sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
a3cc43756147ca068711163c2fc7366f2e609a9b6b03043f3cc7f1451b9265a2 | MATLAB | 15,987 | 330 | function [EEG,com]=pop_marks_select_data(EEG,infotype,indexes,varargin)
com = ''; % this initialization ensure that the function will return something
% if the user press the cancel button
% display help if not enough arguments
% ------------------------------------
if nargin < 1
help pop_mark... |
3c408f1313c6e76b9017da198b938664479098e923d86a81af2d1f909bfdce76 | MATLAB | 16,030 | 551 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
%% viz between-subjects distances
%
% filename = [ DD_INTERM '/species_treesim.mat' ] ;
% spsim = load(filename) ;
%% read in outlier info
filename = [ DD_INTERM '/run1_divergences_n... |
e6e6116f1581c5c5be60eda4cf78cc69281ec04a10ca52ab3490b534a9de977a | MATLAB | 16,083 | 502 | function Figure_SI_KymographSensitivity()
% Analysis of visoelastic 1D domain with nelem elements
% Chooses apporach b) from following two possible extensions for 1 elements:
% a) Elemental equilibrium (internal viscosity): for each element [x_1^e x_2^e]
% f=k1*(l^e-l0^e)+k2*(l^e-L^e)+eta*\dot l^e
% x_1^e=x_... |
b59739c92a2b3033da5927291fafcf038e63a311faa60bd434842748fff30a06 | MATLAB | 16,154 | 588 | clear
%% Fig. 1A
%% power specturm on every point
% rsData is the spatial resized voltage signals
% cortexMask is also spatial resized, cortexMask==1 means inside the cortex
explabel={[2,18],[2,7],[1,3],[1,3],[1,6]};
path={'2017 APR 19 publish','2018Feb 04 M2553M publish','2018Feb 04 M2555M publish','2018Feb 04 M2556M ... |
b804667c1b13640960caee3e773a5cc8fba93be919a6284d2ba0b7a269d6e820 | MATLAB | 16,171 | 351 | % A property grid based on the JIDE grid implementation.
% A graphical user control based on the integrated JIDE PropertyGrid that
% mimics MatLab's property inspector. Unlike the inspector, it supports
% structures, new-style MatLab objects, both with value and handle
% semantics.
%
% The property grid displays... |
5244d3ef4c4608b52c3e85c25e5cdd33a8ef121d3ed25e78633aa30151f96472 | MATLAB | 16,176 | 442 | function [varargout] = MarkovNoJump(s, t, priorpAgB, priorpBgA, method, MemParam, OutPut, AboutFirst,prior_data)
% Ideal Observer that estimates the hidden transition probabilities
% generating the observed outomes.
%
% Usage:
% [MAP, ...
% m_hat, ...
% s_hat, ...
% pmY, ...
% predA, ...
% ... |
051883f5ebfa403efb2ab437f7d7c7cba978cfec4ccb2ccf484b3bc89dc159ba | MATLAB | 16,181 | 440 | function [stats] = plotMUAV1V6meanOpto_ksTest( fullSessionName, tr, aMU1eS, aMU6eS, preT, postT, xlimPl, Fs, msSmooth)
% plots mean MUA psth across channels and makes ks test to find significantly modulated
% channels
% changes from previous version:
% - changed baseline and stimulation period for statistis from 250m... |
9b2e91f29c1e47189bba171b9b0f3c7e0eba57774ba2fc084cdc64427f439293 | MATLAB | 16,199 | 739 |
%%
setUpPaths
for len=1:23
processData
fs=29.133;
NewTime = -1/fs*60:1/fs:1/fs*100;
TIO = NewTime >0.250 & NewTime <1.000;
clear ExpectMeaned Sig fano pStore sCir pStore pStoreTime Estore pStoreTimeError Expectataion
for expect =1:ExpCond
if expect ==1
trials =(RandTr... |
89898f2fffcb76caa58456cf4a2f8eaaaa82d8fe5f95ced7832464186965c3ad | MATLAB | 16,212 | 582 | function varargout = Appetitive_training(varargin)
%
%Appetitive_training({'C:\Users\...*.rcx'},{'Title String'})
%
%This GUI allows a user to hand-train an animal to associate a sound
%with a water reward. Pure tones and broadband noise are both supported.
%Input 1: 1x1 cell array containing the filename of an RPVds ... |
fd5a13d5786badad62d892ba5218b773266848aab01fdf359be1522c4b3754b9 | MATLAB | 16,229 | 351 | function customTemplates = createCustomTemplates(channelInfo,varargin)
%createCustomTemplates creates EEG templates according to user's montage.
% CUSTOMTEMPLATES = createCustomTemplates(channelInfo) returns
% topographic EEG templates for 18 functional brain regions according to
% the channel locations defined ... |
3fb473b5276a731d35f654c1108d3c49d5c08bece3d2f8000cd270a79e94cdb5 | MATLAB | 16,317 | 446 | function varargout = analyzetpstack_previewimage(command, thestackname, thefig, arg4)
debugging = 0;
if nargin==0, % it is a callback
h1 = gcbf;
analyzetpstack_slicelist(gcbo);
return;
end;
if nargin>=3, % then is command w/ fig as 3rd arg
fig = thefig;
ud = get(fig,'userdata');
stackname = get(findo... |
d6e0e8b29d71080d3c41a04c61b1db9eeff1ce5e747e577f8394687df877e136 | MATLAB | 16,352 | 376 | % ERP decoding algorithm for Decoding Toolbox
%Function written by Aaron Simmons (UC Davis)
%Original Algorithm Author: Gi-Yeul Bae (Arizona State University)
function [MVPC, ALLMVPC] = erp_decoding(ALLBEST, nIter, nCrossBlocks, DataTimes,relevantChans,classcoding,equalT,ParWorkers,method,BetaWeights,Tooltype,... |
4cd22e48be98c2ae2bc23b875a1c39842fdbe8fdd76cc2a99a5fa7f894089702 | MATLAB | 16,369 | 448 | %% getModelSetup
% gets the different types of models. By default, uses the cosine tuning model (same dir tuning for sample/test, but different cat tuning)
%
% Directions that are only used in the sample or test stimulus can be specified using the optional fields TaskInfo.Direction_sample and TaskInfo.Directions_test
%... |
a7786c511f676b5f44b0f0abf193e8dace4bfb90c37b4cc03946c1d4b048112d | MATLAB | 16,427 | 636 | function DATA = pp_plot_rasters_AMBehavior_v2(path, subject, session, block, channel, clu)
%
% pp_plot_rasters(subject, session, channel, clu)
% Plots a raster and psth for each unique stimulus. Clu is the label
% given by UMS (not an index), found in Spikes.sorted.labels.
%
% KP, 2016-04; last updated 2016-0... |
b766dea82f3959e80ee46aa726760cf0f5fc7680bab444ea2ef6c952ff25bbcf | MATLAB | 16,490 | 635 | function DATA = pp_plot_rasters_AMBehavior_OnTask(path, subject, session, block, channel, clu)
%
% pp_plot_rasters(subject, session, channel, clu)
% Plots a raster and psth for each unique stimulus. Clu is the label
% given by UMS (not an index), found in Spikes.sorted.labels.
%
% KP, 2016-04; last updated 20... |
290cac700d49e446bbdee07d8fc220b1fb84122ace9963c84a2213ca80e6911d | MATLAB | 16,497 | 630 | function DATA = pp_plot_rasters_AMBehavior_OffTask(path, subject, session, block, channel, clu)
%
% pp_plot_rasters(subject, session, channel, clu)
% Plots a raster and psth for each unique stimulus. Clu is the label
% given by UMS (not an index), found in Spikes.sorted.labels.
%
% KP, 2016-04; last updated 2... |
866697106ca21399b6841f5e940aa7be27d46dd9378027f097b6c84428bb4e5e | MATLAB | 16,544 | 538 | %b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% ERPLAB Toolbox
% Copyright © 2007 The Regents of the University of California
% Created by Javier Lopez-Calderon and Steven Luck
% Center for Mind and Brain, University of California, Davis,
% javlopez@ucdavis.edu, sjluck@ucdavis.edu
%
% This program... |
b8cfa76381ee47196d053c16e4675e235fc49151648a52fc4eebda77bda9bcb1 | MATLAB | 16,550 | 427 | function [stats] = plotMUAV1V6meanOpto_ksTest_MonkeyD_control( fullSessionName, tr, aMU1eS, aMU6eS, preT, postT, xlimPl, Fs, msSmooth)
% plots mean MUA psth across channels and makes ks test to find significantly modulated
% channels for opto control data in MonkeyD
sessionNr = 20573;
mapnames = {'V1_1A'; 'V1_1B... |
e115b0ece3625ed9363709198f55b96fe3870d923fc6919252bc54d14207f692 | MATLAB | 16,557 | 394 | function level20_discrete
try
% Level 8 Noise
% Options:
% Discrete / Continuous
% Spatially separated / collocalized
%
% Spatial separation options:
% Signal(Left) + Noise (Right)
% Signal(Right) + Noise (Left)
% Signal(Both) + Noise (Both)
global DA gf h
% DA: TDT connection structur... |
852506d8abcb8b9ddc79d7bf61464a5f8b6bf6f9ade6449ffd662e1f3de4f4a0 | MATLAB | 16,588 | 404 | %% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Delays__ = {'4s','8s','16s'};
Target = 'LONG';
tlimsAll = [-5 5];
tlimsShort=[-5 6];
tlimsMedium=[-5 10];
tlimsLong=[-5 20];
shift = 0;
plotOnline = false;
bw=0.05;
Nbs = 500;
tbShort=tlimsShort(1):bw:tlimsShort(2);
tbMedium... |
5ddb11ac8ca72a6661cb5e6b15b58bd0fea168a9ecf0ea929b6707ad150bc666 | MATLAB | 16,623 | 459 | classdef Feature < DeepActionProject
%FEATURES Summary of this class goes here
% Detailed explanation goes here
properties
VideoName
Stream
Camera
end
methods
function self = Feature(project, vidName, stream, camera)
self = self@DeepActionProje... |
dc13d578615081d5849a8a7eb7360b5d2166b89a1e94d5fd49ff40f6c8c8293e | MATLAB | 16,625 | 329 | %% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Delays__ = {'4s','8s','16s'};
Target = 'LONG';
tlimsAll = [-5 5];
tlimsShort=[-4 10];
tlimsMedium=[-8 10];
tlimsLong=[-16 10];
tlimsANOVA = [-2 2];
shift = 0;
plotOnline = false;
runCVEdecoder = true;
ResampleTS = true;
ResampleCVE = true;
mi... |
d31cf830c6d6a6c4b42ad5b0534dc331ad44caa22e8724a829ebf5f55b0d4f08 | MATLAB | 16,673 | 611 | function AMRate_Depth_v2
%---Script that analyzes behavior data from AM Rate Detection Task.
%Created 06/23/16 JDY. Initially looking at test data from running myself.
%Updated the scripte do plot psychometric functions on data (03/16/16 JDY).
clear all
close all
clc
%---FLAG---%
Save = 1;
Ephys = 0;
CHL = 0;
CHLE... |
4ba15c693f03198c82beee7822e216fcb2dbdec50ff7621052756d0476e8b5d0 | MATLAB | 16,707 | 485 | %% Demo_008 Pooling Utility
% This demo illustrates the use of psignifits automatic pooling utility.
% For this illustration we use the following, not so handy dataset of a
% Quest run with 400 trials:
data =[...
1.3262 1.0000 1.0000;...
0.8534 1.0000 1.0000;...
0.4717 0 1.0000;...
... |
78478d1fcc032e12bffc6993e1b682c7e26e3e9f4e5bdd419e2e889ff160d7bc | MATLAB | 16,790 | 420 | function PlotFromKymo(dx,Ekimo,Skimo,Xkimo,Xkimo0,Velo)
% Plot curves from kymograph data
% 1. Stress profiles at differnet imes
% 2. Strains profiles at differnet imes
% 3. Condnesation profiles
% 4. Stress kymographs
% 5. Strains kymographs
% 6. Stress 3D data. Profiles at each time.
% USAGE Example:
%
% PlotFromKymo... |
3566648a70695e3cd80a5fa84c14f420f5061d5d6039804092acbfa92f199ca9 | MATLAB | 16,856 | 392 | function [all_STFT, all_freq_Hz, all_t_STFT, mean_all_ER_percents,f0,Fb] = ...
extract_time_freq_signal(in_data, f_samp, x_vec, varargin)
% Compute the short-time fourier transform along x_vec in time and from
% f_begin to f_stop Hz in frequency.
% If f_stop < f_begin+f_step, only one frequency is considere... |
bff825d1659e86e98237b900218e06391f965ec79971c7ef66f37972cff07fd6 | MATLAB | 16,881 | 335 | function [projected_data,label,projected_data_e,label_e] = NeuralTraj_v2(dataset,dataset_e,trials,session,etrials,count,m,st,m_e,st_e,xc1,xc2,Test)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This code computes the projection of neural activity onto
% principal components generated fr... |
58bb9143260c00eb88a5e2f597224028059972e2feee88429a04dba42e75abca | MATLAB | 16,910 | 624 | function varargout = DB_Browser(varargin)
% DB_Browser
%
% Browses MySQL Electrophysiology database.
%
% The database IDs of items selected in the lists of the DB_Browser GUI can
% be accessed externally by the following:
% IDs = getpref('DB_BROWSER_SELECTION')
% % IDs will be a structure with fieldnames w... |
793f205990471d2cf472fa3b4d97c7f7acca342eed7b36815f016cb2f9b0b275 | MATLAB | 17,020 | 448 | function out = seqIo( fName, action, varargin )
% Utilities for reading and writing seq files.
%
% A seq file is a series of concatentated image frames with a fixed size
% header. It is essentially the same as merging a directory of images into
% a single file. seq files are convenient for storing videos because: (1)
%... |
6631db78dab8535bf24777205a26151f4d7f0d7ffc40838fe990334f608a0c1c | MATLAB | 17,042 | 463 | function [ outEEG ] = erplab_shiftEventCodes(inEEG, eventcodes, timeshift, varargin)
%ERPLAB_SHIFTEVENTS_EEG Shift the timing of user-specified event codes.
%
% FORMAT:
%
% EEG = erplab_shiftEventCodes(inEEG, eventcodes, timeshift, rounding, displayFeedback, displayEEG)
%
%
% INPUT:
%
% inEEG - EEGLAB ... |
0b81e339e3d089fa7b5090791f82bbe4b381cf6eeacb77ec0c961d5eff26da54 | MATLAB | 17,087 | 365 | %
% Author: Guanghui ZHANG && Steven Luck
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2024
% ERPLAB Studio Toolbox
%
function varargout = f_mvpc_grandaverageGUI(varargin)
global observe_DECODE;
addlistener(observe_DECODE,'Count_currentMVPC_changed',@Count_currentMVPC_changed);
addlist... |
27f33f30cedfdce817e67ca114544a7146ba0608bf0a45e4775d3963355fa340 | MATLAB | 17,088 | 436 | % New ERP viewer GUI Layout
%
% Author: Guanghui Zhang & Steve J. Luck
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2022 & 2023
% ERPLAB Studio Toolbox
%
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as ... |
a50e438b3f805bc7999d8c8aa340397380ec699c55fadb1a3f119c8725ec7c30 | MATLAB | 17,094 | 678 | function varargout = NHP_Joystick2AFC(varargin)
% NHP_Joystick2AFC
%
% Simple GUI for Sound Localization using 2AFC paradigm
%
% Daniel.Stolzberg@gmail.com 2016
% Last Modified by GUIDE v2.5 07-Mar-2016 14:13:18
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilena... |
403b9719acccee3aff7f935491324c8dd4d0bd82420098f9fba2287a6ea2e787 | MATLAB | 17,255 | 404 | % pop_epoch() - Convert a continuous EEG dataset to epoched data by extracting
% data epochs time locked to specified event types or event indices.
% May also sub-epoch an already epoched dataset (if sub-epochs are
% same size or smaller). This pop_function calls epoch().
% U... |
ef92b925449e5aa4d082c3329abe2bd88cd7c1855fc3f462d226d37237de62a8 | MATLAB | 17,319 | 481 | %% Expand wildcards for files and directory names
%
% Pattern matching of file and directory names, based on wildcard
% characters. This function is similar to wildcard expansion performed by
% the Unix shell and Python glob.glob function, but it can handle more
% types of wildcards.
%
% [LIST, ISDIR] = glob(... |
6c7e40806b5b4500d5ccc087b0949390062db0c26b2005739f00ff018838fac7 | MATLAB | 17,344 | 403 | function level23_spatial
try
% Level 8 Noise
% Options:
% Discrete / Continuous
% Spatially separated / collocalized
%
% Spatial separation options:
% Signal(Left) + Noise (Right)
% Signal(Right) + Noise (Left)
% Signal(Both) + Noise (Both)
global DA gf h
% DA: TDT conne... |
1a8e97b889e1233061af02d1348472295b42c383199fb133685b8d20939844e0 | MATLAB | 17,354 | 573 | function varargout = Tinnitus2AFC_Monitor(varargin)
% TINNITUS2AFC_MONITOR MATLAB code for Tinnitus2AFC_Monitor.fig
% TINNITUS2AFC_MONITOR, by itself, creates a new TINNITUS2AFC_MONITOR or raises the existing
% singleton*.
%
% H = TINNITUS2AFC_MONITOR returns the handle to a new TINNITUS2AFC_MONITOR or t... |
bc24d7a176cb94645c94168275c6f9965f333e895179329fa36bf38c78d7a335 | MATLAB | 17,384 | 405 | %% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Target = 'LONG';
Areas = {'PFC','HP','Joint'};
TimeSpan = 4;
bw=0.05;
tlimsAll = [-5 5];
tbAll = tlimsAll(1):bw:tlimsAll(2);%0:bw:2*sum(abs(tlimsAll));
maxRange=20; % Upper limit of assembly size to explore
noTrials = 5; % How many ... |
e59b7f714d63733b183e0ff90a73e4703987911e93a2536f8dbb8b3bdbd779b4 | MATLAB | 17,394 | 531 | function varargout = continuousFFT(varargin)
% CONTINUOUSFFT MATLAB code for continuousFFT.fig
% CONTINUOUSFFT, by itself, creates a new CONTINUOUSFFT or raises the existing
% singleton*.
%
% H = CONTINUOUSFFT returns the handle to a new CONTINUOUSFFT or the handle to
% the existing singleton*.
%
% ... |
8572904d71395362bacafe232567f5ec17cfbdd675dc75bce452d9a91dc72712 | MATLAB | 17,462 | 778 | function varargout = PumpControl2015_vTDT(varargin)
% PumpControl2015_vTDT MATLAB code for PumpControl2015_vTDT.fig
% Edit the above text to modify the response to help PumpControl2015_vTDT
% Last Modified by GUIDE v2.5 23-Sep-2015 10:30:45
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = str... |
c51ef4a86c6eabe48cc6ebf497674487377c6eacf3a9c6298217f283f8b93a2e | MATLAB | 17,505 | 437 | clear
Targets = {'SHORT','MEDIUM','LONG'};
Delays_ = {'Delay_0'};
Delays__ = {'0s'};
Dirs = {'Left','Right'};
bw=0.05;
bw_hist = 0.05;
pat = 'C:\Analysis\AssemblyAnalysis\raw';
cd(pat)
fileList=dir('allTimestamps\*SHORT*.mat');
Areas = {'HP','PFC'};
tlims= [-5 10];
length_ = sum(abs([tlims]))/bw;
len... |
ede1b2ac0a8e2ead8ac7e866f9495f2c145a40f91982684dabde97bb1d555d27 | MATLAB | 17,566 | 579 | % PURPOSE: Calculates the average amplitude/power spectra across given frequencies using Fourier Transform on continuous EEG.
%
%
% FORMAT :
%
% [EEG,fft_out, COM] = pop_continuousFFT(EEG, 'ChannelIndex', [1:nchans], 'Frequencies', [0 3;3 8]);
%
% INPUTS :
%
% EEG - Currently loaded EEG structure array
% ChannelIn... |
4210c31b1ce827a7d0f8d60e3cdfe81b52f5cef5e3fb0583ab5fac3f95d65f5f | MATLAB | 17,580 | 530 | %%this function is used to call back the parameters for plotting mvpc wave
% *** This function is part of EStudio Toolbox ***
% Author: Guanghui Zhang & Steven Luck
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2024
function OutputViewerparerp = f_preparms_decodetab(MVPC,matlabfig,Hist... |
c3e554885c3417d2b7f50babeddb749ce5c28fa1d91ef79357bd137c330c17c4 | MATLAB | 17,616 | 401 | %
% This script produces supplementary figures 3-5
%
% Dora Hermes, Dorien van Blooijs, Max van den Boom, 2022
clear
close all
clc
%%
% Load the ccepData and ccepAverages from the derivatives
myDataPath = setLocalDataPath(1);
if exist(fullfile(myDataPath.output, 'derivatives', 'av_ccep', 'ccepData_V2.mat'), 'file... |
f35d954094844958c3d1fd66afe9434e74f676f0fb589ac7f9a9e25482ec0967 | MATLAB | 17,619 | 444 | % Comparison between TENS sync and TENS async
conditions_names = {'', '', 'TENS sync', '', 'TENS async'};
numberPatients = 11;
load('OFF_ON_FBI_data.mat'); % either run analysis.m or load the struct
%% Questionnaire
% Sub
plotQuest = [SubQuestOFF(1:4, 3) + 3 SubQuestOFF(1:4, 5) + 3];
plotSem = [semSubQuestOFF(1:4, 3) ... |
329c5183fc41891375875fedf7a463ecc38f9a8f51287796a53f90ef4d8cfbf4 | MATLAB | 17,668 | 424 | clear
Targets = {'SHORT','MEDIUM','LONG'};
Delays_ = {'Delay_2','Delay_4','Delay_6','Delay_8'};
Delays__ = {'2s','4s','8s','16s'};
Dirs = {'Left','Right'};
bw=0.05;
bw_hist = 0.05;
pat = 'C:\Analysis\AssemblyAnalysis\raw';
cd(pat)
fileList=dir('allTimestamps\*MEDIUM*.mat');
Areas = {'HP','PFC'};
tlims=... |
43ecdb1048418bc605a3c7d581c640775e8e1adf924afe1efe4a291541e044b2 | MATLAB | 17,694 | 597 | function varargout = chanloc(varargin)
%
% ERPLAB
% axs 2017
%
%
% CHANLOC MATLAB code for chanloc.fig
% CHANLOC, by itself, creates a new CHANLOC or raises the existing
% singleton*.
%
% H = CHANLOC returns the handle to a new CHANLOC or the handle to
% the existing singleton*.
%
% CHANLOC(... |
bb72e30044000f8d23e0c09092c4a14c3a8c8a111c72bcf95722d1f711b69408 | MATLAB | 17,697 | 288 | function properties = visedconfig2propgrid(visedconfig)
if nargin==0;%Use the global object BATCH_CONFIG
global VISED_CONFIG
if isempty(VISED_CONFIG);
sprintf('%s','There is no VISED_CONFIG object in the workspace... creating default.\n')
VISED_CONFIG=visedconfig_obj;
end
visedconfig=VI... |
574b9b46f9812645a737305719559fc8dafddacd79e720ca5a5654067ad5cf6c | MATLAB | 17,798 | 592 | %this is a program that generates trial averages and forms clusters based
%on that. Created by Haleh Fotowat.
close all
clearvars
path=uigetdir;
cd(path)
%read the pooled clustering data
load('DMDLBRDLCB_082628_091112_HA.mat')
clear IDX
load('Peaks_EXPFits_DMDLBRDLCB_v2.mat')
ISI=40;
per2p=1.06295;
stim_type_cnt=5;
re... |
23732f6ab739f3daf6da6c6fd9cb9e61db1804708a103c421f14cb475184d206 | MATLAB | 17,816 | 470 | % erplab_interpolateElectrodes() - interpolate data channels
%
% Usage: EEG = erplab_interpolateElectrodes(inputEEG, replace_elecs, ignore_elecs, method)
%
% Inputs:
% EEG - EEGLAB dataset
% replace_elecs - [integer array] indices of channels to interpolate.
% For instance, these c... |
c78d9a190549526b8355308b9c77bfebae11b270936859c7b1395a8cfeef78a2 | MATLAB | 17,846 | 574 | function [pt,dudt,fofthandle] = interparc(t,px,py,varargin)
% interparc: interpolate points along a curve in 2 or more dimensions
% usage: pt = interparc(t,px,py) % a 2-d curve
% usage: pt = interparc(t,px,py,pz) % a 3-d curve
% usage: pt = interparc(t,px,py,pz,pw,...) % a 4-d or higher dimensional curve
% usag... |
0de85c89c3865fb868890bedf00be4276de73eca46d3f35a8d78d6478b2188b0 | MATLAB | 18,085 | 461 | %% BLP_behavior_plotting
% transplanted from prism file created by Lema
% updated based on re-analysis by MSF/NK 210825
% some animals dropped, ChR2 activation entirely removed from the ms
%% Fig1e Mono VS Di in hCAR
%L108,L111,112 (N=3)
Fig1e_Mono=[ 0 0 0 0 100.0000 86.8421
... |
f8abb7e221ebfbe87454513c701b3594b7bcd195e49787344d64965e477512b3 | MATLAB | 18,122 | 419 | function Ass = getAssemPatterns(Name_,bw,FSC,ciHld,ciHsc,FL)
% Analyse patterns in assembly activation
%
% Aleksander PF Domanski PhD UoB 2016
% aleks.domanski@bristol.ac.uk
%
%
% Loads data generated by runFAassem_[epoch] code (i.e. looks at assembly
% activations that are calculated on a continous timebase,... |
2838719e577b5241158c14209d8819f4d085a38fa3d002548a90e00466d39ba3 | MATLAB | 18,179 | 386 | classdef pe_Plot < handle
% TO DO:
% property validations
properties (SetObservable)
% Data
x_data % X-axis vector (time)
data % Holds active data (data currently being used)
original_data % Stores data that was originally sent to t... |
bdb2d1adc3dc4e29c958cf5b27612b9f3907a2393cc7b4d0271f076c3ca7de1f | MATLAB | 18,228 | 449 | function find_placement_sens(iSubject, rootDir, distName)
% find_placement_sens(1, rootDir)
% find_placement_sens(2, rootDir, 'gamma')
% iSubject = 1 for Subject1, 2 for Subject3
computeSeparately = false;
% Subject1, fascicles from 34 on are peroneal?
[numFibersAtPercepThreshold, placements, endo, percepTh... |
1487128294c40955d4dff513b34521ce4fd531add4a7ecf1d1f6d84ef89d924b | MATLAB | 18,245 | 296 | % Copyright (c) 2016, Ander Biguri
% All rights reserved.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are met:
%
% * Redistributions of source code must retain the above copyright notice, this
% list of conditions... |
af0fb461fe02b55c2be13abe3dc63caffabb4fcede5f1a2713f55c5ebd4466fd | MATLAB | 18,265 | 372 | %Author: Guanghui ZHANG--zhang.guanghui@foxmail.com
%Center for Mind and Brain
%University of California, Davis
%Davis, CA, USA
%Mar. 2024
% ERPLAB Studio
function varargout = f_EEG_CSD_GUI(varargin)
global observe_EEGDAT;
addlistener(observe_EEGDAT,'eeg_two_panels_change',@eeg_two_panels_change);
addlistener(observ... |
726b746847fc97a924cb4888ad8509e95768eece644d1ecca8438fe370e758ec | MATLAB | 18,391 | 621 | function varargout = Appetitive_training_Food(varargin)
%
%Appetitive_training({'C:\Users\...*.rcx'},{'Title String'})
%
%This GUI allows a user to hand-train an animal to associate a sound
%with a water reward. Pure tones and broadband noise are both supported.
%Input 1: 1x1 cell array containing the filename of an R... |
5137b0f8c6bc7e423279d798c579cacac629ed8325ed49b3a1fed96b88ade9d7 | MATLAB | 18,396 | 375 | %Author: Guanghui ZHANG--zhang.guanghui@foxmail.com
%Center for Mind and Brain
%University of California, Davis
%Davis, CA, USA
%Feb. 2022 && Nov. 2023
% ERPLAB Studio
function varargout = f_ERP_CSD_GUI(varargin)
global observe_ERPDAT;
addlistener(observe_ERPDAT,'Count_currentERP_change',@Count_currentERPChanged);
ad... |
e2667038d4044473b0587241c2cb651ad64bf5d2ac668c8b47b7fce45d67659c | MATLAB | 18,472 | 501 | function varargout = getTankData(cfg)
% varargout = getTankData(cfg)
%
% cfg fields (default): server ('Local')
% - enumerated server as char string
% tank (no default)
% - if tank is registered then only the tank name
% ... |
c8a3740a0f3c9115c5ca9b73667ee38b3bb0c6f370b4129e4acd67c1ace18aa5 | MATLAB | 18,484 | 429 | % Comparison between FBI sync and FBI async
conditions_names = {'FBI sync', 'FBI async'};
numberPatients = 11;
load('OFF_ON_FBI_data.mat'); % either run analysis.m or load the struct
%% Questionnaire
% Sub
joinedEmbQuestFBI_11 = [];
semEmbQuestFBI_11 = [];
% Only consider 11 subjects
for c = 1: size(EmbQuestFBI, 3) % ... |
3952347c0bb34c673518892bcd8bf9f35e6a237df56609ee97adcfe21edd007c | MATLAB | 18,508 | 445 | %% A function for processing multiple OH/OHA/TOH/TOHA trials.
% If varargin is not empty, then it must be the
% variables graphFlag,diaryFlag,filesFlag,verbose,startDir,maxNumRecords.
% Copyright (C) 2022 Richard Hugh Moulton
%
% This program is free software: you can redistribute it and/or modify
% it under the ... |
26a6ea3a30fca13a3b91120d80cd006721dcd5801a20759a5583ff5f57adbd4a | MATLAB | 18,603 | 592 | %
% Author: Javier Lopez-Calderon & Steven Luck
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% ERPLAB Toolbox
% Copyright © 2007 The Regents of the University of California
% Created by Javier Lopez-Calderon and St... |
9172de34764a6f9f6d36f30dbe54bf1a6a1876f047530aff9f4a01322ac63e41 | MATLAB | 18,836 | 516 | % PURPOSE : Interpolating marked epochs based on flags.
%
% FORMAT :
%
% >> EEG = pop_artinterp(EEG, parameters);
%
% INPUTS :
%
% EEG - input dataset
%
% [EEG, com] = pop_artinterp(EEG, 'FlagToUse', replaceFlag, 'InterpMethod', interpolationMethod, ...
% 'ChanToInterp'... |
3c46d7ca6f4d1ba679cb10ac71f45dcb5394abbe12e52e80eda7b6c4dc39a630 | MATLAB | 18,869 | 715 | %% Triple Correlation Script - Figure 4
close all;
clearvars
clc;
set(0,'defaultAxesFontSize',30)
C=150; % columns
R=150; % rows
% Only analyze part of the image
% determined by Rr and Cr
T1=7;
N1=7;
T2=7;
N2=7;
Cr=C-max(T1,T2);
Rr=R-max(N1,N2);
str = 'Local Dynamics';
for n=9:50:Rr;
for t=9:50:Cr;
... |
54bcef5877743832bb295a0ea50eb15a6a4771149f9cdae9a3528975e8c03143 | MATLAB | 18,897 | 439 | % PURPOSE: gets epoch indices from epochs that meet a set of criteria.
%
% FORMAT
%
% eindices = getepochindex6(ALLEEG, parameters)
%
% INPUTS
%
% ALLEEG - epoched dataset or ERPset
%
% The available parameters are as follows:
%
% 'Dataset' - dataset index(ices) (from ALLEEG)
% 'Bin' ... |
9fa167edfbf6ae7fd89ae27e055a0bdcd363d067f379185b83d33e46a6d283b6 | MATLAB | 19,053 | 340 | %% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Delays__ = {'4s','8s','16s'};
Target = 'LONG';
runCVEdecoder = false;
ResampleTS = false;
ResampleCVE = false;
minTrialCount = 5;
bw=0.05;
Nbs = 10;
Nbs_TScore = 10;
tlimsAll = [-2 5];
tlimsNormWin = [-2 -0.2];
tbAll = tli... |
5bb0dd2e1103c9ddfe01c2d5fe2351960fab14a78d4cf47d449ebdfef0aa6b52 | MATLAB | 19,337 | 432 | %
% This script produces the images for:
% - Figure 1A - that depict a MNI surface with tracts, subtracts, ROIs and electrodes
% - Supplemental Figure 9 - distribution of electrodes over different age groups
%
% Max van den Boom, Jaap van der Aar, Giulio Castegnaro, Dora Hermes, Dorien van Blooijs, 2022
%
%%
%... |
e93374ed0dfa67a11afc85b1557250e43d662cd8475f507acae7a30886bd3919 | MATLAB | 19,582 | 590 |
if ~exist('putativeLoopCounts', 'var') || isempty(putativeLoopCounts)
putativeLoopCounts = [5, 4, 3, 2, 1];
end
if ~exist('totalClusters', 'var') || isempty(totalClusters)
totalClusters = 100;
end
if ~exist('selectingLoops', 'var') || isempty(selectingLoops)
selectingLoops = 1;
end
%Add terminal state... |
967ca631e4f39facf84911808b2f14cc56e5163a6892c787d42644b83aa82e07 | MATLAB | 19,725 | 476 | %% %%%%%% PREAMBLE %%%%%%
clear
Target = 'SHORT';
switch Target
case 'SHORT'
Delays_ = {'Delay_0'};
Delays__ = {'0s'};
case 'MEDIUM'
Delays_ = {'Delay_2','Delay_4','Delay_6','Delay_8'};
Delays__ = {'2s','4s','6s','8s'};
case 'LONG'
Delays_ = {'Short','Mediu... |
a55c39f998e12460a6cd168ed00ae438762f3f6bfb258015a9bd7c2a846421a0 | MATLAB | 19,819 | 596 | function varargout = basic_characterization(varargin)
% BASIC_CHARACTERIZATION MATLAB code for basic_characterization.fig
% BASIC_CHARACTERIZATION, by itself, creates a new BASIC_CHARACTERIZATION or raises the existing
% singleton*.
%
% H = BASIC_CHARACTERIZATION returns the handle to a new BASIC_CHARACT... |
e251863a155b3576b8a2b2042cc1e88659cbe588d81479f2c6674a759d0b2ab7 | MATLAB | 19,945 | 704 | function AMRate_Depth_Final
%---Script that analyzes behavior data from AM Rate Detection Task.
%Created 06/14/2017 JDY. Gathers all behavior session matlab files and
%saves accordingly.
clear all
close all
clc
%---FLAG---%
Save = 0;
Ephys = 0;
CHL = 0;
CHLEphys = 0;
NoFringe = 1;
%---Animal ID and Date---%
% Ger... |
243232d4faf9e73e9b85544218105932bbc51e73b615b68f2d8528466292c3fd | MATLAB | 19,987 | 599 | % PURPOSE : Plot temporal generalization matrix from MVPC data
%
% FORMAT :
%
% >> pop_plotempgenerMatrix(MVPC);
%
% INPUTS (Required) :
%
% MVPC or ALLMVPC - input dataset (MVPCset) or input ALLMVCP
%
% Times - array of times (in milliseconds) to plot
% de... |
2011671c41e5b4294675ff7ada35a2d9a0da0d56a567868831acef52ba829158 | MATLAB | 20,058 | 422 | function [mappedA, mapping] = compute_mapping(A, type, no_dims, varargin)
%COMPUTE_MAPPING Performs dimensionality reduction on a dataset A
%
% mappedA = compute_mapping(A, type)
% mappedA = compute_mapping(A, type, no_dims)
% mappedA = compute_mapping(A, type, no_dims, ...)
%
% Performs a technique for dimension... |
1aaeeee0710df67609a4acd4b8395f0e0646693a2d631af07689c46bdb13e236 | MATLAB | 20,168 | 526 | % pop_continuousartdet.m (alpha version). Reject commonly recorded artifactual potentials (c.r.a.p.)
%
% There are a number of common artifacts that you will see in nearly every EEG data file. These
% include eyeblinks, slow voltage changes (caused mostly by skin potentials), muscle activity
% (from moving the head or ... |
1ba7a60bbd74be2ae6b06fc64d1ff7aaee44c739b257f3f8b12ecc83e6e8e3c9 | MATLAB | 20,228 | 575 | %% Analysis Decorrelation Experiment (1-sec Movies)
addpath ../functions
plt = figureUtils;
% 1. Load perceptual data
load('../dataFiles/Exp4_results.mat')
col = columnsRawData;
% 2. Load Stimuli information
load('../dataFiles/Exp4_stimuli.mat')
stimIDs = {stimuli.id};
B = FeatureModel('trajAnaObj_ela5_1sec', ... |
5290440a74714eb221a9137dbfd685e68ccda08dbcb86e009a2c82670cbd02fc | MATLAB | 20,244 | 508 | classdef projection < handle
% Projection object connecting layers and nodes to other layers
%
%
% Properties
%
% weights - matrix of weights from one layer to another (rows = source units, columns = targets)
% weightsTemp - temporary storage of weight values before update
% source - name of source object
% ... |
a0a89fc1f8b3b97a6cfd4136ac13634222b9aae3e7abd1e37dc80638a8202a11 | MATLAB | 20,263 | 402 | %
%
%
%
% Hi Eric. I modified/edited the coding of pop_EEGsimulate, eegsimulateGUI, and pop_fakeEEG.
% For instance. Inserting a "trend" is separated from inserting an "evoked" activity. Indeed you may be able now of inserting both a
% linear trend and then 100 square-like evoked waveforms. I also changed some Pa... |
dff3f428cd0bc00bce94193e318d70b60c79669ba59984c2af20cd46c0a6d359 | MATLAB | 20,289 | 607 |
if ~exist('putativeLoopCounts', 'var') || isempty(putativeLoopCounts)
putativeLoopCounts = [5, 4, 3, 2, 1];
end
if ~exist('totalClusters', 'var') || isempty(totalClusters)
totalClusters = 100;
end
if ~exist('selectingLoops', 'var') || isempty(selectingLoops)
selectingLoops = 1;
end
%%
% figure(7);
% c... |
7887c5d6249f857a8c6a97821aa7bda9cc7dd7581b76f86b1ee6c6e5c3508224 | MATLAB | 20,336 | 521 | %% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Delays__ = {'4s','8s','16s'};
Target = 'LONG';
tlimsAll = [-5 5];
tlimsShort=[-4 10];
tlimsMedium=[-8 10];
tlimsLong=[-16 10];
tlimsANOVA = [-4 4];
shift = 0;
plotOnline = false;
bw=0.05;
Nbs = 500;
tbShort=tlimsShort(1):bw:tl... |
2b5fef4b7601c5307e10d438a8839a185d3df09fb1613c293cd73f5819cb6a40 | MATLAB | 20,339 | 557 | function varargout = f_ERP_save_multi_file(varargin)
% NOTE: Migrated from GUIDE (.fig) to programmatic .m for version control.
% Original .fig archived outside ERPLAB. Edit here, not the .fig.
% Migrated to .m: April 2026 by Kurt Winsler
%
% Usage: Answer = f_ERP_save_multi_file(ALLERP, EEGArray, suffix, ERPIndex, sho... |
f1fdac8404d4f9af7c676948d4d3a846b113d2257e9f7611f9aa1dbe1f369c49 | MATLAB | 20,408 | 522 | %% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Delays__ = {'4s','8s','16s'};
Target = 'LONG';
tlimsAll = [-5 5];
tlimsShort=[-4 10];
tlimsMedium=[-8 10];
tlimsLong=[-16 10];
tlimsANOVA = [-4 4];
shift = 0;
plotOnline = false;
bw=0.05;
Nbs = 500;
tbShort=tlimsShort(1):bw:tl... |
77adea8d378579ece5f50f3ead32907ee31f5cc282cc611514afe52c465eaa95 | MATLAB | 20,415 | 514 | % pop_fig_EditEvent() - Set parameters for editing events from the eegplot figure window.
%
% Usage:
% >> g = pop_fig_EditEvent(data, g, Latency, EventType, EventIndex, Proc);
%
% Inputs:
% data - EEG channel data being displayed in eegplot figure window.
% g - eegplot UserData
% Latency - da... |
726332f1cd4fd019f9beb0f5bc0e43a5f31b20b726e03a56c02a2fee37a7e6e2 | MATLAB | 20,511 | 443 | %
% Script for supplementary figure 6 and 7 - investigates the influence of seizure onset zones (SOZ) on latencies
%
% Max van den Boom. Dorien van Blooijs, Dora Hermes. 2022
%
clear
close all
clc
myDataPath = setLocalDataPath(1);
if exist(fullfile(myDataPath.output, 'derivatives', 'av_ccep', 'ccepData_V2.mat'), 'fi... |
e44c7a06e72b5f7f4682d86e8746db54c817bd38c5ca9f51c2763eb35bc04346 | MATLAB | 20,530 | 572 | function varargout = read_meas_prot(filename, varargin)
%READ_MEAS_PROT read pulse sequence protocol from VB13A- and VB15A-style "meas.dat"
%
% YAPS = read_meas_prot(filename)
% jonathan polimeni <jonp@padkeemao.nmr.mgh.harvard.edu>, 2007/jan/03
% $Id: read_meas_prot.m,v 1.1 2008/05/21 19:01:01 greve Exp $
%**... |
e53d1d90b6363d2da36e4db27bad112a57972cd0d3ae37723091c9e7186994e8 | MATLAB | 20,560 | 648 | classdef BoxPanel < uix.Panel & uix.mixin.Panel
%uix.BoxPanel Box panel
%
% p = uix.BoxPanel(p1,v1,p2,v2,...) constructs a box panel and sets
% parameter p1 to value v1, etc.
%
% A box panel is a decorated container with a title box, border, and
% buttons to dock and undock, mini... |
9172d7240d097df5e78097ab38df1e4b6c263439a7789f598d6e9ecf3d4f4b96 | MATLAB | 20,612 | 723 | function f = RIF_mdanalysis(unit_id)
% RIF_mdanalysis
% RIF_mdanalysis(unit_id)
%
% Rate-Intensity Function analysis.
%
% See also, RF_analysis
%
% Daniel.Stolzberg@gmail.com 2013
if nargin == 0 || isempty(unit_id)
unit_id = getpref('DB_BROWSER_SELECTION','units');
end
defaults.respwin = [0 0.1]... |
674fda8f3709d37d6382aace2db51274d767898b1afee0b71dcf402e27197596 | MATLAB | 20,619 | 475 | classdef GridFlex < uix.Grid & uix.mixin.Flex
%uix.GridFlex Flexible grid
%
% b = uix.GridFlex(p1,v1,p2,v2,...) constructs a flexible grid and
% sets parameter p1 to value v1, etc.
%
% A grid lays out contents from top to bottom and left to right.
% Users can resize contents by d... |
e03c3e6171ee029618c7b807a14e10072628e9da4f9f28d94a3e1a66e0a59c13 | MATLAB | 20,661 | 452 | %%This function is used to get the 'Bin & Channel Selection' Panel and record the change of th selected channels and selected bins
% *** This function is part of ERPLAB Studio Toolbox ***
% Author: Guanghui Zhang
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2022 & Oct 2023
function va... |
211afb5677dac644ec5d6028adf4cdc5d72e1191fc0394ff7c797d51a8c60ca4 | MATLAB | 20,740 | 608 | function [return_r,return_intersect,return_slope, mismatch, left_gt_right, FC_left_gt_right] = calculate_mismatch_for_subject(sc,fc,a,b,c,PREFIX,subj_name,order_i, mask, IS_PLOT_REG,IS_PLOT_EXAMPLE)
% OC - do not run Roshenthal anymore, so all laterality calculations are
% wrong!
global fig_2_order;
% formerly ... |
0500dddbce9b63de0646e551557c31d136a4c68bab358c3ef4db63d4419f1369 | MATLAB | 20,795 | 479 | %% %%%%%% PREAMBLE %%%%%%
clear
Delays_ = {'Short','Medium','Long'};
Delays__ = {'4s','8s','16s'};
Target = 'LONG';
RunErrors = false;
tlimsAll = [0 5];
tlimsShort=[0 4];
tlimsMedium=[0 8];
tlimsLong=[0 16];
shift = 0;
plotOnline = false;
bw = 0.05;
Nbs = 500;
tbShort=tlimsShort(1):bw:tlimsShor... |
3a53bf8095791be7b4493406a0ab451fb7400ab934480b47887c839d607acc24 | MATLAB | 20,842 | 822 | %%This function is to create simulated ERPset with single channel and bin
%Format:
% [ERP, erpcom] = pop_ERP_simulation(ALLERP,BasFuncName,'EpochStart',EpochStart,'EpochStop',EpochStop,'Srate',Srate,'BasPeakAmp',...
% BasPeakAmp,'MeanLatencyOnset',MeanLatOnset,'SDOffset',SDOffset,'ExGauTau',ExGauTau,'SinoiseA... |
3a557926434a88cac3b0805e4ed8d53c682744419d1889abd066a5d33a3bc8f4 | MATLAB | 20,871 | 534 | % DQ_Spectra_GUI
% "ERPLAB Data Quality Metrics" - shows per-channel/per-frequency-band
% spectral power/amplitude for continuous EEG data quality, with optional
% color-heatmap or outlier highlighting, and a spectrum plot for the
% selected channel(s)/band.
%
% NOTE: Migrated from GUIDE (.fig) to a programmatic uifigu... |
e261d25c8abf1e2929fc6f10dcdf22fedf4c2e2218dcfa76ce1c2c1b80693ab3 | MATLAB | 20,899 | 512 | clear
Targets = {'SHORT','MEDIUM','LONG'};
Delays_ = {'Short','Medium','Long'};
tlimsShort=[-10 5];
tlimsMedium=[-10 5];
tlimsLong=[-10 5];
tlimsANOVA = [-5 5];
shift = 0;
plotOnline = false;
bw=0.05;
tbShort=tlimsShort(1):bw:tlimsShort(2);
tbMedium=tlimsMedium(1):bw:tlimsMedium(2);
tbLong=tlimsLong(1):bw:... |
ef77c2484b9e772f78be8e3ae3a2296f2a496c425fa1bb791d3fe5e343d3e633 | MATLAB | 20,904 | 648 | function varargout = CondAvoidGUI(varargin)
% CondAvoidGUI M-file for CondAvoidGUI.fig
% CondAvoidGUI, by itself, creates a new CondAvoidGUI or raises the existing
% singleton*.
%
% H = CondAvoidGUI returns the handle to a new CondAvoidGUI or the
% handle to
% the existing singleton*.
%
% ... |
78cf1d8dad507d7c6e0e9db7d69ff598080e12383e13fd7a288998d8df2d354e | MATLAB | 21,076 | 526 | % >> EEG = pop_artblink2(EEG, twin, bwidth, ccovth, chan, flag);
%
% Inputs
%
% EEG - input dataset
% twin - time period in ms to apply this tool (start end). Example [-200 800]
% bwidth - Width of the simulated blink (Chebyshev window) in ms.
% ccovth - normalized cros-covarianze (ccov). Value ... |
2063cdfada2a0d68a12484afaaefbcd330aedfbf380b71996ad8d29fcd4b760f | MATLAB | 21,156 | 475 | function AssemblyImagePlotDiscreteJointOnly(Factor,Rates,Units,Events,plot_win)
% Make raster of units higlighting those tagged as assembly members
%
% Aleksander PF Domanski PhD UoB 2016
% aleks.domanski@bristol.ac.uk
%%
threshold = 3; % Which level of scrutiny to apply to thresholding
colorscale{1} = zeros(size(Facto... |
5b2596d44c362f285350fe70b021a4a31c19d48e7b1763bd3b0f37b392fd6b9c | MATLAB | 21,167 | 430 | %%% This code needs cleaning. In short, it will use the .obj that contain
%%% the anatomy of the cut, and the injection data from the Allen Mouse
%%% Brain Atlas to compute the number of fibers from auditory to visual
%%% cortex, before and after transectomy.
close all
%% Load CCF atlas
allen_atlas_path = '\\zserver... |
480a64bf7b5151f0e8eeef2ae3d7dac8a66d54ac636cc4001a21e839514114de | MATLAB | 21,295 | 519 | % Preamble
clear all; close all
% ClassNames = {'Pre-Sample','Sample/Choice','Early Delay','Late Delay','Post-Choice'};
% ClassColors = {[0.7 0.9 0.9],[0.9 0.1 0.1],[0.9 0.7 0.9],[0.9 0.5 0.9],[0.9 0.9 0.7]};
noClusts = 6;
ClassNames = {'Pre-Sample',...
'Sample',...
'Early Delay'... |
10ee919373eb791a4356953c2b76d4d570ab5bd1ea9cad89262a6d7be6c2a3d7 | MATLAB | 21,401 | 677 | function varargout = online(varargin)
% ONLINE MATLAB code for online.fig
% ONLINE, by itself, creates a new ONLINE or raises gfe existing
% singleton*.
%
% H = ONLINE returns gfe handle to a new ONLINE or gfe handle to
% gfe existing singleton*.
%
% ONLINE('CALLBACK',hObject,eventData,handles,... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.