sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
80a597b482cb19080e86d6d6fc338afe7515c1bc290b006aad997ebd50a75cc5 | MATLAB | 3,704 | 60 | in scanfiles:
% figure(979); clf; plot(tt,PSTHs); title('PSTHs'); xlim([-10 30]); %set(gca,'yscale','log');
% figure(978); clf; plot(tt,PSTHZs); title('PSTHZs'); xlim([-10 30]); %set(gca,'yscale','log');
% figure(977); clf; plot(tt,PSTHZsPOm); title('PSTHZsPOm'); xlim([-10 30]); %set(gca,'yscale','log');
% figure(9... |
0ea3860cad5443f415f7cb033ace9cd2e7c22c8313a4b9a8066f04abc70681d5 | MATLAB | 3,706 | 100 | function cfg_artifacts=st_artifact_reject_grid(cfg_artifacts)
% ST_ARTIFACT_REJECT_GRID determines a rejection grid (i.e. segments to fully reject)
%
% Reject segment when proportion of artifactual chans >= segmentrejectthresh
% Lower values are more aggressive (a few artifactual channels will label a segment for... |
e837956bb3179eac9afd631dc886ba85fe4faa17c30013a7b249727fadaf1a2a | MATLAB | 3,707 | 104 | function subj_Variance_response_LCMV(sn)
% source reconstruct post-response beta variability increase
load('subs.mat');
subname = subs.name{sn};
set_name = fullfile(Dir.prepro,[subname,'_clean.set']);
EEG = pop_loadset('filename',set_name);
EEG = pop_select(EEG,'nochannel',{'LHEOG','RHEOG','BVEOG','TVEOG'});
... |
6c7fd34fdb58e844b6816ec168e0945447b8cb44e2f63cbc2592d58049de53ac | MATLAB | 3,713 | 82 | function mltp_slice_fnvt_to_slice_can_movement(obj, session)
% This function calculates the movement in cm/s for each trial. We need
% to store this because when we map a rectangle to a square for the 90
% degree correlations the spike maps has a minimum speed threshold,
% which should come from the tru... |
811ac95d7d70f7b842e1261507c4ae83b3eb134577680141502687a8b0e7ce29 | MATLAB | 3,713 | 120 | clear all
close all
clc
%%%%%%%%%%% ADDPATH TO EXCEL FILE
addpath('J:\Carlo\CarloKaizhen\CC110-0513\KaizhenSelected')
%%%%%%%%%% READ EXCEL FILE
read_name='CC110_0513_Ymaze_traces_20Hz.xlsx';
data=xlsread(read_name)
data_zscore=zscore(data,1,1)
%%%num_cells=length(data_zscore(1,:))
num_cells=length(data(1,... |
6ad2e70304da88d28ea5d835cb72be2d8a000c5224d2d8eaacef6521d651b3f3 | MATLAB | 3,714 | 93 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [averageCorrelations, totalSamples, numCells, numSamplesExcluded, animalSessionCellIds, animalSessionCellNames] = compute_bfo180_similarity_using_percell_table(PerCell180, fieldNamesWanted, BFO180_MIN_MAPS)
BFO180_MIN_CO... |
cc58abd971e5b418fd5b1c14d270bd69c4ae3ed8b978e44e1ec2d2f82ab88395 | MATLAB | 3,714 | 117 | function ml_two_contexts_plot_averaged_combined_orientation(pc, contexts)
% contexts must be "all" or "within"
% This code make the orientation plot averaged across days
% Load the project settings if not already loaded
if isempty(pc)
pcFilename = fullfile(pwd, 'project_config.json');
if ~isfile(pcFilename)
... |
7c0f0fe9d9bad2bb32aeb13a213bcfb7cadf798be06826833afbec2b51fd1cf2 | MATLAB | 3,715 | 76 | function subject_FD_parse_v2_octave(FD_movement_files,skip_seconds,epi_TR,brain_radius_in_mm,output_dir)
% Code from OHSU Fair Neuroimaging Lab
% Written (2014) and commented (9/8/2015) by Eric Earl
%
% FD parsing Nipype wrapper pulling in list of motion files
%
% Modified to read (and ignore) DVAR_pre_reg, DVAR_post... |
77e071b08239bba3dd01de25cdb5d5f204c0e0f8611808b1053c79ee0b50f834 | MATLAB | 3,717 | 76 | function subject_DVAR_parse_v2_octave(FD_movement_files,skip_seconds,epi_TR,brain_radius_in_mm,output_dir)
% Code from OHSU Fair Neuroimaging Lab
% Written (2014) and commented (9/8/2015) by Eric Earl
%
% FD parsing Nipype wrapper pulling in list of motion files
%
% Modified to read (and ignore) DVAR_pre_reg, DVAR_po... |
88f7648f13237f3947421943309a3f917fc2e294df07530454f60db0af85d04d | MATLAB | 3,717 | 117 | %{
For the specified k and cognitive variable, extract the frequency, transition
distance, and idiosyncrasy p-values. FDR-correct to generate new p-values
and threshold correlations with them.
Output:
pcorr.csv Original p-values from all metrics in one table.
pcorr_fullfdr.csv FDR-corrected p-values from all metrics in... |
d6e9d313a1ea51548b150f79b8a57c80f7b0dd15782ee37768210d583e7b9731 | MATLAB | 3,720 | 116 | function neighbours=st_get_minimum_neighbours(cfg)
% ST_GET_MINIMUM_NEIGHBOURS creates a neighborhood structure such that each channel has at least a specified number of neighbors.
%
% Use as:
% neighbours=st_get_minimum_neighbors(cfg)
%
% Required configuration parameters:
% cfg.elec = FieldTrip ... |
a589709e86123097df6b154a455e8d21bf47f33c9e71b5066639241f2f863a88 | MATLAB | 3,723 | 91 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [F, success] = ml_alg_compute_best_aligned_map_table_v3(T, comparisonMethod, REFLECT_ONE_CONTEXT)
F = [];
success = true;
wb = [];
% Get unique animalName, sessionName, cellName combinations
R = get_... |
8b42a78f0c876841441e4d0979c0f3f205dfa7918e6b0cc417079ba0d80b926c | MATLAB | 3,725 | 93 | function [boxes, blobIndIm, blobBoxes, hierarchy, priority] =...
Image2HierarchicalGrouping(im, sigma, k, minSize, colourType, functionHandles)
% function [boxes blobIndIm blobBoxes hierarchy] = Image2HierarchicalGrouping
% (im, sigma, k, minSize, colourType, functionHandles)
%
% Create... |
b90f017139f1edc9acc9640e302eca942b35b2ee92cc7197b70fd3fb256a8b5e | MATLAB | 3,725 | 74 | %% RUSH configuration
vol_params.vol_sz = [600,600,150]; % Volume size to sample (in microns)
vol_params.vol_depth = 50; % Set the depth of imaging (depth at the middle of the simulated volume)
vol_params.neur_density = 3e4;
pixel_size = 0.8; % pixel size of your system
vol_params.vres = 1; % ... |
b3fe3bd1f6f9b849e78171dbb67f814285bc503b36f8f74360a54c95921e504f | MATLAB | 3,726 | 90 | classdef diffusion_mapping_tests < matlab.unittest.TestCase
% Regression tests for matlab/analysis_code/diffusion_mapping.m
% Covers issues #98 (complex eigenvalues) and #94 (sqrt(N) component cap).
methods(Test)
function test_real_eigenvalues_on_cosine_similarity(testCase)
% Issue #98:... |
7e05e5cc6c17a738c9ea9aed561d014e04968ef24c07aba860066d9d6aa1a66d | MATLAB | 3,727 | 103 | %aLFP
%plot xcorr btwn meanLFP (mean over all elecs)and motion variables
% odd/even by movie
%clear all; %close all;
if ~exist('rrr'), rrr=0; end;
rrr=rrr+1;
[user sys]=memory;
MALAB_used_mem(rrr) = user.MemUsedMATLAB/10^6; %in MB
fprintf(1,'available memory: %.0f matlab used: %.0f MB rrr=%d\n',sys.Physical... |
b8de103cc8637177f3306730cfe31d934f7d84ace3a95d15248f4fb0cba0aa43 | MATLAB | 3,727 | 117 | function [proj] = elproj(pos, method)
% ELPROJ makes a azimuthal projection of a 3D electrode cloud
% on a plane tangent to the sphere fitted through the electrodes
% the projection is along the z-axis
%
% [proj] = elproj([x, y, z], 'method');
%
% Method should be one of these:
% 'gnomic'
% 'stereographic'
... |
c4857b5336a2825b2125d0f87019febaed3ed0fa1ec7a3d82806d347c2c8c4b6 | MATLAB | 3,728 | 119 | %% estimate the PDF with 2^4 to 2^10, calculate frechet distance, and compare
%% para
path = pwd;
Modal = {'DBM','VBM'};
Type = {'smooth','nosmooth'};
NP = 2.^(4:10);
roi_num = 48;
sub_num = 444;
Fre_dis = struct;
Fre_dis1 = struct;
results = struct;
results1 = struct;
%% PDF
for itype = 1:length(Type)
for imoda... |
f921a8db27f2367bbb5e466e550d263a99d319336a20d4e44b7c32a00a20617b | MATLAB | 3,729 | 124 | % run_simulations_highFR_stdRP.m
% to generate a new set of
% 540 x 100 simulations
% (# param combos x # iter)
%%
clear all;
close all;
clc;
%% add fn paths if not added yet
% assumes script run within local directory
scriptdirs = {
'../../analyze';
'../../figures';
'../../helper_functions';
'../../simulate';
};
addp... |
1a5fd4ec2c203d6a70acc477303eed6209b447cd3858d1b973d7c263c7eb9863 | MATLAB | 3,734 | 124 | function[data,h]=SONGetMarkerChannel(fid, chan, varargin)
% SONGETMARKERCHANNEL reads a marker channel from a SON file.
%
% [data{, h}]=SONGETMARKER(FID, CHAN)
% FID is the MATLAB file handle and CHAN is the channel number (1 to Max)
% DATA is a structure containing:
% DATA.TIMINGS: a length n vector with the marker ... |
0e16fb597b8f80f3087b78c0bb9d145cd379f4384cf854eca7534fd3aae60383 | MATLAB | 3,735 | 85 | function [Best_HiddenMarkoModels, info] = HiddenMarkovModel_val_cross(HiddenMarkovModels, emision_sequence_cross, info,str_save_append)
%% Validate and select the best Hidden Markov Models (HMMs) using cross-validation.
%% authors: Stefano Diomedi
%% date: 22nd February 2024
%
%% Inputs:
% - HiddenMarkovModels: ... |
8e8828bea4f621293c9272ddff20bbe3b6b9f99a7c4e91cd785cd4078a660186 | MATLAB | 3,736 | 96 | % mglCreateTexture.m
%
% $Id$
% usage: [texture, results] = mglCreateTexture(image)
% by: justin gardner
% date: 04/10/06
% copyright: (c) 2006 Justin Gardner, Jonas Larsson (GPL see mgl/COPYING)
% purpose: Create a texture for display on the screen.
% Image should be m x n x 4... |
93b6e91ce305a78233f9de7abacb0527d22f3f62257a02a5918951d884a4274c | MATLAB | 3,737 | 43 | mouse: 'Thalamus39' %Name of mouse
date: '20160401' %Date of experiment
session: 'Emergence' %Recording session
movie: '40' %Movie within session
nucleus: 'POm' %Nucleus expressing ChR2
whiskers: 'W' %If mouse has whiskers(W) or trimmed whiskers (nW)
CSCs: [1 2 3 4 5 6 7 10 11 12 13 14 15 16] %CSCs that have good... |
28fb80a9244f7f8ed615eb22e3e1a1d80e71b121224a33fe24b81cca43d7ca25 | MATLAB | 3,738 | 106 | % ********** Setup the directory on your computer **********
clear
restoredefaultpath
filePath = matlab.desktop.editor.getActiveFilename;
root0 = fileparts(filePath);
addpath(genpath(fullfile(root0,'lib')));
root = fullfile(root0,'data');
projname = 'sphere_1';
%% Read simulation result
files = dir(fullfile(root,proj... |
b5f30ffc1bc58b783370c57004ba48c7fedfcd8f6b83bfdec5eaf33528eacab0 | MATLAB | 3,738 | 86 | addpath(genpath('.'))
%%
% name of the videos
list_Exp_ID={'Mouse_1K', 'Mouse_2K', 'Mouse_3K', 'Mouse_4K', ...
'Mouse_1M', 'Mouse_2M', 'Mouse_3M', 'Mouse_4M'};
num_Exp = length(list_Exp_ID);
% avg_radius = 10; % original_masks
avg_radius = 9; % added_refined_masks
lam = 15;
r_bg_ratio = 3;
% r_bg_ext = li... |
166bdce002ddb2072dd43a12d243b82623ff8b61fbd149c6a3f36811523840b9 | MATLAB | 3,740 | 102 | function [dat] = read_nex_data(filename, hdr, begsample, endsample, chanindx)
% READ_NEX_DATA for Plexon *.nex file
%
% Use as
% [dat] = read_nex_data(filename, hdr, begsample, endsample, chanindx)
%
% See also READ_NEX_HEADER, READ_NEX_EVENT
% Copyright (C) 2007, Robert Oostenveld
%
% This file is part of FieldTri... |
7c9b5323a0449d4338b581b2dca4c1eb7b522dd96f0aa9b58f2ceeadc8ca6d07 | MATLAB | 3,741 | 73 | % Parameters setting template
% ----------------------- Parameters set in GUI or script ------------------------
% parameters don't need to change
handles.Params.saveOutput = 1; % default
handles.Params.LapPhaseCorrection = 0; % default
% Method Dictionary
handles.Param... |
837d842130e9bd7a4a08b7ad1ee66c862d51d5bf767e33ce77a5682a3d6e07de | MATLAB | 3,742 | 104 | function [] = ExtDataFig03_BidirRespMod_Normalized()
% Code for plotting the mean change in ΔF/F after song-type transitions relative to ΔF/F before the transitions in Extended Data Fig. 3e,l.
GT = 'dPR1TN1SG';
switch GT
case 'dPR1TN1SG'
ylimrange1 = [-.3 .6];
ylimrange2 = [-.3 .6];
end
%% parame... |
d7746ccda768f541de601081e7daab188b89e9451cf782b7fef07e4c84931f0e | MATLAB | 3,742 | 96 | % getCorrCoeffBehContParam_cond_all.m
%
% Function that gets all pairwise correlation coefficients for all input
% continuous behavioral parameters, across all flies (specified as list of
% pData file names).
% Calls getCorrCoeffBehContParam_cond_fly()
%
% INPUTS:
% allBehParams - array of structs for behavioral pa... |
b1d3cc772d2b59a7ced010838beac05ab0ff7883684b64f0596856a6e4c788e5 | MATLAB | 3,745 | 92 | function data = TDMS_readFileHelper_v2(fid,optionStruct,metaStruct,paramsStruct)
%TDMS_readFileHelper_v2
%
%
SECONDS_IN_DAY = paramsStruct.SECONDS_IN_DAY;
CONV_FACTOR = paramsStruct.CONV_FACTOR;
UTC_DIFF = paramsStruct.UTC_DIFF;
STRING_ENCODING = paramsStruct.STRING_ENCODING;
%INPUT UNPACKING
%===========... |
fb163c26e17dbcf8c2ed8189625564cfce6df61a5606583bb0f0c19c0ef32fef | MATLAB | 3,745 | 144 | %Number of Model Iterations
iterations = 10000;
%Number of Mosquito Intervals
interv = [1:10];
mcount = [21:30];
%Capture PIs
SimulationOutputPI = nan(iterations,max(interv));
SimulationOutputHSR = nan(iterations,max(interv));
%Define Zones
X = [98.88;564.69;564.69;101.46;701.46;1157.59;1156.95;701.46];
Y = [68.55;69.... |
42505d5cf603ea7ba693c5cc789a2a7b1d1f1fb9f4cc7cbf2ee5c09a38c6f36b | MATLAB | 3,746 | 106 | function mvar = ft_datatype_mvar(mvar, varargin)
% FT_DATATYPE_MVAR describes the FieldTrip MATLAB structure for mvar data
%
% The mvar datatype represents multivariate model estimates in the time- or
% in the frequency-domain. This is usually obtained from FT_MVARANALYSIS,
% optionally in combination with FT_FREQANAL... |
d5e0a8c56744de31eceb2be1a67906d65ae2d6a53022703cd61ff93d89f15442 | MATLAB | 3,752 | 88 | % DERIVATIVE5 - 7-Tap 1st and 2nd discrete derivatives
%
% This function computes 1st and 2nd derivatives of an image using the 7-tap
% coefficients given by Farid and Simoncelli. The results are significantly
% more accurate than MATLAB's GRADIENT function on edges that are at angles
% other than vertical or horizont... |
218b6e316f9f8fd2dfc2485c5a64338fc8a05e4e2306c81ae1dd305b0b26a04a | MATLAB | 3,753 | 127 | function [mnv,mxv] = spm_minmax(g)
% Compute a suitable range of intensities for VBM preprocessing stuff
% FORMAT [mnv,mxv] = spm_minmax(g)
% g - array of data
% mnv - minimum value
% mxv - maximum value
%
% A MOG with two Gaussians is fitted to the intensities. The lower
% Gaussian is assumed to represent backgr... |
36c135c060494ef32c25f84b5037f273a373d9fbc72a7dac0debf37d87d1ee95 | MATLAB | 3,753 | 127 | % plotOptoFicTrac_allFlies.m
%
% Function that takes output files from extractFicTracOpto_fly() and
% generates a plot of the specified FicTrac param. Plots
% mean for each fly as well as across flies. User selects one dur, one ND,
% one FicTrac parameter, and whether to plot raw values or change in the
% paramete... |
4173e5072e61f64561d49ea78a87d35680320caa92c803b286b7aa1f4fb6d2a8 | MATLAB | 3,760 | 98 | %% fast slow trial,neron reponse on set
clear
close all
file=dir('ACC*reverse*.mat');
earlylick=[]; latelick=[];
k1=1;k2=1;
for jj=1:length(file)
load(file(jj).name)
totalevent=sort([Events.C1S3;Events.C1S5]);
fa=find(outcome(:,1)==4);
for i=1:length(fa)
cuetime=totalevent(fa(i),1... |
1cbed400f72612b0952eca3e01c6f0916330da86b488a774971a63aca512b39b | MATLAB | 3,762 | 144 | function[data,header]=SONGetChannel(fid, chan, varargin)
% SONGETCHANNEL provides a gateway to the individual channel read functions.
%
% [DATA{, HEADER}]=SONGETCHANNEL(FID, CHAN{, OPTIONS});
% where:
% FID is the matlab file handle
% CHAN is the channel number to read (1 to Max)
% OPTIONS if pr... |
43c6ca00fc7c94adb9e4ddaa0b52847f2da63745e900bddf35762c25b5d1a603 | MATLAB | 3,763 | 108 | function results = vl_test_pr(varargin)
% VL_TEST_PR
vl_test_init ;
function s = setup()
s.scores0 = [5 4 3 2 1] ;
s.scores1 = [5 3 4 2 1] ;
s.labels = [1 1 -1 -1 -1] ;
function test_perfect_tptn(s)
[rc,pr] = vl_pr(s.labels,s.scores0) ;
vl_assert_almost_equal(pr, [1 1/1 2/2 2/3 2/4 2/5]) ;
vl_assert_almost_equal(rc, ... |
632342a11a46475f494e27ce2d1d97e3660f9dea9b7e9c072aa5ad81f3909546 | MATLAB | 3,763 | 112 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
% This is the main script (for tetrodes) to compute the data tables we need to perform the
% further analysis.
close all
clear all
clc
run('../figure_scripts/load_figure_config.m')
addpath(genpath('.'));
tstart = tic;
dateTag =... |
9b0b4bf48ce0a3bb6dfd42f6d16105625fd242aeec194a42c11a80f0bc6dca9e | MATLAB | 3,764 | 116 | function [unwrappedPhase, PhaseLaplacian] = phase_unwrap_laplacian_2D(dataPhase, Params, RefVox, zp, padsize)
% [unwrappedPhase, PhaseLaplacian] = phase_unwrap_laplacian_2D(dataPhase, Params, RefVox, zp, padsize)
%================================
% HEADER
%================================
%
% Name: phase_... |
0f0c8dba1b5683332dc6a18b5f3b0f851710272d1740346ff235e1194521315e | MATLAB | 3,767 | 127 | % plotIInjFicTrac_allFlies.m
%
% Function that takes output files from extractFicTracIInj_fly() and
% generates a plot of the specified FicTrac param. Plots
% mean for each fly as well as across flies. User selects one dur, one ND,
% one FicTrac parameter, and whether to plot raw values or change in the
% paramete... |
f4b80ff98ddf5bca47d61850a4639544bad67d1b6bb9d70640c543c160f407c6 | MATLAB | 3,767 | 141 | % xcorrWGaps.m
%
% Function to compute cross-correlation when there are non-random gaps in
% the data.
% Operates on 2 input vectors. Gaps in vectors should be NaNs. Input
% vectors must have same sampling rate.
% Uses corr function to calculate Pierson's correlation for each lag, after
% removing missing data point... |
fbb3a5d8623e077027ddd7e7b2f7efebe0dac79e9a72ec7514d252b32bcd5782 | MATLAB | 3,767 | 75 | % Get header of the system information
% [ Yokogawa MEG Reader toolbox for MATLAB ]
%
% brief:
% This function retrieves information about channel in the specified file.
%
% usage:
% channel_info = getYkgwHdrChannel(filepath)
%
% arguments:
% filepath : file path
%
% return values:
% channel_info ... |
0397419767f60486dae8a05ccc28e82bf3efa6efafc28feb0f9a7271ce2646d6 | MATLAB | 3,769 | 131 | function [] = ExtDataFig05_pIP10_AveTimeCourse_OptStim_Neuron()
% Code for plotting the time course of ΔF/F recorded from dPR1 and TN1A in Extended Data Fig. 5g.
GT = 'TN1dsx';
%% parameters
nTrials = 3;
nStim = 6;
T = 1370; % T
FlightTrialThre = 3;
PreEventImg = 72; % 10 s (71.0443)
OneTrialDur = 214; % 30 s (213.... |
bb27c7273c2bad856a78e367ec87060e844c409dad0f49822e87e25fae519af3 | MATLAB | 3,769 | 110 | <<<<<<< HEAD
function [ims, imsTime, imsTime_n] = createIMS(result_f, key_f, general)
% Calculate IMS
imsTime_n = 0;
imsTime = 0;
oldID = -1;
oldID_id = -1;
i_r = 0;
% Only for matching_function == 'library'.
% I load the library for better performance
if strcmp(general.MATCHING_function, 'library') == 1
loadlibra... |
d17348c5c2a76b31f409d2800e5debfefa51aecb07f099ddc82ec3e17ab25a87 | MATLAB | 3,769 | 101 | % function fig3_source_to_xlsx(means, sems, x, pos_true, neg_true, ...
% source_data_fname, sheet_name)
%
% wrote this in an effort to fit data for all figures into one excel file
% with one sheet per figure. this is the fig 3 part.
% means is a cell wth a 2-row-array for each panel. same with sems. x just
% has on... |
627828ad4aa0fba608298f0711e29b03e8dc0850adca5c544e7397214235ac6d | MATLAB | 3,770 | 127 | % f_DesignIIRfilter.m
%
% Copyright (C) 2015, Miguel Navarrete
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any la... |
2ad8587d80db1b80f43f227b7f1b9c7b28c072b49ea6097acef6a54dfff05291 | MATLAB | 3,771 | 111 | function this = gifti(varargin)
% GIfTI Geometry file format class
% Geometry format under the Neuroimaging Informatics Technology Initiative
% (NIfTI):
% http://www.nitrc.org/projects/gifti/
% http://nifti.nimh.nih.gov/
%_____________________________________________________________... |
5b01fa039a2c7915ddedb2cc7be4e9c00aa324226053c658496220abc3cb4348 | MATLAB | 3,771 | 100 |
function [success, errorString] = IBEI_calcIBEILogHist(startFolder, outputFolder, param)
trialFiles = dirr(startFolder);
numTrials = length(trialFiles);
trialFilenames = {trialFiles.name};
idxUnderscore = strfind(trialFilenames,'_');
idxDot = strfind(trialFilenames,'.');
phaseNames = [];
c = 0;
for hh = 1:numTrials
%... |
9aaeed7980f1114173c2466785dacc631f5df40a11c2b9e9af361db45abcc72f | MATLAB | 3,771 | 84 | % dir_method = 'CNMFE'; save_date = '20221221';
% dir_method = 'min1pipe'; save_date = '20230111';
addpath(genpath('.'))
%%
% name of the videos
list_Exp_ID={'Mouse_1K', 'Mouse_2K', 'Mouse_3K', 'Mouse_4K', ...
'Mouse_1M', 'Mouse_2M', 'Mouse_3M', 'Mouse_4M'};
num_Exp = length(list_Exp_ID);
% dir_parent=fu... |
8f929e76645f23f874a796278268be5607e6f5e4be2992969623e0b5bfd67e70 | MATLAB | 3,772 | 92 | function varargout = corrTimeAndSpace(t1,t2,s1,s2,varargin)
% varargout = corrTimeAndSpace(t1,t2,s1,s2,varargin)
%
% Correlate two decompositions using both the timecourses (t1 and t2) and
% spatial profiles (s1 and s2).
%
% 2018 - Adam Charles
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
26514708854da6d44e5bdf1f80559d9f243cb09a84aaf9d3185a3cff9f278496 | MATLAB | 3,774 | 107 | classdef rpgdegibbs_s < handle
properties (GetAccess = public, SetAccess = private)
end
methods (Access = public)
function this = rpgdegibbs_s()
end
function imgdg = degibbs(this,img, dim, pf, params)
if nargin <= 4
... |
9ed45c40a63da5314bd68724d3515657f7fca684e35a5b9f8724518ae4435436 | MATLAB | 3,774 | 108 | % fictracImg.m
%
% Experimental Function
% For simultaneous acquisition of FicTrac and 2P imaging data
%
% INPUTS:
% settings - struct of settings from twoPhotonSettings()
% flyData - fly metadata from getFlyMetadata()
% exptDuration - duration of experiment, in seconds
%
% OUTPUTS:
% exptReturn - returns 1 upo... |
cb2e5a0708652ab4706301a4a6f2f73dd5f75f6ad45a3fd75cf0ba56834381f7 | MATLAB | 3,774 | 112 | function [intensities,intensities2, red_locs, s2p_median, red_cell_ids,s2p_centroids,red_ids] = findintensities_all_s2p_mask(red_wavelength_stack,Fall,redcells)
% FINDINTENSITIES_ALL_S2P_MASK uses suite2p mask outputs. Returns intensities for each red selected cell
% across pockels and wavelenths; also returns the loca... |
0ccd2063160c3fbe107714a312a982dc7db8413043888b6a080bc82d210b8b14 | MATLAB | 3,775 | 104 | function P_map = TFI_autofit(D_map, chi_est, R2starMap, maskErode, mask_LBV)
% P_map = TFI_autofit(D_map, chi_est, R2starMap, maskErode, mask_LBV)
%% Author: Xu Li
% Affiliation: Radiology @ JHU
% Email address: xuli@mri.jhu.edu
%
% Purpose:
% fit the TFI P_map functino parameters, i.e. sigma0 ,r0, sigma1, sigma... |
886c93d1d6d8b1121af41130fff9b1e5752d974e0e1d735ffda6ff5162e71cc2 | MATLAB | 3,775 | 119 | %% tdt2mat.m %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Import data from TDT system recording into Matlab structure
%
% S = tdt2mat(filepath, tank, blk, event)
%
% INPUTS
% filepath: folder where tank is stored
% tank: tank name
% blk: block name
% event: event name (ie 'Wave')
%
% OUTPUT
% data structure with... |
1f9a91ad531cfbe1d47882db343fc07bcfb728b73d27409ce5aad0409d80ab15 | MATLAB | 3,777 | 122 | function [magn] = read_ctf_sens(filename);
% READ_CTF_SENS reads MEG sensor information from CTF configuration file
%
% magn = read_ctf_sens(filename)
%
% where the returned structure meg has the fields
% magn.pnt position first coil
% magn.ori orientation first coil
% magn.pnt2 position second coil
% ... |
6e4cc04308ff6e8341ccfb9131dbf2c9c855fb4edfeacb65b5eda2fea9101f0c | MATLAB | 3,778 | 87 | % "Wire coil creator" tool for the entire coil. Models the outer surface
% of coil windings by multiple wire segments. The output is saved in the
% binary file coil.mat and includes:
% Pwire{:, 3} - set of nodes for all wires
% Ewire{:, 2} - set of edges/segments for all wires (current flows from the fir... |
07fc1ac93bf223381c52240d4a4429ddd0de343686da565912523b29581858f3 | MATLAB | 3,779 | 62 | function neur_params = check_neur_params(neur_params)
% neur_params = check_neur_params(neur_params)
%
% This function checks the elements of the struct neur_params to ensure
% that all fields are set. Fields not set are set to a list of default
% parameters. The struct checked is:
%
% - neur_params - Struct cont... |
66b785cd3aa981bb9cfcf75ec6d5e3d65f83f17f2a15d1bd44a6f5c14fce9912 | MATLAB | 3,780 | 135 | vid = VideoReader(vidName)
addpath(YourPath)
%generate mode background model
ModeBackgroundModel
%% detecting
hblob = vision.BlobAnalysis(...
'CentroidOutputPort', true, ...
'AreaOutputPort', true, ...
'BoundingBoxOutputPort', true, ...
'MinimumBlobAreaSource', 'Property',...
'MajorAxisLengthOutpu... |
8bd6cb0b326c98aaa9a3c93d9f484144c71b20690f2350171a0f2e4a5eab56c2 | MATLAB | 3,780 | 172 | function [chm, snrk] = modkurt(ch,k,p);
% Modify the kurtosis in one step, by moving in gradient direction until
% reaching the desired kurtosis value.
% It does not affect the mean nor the variance, but it affects the skewness.
% This operation is not an orthogonal projection, but the projection angle is
% near pi/2... |
62f5b007b8a95c88b2dd71a40b8c3733358a39482596c555e0a7affdda1d8ef2 | MATLAB | 3,782 | 120 | % run_simulations_pbase_vary.m
% to generate a new set of
% 144 x 100 simulations
% (# param combos x # iter)
% note: random seeds not available for this case
% (# param combos x # iter)
%%
clear all;
close all;
clc;
%% add fn paths if not added yet
% assumes script run within local directory
scriptdirs = {
'../../a... |
24c277df49444f2cb25a903fbebbf630556e6da20d33116401aa55acb099eabc | MATLAB | 3,783 | 98 | % check Eculidian distance vs monomodal EEG or fMRI connectivity
% SI Table 12
%
% 2023-10-13 Jonathan Wirsich
euclDist = getEuclidianDistanceDesikan(); %import Euclidian dstances for Desikan fsaverage
vec_ED = model.Connectome.getLoopedVec(euclDist);
[confs, confs_label, groups, eeg_conn_types, bands, atlases, seria... |
758f3a49088bae26f0ec25656cf5a9a7ee5ca0599e3b67ba3fe993f2d9c5cd61 | MATLAB | 3,783 | 104 | % 4th model space
MS_name = 'MS_FADE_04';
MS_axis1 = {'PE', 'TD'};
MS_axis2 = {'00x1', '00x2', '0x1', '0x2', '1dd-ip', '1dd-cp', '1dd-lr', '1th-l', '1th-a', '1th-s', '2nf', '2nr', '2ns', '3', '5'};
GLM_names = cell(numel(MS_axis1)*numel(MS_axis2),1);
for i1 = 1:numel(MS_axis1)
for i2 = 1:numel(MS_axis2)
... |
7c98954fb68284cc758855ea0ca0dafed2fd02e4910c54f1bdd976260b2d50f8 | MATLAB | 3,789 | 117 | function getNODDImaps(pathIn,pathbval,pathbvec,pathMask,folderOut,Basename,NODDImodel,NODDIfix,NODDIval)
% Fit and get NODDI parameter maps
%
% pathIn: path to dwi (.nii) file
% pathbval: path to bvalues (.bval) file (FSL style)
% pathbval: path to bvectors (.bvec) file (FSL style)
% pathMask: path to mask (.nii)... |
5257bda505246408d9898416c194abba69969615de8590c5cd3389a6f3fffa99 | MATLAB | 3,790 | 111 | classdef MLCaiNeuron < handle
properties
spatial_footprint;
spikes
trace_filt;
trace_raw;
timestamps_ms;
%calciumEvents; % computed from the time series
numTimeSamples;
neuronId; % Its number in the neuron.hdf5 file
end %... |
e6d606a97726ee9d8ed3221af7bb5e0e90edb18fca4628f4e8bb43b72d6b0b8e | MATLAB | 3,790 | 145 | tic
%% open/read file and set up Environment
activateCEDS64
WAVELENGTH = 999;
file = 'Z:\1_Maxwell_Gagnon\ProjectData_Ruth\191217\191217_VSFP_Mouse_1_x2_VOR.smr';
fhand1 = CEDS64Open(file);
% Drum Position
[ ~, sineWave, ~ ] = CEDS64ReadWaveF(fhand1, 3, 600000000, 0);
% FLUOR Signal
[ ~, chan11, ~ ] = CEDS64ReadWaveF(... |
447241685d470cef23be5475343b0646fee9d057c1c3b4b45c6c08efc5f12eca | MATLAB | 3,794 | 107 | function [SUMtable, SUMarray, SUMtableCell] = Summary(iSes,nose,SUMtable, SUMarray, SUMtableCell)
globals;
SUMtable(iSes).iSes = iSes;
SUMtable(iSes).Sesname = Sesname;
SUMtable(iSes).mouse = Tagging.mouse;
SUMtable(iSes).date = Tagging.date;
SUMtable(iSes).mouseNo = Tagging.mouse(end-1:end);
SUMtable(iSes).nu... |
f7c9227ee960967ff8da79b02e8df8f7eb3989b07be4c9f6aacf30e9d742eefb | MATLAB | 3,795 | 94 | % looks at overlap between nnUNet output and a hippocampal mask generated
% via affine to CITI168. Note most of the time these will already be affine
% registered but not when the --rigOnly flag was used (ie. in TSE data)
%% ASHSatlas (7T-TSE)
addpath(genpath([getenv('AUTOTOP_DIR') '/tools']));
ref_mask = [getenv('AUT... |
75d9c2a425346637f9459e07264caf4b5aa74c9ea98d9ffe06ff65b6189f11d3 | MATLAB | 3,798 | 100 | addpath('funcs');
% [r,v,g] = once(0.3, 0.015, 0.02, 2000);
p_base = [0.1184, 0.1552, 0.0846, 0.0629, 0.0323, 0.0000, 0.0076, 0.0000;
0.1008, 0.1371, 0.0363, 0.0515, 0.0755, 0.0000, 0.0042, 0.0000;
0.0077, 0.0059, 0.0519, 0.1453, 0.0067, 0.0003, 0.0453, 0.0000;
0.0691, 0.0029, 0.1093, 0.1... |
379190ebc252211450a4ba07b600a6f0da16a3cb5b5388c86957c686a9c8e6a1 | MATLAB | 3,799 | 103 | % function invcompE(tol,N)
%
% Return metrics relating to receiver operator characterics (ROC) for
% Eventer output. The invcompE function must be run within an
% eventer.output/Data_chX_wavename directory. The root directory of the
% original eventer analysis should contain a text file called
% 'EventTimes.txt' or Ev... |
696974543cc0df82e2708f63f88b37445aed6365bff3dcca0e9ec79683f97d04 | MATLAB | 3,799 | 147 | function [chi_M, chik_tkd] =SFCR_m_SB(deltaB, D_k, DPWeight, maskErode, maskSS, wG, lambdaSet, itermax, thred)
% [chi_M, chik_tkd] =SFCR_m_SB(deltaB, D_k, maskErode, maskSS, wG, lambdaSet, itermax, thred)
% SFCR M-step using Split-Bregmen L1 solver
%
% Input: deltaB, D_k, maskErode, maskSS, wG, lambdaSet, itermax, ... |
0797a17e4702306696aa148b08703c5475c038cd780d0fae2f87f1ec76a11dd8 | MATLAB | 3,802 | 128 | function[data,h]=SONGetEventChannel(fid, chan, varargin)
% SONGETEVENTCHANNEL reads an event channel from a SON file
%
% DATA{, H}]=SONGETEVENTCHANNEL(FID, CHAN{, START{, STOP{, OPTIONS}}})
%
% FID is the matlab file handle and chan is the channel number (1-max)
% If START/STOP are absent, all data is read. When presen... |
d393ef814106df69fb7511b381e8289fbe9524093e268aef0f6c79d8a9911e15 | MATLAB | 3,802 | 108 | function [H,details] = vl_harris(I,si,alpha)
% VL_HARRIS Harris corner strength
% H = VL_HARRIS(I,SI) computes the Harris corner strength of the image I
% at ``integration'' scale SI.
%
% The Harris strength [1] of a pixel is a statistic of the gradient
% of the image integrated in a neighborhood of that pixel. Th... |
aeb4b86aea8abd013b55957e8647dc53c6bebbe351954170964ffa9305bb40b7 | MATLAB | 3,803 | 78 | function subject_FD_parse_BIDS(FD_movement_files,skip_seconds,epi_TR,brain_radius_in_mm,result_dir,output_prefix)
% Code from OHSU Fair Neuroimaging Lab
% Written (2014) and commented (9/8/2015) by Eric Earl
%
% FD parsing Nipype wrapper pulling in list of motion files
%
% Modified to read (and ignore) DVAR_pre_reg, ... |
e88ab09c6abb79d2990d061d79a3489094258360d47dfd3f9b1623d078b6a6e7 | MATLAB | 3,805 | 94 | function [gp_vals] = masked_3DGP_v2(grid_sz, l_scale, p_scale, mu, bin_mask, threshold, l_weights)
% [gp_vals] = masked_3DGP_v2(grid_sz, l_scale, p_scale, varargin)
%
% This function draws from a 3-D GP with mean mu, length-scale l_scale and
% variance scale parameter p_scale. Basically it returns a volume X, where
%... |
59c12184c4f0687c12a991d968c1e4a1e9c120113bd8f5f6487de1774e206d54 | MATLAB | 3,808 | 77 | classdef AlignedDynamicTable < types.hdmf_common.DynamicTable & types.untyped.GroupClass
% ALIGNEDDYNAMICTABLE DynamicTable container that supports storing a collection of sub-tables. Each sub-table is a DynamicTable itself that is aligned with the main table by row index. I.e., all DynamicTables stored in this group M... |
527afb7b7fd17092c9280b75de878b697e62be8e3eca7e1141058bf788743201 | MATLAB | 3,810 | 94 | function cfg_artifacts=st_expand_artifacts_to_segments(cfg_artifacts)
% ST_EXPAND_ARTIFACTS_TO_SEGMENTS expands artifacts from bad channels across segments
%
% Expand artifacts across all segments of channel when proportion of unrejected artifacual segments >= badchannelthresh
%
% Use as:
% cfg=st_expand_ar... |
1505fb9ebae9d84ab2032c5054d592c42ba01c1fe5ff673f331b3a102e33436b | MATLAB | 3,816 | 87 | function [I Q F]=motif4funct_wei(W)
%MOTIF4FUNCT_WEI Intensity and coherence of functional class-4 motifs
%
% [I Q F] = motif4funct_wei(W);
%
% Functional motifs are subsets of connection patterns embedded within
% anatomical motifs. Motif frequency is the frequency of occurrence of
% motifs around a no... |
5a549faa5cb8add72832f7a5b04d3c00dad2e2aa52b131c020d5070ab503a24c | MATLAB | 3,816 | 163 |
function [layers, net_output_info, dag_net]=gen_network_featnet_imgraw(featnet_config)
dag_net=dagnn.DagNN();
start_var_name='data_input';
layer_gen_info=[];
layer_gen_info.one_output_dim=3;
layer_gen_info.one_outputs={start_var_name};
layer_gen_info=do_add_img_input_scratch_path(dag_net, featnet_config, layer_ge... |
7457084ddfabe2cfaba223b960aeaea492354012dd13374a89b6cb92b321c70c | MATLAB | 3,818 | 76 | function [GDPIndex, GDP_Onsets, GDP_Offsets, data_sorted, options] = detectGDPs(data, Nrois, options)
% This functions detects GDPs from Ca2+ transient (CaT) times as obtained from multi-neuronal Ca2+ imaging.
% ==========================================================================================================... |
244e38873047d6b481578600f8b9cb8a79ec2f84daeefc736e75a1e1511e2d5e | MATLAB | 3,819 | 139 | % mglDispVisualAngleDiscrepancy.m
%
% $Id:$
% usage:mglDispVisualAngleDiscrepancy()
% by: justin gardner
% date: 03/29/10
% purpose: Display the discrepancy between what you ask for and what you
% get in terms of visual angle based on current settings
% of mglVisual... |
6f26e985f60c916d63daa8ee8d6d782ee90ea937fe5b2fcaece85f5fa3b9de3c | MATLAB | 3,822 | 107 | function [] = Fig01_BidirRespMod_Normalized()
% Code for plotting the mean change in ΔF/F after song-type transitions relative to ΔF/F before the transitions in Fig. 1j,m.
GT = 'dPR1NPTN1SGNP'; % Fig. 1j,m
switch GT
case 'dPR1TN1SG'
ylimrange1 = [-.3 .6];
ylimrange2 = [-.3 .6];
case 'dPR1NPTN1... |
0b62213ad239f7eabba24cf57b6db8ee6277578396ac215f185706c285d624eb | MATLAB | 3,824 | 82 | %%% THIS CODE PERFORMS THE FOLLOWING FUNCTIONS:
% 1. Extracts LFP data for each experiment of interest
% 2. Identifies individual channels as bad based on user defined RMS voltage, ignores these as well as internal reference channel, and also removes sync channel
% 3. Saves processed LFP data together with processin... |
62c16e2ac680a9dc5b628574bacd4d15d9c927f18ff75523ca5c3a32cc97896d | MATLAB | 3,825 | 78 | function filtStreaming ( obj, fs, data_type, filterType, order, varargin )
% Filter LFP signal from streaming recordings
%
% Syntax:
% FILTSTREAMING( obj, fs, filterType, varargin );
%
% Input parameters:
% * obj - object containg data
% * fs - sampling frequency
% * filterType - type of filter selected
% ... |
b5c1c410dd8108e8f7333f0e2a8fefadb68572f82ebbed384864b1ec6c09766d | MATLAB | 3,826 | 102 | %Calculate cluster correction for a F-observed and the permutation
%distribution
%
%EXAMPLE USAGE
% >> [h, p, clust_info, est_alpha] = Fclust_corr(F_obs, F_dist, 0.05, chan_hood, 3.84)
%
%REQUIRED INPUTS
% F_obs - An electrode x time points array of observed F-values
% F-dist - A permutation x ... |
c83088d346f414934a90bfb75929d65fe639762222e16de0b2ce2e124528c122 | MATLAB | 3,828 | 148 | function varargout=stitchedPlanesToVolume(channel)
% Write stitched image planes from a channel to multi-page TIFF
%
% function fname=stitchedPlanesToVolume(channel)
%
% PURPOSE
% All planes of one channel to a multi-page TIFF. Only a good idea for smaller datasets.
% For larger datasets see resampleVolume.m
%
%
% INP... |
1c56152c5e316961a0c1282221085049d25b85bea7968a231fee16af657ba2a7 | MATLAB | 3,829 | 112 | function [renumId] = SolvingTSP(target_new)
%SOLVINGTSP target_newðxz½Êɨ¢ÄߢÉÔðUèȨ·Ö
% Ú×à¾ð±±ÉLq
nStops = size(target_new,1);
stopsLon = target_new(:,1);
stopsLat = target_new(:,2);
idxs = nchoosek(1:nStops,2);
dist = hypot(stopsLat(idxs(:,1)) - stopsLat(idxs(:,2)), ...
... |
6193f727a58fb8c123dc3eeef8edefc60be9d582059fe5496e172efe6357a45b | MATLAB | 3,829 | 126 | % run_simulations_stdFR_stdRP.m
% to generate a new set of
% 540 x 100 simulations
% (# param combos x # iter)
%%
clear all;
close all;
clc;
%% add fn paths if not added yet
% assumes script run within local directory
scriptdirs = {
'../../analyze';
'../../figures';
'../../helper_functions';
'../../simulate';
};
addpa... |
a56df3c5f1c558ce2fb1f2d3bedd7564ca6c8e76ffb48cca786cf4b3dc13017e | MATLAB | 3,832 | 119 | %
% Diagonality plots.
%
% PARAMETERS
% $NETWORK
% $DECOMPOSITION
%
% INPUT
% dat/decomposition_split.{source,training}.$DECOMPOSITION.$NETWORK.mat
% dat/decomposition_split.training.sym.$NETWORK.mat
% dat/split.$NETWORK.mat
% dat/means.$NETWORK.mat
% dat/info.$NETWORK
%
% OUTPUT
% plot/diagonality.{self,base}.[a]... |
b4e85b34f9117a963e9358ca0f003f06be65a2395da8302a0e636a37b9e0d67b | MATLAB | 3,832 | 85 | function fH = makeFigure6_PRFModelFits(ds,roisToPlot,spatialModel,temporalModel,saveFigs, saveFigDir)
% Function to reproduce main manuscript figure 6:
% panel a/b: V1 & VO1 time series + LSS, CSS, CST model prediction for each stimulus condition
% panel c: violin plots showing cross-validated R^2 for LSS, CSS, CST m... |
aeb8168a4d5691c43894929631cd878f078847589d885f0a19d5b8033bc9d127 | MATLAB | 3,833 | 126 | % run_simulations_stdFR_RPk0nr3.m
% to generate a new set of
% 540 x 100 simulations
% (# param combos x # iter)
%%
clear all;
close all;
clc;
%% add fn paths if not added yet
% assumes script run within local directory
scriptdirs = {
'../../analyze';
'../../figures';
'../../helper_functions';
'../../simulate';
};
add... |
33880a0dd559e29e2e45b3aba0bc1213124ee06fdb16e9faf83cb9454a55f7ae | MATLAB | 3,834 | 99 | function memStats = memoryInfo()
% Cross-platform function to get memory usage
%
% @author Sviatoslav Danylenko <dev@udf.su>
% @license BSD
%
% Return values:
% memStats: memory info @type struct.
%
% The following is the fields of memStats:
% free: the amount of free memory in ... |
8d3385c9207151f2ceb2d4951d45ba7c86ac657b4c616f06f33951f0d89ecf4d | MATLAB | 3,836 | 116 | clear; close all;
subs = ls('datasets/HCPaging100/hippunfold/');
subs = strsplit(subs)';
subs(end) = [];
subs(74)=[]; % this subject seems to be missing from subjects_info.csv
%subs(31)=[]; % missing from ashs
subs(51)=[]; % this subject seems to be missing from subjects_info.csv
%% load all data
T = readtable('dat... |
b140dea8a3be6468653eb5527496b1d924cd6cc47aa4ee113057642a50daa1e1 | MATLAB | 3,837 | 126 | % run_simulations_stdFR_RPk0.4nr4.m
% to generate a new set of
% 540 x 100 simulations
% (# param combos x # iter)
%%
clear all;
close all;
clc;
%% add fn paths if not added yet
% assumes script run within local directory
scriptdirs = {
'../../analyze';
'../../figures';
'../../helper_functions';
'../../simulate';
};
a... |
ee5d489d2d9730ffcb4d42f87f387025993e653e9a5d3d6eb8ca049528de6969 | MATLAB | 3,837 | 92 | function data = TDMS_readFileHelper_v2(fid,optionStruct,metaStruct,paramsStruct)
%TDMS_readFileHelper_v2
%
%
SECONDS_IN_DAY = paramsStruct.SECONDS_IN_DAY;
CONV_FACTOR = paramsStruct.CONV_FACTOR;
UTC_DIFF = paramsStruct.UTC_DIFF;
STRING_ENCODING = paramsStruct.STRING_ENCODING;
%INPUT UNPACKING
%... |
769f45d8d1fc18588e35bb427b08ebf87a0cdd94c78e267c9f4bb1bb8a0736a0 | MATLAB | 3,838 | 143 | % results = eyeAnalysis
% Run this to eye track on saved image files
% Adds to a results structure that already has time info
% to do - have ROI picked automatically based on pupil radius size, and
% move with pupil
%% Parameters - try changing if needed
load settings
prevsettings = 1;
% Shouldn't need to change unl... |
02b2d46e6cdc6600ae1b41802fb5f8132faeaab0a227e6686413b02e82b18292 | MATLAB | 3,840 | 101 | %% early/late trial,neron reponse onset
clear
file=dir('ACC*uncertain*.mat');
earlylick=[]; latelick=[];
k1=1;k2=1;
for jj=1:length(file)
load(file(jj).name)
totalevent=sort([Events.C1S3;Events.C1S5;Events.C1S12]);
hit=find(outcome(:,1)==1);
for i=1:length(hit)
cuetime=totalevent(hit(... |
a8817b082f8fb3e4e9c2b353c7497d8ed353985b0f283b68c539922a3a8843bf | MATLAB | 3,840 | 126 | % run_simulations_stdFR_RPk0.7nr18.m
% to generate a new set of
% 540 x 100 simulations
% (# param combos x # iter)
%%
clear all;
close all;
clc;
%% add fn paths if not added yet
% assumes script run within local directory
scriptdirs = {
'../../analyze';
'../../figures';
'../../helper_functions';
'../../simulate';
};
... |
a04325473d9a4713deafa18082c27f42a5851f5020ec0d73b8dd2412bd5a3a74 | MATLAB | 3,841 | 129 | %
clear,clc;
ShapeSurfPath = '/media/data2/Epilepsy_Shape/Templates/Shape_Surf';
ShapeStatisticPath = '/media/data2/Epilepsy_Shape/Data/Shape_Statistics';
%% Load Summarized Shape Features
LogJacs_csv = importdata('/media/data2/Epilepsy_Shape/Data/Shape/LogJacs_all.csv');
Thick_csv = importdata('/media/data2/Epilepsy_... |
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