sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
1495f3f43300045162cb8f62123711618fe8407c92238cf0314025629c835eb2 | MATLAB | 14,140 | 333 | function [areas,total_bins,overlap_bins, total_area, overlap_area]=...
interunit_peak_finding_210726(spon,stim, spon_dir, stim_dir, parent_dir,if_cw)
% Testing peak finding capabilities across multiple units for elimination
% of zeros
% Ensure status and tunnel pairs are loaded spon and post stim
% Fixed saving iss... |
8910d8e0dfb1b480fd7f663ea4149a826a3617ed80570e5f64e2211d7344deb5 | MATLAB | 14,177 | 385 |
%% CLEAR AND INITIALIZE
clear;close all;clc;tic;
%% DEFINE THE STRUCTURE THAT WILL HOLD ALL THE PARAMETERS
params = [];
%% DEFINE INPUTS AND OUTPUTS
params.data_folder = 'F:\2022-131\PAVLOV\DATA';
params.analysis_folder = 'F:\2022-131\PAVLOV\Analysis';
params.figure.folder = params.analysis_folder;
%% STEP1 %% ... |
344224c911562191690199b20564d07a106394764ce2d398748704cc6086c17e | MATLAB | 14,203 | 322 | % function cfg = decoding_describe_data(cfg,labelnames,labels,regressor_names,beta_loc,xclass)
%
% This functions creates the link between the file names of regressors
% (e.g. beta_0001.img) and its corresponding label name (e.g. button press),
% label number (e.g. -1 or 1) and decoding step number (e.g. run 1). These
... |
109e4d697b5aaf4604402513faf50ebc0580be5892fc52d907e2029faa174335 | MATLAB | 14,227 | 245 | %% Extended Data Fig. 5h-i: Spearman correlation between features of baseline activity
% and relative post-stim propagative event frequency in neighboring astrocytes
% Ext. Data Fig. 5h: the feature of baseline activity is baseline propagative
% event rate (# propagative events/30s)
% Ext. D... |
4b772c2ca95cc03699537f037f5d0c758db398d8f44c4824a91bc1319282b010 | MATLAB | 14,228 | 261 | function [Fig, statsOut] = plotCellPropsByAge( Res, area, varargin )
%UNTITLED4 Summary of this function goes here
% Detailed explanation goes here
%% Params
prms.cellType = 'BVC';
prms.ageBins = [16 18; 19 21; 22 25; 26 36; 40 40]; % default: [16 18; 19 21; 22 25; 26 36; 40 40]; [15 18; 19 21; 22 24; 25 2... |
2c8c3dc96d65dd053aefe82e5a8d0e3b8ba6234561eaeeae71be805a0b114ea6 | MATLAB | 14,246 | 469 | function [] = write_to_afni(subj,objtype,objin,sample_filename,varargin)
% Writes an object to a file, using the header info from a specified file.
%
% [] = WRITE_TO_AFNI(SUBJ,OBJTYPE,OBJIN,SAMPLE_FILENAME,...)
%
% Writes an object in subject structure SUBJ, of type
% OBJTYPE to a file. OBJIN specifies the name of the... |
70b1d9c694ff23631d2301fe557224a8df66b631cd833718a86a3ed6e6f4f245 | MATLAB | 14,260 | 371 | % STATUS: outdate.
% use preprocessFNIRS06_CV_GLM_ssBeta_MultiOnly_Version02 instead
%
% SYNTAX:
% preprocessFNIRS06_CV_GLM_ssBeta_MultiOnly(s,numClasses,rejTrOp,rejChnOp,...
% lpFilt)
%
% DESCRIPTION:
% Preprocess raw data (light intensities) and perform cross Validation
% where SS beta coefficients from traini... |
752c78456f2d6d5c8511ae1dd659f3e80e62c7bd8c97f98b24431016a572a991 | MATLAB | 14,281 | 407 | function data = open_doric(filepath,params)
%% argument to enable the plot of debug figures
debug = params.debug;
recording_config = params.recording_config;
%% PARAMETERS START
%remove artifacts from chuncks
artifact_th_high = 10; % MAD
artifact_th_low = 1; % MAD
%PARAMETERS STOP
%% LOAD DORIC DATA
[header, raw_dat... |
13364160e8b95b52d35395e24734b1fb00c7779c4ec52443f48e0d3e8f6a027c | MATLAB | 14,289 | 512 | clear; clc; close all;
NoCol = 1;
datapaths;
FigNums = {'Fig3','FigS2'};
for egunit=1:2
if egunit==1
mouse1 = 26;
unit1 = 118;
IntSel = 60;
MfSel = 16;
elseif egunit==2
mouse1 = 42;
unit1 = 13;
IntSel = 60;
MfSel = 64;
end
FigPathUnit = [FigPath,filesep,FigNums{egunit}];%['B:\AMSali... |
6d2ff7308c505cb9c699c3daec834a635be1cd59262716c45292e774fd0a5107 | MATLAB | 14,327 | 285 | %Parts of figure: S7.
%2024/02/26
%% define directories:
root_dir=define_flicker_root_dir;
source_data=[root_dir '/stg-analyses/NatureComm2024-figures/Source Data']; %where source data for figures is stored
figures_dir=[root_dir '/stg-analyses/NatureComm2024-figures'];
%% fetch data:
all_subjects=fetch_flicker_subjec... |
a197636620ec0f4e469a6d0b6b09d68bc4d9f5c149cdf61561e3568e92caa9ba | MATLAB | 14,341 | 393 | function [b, c, params] = make_bc_fast(signal, spatial_size, options)
% MAKE_BC_FAST Performs a linear polynomial expansion
%
% [b, c] = make_bc_fast(signal, spatial_size, options)
% or
% [b, c, params] = make_bc_fast(signal, spatial_size, options)
%
% Compute b, and c parameters in up to four dimensions. The
% paramet... |
ce66859368e5706adaa65ab6fed182a590790845d7869658dcf606138b2de157 | MATLAB | 14,390 | 413 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Demonstration of Basic Utilities of JSONlab
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
rngstate = rand ('state');
randseed=hex2dec('623F9A9E');
clear data2json json2data
if(exist('isequaln')==0)
isequaln=@iseq... |
ae874cdb63d851016ff752c7634c9d8783a82a7131cd7c7f69ac8c6bd11cb3e2 | MATLAB | 14,402 | 488 | function [errmsgs warnmsgs] = unit_zscore_runs()
% [ERRMSGS WARNMSGS] = UNIT_ZSCORE_RUNS()
%
% This is a script that tests the test_zscore_runs function. It
% does negative and positive tests on the pattern, selectors and
% the actives selectors.
%
% ERRMSGS = cell array holding the error strings
% describing any tes... |
fa10f17e9ba1930acdba657dbf371a47f168016392f077a6ecc5aa6bb2ab64ac | MATLAB | 14,509 | 367 | close all; clear;
addpath('D:\Documents\Software\export_fig')
addpath('D:\Documents\Software\spm12\');
spm('defaults', 'eeg');
cd 'D:\Documents\Data\MELDsimulations\spm_datasets'
resultsSavePath = 'C:\Users\smellor\OneDrive - University College London\UCL\Project\Reading\OPMpapers\MELDsimulations\Figures';
%% Load... |
8b419e3779672338780b2699ed7d2f8b2dac3d060042214389b324a6523b3657 | MATLAB | 14,511 | 384 |
% MakeWhlFile_3spots(fileBase,Session,invertSyncBool,videoRes,nSamplesPerScreen)
%
% Synchronize electrophysiological data, video streams and behavioral events
%
% Inputs
% A .led file, a .spots file, and a .maz file
%
% Outputs
% A .whl file and a .evt file
%
% Required parameters
% fileBase: the (common) base nam... |
84405d9b1278dfce422aae2728933649950fcaf2b033342d664cf838c1bf9724 | MATLAB | 14,520 | 373 | % STATUS: active.
%
% SYNTAX:
% preprocessFNIRS06_CV_GLM_ssBeta_MultiOnly_Version02(s,numClasses,...
% rejTrOp,rejChnOp,lpFilt)
%
% DESCRIPTION:
% Preprocess raw data (light intensities) and perform cross validation
% where SS beta coefficients from training fold is passed to test fold.
% Perform classification us... |
d8d4cce9f8f7fa20b0cdb8b70b121ab7243b2916c7dc00efcab3679e83dc7171 | MATLAB | 14,529 | 424 | classdef FuncRegClass < matlab.mixin.Copyable
properties
userfuncdir
userfuncfiles
entries
type
typeNameIdx
config
logger
end
methods
% ---------------------------------------------------------------------------------... |
fa026e1500a68d03ef812211dcfd95293947b78e5965cae96ae0f6e9aa7a16fe | MATLAB | 14,580 | 307 | function [FigHst, FigRQ, statsOut] = figure4Plots( Res, varargin )
% Analyse distribution of Phi in CCE.
prms.egEnsembles = {}; % {'r345_P20','r315_P21'}; % {'r372_1406018', 'r372_140609'}; % {'r345_P16','r315_P18','r345_P20','r156_P23'};
% Ensemble notes: Adult, r372_140609, t7c7, AC ... |
4ceacb6b382449eb616cbe8d17f2646a15dc849c4b87fc98282e795b76ead7cb | MATLAB | 14,602 | 328 | function vidObj = msAutoSegment2(vidObj, frameLimits, cellAreaLimits, downSamp,corrCoefThreshDefault,plotting)
%MSAUTOSEGMENT2 An serial iterative algorithm for identifying the boundries
%of active neurons.
% vidObj = The Miniscope data structure which contains location of video
% files, bright spot information, an... |
85f6d4cc5210c62347db1dee35bc44f88ae4894783df07722cf28a5ef4f945ab | MATLAB | 14,640 | 399 | %% cue
MaestroPath = 'C:\Users\Owner\Desktop\DATA\albert\';
supPath = 'C:\noga\TD complex spike analysis\Data\albert\pursuit_8_dir_75and25';
load ('C:\noga\TD complex spike analysis\task_info');
req_params.grade = 10;
req_params.cell_type = 'CRB|PC';
req_params.task = 'pursuit_8_dir_75and25';
req_params.ID = 4000:500... |
803e04ee6612a002e7e77410663442f30c072ca5907dbff04a9dc218870cbd91 | MATLAB | 14,698 | 347 | % UNDERSTANDING METRICS
%
% The purpose of this tutorial is to gain a better understanding of
% the different classification and regression metrics in MVPA-Light as well
% as the different types of outputs that classifiers produce.
%
% Contents:
% (1) Classification: Relationship between dvals (decision values), accura... |
f388b7f02564ae42f92dd480f1292d0fffe7547a3a839ffa1b4e4ef75c7abd05 | MATLAB | 14,753 | 316 | classdef Actionpotential < Sharedmethods
%ACTIONPOTENTIAL Action potential object
% Detailed explanation goes here
% ---------------------------------------------------------------------------------------------------------------------
% Author: Thijs Verhoog (thijs.verhoog@gmail.com)
... |
620c8c6f22cdd3bd11e0e83ec80990b4d3c53c7000f9d4c16862568124382af4 | MATLAB | 14,803 | 472 |
%function CueRotPaper_GetSigmoid
% Copyright Adrian Duszkiewicz and Eliott Owczarek 2020-2021
% Sigmoid fitting code incorporates elements of:
% R P (2021). sigm_fit (https://www.mathworks.com/matlabcentral/fileexchange/42641-sigm_fit), MATLAB Central File Exchange. Retrieved June 9, 2021.
clear all
%% Load data
... |
7a979d341fe0fd2cd5619f2e37abdd5e1228df1177c2133f14634bbc93f928f3 | MATLAB | 14,934 | 317 | function [Summary] = CCstepSummary(a, cellname)
ss=load('D:\Morphys\Data\Electrophysiology\SetupSettings\Setupsettings_INF.mat');
ss=ss.obj;
Summary=struct;
if isa(a, 'Abffile') || iscell(a)
if numel(a)==1
sweep=a.getchannel.getin('signal', 'primary').getsweep;
a2=a;
... |
de6bf74c44d1f6e3efa8d77b3d384a92bd4f54454c8eb946cc52167aed6aa941 | MATLAB | 14,992 | 391 | function [h_Fig, h_sp, fit_info] = plotSizeDurPDFScaling(x_reps_str, eta_val, eps_val, tau_val, rep_string, h_Fig, h_sp, data_color, make_subplot)
% Function for plotting size and duration PDF subplots, along with size vs.
% duration scaling plot
% Input strut x_reps_str is loaded from the results directory; provide th... |
200ae97493b5242f8728a6fb6850bde5de5d598a7064ae73b1610ccd95d340a5 | MATLAB | 15,003 | 542 | %% Length FF
region=["EC-DG","DG-CA3","CA3-CA1","CA1-EC"];
regLabel1ff=[];regLabel1fb=[];
set(0,'defaultAxesFontSize',16)
set(0,'defaultAxesTickLength',[0.04,0.08])
set(0,'defaultaxeslinewidth',2)
region=["EC-DG","DG-CA3","CA3-CA1","CA1-EC"];
well_regList={"EC-DG","DG-CA3","CA3-CA1","CA1-EC"};
figOrder=[1 2 4 3];
if ~e... |
ae4212a6e713fb5feb89cb7656c079202eb88e7c420adcedc13c162dd6b1b275 | MATLAB | 15,010 | 405 | classdef ClassificationOutputLayer < nnet.cnn.layer.Layer & nnet.internal.cnn.layer.Externalizable
% ClassificationOutputLayer Classification output layer
%
% To create a classification output layer, use classificationLayer
%
% A classification output layer. This layer is used as the outp... |
c8bce56c5910ba0001a3bd6ff8bbad8b97f07ec61a146932eeb057e00c8a2c3c | MATLAB | 15,020 | 405 | %% Loads and Plots Medians and SE for all IBSR and BD distributions
% Sam Lassers
% Plots median IBSR and BD from loaded variables. Also creates distribution
% based off of the ln transformed data centroids.
%% Load Data
clear
clc
cd("D:\Brewer lab data\HFS\")
%Well
nostim_well_bd=load("nostim_well_BD_5... |
f1cd67d4ad132b84c95ffed6d3f6b30174a58c26ce316474fb3913260b2db833 | MATLAB | 15,101 | 408 | function varargout = markLines(varargin)
% MARKLINES MATLAB code for markLines.fig
% MARKLINES, by itself, creates a new MARKLINES or raises the existing
% singleton*.
%
% H = MARKLINES returns the handle to a new MARKLINES or the handle to
% the existing singleton*.
%
% MARKLINES('CALLBACK',hO... |
4c4660e547d630f832b23c4eae4089e72e7fd6ef6cd58e504a29a792b0e2009b | MATLAB | 15,118 | 312 | %Shows examples of raw LFP, segmented LFP and PSD for given ch and condition.
%Includes parts of panels in figures 1C, 1E, 2A, 2B, S2A, S2B, S3A.
%2024/02/26
%% set directory paths:
root_dir=define_flicker_root_dir;
figures_dir=[root_dir '/stg-analyses/NatureComm2024-figures'];
%% define details of examples, fetch da... |
b44d2b3a877c58143bb773b605ed219b8edf2710f16774937990f51d493e96ba | MATLAB | 15,187 | 362 | %% Figure S3 in Finkel et. al.
% Transition analysis
% After eight trials, a drop of water from the correct response port was released in the 9th trials.
% These block cue trials were no included in the following analysis.
% load data array
load('E:\CM_NeuralActivity_Analysis\Data_array\AllTrials_25bin_noSmoot... |
7509a2e7287609975f50c61ccece29bbc863f16fac0ba3d129ce709c6f872d6a | MATLAB | 15,199 | 440 | % Alex Sel 18/10/18
% Outputs all the trials time-locked to the visual onset, correct and
% incorrect, as coded by last colunm (1 = correct, 2 = incorrect)
function [all_trl_visual, all_trl_decision, all_trls_feed, trl_visual_feed, trl_R_feed, trl_R_feed2, group] = define_epochs_all(cfg,R_trl,rd,data_filtered)
... |
4bd6500369342b127be70de6c9f6251397c3062aaefbf970944d4f573d3fd25a | MATLAB | 15,201 | 454 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [Elements,varargout] = plyread(Path,Str)
%PLYREAD Read a PLY 3D data file.
% [DATA,COMMENTS] = PLYREAD(FILENAME) reads a version 1.0 PLY file
% FILENAME and returns a structure DATA. The fields in this structure
% are defined by the P... |
afc029b5f031332c5ceb8e1132f440e019241a0cf4543bcab588feb9634fef7c | MATLAB | 15,206 | 596 | % Author : Andreas Seas
% Created : 22-10-28
% Edited : 22-10-28
% Descr : generate figure 3 and its subfigures
%% clear slate
close all;clear;clc
%% Inputs
CBcolor = [255, 215, 0]/255;
FMcolor = [255, 0, 0]/255;
CCcolor = [0, 0, 213/255];
% save figs?
savefigs=false;
%% set up the data
[... |
db2ddf8ba3fa92091c3f683e984f0fb217023b57c8da7e586e51d2d9561da161 | MATLAB | 15,236 | 286 | function layer = lstmLayer(numHiddenUnits, nameValueArgs)
%lstmLayer Long Short-Term Memory (LSTM) layer
%
% layer = lstmLayer(numHiddenUnits) creates a Long Short-Term Memory
% layer. numHiddenUnits is the number of hidden units in the layer,
% specified as a positive integer.
%
% layer = lstmLayer(nu... |
a1e3f1d011ddecdc9618c384232119e2e0de5569157f3f1e93728edd80237dd9 | MATLAB | 15,241 | 388 | % STATUS: active.
%
% SYNTAX:
% preprocessFNIRS06_CV_GLM_ssBeta_MultiOnly_Parallel(s,numClasses,...
% rejTrOp,rejChnOp,lpFilt,opIsLocal)
%
% DESCRIPTION:
% Parallel computing version of
% preprocessFNIRS06_CV_GLM_ssBeta_MultiOnly_Version02.m
% Preprocess raw data (light intensities) and perform cross validation... |
6b6f9b256dbb2b1b0a8761402b9c9a5cc8c6ce6022b1f360fb3586ae1e6e984c | MATLAB | 15,304 | 272 | %% Fig 1d and Extended Data Fig. 1f: Scatter plots of event features color-coded by onset latency
% For a flexible number of conditions, features to plot on x & y and
% flexible number of treatment levels (if provided)
% modified from 'AllTS_Area_Duration_Amp_aggregated_20191031_NoReg_raincloudCDF.m'
%
% 1. Load ... |
99b0529e33c60ea2280be62018bd69cea41ef8ee6d92d8bb77f297f6fd20024a | MATLAB | 15,346 | 632 | function Duszkiewicz2024_Figure_SingleRec_IsomapWake
% This script reporoduces panels from:
% Figure 7, Extended Data Figure 10
% Run in folder A3706-200313 to reproduce the manuscript figure
% Dependencies:
% TStoolbox
% CircStat toolbox
% TODO: script dependencies, links to external functions
% Copyright (C) 202... |
1d3afdc317ad3dcb2da7c00f204b3feba7d60fea02682e32c7ad4d6606d4fc90 | MATLAB | 15,361 | 395 | % This function was used for PFC vs. RE decoding analysis
function mPFC_RE_decoding
% listed are example files for illustration only
folder_name_pfc={
'20161218#47', [1,5,9,13],[17,21,25,29];
'20161220#44', [1,5,9,13],[16,24,28];
};
folder_name_re={
'20180325#4',[1,5,9,13,17,21,25],[]; %re... |
e76ef5f0f938389bdf741fe537df4985575b3e2cada2e8f70639ccf8db5c9af4 | MATLAB | 15,368 | 280 | %% Extended Data Fig. 7b: Distance of neighboring astrocytes from the uncaging site
% Distance of active neighboring astrocytes from the uncaging site (neighboring cells that have at least 1 AQuA event within PostStimActivityWindow)
% Exclude uncaging cell and ramping cells
% Measures distance (in um) from the cente... |
503cc2a63e37917c50fab80bb60818c8b4db424d0e543bff05ce489aef6bc73b | MATLAB | 15,397 | 347 | %% Analysis script
% Written by D.B. Heyer
close all, clear all
%% Set path to load and save data
basedir = 'D:\Morphys\Data\Labbooks\RWS\ConnectivityRene' ;
%basedir = 'C:\Users\DBHeyer\Documents\PhD\Human Database\Morphys\Data\Labbooks\MBV\MetadataCSVs' ;
savename = 'CellSummary_ConnectivityRene';
%% import CSV fil... |
dfbe3296392f6c2cc5e02a495aefde2d82bbc194c1f60f88c812c7259ecef85f | MATLAB | 15,425 | 385 | classdef SequenceInputLayerClass < nnet.cnn.layer.Layer & nnet.internal.cnn.layer.Externalizable & ...
nnet.cnn.layer.mixin.NormalizableInput & ...
nnet.internal.cnn.layer.Summarizable
% SequenceInputLayer Sequence input layer
%
% To create a sequence input layer, use sequenceInputL... |
43cebff9fa6f001f8470b89d12e67ce550120cfebc19832d88ff49fcf2681adc | MATLAB | 15,468 | 317 | function layer = sequenceInputLayer(inputSize,nameValueArgs)
% sequenceInputLayer Sequence input layer
%
% layer = sequenceInputLayer(inputSize) defines a sequence input layer.
% inputSize is the size of the input sequence at each time step,
% specified as a positive integer or vector of positive integers.... |
b40e761cd6e3b86b1afcdb055f78f2abdfc6b4099024ac52d15dae9c00e78f07 | MATLAB | 15,509 | 257 | %% Fig. 3b, right (overlay): representative spatial heatmap showing the
% change in the number of active frames/ px (post - pre). Using all events
% 150s pre- and post-stim within the field-of-view. If landmarks were
% drawn in AQuA, these can be drawn on top of the heatmaps.
%
% Modified from SpatialHeatMap... |
9bce4eaef8942dc507e5fe3565a8ae2faf49dc7152182b222cc6fb5e8cee096f | MATLAB | 15,512 | 395 | % split into single and multi groups.
% new. Use trials from dcNew var
% option to re-run training and classifying or pull from saved data
% sbjList is cell array of experiment "number". Ex: sbjList = {'01','02'};
% sbjList = {'08','10','12','13','14','15'};tInd = 8;featureName = 'Cumulative Sum';numRept = 5;numClasses... |
62aea6560e624842685731840243ff9f56f49175ba1e1a823c042eab6b4b50c2 | MATLAB | 15,519 | 553 | % tCFS_E3_figure4_dBdiff
% job=[];
% job.concatGFX= 1;
% job.plotPFX=0;
job.plotGFX=1;
job.compareFits=1;
job.plotGFX_oscillator=1;
% plotType==1; % as per other MS figure
%% set up some directories.
% homedir = 'C:\Users\mdav0285\OneDrive - The University of Sydney (Staff)\Desktop\tracking-CFS';
homedir= '/Users/ma... |
f9ded36cb81b02aa4684f908a54c3768051f377f1c968a475fa9885835ad741b | MATLAB | 15,529 | 337 | %% Update 4/25/22: updated to have sliding time step
% added non uniform time scale
clear
clc
% outfolder = "D:\Brewer lab data\HFS\Temporal Analysis\40 HFS\AFR Output";
load("D:\Brewer lab data\HFS\Temporal Analysis\40 HFS\dataInfo.mat")
outfolder = "D:\Brewer lab data\HFS\Temporal Analysis\40 HFS\AFR Output Full Inde... |
847ef1f83f0c34401674c502b52470fdfd6e55d92ba17d645ee5f72600a5b80d | MATLAB | 15,583 | 388 | % 1. Add the path of the current script to the search path
% 2. Change the current folder to "Fig2 PFstimulation_stimulus dependence"
% 3. analyze the data within the folder
% 4. Using ctrl+enter within each function to run each section
%% Section 1: Open files
% 1. ctrl+enter to run this section
% 2. Select "y... |
371c83c6ad9b8e0ca1dc0d7dd13dfa67103f41f2e57ed1f2c498db8809d393fc | MATLAB | 15,623 | 341 | function [hdr,vol] = minc_read(file_name,opt)
% Read a MINC file http://en.wikibooks.org/wiki/MINC
%
% [HDR,VOL] = MINC_READ(FILE_NAME,OPT)
%
% FILE_NAME (string) the name of a minc file.
% HDR
% FILE_NAME (empty string '') name of the file currently associated with the
% header.
% TYPE (string) the file for... |
9364eab5d61c2a71807648bb9e9e5c9d135cd3a2daf89a4e2187fb859042af90 | MATLAB | 15,715 | 220 | %% Extended Data Fig. 7: Prepare the data struct for calculating the change in event frequency post-uncaging
% Bin events into static time bins of chosen duration
% From Aggregate_MC_ftsFiler_MultCond_XSecBins_20220524.m
% This is similar to Section E of Fig2_3_PreppingDataStruct.m
% modified 20220524 to change... |
951b7de8ca719dc08cfe19f7156dd856561f2c417d8b34abc95427169c267dea | MATLAB | 15,753 | 334 | function [sync1,sync2] = DisplaySYNC4(sync1,sync2,nSamplesPerScreen)
AFdeletedspots = [];
AFaddedspots = [];
% Align first nSamplesPerScreen samples
if nargin < 3,
nSamplesPerScreen = 100;
end
nSamplesPerScreen = min([nSamplesPerScreen length(sync1) length(sync2)]);
ratio = (sync1(nSamplesPerScreen)-sync1(1))/(s... |
95bfb7ff97c27d8558c15156d58f716fca1a8ba6e263f7b0dfc703e5a6e24931 | MATLAB | 15,899 | 599 | function Duszkiewicz2024_Figure_GainSimulation
% This script reporoduces panels from:
% Extended Data Figure 8
% Dependencies:
% Copyright (C) 2023 by Adrian Duszkiewicz and Adrien Peyrache
%
% This program is free software; you can redistribute it and/or modify
% it under the terms of the GNU General Public Licen... |
a3a0d61ac6925788c7d8f98da371468d981386fe46d218b759b81739ae7ab9b2 | MATLAB | 15,935 | 510 | % 1. Place this code in the data folder of
% "Fig5 Dendrite-Soma-AIS simultaneous recording"
% 2. ctrl+enter to run each section
%% Section 1: Open files
% Select all file in the subfolders Dendrite, Soma, and then AIS
% within the folder of "Fig5 Dendrite-Soma-AIS simultaneous recording"
% ctrl+enter to run... |
1dca36a83755c0077264bd9ce08c7f384ff8d6fc947c99cc197ab59c7323d255 | MATLAB | 15,967 | 356 | % Status: Inactive
%
% split into single and multi groups.
% new. Use trials from dcNew var
% Plot bar chart by channel using ROI names.
% Use this one.
function calcCumSumUpdateDCNew_BarChart_ChnName(sbjNum,numClasses)
% channels pruned stored in mlActAuto var
processedDataDir = ['C:\Users\mn0mn\Documents\ResearchPr... |
ccd41fe1f185b1284559f28ce5c86b9e2c56ca95ad958d82e033b8ab5b6658ed | MATLAB | 15,991 | 346 | %% Make Flow Figure Images
function FlowFigureImages(fileParams, flowFigureImageParams)
%% Start FlowFigureImages Script
fprintf('\n\n- - - Starting FlowFigureImages - - -\n\n');
%% File Parameters
exportFolder = fileParams.exportFolder;
%% Flow Figure Parameters
frameNum = flowFigureImageParams.frameNum;
%% Define ... |
fbd8a2d728b9406719d68f9a0f44762a907bc2656add226e872340a01ff3e224 | MATLAB | 16,005 | 421 | % UNDERSTANDING PREPROCESSING
%
% In this example we look into preprocessing pipelines. Preprocessing
% includes demeaning, z-scoring, PCA, sample averaging, feature
% extraction methods such as PCA, and any other
% approaches that operate on the data prior to training.
%
% An important distinction is between what wi... |
c2c0469abd865828c5d76a799de2a2bc36cb039c7484b73fa70975cb9e80a281 | MATLAB | 16,009 | 397 | % GETTING STARTED WITH REGRESSION
%
% This is the go-to tutorial if you are new to the toolbox and want to
% get started with regression. It covers the following topics:
%
% (1) Loading example data
% (2) Regression with cross-validation and explanation of the cfg struct
% (3) Plotting results
% (4) Compare Ridge, Ker... |
109556d7658a9b68ee7db12884f9e13e2f053713b5a0294b34cd3802771e3a54 | MATLAB | 16,079 | 315 | % This script is an example on how to perform a searchlight decoding
% analysis on brain image data. It is combined with a tutorial.
%
% Every decoding analysis needs a cfg structure as input. This structure
% contains all information necessary to perform a decoding analysis. All
% values that you don't set are a... |
08d8f513205c2e8c9ed6404554365a6765d2478b9c0ebe75e8cb1f6f28f204d3 | MATLAB | 16,123 | 443 | % [ wave, f, t, coh, phases, raw, coi, scale, period, scalef ] = getWavelet( x, Fs, fMin, fMax, nbins, mother, scaling, graphics )
%
% [ wave, f, t, coh, phases, raw, coi, scale, period, scalef ] = getWavelet( x, Fs, fMin, fMax, nbins, scaling, graphics )
%
% x:
% vector - wavelet analysis is applied
% multi-co... |
dd736ff9b10d6a291ba8b440ca1b7f42f1c2a44761511948d3cda92e0d0b593d | MATLAB | 16,130 | 351 | % Bo2026_AmygdalaFIR_create_atlas_object.m
%
% How the data-driven amygdala clusters in
%
% Bo, K., Lindquist, M. A., Gianaros, P. J., & Wager, T. D. (2026).
% Spatiotemporal dissociation of human amygdala response to negative
% affect. bioRxiv. doi:10.64898/2026.08.18.745530
%
% were made, and the script that wr... |
fc536050bb846b2fe56f99170e9b1cfd7c779426cd33f4f59d6af3bd6923b969 | MATLAB | 16,145 | 372 | % split into single and multi groups.
% new. Use trials from dcNew var
% Use different method of concatenating to validate the code in
% calcCumSumUpdateDCNew.m
function calcSlopeValueUpdateDCNew(sbjNum,numClasses)
% channels pruned stored in mlActAuto var
processedDataDir = ['C:\Users\mn0mn\Documents\ResearchProjects... |
883a5c2a48ea28686ce175081bf7f48a5917cf959719622abc73d4fac0a47d3f | MATLAB | 16,191 | 465 | % 1. Add the path of the current script to the search path
% 2. Change the current folder to "Fig2 PFstimulation_stimulus dependence\WT",
% "Fig2 PFstimulation_stimulus dependence\L7SK2", or "Fig2 PFstimulation_stimulus dependence\CaMKII"
% 3. Using ctrl+enter within each function to run each section
%% Secti... |
24a3fc2ccde5f793f83b1ec9bcf14e85049502357b3c11d5c0ebb6ec956e3b94 | MATLAB | 16,293 | 449 | function [gamma_fit, gamma_range, minS_gamma_fit, minS_gamma_range] = fitGammaRange(dur_bins, ave_sizes, plot_diagnostics, plot_name)
% Function for adaptively fitting the size ~ duration scaling curve
% Input strut x_reps_str is loaded from the results directory; provide the
% desired parameter values through eta_val,... |
c142247af6e6d4587d0943918482451b0697ef83029ac161a144369f3ad2c5d1 | MATLAB | 16,393 | 360 | %% PT condition
% Load all Can See condition data in a matrix freq x time x channel x subjects
for sub = 1:length(subject_list)
subject = subject_list{sub};
load([TFR_Data subject, '_tf_data_' int2str(1)])
% initialize matrices on 1st subject
if sub == 1
tf_all_PT_Can = zeros([size... |
8fffe811413ef03b1a8392e425694c83c5488bdba96f994d48fea8ded165462f | MATLAB | 16,556 | 487 | function varargout = SLMPhaseMaskMakerCUDA3D(varargin)
% Lloyd Russell 2015
% Implements a weighted GS algorithm using Martin Persson's HOTlab DLL
% (https://github.com/MartinPersson/HOTlab)
% Parameters
% =========================================================================
% None : open a load file GUI
%... |
723d92d60cc345c8614f916cd11e325352e7bd2502a0b03bf472135c89cf6dcb | MATLAB | 16,583 | 458 | function [label, center, bCon, sumD, D] = litekmeans(X, k, varargin)
%LITEKMEANS K-means clustering, accelerated by matlab matrix operations.
%
% label = LITEKMEANS(X, K) partitions the points in the N-by-P data matrix
% X into K clusters. This partition minimizes the sum, over all
% clusters, of the within... |
dcb412941ff8d2828968da428fdf3ce43fe8cc5a8a3057f5603b11c0816d131e | MATLAB | 16,617 | 427 | % STATUS: experimental.
% Not for publication
%
% SYNTAX:
% preprocessFNIRS06_CV_GLM_ssBeta_MultiOnly_Peripheral(s,numClasses,...
% rejTrOp,rejChnOp,cond)
%
% DESCRIPTION:
% Compare left vs center, right vs center, center vs peripheral.
% Only IPS
% Preprocess raw data (light intensities) and perform cross Validati... |
464a06519550e218be5c2c5f1fab6c02345c674d2f26f8397b5ac739979b1c51 | MATLAB | 16,624 | 542 | function demprgp(action);
%DEMPRGP Demonstrate sampling from a Gaussian Process prior.
%
% Description
% This function plots the functions represented by a Gaussian Process
% model. The hyperparameter values can be adjusted on a linear scale
% using the sliders (though the exponential of the parameters is used
% in th... |
f918a49662a9d5e98956f513444a9af2fff2d24a94fa7f6634a135f8613178a3 | MATLAB | 16,686 | 462 | % split into single and multi groups.
% new. Use trials from dcNew var
% option to re-run training and classifying or pull from saved data
% sbjList is cell array of experiment "number". Ex: sbjList = {'01','02'};
% Group by subject instead of channel.
%sbjList = {'08','10','12','13','14','15'};tInd = 8;featureName = '... |
18fdc0b1dbc78114c059c9f26e3eb8de7040a5bbbec40ecb5c67c0ce2f2636fc | MATLAB | 16,722 | 466 | function [success,message] = xlsappend(file,data,sheet)
% XLSAPPEND Stores numeric array or cell array to the end of specified Excel sheet.
%
% REQUIRES ONLY ONE CALL TO THE EXCEL ACTXSERVER, so the overhead is less
% than for successive xlsread/xlswrite calls.
%
% [SUCCESS,MESSAGE]=XLSAPPEND(FILE,ARRAY,SHEET... |
e60e8a14b35e16b8f8c10636e61c6610e73c85ac8d62619e31dbc2d3ad79a739 | MATLAB | 16,745 | 415 | classdef FullyConnectedLayerClass < nnet.cnn.layer.Layer & nnet.internal.cnn.layer.Externalizable
% FullyConnectedLayer Fully connected layer
%
% To create a fully connected layer, use fullyConnectedLayer
%
% A fully connected layer. This layer has weight and bias parameters
% that... |
3eec2f98803921ecab475c93fa86d4de790d0bfc8f4977bcfad0f0d947dcac0a | MATLAB | 16,759 | 493 | %% Plot PC activity during VORD and cancellation
function [fH_canc_pop, fH_vord, fH_canc, fH_vord_split, fH_canc_split, fH_traces] =...
plotCancellationPopSeparate(I, K1, K2, K0, pop, B, S)
% [fH_vor_pop, fH_canc_pop, fH_vord, fH_canc, fH_vord_split, fH_canc_split, fH_traces] =...
% plotCancellationPop(I, K1,... |
0dfa5167c3a88c11a07b3b62341b6e81c7c3b2f556467746766ef58c2db44c7f | MATLAB | 16,963 | 480 | function this = primarySleepSense(this)
%PRIMARYSLEEPSENSE Estimate primary sleep window on an ACTI object
%
% Ref. [1] Crespo et al. Med Biol Eng Comput 2012. PMID: 22382991
%
% Parameter setting:
% SleepInfo.Option = 'Estimate'
% SleepInfo.ModeParameter.Prim = ...
% .zeta Max valid con... |
2973c3f247fc73d3f936113b2a9444cfe937becffe83a582aec4db95a868c0db | MATLAB | 16,980 | 348 | function step1=analysis_step2(step1)
%% LOADING REQUIERED DATA
tsvfilename = [step1.data.folder filesep step1.session.prefix '.tsv'];
boris_data = boris_tools.load_boris_aggregated_data(tsvfilename,step1.dio3.raising_times);
boris_data = boris_tools.rename_roman_events(boris_data);
%% PARAMETERS
%%before_msec = step1... |
0cc213a652c8938168dd54c38f99ee02dfe295907c0c1a0aafe7f5e1232305e4 | MATLAB | 16,989 | 530 | function plot_vMMM_all(performance, id, meth, save_flag)
% _
% Estimation of von Mises mixture model for random dot kinematogram data.
%
% written by Joram Soch <joram.soch@bccn-berlin.de>, 07/08/2018, 15:10 (V1)
% edited by Joram Soch <joram.soch@bccn-berlin.de>, 06/04/2020, 22:30 (V5)
% edited by Felix Töpfer <felix.... |
e30e82e90c06c4b6a73dd8d1e07bc3f8dbfc8ae1aa691a668d3b96f45bfd269d | MATLAB | 17,049 | 293 | %Parts of figure: S4.
%2024/02/26
%% set directories:
root_dir=define_flicker_root_dir;
source_data=[root_dir '/stg-analyses/NatureComm2024-figures/Source Data']; %where source data for figures is stored
figures_dir=[root_dir '/stg-analyses/NatureComm2024-figures'];
%% fetch data:
[~,all_sessions]=fetch_flicker_subj... |
8c8d198bf97e081c590618ddbe68a0868604b68d25472f1fb83c28d79aa40a20 | MATLAB | 17,099 | 525 | function varargout = ProcStreamOptionsGUI(varargin)
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @ProcStreamOptionsGUI_OpeningFcn, ...
'gui_OutputFcn', @ProcStreamOptionsGUI_Output... |
8ffb60664fac528cd5ce5bcb8e5e0805af04cc77019881e168c8df3c5ee1e347 | MATLAB | 17,136 | 533 | function [h info] = view_pattern_overlay(subj, underlay, overlay, varargin)
% VIEW_PATTERN_OVERLAY - Overlays one pattern/mask onto another. (ie., montage)
%
% Usage:
% h = view_pattern_overlay(subj, underlay, overlay, ...)
% [h info] = view_pattern_overlay(subj, underlay, overlay, ...)
%
% VIEW_PATTERN_OVERLAY will ... |
78ca462d5787f07ecf9b1f73c30fa797101d1e9e58945a542c6a00f52bf7ecf1 | MATLAB | 17,162 | 436 | function remove_and_add_neurons(data, neurons_cleaning, outputpath, inversion)
% click on a neuron to delete it and then click on save to permanently
% remove it from the sets of tracked spots
% click on button to add neuron and then save to check the resulting track
addpath('./Functions/');
% GUI Initializat... |
7b3f3f14646d9bf2b6a56b84f3018de2e7e44c64d4be1f891af676e537bb9f46 | MATLAB | 17,174 | 368 | classdef Actionpotential < Sharedmethods
%ACTIONPOTENTIAL Action potential object
% Detailed explanation goes here
% ---------------------------------------------------------------------------------------------------------------------
% Author: Thijs Verhoog (thijs.verhoog@gmail.com)
... |
608c39dece3aea4f3d092f71c9ac6842b82a35c19061067655bd5973f01a54f4 | MATLAB | 17,225 | 494 | function [err, V, Info, ErrMessage] = BrikLoad (BrikName, param1, param2)
%
% OLD USAGE for backward compatibility, see New Usage
%
% [err, V, Info, ErrMessage] = BrikLoad (BrikName, [form], [MachineFormat])
% or
% [V,Info] = BrikLoad (BrikName, [form], [MachineFormat])
% or
% [V] = BrikLoad (BrikName, [form], [... |
0a6a0d70b046f2d2cc0d6c6d00c3b2ee7e0934b28b1a878c996acc0af5c05a96 | MATLAB | 17,268 | 371 | classdef LSTMLayerClass < nnet.cnn.layer.BaseLSTMLayer
%LSTMLayer Long Short-Term Memory (LSTM) layer
%
% To create an LSTM layer, use lstmLayer.
%
% LSTMLayer properties:
% Name - Name of the layer.
% InputSize - Input... |
3ca37950e45e3dbdcd9b6166949072dc8bf6707f6c14ed77dfe3d670aae4a9f7 | MATLAB | 17,365 | 205 | %Segment flicker trials into 2-pulse trials.
%2024/02/26
function [conditionIndex,result]=converttimestamps3(trials,field,numberCycles,repeatCycles)
%create index of conditions:
conditionIndex={'5.5Hz-Baseline' '40Hz-Baseline' '80Hz-Baseline' ...
'5.5Hz-RV' '5.5Hz-RAV' '5.5Hz-RA' ...
'4... |
4410dd7d7a9e27ff98fae9fe0b2d4f1ef9bdde88e1b0d8c5c5930faf519e1986 | MATLAB | 17,370 | 446 | % STATUS: experimental.
% Not for publication
%
% SYNTAX:
% preprocessFNIRS06_CV_GLM_ssBeta_Peripheral(s,numClasses,...
% rejTrOp,rejChnOp,cond)
%
% DESCRIPTION:
% Compare left vs center, right vs center, center vs peripheral.
% Only IPS
% Preprocess raw data (light intensities) and perform cross Validation
% wher... |
79324c7bf709236ae8a2f2c9520eca2398aaaf9e38937784949dc31bdb1c00d4 | MATLAB | 17,546 | 394 | function [qrs_amp_raw,qrs_i_raw,delay]=pan_tom(ecg,fs,gr)
%% function [qrs_amp_raw,qrs_i_raw,delay]=pan_tompkin(ecg,fs)
% Complete implementation of Pan-Tompkins algorithm
%% Inputs
% ecg : raw ecg vector signal 1d signal
% fs : sampling frequency e.g. 200Hz, 400Hz and etc
% gr : flag to plot or not plot (set... |
24d9655684475f26b626c51b141baf9e479746c6a241939dca28fac9a4c7502d | MATLAB | 17,623 | 554 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Pre-proceessing for OPM-SIM data
% by Reto Fiolka, 09.09.2021
%
% -Allow redo of cross-correlation matching
% -Allow random starting timepoint, and estimate for that
% timepoint correla... |
7e5ecea2d6c4bc9497b45e5fca5b34981f2ccde0883e139f781793185f4611cf | MATLAB | 17,625 | 359 | function RUN_MODEL(savename)
% RUN_MODEL Fit of closed loop model parameters to visual and vestibular data
% RUN_MODEL(filepathname) runs all feedback strengths: 0, 0.1, ... 1 and
% stores the results in the folder filepathname within results
% RUN_MODEL(FILEPATHNAME, FEEDBACKS) runs the specified strengths
% (... |
cb6793fa293e39698a74790a44ef46ee1be1f87bcf628e391a77bea32230cc8d | MATLAB | 17,750 | 478 | function [err, ErrMessage, Info] = WriteBrik (M, Info, Opt)
%
% [err, ErrMessage, Info] = WriteBrik (M, Info, Opt)
%
%Purpose:
%
% Writes a data vector or matrix in AFNI's format
% Also write data in AFNI's 1D file format
%
%Input Parameters:
% M is the brick data (in vector or matrix format)
% for 1D... |
f0b07df2abd42b36ca7e671aac2990736a871893a41b7e5d643f28d002c9a3b0 | MATLAB | 17,858 | 495 | classdef ProcInputClass < handle
%
% ProcInputClass stores processing stream input parameters that are independent
% of acquisition data or is derived from acquisition data but not stored there.
%
properties
tIncMan; % Manually included/excluded time points
mlActMan... |
8474969785717d5f57f655dd4f00115d2d3bc7f70d0f9d8afd88a074fe09c66c | MATLAB | 17,902 | 562 | % RPROP Unconstrained local minimization using Rprop
% [X,E,EXITFLAG,STATS] = RPROP(FUNCGRAD,X0,PARAMETERS,VARARGIN) Minimize a
% function FUNCGRAD starting from the parameters X0. Optionally a
% structure PARAMETERS can be used to override the default parameters.
% Each additional parameter VARARGIN will be pa... |
05fc84f9e700a75e71bdbbc1b446c10cab49730656b860cfcdf432b9844b76d9 | MATLAB | 17,946 | 366 | classdef Spike2Channel < Sharedmethods
%Channel Object describing amplifier channel
% Each amplifier channel has analog outputs and analog inputs. Here, the mapping of these inputs and outputs onto the
% BNCs of the axon digidata is specified. Also contains the lists of corresponding Analogin and Analog... |
91690ea6361e419debd3f44f981011c1eb28cee533f0dadad05b77640c19e5dc | MATLAB | 17,951 | 665 | function result = query(BIDS, query, varargin)
%
% Queries a directory structure formatted according to the BIDS standard
%
% USAGE::
%
% result = bids.query(BIDS, query, filter)
%
% :param BIDS: BIDS directory name or BIDS structure (from bids.layout)
% :type BIDS: structure or char
%
% :param... |
8a2f2915bde69fcafda2d8dde3f0422d02947b2cefd7af20f339d086edb087fc | MATLAB | 18,076 | 308 | function [bvcMap] = makeBVCMap_v2( dist, phi, mapSize, barrStr, barrCirc, binSize, tuning, varargin )
% Make BVC map, v2: barriers specified as vectors, represented at high spatial sampling frequency.
%
% Two ways to use. (1) Model map way (this is the normal way):
%
% bvcMap = makeBVCMap_v2( dist, phi, mapS... |
79d82f03bda6a7d60576eb8c733d65fc354723e9a291baeb4797d71e61980460 | MATLAB | 18,082 | 484 | function [err,FigHndls] = DispIVSurf (NodeList,FaceSetList,UsedNodeSet,ITvect,FigHandle,DispOpt)
%
% [err,FigHndls] = DispIVSurf (NodeList,FaceSetList,UsedNodeSet,ITvect,FigHandle,[DispOpt])
%
% NodeList is a Nx3 matrix containing the node index and the
% XYZ coordinates of each of the N nodes that form the surface m... |
28a744a7a891a89f4817ed602b1f1f00481a7b2c172c6c68ea2bf4220d2d2759 | MATLAB | 18,116 | 415 | function [n_best P_best V C]=fast_oopsi(F,V,P)
% this function solves the following optimization problem:
% (*) n_best = argmax_{n >= 0} P(n | F)
% which is a MAP estimate for the most likely spike train given the
% fluorescence signal. given the model:
%
% <latex>
% \begin{align}
% C_t &= \gamma*C_{t-1} + n_t, \qquad... |
637cee07fb3fee36d9a16004a6ed5bfc5e78ba990f8400615c8baf35a8feab62 | MATLAB | 18,127 | 356 | classdef NWBfile < Sharedpaths & Sharedmethods
% NWBfile:
% This uses matlab's built in hdf5 functions to load electrophysiology data from a
% NWB file (Neurodata Without Borders, see https://neurodatawithoutborders.github.io/)
% -----------------------------------------------------------... |
9413be6b6e3c666cdcb021fbbc2ea021581cd8d759ca2463fd238ee4b53a1d0b | MATLAB | 18,173 | 344 | %% Comparison_Spontaneous_Stimulated_data
% Sam Lassers
% Uses inputs from h5 MCS files in order to perform a t test and linear
% regression. Input directories with h5 files converted from spontaneous
% and stimulated data sets from MCS.
% Change log starting 6/2/21 because this has gotten software sized
% added scali... |
154d7692e0da2db6cd14a113b739766d5acde0970dad7e1e670dc5ca2599e826 | MATLAB | 18,209 | 607 | function BEH_analysis_regression(dir,fin,model)
%load raw data
load(sprintf('BEHdata-%s.mat',fin),'BEHdata')
%load summary data
load(sprintf('BEHsummary-%s.mat',fin),'BEHsummary')
% load parameter fits
load(fullfile(dir.dir_fits,strcat('fit-', model, '-', fin, '.mat')),'results');
%load simulated variables
load(ful... |
027a376364800860e1b06743dde6b34958d513158352e5821551210fa213b9fb | MATLAB | 18,267 | 720 |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Projective Oblique Structured illumination Microscopy processing
%
% -edge mirroring added
% -Unmixing at native resolution, then upsampling via zero
% ... |
bb5f3a346a9d79011897e695e9616440fe1d72f270c51a9d3d5a164b1eec58f0 | MATLAB | 18,315 | 420 | function identification_step(data,neurons_cleaned,outputpath,voxel_size)
%
addpath('./Functions/');
% variables initialization
timepoint = 1;
slice = 1;
selection=[];
assigning=0;
% directions=[];
chosen_point=[];
clicked_id_to_assign=[];
if nargin<4
voxel_size=[0.267 0.267 2];
end
zratio=voxel... |
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