sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
1c79211d151ca2972c2203f4b6fca242acab06a88538dfe03cd034cc9e19f063 | MATLAB | 11,856 | 394 | classdef DensityPeakClustering < jrclust.interfaces.Clustering
%DENSITYPEAKCLUSTERING A Rodriguez-Laio clustering of spike data
%% OLD-STYLE PROPERTIES, publicly gettable (will be deprecated after a grace period)
properties (SetObservable, Dependent, Hidden, Transient)
cviSpk_clu; % => spike... |
58b0df38b8c7d6d90a94e95b66a0b147732cda9ac0cb13bdd626fc4ca91ec4f0 | MATLAB | 11,887 | 205 | function PeakTouchPhase
% NXRIOÌs[NÌʪz
global CCresultRtouchWon CCresultLtouchWon RpegTouchallWon LpegTouchallWon SpikeArrayWon tfile pegpatternname trimFolder2 IntervalCount PeakInterval PeakPhaseCount
findpeaks(CCresultLtouchWon,'MinPeakDistance',30);
[Lpks,Llocs]=findpeaks(CCresultLtouc... |
0c5c534075d3fb13ce260c511a64554768e908a6246b790dabd6183174741c90 | MATLAB | 11,912 | 300 | %% Function To save CSV files from Network to Gephi Format
% Functional Network of Neural Ensambles
% RUN IN: Ensemble_Sorting.m
% AÑADIR NODOS DE REFERENCIA ESPACIAL: ESQUINAS DE NEGRO
% AÑADIR NODOS SIN CONEXION PARA AMPLIAR LA DIFERENCIA ENTRE GRUPOS
% Optimizar código
% Input
% Raster (frames x cells) Matr... |
d282d7b63d77fc1a5b0b97cf9e51345446f2a24a3eb834955292ec7a24e9bae2 | MATLAB | 11,912 | 265 | classdef Statistics
% getShuffleData and getTestTrainTrials are modified dPCA functions.
methods(Static)
function [resampled_Xtrial] = bootstrp(Xtrial,numOfTrials,B,S,D)
resampled_Xtrial = Xtrial;
N = size(Xtrial,1);
%%%%%%%%% Bootstrap trials for each tri... |
e580d7c0e0963eb5f2c4d49f458c2c700d5ee928d55d632d55746df40573960f | MATLAB | 11,912 | 272 | function reconstructSiemensMP2RAGEwithTCL(rawDataFile,TCLdir,varargin)
% function reconstructSiemensMP2RAGEwithTCL(rawDataFile,TCLdir,varargin)
%
%
% Usage:
%%%%%%%%
%
% 'rawDataFile' - this is the filename for the raw data you exported from
% TWIX (including the full path). Due to the way I chose to
%... |
98ab0980c597ddd0f004d5db16438874e996f89d4e2c3af83f3682f75863fc48 | MATLAB | 11,936 | 319 |
function [P_O_model ,alpha_out , beta_out , alpha_T_out , b_c_ot_nc_out , P_observ_cond_to_state_out , P_observ_cond_to_state_comp_out]...
= forward_backward_lsim_sed( pi_0_lsim , coupling_tetha_IM , transition_matrices_IM , gmm_para_lsim , Y_in )
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
efcabbb1b8f827fd0a24c777a5b940f394b606856b4dba828ca1b5f4d1160c43 | MATLAB | 11,939 | 220 | % Test script for an ECG denoiser based on a data driven MAP estimator in
% the phase and time domains
close all
clear
clc
seg_len = 10.0; % ECG segment length
% Load data
% datafilepath = '../../../DataFiles/Physionet.org/files/ptbdb/1.0.0/'; % Change this path to where you have the .mat data files
% fs = 1000.0; %... |
2e66c38a7414c18519083e91a141082792b166203295d0b951d391a90f3e1e7b | MATLAB | 11,968 | 264 | %% 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
%... |
a310d063bf9505d95e2fecdcc7882aac90f586df40393ceb215da04fe87d00ca | MATLAB | 11,987 | 257 | function [nexFile] = readNexFile(fileName)
% [nexFile] = readNexFile(fileName) -- read .nex file and return file data
% in nexFile structure
%
% INPUT:
% fileName - if empty string, will use File Open dialog
%
% OUTPUT:
% nexFile - a structure containing .nex file data
% nexFile.version - fil... |
6dc1aabff10c6faff0cec54afa04accf3941f5ab18ec32fbcf1acc0e787820dc | MATLAB | 11,997 | 293 | function MultiLeadECGPlotterStandardSize(data, ch_names, fs, ref_ch, t1_small, t2_small, t1_long, t2_long, Title)
% fh = figure('Units', 'centimeters', 'PaperUnits', 'centimeters', 'Position', [1.0, 1.0, 19.59, 25.94], 'PaperOrientation', 'Portrait', 'PaperType', 'usletter');%, 'visible','off');
% h0 = subplot('Positi... |
85c7e5924d72fb8002d1a061ee4da39311a4481ca86fa2627fc9fcd22d21eaf2 | MATLAB | 12,012 | 290 | function AllLFPauto
%WheelAnalyzer24chSpikeÅðÍðs¢AʪÉcÁÄ¢éóÔÅs¤
%MATLABtH_ÉNlx2MatCSC.mexw32ÆNlx2MatCSC.mexw64ðüêĨB½ÔñÇ¿ç©ÐûÅæ¢B
%timestampsÍ270336¸ÂÁB270msÆvíêéBtimestampsÌ512ÂÌTvB
%270336/512=528. TvOÍ0.528ms²ÆBfs=1... |
f30530ae33e711d0da0d4c92e917d8efd63c30f067ce67314ef943ab8b245dca | MATLAB | 12,015 | 315 |
%%
clear;
clc;
%% load files
% [file, path] = uigetfile('*.mat');
% datafile = fullfile(path, file);
% load(datafile)
[file, path] = uigetfile('spike_clusters.npy');
datafile = fullfile(path, file);
spike_clusters = readNPY(datafile);
cd(path)
[file, path] = uigetfile('spike_times.npy');
datafile ... |
293c9d2ee95dbc3c31103e5ee596e07c8beff8b79d2cad9cd3e959ddea9655e6 | MATLAB | 12,017 | 330 | function [Trace,Cells]=mnl_ReadXML_DendritesAndSomas4(fname)
%Amended to go even faster and removed the chances for duplication on the
%traces portion
filename=sprintf('%s%s',fname,'.xml');
[s]=xml2struct(filename);
%% Step 1 - Store the somas
if isfield(s.mbf,'contour')==1 %if somas exist
nContours=size(s.mbf.cont... |
d2176d724c76db380b5066d789a006d5c624441c27c3c9b705de216668669ab9 | MATLAB | 12,034 | 458 | %% Cross-time decoding analysis
sessionTags =...
{'M22027', '20220517';...
'M22029', '20220607';...
'M22031', '20220524';...
'M22032', '20220621';...
'M22033', '20220706'};
for isession = 1:5
clear stat run
fname = [sessionTags{isession,1},'_', sessionTags{isession,2},'_basic.mat'];
load(f... |
dacd2f23122f8a620ee5976cceeaf053112ee143e6aeab20f3edfb1704a97948 | MATLAB | 12,048 | 219 | function [myState]=Model_RL2(myState, myParam, myMap, mode, varargin)
%% extract current/previous state/action
state_current=myState.state_history(myState.index);
action_current=myState.action_history(myState.index);
%% process
switch lower(mode)
%% [random decision(action selection) mod... |
30c66ffe6fa63c4bd26a67073fa8e0d1920c705dfd391b12908a99c266a25791 | MATLAB | 12,057 | 309 | function CycleTable = measure_cycle_properties(ChannelBroadband, CycleTable, SampleRate)
% Identifies various ways to characterize each peak. Based on Cole 2019,
% but relative to the negative peaks rather than positive peaks.
% NOTE: all fieldnames should start lowercase, so I know later on that they
% come from here.... |
62e22e5129086e7edd481ae14eab8788db0db83acf797ea1b61fd15a9f733f1c | MATLAB | 12,065 | 361 | function [f2Beads,Scale]=mnl_Pipeline_MeasurePSFandCA(fname)
%% Now Load in the Image
[Data,Scale,dim]=mnl_Load4Dimage;
Mdim=[dim(2) dim(1) dim(3) dim(4)]; %The MATLAB way of storing dimensions
%% Load in the Beads
if exist('fname','var')==1
ID=fname(end-3:end);
else
ID=[];
end
if strcmp(ID,'.xls')==1
% Ext... |
9b91cae70d1fbb60b74c65c742e8815e6b52a06b3f3ade4fe63ef4e696f85c2d | MATLAB | 12,066 | 300 | function [data_posterior_est, data_prior_est, n_var] = ecg_den_time_domain_gp(data, peaks, params)
% ecg_den_time_domain_gp - An ECG denoiser based on a data-driven Gaussian Process MAP estimator in the time domain
%
% Usage:
% [data_posterior_est, data_prior_est, n_var] = ecg_den_time_domain_gp(data, peaks, params)
... |
6dc26301b10f3a1310182437940fc2f24ff08823dfb0cbb91a9335f85782bcc5 | MATLAB | 12,067 | 256 | function update_spike_axis(app, static)
%UPDATE_SPIKE_AXIS Summary of this function goes here
% Detailed explanation goes here
sel_cluster = find(strcmp(app.popup_cluster.Value,app.popup_cluster.Items));
int_idx = find(strcmp(app.popup_int_spike.Value,app.popup_int_spike.Items));
%data = app.data(app.settings.chan... |
bb74149beaaf1546b24d336f9fc80cdea71d161e8e87947e2d7798e0e1d1ca18 | MATLAB | 12,067 | 374 | function [cData,Scale,dim]=mnl_CorrectForChromaticAberration
% Does exactly what it says on the tin! Uses bfopen to open anyimage with
% the scale information and then corrects the chromatic aberration based on
% the regressions calculated from bead data. Finally it saves each channel
% separately using the function sa... |
caa29fd155979bb2a33e30da8f19115095dc4f6e2729b4972b058ca07ab59b46 | MATLAB | 12,089 | 314 | function [mOutGRAPPA, timingReport] = performHostGRAPPArecon(twix_obj,tempDir,combinePars)
%
%%%%%%%%%%%%%%%%% -- Jan 2018, gallichand@cardiff.ac.uk - this function
%%%%%%%%%%%%%%%%% should now be obselete, as it is replaced by the _RAMonly
%%%%%%%%%%%%%%%%% or the _toDisk variants, which include newer options.
%%%%%%%... |
0d9fa530ab6d6a80d07cabb0bdf8d804eccb959f33ae0cb8f892094ecaf607fc | MATLAB | 12,102 | 336 | function matsuda20190913RepeattouchW468
global CCresultRtouchWon CCresultLtouchWon RpegTouchallWon LpegTouchallWon SpikeArrayWon tfile pegpatternname trimFolder2
% cd('C:\Users\C238\Desktop\CheetahData\2019-9-15_14-29-36 17301-03');
% dpath=('C:\Users\C238\Desktop\CheetahData\2019-9-15_14-29-36 17301-03\');
% dpa... |
d094c8c35e9992df8120b107691ba16792ecc783ba5c767f97b086f743dd5e35 | MATLAB | 12,122 | 490 | function varargout = corrplot1(varargin)
%CORRPLOT Plot variable correlations
%
% Syntax:
%
% corrplot(X)
% corrplot(Tbl)
% [R,PValue,H] = corrplot(...)
% [...] = corrplot(...,param,val,...)
% [...] = corrplot(ax,...)
%
% Description:
%
% CORRPLOT creates a numVars-by-numVars grid of scatter plots between
%... |
acd9c33ab1da33c0f7d79bc186002790be96f591654749af893eeefb1506e4a1 | MATLAB | 12,165 | 368 | %% analyse allen PSTHs
areas = {'VISp', 'VISl', 'VISal', 'VISrl', 'VISam', 'VISpm', 'LGd', 'LP'};
minTrials = 10;
%% load data
dataDirectory = 'E:\AllenInstituteAnalyses\AllenDataAnalysis\Data\rawMatFiles';
dataFiles = dir(fullfile(dataDirectory, 'psth_session*'));
for isession = 1:numel(dataFiles)
load(fullfi... |
8258e578a2e3200d8c98bc2d6212c4740dedbfa37a40327920045881db1bb821 | MATLAB | 12,176 | 275 | function [penalty_factor, cc, ee, L_curveC, L_curveE] = optimal_smoothness_factor(xx, bb, ss, mode, SmoothnessFactor, penalty_factor0, signorm, ACCURACY, MAX_ITERATION, FORGETTING_FACTOR, LCurveSweepLength, LCurveSweepFator)
% optimal_smoothness_factor - Calculate the optimal smoothness factor for a piece-wise Tikhonov... |
9369944d62a9d63a10c589ee6541724d3ab940398b57e5c3969c6745d9711727 | MATLAB | 12,186 | 426 | function [params model er indexes method] = ECGBeatFitterAuto(ECGmean,meanphase,approach,varargin),
%
% [params model er indexes method] = ECGBeatFitterAuto(ECGmean,meanphase,approach,stopth,divisions,maxit,energyth,wlen)
% Automatic fitting of sum of Gaussian kernels over a given ECG
%
% inputs:
% ECGmean: the i... |
e213f0f11754af3acc6eef9fc682c0cc554ce0465d0662fe75cb16d6a6538a2c | MATLAB | 12,189 | 253 | function [alignedC] = clusterAlignment(c,varargin)
% [alignedC] = clusterAlignment(c,varargin)
% ------------------------------------------------------------------------
% Align cluster indices across different clustering solutions. 'c' is an n
% x p vector of n different clustering solutions. This script will
% iterat... |
9dc880f0c29a536b17a26ff9239ecfa4fd5efe707a491ebbd7cebab351bae30d | MATLAB | 12,204 | 254 | clear all
% order one: sound simple, sound complex, line complex, line simple, line
% complex, sound complex
eegOrigDir = '../Bedrest_PreEEG/EEGFilter';
eegdirNew = '../Bedrest_PreEEG/EEGCutted';
% first campaign HDBR
subject = {'A_1','A_2','A_3','A_4','A_5','A_6','A_7','A_8','A_9',
'C_1','C_2','C_3','C... |
dd6706311af57db992ec852c294714f70d770b16c4f50281c1b6399523354074 | MATLAB | 12,215 | 339 |
idx_single =[7];
cluster = {[1:4]};
path = 'E:\data\uncaging\multi cluster cooperation\112222\cell4';
preflix = '221123_001';
% single clust
clear PC shutter
filename_single = sprintf('%s.singlecluster.%d.wcp',preflix, idx_single);
out=import_wcp(fullfile(path, filename_single),'debug');
n_channel = out.channel_n... |
755f3baee0a527f920a09999f5e07ad7bf9b5900253a939bdd32672b9876a236 | MATLAB | 12,217 | 311 | function [efPxTrace,Somas,BkgSigCumulativeDistribution,NumLengthThresh,MagThresh,BkgMedian,MaxValues]=mnl_ProcessTracesFromNeurolucida_DendritesSomas_v14(fname,cData,Scale,dim)
% Process the traces that have been extracted from Neurolucida and then get
% the corresponding raw voxel values for each trace (NB Trace=the
%... |
10a822dfa1861d8801972651fbfcc4de67df273e38725be3fe4b2b779b926494 | MATLAB | 12,247 | 304 | function spike_res = spike_analysis(app, update)
%SPIKE_ANALYSIS Summary of this function goes here
% Detailed explanation goes here
if nargin == 1
update = false;
end
MIN_CLUSTER=10;
calc_flag = true;
% if ~isempty(app.spike_res)
% spike_res = app.spike_res;
%
% if (spike_res.analysis.sorting ==... |
bb8d5c5a7b008519af4459db001a0cedb6ff3cffb0fdb67bdc177b2d2affe6de | MATLAB | 12,261 | 296 | function [FragmentValues,BkgMean,MaxValues]=mnl_SplitTracesIntoFragments_v2(Trace,Scale,Data,SampleBkgVxList)
% Function that splits every trace into fragments of all possible lengths
% based on the number of points
%
%Inputs
% Trace - List of the Traces
% Scale - The scale of the image (Data)
% Data - The image to get... |
4eccc18da592af1d9ea40cee6d71cc856688088e6e73d086fa4f73048ae5047a | MATLAB | 12,278 | 303 | function TouchInterval
global CCresultRtouchWon CCresultLtouchWon RpegTouchallWon LpegTouchallWon SpikeArrayWon tfile pegpatternname trimFolder2 IntervalCount pegpatternum
% NXRIO©çs[Nðo
% subplot(2,2,3);
findpeaks(CCresultLtouchWon,'MinPeakDistance',30);
[Lpks,Llocs]=findpeaks(CCresultLtou... |
4e49288cf79844054ed9c17e475e88aefd9e47d9c1df0e4588de47cc633c2d56 | MATLAB | 12,294 | 325 | function mnl_ComparingClusters(efPxTrace)
%% Extract the imput matrix and weights (magnitude)
dim=efPxTrace(1).dim;
nTrace=size(efPxTrace,2);
nXFP=size(efPxTrace(1).VecNormMean,2);
InputWeights=nan(nTrace,1);
InputMatrix=nan(nTrace,nXFP); % Done this way so if a value is missing we can see it
for i=1:nTrace
if isn... |
82911f4da8720d511f00a382ab2c93962257b8a1008f72c5dbe8d83e91d49974 | MATLAB | 12,294 | 325 | function mnl_ComparingClusters(efPxTrace)
%% Extract the imput matrix and weights (magnitude)
dim=efPxTrace(1).dim;
nTrace=size(efPxTrace,2);
nXFP=size(efPxTrace(1).VecNormMean,2);
InputWeights=nan(nTrace,1);
InputMatrix=nan(nTrace,nXFP); % Done this way so if a value is missing we can see it
for i=1:nTrace
if isn... |
41fa720b07b56ca7f3915b402c996feaabe17796156bbc2694a903ca8a983ad2 | MATLAB | 12,296 | 333 | function varargout = Randomizer_Import_ERP(varargin)
% RANDOMIZER_IMPORT_ERP M-file for Randomizer_Import_ERP.fig
% RANDOMIZER_IMPORT_ERP, by itself, creates a new RANDOMIZER_IMPORT_ERP or raises the existing
% singleton*.
%
% H = RANDOMIZER_IMPORT_ERP returns the handle to a new RANDOMIZER_IMPORT_ERP or... |
22463b44fb93c0ee8d22bb886d850f2f298c300f28df9ed530a0e407c66bc3bd | MATLAB | 12,311 | 306 | function spike_res = spike_analysis(app, update)
%SPIKE_ANALYSIS Summary of this function goes here
% Detailed explanation goes here
if nargin == 1
update = false;
end
MIN_CLUSTER=10;
calc_flag = true;
% if ~isempty(app.spike_res)
% spike_res = app.spike_res;
%
% if (spike_res.analysis.sorting ==... |
27bf676878af39d97f565d6e8f077201f0003a45d2cab0b5122e1e775f2ad5bb | MATLAB | 12,320 | 298 | function save_spike_results(app)
[int_idxs,~] = listdlg('PromptString',{'Please select intervals ',...
'to be plotted/saved.',''},...
'SelectionMode','multiple','ListString',app.popup_int_entropy.Items);
[form_idxs,~] = listdlg('PromptString',{'Please select fileformat ',...
''},...
'SelectionMode','m... |
13139af39fcf502e5a1118177db51bf963ba386d0140351ca197377d07b31d3e | MATLAB | 12,353 | 377 | function varargout = Ragu_Cormat(varargin)
% Ragu_Cormat M-file for Ragu_Cormat.fig
% Ragu_Cormat, by itself, creates a new Ragu_Cormat or raises the existing
% singleton*.
%
% H = Ragu_Cormat returns the handle to a new Ragu_Cormat or the handle to
% the existing singleton*.
%
% Ragu_Cormat('C... |
08fbbbf2f2c1e1674cb6eb44acc3b4a878979737b00329e4c5ee53ca8a1f1064 | MATLAB | 12,369 | 206 | function SpikeFormAnalysis20191125
clear all;close all;
path=['C:\Users\C238\CheetahWRLV20220213'];
cd(path)
LS1=ls;
AllCellwidth=[];
AllCellPtoT=[];
MeanFreqArray=[];
SumCell=0;
for i=1:length(LS1(:,1)) %%}EXÔ
trimFolder1=strtrim(LS1(i,:));
if ~strcmp(trimFolder1,'.') && ~strcmp(trimFolder1... |
d3e0f7e2f6ebfd0052d8440632f1978b9ba672bb521fbfeb26897be135639b0a | MATLAB | 12,369 | 198 | %%% LBPD %%%
% CITATION
% If you find LBPD functions useful, please cite the following paper(s):
%
% 1) Spatiotemporal whole-brain dynamics of auditory patterns recognition. BiorXiv.
% Bonetti, L., Brattico, E., Carlomagno, F., Cabral, J., Stevner, A., Deco, G., Whybrow, P.C., Pearce, M., Pantazis, D., Vuust, P., K... |
5e12f555001a342b7ada3fb811354f825abf8e934771681a0983e5e0eb622f2e | MATLAB | 12,385 | 259 |
% Line Complex, Line Simple, Sound Complex, Sound Complex, Sound Simple, Line Complex
clear all
eegOrigDir = '../Bedrest_PreEEG/EEGFilter';
eegdirNew = '../Bedrest_PreEEG/EEGCutted';
%first HDBR campaign
subject = {'B_1','B_2','B_3','B_4','B_5','B_6','B_7','B_8','B_9',
'D_1','D_2','D_3','D_4','D_5','D... |
a3ccb834486a926d904707315358d844652d94d73baa758c5093cbc2a70340d8 | MATLAB | 12,417 | 258 | function eps2pdf(source, dest, crop, append, gray, quality, gs_options)
%EPS2PDF Convert an eps file to pdf format using ghostscript
%
% Examples:
% eps2pdf source dest
% eps2pdf(source, dest, crop)
% eps2pdf(source, dest, crop, append)
% eps2pdf(source, dest, crop, append, gray)
% eps2pdf(source, dest, crop... |
9528389af5d3e976c2a4fc3f7654228f5d44c4580b28dab25df307dd2f4fdabb | MATLAB | 12,428 | 237 | %% Calcium Imaging Analysis Operator (segmentation)
% CIOA_02_segmentation is the second of a series of scripts aiming for an
% easy-to-use calcium imaging analysis pipeline. Here, we pool trials,
% subtract a reference stimulus, segment the images into granules, and
% provide a first assessment of whether a granule wa... |
9eaa673edf79eef7e2dcd0b4b6b4409a985e0376e99f1a40dfc190302d3b63e5 | MATLAB | 12,457 | 343 | function varargout = PostDimReduce(varargin)
% PostDimReduce
%
% Pop-up figure that allows user to upload the reduced dimensions to
% DataHigh and/or save them. It also allows to choose the top p
% dimensions.
%
% Copyright Benjamin Cowley, Matthew Kaufman, Zachary Butler, Byron Yu, 2012-2013
% ---GNU General Pub... |
4b9d131254f0de5b60a8922606f9a18d445af37af12370ddf8412749facb898a | MATLAB | 12,460 | 254 | function x_filtered = freq_domain_equalizer(x, method, params, varargin)
% freq_domain_equalizer - Frequency domain equalization
% This function implements several frequency domain equalizers that alter
% the frequency-domain magnitude response while preserving the phase.
%
% Syntax:
% x_filtered = freq_domain_equali... |
fb6d0989f26d86f75fcbb61e8444583f7e0cdd9d4f679d7d4325baf61af67f81 | MATLAB | 12,502 | 241 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This script plots population fits using the K-PD
% model calibrated to different groups of treated and untreated animals,
% It generates the plots of Figures 2A and S2 of the manuscript
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
e0a622633e6f882ff84a494edaa4875bf2630f8e680932ab27129d4078b8eda7 | MATLAB | 12,538 | 371 | %% analyse various discriminant analyses
sessionTags = {'M22027', '20220517';...
'M22029', '20220607';...
'M22031', '20220524';
'M22032', '20220621';
'M22033', '20220706'};
dataDir = 'C:\Users\edward.horrocks\Documents\Code\V1Dynamics\Data\basic_111022';
% dataDir = 'E:\V1Data\Data\basic_111022';
fo... |
6eb547a78e454bb6872709bfab649fe5b6638fe6dc1a492c857e00e5003d60f0 | MATLAB | 12,546 | 345 |
%{
----------------------------------------------------------------------------
Determine the time window for task relevant neurons
%Before start of task
%Start of task
%Sound on
%Sound off
%Before choice
%After choice (0sec)
%After choice (1sec)
%After choice (2sec)
%p = 0.001
-------------------------... |
0cd2aa1188cd6bb2a987b4afb4c575d94725a2e4af07e01ccc5519cb195510de | MATLAB | 12,564 | 419 | %datasetName = 'MNIST';
datasetName = 'CIFAR';
%datasetName = 'CIFAR-100';
%datasetName = 'SVHN';
%datasetName = 'tangent';
if (ispc)
kWorkspaceFolder = ['C:\Users\sergeyd\Workspaces\' datasetName];
else
kWorkspaceFolder = ['/media/sergeyd/OS/Users/sergeyd/Workspaces/' datasetName];
end;
Iter = 0;
kMaxIter = [1... |
79762b362e42374bbd705978e4eaf859748a2938b2550e95183fc9e3dc7e5829 | MATLAB | 12,580 | 378 | function burst_res = burst_analysis2(app)
%BURST_ANALYSIS Summary of this function goes here
% Detailed explanation goes here
cla(app.ax_msna_raw), 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(app.ax_ms... |
25c5698e89c24039ad615c5e2710e4b9d4d76b7f3cda79144411566741d678ee | MATLAB | 12,599 | 310 | %%Date: 09-04-2019 . Programmed by: D. Bolger
% Function to carry out ICA on a selected EEG dataset.
% Updated March/April 2020.
% To run ICA, it requires that the ADJUST toolbox is installed.
% It also runs the ADJUST toolbox to assist the user in identifying ICA
% components that correspond to ocular and muscular... |
f5fb8537fcc9dda3b5a19d563ecbb49ee4d373d1f679419a82636616c6a65bce | MATLAB | 12,611 | 378 | function burst_res = burst_analysis2(app)
%BURST_ANALYSIS Summary of this function goes here
% Detailed explanation goes here
cla(app.ax_msna_raw), 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(app.ax_ms... |
75c60aa5eede7643f1cdf0a6ede4c233d3ce628e3fd99f3c3366519add0b4a86 | MATLAB | 12,628 | 303 | function save_spike_results(app)
[int_idxs,~] = listdlg('PromptString',{'Please select intervals ',...
'to be plotted/saved.',''},...
'SelectionMode','multiple','ListString',app.popup_int_spike.Items);
[form_idxs,~] = listdlg('PromptString',{'Please select fileformat ',...
''},...
'SelectionMode','mul... |
75eb5ab1ab1f1398487e59623fd1b9adac8060ff7b42ee08b1ef621f57261258 | MATLAB | 12,629 | 355 | function qt_rr_prior = compute_qt_rr_prior(data_bias, ecg_rpeaks_index, ...
ecg_qrson_index, ecg_qrsoff_index, ...
beat_quality_twave, avg_intervals_ecg, rr_intervals_ecg, ...
index_clustering, num_cls, fs, win_sample_T, quality_thr, rr_percentile)
%COMPUTE_QT_RR_PRIOR Estimate QT and RR from clean high-qu... |
28e4b5b93a5bbabecb0688f3a5582479047aa45c911b877fecf428834acd359b | MATLAB | 12,630 | 303 | function save_spike_results(app)
[int_idxs,~] = listdlg('PromptString',{'Please select intervals ',...
'to be plotted/saved.',''},...
'SelectionMode','multiple','ListString',app.popup_int_entropy.Items);
[form_idxs,~] = listdlg('PromptString',{'Please select fileformat ',...
''},...
'SelectionMode','m... |
6d3eba62720ce07979ac745c7809c323876360faca60f59a51cd5d71558e939c | MATLAB | 12,650 | 375 | function bootstrap(obj, varargin)
%BOOTSTRAP Bootstrap a JRCLUST session
% metafile: optional string; path (or glob) to meta file(s)
if nargin > 1
metafile_ = jrclust.utils.absPath(varargin{1});
if isempty(metafile_) % TODO: warn?
metafile = '';
workingdir = pwd();
... |
d9602cad75e51fb4cfbb5e7d4b84bd6f896eb80f52d82286555b33b956bcba33 | MATLAB | 12,668 | 338 | function data = extractH5_WS(h5file)
%Extract WaveSurfer Data from H5 File
%
% data = extractH5_WS(h5file);
%
% Description: This function parses the H5 file generated after an
% acquisition using the wavesurfer software. The function uses a
% combination of original code as well as code found in the inn... |
d55686693a1c720748e0097fae4d3e53548cd70c60d66b5b1e7c68ce871ee02b | MATLAB | 12,691 | 296 | %% Paper3: 1st test
% Testing different combinations of x and y for E and I cells.
% Output: save the turning curve data
% Input xE, xI, yE, yI;
% Version 1: xE, xI only. yE and yI are kept as 1 from the beginning to end
% Zhuo-Cheng Xiao 06/18/2023
function [] = HPC_TestEIxy(xE,xI)
CurrentFolder = pwd
addpath(Current... |
72a3943e03f0b68d2c4b6f52930a6be4bf0411ce0d17ca515f650d7dda5ad5e0 | MATLAB | 12,704 | 383 | function varargout = DragTrajectory(varargin)
% DragTrajectory
%
% Allows users to interactively change the dimension data by
% "dragging" and thus changing the values for each dimension.
%
% Copyright Benjamin Cowley, Matthew Kaufman, Zachary Butler, Byron Yu, 2012-2013
% ---GNU General Public License Copyright--... |
7c3c68c30850351516c483eeb09042e8cb75e2c207e7d9cbd3f80c1139cae93c | MATLAB | 12,720 | 351 | function RepeatFig20170605
close all
%@o11ooÆoo11oÅÅࢪðTµÄA»±ðSÉ10binlûç¢HÌÍÍÅvlðßé
%@»ê¼êÌÌæÉ¢ÄAoo1ooAo11ooAoo11oAo111oA1111oAo1111A11111ÅÌlðßéB
%@
cd C:\Users\B133_2\Desktop\MatFig\11901_170607aSc8_SS_02
rFileName='11901_170607';
l... |
1af619280113f4b824334bb284e2c94fa3ee5158088b9e9f65f292ed35baaf0c | MATLAB | 12,738 | 316 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Statistical Summary:
%
% 1. contrast between session1 and second replication, ok
% works good.
% 2. contrast between anesthesia and third replication, ok
% works ok
% sig between tph blue anesthesia and awake 2
% 3. contrast between second and... |
0ef62505e0841111b91559442d4079ad8d155090d336ff0b7e73f6052ebccac8 | MATLAB | 12,748 | 405 | function varargout = plot_spectrum(spec_info,param)
if ~exist('param'), param='';end
if ~isfield(param,'display'), param.display = 'real';end
if ~isfield(param,'display_var'), param.display_var = 1; end
if ~isfield(param,'mean_line_broadening'), param.mean_line_broadening = 0;end
if ~isfield(param,'xlim'), param.... |
6da0406df89ad89da6af4d3b99a5b41f0814dd5e139431ad40923c3c95efa753 | MATLAB | 12,778 | 282 | %% 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
%... |
389e3e2c1a97e17732a7d155cfa80b13a80f6f1fcc13c9d5b7d6e2e74e64d7b9 | MATLAB | 12,787 | 381 | %% plot response
clear
clc
cd('I:\My Drive\ELYASHIV\PFC_paper_results_after_revision\DREEDDS_VS_CONTROL\anova_control_vs_dreedds\new_running_like_phb_cno_code')
T = importdata("all_cells_with_response_parameters_and_tags.mat");
%% take out Nan magnitude cell (baseline = 0)
T.tag = T.tags;
T.cno = contains(T.ta... |
bc3606bb547b05cee06ea559a24486a285c9b3be21cbe481aa6f5423892ee0fc | MATLAB | 12,787 | 329 | function [X,ndx,dbg] = natsort(X,xpr,varargin) %#ok<*SPERR>
% Alphanumeric / Natural-Order sort the strings in a cell array of strings (1xN char).
%
% (c) 2012 Stephen Cobeldick
%
% Alphanumeric sort of a cell array of strings: sorts by character order
% and also by the values of any numbers that are within the strings... |
50f3a986bf0326361d54386c9d91848572e51b15a8a739246bb29888d26c005b | MATLAB | 12,794 | 306 |
%{
----------------------------------------------------------------------------
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... |
2952ce2f925d8059c7a75e36dc7fe5d3b5b4b4e0246759c9e7d4cbf167017d35 | MATLAB | 12,822 | 393 | function [Kappa,F1score,Recall,Precision,TruePositiveRate,FalsePositiveRate]=mnl_EvaluateClassifierPerCell(efPxTrace,ClusterIDs,Clusters,dim,DisplayFig,EuThresh,NumTraceLim)
%NB now excludes cells which have fewer traces than the minimum trace
nTrace=size(efPxTrace,2);
EuThresh=num2str(round(EuThresh,2));
%% Create the... |
034d38f6cd162515054ae06e3056058e6a9478b893331fc6bc2eda446b120b06 | MATLAB | 12,864 | 351 | function calc_combine_stats(app)
intervals = {[]};
signals = {[]};
anocovas= [];
for i = 1: length(app.comb_stat)
if i == 1
intervals = app.comb_stat(i).intervals;
signals = app.comb_stat(i).signals;
else
intervals = unique(horzcat(intervals, app.comb_stat(i).intervals),'stable');
... |
5593a6278d6c7c2050870ce4c77c1ac16ec7254b076791aecfb8471327d98a4c | MATLAB | 12,892 | 311 | function [oData, v] = dataThresh(data, varargin)
% Threshold and manipulate brain data matrices.
%
% [oData, v] = dataThresh(data, ...) thresholds and manipulates brain
% data based on specified parameters. This function allows for the removal
% of positive or negative values, application of p-value thresholds,
... |
630de97c90d7884516582ffe1c65cb222ebb7f0ba55a2e294feb403529824378 | MATLAB | 12,898 | 299 | function [feature_vec, feature_info] = ecg_area_amp_features(data, position, fs)
% function [feature_vec, feature_info] = ecg_area_amp_features(data, position, fs)
% Extract features related to the ECG amplitude and area under the
% curve of different ECG parts.
%
% Inputs:
% data: EC... |
3d35958b7cb0c25ecd52b121b4aee8a1f2e9b564d0d1080bd55d10632220451e | MATLAB | 12,926 | 308 |
%{
----------------------------------------------------------------------------
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... |
a83f1ee6d77b88025da709be4b95b2e19ca2f35524cc54d2c01dd6ef88b49d2f | MATLAB | 12,932 | 235 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
warning(['In the analysis, animals that did not develop a PT and animals that were dead following surgery are removed'...
' and NaN was applied when there was no disease at endpoint.'...
' This is not done in the master file and might e... |
aaa34cfa58581cf2a210dd425aa94ed3c1b98537790f4a9d28f260668819059a | MATLAB | 12,956 | 278 | function Data = Map_Worm_Axes(Data,Plot,Record,Ax)
% This function uses an estimated midline to run a sliding window and find the worm axes.
% It first corrects the estimated midline and then uses it to find the other axes by detecting peaks within each window.
% TODO:
% Add the orientation of rectangles relat... |
7a6436c8bead9d36ae1406fafa5a755450f5f7be2bc2582bbd5ecbf56617fae1 | MATLAB | 12,957 | 352 | function calc_combine_stats(app)
intervals = {[]};
signals = {[]};
anocovas= [];
for i = 1: length(app.comb_stat)
if i == 1
intervals = app.comb_stat(i).intervals;
signals = app.comb_stat(i).signals;
else
intervals = unique(horzcat(intervals, app.comb_stat(i).intervals),'stable');
... |
821c1d1601d867bf89143e3e97ca8e49c9167719a76b802955da92f8b4bd5c84 | MATLAB | 12,962 | 303 | %% Plot all trial types grouped by stim types
% Plot nondrifting unit (at least 4 blocks and the last block is longer than 30 trials)
MouseName = 'EF0151';
MainDir = 'E:\';
seDir = [MainDir, MouseName, '\MSessionExplorer_', MouseName];
seFilePaths = MBrowse.Files(seDir);
for j = 1: length(seFilePaths)
... |
fe278c5a505b603ce441e5d74bb5c4a13f0239238a0f431f137ab035a5554a41 | MATLAB | 12,969 | 236 | %%Prerequest
%combined behavioral and spike data in a single file folder
%
%decoding will take 48.8299 s/cell
%% 1. retrieve data
disp('select brain region folder about combined files');
Folder_region = uigetdir('E:\Wang_combined files\mat\');
FileList_SpikMat = dir(fullfile(Folder_region, '**\*Spike*.mat'));
F... |
dc073c08960de4b795b7bf6b948d4d62b67ba4a4bdf38f19d8d737dc1f1d4f40 | MATLAB | 12,998 | 385 | function varargout = Ragu_ImportIndFeatFromExcel(varargin)
% RAGU_IMPORTINDFEATFROMEXCEL MATLAB code for Ragu_ImportIndFeatFromExcel.fig
% RAGU_IMPORTINDFEATFROMEXCEL, by itself, creates a new RAGU_IMPORTINDFEATFROMEXCEL or raises the existing
% singleton*.
%
% H = RAGU_IMPORTINDFEATFROMEXCEL returns the... |
dd44a3c402f4ecf096eb2fe9f82255b9bcb5ce8f984f7b7b23b5e7b1bdd9b58a | MATLAB | 13,007 | 380 | %{
----------------------------------------------------------------------------
Analyzing behavioral data
At least for the correct rate
----------------------------------------------------------------------------
%}
function Figure1c_Dual_Full_psycho_analysis_230630_all_session
analysis_folder = {
'G:\I... |
94b080d3d9b7cddb14b8a17d395d474d8ec666860ab02013b4d0e5a3189b8938 | MATLAB | 13,011 | 335 | function [gsData]=mnl_4DtoGrayscale(fn,Data,dim)
%[Data,Scale,dim]=mnl_Load4Dimage;
%[Data,dim]=mnl_Load4Dimage_Somas; %Done so I don't use the metadata
%Per Channel
for i=1:dim(3)
for j=1:dim(4)
a=Data(:,:,i,j);
test(:,:,j)=a;
end
Chan(i).Zstack=test;
clear a
end
%Make Each Slice Graysc... |
dbad0204fbf84cf75487fe84db98673177c21cdc083fdc09a010d0f57d1666e6 | MATLAB | 13,017 | 300 | classdef readInData < handle
%This calss will handle different types of data, and present a easy and
%common interface.
properties
par % parameters used, this will be updated with the data readed.
nick_name % name of the file without extension.
with_raw % boolea... |
28952adb79ccf6db4aa35ab56e75c2e34fc534110324e41339b66d1091f224fa | MATLAB | 13,040 | 465 | function RaguShowMSFit(h)
% Copyright 2009-2011 Thomas Koenig
% distributed under the terms of the GNU AFFERO General Public License
out = get(h,'UserData');
figure(h);
if (isfield(out,'strF1'))
strF1 = out.strF1;
else
strF1 = 'Factor 1';
end
if (isfield(out,'strF2'))
strF2 = out.strF2;
else
strF2 =... |
c995a8d3bc9a0c6beb7d9d802c72d5867e67846f222e85c2ab855e374fdaecbe | MATLAB | 13,051 | 264 | function results = correlation_analysis(app)
if ~isempty(app.burst_ints)
tmp =find(vertcat(app.burst_ints.type) == 1);
borders = nan(length(tmp)+1,2);
int_names = {'full interval'};
for i = 1: length(tmp)
borders(i+1,:) = app.burst_ints(tmp(i)).borders;
int_names{i+1... |
c686af4fd66048dabe967dca8d9a62034fe107deaed93d3e20f18daa42961321 | MATLAB | 13,090 | 350 |
%{
----------------------------------------------------------------------------
Determine the time window for task relevant neurons
%Before start of task
%Start of task
%Sound on
%Sound off
%Before choice
%After choice (0sec)
%After choice (1sec)
%After choice (2sec)
%p = 0.001
-------------------------... |
5374c96cc8fe77a58116b54ff5cf2f546b6becaacadce79446bdd480e351d138 | MATLAB | 13,094 | 390 | %%
close all
% clear all
idx_single =[10];
spine = {[1:16]};
idx_sum = 10;
idx_SLM = 1;
branch_no =1;
path = 'E:\data\uncaging\multi cluster cooperation\013123\cell2';
preflix = '230131_001';
clear Vm PC shutter
filename_single = sprintf('%s.single_spine_series_16synapses.%d.wcp',preflix, idx_single(1));
%filename_... |
6debab4ad7a87e97f9bac7ddab3a59aefd2f264301739cebcecc86462e1f7766 | MATLAB | 13,094 | 372 | % plots the final exploratory analyses
clear
clc
close all
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% parameters
Parameters = analysisParameters();
Paths = Parameters.Paths;
Participants = Parameters.Participants;
SessionBlockLabels = {'BL', 'SD'};
CacheDir = fullfile(Paths.Cac... |
4912989a57b799a0a42584d057f1024975519c6a6fc56c486eca6a53b4b3fec4 | MATLAB | 13,100 | 388 | clearvars
close all
badtrls = 0
if badtrls
project_dir = '.\Adults_badtrls\';
else
project_dir = '.\Adults\';
end
EVOKED_results_adults = table({},...
'VariableNames',{'ID'});
EVOKED_results_kids = table({},...
'VariableNames',{'ID'});
conwin = [2.5,3];
extension_T = '';
load([project_... |
4268fd23e488548c9c1e410981d0952c1f08bd286f73ddb7c37c8f2d83d77391 | MATLAB | 13,106 | 327 | %% FourCageDecision_Model
% Applies a Bayesian decision-making model to the 4cage behavioral data in
% order to asses the quality/reliability of different information classes.
% For these experiments, a single animal (gregarious or solitarious) was
% places in a circular arena (d=90cm) with four stimulus cages, placed... |
c1813632665268efabe7d71c0505a0b6e8d80154a652e6e6568da98003d71e49 | MATLAB | 13,117 | 330 | function [X,ndx,dbg] = natsort(X,xpr,varargin) %#ok<*SPERR>
% Alphanumeric / Natural-Order sort the strings in a cell array of strings (1xN char).
%
% (c) 2012 Stephen Cobeldick
%
% Alphanumeric sort of a cell array of strings: sorts by character order
% and also by the values of any numbers that are within the s... |
a9315a29d6d6f60fafe0e3b98a18bbb31d94ef603cbfe912c7cd0624572ac3a1 | MATLAB | 13,118 | 330 | %% plot 6x4 behavior + model data
% Panel A
clear all; clc; close all
conditions2 = {'hon','ion','bon','ccon', 'hof', 'bof'};
load('alldata.mat');
conditions = {'hexon','iaaon','bzaon','citon', 'hexoff_05s', 'bzaoff_05s'};
% onum = [1,2,3,4,1,2]; %which odor to plot the mean for
ylims = [12,12,12,12,12,12];
odo... |
5cab51f10bd0654e3e89d1befe0ac7c7e9f3bde61babbaf3040ff6b832fffedb | MATLAB | 13,132 | 293 | %% 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
%... |
045229b7c2109ff292eaf01cf84379aa5038f56a3d1b7a884f154e716d372bed | MATLAB | 13,164 | 278 | function [corr_achda, lags, shuff_achda] = AK_corrFP(beh, varargin)
%Cross-correlation between ACh and DA photometry signals acquired during
%dual color photometry recordings
%
% [corr_achda, lags] = AK_corrFP(beh)
% [corr_achda, lags] = AK_corrFP(beh, win)
% [corr_achda, lags, shuff_achda, min_val, min_lag... |
a130c4bf165501c19568df6f8b09cce17e2adaefc4adb00d44d293b3d85935bc | MATLAB | 13,201 | 273 | function varargout=findND(X,varargin)
% Find non-zero elements in ND-arrays. Replicates all behavior from find.
%
% The syntax is equivalent to the built-in find, but extended to multi-dimensional input.
%
% The syntax with more than one input is present in the doc for R14 (Matlab 7.0), so R13 (Matlab
% 6.5) is the lat... |
47c1afec722bdfa1c6bf4ac3463ccd33cb6d6024e8a332202e9d6a5fd7b13b6b | MATLAB | 13,204 | 276 | %% recording summary
% zScore, tHit vs. tCR: isResponsive
recSite_total = unique(zScore_all.recSite);
for i = 1:length(recSite_total)
tb = zScore_all(strcmp(zScore_all.recSite, recSite_total{i}), :); % select recording sites
mouse_number = length(unique(tb.MouseName));
session_number = length(unique... |
3d05a1f39ac2489e965ee4fa08d02b08e4b05a17fc61d19f76ac2455ab563c78 | MATLAB | 13,243 | 360 | %% msBatchPC_v4_ZX.m
% This code is used to find four kinds of place cells recorded by miniscope.
% v3: Use data from behav file.
% Compute multiple cells in the same time instead of shuffle.
% Considering that there are more than one calcium imaging recording in one
% session.
%
% v4: intergrate PC analysis into a fun... |
cd54d19e36fafaffdddaef5cde6b8c9fe5c7ac0f65fe923f993db55666dc95f5 | MATLAB | 13,289 | 310 | function [grappaRecon_1DFFT, mOutGRAPPA] = performHostGRAPPArecon_RAMonly(twix_obj, counterStruct, nSliceNeighbours, combinePars, lambda)
%
% function [grappaRecon_1DFFT, mOutGRAPPA] = performHostGRAPPArecon_RAMonly(twix_obj, counterStruct, nSliceNeighbours, combinePars, lambda)
%
% Applies GRAPPA to the host data, whi... |
f256581790a2996492c289ce9145220d8172e0e6765b969cf747efcec8604fef | MATLAB | 13,325 | 282 | %% Correct trials
% tBlock vs. vBlock
% Baseline activity of correct trials in respond-to-touch block vs. respond-to-light blocks
% Chang et al., Fig 2c
% tStim vs. vStim
% Negative controls: baseline activity of correct tactile trials vs. visual trials
% Positive controls: sensory-evoked activity of correct tactile ... |
85d6f1490cff784799704cbcd5296e0ce3f0a81e1b663e4062bcd088d977d2f8 | MATLAB | 13,339 | 340 | function [est,HDI,K]=rst_data_plot(Data,varargin)
% plots the data split by groups showing each data points with the
% distribution and a summary statistics estimator with 95&% Bayes boot HDI
%
% FORMAT: [est,HDI,KDE]= rst_data_plot(Data,options)
% [est,HDI,KDE]= rst_data_plot(Data,'between',0.25,'datascatter'... |
2b9ebf8008d63da99d1c718f93564720ce7e7529a57c829140061957e0ed62e8 | MATLAB | 13,383 | 276 | %function CREx_ERSP_MorletComplex()
%% Script to carry out time-frequency analysis of segmented EEG data.
% The time-frequency analysis is carried out using complex Morlet wavelets.
% The spectral bandwidth is defined by defining the fwhm and the empirical
% fwhm is estimated for each frequency of interest and ex... |
956b15a67b1aee1b45d8751b469e951bb84afddf67211de131d6705d24134aff | MATLAB | 13,408 | 354 | % EEGVR_write2excel()
savedir = cd;
%% Maybe a dialogue box opens in which to mark "Group" and "Session"
test = 1;
while test == 1
prompt_study = {'Task (Mismatch/Passive Listening)'}
dlg_title ='';
deflts = {''};
num_lignes=[1];
studyin = inputdlg(prompt_study,dlg_title,num_lignes,deflts);
... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.