sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
f8a13e47e36a58f858080810d02d9b3a2297f1d67dd273a25333bcda47a5f923 | MATLAB | 9,769 | 253 | %{
----------------------------------------------------------------------------
Analyzing behavioral data
At least for the correct rate
----------------------------------------------------------------------------
%}
function Figure1f_Dual_behave_analysis_block1_220818_short_long
analysis_folder = {
'G:\Is... |
aeb9719bcc89b449007b9dc11f5969bf1fc98f43282f5d9518e27b2bf30315e1 | MATLAB | 9,784 | 257 | %% CM_inh_preprocessing
% batch processing
% cd 'F:\Users\Yiting\YitingData\YT086\Intan_YT086'
cd 'F:\YT093\Intan_YT093'
folderNames = dir('*2*');
% % YT053
% inhSite_all = {'sham' 'sham' 'AMM' 'AMM'... % 181115, 16, 18, 19
% 'AMM' 'sham' 'AMM' 'AMM'... % 181120, 21, 22, 23
% 'Prt'... |
d4221a14be450024cd692bada7dd034c5683e1797bb606d22a1418f6097346dd | MATLAB | 9,784 | 245 | function freezeColors(varargin)
% freezeColors Lock colors of plot, enabling multiple colormaps per figure. (v2.3)
%
% Problem: There is only one colormap per figure. This function provides
% an easy solution when plots using different colomaps are desired
% in the same figure.
%
% freezeColors freeze... |
d2e3a3bfccf9fd902a573c611709cd3f63c252760ac4441c9ab61484c2dbe2dc | MATLAB | 9,799 | 321 | % The basic application of the 'reslice_nii.m' program is to perform
% any 3D affine transform defined by a NIfTI format image.
%
% In addition, the 'reslice_nii.m' program can also be applied to
% generate an isotropic image from either a NIfTI format image or
% an ANALYZE format image.
%
% The resliced NIfTI fi... |
0e89a4e5a6db5485440e17204aa2293f714c7dee33c4ec9cc0f9b5e53c677141 | MATLAB | 9,820 | 282 | function LFPanalysis(SpikeStartTime,SpikeStopTime,StartTime,FinishTime,TurnMarkerTime,OneTurnTime,Timestamp,Samples,RPegTouchAll,ts_spike,event_name,event_ts)
global fname dpath DrName SpikeStartTime SpikeStopTime StartTime FinishTime TurnMarkerTime OneTurnTime Timestamp Samples RPegTouchAll ts_spike event_name event_... |
0ae8e8d71f6831a640275063c4fcffc60f95567cd4fc7bb62172c6ff113bfee6 | MATLAB | 9,827 | 225 | function senpai_strahlerord(swc_mat, neuron, path_out, filename)
% senpai_strahlerord:
% produces a strahler ordering and a series of related statistics.
% the output is stored in an output .mat file
%
% Execute the function in the command window:
% Syntax:
%
% senpai_strahlerord(swc_mat, path_out... |
665bb23f98242af88fccf12a59d33463f8608bb1f4f9e5778330f74a1e606b54 | MATLAB | 9,834 | 324 |
function []=GUI1(fileName, fileType)
f = figure ('menu','none',...
'Position', [950 450 650 520],...
'visible','off');
set(f,'name','Peak Detection Parameters','numbertitle','off')
%% spacing of objects
xText1Pos=20;
yText1Pos=470;
xText1Siz=95;
yText1Siz=40;
spaceText1=60;
x2Pos=220;
y2Pos=465;
y2space... |
a87787008cdda4f4932e0faa1e890d2c1fc94165eee7f01e9ca2840b2cdfa49a | MATLAB | 9,834 | 124 | clear
cd D:\Canada_2020\CLSA
clsa_base=readtable('D:\Canada_2020\CLSA\data\clsa_dru_bl_cog1.csv'); clsa_base=sortrows(clsa_base, 2);
clsa_snps=readtable('D:\Canada_2020\CLSA\data\CLSA_dosage.csv');clsa_snps=sortrows(clsa_snps, 2);
clsa_snps(:,'ADM_GWAS3') = [];clsa_snps(30098:end,:) = [];
clsa_base.CCC_HBP_COM(clsa_ba... |
1454303623a60a37c329ffa6760d93d7e417a4de26bb8ecc76dc2d07d3cfd74c | MATLAB | 9,836 | 251 |
%{
----------------------------------------------------------------------------
Determine the time window for task relevant neurons
%Start of task
%Sound on
%Sound off
%Before choice
%After choice (0sec)
%After choice (1sec)
%After choice (2sec)
%p = 0.001
%Each epoch, predict the prior, sensory and choice... |
31616aa410737243395c65fa2395b3fe05ff0eed52e654415a233c8cdbd85850 | MATLAB | 9,844 | 277 | function eventwindowPhotomPlot_LoneFigV2(x,y,eb,setupParam,TrialParam,allTrials,ProcessedEventWindowData,loneFigure)
allTrialsID = allTrials.ID;
if setupParam.CompareGroups == 1
GroupParam = TrialParam.GroupParam;
groupnames1 = fieldnames(allTrialsID);
groupidx = zeros(1,numel(groupnames1));
for i... |
73533d2b008c9369fd6a5bf88b98c640458ecb80c5430d4b20b9ade3d79bcc04 | MATLAB | 9,851 | 217 | %%*************************************************************************************************************
% Date: 19-09-2022 Programmed by: d. Bolger
% Script to take load in time-frequency data from the *timefreq.mat files
% and to average TF data over defined frequency bands and time-windows.
% T... |
a2639bb70605e7757196e4cbe1ec00b1b8f40c221a5231beec841dd9f087b05d | MATLAB | 9,878 | 272 |
%{
----------------------------------------------------------------------------
First_take number of frames in each tif files
Analyzing imaging data simply
At least for the correct rate
----------------------------------------------------------------------------
%}
function Task_kaiseki_tokyo1_20220221_make_av... |
643576b9d475c5ec77eff6747b8ac08d3c16390cc574c499a593854ae1bd6055 | MATLAB | 9,910 | 340 | function hsvdRAW(filename,magnet,hsvdflag,npeak,ncol)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% hsvdRAW.m
% Remove selected peaks using filtered HSVD algorithm (from mrui)
% Use .RAW file ONLY (for Vnmr fid use peakremoval.m)
% Run under Sun Solaris
%
% hsvdRAW(filename,magnet,hs... |
8998016c5cbf52e2c0f6b97f0f0cc3f89209412e9f47c9aa8944dd1e22e11f97 | MATLAB | 9,921 | 286 | function [GaussParams, varargout] = qtParamsGausFit(ecg, fs, varargin)
% Estimate the Q-T interval and some other Q-T parameters by fitting
% Gaussian function models.
%
% Syntax:
% GaussParams = qtParamsGausFit(ecg, fs)
% GaussParams = qtParamsGausFit(ecg, fs, rpeaks)
% GaussParams = qtParamsGausFit(ecg, fs, r... |
55991218c1764b2926356577912e8ee94e3a6671523082e41649c3202e9f5261 | MATLAB | 9,922 | 279 | function pretouch20190608
%¼àRFXpCNª Á½¼OÌ^b`©çXpCNÜÅÌÔðp¢½\ª
global ACresult ACresultW CCresultDrinkOn SpikeArray TurnMarkerTime RpegTouchallWon LpegTouchallWon...
RpNum LpNum CCresultSpike locsP1time locsP2time locsP1time2 locsP2time2 pksA1 pksA2 CCresultRtouchWon CCresul... |
b4cd3d25c55365d5c411a99ca35fc718c3c49775d1f5c443c9eff87f1c7fd62d | MATLAB | 9,937 | 211 | function spike_res = transduction_analysis (app, update)
% if nargin == 1
% update = false;
% end
% MIN_CLUSTER=10;
% % MSNA = app.data(app.settings.channel_idx.msna).data;
% % data = app.data(app.settings.channel_idx.msna).data(app.settings.interval(1,1)/app.data(app.settings.channel_idx.msna).ts(1):app.settings.... |
b8ddd79f273f8b64b60d412561873a852ad1c0c89731c1b369e804c02dc76cb6 | MATLAB | 9,937 | 198 | function FRA_analysis_combine_awake(complete_FRA_files,save_path_input,Rsquare_threshold)
% Authors: Simon Wadle & Tatjana Schmitt, 2019-2023
% this function extracts important parameter from FRA data
% gets called by 'pipeline_complete_SPLanalysis_awake_FMR1.m'
for ii = 1:size(complete_FRA_files, 1)
path_... |
f0561d8e8ff5b2a2cce693daa21ece0ee1cbf3a0b1ebb1e3e5ce080c108ae46b | MATLAB | 9,974 | 197 | function [feature_vec, feature_info] = ecg_angle_features(data, fs, ...
low_pass_fre, high_pass_fre, ...
median_window_coff, mean_window_coff, lead_list, ...
... |
0525a77973ef879a4064f169e55ea35f133df19ec24bd1d198e4389d58c9d703 | MATLAB | 9,983 | 276 | function [newD, C, lat, explained, params] = reducedims_EH(D,alg, dims, handles)
% REDUCEDIMS a dimensionality reduction tool
% REDUCEDIMS(D,DIMS,ALG,DATATYPE), where D is the high dimensional data to be
% reduced, DIMS is the number of dimensions to reduce to, ALG is an
% integer representing the reduction algor... |
46eb5c91bd2cbfc1de7f9d7c42165e37efc777f8246d4e6eb13c4a0c43002fd2 | MATLAB | 9,991 | 254 | function AllLFPauto20180420
%WheelAnalyzer24chSpikeÅðÍðs¢AʪÉcÁÄ¢éóÔÅs¤
%MATLABtH_ÉNlx2MatCSC.mexw32ÆNlx2MatCSC.mexw64ðüêĨB½ÔñÇ¿ç©ÐûÅæ¢B
%timestampsÍ270336¸ÂÁB270msÆvíêéBtimestampsÌ512ÂÌTvB
%270336/512=528. TvOÍ0.528ms²... |
98b8fad572f92add578383d2c630ad52b1ecdb74968139624aecc9038f186988 | MATLAB | 10,021 | 277 | function [newD, C, lat, explained, params] = reducedims_EH(D,alg, dims, handles)
% REDUCEDIMS a dimensionality reduction tool
% REDUCEDIMS(D,DIMS,ALG,DATATYPE), where D is the high dimensional data to be
% reduced, DIMS is the number of dimensions to reduce to, ALG is an
% integer representing the reduction algor... |
e000126b08819a5380c1dec7e7648b35244643fba911fe13a67fa61e4497e23c | MATLAB | 10,025 | 147 | clear;
close all;
clc;
addpath 'G:\Sameni\Documents\Papers\Journal 40 (Spline ECG Filtering)\CODES'
randn('seed', 0);
rand('seed', 0);
% % % dbstop if warning
type = {'Normal', 'Arrhythmia', 'PTB'};
for ttp = 1 : length(type),
switch(type{ttp})
case 'Normal'
pth = 'J:\ECGData\Normal';
... |
501b7249bdff78603cf03a4f504534427b450da870d349b05799eb527e68578e | MATLAB | 10,036 | 100 | % load data
% % % R1 = importdata('E:\Sameni\Projects\Seizure\SourceCodes\Probabilistic\SourcesWithResultsBackup\testFreqDomainEnergyIncreaseRate01.txt');
% % % R2 = importdata('E:\Sameni\Projects\Seizure\SourceCodes\Probabilistic\SourcesWithResultsBackup\testICASubspaceAngles01.txt');
% % % R3 = importdata('E:\Sameni\... |
5f509b506b58b60472bc55bc6cb54bce12d5e388aad24c9aac6b4599085c44f6 | MATLAB | 10,039 | 305 | function [max_resp, mean_resp] =viewphotometry_avg_PV(cellids, root, resdir, varargin)
%VIEWPHOTOMETRY_AVG_PV Average PSTH of PV fiber photometry data.
% VIEWPHOTOMETRY_AVG_PV(CELLIDS,ROOT, RESDIR, VARARGIN) creates an average PSTH
% of fiber photometry data recorded from sessions listed in CELLIDS and locate... |
8ab33f67a1388a0b3257454ad99eba18de042f805197203ae63a04c5931a52eb | MATLAB | 10,039 | 195 | %% function C_SS_mean = AveSpatKer_Rec(C_SS_Pixel_Us,N_HC,NPixX,NPixY)
% Input: C_SS_Pixel_Us: A Pixel connectivity matrix (from network).
% Pre(col)*Post(row)
% N_HC,NPixX,NPixY: # of hypercolumns, # of pixels per HC
% Output: C_SS_mean: Averaged spatial kernal of firing rats. Same size as
% C_SS_Pixel_Us
% Zh... |
91e819e59d604a112f22ec790872c0a140662696955b41573cc7fb09a464e47d | MATLAB | 10,046 | 208 | function frequency_response_area(SPL_file,fit_flag,overwrite)
% Authors: Simon Wadle & Tatjana Schmitt, 2019-2023
% this function constructs FRAs and fits the mean over SPLs
% gets called by 'pipeline_complete_SPLanalysis_awake_FMR1.m'
%% load file
load(SPL_file, 'export_struct');
%% extract data
temp_fiel... |
5256610738cb443d9ff0fd3291398429d39ad193b8e6125d5089adfd889b74ea | MATLAB | 10,048 | 280 | % epochs the time-frequency data, and corrects each trial by the session
% average.
clear
clc
close all
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% Parameters
OnlyClosestStimuli = false; % only use closest trials (legacy)
OnlyEyesOpen = false; % only used eyes-open trials. Need to... |
1c16e7caf7253b36916c3631125161153b5b9d2153940a3a5ffb079abc26dc7c | MATLAB | 10,050 | 302 | function [A,S]=jade(X,m)
% Source separation of complex signals with JADE.
% Jade performs `Source Separation' in the following sense:
% X is an n x T data matrix assumed modelled as X = A S + N where
%
% o A is an unknown n x m matrix with full rank.
% o S is a m x T data matrix (source signals) with the properties... |
6b8b04ca443e08bf8012cff79fe3acdb8d0d66f2bca06eded75e1b6b5b1aa6e8 | MATLAB | 10,063 | 234 | function save_spec_res(app)
%UNTITLED save spectral analysis results
% Detailed explanation goes here
cols = {[0 0.4470 0.7410],[0.8500 0.3250 0.0980];...
[0.9290 0.6940 0.1250],[0.4940 0.1840 0.5560];...
[0.4660 0.6740 0.1880],[0.3010 0.7450 0.9330]};
[int_idxs,~] = listdlg('PromptString',{'Please ... |
cde07311bff9097bed37c05362ea7451ab932162c27c1faf3e403320df4133a3 | MATLAB | 10,063 | 237 | function [WF] = getWFprop(WF, varargin)
%Charactirization of waveform shape and temporal properties
%
% Description: This function will calculate waveform features for units in
% a recording, using waveforms extracted into T-Lab data structure
%
% [WFprop] = getWFprop(WF, varargin)
%
% INPUT
% WF - struct... |
e86fc527197c086964a93de88b17079ab569495b63b822a576195f03a95a4ff1 | MATLAB | 10,073 | 189 | %% mean-field stuff. We use parameters andto estimate firing rates
%% NOTE! mean Vs are now autonomus from single cell simulations
% Input: C_EE,C_EI,C_IE,C_II connectivity matrices
% S_EE,S_EI,S_IE,S_II synaptic strength
% p_EEFail Synaptic failure prob
% lambda_E lambda_I LGN input
%... |
d8f55b43c213f80380a1490cd411b35123b08236df0f0ff6d8b65ab284c26173 | MATLAB | 10,075 | 209 | function Repeat_heatmap_analysis
%%% gt3Ælt2ÌdevideÌq[g}bvÌðÍ
%%% devideÌq[g}bvÅÌmodulationÆcomplex patternÅÌmodulationð¼ÚvZµ½àÌðärµÄ¢éB
path='C:\Users\C238\Desktop\touchcellLtRt_Hirokane';
R_interval_mod=[];
L_interval_mod=[];
R_interval_mod_heat=[];
L_interval_mod... |
5c24b7fdf739f413586c2d09d1ef45d7fb787dd4745420b6af62ca2c71b466df | MATLAB | 10,079 | 251 | function Negative_W3_W2_or_All_pattern_1_20200309
path=['C:\Users\C238\Desktop\touchcellLtRt_terashita'];
cd(path);
LS=ls;
NegativeLtouchUnit=[];
NegativeRtouchUnit=[];
LtNWPointArray=zeros(1,4);
LtNWFireArray=zeros(1,4);
RtNWPointArray=zeros(1,4);
RtNWFireArray=zeros(1,4);
W23NegativeLtouchUnit=[];
W2... |
058a85bcef31918aaf8eb2a1a38bcd22d5e1cf4d38b00a5ada8cb307dbeed2d0 | MATLAB | 10,082 | 284 | function [Xhat,Phat,X,PSmoothed,a] = EKSmoother(Y,X0,P0,Q,R0,Wmean,Vmean,Inits,VarWinlen1,tau,gamma,VarWinlen2,varargin)
%
% The Extended Kalman Filter (EKF) and Extended Kalman Smoother (EKS) for
% noisy ECG observations.
%
% [Xekf,Pekf,Xeks,Peks,a] = EKSmoother(Y,X0,P0,Q,R,Wmean,Vmean,Inits,VarWinlen1,tau,gamma,... |
c1e7e07c5cf2447db5a1e245067f455f4b33c7bdf756bfcdb4a695d68de1626a | MATLAB | 10,085 | 198 | function readCSC
%MATLABtH_ÉNlx2MatCSC.mexw32ÆNlx2MatCSC.mexw64ðüêĨB½ÔñÇ¿ç©ÐûÅæ¢B
%timestampsÍ270336¸ÂÁB270msÆvíêéBtimestampsÌ512ÂÌTvB
%270336/512=528. TvOÍ0.528ms²ÆBfs=10^6/528
% pathnameCSC = 'C:\Users\kit\Desktop\2010-1-17_20-46-17\CSC4.Ncs';... |
d984113c3cd9aea819de3254b2d8792224eac6196f74d86f7f0a26fa5059a0f1 | MATLAB | 10,086 | 238 | function [hemi, hemi2, d, d2, sz, ci] = loadBrainData(f, underlayVertices, ln, rn, varargin)
% Loads Brain Data from Various File Formats
%
% [hemi, hemi2, d, d2, sz, ci] = loadBrainData(f, underlayVertices, ln, rn, app)
%
% **Description**
% ----------------
% The `loadBrainData` function loads brain imaging data ... |
9cc4e2a13a8a1183f0077bd3a22ed30c28cf3c56ef831657d5207b093db6d223 | MATLAB | 10,094 | 311 | %% basic tracking of mouse position
% Example code for unsupervised whisker tracking in freely behaving mice/rats
% This script extracts rough position of the mouse. This position is then
% used for simple whisker tracking.
%
% 2014 Jakob Voigts (jvoigts@mit.edu)
vid = VideoReader(fullfile('example_data/example_video... |
d172cb82de8e6de4e9cba09205b3b159a0c0f9821bab33b19c9b7bc064c1821d | MATLAB | 10,097 | 282 | function [hCfg, res] = v3(filename)
%V3 Import an old-style session (_jrc.mat) to the new style
[hCfg, res] = deal([]);
filename_ = jrclust.utils.absPath(filename);
if isempty(filename_)
error('Could not find ''%s''', filename);
end
try
S0 = load(filename_, '-mat');
catch M... |
128da31edd08c776cc8cf33a1abad52ca6136d092448785dbfb5a72a8763d414 | MATLAB | 10,101 | 519 | function [radX SpikeTimeX] = computeRadFiring(t_ECG,t_SPIKES,ind_SPIKES)
% t_ECG=t_events_plus,
% t_SPIKES,
% ind_SPIKES=1:length(t_SPIKES);
t_CORTOpeak=t_SPIKES(ind_SPIKES)';%ECG_RESULTS.t_events; %BELT_Rpeak;
t_LUNGOpeak=t_ECG;%t_maxima(1:end);
N_ipol=50; %interpolation
%
% for i=1:length(t_CORTOpeak)%floor(len... |
e3169a558125564b7d19af9a0a079a8fa812e94ff21c4e7ad0fc41c0a70ac2d1 | MATLAB | 10,119 | 267 | function varargout = Randomizer_Tanova_Options(varargin)
% RANDOMIZER_TANOVA_OPTIONS M-file for Randomizer_Tanova_Options.fig
% RANDOMIZER_TANOVA_OPTIONS, by itself, creates a new RANDOMIZER_TANOVA_OPTIONS or raises the existing
% singleton*.
%
% H = RANDOMIZER_TANOVA_OPTIONS returns the handle to a new ... |
f5375a660cc0e8adfdda74c7c0e1b353679cf3e15e3c5889945a2c8d439ee380 | MATLAB | 10,119 | 271 | function [diff,CI,p,alphav,h]=rst_gp_multicompare(gp1,gp2,varargin)
% Test for differences between groups with an adjustment for multiple
% comparisons - This is not the same as post-hoc testing in ANOVA in which
% a significant interaction was found in a 1st place. The control is across
% tested difference only. Th... |
c44c907739d244039c9646350b37ef116f9e8d49e0cd6267b1fb672541fd92b5 | MATLAB | 10,130 | 208 | function [Vertices,Segments] = Segment_Skeleton(Im1_NoiseReduction,Im1_branchpoints,Im1_endpoints,Im_Skel_Rad)
Messages = 0;
[Ly,Lx] = size(Im1_branchpoints);
% BP_Min_Dis = 4;
if(Messages)
assignin('base','Im1_NoiseReduction',Im1_NoiseReduction);
assignin('base','Im1_branchpoints',Im1_branchpoints);
as... |
1df385a230b618dee73617cec757d6359ca9f1a36905f00ff8f10a11dbf4a277 | MATLAB | 10,147 | 299 | function [GaussParams, varargout]=qtParamsGausFit_cl(ecg, fs, varargin)
% 'corrected levels' version.
% estimate the Q-T interval and some other Q-T parameters by fitting
% Gaussian function models.
%
% Syntax:
% GaussParams=qtParamsGausFit(ecg, fs)
% GaussParams=qtParamsGausFit(ecg, fs, rpeaks)
% GaussParams... |
5e2f4ce3572f52e75b54293ce22e5b1c593eb60f8d11650951625311cd8b8a5f | MATLAB | 10,161 | 242 | %% Unit Plot
% Plot nondrifting unit (at least 4 blocks and the last block is longer than 30 trials)
MouseName = 'EF0114';
MainDir = 'F:\';
seDir = [MainDir, MouseName, '\MSessionExplorer_', MouseName];
seFilePaths = MBrowse.Files(seDir);
for j = 1: length(seFilePaths)
load(seFilePaths{j})
%... |
0ec7e642e4404e00be7bc7db73e971465d9353e2a50ad34ab6c67e29b646630a | MATLAB | 10,162 | 189 | function update_burst_axis(app, keep_xl)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
cla(app.ax_msna_int), cla(app.ax_burst_res)
cla(app.ax_burst_interval_his), cla(app.ax_burst_duration_his)
cla(app.ax_burst_amplitude_his), cla(app.ax_burst_integral_his)
cla(app.ax_burst_res), cla... |
9b0ae20eadda572bee2a4892c2ee4584037e11a866b95a1a0007c78fcc757358 | MATLAB | 10,175 | 245 | %
% Test program for generating synthetic maternal and twin fetal ECG
% mixtures with realistic ECG noises, and extracting independent components
% using the JADE ICA algorithm.
% The results may be compared in different SNRs for the maternal ECG and
% the fetuses. In this example, since there are eight recording ... |
2979bbf541fca42e369376b6f3ec513c52d2d9583a27ac8de250fceca26412a8 | MATLAB | 10,192 | 132 | %This code calculates the evoked calcium event rates and fluorescence for
%an arbitrary set of behavioral event timestamps. The responses are
%classified as activated or inhibited based versus a time shuffled null
%distribution of responses to the same event. Firing rate responses can be
%classified (Jimenez et al.... |
faadf6905650818c0d5a338cea49184cda0d50e833703d0409bed4984669b343 | MATLAB | 10,205 | 230 | classdef FileRunner
% Summary of this class goes here
% Detailed explanation goes here
properties (SetAccess = private)
files; % listing of the files that are read
last_file; % the last file starts from 0
file_read_error; % reading error starts from 1
type; % ty... |
4eb8adc396e7a2743a2cb812b3eac893411ae21279108be6fbfa16d3d6eef152 | MATLAB | 10,206 | 257 |
%{
----------------------------------------------------------------------------
norm_Task_kaiseki_tokyo1_20220316_sound_choice_separate2_detail
----------------------------------------------------------------------------
%}
function norm_Task_kaiseki_tokyo1_20220316_sound_presound_ishizu(folders)
analysis... |
9e88d01974fdad53cd28e6f68f6c44638129cb872f839b5b409c9dcbd384ab54 | MATLAB | 10,226 | 220 | % Function to Select frames per Condition Manually
% Extract Descriptive RasterFeatures and seve the, @
% ...\FinderSpiker\Raster Features
% Run After Finder_Spiker_Calcium.m and Detected & Undetected Scripts
% Load Saved Data in the EXPERIMENT_DATE.mat Files
% It runs until selection is OK (according to the user)
% In... |
f384531f32bdfb65c764064096f0ec00ac4c872bb8e07f1daa2e3a8b27b9296d | MATLAB | 10,227 | 219 | %% mean-field stuff. We use parameters andto estimate firing rates
%% NOTE! mean Vs are now autonomus from single cell simulations
% Input: C_EE,C_EI,C_IE,C_II connectivity matrices
% S_EE,S_EI,S_IE,S_II synaptic strength
% p_EEFail Synaptic failure prob
% lambda_E lambda_I LGN input
%... |
fa1815c80d635a72ba66fe2c01c6f8c8ce8d651716501cdff6833c2e9e4749c9 | MATLAB | 10,239 | 296 | function RLphase20190517JS
global ...
ACresult ACresultW CCresultDrinkOn SpikeArray TurnMarkerTime RpegTouchallWon LpegTouchallWon...
RpNum LpNum CCresultSpike locsP1time locsP2time locsP1time2 locsP2time2 pksA1 pksA2 CCresultRtouchWon CCresultLtouchWon dpath3...
StartTime FinishTime DiffMaxMinR D... |
351458ad2b7cc6f0e64ed2e7fcdc07c41e73b710e4358618bf97b53bc147f0d4 | MATLAB | 10,248 | 254 | % This program is intended to check statistics of motion artefacts on
% behaviorss
%
% Procedure
% %% 1. datapath to the 6 motions data
% %% 2. make list of the datasets
% %% 3. extract time series of motion artefact
% %% 4. make contract between two groups
% %% 5. preparation for visualization
% %% 6. Visualize the re... |
6f8e9df0725bca9089e773253c5cb9fa9f6e86f2dab5690da6e9b786df0c1f65 | MATLAB | 10,248 | 210 | % Statistical test for indirect interactions in gene regulatory networks
%
% Reproduces results shown in Fig 3 discussed in the section "Inferring functional modules in gene regulatory networks" in
% "Correlations reveal the hierarchical organization of networks with latent binary variables" (2023) Stefan Häusler
%
% C... |
fb51327b11ca6b913c1152f6ea98b8542aa817ef00d4c46f974e2a8c8ec111c6 | MATLAB | 10,258 | 335 | % this script calculates FWF in GM ROIs extracted using the atlas
% normalized to the subject's space
clc
clearvars
close all
addpath(genpath('/storage/stella/MATLAB_toolboxes/'));
addpath('/storage/stella/Analysis/matlab_scripts/');
addpath('/storage/stella/Analysis/DTI_FreeWaterFraction_May2022/SCRIPTS_MATLAB/');
lo... |
1b19759b2a3d1cda1863e67eb6e5bd3465f31d245f96d5f7e60143cfd3db2163 | MATLAB | 10,269 | 301 | %%
clc
clear all
close all
%% Load in DLC-generated CSV file with x,y coordinates for defined labels
baseFileName = uigetfile('.csv');
Positions = readmatrix(baseFileName);
%% Extract positions from DLC-generated CSV and take out low probability paw positions
filename = baseFileName(1:35);
RealPositions = Po... |
ba58d6e13cd930830fadebb3115906e28de464abda9359b86d9f2a7d821087b5 | MATLAB | 10,313 | 288 | function [peak_refined_indexes, peak_quality_scores, ecg_quality] = peak_refiner_matched_filter(ecg_raw, peak_indexes, fs, params)
% peak_refiner - R-peak refiner for an existing R-peak detector method with R-peaks in R_peak_indexes
% Syntax:
% [R_peak_refined, R_peak_quality, ecg_quality] = peak_refiner(ECG_raw, R_... |
271a354102ce404f0a93997d4bcaf3be971a5b340f43b01336bfde4b2f1beb3c | MATLAB | 10,316 | 236 | function save_spec_res(app)
%UNTITLED save spectral analysis results
% Detailed explanation goes here
cols = {[0 0.4470 0.7410],[0.8500 0.3250 0.0980];...
[0.9290 0.6940 0.1250],[0.4940 0.1840 0.5560];...
[0.4660 0.6740 0.1880],[0.3010 0.7450 0.9330]};
[int_idxs,~] = listdlg('PromptString',{'Please ... |
ee8984c234a20cbf95179b153b5d37df5ee1c8bc0d764fa3a658753f0f132cad | MATLAB | 10,317 | 219 | %æsyOiyOP|UjÌOÉXC_ðÝè·éB
function varargout = TouchDividerAnalyzer(varargin)
% TOUCHDIVIDER M-file for TouchDivider.fig
% TOUCHDIVIDER, by itself, creates a new TOUCHDIVIDER or raises the existing
% singleton*.
%
% H = TOUCHDIVIDER returns the handle to a new TOUCHDIVIDER or the... |
619dca6ce31d7168cd554de316ad0b82e0639751908787cb3a3928d7b0900d9c | MATLAB | 10,319 | 280 | function untitled20191024
%¼àQFXpCNª Á½¼ãÌ^b`©çXpCNÜÅÌÔðp¢½\ª
%untitled20190311©çÌÏX_F1000rɼ·Æ±ëjMaxÌlð¬æêÊÜÅÉÏXAqxgÏ·ðgíÈ¢æ¤Éµ½
global ACresult ACresultW CCresultDrinkOn SpikeArray TurnMarkerTime RpegTouchallWon LpegTouchallWon... |
13467cdbbe949df2a903ce644e1fe9e30a9b36fcdb5205f6be7e63dd8441c90a | MATLAB | 10,327 | 190 | function update_burst_axis(app, keep_xl)
%UNTITLED Summary of this function goes here
% Detailed explanation goes here
cla(app.ax_msna_int), cla(app.ax_burst_res)
cla(app.ax_burst_interval_his), cla(app.ax_burst_duration_his)
cla(app.ax_burst_amplitude_his), cla(app.ax_burst_integral_his)
cla(app.ax_burst_res), cla... |
7e504ba9e6173a86d26ed0438b026e73cc53bf0d9a9f488eba659ac8d270d861 | MATLAB | 10,332 | 244 | function [grid_sizes, grid_size_prominences, mask_size, matched_filter_powers_avg, I_peaks] = ecg_gridest_matchedfilt(img, varargin)
% ECG_GRIDEST_MATCHEDFILT Estimates grid size in ECG images using matched filtering.
%
% This function analyzes an ECG image to estimate the grid size using a
% matched filter-based appro... |
35aafacbee5c0adf0f35a9e96e77d346375c1b1bcf52e006da7fbf41786beaab | MATLAB | 10,344 | 367 | classdef cylindricalFit<quadricFit
%A class for executing and managing cylinder fits
properties (SetAccess=protected)
center
radius
height
end
properties (Dependent, Hidden)
axis
yp
end
properties (Hidden)
... |
bfe1b3405485bf5512d6eb88c5a9995d16e2ef7c9ee3c73b2938f3c63a9ad3ea | MATLAB | 10,346 | 292 | function RLphase190531ALL
global ACresult ACresultW CCresultDrinkOn SpikeArray TurnMarkerTime RpegTouchallWon LpegTouchallWon...
RpNum LpNum locsP1time locsP2time locsP1time2 locsP2time2 pksA1 pksA2 CCresultRtouchWon CCresultLtouchWon dpath3...
StartTime FinishTime DiffMaxMinR DiffMaxMinL fname tfile OneTur... |
0275b1dad60db0be32d2a6f5094ccf3d9d16a2169fe7243b6aae42827ecd9a8a | MATLAB | 10,361 | 249 | function spike_res = spike_analysis(app)
%SPIKE_ANALYSIS Summary of this function goes here
% Detailed explanation goes here
MIN_CLUSTER=10;
% MSNA = app.data(app.settings.channel_idx.msna).data;
% data = app.data(app.settings.channel_idx.msna).data(app.settings.interval(1,1)/app.data(app.settings.channel_idx.msna)... |
79b5ea0add56dda00676946e2493998fd7b8b48a553b92a483489c54ce66c0a6 | MATLAB | 10,380 | 289 |
%{
----------------------------------------------------------------------------
Determine the time window for task relevant neurons
%Start of task
%Sound on
%Sound off
%Before choice
%After choice (0sec)
%After choice (1sec)
%After choice (2sec)
%p = 0.001
%Each epoch, predict the prior, sensory and choice... |
6499a77cb806f524873ab8f70def9348adcdb0802d3da463511ad2d4260c840c | MATLAB | 10,409 | 264 | % Function to make funstional Network from Raster Matrix
% Input
% R: Condition Raster: Cells x Frames
% XY: Original Coordinates: [x,y]
% r: radius: vector
% NameCondition: Name of the Condition: String array
% Output
% A: Adjacency Matrix
% IndxNeuron... |
ddc892065059c3ce91544ea57267a4f52141073c4e3e29b44ff5d57ca98c2673 | MATLAB | 10,423 | 320 | clear
clc
cd('I:\My Drive\ELYASHIV\PFC_paper_results_after_revision\new_ramp\ramp_statistics')
% save('all_ramps_table',"T")
T = importdata("all_ramps_table.mat");
T.mean_ramp = T.mean_ramp(:,1:120)
T.norm_ramp = T.mean_ramp - mean(T.mean_ramp(:,1:10),2);
T.short_ramp = T.norm_ramp(:,31:90);
for i = 1:lengt... |
b45d59ef7c5457ee647b847b6402917dadb4d7a9ea3b3fb1a409d3e6644f8540 | MATLAB | 10,436 | 342 | function burst_res = burst_analysis(app)
%BURST_ANALYSIS Summary of this function goes here
% Detailed explanation goes here
try
plot_flag = isa(app.ax_msna_raw, 'matlab.ui.control.UIAxes');
catch
plot_flag = false;
end
if plot_flag
cla(app.ax_msna_raw), cla(app.ax_burst_interval_his), cla(app.ax_burst_d... |
cf8e3a792968d0722edbcc53622e3b773e29c21ecebc31af497fe5b735e816b6 | MATLAB | 10,438 | 255 | %% msRunCNMFE_large
% CNMFE source extraction, based on original work by Pengcheng Zhou. This
% version allows you to perform unsupervised analysis. It is recommended to
% first run a few manual analyses to establish your parameters, then use
% the CNMFE_large (patches analysis) with established parameters.
% Based on ... |
a3162a6396904cfcc376c4d1af09cd9f27a653e6dcafa32dd90b57d8727305cd | MATLAB | 10,443 | 217 | %% MF+v for the field. Ver1: LGN on/off not considered so far.
% Input: NW parameters,
% connectivity matrices,
% External input rates
% Pixel setups
% Output: FrE, FrI, mVE, mVI
% Note: Let's not use anything to speed up linear inverse for now.
%% Functions quoting outside this file:
% 1. functi... |
438ce1f8e244c45baa4c92d80c103a3f74431057f9e1a6a3dc3a002f9e796738 | MATLAB | 10,444 | 296 | function varargout = ecg_beat_fitter_gmm_gui(varargin)
%
% ecg_beat_fitter_gmm_gui(ECG,Phase,ExpParamName),
% Graphical user interface for ECG approximation with sum of Gaussian kernels.
%
% inputs:
% ECG: a single ECG waveform used for model training
% Phase: the phase corresponding to the ECG waveform
% ExpPa... |
59d29181304c19e1300af70d3daef057e2a6d50e3c63e784c310c688bb19bdbe | MATLAB | 10,448 | 250 | clear
close all;
clc;
R1 = importdata('/Users/rsameni/Desktop/Seizure/kaggle/SourcesWithResultsBackup/testFreqDomainEnergyIncreaseRate01.txt');
R2 = importdata('/Users/rsameni/Desktop/Seizure/kaggle/SourcesWithResultsBackup/testICASubspaceAngles01.txt');
R3 = importdata('/Users/rsameni/Desktop/Seizure/kaggle/SourcesWi... |
f910554b06919a96f2edaf378e3c654608c1d551c0887785c9838ed2efc8c1ea | MATLAB | 10,454 | 195 | function [fp2ph, fp2ph_norm, da2achph_norm, mid, da2achph] = AK_fp2phase(beh)
%Distribution of signal fluorescence to the instantaneous phase of a
%second photometry signal, acquired using dual color fiber photometry
%
% [fp2ph, fp2ph_norm, da2achph_norm, mid, da2achph] = AK_fp2phase(beh)
%
% Description: Thi... |
46d643c948dcd8d6e23828d48751d8e3a97676d092f957ae69e7e0d6b74548e6 | MATLAB | 10,465 | 284 | function [ftrack_out,ftrack_mstaxis,ftrack_lpc_coeffs] = get_formant_tracks(y,fs,faxis,ms_framespec,nlpc_coeffs,yes_preemph,nformants,ftrack_method,yes_verbose)
frames_per_dot = 10;
dots_per_line = 50;
if nargin < 2 || isempty(fs), fs = 11025; end
if nargin < 3 || isempty(faxis), faxis = linspace(0,fs/2,1025); end
if... |
7d22ecdf764384e394a4d00aeb4e452c8acb3937ff7b0bc4f027009d22d6be10 | MATLAB | 10,480 | 244 | function save_spec_res(app)
%UNTITLED save spectral analysis results
% Detailed explanation goes here
cols = {[0 0.4470 0.7410],[0.8500 0.3250 0.0980];...
[0.9290 0.6940 0.1250],[0.4940 0.1840 0.5560];...
[0.4660 0.6740 0.1880],[0.3010 0.7450 0.9330]};
[int_idxs,~] = listdlg('PromptString',{'Please ... |
7459e9c35e9445c9d4374baf7b3ec2bbcb231e7284ac9cc5e70d6d65f7c62b86 | MATLAB | 10,483 | 302 | function [rgb_out, data_out, data_rgb_out, ticks, stmp] = colorcubes(n, w, inData, plotSwitch, limits, ax, cmapIn, mapData)
% Creates a cube of cubes in the RGB color space.
% COLORCUBES, with no arguments, shows 5^3 = 125 cubes with
% colors equally spaced in the RGB color space.
% COLORCUBES(n) shows n-by-n-... |
6f8f1c28226387a9544d184ffa90a1748eb1ba3e90a67c17c158f5306fb32411 | MATLAB | 10,507 | 308 | function [h,CI,p] = rst_1ttest(varargin)
% performs a robust one sample test, ie tests if an estimator is different
% from zeros.
%
% FORMAT
% [h,CI] = rst_1ttest(data)
% [h,CI,p] = rst_1ttest(data,'estimator',plot_option,alpha,nboot)
%
% INPUTS
% - data is either a vector or a matrix, in the latter case tests are
% p... |
3f134bc2405b053f8d323e7220ac55e8c97da06c383df1a25f898360bc5c3bb9 | MATLAB | 10,510 | 208 | %PegTouch.m %PegTouch analysis
%1AFInfoidate, mouseID, sessionNo,training condition, Num.Turns,TotalTouchTime, TotalWaterOn, Num.Stops, 1-10, 11-20, 21-30, 31-40,,,)
%2B:Start time array
%3C:Stop time array
%4D:TurnTime, cumulative
%5E:OneTurnTime
%6F:cumulativeTouchTime array; fall down
%7G:WaterOnTime arra... |
e9b42a4f5989a912769188399b4bbcd9c460d48b2cea996346722053ad1a763a | MATLAB | 10,513 | 208 | %PegTouch.m %PegTouch analysis
%1AFInfoidate, mouseID, sessionNo,training condition, Num.Turns,TotalTouchTime, TotalWaterOn, Num.Stops, 1-10, 11-20, 21-30, 31-40,,,)
%2B:Start time array
%3C:Stop time array
%4D:TurnTime, cumulative
%5E:OneTurnTime
%6F:cumulativeTouchTime array; fall down
%7G:WaterOnTime arra... |
c7e58b975f97fd1175321d4935ea324acacdd535a05a2c7b1a88cb7e219277e0 | MATLAB | 10,522 | 366 | function illustrate_eq_algorithm(dim,N,varargin)
%ILLUSTRATE_EQ_ALGORITHM Illustrate the EQ partition algorithm
%
%Syntax
% illustrate_eq_algorithm(dim,N,options);
%
%Description
% ILLUSTRATE_EQ_ALGORITHM(dim,N) illustrates the recursive zonal equal area
% sphere partitioning algorithm, which partitions S^dim (the unit... |
921b51f0dbd276a757ffbf352e91486bec00d44cf01c82fe3a3add71add09a40 | MATLAB | 10,528 | 265 | close all;
clear;
clc;
rawspectra = 'AllSubjectsRawSpectra.txt';
resultfname1 = 'testProcessSeizureEEGRWAofRawSpectra.txt';
resultfname2 = 'testProcessSeizureEEGAllSpectralFeatures5.txt';
% parameters
subject = {'Dog_1', 'Dog_2', 'Dog_3', 'Dog_4', 'Dog_5', 'Patient_1', 'Patient_2'};
ffs = 120;
f0 = 60; % powerline fr... |
83131c3712dc1f7f553c71574dc989f59896d3f4feb8ad540d6a978f9b11498f | MATLAB | 10,546 | 281 | %function [pval, t_orig, tmx_ptile, seed_state, est_alpha]=mxt_perm1(data,n_perm,alph,tail,verblevel,seed_state,freq_domain)
%
% mxt_perm1-One sample permutation test based on a t-statistic and null
% hypothesis of a mean of zero. Can handle multiple electrodes and time
% points/frequencies. According to Hemmelammnn e... |
5985a5cab822c043ec9fd6f5c6111affceacd76912b9eed8f3f5a23dfaa7f68e | MATLAB | 10,547 | 193 | function Set_Objects_UI(P)
P.GUI_Handles.Main_Figure = uifigure('Name',[P.GUI_Handles.Software_Name,' ',P.GUI_Handles.Software_Version],'AutoResizeChildren','off');
clf(P.GUI_Handles.Main_Figure);
set(P.GUI_Handles.Main_Figure,'WindowState','maximized','Color',P.GUI_Handles.BG_Color_1);
drawnow;
P.GUI_Handles.... |
2b94ecd8e8ba9bd028ffcb2154c56579d2819038ca2de39523b6d647227de1ae | MATLAB | 10,555 | 125 | module load MATLAB/2020b
matlab -nodesktop -nodisplay
cp /external/rprshnas01/external_data/rosmap/neuroimaging/data_transfer_june6_2022/freesurfer/v6/mri_cortical_thick_v6d_* ./
map_thick_l=readtable('/external/rprshnas01/external_data/rosmap/neuroimaging/data_transfer_june6_2022/freesurfer/v6/mri_cortical_thick_v6d... |
49225df03a500634e060c0f6b390a180f96ab93a3ef77d691ef75619b4292551 | MATLAB | 10,561 | 258 | function Positive_W3_or_All_Pattern_1_20201208
path=['C:\Users\C238\Desktop\touchcellLtRt_Hirokane'];
cd(path);
LS=ls;
PositiveLtouchUnit=[];
PositiveRtouchUnit=[];
LtPWPointArray=zeros(1,5);
LtPWFireArray=zeros(1,5);
RtPWPointArray=zeros(1,5);
RtPWFireArray=zeros(1,5);
W3PositiveLtouchUnit=[];
W3Positiv... |
66de120772536dc1e4ee7583e921dddeff1f9c8f971683a0b178185c54ea0632 | MATLAB | 10,562 | 258 | function Positive_W3_or_All_Pattern_1_20200302
path=['C:\Users\C238\Desktop\touchcellLtRt_terashita'];
cd(path);
LS=ls;
PositiveLtouchUnit=[];
PositiveRtouchUnit=[];
LtPWPointArray=zeros(1,5);
LtPWFireArray=zeros(1,5);
RtPWPointArray=zeros(1,5);
RtPWFireArray=zeros(1,5);
W3PositiveLtouchUnit=[];
W3Positi... |
bbf4971a2a334d7c6dd393b67a78d6c5d2a8db3b94603003605fa93306c8a1bb | MATLAB | 10,572 | 246 | %% Subspace overlap for VTN and control TTT
% For each session, subspace overlap is calculated by average tHit and tCR.
% no session concatenation
% Dimentionality reduction analysis is not suitable for a sessions with few units.
% To control this, only sessions with more than 10 units are included and the num... |
70d965903fb2864535067cf73591692b26a80f81aeaf2d4a060086202f89a5d6 | MATLAB | 10,575 | 241 | function [feature_vec, feature_info] = ecg_time_intervals_features(position, fs)
% function [feature_vec, feature_info] = ecg_time_intervals_features(position, fs)
% Extract features related to the ECG time interval
%
% Inputs:
% position: Fiducial points of the ECG signal (expressed as sampl... |
81db99f9e49692e131dcfa0770465778cb0159c5c7b1894ce9f69e63d47b01f8 | MATLAB | 10,579 | 155 | clear;
close all;
clc;
addpath 'G:\Sameni\Documents\Papers\Journal 40 (Spline ECG Filtering)\CODES'
randn('seed', 0);
rand('seed', 0);
% % % dbstop if warning
type = {'Normal', 'Arrhythmia', 'PTB'};
for ttp = 1 : length(type),
switch(type{ttp})
case 'Normal'
pth = 'J:\ECGData\Normal';
... |
f64f1825e1cd0118507797ca2fe007787be31d47bab8abe02661cbb1d559e51c | MATLAB | 10,580 | 367 | function hsvdRAW(filename,magnet,hsvdflag,npeak,ncol)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% hsvdRAW.m
% Remove selected peaks using filtered HSVD algorithm (from mrui)
% Use .RAW file ONLY (for Vnmr fid use peakremoval.m)
% Run under Sun Solaris
%
% hsvdRAW(filename,magnet,hs... |
be46c033a97788a17581aeede1283a70ef037a8fee92979ea8fb9d52d90ccb6f | MATLAB | 10,613 | 270 | function PlotRepeatTouchSpike20171011(TouchIntervalSet,SpikeA,NN,PegTouchAll,fname,tfile)
% [FigA FigB FigC FigA3 FigAA]=PlotRepeatTouchSpike20170823(TouchIntervalSet,SpikeA,NN,PegTouchAll,fname,tfile)
global FigA FigA3 FigAA
%SÄÌ^b`´Ôuðâ³
Hist0=cell(length(NN),4);
SpikeCount=cell(length(NN),4);
Spike... |
21f06a25cbebd88083f00c3e107331c77c4e1377ec5bdc42cec101c7203e01c3 | MATLAB | 10,624 | 231 | function [erps_rwa, erps_mean, erps_rwmd, erps_median, erps_var, stacked_targets] = erp_extractor_rwa(data, fs, target_indexes, erp_wlen, varargin)
% Event Related Potential extraction using Robust Weighted Synchronous Averaging
%
% Usage:
% [erps_rwa, erps_mean, erps_rwmd, erps_median, erps_var, stacked_targets] = e... |
a5bada377c9645b21293c8213be587753bc34516842997b9b1aa29b5d359ba80 | MATLAB | 10,648 | 249 | function [data_posterior_est, data_prior_est, n_var] = ecg_den_phase_domain_gp(data, peaks, params)
% ecg_den_phase_domain_gp - An ECG denoiser based on a data driven Gaussian Process filter in the phase domain
%
% Usage:
% [data_posterior_est, data_prior_est, n_var] = ecg_den_phase_domain_gp(data, peaks, params)
%
%... |
3070d11fb356e59628b4eb9c78e3fe068a2579c2e48a97556116c01353e133f4 | MATLAB | 10,654 | 301 | %% Date: 03-03-2022 Programmed by: Deirdre BOLGER
% Function to plot ERPs of the selected data.
%c
%*****************************************************************
%% LOAD IN EEG DATA
study_session = 'Test_9';
conds = {'Match','Mismatch'};
numsuj = 9;
condnames = conds;
data_meansuj = cell(1,size(co... |
2d833d1bbe17cc19ad6556fe7c02df066bbd514778424acc6044837f1d65b354 | MATLAB | 10,658 | 224 | %% Function with the system of differential equations for 5-HT+HA varicosities.
function dy=msc(t, y, v2, ssri_molecular_weight, SSRI_start_time, SSRI_repeat_time, SSRI_q_inj, fmh_molecular_weight, FMH_start_time, FMH_repeat_time, FMH_q_inj, mc_switch, mc_start_time, btrp0, eht_basal, gstar_5ht_basal, gstar_ha_basal, ... |
fa3ea6825c28796c84a4c5568874aa3942c3029914f3c9d93431232a73e1eaa8 | MATLAB | 10,660 | 210 | %--------------------------------------------------------------------------
%RETROICORplus_calc
%
%Uses heart rate and respiration data to create nuisance regressors
%for physiological pulsations.
%
%Output:
%CPR: cardiac phase regressors (2 (sin+cos) * order regressors)
%RPR: respiratory phase regressors (2 (sin+cos)... |
4a716c85594665c4a3146ced3b214f17aed241024d9dd4714a2c58dea682b72a | MATLAB | 10,663 | 297 |
%% Date: 03-03-2022 Programmed by: Deirdre BOLGER
% Function to plot ERPs of the selected data.
%
%*****************************************************************
%% LOAD IN EEG DATA
conds = {'Filler', 'Test'};
numsuj = 10;
condnames = conds;
data_meansuj = cell(1,size(conds,2));
data_GA = c... |
333f36ba8f350b3f048d5bc25865cc59dbee322024f47afe03751a4012e45d4c | MATLAB | 10,671 | 297 |
%% Date: 03-03-2022 Programmed by: Deirdre BOLGER
% Function to plot ERPs of the selected data.
%
%*****************************************************************
%% LOAD IN EEG DATA
conds = {'Match', 'Mismatch'};
numsuj = 30;
condnames = conds;
data_meansuj = cell(1,size(conds,2));
data_GA ... |
8543d5c3f31c9af5332eab3f04892fc592c11363ad4c85c7671275e3f3201d06 | MATLAB | 10,671 | 370 |
function fractional_sampling(varargin)
% sys_argv = str2double(varargin{1});
%%
% rng(sys_argv)
savefigpath = './fig/'; % folder for figures
savedatapath = './data/'; % folder for data
if not(isfolder(savefigpath))
mkdir(savefigpath)
end
if not(isfolder(savedatapath))
mkdir(savedatapath);
end
%%
p.lo... |
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