sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
bc3bdd0e6ca85ced0155d39f19cd4e9f0ae5fa640b672a8a4fb89f6cc23435d9 | MATLAB | 13,418 | 462 | close all;
clear;
clc;
% parameters
subject1 = 'Dog_3';
subject2 = 'Dog_3';
tri = 9;
number1 = tri;
number2 = tri;
path1 = ['E:\Sameni\Projects\Seizure\' subject1 '\'];
path2 = ['E:\Sameni\Projects\Seizure\' subject2 '\'];
mode1 = 'interictal';
mode2 = 'preictal';
SpectralWinLen = 5.0; % in seconds
SpectralOverlapPerc... |
341315ae3a9a1d2f556a7d33caa67727f6d50f831c805de910afe519639be836 | MATLAB | 13,456 | 320 | %% Plot correct trial types grouped by stim types
% Plot nondrifting unit (at least 4 blocks and the last block is longer than 30 trials)
MouseName = 'YT084';
MainDir = 'F:\';
seDir = [MainDir, MouseName, '\MSessionExplorer_', MouseName];
seFilePaths = MBrowse.Files(seDir);
for j = 1: length(seFilePaths)
... |
409982356ae2f349e44b4b387f34a7af42b78f2a9a7f60e264d84dc99f98769f | MATLAB | 13,458 | 272 | function results = correlation_analysis(app)
if ~isempty(app.burst_ints)
tmp =find(vertcat(app.burst_ints.type) == 1);
borders = nan(length(tmp)+1,2);
int_names = {'full interval'};
for i = 1: length(tmp)
borders(i+1,:) = app.burst_ints(tmp(i)).borders;
int_names{i+1... |
4ef8977c998f2c06ca2391698084a66b10e569e9ff284447d70805b3f2c960e5 | MATLAB | 13,461 | 275 | function results = correlation_analysis(app)
if ~isempty(app.burst_ints)
tmp =find(vertcat(app.burst_ints.type) == 1);
borders = nan(length(tmp)+1,2);
int_names = {'full interval'};
for i = 1: length(tmp)
borders(i+1,:) = app.burst_ints(tmp(i)).borders;
int_names{i+1... |
f363545fbec9a5916ad6c12701aeae365118bfbe9d31ba6befabd4a7f50cd8bd | MATLAB | 13,478 | 300 | %% mean-field stuff. We use parameters andto estimate firing rates
%% NOTE! mean Vs are now autonomus from single cell simulations
% Input: C_EE,C_EI,C_IE,C_II connectivity matrices
% S_EE,S_EI,S_IE,S_II synaptic strength
% p_EEFail Synaptic failure prob
% lambda_E lambda_I LGN input
%... |
5370c8abe502d2618f7e2640e1ed87c78c64a9d6113b8ad3182a32f14d44f65c | MATLAB | 13,494 | 248 | function [datas, data_d, norm_datas, norm_data_d] = load_compute_normalized_mean(...
column,...
min_value,...
normalization_function) % median or mean
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Loads the data from the column <column> of the file <address_data>
% Computes no... |
dfe48904bf02fb18c077e301bcdf615d7f025a59c73748bfd0b52c7dd20ab78a | MATLAB | 13,507 | 441 | function gui_adv(x, y)
%
% This file is needed by FASTICAG
% This is the advanced options -dialog
% 27.5.1999
% Hugo Gävert
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Global variables
% Handle to the window
global hf_FastICA_AdvOpt;
% Handles to some of the co... |
10ef699e96966b70a4d514e3b146d91364a5b11b3af3d1248681fccdcb41002c | MATLAB | 13,596 | 324 | %% Widefield_BerryLeafAnalysis_Population
% This script pools the data across all animals for both social phenotypes.
% It plots the respective activity time courses with corresponding
% swarm/violin plots.
%
% Version:
% 05-Jan-2024 (R2023a)
% Prepare
clc; clear all; close all
warning('off')
% Add toolboxes
% A MAT... |
5a4f75e923e983bd0f1ade00a86bb39f86848c7331143f57ddb8e4e596da647f | MATLAB | 13,608 | 342 |
%{
----------------------------------------------------------------------------
First_take number of frames in each tif files
Analyzing imaging data simply
At least for the correct rate
----------------------------------------------------------------------------
%}
function Task_kaiseki_tokyo1_20220912_sound_c... |
845162c7d528bf9d674a595ea8ac0bb923e5a9cca9feedad67db66d2f39e64fd | MATLAB | 13,609 | 398 | function icaplot(mode, varargin);
%ICAPLOT - plot signals in various ways
%
% ICAPLOT is mainly for plottinf and comparing the mixed signals and
% separated ica-signals.
%
% ICAPLOT has many different modes. The first parameter of the function
% defines the mode. Other parameters and their order depends on the
... |
745900f5124e231f7c50f4ea39db219d3cfd996084554fb0aa4dcbff87aed8b4 | MATLAB | 13,612 | 437 | %% info saturation estimation based on kafashan et al
% to do
% - load basic.mat
% - partition trials by state (runFlag)
% - get binned spike counts
% - loop through each speed combination (just neighbouring?), w/ and w/o
% shuffling ?one set of trials
%% loada data
sessionTags = {'M22027', '20220517';...
'M22... |
00d6092a294b6f1f898ba8c2973de94133cf1e3292491336b7973210ac687c4b | MATLAB | 13,667 | 321 | function [FragmentValues,BkgMean,MaxValues]=mnl_CalculateMaxValues_v3(Trace,Scale,Data,SampleBkgVxList,NumLengthThresh,SubFrag)
% Calculate the the Maximum Values of each trace, and also calculates the
% fragment values, including the split sections for measuring the
% brightness quality
%
%Inputs
% Trace - List of the... |
1a346e7f22161f7c32bfde226e3e5966bf0dbaf20630ece6f993970577c72d24 | MATLAB | 13,681 | 329 | function simulate_surgery_vs_NA_f(...
output_dir,...
folder_fit,...
dose,...
resection_times,...
percent_relapse_overall_data,...
flag_compute,...
flag_compute_control,...
flag_plot_kinetics,...
flag_plot_final_vs_NA_duration,...
flag_plot_legend,...
flag_print_numbers)
const... |
4c1bab54eba81069733df988637b31af53f1b3ead54792870fce460c178b6835 | MATLAB | 13,688 | 296 | function [data, result]= readtext(fname, delimiter, comment, quotes, options)
% Usage: [data, result]= readtext(fname, delimiter, comment, quotes, options)
%
% Whatever text file you give it, readtext returns an array of the contents (or send me a
% bug report). Matlab can't read variable length lines or... |
ee9f285615e54f9a98ab3e1b39c6999e609903f37f4cde1ba88798cfca27c4e9 | MATLAB | 13,694 | 331 | function [clusterConsensus,itemTracker,clusterTracker,exemplarTracker, alignedC] = consensusClustering(inData,nPerms,pItem,kRange,cAlgo,distance,neighbor_num,maxIter,maxReps,center,scale,verbose)
% Perform consensus clustering using a variety of clustering algorithms.
% Please ensure the algorithm of your choice (as co... |
8f1fd2a2de6c2f1cb5b7973fe9a7202585f8dd4d3118833ee91112cdb9630915 | MATLAB | 13,719 | 404 | %% analysing decoding with diff pop sizes
sessionTags = {'M22027', '20220517';...
'M22029', '20220607';...
'M22031', '20220524';
'M22032', '20220621';
'M22033', '20220706'};
dataDir = 'C:\Users\edward.horrocks\Documents\Code\V1Dynamics\Data\basic_111022';
for isession = 1:size(sessionTags,1)
fn... |
73bcb538bd82b1ef0d0c905a812c8c54c8a4c8d4b853858a8adb7531a9b1c950 | MATLAB | 13,721 | 361 |
function [P_O_model ,alpha_out , beta_out , alpha_T_out , b_c_ot_nc_out , P_observ_cond_to_state_out , P_observ_cond_to_state_comp_out]...
= forward_backward_lsim( pi_0_lsim , coupling_tetha_IM , transition_matrices_IM , gmm_para_lsim , Y_in )
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% SE... |
1af8324c3519726c3bf9b1cbd9e2b9395575d3699dbe6020fe6cdf4844d784f7 | MATLAB | 13,751 | 363 |
function [P_O_model ,alpha_out , beta_out , alpha_T_out , b_c_ot_nc_out , P_observ_cond_to_state_out , P_observ_cond_to_state_comp_out]...
= generic_forward_backward_lsim( pi_0_lsim , coupling_tetha_IM , transition_matrices_IM , gmm_para_lsim , Y_in )
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
cf4b454207b16b4b234b94eb2414e09623efd406499d31330a4148a9594eb40a | MATLAB | 13,752 | 426 | function varargout = GeneticSearch(varargin)
% GeneticSearch(DataHighFig)
%
% Allows the human to perform a supervised genetic algorithm to search for
% a desired projection.
%
% Copyright Benjamin Cowley, Matthew Kaufman, Zachary Butler, Byron Yu, 2012-2013
% ---GNU General Public License Copyright---
% This file ... |
9f73c7a6d7d7cbad3fd112d4682cdcba848e9703a095bb372eca8b7ac4e64f43 | MATLAB | 13,773 | 503 | %% Attractor Landscape Analysis
%Load data
load('ts_monkeyFb');
load('ts_monkeyZb');
% Data order file
load('data_order_combo');
% 1=left
% 2 = right
% 3 = sham
% Calculate Functional Connectivity - correlation matrices
for ii = 1:29
ts_corr_monkeyF(:,:,ii) = corr(ts_monkeyFb(:,:,ii)');
end
for ii = 1:45
ts_corr_mo... |
12409fe0d80c0bab4bfa02474a412f58c05e5b7b277f7b74d429082bbb4cbb0f | MATLAB | 13,806 | 324 | function [locOpt,globOptPac,dP,postdPCorrR_pacbc,postdPCorrP_pacbc,postdPCorrR_pacdip,postdPCorrP_pacdip,predPCorrR_pacbc,predPCorrP_pacbc,predPCorrR_pacdip,predPCorrP_pacdip,sigmaTolNew] = optimalConsensus(p,bc,dip,dipP,dipCase,type,numStdDevs,pThresh,sigmaTol,kRange,autoAdjFac,conThresh,varargin)
% v -- either pac or... |
9d2ba2afa4cf8709d97dff12fc7e8d5fb13c456a525a2c58e2392ded9a68bc3a | MATLAB | 13,843 | 463 | function uTest_DGradient(doSpeed)
% Unit test: DGradient
% This is a routine for automatic testing. It is not needed for processing and
% can be deleted or moved to a folder, where it does not bother.
%
% uTest_DGradient(doSpeed)
% INPUT:
% doSpeed: If ANY(doSpeed) is TRUE, the speed is measured.
% OUTPUT:
% On fai... |
f810dae24501a480f236606b7eae105b60fa2d66ea8c8b5cc783ed82d2bb34d6 | MATLAB | 13,859 | 359 | close all
clc
clear
% results0 = importdata('J:\ECGData\PTB\AllDataSmootherResultsPTB06_ComparisonWithWavelet2_Backup.txt'); fs = 1000;
% results0 = importdata('J:\ECGData\Arrhythmia\AllDataSmootherResultsArrhythmia06_ComparisonWithWavelet2_Backup.txt'); fs = 360;
results0 = importdata('J:\ECGData\Normal\AllDataSmoothe... |
8b27d236e3b36f0c8282dff4fa3731c6d042353dc2901a094a18a84bf960ea4d | MATLAB | 13,887 | 263 | clearvars -except Behav_path Path_figures Path_variables
close all
% caculate TFR separately for each drug
SubjectID={'S01' 'S02' 'S04' 'S05' 'S06' 'S07' 'S08' 'S10' 'S11' 'S12' 'S15' 'S17' 'S18' 'S19' 'S20' 'S22' 'S24','S21','S25','S23'};
Drug=[3 1 1 2 3 2 3; 3 1 3 2 1 2 0; 1 3 2 1 3 2 0; 2 1 1 3 2 3 0; 2 1 3 1 2 ... |
45abef317ebbee17d640cddc61e9d50eff220d1a3bcff1b0c3c4d5474902c0b2 | MATLAB | 13,923 | 440 | %% TE Gaussian Analysis - Number 2 - 1000 permutation significance iterations
%Analysis of monkey F
inhibit_monkeyF = load('TE_gaussian_1000_inhibit_monkeyF.mat');
sham_monkeyF =load('TE_gaussian_1000_sham_monkeyF.mat');
%significance from 10 point permutation in JIDT toolbox
sig_pval_inhibit = double(inhibi... |
1bb8e6f4654908e1148add3d616e22633eecdced1a59a0b2f5077547f75e8748 | MATLAB | 13,925 | 405 | function plot_spikes(handles)
set(handles.file_name,'string','Plotting...');
drawnow;
if exist('groot','builtin')
if isprop(handles.wave_clus_figure,'GraphicsSmoothing')
set(handles.wave_clus_figure,'GraphicsSmoothing','off');
end
try
set(groot,'defaultfiguregraphicssmoothing','off');
... |
0b3a7697d03febcaf3895fe802289eaa423c6f97bb762b975395c2249b85e2ec | MATLAB | 13,939 | 330 | clear all; clc; close all;
addpath( 'Z:\Jongrok\Backup\HyperBrainX\DecSpace2\Zenodo\code\functions' );
addpath( 'Z:\Jongrok\Backup\HyperBrainX\toolbox\dPCA-master\matlab' );
addpath('Z:\Jongrok\Backup\HyperBrainX\toolbox\ssPreprocessTool\fieldtrip-20230318');
ft_defaults;
neural_Dir = 'Z:\Jongrok\Backup\Hype... |
c43e37f48e9e0a460f13044b76760bc28d6bd0b359095350365d6d9198a39869 | MATLAB | 14,074 | 503 | clear all;
close all; clc;
matrixBeforeHex = ([1 0 0 0 0 1 1 1 1 0
1 0 1 0 0 0 0 0 1 0
1 1 1 1 0 1 0 1 1 1
1 1 1 0 1 1 1 1 1 0
1 0 0 0 0 1 1 1 1 0
1 1 1 1 1 1 1 1 1 0
1 1 0 1 1 0 0 1 1 0
1 1 0 1 1 1 0 0 1 1
0 0 1 0 0 0 1 0 0 0
1 0 0 1 1 1 1 1 1 1
1 1 1 1 0 1 1 1 0 0
1 1 1 1 1 0 0 1 1 1
0 0 1 0 0 1 0 1 0 0... |
40e8d40c1af58019a891d43fe886ddab17faf8de38350811faf92ac63b2b36fb | MATLAB | 14,076 | 280 | function WindowApplySpikeOff20200225(RorL)
global RtouchSpikeOffUnit LtouchSpikeOffUnit LtNegativeSpikeOffKaisuu RtNegativeSpikeOffKaisuu ...
RtPositiveSpikeOffKaisuu LtPositiveSpikeOffKaisuu LtStep4SpikeOffKaisuu RtStep4SpikeOffKaisuu ...
LtStep3SpikeOffKaisuu RtStep3SpikeOffKaisuu
%%%%%%%%LtouchSpikef... |
326cdd330df99632c825868fd1885a7501544f715ef6383afefe42b21ac95e06 | MATLAB | 14,080 | 348 | function fiducials = qt_estimator_sum_of_gaussians(ecg, fs, varargin)
% qt_estimator_sum_of_gaussians - Estimates Q-T interval and related parameters using ECG data.
%
% Syntax:
% fiducials = qt_estimator_sum_of_gaussians(ecg, fs)
% fiducials = qt_estimator_sum_of_gaussians(ecg, fs, params)
%
% Inputs:
% ... |
bfba3646394a40eccef1d4f84399a017bd8f234f1730a7b208182922caaf40c7 | MATLAB | 14,110 | 352 | function hCFig = RDPreview(hClust)
hCFig = jrclust.views.ControlFigure('FigRLPreview', [0.05 0.0 0.5 1], 'RL Preview', 1, 0);
set(gcf, 'CloseRequestFcn', @finalize);
hCFig.addAxes('default');
% populate the site # dropdown
hCFig.addUicontrol('siteNoLabel', 'Style', 'text', ...
... |
99d00219f8fe3eb6ff2ab6e03f9174d3b0f7101e68be6e9973f2a08d8aa2d2cb | MATLAB | 14,148 | 425 |
%{
----------------------------------------------------------------------------
Determine the time window for task relevant neurons
%Start of task
%Sound on
%Sound off
%Before choice
%After choice (0sec)
%After choice (1sec)
%After choice (2sec)
%p = 0.001
%Each epoch, predict the prior, sensory and choice... |
107fd570a474e159cf235e3f724215007f436c78f8ea4ad3dd35e2328a8d8337 | MATLAB | 14,161 | 383 | %% FIBER PHOTOMETRY ANALYSIS - ENTIRE SESSION (FIGURES 3 AND 4)
% Code written by Carrie Ann Stine
% Michael Bruchas Lab - UW
% Analysis code used for Figures 3 and 4 in NOPLight manuscript
% Script used to calculate the z-score of a fiber photometry trace over an
% entire recording session
%% Reset MatLab workspac... |
41155fbdb1dac84071dfb90d6993fa17d20066e34100f7965f0be21029d361b6 | MATLAB | 14,174 | 346 | function PlotRepeatTouchSpike20180306(TouchIntervalSet,SpikeA,NN,PegTouchAll,fname,tfile)
% [FigA FigB FigC FigA3 FigAA]=PlotRepeatTouchSpike20170823(TouchIntervalSet,SpikeA,NN,PegTouchAll,fname,tfile)
global FigA FigA3 FigAA
%SÄÌ^b`´Ôuðâ³
Hist0=cell(length(NN),4);
SpikeCount=cell(length(NN),4);
Spike... |
28f840ea9a35d439ec891ef08071eaa42bf6b2dcf83ecb7a708594194abc47ce | MATLAB | 14,180 | 265 | % run_retroMoCoDemo_simulateMotion.m
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Whereas run_retroMoCoDemo.m uses real example data acquired with a pulse
% sequence with FatNavs inserted into it to demonstrate the
% motion-correction, this script uses the retroMoCoBox to simulate
% motion-corrupted data - and then see how... |
c02cd73998ea2e40c52df9eb6bf1db993a3bc41289c72fdb62f6658b4459f431 | MATLAB | 14,180 | 392 | % ProgressBar
%
% Handy progress bar that can be used in GUI or text interface.
% - Faster than waitbar (MATLAB builtin)
% - GUI interface
% - CLI interface
% - Parfor compatibility
%
% -=#( Monospaced fonts are recommended for the CLI interface )#=-
%
% GUI progress bar
% | N = ... |
d339540246581380e2dadc361a69b011da1300b13b11ff136b996e74b99fe718 | MATLAB | 14,228 | 418 | classdef Config < dynamicprops
%CONFIG JRCLUST session configuration (P++)
%% OBJECT-LEVEL PROPERTIES
properties (Hidden, SetAccess=private, SetObservable)
customParams; % params not included in the default set
isError; % true if an error in configuration
isV... |
b456ed7162c4768ca89c482d15201508be649dcb7ba8319094c4eea31e4d6f32 | MATLAB | 14,287 | 422 | clear
close all
clc
load ECG2
s = data(14, 1:end);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
warning('off', 'MATLAB:nearlySingularMatrix'); % THIS IS JUST FOR AVOIDING THE MATRIX SINGULARITY WARNINGS. A MORE NUMERICALLY STABLE VERSION OF THE CODE MIGHT BE NEEDED
%%%%%%%%%%%%%%%%%%%%%... |
e4caa9a1c291e4a36e809d8df3c8e229e929e3fee9b9b6ae4bd164bf0a98716b | MATLAB | 14,355 | 395 |
%{
----------------------------------------------------------------------------
First_take number of frames in each tif files
Analyzing imaging data simply
At least for the correct rate
----------------------------------------------------------------------------
%}
function Task_kaiseki_tokyo_decode_single_neu... |
2316f97a7462e6b32c08036357f29fa1156cc1af370268f969109d6e8c9afaac | MATLAB | 14,391 | 425 |
%{
----------------------------------------------------------------------------
Determine the time window for task relevant neurons
%Start of task
%Sound on
%Sound off
%Before choice
%After choice (0sec)
%After choice (1sec)
%After choice (2sec)
%p = 0.001
%Each epoch, predict the prior, sensory and choice... |
4db971d5d5f8b24c4875c1c67d08a64bd07dc4684f13880cbeb524f2699e5d0f | MATLAB | 14,392 | 226 | close all
clc
clear
% results1 = load('J:\ECGData\PTB\AllDataSmootherResultsPTB07_NaiveSweepGammaBasedOptimized_Backup.txt');
% results1 = load('J:\ECGData\Normal\AllDataSmootherResultsNormal04_NaiveSweepGammaBased_Backup.txt');
% results1 = load('J:\ECGData\Normal\AllDataSmootherResultsNormal07_NaiveSweepGammaBasedOpt... |
341c3d0015f1d5f7a0fee73b6257da1dccbf0363ffd683e9fe385972598a0710 | MATLAB | 14,413 | 390 | function [map,prm] = cubehelix_view(N,start,rots,sat,gamma,irange,domain)
% An interactive figure for Cubehelix colormap parameter selection. With demo!
%
% (c) 2015 Stephen Cobeldick
%
% View Dave Green's Cubehelix colorschemes in a figure.
%
% * Two colorbars give the colorscheme in color and grayscale.
% * A... |
7050476d2e3e3d37bae74154dfe7051bd0418e0bbaf8d724db35abea55f253f3 | MATLAB | 14,425 | 426 |
%{
----------------------------------------------------------------------------
Determine the time window for task relevant neurons
%Start of task
%Sound on
%Sound off
%Before choice
%After choice (0sec)
%After choice (1sec)
%After choice (2sec)
%p = 0.001
%Each epoch, predict the prior, sensory and choice... |
3b3ab458e4ab24f476ecaed7667e4e2337ef3ba0c1cc00ebae2fe5f80d95c7da | MATLAB | 14,460 | 289 | function TE = solo2trialevents_pavlovian_optoinh(filepath,ifsave)
%SOLO2TRIALEVENTS_PAVLOVIAN_OPTOINH Creates trial events structure.
% SOLO2TRIALEVENTS2_PAVLOVIAN_OPTOINH(SESSPATH,IFSAVE) Creates TE trial events
% structure. The events are extracted from the saved behavior file (FILEPATH).
% Most of the ev... |
c9481467ed00af45990bd61886adabb15d798f4e28753a37af4a7dc6b1a4b8a6 | MATLAB | 14,478 | 427 |
%{
----------------------------------------------------------------------------
Determine the time window for task relevant neurons
%Start of task
%Sound on
%Sound off
%Before choice
%After choice (0sec)
%After choice (1sec)
%After choice (2sec)
%p = 0.001
%Each epoch, predict the prior, sensory and choice... |
895fb425171de7a93c407e92cb39a1f57bc48baaf10449b055505d93eb1e5533 | MATLAB | 14,503 | 318 | %% mean-field stuff. We use parameters andto estimate firing rates
%% NOTE! mean Vs are now autonomus from single cell simulations
% Input: C_EE,C_EI,C_IE,C_II connectivity matrices
% S_EE,S_EI,S_IE,S_II synaptic strength
% S_EL6,S_IL6,rE_L6,rI_L6 L6 Input
% p_EEFail Synaptic failure pro... |
a97519ad7a6d411fb1da17950e9789910ad916a92bbaa1001573623813dd88be | MATLAB | 14,524 | 498 | close all;
clear;
clc;
% parameters
subject1 = 'Dog_1';
subject2 = 'Dog_1';
tri = 15;
number1 = tri;
number2 = tri;
path1 = ['E:\Sameni\Projects\Seizure\' subject1 '\'];
path2 = ['E:\Sameni\Projects\Seizure\' subject2 '\'];
mode1 = 'interictal';
mode2 = 'preictal';
SpectralWinLen = 5.0; % in seconds
SpectralOverlapPer... |
0d2e3e50ff4007ac682e434471b8a5d0d1dbccee8dc8e466b9546b9f94a0b019 | MATLAB | 14,562 | 434 | %% analysing decoding with diff pop sizes
sessionTags = {'M22027', '20220517';...
'M22029', '20220607';...
'M22031', '20220524';
'M22032', '20220621';
'M22033', '20220706'};
dataDir = 'C:\Users\edward.horrocks\Documents\Code\V1Dynamics\Data\basic_111022';
for isession = 1:size(sessionTags,1)
fn... |
905a550b1b5daea55b90b738c648323924d1656a66fbe028cdc1f69997f2b7a6 | MATLAB | 14,562 | 452 | %% This script runs the GAM analysis described in methods, and replicates figure S5c
% To install pyGAM, follow the instructions here (https://pygam.readthedocs.io/en/latest/) for pip installation
% agv models correspond to ANGULAR HEAD VELOCITY, bv to TRANSLATION SPEED
clear all
close all
rng shuffle
load sam... |
77d6ba9922a3b4a19f6be6a261ce9b2e0c21cf604f53aa961ca072c52a384799 | MATLAB | 14,572 | 376 | function [psth, blank, binMidPoints] = makePSTH(spikeTimes,intervalsCell,blankIntervals,options)
%% options
if ~exist('options','var'), options=struct; end
% timing and smoothing options
if ~isfield(options,'binWidth'), options.binWidth=10; end
if ~isfield(optio... |
1b5dcc1157655b2b39c5dcd6e8a570ba85fa656ea5f793c274ca726bcee41f3a | MATLAB | 14,596 | 428 | %% Figure 2A
load(fullfile(pwd, 'datasets', 'singleclust.mat'))
addpath(genpath('plotting'))
dt = 5e-5;
i_plot = [137:139];
for i = 1:length(i_plot)
t = -500*dt:dt:dt*(size(data(i_plot(i)).EPSP, 1)-1-500);
plot_traces_with_gradient(t, data(i_plot(i)).EPSP);
end
for i = 1:length(i_plot)
t = -500*dt:dt:dt*(si... |
b656aa57a880cd3e3f5d4cf2c7f27e55d3c0ab20b19b5d9aa343f085396ef9d0 | MATLAB | 14,605 | 413 | % Evaluates the quality of the burst detection, by plotting the change in
% spectrum of the data with and without bursts, and providing ratios
% quantifying how much power was captured by the bursts.
clear
clc
close all
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% parameters
WelchWi... |
f8da94730fcb711a0122056313645c7a300c1ac87cdac9f7f449839215b6ab59 | MATLAB | 14,715 | 425 |
%{
----------------------------------------------------------------------------
Determine the time window for task relevant neurons
%Start of task
%Sound on
%Sound off
%Before choice
%After choice (0sec)
%After choice (1sec)
%After choice (2sec)
%p = 0.001
%Each epoch, predict the prior, sensory and choice... |
65d426e3ca128a3d74c12327a74bef8abaef9a99060b6e941d338d00991bc485 | MATLAB | 14,716 | 328 |
%{
----------------------------------------------------------------------------
norm_Task_kaiseki_tokyo1_20220316_sound_choice_separate2_detail
----------------------------------------------------------------------------
%}
function norm_Task_kaiseki_tokyo1_20220316_sound_choice_ishizu_TCchoice(folders)
a... |
020bbba9184911110e5cbefc4c68e1332a76642a77a032b6c61e35e268de1f9b | MATLAB | 14,735 | 227 | function gui_help(which_help)
%
% Used by FASTICAG
% All the help texts and title used by GUI are stored here.
% Make changes here.
% Also displays the helpwindow with the selected text
% Hugo Gävert
% 15.1.2001
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
switch ... |
4847b66c3c6893151bcf265a77a31e734ae9269b8533a93f8378a9024aac4982 | MATLAB | 14,742 | 419 |
%{
----------------------------------------------------------------------------
Determine the time window for task relevant neurons
%Start of task
%Sound on
%Sound off
%Before choice
%After choice (0sec)
%After choice (1sec)
%After choice (2sec)
%p = 0.001
%Each epoch, predict the prior, sensory and choice... |
6d9bfd52181e7741119b8b8153c823ad1ba0b2ffb5d4d628dd267167f662962f | MATLAB | 14,767 | 394 | %% PCA & SVM Classification of
% Feature Matrix: X
% Label vector: Y
% PCA: variance weighted
% SVM:
% Multiclass: fitcecoc
% One-Versus-All: fitcsvm
% Read Table(s) and Select Features from Datasets:
% - Raster_Activity_Dataset_XXXX.csv
% - General_Ensembles_Dataset_YYYY.CSV
% - Network_Features_Datas... |
732838795580e08e4d8d8fa149326168264df7d28fc062abba3e429939ade471 | MATLAB | 14,774 | 420 |
%{
----------------------------------------------------------------------------
Determine the time window for task relevant neurons
%Start of task
%Sound on
%Sound off
%Before choice
%After choice (0sec)
%After choice (1sec)
%After choice (2sec)
%p = 0.001
%Each epoch, predict the prior, sensory and choice... |
9e5c2eca3d35e4e271360576c6107414cba6a6a069e3cac780edd11ccbc7df89 | MATLAB | 14,839 | 325 | function results = correlation_analysis(app)
if ~isempty(app.burst_ints)
tmp =find(vertcat(app.burst_ints.type) == 1);
borders = nan(length(tmp)+1,2);
int_names = {'full interval'};
for i = 1: length(tmp)
borders(i+1,:) = app.burst_ints(tmp(i)).borders;
int_names{i+1... |
3ecf01847758cd1fe1afa9e75f6b9b46fdd5b181f90d633c89f468fe385f4cdb | MATLAB | 14,848 | 439 |
%{
----------------------------------------------------------------------------
Determine the time window for task relevant neurons
%Start of task
%Sound on
%Sound off
%Before choice
%After choice (0sec)
%After choice (1sec)
%After choice (2sec)
%p = 0.001
%Each epoch, predict the prior, sensory and choice... |
e27e98c9215ded38a8e605a24a63c369fdfb624f0543ced69d0988688ad5daff | MATLAB | 14,937 | 436 |
%{
----------------------------------------------------------------------------
First_take number of frames in each tif files
Analyzing imaging data simply
At least for the correct rate
----------------------------------------------------------------------------
%}
function Task_kaiseki_tokyo_decode_single_neu... |
42919c8f98e3ec538ea430613921fa9921189de4f7bac1180add39c2d2d3ea5c | MATLAB | 15,078 | 391 | function [Dimension]=mnl_EvaluateNoisePerNDimensions_v2(maxDim)
%Function to estimate the noise generated per cell.
%Fixed Variables
NumPoints=10000;
Spreads=[0.1,0.5,1,2,4,8];
NoiseValues=0:0.01:1; %I'm goingto add the noise up to 25%
szSp=size(Spreads);
szN=size(NoiseValues,2);
%% Generate Poission Distributions Fo... |
cfd339f661fea11a2af8ab014384d016d8ecba5c2be8562c79256f773688e83b | MATLAB | 15,078 | 436 | %% This script runs the GAM analysis described in methods, and replicates figure S5c
% To install pyGAM, follow the instructions here (https://pygam.readthedocs.io/en/latest/) for pip installation
% agv models correspond to ANGULAR HEAD VELOCITY, bv to TRANSLATION SPEED
clear all
close all
rng shuffle
load sam... |
bea8e3f33c96d8bb1fa1ecf003bebad4da08cc43e1382c5b5226f7aedab53498 | MATLAB | 15,079 | 460 | function [C_save, Sig_save, adj_save, Theta_save, ar_gamma, ar_theta, ...
nu_save, trans_save, ar_nu, ppi_HMM, states,edge_probs,...
states_ar,states_prop_storage, scott_ar, base_ar,num_prop_scott, num_prop_base]...
= MCMC_Algorithm(V0, V1, lambda, pii, alpha, beta,my_w, sigma_alpha_1,...
alpha_0, burnin, nmc... |
2f61cebcbfd1384342e7858579d4e4a2467122e3ca7db27a02e5eb90d5cc67a7 | MATLAB | 15,088 | 356 | function PlotRepeatTouchSpike20180312(TouchIntervalSet,SpikeA,NN,PegTouchAll,fname,tfile)
%AutoCorrðî@0.8{A1.2{ÌàÌÆärAµ½ªÁÄNNÌÂÍRD
% [FigA FigB FigC FigA3 FigAA]=PlotRepeatTouchSpike20170823(TouchIntervalSet,SpikeA,NN,PegTouchAll,fname,tfile)
global FigA FigA3 FigAA
%SÄÌ^b`´Ôuð... |
ba89253e9c11096e6e7cb681b16a7fb07a10fa26e2713dedae3ba92929bb3ee4 | MATLAB | 15,099 | 362 | %% Widefield_PureOdorAnalysis_Population
% This script pools the data across all animals for both social phenotypes.
% It plots the respective activity time courses with corresponding
% swarm/violin plots.
%
% Version:
% 05-Jan-2024 (R2023a)
% Prepare
clc; clear all; close all
warning('off')
% Add toolboxes
% A MATL... |
810a2f22cb265f26b0855db9841e2446abcb818eea2a91ceb1f63afdf26faf3a | MATLAB | 15,101 | 416 | function [bf_outs] = run_beamformer(fwd_method,sourcepos,S,do_bf,max_or_min,MFC)
%% Function to run whichever beamformer you choose
% [bf_outs] = run_beamformer(fwd_method,sourcepos,S,do_bf,max_or_min,MFC)
% [INPUTS]
% fwd_method = 'single' (single sphere method).
% = 'local' (local spheres me... |
5a58c79c6d6bb4b29ab4c9fc0ce89217eefed93445fc59e5058f185953213ab1 | MATLAB | 15,146 | 422 | function RLphase190415meanJS
global ACresult ACresultW CCresultDrinkOn SpikeArray TurnMarkerTime RpegTouchallWon LpegTouchallWon...
RpNum LpNum CCresultSpike locsP1time locsP2time locsP1time2 locsP2time2 pksA1 pksA2 CCresultRtouchWon CCresultLtouchWon dpath3...
StartTime FinishTime DiffMaxMinR DiffMaxMinL... |
a96d10e987240e0ed157d4a18cefc043043445ade2c2ee181a8af26ce4385beb | MATLAB | 15,154 | 351 | function [A, bcol, alpha] = print2array(fig, res, renderer, gs_options)
%PRINT2ARRAY Exports a figure to a bitmap RGB image array
%
% Examples:
% A = print2array
% A = print2array(figure_handle)
% A = print2array(figure_handle, resolution)
% A = print2array(figure_handle, resolution, renderer)
% A = print2ar... |
9793edafff123a8b52694c3b9cce944189be6c7d4da4887641e6387c7bacea28 | MATLAB | 15,198 | 408 | function FigureS11a_drawEachNeuronTrace_TCchoice
parent='G:/Ishizu_data';
dataPath='/Revise_ishizu/output/SpikeTrace_longtone';
outPath='/Revise_ishizu/output/drawEachNeuronTrace_TCchoice';
% hulistic parameter %
p_threshold = 1.0e-10;
figsaveTYPE='-dpng';
%--------------------%
%% collect the data of fir... |
3b6c79cc38ab5936530df3451c7f3b78412b5d2222fcef33f28707ef283c47f5 | MATLAB | 15,207 | 289 | % Authors: Simon Wadle, 2019-2023
% this function takes the output from 'multiple_day_Fall_extraction_v3_2.m'
% and extracts activity from each cell aligns it to the tone onset and
% analyzes pre and post activity via ANOVA
clearvars
% analysis options
pre_analysis_window = 12; % How many frames befor... |
ea44da6700e63a8f8c0b68f4cd9c7d02e5e2613c0fa00b8e00af3d44991636a6 | MATLAB | 15,211 | 488 | function Clusters_Struct = Map_Branches_Classes(P,Ax)
% TODO:
% Rescale X by dividing by the half-radius.
% Add min\max to rescale.
% clear all;
% close all;
Mode = 2;
FontSize_1 = 18; % 36.
Class_Colors = P.GUI_Handles.Class_Colors;
Plot_Type = P.GUI_Handles.Control_Panel_Objects(4,4).Value;
s... |
2843b56dd080ac98bbd888bf77a9e08d0e583a888139d00632ebfd4ab81f9677 | MATLAB | 15,228 | 507 | % close all
clear all
idx_SLM = 2;
branch_no = 2;
path = 'E:\data\uncaging\multi cluster cooperation\010322\cell3';
preflix = '220103_001';
clear PC shutter
filename_SLM = sprintf('%s.summation_rep.%d.wcp',preflix, idx_SLM);
out=import_wcp(fullfile(path, filename_SLM),'debug');
n_channel = out.channel_no;
n_recor... |
b3e43f77ef13670a66e05e2ff3e0227e459212e55c8569f3e3450f8c8c120a10 | MATLAB | 15,264 | 368 | classdef TracesController < jrclust.interfaces.FigureController
%TRACESCONTROLLER Summary of this class goes here
properties (SetAccess=private)
hCfg;
hClust;
hRec;
end
properties (SetAccess=private, Transient)
hFigPSD;
hFigTraces;
showFilter;
sh... |
e57bcc4aa8438f0b301e2b7350517f63001ea4ad4c50c8b124813033f47a19b0 | MATLAB | 15,300 | 264 | % pre-stimulus lick and no lick trials
%
% Construct data array
% Construct firing rate and trial number arrays from MSessionExplorer
% 1) Apply quality filters to select good units
% 2) Remove outliers (mean firing rates > 50 Hz)
% 3) Smooth the data (Gaussian kernel) for 10 ms bin
% 4) Remove pre-stimulus c... |
a610df8bf348ba475f408f5df667a2bb1638fefea3cb3defdff6dbd205fbc25f | MATLAB | 15,336 | 267 | function TouchPhase
% ¼«Ì^b`Ìʲ×é
global CCresultRtouchWon CCresultLtouchWon RpegTouchallWon LpegTouchallWon SpikeArrayWon tfile pegpatternname trimFolder2 PhaseCountRate
%SpikeArrayÅLPegTouchAllARpegTouchallðACµ½NXRIO
%SpikeArrayÅLPegTouchAllðAC·é
% duration=5000... |
edec1f369c6674db7890695a4de5a7898466dcf39e2f57c7fc00a2d5e3aaac38 | MATLAB | 15,372 | 328 | function results = correlation_analysis(app)
if ~isempty(app.burst_ints)
tmp =find(vertcat(app.burst_ints.type) == 1);
borders = nan(length(tmp)+1,2);
int_names = {'full interval'};
for i = 1: length(tmp)
borders(i+1,:) = app.burst_ints(tmp(i)).borders;
int_names{i+1... |
28dfba0ca41b1f52e69c1d01ba470828ab27bed8d7d9cd7adb541455b7c2cceb | MATLAB | 15,419 | 351 | function mrprot = parse_mrprot(arr)
% parse mrprot (text) structure
% E. Auerbach, CMRR, Univ. of Minnesota, 2022
% some changes by Steven Baete, NYU LMC CBI, 2013 (SB)
version = '2022.04.01';
fprintf(' ** parse_mrprot version %s started (%d bytes input)\n', version, numel(arr));
tstart = tic;
% i... |
4188a8e8c7bc0b6dff192514d01fb0475ae515201521308d5a7c2abc0ff7183a | MATLAB | 15,458 | 426 | function RLphase190415mean
%¼àPF¶E»ê¼êÌXpCNÌÊðp¢½\ª
global ACresult ACresultW CCresultDrinkOn SpikeArrayWon TurnMarkerTime RpegTouchallWon LpegTouchallWon...
RpNum LpNum CCresultSpike locsP1time locsP2time locsP1time2 locsP2time2 pksA1 pksA2 CCresultRtouchWon CCresultLtouchWon dpath3.... |
777bea3b42e6cce5b3d1f63361fcf0ad3ff9d3150555e9b7aea213c11950f67f | MATLAB | 15,475 | 381 | close all
clc
clear
% results0 = importdata('J:\ECGData\PTB\AllDataSmootherResultsPTB06_ComparisonWithWavelet2_Backup.txt'); fs = 1000;
results0 = importdata('J:\ECGData\Arrhythmia\AllDataSmootherResultsArrhythmia06_ComparisonWithWavelet2_Backup.txt'); fs = 360;
% results0 = importdata('J:\ECGData\Normal\AllDataSmoothe... |
58f2cb53373445b4d16e223a90fcdda758dee0511f17f13a6678792109c3741e | MATLAB | 15,497 | 348 | function PegTouchAnalysis24ch(R_PegTouchCell,L_PegTouchCell,SliderTouch,TurnMarkerTime,OneTurnTime,RpegTimeArray2D,LpegTimeArray2D,FTselect)
%'PegTouch'ÍsensorÌîñð¾½¾¯B12ch·×ĪRpeg12{ÉèÄçêÄ¢éÆ«ÉÍPegTouch¾¯Åàæ©Á½B
%µ©µARLÅ6ch¸Âgp·éÛÉÍA1-6A7-12ðèÄéKvª ... |
9ff69709bca4942fdb480cdd09eb26282edbe8add689258e86db116556cdc7fd | MATLAB | 15,504 | 337 | function [nexFile] = readNex5File(fileName)
% [nexFile] = readNexFile(fileName) -- read .nex5 file and return file data
% in nexFile structure
%
% INPUT:
% fileName - if empty string, will use File Open dialog
%
% OUTPUT:
% nexFile - a structure containing .nex file data
% nexFile.version - f... |
130ddaef93f2096254b66e67de3489fd3908e1c4441516cb035332c18cd7edba | MATLAB | 15,510 | 454 | % this script calculates FWF in WM ROIs extracted using the atlas
% normalized to the subject's space
clearvars
close all
addpath(genpath('/storage/stella/MATLAB_toolboxes/'));
addpath('/storage/stella/Analysis/matlab_scripts/');
addpath('/storage/stella/Analysis/DTI_FreeWaterFraction_May2022/SCRIPTS_MATLAB/');
load(... |
54943312d0e2dce93fb94e285554b61d14bc87822c138c0194fc802b6acfdc40 | MATLAB | 15,531 | 358 | function Lt_Rt_Pattern1_and_CV__W3_Touch_Main20200312
path=['C:\Users\C238\Desktop\touchcellLtRt_terashita'];
cd(path);
LS=ls;
PositiveTouchesPointArray=zeros(1,6);
FRCVLPWTouches=[];
FRCVRPWTouches=[];
MeanLt_FR_Session=[];
MeanRt_FR_Session=[];
MeanLt_CV_Session=[];
MeanRt_CV_Session=[];
Posi5L=[];
fo... |
ee32c11cf15a6ab0bd21d72fc9799ebdfa8159b18e57d8578f60f42e36431568 | MATLAB | 15,535 | 388 | function [timingReport, tempNameRoots] = performHostGRAPPArecon_toDisk(twix_obj,tempDir,counterStruct, nSliceNeighbours, combinePars)
%
% function [timingReport, tempNameRoots] = performHostGRAPPArecon_toDisk(twix_obj,tempDir,counterStruct, nSliceNeighbours, combinePars)
%
% Applies GRAPPA to the host data, which here ... |
cc36b30eb356604c7dbb8fe329fa643673ef885e8856e392a00ebd19d036ef51 | MATLAB | 15,538 | 244 | function create_report(app)
tmp = sort(app.lstbx_report.Value);
idx = nan(length(tmp),2);
for i = 1: length(tmp)
tmp_idx = [find(tmp{i} =='[',1),find(tmp{i} =='-',1), find(tmp{i} ==']',1)];
idx(i,1) = int16(str2num(tmp{i}(tmp_idx(1)+1:tmp_idx(2)-1)));
idx(i,2) = int16(str2num(tmp{i}(tmp_idx(2)+1:tmp_idx(3)... |
b083715e099c965bdffee763e730c0e335b56311666234eda86a3df540ab3f95 | MATLAB | 15,609 | 274 | function Rtseq5Touch
%s[NÔÌ4ÂÌC^[o̽ÏðÆÁÄA3ÂÚÌEChEðîɵĽÏÌC^[oÅEChEðÝè·é
global CCresultRtouchWon CCresultLtouchWon RpegTouchallWon LpegTouchallWon SpikeArrayWon tfile pegpatternname trimFolder2 pegpatternum RtFR_Array
%SpikeArrayÅLPegTouchAllARpegTou... |
df36ddaaf2147e298eacb163d7932b8efe41f4df53841c3efc796380fc8edc4d | MATLAB | 15,611 | 274 | function Ltseq5Touch
%s[NÔÌ4ÂÌC^[o̽ÏðÆÁÄA3ÂÚÌEChEðîɵĽÏÌC^[oÅEChEðÝè·é
global CCresultRtouchWon CCresultLtouchWon RpegTouchallWon LpegTouchallWon SpikeArrayWon tfile pegpatternname trimFolder2 pegpatternum LtFR_Array
%SpikeArrayÅLPegTouchAllARpegT... |
c845f94ae6545bc496052994c0e8c9e669b1f46c533bd7bb06c71dcb764b0808 | MATLAB | 15,625 | 250 |
function create_report(app)
tmp = sort(app.lstbx_report.Value);
idx = nan(length(tmp),2);
for i = 1: length(tmp)
tmp_idx = [find(tmp{i} =='[',1),find(tmp{i} =='-',1), find(tmp{i} ==']',1)];
idx(i,1) = int16(str2num(tmp{i}(tmp_idx(1)+1:tmp_idx(2)-1)));
idx(i,2) = int16(str2num(tmp{i}(tmp_idx(2)+1:tmp_idx(... |
0cbcc6c3169d489781a4c052d10c12b81f5532b46df541c8c09fb67d124597bc | MATLAB | 15,663 | 418 | function processSession_PSTH(inputFileName,outputFileName,dataDir)
%% load the **_basic.mat file to process
load(fullfile(dataDir,inputFileName))
%% process trials
% filter trials to the ones we want to analyse and sort according to
% behavioural state
% exclude any trials that did not run for appropriate time (so... |
a1d2560e9ad024ddbd24e65d953e2ffa1549c58cde3c97a05b13483136dccb8c | MATLAB | 15,681 | 499 | %% Temporal correlation of total, signal and noise correlatons
%% load dataa
sessionTags = {'M22027', '20220517';...
'M22029', '20220607';...
'M22031', '20220524';
'M22032', '20220621';
'M22033', '20220706'};
dataDir = 'C:\Users\edward.horrocks\Documents\Code\V1Dynamics\Data\basic_111022';
%dataDir = ... |
9d329d968b59cf6090f583666e51b299286135e1d621790ac07fb85eb5895f33 | MATLAB | 15,686 | 480 | function [M,MG] = spmup_timeseriesplot(fmridata, cn1, cn2, cn3, varargin)
% routine to produce plots a la Jonathan Power
%
% FORMAT spmup_timeseriesplot(fmridata, c1, c2, c3, options)
% [M,MG] = spmup_timeseriesplot(fmridata, c1, c2, c3, ...
% 'motion','on',... |
346e8ff3ab675fc7c1586881a3cc2672a86896c732697917fc6c5c07d13707d1 | MATLAB | 15,712 | 364 | function cellclassify20190712
global ACresult ACresultW CCresultDrinkOn SpikeArray RpegTouchallWon LpegTouchallWon TurnMarkerTime RmedianPTTM RpegMedian LmedianPTTM LpegMedian...
RpNum LpNum OneTurnTime CCresultSpike locsP1time locsP2time locsP1time2 locsP2time2 fname tfile WaterOnArrayOriginal A1 A2 WaterOnP... |
473d343d5e94fda170eba5574f8469102f20616ece1aaf3771f20817287837c6 | MATLAB | 15,716 | 365 | function cellclassify20230425
global ACresult ACresultW CCresultDrinkOn SpikeArray RpegTouchallWon LpegTouchallWon TurnMarkerTime RmedianPTTM RpegMedian LmedianPTTM LpegMedian...
RpNum LpNum OneTurnTime CCresultSpike locsP1time locsP2time locsP1time2 locsP2time2 fname tfile WaterOnArrayOriginal A1 A2 WaterOnP... |
6506e96002ba6a215638859f7278dce6ad6ac944070e76995b942005dd0b4d73 | MATLAB | 15,729 | 478 | function FigureS12gh_WheelSpeedvsPrior
% relavant to the REVIER#1 major 1-3 comment
%
% The influence of task-irrelevant movement such as running speed to
% cortical activity
% The correlation with prior value and biased choice in subsequent trials
parent='G:/Ishizu_data';
workpath='/Revise_ishizu';
outpath=... |
47a511c074e8ed2091c928b1e14f069ea4c1828ffa062f363c680754a22f074b | MATLAB | 15,736 | 347 | %% mean-field stuff. We use parameters andto estimate firing rates
%% NOTE! mean Vs are now autonomus from single cell simulations
% Input: C_EE,C_EI,C_IE,C_II connectivity matrices
% S_EE,S_EI,S_IE,S_II synaptic strength
% p_EEFail Synaptic failure prob
% lambda_E lambda_I LGN input
%... |
b159d0b626ab598be0b1f6a6566346ef64d749509fcb1b9314243f62b79b05cf | MATLAB | 15,737 | 391 |
function [positions, EXITFLAG] = fiducial_det_ppg(data, ecg_rpeaks_index, fs, varargin)
% PPG fiducial points detector based on LSIM approach
% [positions, EXITFLAG] = fiducial_det_ppg(data, ecg_rpeaks_index, fs, varargin)
%
% Inputs:
% data: Vector of input ECG data
% ecg_rpeaks_index: R-peak indexes... |
65400276aa9cae53674db076ff82e8f5e4f8262cce46e1afa0592b2b7822ea6e | MATLAB | 15,785 | 454 | % ======================================================================
%> SLICEBROWSER2 M-file for SliceBrowser2.fig
%> SliceBrowser2 is an interactive viewer of 3D volumes,
%> it shows 3 perpendicular slices (XY, YZ, ZX) with 3D pointer.
%> Input: a) VOLUME - a 3D matrix with volume data
%> ... |
2be26bdcca724f5fd2b1664666b00f752c74555bb75cb0d73395bbd632ff2dbf | MATLAB | 15,797 | 453 | function [result] = writeNexFile(nexFile, fileName)
% [result] = writeNexFile(nexFile, fileName) -- write nexFile structure
% to the specified .nex file. returns 1 if succeeded, 0 if failed.
%
% INPUT:
% nexFile - a structure containing .nex file data
%
% SOME FIELDS OF THIS STRUCTURE (VERSIONS ETC.)... |
59a695331fb6d3208a87240d12e75489159e8fd3f94f1d4dd7df0169df2b0936 | MATLAB | 15,802 | 446 |
%{
----------------------------------------------------------------------------
Determine the time window for task relevant neurons
%Start of task
%Sound on
%Sound off
%Before choice
%After choice (0sec)
%After choice (1sec)
%After choice (2sec)
%p = 0.001
%Each epoch, predict the prior, sensory and choice... |
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