39f149f81a0a1c9625b39a1 | MATLAB | 13,091 | 492 | function [smooth_f, df, disc_f, optimal_alpha, noise_power, acc_power] = ...
extractSmoothDerivative(noisy_f, sampling_frequency, hardThres, plotFlag)
%
%
% [smooth_f, df, disc_f] = ...
% extractSmoothDerivative (noisy_f, sampling_frequency)
%
% Goal:
% 1. Given 1d noisy (temporal) signal, estimate its ... |
f0ee3c01f0ffcb3188018db6b9b2588ea9cc374dc095565e56d40b051b68764c | MATLAB | 13,097 | 293 | %% Characterize performance in a single task
% The question answered by this function is, which recorded variable best
% explains task performance (i.e., the number of targets hit by the
% participant)?
% Copyright (C) 2022 Richard Hugh Moulton
%
% This program is free software: you can redistribute it and/or mod... |
098e8fe7e9951730e49a36545c57c042545da1b0b5ae0eef457a0969d1abc131 | MATLAB | 13,122 | 521 | function DATA = SaveAMDepthDataEphys_v2(path, subject, session, block, channel, clu, bData)
%
% pp_plot_rasters(subject, session, channel, clu)
% Plots a raster and psth for each unique stimulus. Clu is the label
% given by UMS (not an index), found in Spikes.sorted.labels.
%
% KP, 2016-04; last updated 04-07... |
72df61f5219c1f8363f4e98fa0a3c39badb02697d8ff90528c96a26f198430c0 | MATLAB | 13,149 | 341 | function [] = neoaxescenter(ax)
%AXESCENTER locates axes in the center instead of at the edges.
% AXESCENTER(AX) puts axes in the center of axes AX. If AX is not
% supplied, the current axes is assumed. Many of the standard properties
% manipulated through the command line will also work when the axes are in
% t... |
8cea881d861cfea2867268d09a168964f5e3d45a6823e81de8821cf38b296441 | MATLAB | 13,185 | 326 | function varargout = my_splineCSD(varargin)
% MY_SPLINECSD M-file for my_splineCSD.fig
% MY_SPLINECSD, by itself, creates a new MY_SPLINECSD or raises the existing
% singleton*.
%
% H = MY_SPLINECSD returns the handle to a new MY_SPLINECSD or the
% handle to
% the existing singleton*.
%... |
fe698d05da965240010036317acc4064d492e5536524709095625a5c4f3c3d6c | MATLAB | 13,191 | 325 | %%This script is to save history for either current EEGset or current session.
%Author: Guanghui ZHANG--zhang.guanghui@foxmail.com
%Center for Mind and Brain
%University of California, Davis
%Davis, CA, USA
%Oct. 2023
% ERPLAB Studio
function varargout = f_EEG_history_GUI(varargin)
global observe_EEGDAT;
addliste... |
1bbcb5ba3b399e059e243ce27f3f2cf98c68a8134589e609dcb6a5e203cb7ca2 | MATLAB | 13,212 | 370 | % PURPOSE : Calculates (normalized) cross covariance between each epoch, at the specified channel(s), with a
% simulated blink-like waveform
%
% FORMAT :
%
% >> EEG = pop_artblink(EEG, parameters);
%
% INPUTS :
%
% EEG - input dataset
%
% The available parameters are as follow... |
17ae11b9899a8542b082cf13b494c1a32a4b19774a3a9ddf79fcc75f02440801 | MATLAB | 13,220 | 365 | % PURPOSE : Marking epochs containing flatline activity that persists for a given period of time.
%
% FORMAT :
%
% >> EEG = pop_artflatline(EEG, parameters);
%
% INPUTS :
%
% EEG - input dataset
%
% The available parameters are as follows:
%
% 'Twindow' - time period (in ms) to apply ... |
65af496c77d584209869b42700800497560e1fdec400d107ef3ee55b458686e0 | MATLAB | 13,221 | 406 | function NextTrialID = TrialFcn_2AFC_SanesLab(TRIALS)
% NextTrialID = TrialFcn_PureToneDetection_MasterHelper(TRIALS)
%
% This is a custom epsych function for the Sanes Lab for use with
% appetitive Two-Alternative Forced Choice tasks.
%
% NextTrialID is the index of a row in TRIALS.trials. This row contains all
% of t... |
80f67e2a53a6ea6e4fe205c440b176b05dc063c668812a72d487d2ea4781b25c | MATLAB | 13,249 | 464 | function varargout = DRAFT_Headtracker_Behavior(varargin)
% DRAFT_HEADTRACKER_BEHAVIOR MATLAB code for DRAFT_Headtracker_Behavior.fig
% DRAFT_HEADTRACKER_BEHAVIOR, by itself, creates a new DRAFT_HEADTRACKER_BEHAVIOR or raises the existing
% singleton*.
%
% H = DRAFT_HEADTRACKER_BEHAVIOR returns the handl... |
5906546f59d9ced6ddd1f15c8d313b60525139baca6ed36a80016eeeffc1308f | MATLAB | 13,251 | 456 | %%this function is used to call back the parameters for plotting ERP wave
% *** This function is part of EStudio Toolbox ***
% Author: Guanghui Zhang & Steven Luck
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% Oct 2023
function OutputViewerparerp = f_preparms_erptab(ERP,matlabfig,Histo... |
38e44cef7f7b0eaa78e68a3adceb97bfe1c6457fbd41d61a208c72391e442a80 | MATLAB | 13,252 | 341 | %%dowload from https://www.mathworks.com/matlabcentral/fileexchange/46755-str2html?s_tid=srchtitle
% str2html Convert input str to html format for use in uicontrols/menus
%
% uimenus and some uicontrols accept html format strings, e.g. pushbutton,
% listbox, popupmenu (this list is controlled by Math... |
4a8d656065863c67582fd5b4056034adb14222df93193b029bd42fcd71996f57 | MATLAB | 13,260 | 373 | % PURPOSE : Filters EEG data
%
% FORMAT :
%
% EEG = pop_basicfilter( EEG, chanArray, parameters );
%
% INPUTS :
%
% EEG - input dataset
% chanArray - channel index(es) where the filter will be applied.
%
% The available parameters are as follows:
%
% 'Filter' - 'bandpass'- Band pass.
% ... |
67142e1ab7d00f429fcb70aa34008e865a67310f2bea5c23676a0f400c456884 | MATLAB | 13,296 | 297 | function fibers = project_fibers_triangulation(fibers, cross_z, idCross, ...
idCross_prev, section, section_prev, BranchIndex, fibp, minFiberDist)
% PROJECT_FIBERS Porject the fiber center distribution to the
% next layer in every case
%
% [fibers] = project_fibers(fibers, cross_z, idCross, ...
% idCr... |
f8e382933f286929be7db7f35e24a187e94d4a0bea5fccb769aa3cb72ae3901a | MATLAB | 13,321 | 469 | function varargout = DRAFT_Modulation_Behavior(varargin)
% DRAFT_MODULATION_BEHAVIOR MATLAB code for DRAFT_Modulation_Behavior.fig
% DRAFT_MODULATION_BEHAVIOR, by itself, creates a new DRAFT_MODULATION_BEHAVIOR or raises the existing
% singleton*.
%
% H = DRAFT_MODULATION_BEHAVIOR returns the handle to a... |
61448fa4773d2788de4e6d2dd1e0b55cae12aa86a4bddb08c7a86810d44ec516 | MATLAB | 13,330 | 86 | function [trainedModel, validationRMSE, validationPredictions] = trainRegressionModel(trainingData)
% [trainedModel, validationRMSE] = trainRegressionModel(trainingData)
% Returns a trained regression model and its RMSE. This code recreates the
% model trained in Regression Learner app. Use the generated code to
% auto... |
81b647203757324ec9b0e70de963fdcbca6ddceb908d3c17e051a7d8c9867df7 | MATLAB | 13,346 | 413 | clear;
%% Fig2a,anes,histogram of wave direction
cd('/media/user/Elements/NC Data/2017 APR 19 publish');
load('Exp001_Fluo_002_001_sequenceDataFiltered_bandpass0.5_12_box_gp_done.mat','rsDataT','cortexMask','vfsT');
%left hemisphere
thetaLeft=[];
for i=1:size(rsDataT,1)
for j=1:27
if(cortexMask(i,j)==1)
... |
6097ac13da06384e94767d10caebc68def96b151cd708d64097feabc4ba6054e | MATLAB | 13,356 | 466 | function varargout = DRAFT_2_Headtracker_Behavior(varargin)
% DRAFT_2_HEADTRACKER_BEHAVIOR MATLAB code for DRAFT_2_Headtracker_Behavior.fig
% DRAFT_2_HEADTRACKER_BEHAVIOR, by itself, creates a new DRAFT_2_HEADTRACKER_BEHAVIOR or raises the existing
% singleton*.
%
% H = DRAFT_2_HEADTRACKER_BEHAVIOR retur... |
e1d6f12e27dc536491656b96aec917e61ef3e82c29419644ec841aa71e1dd1d7 | MATLAB | 13,400 | 281 |
%Author: Guanghui ZHANG--zhang.guanghui@foxmail.com
%Center for Mind and Brain
%University of California, Davis
%Davis, CA, USA
%Feb. 2022 && Nov. 2023
function varargout = f_erp_dataquality_SME_GUI(varargin)
global observe_ERPDAT;
addlistener(observe_ERPDAT,'Count_currentERP_change',@Count_currentERPChanged);
... |
1da8607bf718e1b48f964fe7f28563cc6350cee41b5dfc052f7d39ca6aee0468 | MATLAB | 13,414 | 304 | % PURPOSE: ERPLAB Studio "Reset" dialog. Collects which tabs to restore to default
% parameters and which datasets to clear, or performs a full factory reset.
%
% FORMAT:
%
% app = estudio_reset_paras(resetparas, enableflags)
%
% resetparas - 1x6 logical, initial checkbox state:
% [eegParams eeg... |
87c3ef342ae54710e921bda679126606f5bca8650f3df07e88cc0a520e588835 | MATLAB | 13,428 | 442 | function varargout = Ventriloquist_Mk2(varargin)
% Ventriloquist_Mk2 MATLAB code for Ventriloquist_Mk2.fig
% Ventriloquist_Mk2, by itself, creates a new Ventriloquist_Mk2 or raises the existing
% singleton*.
%
% H = Ventriloquist_Mk2 returns the handle to a new Ventriloquist_Mk2 or the handle to
% t... |
f2d8efd589a4d480fbbc077cd75496e08325b954533ec43349b9fc3b2da4b2f9 | MATLAB | 13,440 | 389 | % eeg_topoplot() - plot scalp map
%
% eeg_topoplot( vals, chanlocs, 'key', 'val');
%
% Input:
% vals - values, one per channel
% chanlocs - channel structure, same size as vals
%
% Optional inputs:
% 'colormap' - colormap. Possible colormaps are 'blueredyellow', ...
% 'yellowredblue', 'bluere... |
972819008af74f9903293ad11d6c982563ebbcc331945309378a0dffe7d4967f | MATLAB | 13,448 | 366 | %
% Author: Javier Lopez-Calderon & Steven Luck
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% ERPLAB Toolbox
% Copyright � 2007 The Regents of the University of California
% Created by Javier Lopez-Calderon and St... |
2ff7d53387ea7ee22dda75a6388688f3da6a346890b42553ae2097abef2df687 | MATLAB | 13,456 | 250 | clear;clc;
filePath=['D:\Paper_recalibration']; %%% Create a file path
cd(filePath);
%%% download data file : "Data_session.rar" and unzip to above file path
%%% download neuron list file : "Neuron_list.rar" and unzip to above file path
load MSTd_PreData.mat; load MSTd_PostData.mat;
filePath=['D:\Paper_recali... |
6350509484a12ebfdf3c020ed6c0df7c47d3205f9552fa9e56540814f9506839 | MATLAB | 13,480 | 339 | function [outputEEG, commandHistory] = pop_erplabDeleteTimeSegments( EEG, varargin )
% POP_ERPLABDELETETIMESEGMENTS Deletes data segments between if the length of time between any 2 consecutive event codes (string or number)
% is greater than a user-specified threshold (msec)
%
% FORMAT:
%
% EEG = pop_erplabDeleteTim... |
0990893bb8a4b342fc6f6e0ff21fb8b9a20e642bdc577f5a5ac64f941365c20f | MATLAB | 13,492 | 416 | clear;
%% Fig2a,anes,histogram of wave direction
cd('/media/user/Elements/NC Data/2017 APR 19 publish');
load('Exp001_Fluo_002_001_sequenceDataFiltered_bandpass0.5_12_box_gp_done.mat','rsDataT','cortexMask','vfsT');
%left hemisphere
thetaLeft=[];
for i=1:size(rsDataT,1)
for j=1:27
if(cortexMask(i,j)==1)
... |
b2cfbe28c43e25aab8153e15cd7184f7782169e5bf26a4355652e282308b2c20 | MATLAB | 13,505 | 363 | function [bestLocalProjections, bestSigmaValues, bestDiffSigmaValues, localDistances, bestNeighborCounts, distances] = findBestAxes(dynamicsStream, dynamicsDiff, trialStream, calcIndex, meanDistanceMatrix, nearestNeighbors, useLocalDimensions, verbose)
%meanDistanceMatrix = pdist2(dynamicsStream, dynamicsStream);
... |
2740518bf453636343d3f6d63f82c117f1a26839b336e48781bebef9dd8b45a5 | MATLAB | 13,527 | 502 | %% Triple Correlation Script - Figure 3
clearvars
clc;
close all;
C=150; % columns
R=150; % rows
%define the frequency
f = 0.12;
% deterministic component
t=0:C-1;
s=1*sin(2*pi*f*t);
S=zeros(R,C);
for ch=1:R
ph=0;
S(ch,:)=1*(((sin(2*pi*f*t+ph)+1)/2));
end
%addition of noise
y=rand(R,C);
x=1*y+1*S; ... |
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