sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
77b8d3eaf1adcf8f6bf9ed31413a908b616410b5f14fd015d54ad9640094427f | MATLAB | 6,359 | 244 | %% make rasters
clearvars
close all
clc
set(0,'defaultAxesFontSize',30)
%Baseline
load Rat_MEA2Baseline_DIV22_raster_3D_B7_trial13.mat %use for paper
raster_2D(1,:) = raster_3D(1,1,:);
raster_2D(2,:) = raster_3D(1,2,:);
raster_2D(3,:) = raster_3D(1,3,:);
raster_2D(4,:) = raster_3D(1,4,:);
raster_2D(5,:) = raster_3D(... |
d73e58c2287f2888801dc8dcf5fc9d670aad5f25e3278aaea87509bd942d9a9d | MATLAB | 6,369 | 159 | function [r, beta_map, predicted_labels, p] = svr_leave_one_out (data, labels, clipping)
% predict the scores using linear support vector regression
% INPUTS:
% data (#observations x #features) -- data matrix (ROI or voxelwise)
% labels -- scores to predict (i.e. values of dependent variable)
% clipping -- 1 if we only... |
bfa0b8e6554f109832839f171e7be2e243f7ce2110c7cbb4d36880fbcc21e838 | MATLAB | 6,371 | 194 | function outputs = mainProcessingWithOutput(data, Fs, params, textboxHandle, onlyPatterns, suppressFigures)
% Function to filter data, calculate velocity vector fields and identify
% patterns in (row)x(column)x(time)x(repetitions) matrix DATA with sampling
% frequency FS Hz, using the parameter structure PARAMS. Output... |
d79d31a65b6bfa5870e475560329ee981902e5a8c169716c0f6ad685e42504d3 | MATLAB | 6,382 | 220 | function Combined_recovered_parameters
% Script recreates figure 7 from the manuscript. This compared parameter
% distributions recovered using each algorithm, across the 5 most
% identifibale parameters.
subjects = 20; % number of subjects
simulations = 100;
FS1 = 7; % fontsize
Liley_params;
% signific... |
ccdb6f5ffd7a94c05b96d1ceb149759a6647bc2f6516e5e6ff2b2555f3e96eb6 | MATLAB | 6,387 | 204 | %this is a program to plot the ROIs on the reference brain
%read the reference brain. Created by Haleh Fotowat.
close all
clearvars
path=uigetdir;
cd(path)
[X,meta]=nrrdread('Elavl3-H2BRFP.nrrd');
load('MaskDatabase.mat')
%read the pooled clustering data
load('DMDLBRDLCB_082628_091112_HA.mat')
fps=69;
ISI=40;
per2p=1... |
02e477d179092e7b2e40ad6ea7d1c69ece00c2df79d65f5d1bc6b7042c121477 | MATLAB | 6,388 | 122 | function [PC_norm,PC_residual,PC,between_mod_k] = participation_coef_norm(W,Ci,n_iter,par_comp)
%PARTICIPATION_COEF_NORM
%
% [PC_norm,PC_residual,PC,between_mod_k] = participation_coef_norm(W,Ci,n_iter,par_comp);
%
% Participation Coefficient (Guimera and Amaral 2005,Nature,433:895-900) is a measure
% of diversit... |
b29c89cd28c0984f4813b157a86bb90b35ad8e7402953998084e4f4fddfcb457 | MATLAB | 6,400 | 216 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
%% setup vars
thr_vals = [ 0 0.05 0.1 0.15 ] ;
filename = [ DD_INTERM '/' OUTSTR '_divergences_n_outlierdetect.mat' ] ;
divo = load(filename) ;
ff = [ PROJ_DIR '/reports/lab_meeting/... |
31baf4abad50976094cc7ba916ac930bc78fc1c879812ae9b312a49592df0705 | MATLAB | 6,402 | 141 | clear;clc;
filePath=['D:\Paper_recalibration']; %%% Create a file path
cd(filePath);
%%% download data file : "Data_session.rar" and unzip to above file path
%%% download neuron timecourse list file : "Neuron_timecourse_list.rar" and unzip to above file path
load MSTd_PreData_timecourse.mat; load MSTd_PostData... |
f8e610274110ea1613b62c284d0698b3fb5221a6203be4488c485427802a5c90 | MATLAB | 6,415 | 240 | function plot_mode_eigenvectors
%
% Function to plot an individuals mode eigenvector trajectories over time
% and map to the k-means centoid assigned
%
% Fran Hancock
% Aug 2022
%
% fran.hancock@kcl.ac.uk
%
PROJECT = '/Users/HDF/Dropbox/Fran/Academics/PhD/matlab/projects/COBRA_COMPLEXITY_PHASE_FD/';
CON_PROJECT = [PROJ... |
c63012b980f41f23dec1e96e311f97c9dd36d21ab45e0664e694b7c86d9efc17 | MATLAB | 6,431 | 232 | function [arclen,seglen] = arclength(px,py,varargin)
% arclength: compute arc length of a space curve, or any curve represented as a sequence of points
% usage: [arclen,seglen] = arclength(px,py) % a 2-d curve
% usage: [arclen,seglen] = arclength(px,py,pz) % a 3-d space curve
% usage: [arclen,seglen] =... |
a82c08deaa7ffb9040e3ac195d52536639b878a58d595cbf6e29b67d21e341a7 | MATLAB | 6,433 | 199 | function [im] = tpcheckroidriftls(dirname, channel, roiinds, roix, roiy, roiname, plotit)
% TPCHECKROIDRIFTLS - Checks twophoton drift correction performance on linescan data
%
% IM = TPROIDRIFT(DIRNAME,CHANNEL,ROIINDS,ROIX,ROIY,RIONAME, PLOTIT)
%
% Checks drift correction performance. Takes a rectangle (ROIRECT) ... |
edaaab7c269c4da7e39531161c90d500f763621dd8152c8276dde792f97f02ee | MATLAB | 6,436 | 169 | function [sigout,filtout] = filt_main(sigin, fs, filtin, plot_ok)
% FILT_MAIN Main filtering procedure
% [sigout filtout] = FILT_MAIN(sigin, fs, filtin, plot_ok)
%
% Required input arguments:
% sigin - 1-by-n vector of raw data
% fs - samplig frequency (Hz)
% filtin - structure array of user defined f... |
7de15a61a759671cfa12ad462645b3c586e57dd89f2969d1e26b0e9a2537104f | MATLAB | 6,444 | 215 | % write data quality substructure to file
% part of the ERPLAB Toolbox
% axs Apr 2019
%
% Format:
% save_data_quality(ERP, 'dq.mat')
% or save_data_quality(ERP,filename,format_flag)
%
% INPUT: * - mandatory
% * ERP - an ERP structure, which must contain a ERP.dataquality substruct
% filename - a string wh... |
fced2a4fda860320bea5ade3619d6cd49d3e72efbf0d1b7832a91e59178512dc | MATLAB | 6,446 | 209 | function [mapName] = TNC_CreateRBColormap(numValues,type)
% FUNCTION DETAILS: Simple utility to create a RWB style color map
% _________________________________________________________________________
% PART OF THE TONIC PACKAGE
% developed by JOSHUA DUDMAN
% begun at COLUMBIA UNIVERSITY, continuing at HHMI / JFRC
... |
2ea26123eb02b502a1c24535f67a2499be0d1a00726d70546596a171784ad1c6 | MATLAB | 6,451 | 169 | function plot_isi( spikes, show, show_isi )
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% plot_isi - plot histogram of ISI distribution for a cluster
%
% Usage:
% plot_isi( spikes, show, show_isi )
%
% Description:
% Plots a histogram either representing the inter-spike interval (ISI... |
5583e8f45c69c0ed8dd508e08f419c86945f322a7470ee10b27f606b61a95f63 | MATLAB | 6,458 | 183 | clear
% this script shows how to use the qtiplus software
% first, run the seutp script so that all the necessary folders
% are on the matlab path
run('qtiplus_setup')
% the example dataset used here is based on signals rising from a non-central
% Wishart distribution whose parameters are set as explained in... |
4ef4409b00558b0dc90561eaabca92bf979fcc6880506f40a5a494f174ce646f | MATLAB | 6,465 | 195 | % This function is a combination of the zeroaxes.m from Andrew Knight and axescenter.m from Matt Fig.
% I just took the best of them to allow the axes look nice (crossing at the origin) and being able to be interactive.
%
% *** This function is part of ERPLAB Toolbox ***
% Author: Javier Lopez-Calderon
% Center for Min... |
a79c96bd79c5f32f480df0a66039bdfdbf3bd05ffdb5e96125bcb2ae8a62a3cf | MATLAB | 6,487 | 158 | function Assemblies = MakebestEnsembleAssemsCrossShuffle(UnitsReal, Ltrials_,Rtrials_,MaxSize,CorrsToDestroy,noTrials,nReps)
%@TODO: add shuffling of trial labels between cells to non- trial-resampled version
Areas = {'PFC','HP','Joint'};
InfoCriteria = 'max';
nReps = 50;
noTrials = 10;
verbose = false;
Ltr = si... |
93fd4d515b3e23e8a0ed7a214c236dfd4d8e0235caa255ff3bcd1390fee24b40 | MATLAB | 6,490 | 177 | %% regularized Horseshoe prior for rank reduction and shrinkage
% Combining ideas from
%
% Chakraborty, Antik, Anirban Bhattacharya, and Bani K. Mallick. "Bayesian sparse multiple regression for simultaneous rank reduction and variable selection." Biometrika 107.1 (2020): 205-221.
%
% Piironen, Juho, and Aki Vehta... |
daf78a8498d51a69ad07dfa0b7497630b0370a4a86a1dfe8b9e29d9c84ce3af1 | MATLAB | 6,502 | 178 | %%This function is to change the title of inputdlg3 so that the users are
%%easy to know which eegset that they are seeing when using ICLabel
%%Thanks for EEGLAB developers
% *** This function is part of ERPLAB Studio Toolbox ***
% Author: Guanghui Zhang & Steven Luck
% Center for Mind and Brain
% University of Cali... |
29b60b9cd1633a395f8dc36f7f9bb2b7032c1d52603c7efafde7abbe644d4942 | MATLAB | 6,503 | 167 | %% MS peak extraction routine
% This script performs peak picking and peak data extraction at full
% mass resolution. The purpose is to reduce data size while retaining the
% number of variables to obtain a dataset suitable for multivariate
% analysis.
%
% The script is to be run section wise to ensure correct... |
7b409145c956b29d525f9a0771f042afb49f232fdb0e4ea8c091b64fde7a6197 | MATLAB | 6,511 | 191 | %% This function aligns trials based on their date-time distance.
% This is useful for ensuring that paired trials are being analysed (if
% that is what is desired).
%
% 3 Decemeber 2021
%
% %#ok<*ST2NM>
function [t1Matched, t2Matched] = alignTrials(t1Idx,t2Idx,t1TrialsFull,t2TrialsFull,singleTrialFlag,dayMatchFla... |
e7b3f6dfc606bce52079afece6be61ef4bdba95d55560271b80a3887ab23dbd3 | MATLAB | 6,515 | 170 | function I = colormapTestImage(map)
% colormapTestImage Create or display colormap test image.
% I = colormapTestImage creates a grayscale image matrix that is useful
% for evaluating the effectiveness of colormaps for visualizing
% sequential data. In particular, the small-amplitude sinusoid pattern at
% the t... |
1a8bbf1291be86ee18de98361cee5368446ba9d6b8627080dddf73b774428dee | MATLAB | 6,520 | 173 | % Wrapper code: single unit and population decoding between two behavioural outcomes.
%
% (c) 2014 Daniel Durstewitz, Bernstein Center for Computational Neuroscience, CIMH/ Heidelberg University
% Edited by Aleksander PF Domanski PhD UoB 2015
% aleks.domanski@bristol.ac.uk
%
% Iterates across all animals/files
% Uses ... |
99b3d6394c3fc15683b7b8171b760b63e387df567c99c6bfaf1b166a0943dd59 | MATLAB | 6,532 | 156 | function all_params = get_all_params_to_test(consider_flip, combine_decay, ...
relative_weight)
all_AboutFirst = {'WithoutFirst'} ;
% since our sequences have length 100, decay should not be larger than
% 100...
%all_decays = [1:20] ;
% Maheu2019: 55 values tested (cfr fig 5E & p18)
all_weight... |
e7c2162737b9ea43be3ea93341b6293c9091f7406f52a611e78c98938de3492f | MATLAB | 6,538 | 163 | % PURPOSE: reads an EVENTLIST from a text file
%
% FORMAT:
%
% [EEG EVENTLIST] = readeventlist(EEG, elfilename );
%
%
% *** This function is part of ERPLAB Toolbox ***
% Author: Javier Lopez-Calderon & Steven Luck
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2009
%b8d3721e... |
0b46d69a11776a2e5e29008212e4c7acdf35289b32bc251579d5d49663c6fa46 | MATLAB | 6,540 | 201 | function Plot_repertoire_5_modes_reordered
%%%%%%%%
%
% Function to plot the LEiDA as horizonetal bar plots
%
% Joana Cabral Jan 2020
%
% Fran Hancock Feb 2021
% Adapted to HCPUN100
%
%%%%%%%%%%%
% Set up the correct folders
%
Smax=5;
Cmax=Smax-1;
CondMax=3;
n_rows=7;
PROJECT='/Users/HDF/Dropbox/Fran/Academics/Ph... |
4d2fc06963790ef74354ee6ec16340713b1f988a325d4c08f8271873cf251ae3 | MATLAB | 6,556 | 188 | function params = readprairieviewxml3(filename)
% READPRAIRIEXML3 - Read parameters from a PrairieView vers 3 file
%
%
% Reads important parameters from a PrairieView vers 3 file.
fid = fopen(filename,'rt');
if (fid==-1),
error(['Could not open file ' filename '.']);
end;
version = readPVScanVersion(fid);
[image... |
1b0af29b7ad7a50588c78d56843242ab498dc2649e4285a6a55e698e1b23b530 | MATLAB | 6,557 | 172 | function ObjFcn = makeObjFcn(XTrain,YTrain,XValidation,YValidation,Parm)
% the objective function is NOT based on Validation Error but on Other
% Measure (OthMes) such as sensitivity, specificty, auc etc.
%
% net: squeezenet, googlenet, efficientnetb0
%
% use previously trained nets for new datasets (transfer learning)... |
3461c1f88426899ab215178cdb42c66b87eb10e12ade4e9c7d8794d2cf3f1a20 | MATLAB | 6,559 | 192 | function Model_Learning_4_em(p1,p2)
%p1: seed for random number and p1=1:1:\mu. There are \mu independent simulations
%p2: pattern length. p2=1 is for 50 ms;
rng(10+(p1-1)*1e6);
%There are four steps in this program.
%%Step 1: There is no embedded pattern in afferents for 2000 learning cycles.
%%Step ... |
6a5a529f80a4e2089b1206f5cd5a1f13600249a1b94c8730b8a2885d2475bd42 | MATLAB | 6,564 | 138 | function [numSpecplotAnim,Ps_Wake,Ps_NREM,Ps_REM]=Plot_MeansSems_VSspecs(DoseColors,DoseLabels,VStitles,FigureID,f,WAKEspec_dose_anim,NREMspec_dose_anim,REMspec_dose_anim,PlotConditions)
%%% CAVE! this is the standard option to only plot the control animals who have had the respective condition when two conditions a... |
bc18e80dd01aa8f4758fe5ae39a80d4ca3f236dab38dfea66697be417bda994f | MATLAB | 6,569 | 171 | % EEG_Tab_rename_gui
% Rename EEGset dialog for ERPLAB Studio EEG Tab.
%
% NOTE: This file was migrated from MATLAB App Designer (.mlapp) format to a
% plain .m classdef file to allow version control and code editing. The
% original EEG_Tab_rename_gui.mlapp has been archived outside the ERPLAB
% directory. Any future e... |
9739377303cadee24e6fdeb4f2dd8202e8574497f3c8d0a5633f3386825cac3d | MATLAB | 6,572 | 165 | function homog_problem = homogeniseFull2DProblemRetainGrid(problem, Ax, Ay, boundary_type)
% This function takes an input problem, then uses block homogenisation to
% reduce its number of mesh points. Ax and Ay are the number of smaller
% elements (in each direction) to absorb into the larger elements. In the
% current... |
b8763bcbafdeb6d97a2704c1a12fb8e85ead6309823d0a6d6549c692bf0b8123 | MATLAB | 6,585 | 171 | % ERP_Tab_rename_gui
% Rename ERPset dialog for ERPLAB Studio ERP Tab.
%
% NOTE: This file was migrated from MATLAB App Designer (.mlapp) format to a
% plain .m classdef file to allow version control and code editing. The
% original ERP_Tab_rename_gui.mlapp has been archived outside the ERPLAB
% directory. Any future e... |
cf5b447c91fbd0a04b90b748ff21ff53292cb9ba78131251cec168b2837f5f5e | MATLAB | 6,592 | 163 | function all_params = get_all_params_EEG(consider_flip, combine_decay, ...
relative_weight, without_AF)
if nargin<4 ; without_AF = 0 ; end
all_AboutFirst = {'WithoutFirst'} ;
% since our sequences have length 100, decay should not be way larger than
% 100...
%all_decays = [1:20] ;
% Maheu2019: 5... |
ddd88201cfec830f25cce887eac5c1ebdcddcf40c2861cbdd9b5cbeb3de1ea4e | MATLAB | 6,592 | 236 | function plot_adaptive_fstat_threshold
% Generate adaptive threshold for significance test in granger causality
% analysis, using zebrafish embryonic motoneuron data.
%
% This code generate Fig 6 in the manuscript.
%%
fish_trace_pair = [1 1; 1 2; 3 1; 3 2; 4 1; ...
5 1; 5 2; 5 3; 6 1; 6 2];
%%
plot... |
d8af3b691ee36cb65cbfd6dd0efeb424036f19ec4ff6c3092bb1a8b04ea90932 | MATLAB | 6,593 | 165 | %% Setup
util.clearAll;
cur_save_dir = fullfile(util.get_paths().figs,'raw_betas_taste');
util.mkdir(cur_save_dir)
beta_tbl = util.load.beta_table();
% Get colors
colors = util.plot.getColors();
% read the communities
module_idx = modularity.get_frequent_partition();
beta_tbl.module_index = module_idx{1,cellstr(beta_tb... |
d01a5896ad18d5a113a7e0f7eb62b384fe053c2d82401a3bace87ad53a908c7e | MATLAB | 6,602 | 337 | function varargout = ABR_GUI(varargin)
% ABR_GUI;
%
% For use in conjunction with ep_EPhys and TrialFcn_ABR
%
% Daniel.Stolzberg@gmail.com 2015
% Last Modified by GUIDE v2.5 15-Dec-2015 16:30:37
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
... |
e1a48c99c2227e596d63eef9e9294e3ec3d7752ac423bd9ba93a19d5f3480de9 | MATLAB | 6,602 | 130 | %% GMLM.computeMLE_crossValidated
% Fits the MLE using cross validation. Cross-validation is done over trials, not individual bins.
%
% inputs:
% foldIDs (cvparition or array of length obj.dim_M) : the folds for cross validation (K folds)
% if foldIDs is a vector, specifies the test set for ... |
24715ae1c3bd8b1422219cadd1598112fc9e233a6bca0a0146628a36d89eb65e | MATLAB | 6,608 | 215 | function [Genes,Genes_compressed,G]= func_FeatureSelection_CAM(Parm)
% Feature selection of DeepInsight-FS
model = load('model.mat')
%netName = "squeezenet";
netName = Parm.NetName;
cd DeepResults
net = load(model.fileName);
cd ../
% netName = net.trainedNet.Layers(2).Name;
% Oblique = '|';
% [rmp,cmp] = max(netName... |
a6074d37383aaa94dbcae380fb2d48ad6dea1e28f4cc875345a1fe1080c97432 | MATLAB | 6,613 | 165 | function [ni,els,els_ind] = ieeg_position2reslicedImage(els,fname)
% input:
% els [3x] matrix with x y z coordinates of x electrodes (native space)
% default:
%
% Copyright (C) 2009 D. Hermes, Dept of Neurology and Neurosurgery, University Medical Center Utrecht
%
% This program is free software: you... |
202a10101306ea945154bcc0f5b5e5bbb98c26b99dedcb5afee087a25635b9be | MATLAB | 6,622 | 188 | %% Intensity-based Image Registration
% Includes manual control point (CPS) image registration, and automated
% intensity-based image registration.
%
% The script is to be run section wise to ensure correct data processing in
% following steps: (1) load reference images (e.g. PCA scores images)
% ... |
5e8022289a413dd19adad475cccd9e7a7710ad96b04ff80731742d0aaaf2e22a | MATLAB | 6,624 | 234 | %% BBN Calibration
% clear
Channels = 1:17;
Duration = 100; % ms
Amp = 3; % V
bufferDuration = 2*Duration; % ms
HPFc = 1000; % Hz
LPFc = 32000; % Hz
nReps = 3; % number of reps
responseWin = [10 90]; % click analysis window (excluding reflections)
%~~~~~~~~~~~~~~~~~
CHECK_CAL = true; % run after calibration ... |
c93124b6706117dd13b2c4a7a037d829509a4e8548e9bfc7b18ff5b5a2fb4852 | MATLAB | 6,631 | 238 | clear;
% run codes in "Model simulation programs" to get simulation data
% run codes in "model analysis" to obtain the data for figures
% including optical_flow_model.m, mousePatternDetectionmodel.m
n=10;
orderD=zeros(5999,6,n);
orderS=zeros(5999,6,n);
orderScv=zeros(5999,6,n);
speed_mm=zeros(6,n);
for p=1:6
for n... |
35ae001394941ad73be640ab562bc61ada1c47d4be87df1f455552beb3340f27 | MATLAB | 6,633 | 155 |
function f_exportfile_confusion_matrix(ALLMVPC,MVPCArray,meas,time_ind,fileNames,avg_win,tp,decimalNum)
[~, ~, ext] = fileparts(fileNames) ;
if strcmpi(ext,'.xls')
ext = '.xls';
elseif strcmpi(ext,'.xlsx')
ext = '.xlsx';
else
ext = '.txt';
end
for Numofmvpc = 1:numel(MVPCArray)
%% pl... |
7bb5883f3ce8f7c30df413949eeebce634fa82811b3fe5713726569ae110af9f | MATLAB | 6,635 | 238 | clear;
% run codes in "Model simulation programs" to get simulation data
% run codes in "model analysis" to obtain the data for figures
% including optical_flow_model.m, mousePatternDetectionmodel.m
n=10;
orderD=zeros(5999,6,n);
orderS=zeros(5999,6,n);
orderScv=zeros(5999,6,n);
speed_mm=zeros(6,n);
for p=1:6
for n... |
eec9f46cc08887451a65612247f21c431b0d702902e47fb6a79cb3777358ead5 | MATLAB | 6,642 | 96 | % To plot the GLM data, load the .mat data file in this folder and then run the code below
tic
isConn = featureTable_preprocessed.isConn;
featureTable_preprocessed = featureTable_preprocessed(:,2:21);
selectedFeatures_nums = [1 2 3 5 8 15 16 19]; % Based on the feature selection
nCV = sum(isConn); nShuffles = 10000;
k... |
15f15a04667fec160d3080659aca738b0dae84cb91aee4138d4e9a39bde8bd43 | MATLAB | 6,647 | 198 | % PURPOSE : Import ERP from Neuroscan average file (AVG-file)
%
% FORMAT : ERP = pop_importavg(filename, filepath);
%
% INPUTS : filename: (String) Name of the Neuroscan AVG-file to import
% filepath: (String) Directory/Path of the input AVG-file
%
% OUTPUTS : ERP: ERPLAB ERP data struct... |
f32fc3d4b8d3019905497307c5167dbb5405f579fa0b986f21579c268ff32544 | MATLAB | 6,647 | 146 | % SINERAMP - Generates sine on a ramp colour map test image
%
% The test image consists of a sine wave superimposed on a ramp function The
% amplitude of the sine wave is modulated from its full value at the top of the
% image to 0 at the bottom.
%
% The image is useful for evaluating the effectiveness of different c... |
8c26936e47ccc36c678a87ae5bd031a134dacb6c2e57a01a55e1c9e77c34388f | MATLAB | 6,653 | 130 | function spikes = ss_aggregate(spikes, reintegrate_outliers)
% UltraMegaSort2000 by Hill DN, Mehta SB, & Kleinfeld D - 07/12/2010
%
% ss_aggregate - Heirarchical cluster aggregation.
%
% Usage:
% spikes = ss_aggregate(spikes, reintegrate_outliers)
%
% Description:
% SS_AGGREGATE Heirarchical cluster aggregation... |
e015eb580db111e751a8b9f78e156c178771b045f27ee84699b21be61262446b | MATLAB | 6,662 | 198 | function [velocityX, velocityY, allConvSteps] = ...
opticalFlow(video, badChannels, alpha, beta, angleFlag, nStepsDisplay)
% OPTICALFLOW estimates the velocity of pixels between frames in the
% (x x y x t) matrix VIDEO.
%
% INPUTS:
% VIDEO: (X x Y x T) matrix of successive frames of intensity or phase
% d... |
066af246d06521cfd77252abbae964bbf8b007edcf37724af63158ef71c2ff23 | MATLAB | 6,674 | 198 | function [velocityX, velocityY, allConvSteps] = ...
opticalFlow2(video, badChannels, alfa, beta, angleFlag, nStepsDisplay)
% OPTICALFLOW estimates the velocity of pixels between frames in the
% (x x y x t) matrix VIDEO.
%
% INPUTS:
% VIDEO: (X x Y x T) matrix of successive frames of intensity or phase
% d... |
20963ab04c31264c95df8b430e32979b42bda8b97c1c9e2344de368c1136cb22 | MATLAB | 6,676 | 253 | function pp_plot_rasters_AM(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 2016-04
%
set(0,'Defau... |
3acde28ce515bb66070e31165b66c7c097b7187823fd6fcd5a1decb968b000c0 | MATLAB | 6,681 | 162 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%Evaluation tool boxs for PraNet: Parallel Reverse Attention Network for Polyp Segmentation (MICCAI20).
%Author: Deng-Ping Fan, Tao Zhou, Ge-Peng Ji, Yi Zhou, Geng Chen, Huazhu Fu, Jianbing Shen, and Ling Shao
%Homepage: http://dpfan.net/
%Pr... |
4781e1515027fb55dffcfebb062dcfbf02d94b75964695874f80b093dda93eda | MATLAB | 6,683 | 160 | % Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
% Kohl, C., Wong, M.X.M., Wong, J.J., Rushworth, M.F.S. & Chau, B.K.H.
% eLife 2022
% Script to generate Figure 3 - figure supplement 1a
clear all; close all; clc;
% Load collapsed subject data
load('... |
830004bfdda50c2316794152e12eba3f49e9f4f2b9d9a4a4899754f7ddfd8d4a | MATLAB | 6,688 | 160 | % Intraparietal stimulation disrupts negative distractor effects in human multi-alternative decision-making
% Kohl, C., Wong, M.X.M., Wong, J.J., Rushworth, M.F.S. & Chau, B.K.H.
% eLife 2022
% Script to generate Figure 3 - figure supplement 1c
clear all; close all; clc;
% Load collapsed subject data
load('... |
8bf47483cc004fab81fb15d9eaff6fe0489e6adb43e7eac95086489044e80bcc | MATLAB | 6,688 | 233 |
%function FM_sweep_testing()
close all;
handles.RPfile = 'C:\gits\epsych\UserFiles\SanesLab\RPVdsCircuits\KP\ephys_harmonics_test_TDT.rcx';
% handles.RPfile = 'C:\gits\epsych\UserFiles\SanesLab\OpenExProjects\KP\FreqTuning_FM_harmonics\RCOCircuits\FreqTuning_FM_harmonics_lite_buffer.rcx';
% handles.RPfile = 'C:\gits... |
5a19af0175fe9fe812f42ffce784203cb95e5f132e99c0544fc4563036c1daef | MATLAB | 6,711 | 200 | function RUNTIME = ep_TimerFcn_Start(CONFIG, RUNTIME, AX)
% RUNTIME = ep_TimerFcn_Start(CONFIG, RUNTIME, RP)
% RUNTIME = ep_TimerFcn_Start(CONFIG, RUNTIME, DA)
%
% Default Start timer function
%
% Initialize parameters and take care of some other things just before
% beginning experiment
%
% Use ep_PsychCon... |
216229d986357801fceb13fd3696fd79254e429bec14b1c8ee7eb73230e0765f | MATLAB | 6,715 | 166 | % loadtxt() - load ascii text file into numeric or cell arrays
%
% Usage:
% >> array = loadtxt( filename, 'key', 'val' ...);
%
% Inputs:
% filename - name of the input file
%
% Optional inputs
% 'skipline' - number of lines to skip {default:0}. If this number is
% negative the program will only sk... |
6dc2cabb41f053022f7fbea52a2116a27b5364b674218ae66513c3d126050d25 | MATLAB | 6,716 | 178 | % Display the results of the parameter recovery analysis
% - correlation between true and fitted parameters
% - percentages of models recovered
% GOAL:
% [param recov] have one correlation plot for each model (6 models)
% [model recov] histogram of % of each recovered model, per model (eg: true
% model = TP ... |
898e75f6894a1ae072f3f3e4c4e7eaeac6dc65f588e45b9c1ce5510e40633f3d | MATLAB | 6,742 | 161 | %% Examine spike-spike cross-correlations in and out of assemblies
rat = 'JaroslawLONG2'
%% Set up for cross-correlograms
% concatenate all unit spike times
FR.Jointcells = [FR.PFCcells;FR.HPcells];
FR.iCells ={1:length(FR.PFCcells),(1:length(FR.HPcells))+length(FR.PFCcells)};
FR.unitLocs = [ones(length(FR.PFCcel... |
91e4f799865ed8fe4ae6e962a5645d0910324ca02e7f44471185cbb4a1a377e2 | MATLAB | 6,742 | 171 | % eeg_regepochs() - Convert a continuous dataset into consecutive epochs of
% a specified regular length by adding dummy events of type
% and epoch the data around these events. Alternatively
% only insert events for extracting these epochs.
% Ma... |
c2785cbedd1eef9b21f064b694f592c6ca28804eeaa363979625989ab6cb2d3a | MATLAB | 6,746 | 241 | function [stats,st] = SStat_CoxPH(X,d,t,e)
% [stats,st] = SStat_CoxPH(X,d,t,e)
%
% Parameter estimation for the Cox proportional hazards model. Survival
% time ties are handled using Efron's method.
%
% Input
% X: Design Matrix with the time-independent covariates. (mxp, m # of
% subjects, p # of covariates).
% d: Lo... |
fbb8924a5d273b2312c60364901a40c8cb1cbf29aac10758a01364ef4ee40707 | MATLAB | 6,747 | 268 | function step2_crossref_temp_and_behavior_ProperGraph(rootDir)
% Add temperature to each trial
% Add label (bilateral, right, left)
% Define paths
if nargin == 0
rootDir = Cloudstation('Vowels\Noise\Cooling\Data');
% rootDir = Cloudstation('Vowels\Spatial_Unmasking\Cooling\Data');
end
behavDir = fullfile(ro... |
f3dab57380ba8a654dd606abb279661949a7829e57277407ea4d85dd54126978 | MATLAB | 6,762 | 220 | % *** This function is part of ERPLAB Toolbox ***
% Author: Javier Lopez-Calderon
% Center for Mind and Brain
% University of California, Davis,
% Davis, CA
% 2014
%b8d3721ed219e65100184c6b95db209bb8d3721ed219e65100184c6b95db209b
%
% ERPLAB Toolbox
% Copyright © 2007 The Regents of the University of California
% Creat... |
dfecb65e2c7bf307a4bb165cfc5ffc39ded953c1049d5f9a8ac3dbd0e4f0dcd3 | MATLAB | 6,764 | 208 | classdef layer < handle
% Layer object consisting of model neurons
%
%
% Main Properties
% act - vector of length n for n units representing unit activity
% actTemp - temporary representation of updated activity
% noiseGain - controls the level of noise in the neural activity
% projections -... |
f61955d2a206416b723661dc634d36c3c0d9f3b495c83b572ba738b78e60c460 | MATLAB | 6,778 | 158 | function [mydata, myt, myavg, bins]=tpquickpsth(dirname, channel, stimcodes, pixels, plotit, names,binsize)
% TPQUICKPSTH - Gives a peristimulus time histogram for one stimcode
%
% [DATA, T, AVG, BINS]=TPQUICKPSTH(DIRNAME, CHANNEL,
% STIMCODES, PIXELS_OR_DATA, PLOTIT, NAMES, BINSIZE)
%
% Gives a peristimulus t... |
109e1ce0a07f02a59f60be3f94a24710cac9d3bca191107dfb9846ee9e609f4d | MATLAB | 6,801 | 140 | restoredefaultpath
clc; clear; close all force;
data_name='MNI';
base_path = fullfile('C:\Users\Vincent\Desktop\scratch');
out_path = fullfile(base_path, 'output'); addpath(out_path);
codes_dir = fullfile(base_path, 'ET_biomarker', 'tab_data'); addpath(codes_dir);
sub_list_file = fullfile(codes_dir, [data_name,'_subj... |
0fe684e33a6f110677e5a82fa36148d64b5c8c451cf452c15a47333ec29c3e6f | MATLAB | 6,815 | 200 | function INSCAPE_Analysis(DataPath,Output,SubID,DistMethod,BrainStateMap)
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Individualized Network-based Single-frame Co-activation Pattern Estimation (INSCAPE)
% Version: v1.0 ... |
7f6b3a789a320cd00403ab276807fe9a36518d88808c33f45133e3b78a725071 | MATLAB | 6,835 | 174 | function get_subject_eigs_with_reorder
%
% Function to extract individual eigenvectors (mean) and store them for
% visualization with t-SNE. Need to reorder the modes in each run and
% condition as in LEiDA_reliability_across_conditions
%
% Fran Hancock
% May 2022
%
% fran.hancock@me.com
%
PROJECT = '/Users/HDF/Dropbox... |
7b1d7a8157bce3d30f78e855547758eebfd0abe5cb7c34f38586de0a54f6bcef | MATLAB | 6,844 | 172 | function [NBgA, NAgB, NAgA, NBgB, s1, NA, NB] = CountEventInMemory(s, param, prior_data)
% Compute transitions in sequence s.
%
% Usage: [NBgA, NAgB, NAgA, NBgB, s1, NA, NB] = CountEventInMemory(s, param)
% Input:
% s: sequence of event (1s and 2s)
% param: cell with paired arguments (name, value)... |
dbb622dcaa8880c0d01d04f64c9f2cd108c981c3513a866c5d82485a02802fc6 | MATLAB | 6,847 | 276 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
% %% read in proc spreadsheet
%
% filename = [ DD_PROC '/MamiNum_corrected_proc.txt' ] ;
% ssheet = readtable(filename,'Delimiter','\t') ;
%% load centoid data from previosly
% filena... |
f21e81625ce2504f27c094034fd6b9774a363de09fca11870025fb2f6cdd2b27 | MATLAB | 6,849 | 149 | % Package GMLM_dmc for dimensionality reduction of neural data.
%
% References
% Kenneth Latimer & David Freeedman (2021). Low-dimensional encoding of
% decisions in parietal cortex reflects long-term training history.
% bioRxiv
%
% Copyright (c) 2021 Kenneth Latimer
%
% This software is distributed unde... |
ccbdfc24d69db25da39ca7ec0fefd78970b6187ff93b64e3b023cf833946bd28 | MATLAB | 6,851 | 209 | function [PowerSpec,Peak,Med,Mean,No_pix,picMask,PeakPhase,mask,nframe, PeakPos] = bmf_sw_cr_fft_analysis(data,CBF,varargin)
% Merged Stephan's and Jan's code to both be speedy and generate all plots
% data = the raw data (usually aligned)
% CBF = the parameter structure
% varargin = (optional) - include a masked to d... |
6fe62de2328d712ab0dbac096cf99386cf86e66289d51016d804368c191d68a1 | MATLAB | 6,857 | 246 | function varargout = f_EEG_duplicate_GUI(varargin)
% F_EEG_DUPLICATE_GUI MATLAB code for f_EEG_duplicate_GUI.fig
% F_EEG_DUPLICATE_GUI, by itself, creates a new F_EEG_DUPLICATE_GUI or raises the existing
% singleton*.
%
% H = F_EEG_DUPLICATE_GUI returns the handle to a new F_EEG_DUPLICATE_GUI or the hand... |
edccd98cbc9b5dce538e9dee3dbef6d0b85e7503fe635dddf1ebce2217355752 | MATLAB | 6,857 | 182 | function [epi, endo, electrode, fascIdsByAs, activeSites, fendo, endo_orig, cross_pl] = ...
import_nerve(model, varargin)
% IMPORT_NERVE Imports the fascicles' endoneuria contours and the electrode
% active sites.
% The code additionally correct the original geometry of the endoneurium
% contours subtracting... |
ce766886be83ca0ab5adab19c976b2ba1f7723d74d2e94937942c8061560103d | MATLAB | 6,861 | 244 |
if ~exist('clusterCounts', 'var') || isempty(clusterCounts)
clusterCounts = [100 80 60 50 40 30 20 17 15 12 10 8];
end
if ~exist('distanceType', 'var') || isempty(distanceType)
distanceType = 'correlation';
end
if ~exist('maxCheckTime', 'var') || isempty(maxCheckTime)
maxCheckTime = 10;
end
hadError =... |
1245cec031783329bff84e316e8346ea0487dacc885e599e68ba34b6247ad7fb | MATLAB | 6,864 | 255 | function NextTrialID = TrialFcn_TOJ(TRIALS)
% NextTrialID = TrialFcn_TOJ(TRIALS)
%
% Custom trial selection function for time order judgement (TOJ) stimulus
% detection task.
%
% TrialTypes:
% Standard trial = 0
% Deviant trial = 1
%
% Parameters from protocol file used in this function
% TrialType
% *MIN_ST... |
e681a21edea4cfdd424016808af60e6d94414adcc4f9a2d6ebc7153e268a03a4 | MATLAB | 6,881 | 194 | function [Ae, indice, Rp] = vca(R,varargin)
% Vertex Component Analysis
%
% [Ae, indice, Rp ]= vca(R,'Endmembers',p,'SNR',r,'verbose',v)
%
% ------- Input variables -------------
% R - matrix with dimensions L(channels) x N(pixels)
% each pixel is a linear mixture of p endmembers
% signatures R = M... |
046e59d993e15612ac7ebdd0bc51b1bebb7bdab421877261ddf11778960e314c | MATLAB | 6,885 | 248 |
%
% Eric, I was improving the code a little bit (mostly my part) cause it was very slow.
% I also added more stuffs like error detectors (July 11, 2012).
function [ERP serror] = importerpss2(fullname, format, transpose)
ERP = buildERPstruct;
serror = 0;
if nargin<2
error('ERPLAB says: error, fil... |
1a685cd2609518c118af351a019135eafb3820107a4be857885c7afa07771216 | MATLAB | 6,885 | 394 | function varargout = SimpleABR(varargin)
% SimpleABR
% Last Modified by GUIDE v2.5 11-Dec-2015 19:03:23
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @SimpleA... |
1cb7434d3aa6967cb8af5456b1de84d3d93db8b5ee385992fb1b75d808d73d4d | MATLAB | 6,886 | 173 | function simulateMonodomain(problem)
% This function simulates the monodomain equation on a mesh where the
% volume fraction (fraction of accessible material, as opposed to say
% collagenous occlusions due to fibrosis) and conductivity tensor are
% allowed to vary between different elements. Completely non-conductive
%... |
b9e04dd041ec10a2a784e39b552faf501c9545440af0c3340c830cefbab97ca1 | MATLAB | 6,891 | 178 | function level86
global DA gf h
% DA: TDT connection structure
% gf: Go ferrit user data
% h: Online GUI handles
try
%GUI Clock
gf.sessionTime = (now - gf.startTime)*(24*60*60);
set(h.sessionLength,'string', sprintf('%0.1f secs',gf.sessionTime));
% hold light constantly on
DA.SetTargetVal( sprintf('... |
861d664649ab9a4c22ba25072fe2e80e1858dd1249cb433a7ae9c75f86d19729 | MATLAB | 6,909 | 166 | function [k,alpha,f]=stability_anesthesia_fieldmodel(p,branch)
% get the dispersion relation of the steady states
% p is the anesthetic parameter
% branch = 'top' or 'bottom' for seeing the steady states in upper or lower
% branch in the bifurcation graph
% parameter setting
I_sc=0.018; % subcortical firing strength... |
9769546f191acc3b6974a944711faf2ed20b8b7c4634a41fdb7217aa5bbab722 | MATLAB | 6,926 | 173 | %Author: Guanghui ZHANG & Steve Luck
%Center for Mind and Brain
%University of California, Davis
%Davis, CA, USA
%2024
% ERPLAB Studio
function varargout = f_decode_history_GUI(varargin)
global observe_DECODE;
addlistener(observe_DECODE,'Count_currentMVPC_changed',@Count_currentMVPC_changed);
addlistener(observe_DECO... |
554df8da61404ee5c115f839157059d136cd3fb9bf073d40510529f05e3d6f5c | MATLAB | 6,935 | 153 | %
% Calculates average across condition numbers for ccep data
% [average_ccep, average_ccep_names, stimpair_currents, ccep, tt] = ccep_averageConditions(data, srate, events_table, channel_names, stim_pair_nr, stim_pair_name, params, verbose)
%
% data = seeg or ecog data in electrodes X... |
71255ba4b9eda521f8be984d48ce9034194aaf8fddc9fae56bb9d5ed63041346 | MATLAB | 6,958 | 198 | %% Example analysis code from Figure 1 of Coddington, Lindo, Dudman
load('~/Dropbox (HHMI)/Conditioned responding and DA/seshMerge.mat')
control=[1 2 4 6 9 11 15 16 19];
stimPlus=[7 8 12 13 17];
stimMinus=[3 5 10 14 18 20];
final_lat=[16 2 11 1 4 15 6 9 19];
goodPerf=control([1 2 6 8])
badPer = control([4 5 7 9])
... |
b336664b90bda993d6c18409a8d0a2ad304a700475cf5aeacd6ff34d092c3c64 | MATLAB | 6,958 | 237 | function [Genes,Genes_compressed,G]= func_FS_class_basedCAM(Parm)
%[Genes,Genes_compressed,G]= func_FS_class_basedCAM(Parm)
%
% Parm is from Parameters.m file; execute Parm = Parameters(DSETnum);
% where DSETnum is the number of dataset. For example DSETnum=1 for
% dataset1.mat. Therefore, name of dataset file is <... |
be8393ed60accddd111c41176b99c1a75058c8744687d2497b7ff34b2cd07397 | MATLAB | 6,959 | 186 | function [c_ContravsIpsi,p_ContravsIpsi,c_Contra,p_Contra,c_Ipsi,p_Ipsi] = plotTransFig(transFigDat,eigDat)
%% Rename everything
mainFigP = transFigDat.mainFigP;
dataMPC = transFigDat.dataMPC;
M = transFigDat.M;
dataA = transFigDat.dataA;
r = eigDat.r;
compDimP = eigDat.compDimP;
... |
cab45c7921ce7348ed86863b5ca7e0b1dfd6be065b083ee6b70291940cb25387 | MATLAB | 6,969 | 177 | function fibersPerFascicle = place_fiber_fascicle(endos, fascID, fibersPerFascicleCross, fibp, areaMinId, minFiberDist, dirpop, invsquare, plotAll)
% PLACE_FIBERS Places fibers of each population in minimal cross-sectional
% area of the fascicle fascicles.
%
% [fiberPop] = place_fiber_fascicle(populations, fascID... |
399b08715a5f9e95c8f13182bc8903c803d69530bc65a25b1ebe37f4749a1be0 | MATLAB | 6,972 | 203 | % PURPOSE : Restore messy event code values.
% pop_setcodebit sets the bit(s) at position(s) "bitindex" in each EEG.event(i).type value to 0 (off).
% "bitindex" must contain number(s) between 1 and 16.
%
% FORMAT :
%
% EEG = pop_setcodebit(EEG, bitindex, newvalue)
%
% or
%
... |
25ef899a18cbf585095adee75688093c3e75296612b98e5168a9714099497b5e | MATLAB | 6,983 | 199 | clear;
%% svd from all mice
%% using standard cortex mask
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 publish','2018Feb 04 M2560F publish'};
vfs_anes=[];
for M=1:5%M=6 is M1 awake states
exp=explabel{M}(1);
c... |
4c61ca5d6afe463b35988dc63b566664d1c45c4fd012f81d3f31abeba3918492 | MATLAB | 6,996 | 253 | function [stats,st,a,b] = lme_RgFSfit(X,Zcols,Y,ni,Theta0,Dist,model,e)
% [stats,st,a,b] = lme_RgFSfit(X,Zcols,Y,ni,Theta0,Dist,model,e)
%
% Linear mixed-effects estimation by the Fisher scoring algorithm for a
% whole region. This function is intended to only be called from other
% functions to perform region-wise m... |
5da00bbf719c969c55dd550cc11c163a81bbd88943ce01eaddda522b8e7dcc63 | MATLAB | 7,003 | 198 |
function [MVPC, ALLMVPC] = crossnobis(ALLBEST, nIter, nCrossBlocks, DataTimes,relevantChans,classcoding,equalT,ParWorkers,method,Tooltype)
%% Subject List:
nSubs = length(ALLBEST); % # files = # subjects
global observe_DECODE;
%% Step 9: Loop through participants
for s = 1:nSubs %crossnobis is performed within... |
e5b9a2b7113171c4669a1791bb1fe00af90e20fa81042c069ab9a917405bb070 | MATLAB | 7,018 | 143 | function [areaActivity,areaActivityUnscaled,lambda,residualNorm,solutionNorm,regularizedInverse] = fitEEGTemplates(data, templates, plotLcurve, lambda)
%fitEEGTemplates fits EEG-templates (topographies of functional brain areas) to EEG-data
% A = fitEEGTemplates(data, templates) returns a matrix A containing the
% ... |
984271dd4152e6deb9b9cf27e6bcfc156b3dd95f10866094e577126e7d8d2592 | MATLAB | 7,022 | 285 | % fresh start
clearvars
close all
%% run config
config_file='config_mammals_1.m';
addpath(strcat(pwd,'/config'))
run(config_file);
%% load data
filename = [ DD_PROC '/MamiNum_corrected_proc_2.csv' ] ;
ssheet = readtable(filename,'Delimiter','\t') ;
%% read species
filename = [ DD_RAW '/MamiNum_corrected_sciname.c... |
ea7f03dfb13a61148c77bd02d4544ad8fe262015ca4c94557dc11aec20b8b5e1 | MATLAB | 7,023 | 197 | function varargout = polydetrendGUI(varargin)
gui_Singleton = 1;
gui_State = struct('gui_Name', mfilename, ...
'gui_Singleton', gui_Singleton, ...
'gui_OpeningFcn', @polydetrendGUI_OpeningFcn, ...
'gui_OutputFcn', @polydetrendGUI_OutputFcn, ...
... |
37aea4dfe1d60ef45ced5ba97f0b6a92fc447ef87144501058e0403a5040710d | MATLAB | 7,032 | 254 | function varargout=shadedErrorBar(x,y,errBar,varargin)
% generate continuous error bar area around a line plot
%
% function H=shadedErrorBar(x,y,errBar, ...)
%
% Purpose
% Makes a 2-d line plot with a pretty shaded error bar made
% using patch. Error bar color is chosen automatically.
%
%
% Inputs (required)
% x - vec... |
1058dc0036ef544660f85d794cd0c06819ec12313fe1d3120a1fd5706993342a | MATLAB | 7,047 | 206 |
function plot_butterfly(x_data, y_data, varargin)
% Plot the signals in y_data (each row = 1 signal).
% used in TSL_analyze_EEG.
%
% Inputs
% x_data: (1, n_pts) matrix of x values
% y_data: (n_curves, n_pts) matrix
[n_curves,n_data] = size(y_data) ;
% === Default arguments =========== %
eps_fig = 1 ;... |
7473000f0a815b7730caf7015ae7e89b9cbad13a4c94013e685ab911b6da3a3c | MATLAB | 7,054 | 164 | function AssemblyRasterPlotDiscrete(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(Factor.FSC{1},2... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.