sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
5fa52a37fb76cd4971d1409d6bcbf4f2d5b42a89767704073b0c911c8528a2e8 | MATLAB | 4,136 | 87 | function [] = Fig03_Bidir_TN1dsx_Normalized()
% Code for plotting the mean change in ΔF/F after song-type transitions relative to ΔF/F before the transitions in Fig. 3e,g.
%% parameters
T = 1370; % T
Thre_Trans = 6;
Thre_SongType = 0.05;
Thre_Pre = 0.1;
%% Song-type preference index (dPR1, TN1SG)
load(['../Data/Summa... |
767f57968137b704d93a9be1896479d3750a7e96859ad406c90eb4ab30f272cf | MATLAB | 4,136 | 155 | % f_GetBniSignals.m
function [str_SignalsStr s_SigNum s_Scale s_SRate v_IniTime] = ...
f_GetiSignalHeader( ...
p_strBniName, ps_IsBinType)
if nargin < 1
return;
end
if ~exist('ps_IsBinType', 'var') || isempty(ps_IsBinType)
ps_IsBinType = 0;
end
if ~p... |
9806f7ec8c6a3f8b677a2e154860090ee0bc8972e196c20a1d648926c99a0409 | MATLAB | 4,140 | 153 | %SF3
load('Y:\Christian\Processed Data\Event Analysis\standard_ds_onsets.mat')
%% MAKE FIGURES B,C,D
[rate_mch_events,rate_tdt_events,rate_ex_events,durations]= supplemental_report_events (ds_events,2,'ratio');
%% FREQUENCY STATS
%%-- Frequency stats
mt=signrank(rate_mch_events,rate_tdt_events);
me=signrank(rate_mc... |
075ff8043f4388c2deca1ba99c48cbcb80c266e389bd5c76db1dc9f65b9b5b57 | MATLAB | 4,146 | 75 | % not used in paper
folder_name = uigetdir
cd(folder_name) %open the directory of image sequence
allFiles = dir(); %get all the tif files
fps = 14;
pirouetteCount = 0;
tracksByVoltage = struct('maxVoltage', {}, 'LEDVoltages', {}, 'reversalCounts', {}, 'frameCounts', {});
for file_index = 1:length(allFiles)
if allF... |
c28c0a1e399819e57cab9c1797833a8a763349068a29abf7c4734d7d3680ea82 | MATLAB | 4,146 | 135 | function [T_count, list,text_counts,text_missing] = scout_bids_for_gui_env(root_path,varargin)
%% [T_count, list,text_counts,text_missing] = scout_bids_for_gui_env(root_path,varargin)
% Oscar Miranda-Dominguez
% First line of code: Aug 31, 2020
%
% Use this function to extract a list of potential subjects with eno... |
00b79598dbc2ab28babb85abe4d3e7219600bcddb163f736fac2deaebf43c66a | MATLAB | 4,147 | 104 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
% This makes the paper's Figure 4B, which are the cumulative popvector
% curves for across and stability for days 1,2 and 3.
% The figure was post-processed to match the style of the paper.
close all
clear
clc
% Paths
run('../load_f... |
64e6e43cac8f8f33a5ad5967f4629a0575d66bf9923a102979b17a281326c3b8 | MATLAB | 4,147 | 115 | %% Author: Jiri van Bergen and Xu Li
% Affiliation: Radiology @ JHU - Kirby Center
% Contact via xuli@mri.jhu.edu
% Updated 2019-07-09 X.L.
% Updated 2021-06-16 X.L., improved memory efficiency
% Updated 2021-06-24 X.L., cluster version
% Updated 2024-06-07 X.L., for cluster array
%% Start processing of mult... |
98c3e2c9015fef1d91d7c06c5d3eb41104da675929739fc7ef7e8333c223c31b | MATLAB | 4,147 | 122 | function [pntr, trir] = refine(pnt, tri, method, varargin)
% REFINE a 3D surface that is described by a triangulation
%
% Use as
% [pnt, tri] = refine(pnt, tri)
% [pnt, tri] = refine(pnt, tri, 'banks', selection)
% [pnt, tri] = refine(pnt, tri, 'updown', numtri)
%
% If no method is specified, the default is to r... |
31e818393b052cdbf087c6103c8a9d4ec467ceadd8f7b55afc5e974ec94558a5 | MATLAB | 4,148 | 144 | %
% % make figure on formin,
% % threshold 1.15
% %
clear all
%%
excelname='Fig1D_1H FMNL1 precedes Arp3';
experiment='Fmn_arp_c1';
channel1 = readmatrix(excelname,'Sheet','Channel1');
timeinterval=readmatrix(excelname,'Sheet','time interval');
script_BatchProcess_IPI
p2p_allconditions{3}=p2p_all_as_matrix;
intensi... |
7430ae122ab31a3dfbd6c81023a396037f1fad23f56e473a67dbe20e30bc58e4 | MATLAB | 4,149 | 124 | % this script create 2-d slices for 3d scatter
% 3 dimensions are: DeltaE (x), DeltaI (y), and Isens(z)
clear;
clc;
close all;
rootFolder = "figure_40_diff/";
% ON-ON
data = readFilename(rootFolder+"asAllCriteria/*_*_*_*.png",'%f_%f_%f_%f');
data( all(~data,2), : ) = [];
diff = 10;
idx = data(:,4) < diff & data(:,4) >... |
cc6b08cc0e962bc4f0404ebca57caca3133479f03342e6e2a11d79ec71508270 | MATLAB | 4,150 | 92 | function ms = men_msGenerateVideoObj(dataFolder, scopeFilenamePrefix, scopeFilenameSuffix, timestampFilenameSuffix, timestampFilename, settingsAndNotesFilename, MAXFRAMESPERFILE)
%MSGENERATEMS Summary of this function goes here
% Detailed explanation goes here
ms.dataFolder = dataFolder; % Added by GE to keep tr... |
19247e911c97abdeeed2a274eb3558e522534690a4fc2ef0f1bdcc0b25a62b5a | MATLAB | 4,151 | 108 | function STS = rmap(spikes,y,y2,STS);
% updates the STS global struct: STS.sts[], response map
% input:
% x, spike frames,
% y, variable binned along x-axis
% y2, variable binned along y-axis
%
%% ?REPLACE WITH?: (see trajPlot - works fine there!!)
% STS = function Rmap2(uspikes,X,Y,STS)
% Smap = zeros(yNbi... |
a73ae93bd40cd97186ee43b85dde4adc81aa366a5aeec9b90813a7ea5635b287 | MATLAB | 4,152 | 102 | function [Ci Q]=modularity_und(A)
%MODULARITY_UND Optimal community structure and modularity
%
% Ci = modularity_und(W);
% [Ci Q] = modularity_und(W);
%
% The optimal community structure is a subdivision of the network into
% nonoverlapping groups of nodes in a way that maximizes the number of
% within-gr... |
6ad10e6fcb59c84f0dafa384f43381fe6ac86f4cc878053f31fd9a18a28c229d | MATLAB | 4,153 | 122 | gcp;
addpath(genpath('.'))
addpath(genpath(fullfile('..','ANE')))
%%
% 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);
rate_hz = 20; % frame rate of each video
th_IoU_split = 0.5;
thj_incla... |
478bbbdb41541fc21091a4c7e47af843fd52a4feafe8c23ba02a2a82201f598f | MATLAB | 4,154 | 131 | % Radial_Sym_Transform - Loy and Zelinski's fast radial feature detector
%
% An implementation of Loy and Zelinski's fast radial feature detector
%
% Usage: S = fastradial(im, radii, alpha);
%
% Arguments:
% im - image to be analysed (after using imread for example:im=imread('lenna.jpg');)
% ra... |
c52fd3883b4384678eee7a32808ed1538c6dcb2004de6499be2415ff5e20452f | MATLAB | 4,156 | 108 | classdef SpatialSeries < types.core.TimeSeries & types.untyped.GroupClass
% SPATIALSERIES Direction, e.g., of gaze or travel, or position. The TimeSeries::data field is a 2D array storing position or direction relative to some reference frame. Array structure: [num measurements] [num dimensions]. Each SpatialSeries has... |
e210320f718d2997dbaf1f8d7781ad3d698f78b29994dbd7a07949c0720345ec | MATLAB | 4,156 | 82 | function write_nifti2_hdr(filename, hdr)
% WRITE_NIFTI2_HDR
%
% Use as
% write_nifti2_hdr(filename, hdr)
% where
% filename = string
% hdr = structure with nifti-2 header information
%
% See also READ_NIFTI_HDR, READ_CIFTI, WRITE_CIFTI
% Copyright (C) 2013, Robert Oostenveld
%
% This file is part of Fi... |
c591b59d688821fd009b0ddbc3e5eb0f7377ae6505b4c37082c9ac6696a86e73 | MATLAB | 4,157 | 141 | function A=blockModelSampler(W,S,k)
% blockModelSampler Sample adjacency matrix for degree-corrected block-model
%
% Syntax
%__________________________________________________________________________
%
% A=blockModelSampler(W,S,k)
%
%
% Description
%____________________________________________________________________... |
70d08e2fae54e9f8fc486865ded4c601d3f760feaeb5d401135002a5d901b876 | MATLAB | 4,161 | 84 | function fH = plotLMMregressionSlopes_v_pRFsemisat_stRetParams(allLMMResults, ...
params, roisToPlot, cmapROIs, saveFigs, saveFigDir)
% Function to plot LMM regression slopes against DN-ST pRF semi-saturation
% constant (Supplementary figure 9 in the paper:
% Title: Rethinking simultaneous suppression in visual ... |
fdebfefb878ea81b47bdbf081d3f1b6124b96d9d441a8e68b49412c6f2044aca | MATLAB | 4,162 | 117 | %runsta
%run STA on units of one session
% check consistency between all movies of that session
%add:
% b. Check consistency across movies
% i. elecunit (all spikes from each elec)
% ii. bundleunit (all spikes from all elec)
clear all;
globals; initglobals;
DEBUG=1;
PRINT_ERRORS = 0; PRINT_INFO=0; PRINT_NAN... |
c43d59f68f5eb6dd61700eb0e35232822f1c8124be035453c7f9731a10bc3092 | MATLAB | 4,163 | 86 | function sigline_v2(xs,lbl,ymax)
%%% 2024 NOTE: this is a slightly modified version of the 'sigline'
%%% function originally authored by bethel osuagwu:
% (https://uk.mathworks.com/matlabcentral/fileexchange/68314-statistical-significance-line)
% Copyright (c) 2018, bethel osuagwu
% All rights reserved.
%
% ... |
9ee925c3098d84e5fba93e57e86fa8d85eae41e4e7cb6e2d10d6c52d8891e575 | MATLAB | 4,164 | 131 | function [outcomes] = get_pop_sparseness_before(ds_events,ex_thresh,time_bin,before)
%%
% Gives sparseness based on period of time after
% OUTPUT:
% Outcomes:
% -
%%
for d=1:12
cur_onsets=ds_events(d).onsets;
[rand_resp,pv_resp,som_resp,som_onsets,pv_onsets,ex_resp,ex_type] = extract_onsets(cur_onsets,d... |
1b5e7925b717aa5181e9b47c40ec792215da03d3a83f9fc18abe55ea72092247 | MATLAB | 4,166 | 161 | function obj=matPlot(a, opt);
% matPlot: Display a matrix in a figure window
%
% Usage:
% matPlot(mat, opt);
%
% Example:
% % === Example 1
% opt=matPlot('defaultOpt');
% opt.matName='Magic matrix of size 10';
% figure; matPlot(magic(8), opt);
% % === Example 2
% opt=matPlot('defaultOpt');
% opt.matName='Random... |
a515fdb14f2738af1bc3d210e1f1af4cd4a7665b4a66d8218f41da6cada292c7 | MATLAB | 4,170 | 127 | % written by Marge Maallo, 15/11/2021
% CSAN, LiU
% read response mat files for each subject and perform SVM classification
% return confusion matrix
% edited by Marge Maallo, 19/11/2021
% read in scaled timeseries
% edited by Marge Maallo, 23/11/2021
% do 10 repeats so we can get an estimate eg SEM
% edited by M... |
03fedd44dc2a4016319817d4e2bb2e4ce4d25ca5996df1fa00d6a83e3d2f9034 | MATLAB | 4,171 | 156 | %
% Plot the spectrum over time.
%
% PARAMETERS
% $TYPE "full" or "split"
% $NETWORK
% $DECOMPOSITION
%
% INPUT
% dat/decomposition_time.$TYPE.$DECOMPOSITION.$NETWORK.mat
% dat/decomposition_time_runtime.$TYPE.$DECOMPOSITION.$NETWORK
% dat/stepsi.$NETWORK (full only)
% dat/steps.$NETWORK.mat (split only)
%
% OUTP... |
d7c8287ba46aab48874ae2ab3e039844a5e2387037ee0dd9a21578497f58ee56 | MATLAB | 4,171 | 158 | function [dat] = read_nexstim_nxe(filename, begsample, endsample, chanindx)
% READ_NEXSTIM_NXE reads specified samples from a NXE continous datafile
%
% Use as
% [hdr] = read_nexstim_nxe(filename)
% where
% filename name of the datafile, including the .bdf extension
% This returns a header structure with t... |
d7a0d85758192d085118bc59fd0179076ad854fbf297aa243107537eceed51e8 | MATLAB | 4,177 | 143 | % plotNormAEPPEP_allFlies.m
%
% Function that takes output files from saveAEPPEPbyCond_fly() and
% generates a plot of the AEP or PEP for each leg, normalized to the
% unmanipulated condition. Plots mean +/- SEM for each fly. Subplots for
% each leg (left legs on left, front legs on top)
% Select output files throu... |
ecc38b8a265400d4d9dd37e54133fa33187a45df329fc4fd527b68c96cdfbbf2 | MATLAB | 4,177 | 124 | %% Needs to be Manually Edited Every Time!
pID = 'MG112';
data_dir = ['C:\Britni\Data\' pID];
cd(data_dir)
filename = 'network_raw';
subj_dir = [data_dir '\' filename];
%% Initialization and Data Porting (BCD)
% If something goes wrong, you're probably in the wrong folder
mkdir(subj_dir)
files = {'01... |
baac60b6908fde9041a4b32896dc0f6dab7a3744e482c7d2198838ab2159b15e | MATLAB | 4,178 | 75 | % not used in paper
%folder_name = uigetdir
cd(folder_name) %open the directory of image sequence
allFiles = dir(); %get all the tif files
fps = 14;
pirouetteCount = 0;
tracksByVoltage = struct('maxVoltage', {}, 'LEDVoltages', {}, 'reversalCounts', {}, 'frameCounts', {});
for file_index = 1:length(allFiles)
if al... |
cdded100ec2147b8f4f2ca1c08aad2d4110c07b72f9df8437c2b589189602250 | MATLAB | 4,180 | 136 | %Benjamini Hochberg correction
clear all
clc
load('M:\Matt Chilvers\Documents\PhD\Project3_WhiteMatterLesion\Scripts\Plots\ScatterPlots\FinalRegressionAnalysis\Final\lm_data.mat')
%load('/Users/dukelowlab/Library/CloudStorage/OneDrive-UniversityofCalgary/PhD_Projects/Project3_WhiteMatterLesion/Scripts/Plots/Scatt... |
654ba5036f89a97cfec0b62d8549b25c86d89261b4124c66edc43625c199b357 | MATLAB | 4,183 | 121 | %Test FclustGND function
%
%AUTHOR: Eric Fields
%VERSION DATE: 12 June 2020
global test_xls_output;
if isempty(test_xls_output)
test_xls_output = true;
end
%Load a GND for testing
%Load a GND for testing
FMUT_dir = fileparts(fileparts(which('C_FclustGNDTest')));
load(fullfile(FMUT_dir, 'testing', 'da... |
f0d1982cb7005c93db27c29dd67c736cbef231181d8b1b51fe0205502e2fba8e | MATLAB | 4,184 | 88 | % recoverStimData.m
%
% usage: recoverStimData()
% by: justin gardner
% date: 04/29/08
% purpose: Run this function if you accidently stopped your
% stimulus program while it was running (or the program
% crashed) and you are at the debugger prompt K>>). This
% will spit out some lines of... |
864428d7c3fd50af7ad9d339141879e748afa6744c13e650e017d4ebb81ee302 | MATLAB | 4,191 | 113 | function [select] = parameterselection(param, data)
% PARAMETERSELECTION selects the parameters that are present as a volume in the data
% add that have a dimension that is compatible with the specified dimensions of the
% volume, i.e. either as a vector or as a 3D volume.
%
% Use as
% [select] = parameterselection(... |
e2529f28fd39457056e011cc344abb81b6dc9a01cfaaa7167840037bda4229b1 | MATLAB | 4,194 | 115 | function result = DNmodel(param, prfResponse, useGPU)
% Function to predict neural response to time course using the Divisive
% Normalization (DN) model
%
% result = DNmodel(param, stim, t)
%
% INPUTS -----------------------------------------------------------------
% params : (struct) should contain the follow... |
5abce39580e1a2d412dc954fc9dabf22ee71392b40613bd3804e5f501807c0e7 | MATLAB | 4,196 | 102 | %clear PSTHarr tookthese
function [PSTHarrNew,markFP,markFPfr]=FPpsth(camtime,timeFP_RS,timeFP_frames,dfofCorr,evTime,J,K,p,q,S,Norm)
%J=500; %pre
%K=500; %post
%p=299; %start baseline J-p
%q=50; %end baseline J-q
%S=K; %skip this many after last event
for i = 1:length(evTime);
FPx(i) = find(timeFP_RS>camtime(... |
c67615f568c2caa295feb6f9ce2ba565047cf904118e5cb6dab4363f5098ede2 | MATLAB | 4,196 | 120 | function plotScalogram( obj, varargin )
% PLOTSCALOGRAM Continuous 1-D wavelet transform using Morlet wavelet
% Use LFP online streaming recordings
%
% Syntax:
% PLOTSCALOGRAM( obj, varargin );
%
% Input parameters:
% * obj DBScope object containg streaming data.
% * (optional) ax Axis where to ... |
89a4065b5792a3404c7c7dbe43a96d331b9cbad144fb8dbfbd9d446e56cedf35 | MATLAB | 4,197 | 111 | function fH = plotPRFModelCVRSQ_violinPlot(ds,resampledCVR2,maxNC,roisToPlot,saveFigs, saveFigDir)
% Function to generate Violin plots with cross-validated variance explained
% (R^2) for each pRF model,
% Set colors
cmapModels = getColormapPRFModels(0);
modelNames = {'LSS','CSS','CST'};
fH = figure; clf; set(gcf,'Pos... |
f6bd2e8877544c47b9559cee2c17e6cff7bd9e8f45bf238d28497227a55a3bfc | MATLAB | 4,197 | 125 | % computeDFF_trial.m
%
% Function that converts background-subtracted fluorescence signal into
% dF/F (for 1 channel data) or dR/R (for 2 channel data) for user selected
% trial folder. Saves processed data in pData file in same folder.
% Note: assumes that every imaging frame should be used for the baseline
% calcu... |
0854881f4811da2925c9779bbaff891dd1a697cac9b4c5f5c7d29685601cb00c | MATLAB | 4,201 | 103 | function [Ci Q]=modularity_dir(A)
%MODULARITY_DIR Optimal community structure and modularity
%
% Ci = modularity_dir(W);
% [Ci Q] = modularity_dir(W);
%
% The optimal community structure is a subdivision of the network into
% nonoverlapping groups of nodes in a way that maximizes the number of
% within-gr... |
eb335156d43b2a9f803f6e215ab4b606a1ad35b360a91768977f1ccb9225e561 | MATLAB | 4,201 | 101 | % function results_cell = read_fig2_results_from_xlsx(fname, sheetName)
% reads the data from the specified Excel file and worksheet.
%
% Inputs:
% fname (str): Name including path of the .xlsx document.
% sheet_name (str): Name of the worksheet within fname.
%
% Outputs:
% results_cell: Cell arra... |
9c00f4d6ab1300e018c5372ea41879b9d5ca2b11b042cf1903c868ff68a37d20 | MATLAB | 4,202 | 121 | function plotSignalAndStimulation( obj, varargin )
% PLOTSIGNALANDSTIMULATION Computes and plot standard spectrogram
% Use with LFP online streaming recordings
%
% Syntax:
% PLOTSIGNALANDSTIMULATION( obj, varargin );
%
% Input parameters:
% * obj DBScope object containg streaming data.
% * (optiona... |
e57f4c285d98ea66f37e0157ec249a1f4b29dbb18bd46226d976fef00776d6d7 | MATLAB | 4,207 | 114 | function [pyr_mean_activity,mch_mean_activity,tdt_mean_activity,velo,acc] = get_mean_activity(base,ds_events,event_frame,ex_thresh)
conditions={"SOM","PV","Mixed"};
for d = 1:length(ds_events)
%-- load files for each dataset
cur_onsets=ds_events(d).onsets;
load([base ds_events(d).tag 'activity.mat'])
... |
a28ecf110034ee22852b02de896c119ba26b5e34867913e516d968246347897f | MATLAB | 4,209 | 105 | function dfof=debleachBDH(time,sig,wavelen,savename,debleach_flag,numExp,startfit,endfit,baseline_method,manualbase)%,numExp startfit,endfit,baseline_method)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
exptname=strsplit(savename,'\'); exptname=exptname{1... |
5655befa5c8229d3815eb1090371802d312ea3d48e8f65579f4a93aac1f71ec2 | MATLAB | 4,210 | 124 | function [A,W] = fcn_match_length_degree_distribution(A,Dist,nbins,nswap)
% [A,W] = fcn_match_length_degree_distribution(A,Dist,nbins,nswap) takes a
% weighted, symmetric connectivity matrix, A, and Euclidean/fiber length
% matrix, Dist, and generates a randomized network with:
% 1) exactly the same degree sequence... |
578ce8b54d20937e998ce346d3bb84f5f528c26ef6ae350b715e80410b4a3d74 | MATLAB | 4,210 | 117 | function recovery_test(fig2)
% this function test if later touches are less discriminable from the noise
% (Fig 2)
ff=dir('*.mat*');
nunits=33;
AUC_1_correct=nan(1,nunits);
AUC_later_correct=nan(1,nunits);
AUC_12_correct=nan(1,nunits);
AUC_later2_correct=nan(1,nunits);
AUC_1_incorrect=nan(1,nunits);
AUC_later_incorr... |
053c26fef96d4bb4b42292b19a0fc9d83392f4ebcda56a7e4b8dfccf5454148e | MATLAB | 4,218 | 131 | function [out,sucessfulRead,rawOut]=readMetaData2Stitchit(fname,verbose)
% Read acquisition meta data into a MATLAB structure
%
% function [out,sucessfulRead]=readMetaData2Stitchit(fname,verbose)
%
% Purpose
% Read meta-data from a tiled acquisition parameter file and returns
% mosaic meta data as a structure that Stit... |
20bd98f1e7b8343cb3bbdfebe645f6c38690233492cad1601a0d29f6cff9f7ac | MATLAB | 4,224 | 122 | function [eeg] = read_ns_eeg(filename, epoch)
% READ_NS_EEG read a NeuroScan 3.x or 4.x EEG File
%
% [eeg] = read_ns_eeg(filename, epoch)
%
% filename input Neuroscan .eeg file (version 3.x)
% epoch which epoch to read (default is all)
%
% The output data structure eeg has the fields:
% eeg.data(..) ... |
9bf41b60897843327d8217f7b09890114783eb77c135cb96aad7199607646763 | MATLAB | 4,225 | 63 | function dend_params = check_dend_params(dend_params)
% dend_params = check_dend_params(dend_params)
%
% This function checks the elements of the struct dend_params to ensure
% that all fields are set. Fields not set are set to a list of default
% parameters. The struct checked is:
%
% - dend_params - Struct cont... |
3e3e60ea8a3d60c46a06b7f770f9869b92919d4645b2e4c76c8042d75d85a085 | MATLAB | 4,228 | 165 |
function my_net_progress_disp(opts, exp_info, imdb, net_config)
if mod(exp_info.train.ref.current_epoch, opts.fig_plot_step)~=0
return
end
if ~isfield(exp_info.train.ref.tmp_cache, 'epoch_eva_fig')
f1=figure;
exp_info.train.ref.tmp_cache.epoch_eva_fig=f1;
% set(f1,'Visible', 'off');... |
9144679909c9e0e122199f4a192a000b6311ba5c10bfca7c0e1b6a2d0dd75cde | MATLAB | 4,229 | 122 | % Starburst Algorithm
%
% This source code is part of the starburst algorithm.
% Starburst algorithm is free; 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 2 of the License, or
% (at your option) any later vers... |
2a02bcea93af6d52c05489d5e692085b3bc67be4c725d626c23da4db81a785dd | MATLAB | 4,231 | 123 | function [C, C_raw, results_deconv, cc] = HALS_temporal(Y, A, C, maxIter, deconv_options)
%% run HALS by fixating all spatial components
% input:
% Y: d*T, fluorescence data
% A: d*K, spatial components
% C: K*T, temporal components
% maxIter: maximum iteration number
% deconv_options: struct variable,... |
83f74b100606db946385c4f946ddf3e64c7ea6f0011d320a5662c90844e5cc05 | MATLAB | 4,232 | 127 | function [V] = ft_write_mri(filename, dat, varargin)
% FT_WRITE_MRI exports volumetric data such as anatomical and functional
% MRI to a file.
%
% Use as
% V = ft_write_mri(filename, dat, ...)
%
% The specified filename can already contain the filename extention,
% but that is not required since it will be added aut... |
e4715f2c9a8f140c0a0d2fc314aae1b3e9acaec8fc4f8cbfb8e75b9e70ac8637 | MATLAB | 4,235 | 128 | % plotMeanKernels.m
%
% Function to plot all kernels, where those relating the same variables in
% the same direction are plotted on the same subplot. I.e. the yaw
% velocity forward kernel for left, right, sum, and diff. Also shows
% variance explained and number of flies in figure legend. Produces 1
% plot, with... |
b73ca6b8446d5ed880341cac9af10d84adce1d9672a6507b71d17412a7cb4d37 | MATLAB | 4,237 | 133 | function[data,h]=SONGetTextMarkerChannel(fid, chan, varargin)
% SONGETTEXTMARKERCHANNEL 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... |
fd48a413b877bfc36614e0435a77a189e407464a370a800337c100b8792d8058 | MATLAB | 4,237 | 108 | function [nonLinearResponse, params] = applyNonlinearity(prfResponse,params)
% Wrapper function to apply different types of nonlinearities depending on
% the model type.
%
% INPUT
% prfResponse : (double) matrix or array with dimensions time by
% voxels [by channels]
% params : (... |
1219ace7ae75a5683f4cfa4083409b59004c354d3f1dcddb53578f602da9140c | MATLAB | 4,238 | 113 | % initUserDAQ.m
%
% Function to initialize user DAQ (i.e. DAQ that coordinates experiment and
% collects appropriate voltage signals)
% Sets up channels and DAQ and channel settings. Does not set up any
% experiment-specific output streams.
%
% INPUT:
% settings - struct from twoPhotonSettings() containing all DAQ ... |
5be6172ac7eff0e8246ec6bc61c272c6e7924510e3ce3e5188f3002aabdbd049 | MATLAB | 4,242 | 119 | function [globalmatrix, localmatrix] = getSMGMatrix(probe,outputtype)
%GETSMGMATRIX Summary of this function goes here
% Given a characterized probe, this function outputs a
% [nGroups+2]x[1+nModule] matrix for use updating firmware of master
% board of fNIRS modules. Two rows are added to the number of groups, ... |
9e98f6fd7e881c5e0f161472b7e501f91998f51e1d2dfaac5ec5c86fe929ba16 | MATLAB | 4,243 | 189 |
% Author: Guosheng Lin (guosheng.lin@gmail.com)
% This is an example of resume training with lower learning rate.
function demo_refinenet_train_reduce_learning_rate()
rng('shuffle');
addpath('./my_utils');
dir_matConvNet='../libs/matconvnet/matlab';
run(fullfile(dir_matConvNet, 'vl_setupnn.m'));
run_config=[];
... |
f83d7c91a18b409086351ba8c7396f34bb115edd68d2b9ed6595d0a986558358 | MATLAB | 4,243 | 102 | function [to_eval,eval_i,j]=tag2eval(tag_contents,to_eval,eval_i,j,tags)
%TAG2EVAL Extacts statements for evaluation by XML2MAT
%
%Syntax: [to_eval,eval_i,j]=tag2eval(tag_contents,to_eval,j)
%
%Description:
% Autorecursive function that parses tag_contents structure
% generated within XML2MAT (see %RECOVER STRUCTURE w... |
1b04609f9459c297da7f4b71778555045ee0c1616c04fb00970a75bb847e04af | MATLAB | 4,248 | 126 | function [MAT,VARNAME,tag_contents]=xml2mat(XML)
%XML2MAT converts XML string into matlab structure variable
%Syntax: [MAT,VARNAME,tag_contents]=xml2mat(XML)
%Description
% XML is an XML formated string using rules compliant with
% the proceedure implemented in MAT2XML.
% It can also be a file name with MbML t... |
5a8c946915acf95a703b527e7a2434fe80f65a7d2bb3b2723f02f9127dc8077b | MATLAB | 4,250 | 92 | function [N E] = rentian_scaling(A,XYZ,n)
%RENTIAN_SCALING Physical Rentian scaling
%
% [N E] = rentian_scaling(A,XYZ,n)
%
% Physical Rentian scaling (or more simply Rentian scaling) is a property
% of systems that are cost-efficiently embedded into physical space. It is
% what is called a "topo-physical" property... |
ebdfd8e52b638b486861e9475a3e6d9ca8078500146629fbf18904c647b4bb33 | MATLAB | 4,250 | 93 | classdef RECORDINGMODE_STREAMING < RECORDINGMODE_COMMONMETHODS
% Object with properties and methods to analyse streaming fields from PerceptPC json data at NCN lab
%
% Available at: https://github.com/NCN-Lab/DBScope
% For referencing, please use: Andreia M. Oliveira, Eduardo Carvalho, Beatriz Barros, C... |
7b45cce8dc6ec3bef8401812c0338889283678c334c65b253c00c7d9387826e5 | MATLAB | 4,253 | 110 | classdef TimeIntervals < types.hdmf_common.DynamicTable & types.untyped.GroupClass
% TIMEINTERVALS A container for aggregating epoch data and the TimeSeries that each epoch applies to.
% REQUIRED PROPERTIES
properties
start_time; % REQUIRED (VectorData) Start time of epoch, in seconds.
stop_time; % REQUIRED (... |
435ab276349101b6f18aa35e1350660e0be399d26a2143cc6763651ac3552250 | MATLAB | 4,255 | 120 | % plotScatterPCAStepParamsInterp.m
%
% Function to plot scatterplot of output of savePCAinterpStepParam()
% Plots each step param set 1 PC1 vs set 2 PC1, with option to color by
% another step parameter or body parameter
% Select output file of savePCAinterpStepParam() through GUI
%
% INPUTS:
% datDir - path to fold... |
ffb8b34e771951bba011b41cbcdd4e94ee04257f08fa7772949d8ccf12157a7c | MATLAB | 4,256 | 84 | function [resampStruct,spikes,fluor] = generateNextTimePoint(spike_opts, cal_params, n_locs, mod_vals, resampStruct)
% S = generateTimeTraces(spike_opts, S_times)
%
% Generate time traces for a number of simulated neurons. Each neuron fires
% with as am independent Poisson process with a given rate. The firing
% rat... |
ab84eaa6b4e3793be99199af3d88e090eb3e25b31750019e762e9fdb145b8ea7 | MATLAB | 4,257 | 136 | function [trax_X,trax_Y,track_data, track_set] = TrackFinderv2(X,Y,cords,FR, speed)
%UNTITLED3 Summary of this function goes here
% Detailed explanation goes here
remove_blanks = ~cellfun('isempty',cords(:,:));
cords = cords(remove_blanks);
for i = 1:length(cords)
big(i) = length(cords{i});
end
win... |
12856968e4fc56ec6e7b9850bb3c0917b4f11d95469e66195a56b0c6531363c5 | MATLAB | 4,258 | 147 | function r=embedding_dimensions_upper_bound(Session,Area,Ndir,Nbins,threshold,t_from,t_upto,edges_dur_bin)
%% embedding_dimensions_upper_bound computes the upper bound of the coefficient of determination
% between the trajectories within the same bin direction and duration from
% Session and Area
% This function al... |
8db415c03df3bb108059108ef29b791a90af1f127db8d641d9152e866f21988d | MATLAB | 4,261 | 117 | classdef MLArenaRectangle < MLArena
properties
x_length_cm;
y_length_cm;
end % properties
methods
function obj = MLArenaRectangle(referencePointsVideo, x_length_cm, y_length_cm)
% Validate the inputs
if ~all(size(referencePointsVideo) == [2, 4])
... |
dadb4e763eef04f0051278efbf2d5975780975a81f39db9b6d66039a043d4f60 | MATLAB | 4,265 | 129 | function outexpdirs = PrepareSimTrx4JAABA(trxfiles,expdir0,varargin)
if ~iscell(trxfiles),
trxfiles = {trxfiles};
end
[rootoutdir,dataloc_params,analysis_protocol,settingsdir,is_temporally_aligned,forcecompute,nooverwrite] = ...
myparse(varargin,'rootoutdir','',...
'dataloc_params',[],...
'analysis_protocol',... |
253f4ebbd5fbd53f38fb2ad3f3b622ed7d957e6262fbdb538f15fc9ceed99e7f | MATLAB | 4,267 | 130 | function out = summarize_coherency_table(fn)
if nargin < 1
fn = uigetfile('output/*_table.csv');
end
fprintf('Performing summary of %s output\n', fn);
outputFolder = 'output';
if ~isfolder(outputFolder)
mkdir(outputFolder)
end
filename = 'coherency_summary.csv';
fid = fopen(fullfile(outputFolder, filename), ... |
6f7f4faf35b2689d95ad5e19b74891443ba2f5de67635886105cca6b6a8e1c43 | MATLAB | 4,267 | 102 | function [calciumEvents] = ml_cai_neuron_calcium_events(neuron, timestamps_ms, spike_timestamps_ms, MAX_SPIKE_SEPARATION_MS)
%SPIKE_THRESHOLD = 0;
%MAX_SPIKE_SEPARATION_MS = 100;
% % Only use spikes whose values exceed the given threshold
% si = find(neuron.spikes > SPIKE_THRESHOLD);
%
% % Ti... |
5c7491dc39c0b3e788e67991c43f69b5752b6f3bbc9fa226a061271863c6a97d | MATLAB | 4,269 | 117 | function varargout = attributes(varargin)
% XMLTREE/ATTRIBUTES Method (handle attributes of an element node)
% FORMAT varargout = attributes(varargin)
%
% tree - XMLTree object
% method - 'set','get','add','del' or 'length'
% uid - the UID of an element node
% n - indice of the attribute
% key - stri... |
9fa90bd87da91e4911ce4337338602171a98de7cbf515c39b746c35699e1a582 | MATLAB | 4,270 | 101 | function [segMat_405_Control, segMat_472_GCaMP, segMat_Diff] = segMatrix(params)
%% Import & organize data
% Choose Which mouse to load from
if params.mouse == 1
load('Z:\1_Maxwell_Gagnon\ProjectData_Amin\Boris Recordings\Experiment 2\drive-download-20180713T210854Z-001\Raymond_071318_LFP_M1\Recording_1\MATLAB V... |
c84be9bdac304bd1c4cc894746898ee7c1691659cb211f0884e4f8b48a620e49 | MATLAB | 4,270 | 134 | function real_neuron_select
% post process: semi-auto false positive removal
% Jinghao Lu, 10/02/2017
%% initialization %%
%%% select processed file %%%
[file_name, path_name] = uigetfile('*.mat');
file_id = file_name(1: end - 4);
%%% load files %%%
load([path_name, file_name])
roi =... |
86ccaa00833c7462d4999c6fc8f90686c393beaca7c35788559c20f02b0a93f4 | MATLAB | 4,271 | 121 | % computeLegFictracOpto_1Fly.m
%
% Function that extracts the individual leg traces and FicTrac, in response
% to optogenetic stimulation of different durations and intensities (ND
% filters) for a single fly.
% User selects all pData for that fly through the file selection GUI
% Saves the data as a struct in path sp... |
d697a23bb756371c1678a044c0170ffa6ba65b30702d2301d26a32653450503f | MATLAB | 4,271 | 175 | % Function File: [fit S] = chebexp (x, y, n, Tn)
%
% Returns the least-squares unconstrained fit of n exponential
% components with constant offset to XY data using the Chebyshev
% algorithm [1]. The interval in the x dimension must be constant.
%
% This function is effective in finding a solut... |
ea2edac75e7274d7b13aa58c897b852134fa13e1b6ed4ec6ac984a911c67571a | MATLAB | 4,271 | 137 | function [trax_X,trax_Y,track_data, track_set] = TrackFinderv2(X,Y,cords,FR, speed)
%UNTITLED3 Summary of this function goes here
% Detailed explanation goes here
remove_blanks = ~cellfun('isempty',cords(:,:));
cords = cords(remove_blanks);
for i = 1:length(cords)
big(i) = length(cords{i});
end
win... |
3a2ad56b09940f9e4c0ee4cd909d2267337667cf2d06b82130ff22df9ec0d825 | MATLAB | 4,273 | 117 |
function [status] = ml_cai_miniscope_recording_status( trialFolder )
fnSettings = fullfile(trialFolder, 'settings_and_notes.dat');
fnTimestamp = fullfile(trialFolder, 'timestamp.dat');
status = [];
status.settingsAndNotes.exists = isfile(fnSettings);
status.timestamp.exists = isfile(fnTimestamp);... |
5df9a0213455df057de8937adf79c7b162fa5f55ad0acd7a5eb9d71a26c03ab3 | MATLAB | 4,273 | 143 | function plot_func(T,delta,l,num_columns,t_j,t_total,dt,npp,N,num_VTA,R_it,R_kt,T_pt,T_dt,W_ji,Title,t_stim,dopa,dopa_plot)
%info
num_VTA = npp;
new_rate = zeros(2*num_columns,numel(t_j));
new_rate_ele = 0;
new_rate2 = zeros(2*num_columns,numel(t_j));
new_rate_ele2 = 0;
pop_vect = 0:npp:N;
set(0,'DefaultAxesColorOrder'... |
ca0e959ae791a5b831850671cf3f2fac1969d3e1083e1bae55f32568fac12664 | MATLAB | 4,273 | 84 | %% Description
%{
This script computes burst occurrence rates for the beta (20-30 Hz) and
gamma (60-92 Hz) bands and tests whether burst rates of a mouse (in a
solitary condition) change in response to threats instigated by a spider
robot.
%}
%% Configure Library Path
UTIL_DIR = genpath('/Users/scho/Cho2024_MouseEsca... |
b0354cbc49a920465580876f0025558e17d4e3e3b65df48d4d972896a9f6815e | MATLAB | 4,276 | 101 | % check EEG-fMRI for individuals
% SI Table 16
%
% 2023-10-13 Jonathan Wirsich
[confs, confs_label, groups, eeg_conn_types, bands, atlases, serialized_path] = init_serialized_conf_tle();
for atl=1:1
%load connectomes
[allgroup_mean_fMRI, allgroup_mean_EEG, allsub_fMRI, allsub_EEG, groups, ...
group_... |
0148ee6f2d6f0901479055a827fe1b89c5694f017de57ad025354717ac1e10c2 | MATLAB | 4,277 | 142 | function results = vl_test_svmtrain(varargin)
% VL_TEST_SVMTRAIN
vl_test_init ;
end
function s = setup()
randn('state',0) ;
Np = 10 ;
Nn = 10 ;
xp = diag([1 3])*randn(2, Np) ;
xn = diag([1 3])*randn(2, Nn) ;
xp(1,:) = xp(1,:) + 2 + 1 ;
xn(1,:) = xn(1,:) - 2 + 1 ;
s.x = [xp xn] ;
s.y = [ones(1,Np) ... |
0fc1741ab06602c436a961e11d754ab2eaa8487813aa8323b0568826885a36dc | MATLAB | 4,278 | 98 | function [boxes blobIndIm blobBoxes hierarchy priority] = VideoFrame2HierarchicalGrouping(colourIm, flowIm, segmentIm, sigma, k, minSize, colourType, functionHandles)
% function [boxes blobIndIm blobBoxes hierarchy] = Image2HierarchicalGrouping
% (im, sigma, k, minSize, colourType, functi... |
bf8e8b421d03383dbeba78fa60722aca27611781208ec5a8bbcc825638bbebc5 | MATLAB | 4,285 | 139 | addpath(genpath([getenv('AUTOTOP_DIR') '/tools']));
clear;
subs = ls('datasets/HCP1200_testSet/ManualGroundTruth');
subs = strsplit(subs)';
subs(end) = [];
comp = {'manual_lbl' 'labelmap-postProcess' 'subfields-BigBrain'};
task = {'Task101_hcp1200_T1w' 'Task102_hcp1200_T2w' 'Task103_hcp1200_T1T2w' 'Task104_hcp1200_b1... |
8df2ef4c933b311f34145fab77b0d696593f8304b3bab754081fbaff1b299111 | MATLAB | 4,290 | 113 | function [evt,evm] = markpointproc(CIF,CIFMAX,MKF,TIMEMAX,NUMMAX,MARKDIM,HISTLEN)
% MARKPOINTPROC
% [T,M] = MARKPOINTPROC(CIF,CIFMAX,MKF,TIMEMAX,NUMEVMAX,MARKDIM,HISTLEN)
% generates a marked point process using the conditional intensity
% function CIF and mark generating function MKF. Events are generated
% until... |
0dec99edbe31786229f5d6f7277ead6a68302b567a35a2ec4bd15e82dbaa5e61 | MATLAB | 4,292 | 101 | % init global values
%clear STA STAshuf STS;
%SearchSubFolders = 0; % if 1, search files in all subfolders
SearchSubFolders = 1; % (ehud jan 1 2019, for new data) if 1, search files in all subfolders
Nboot = 100;
basecolors='rgbmcky';
bef_s = 0.05; aft_s = 0.05;%s. STA pars
yBins = [-90:20:90];
STS_FUNC='sta'... |
4c83cf1bad38e1a6b0c1c0f0df44b6de4b79cde7252ad12077eb873af87f6714 | MATLAB | 4,292 | 92 | % Calculate spatial contribution to gloab EEG-fMRI correlation and local EEG-fMRI correlation
% Figure 3 and SI Table 7, 8 and 15
%
% 2022-08-22 Jonathan Wirsich
% 2023-08-16 Bug fix (only push selected subgroups for permutation) - jwirsich
% 2023-10-13 Add Interhemispheric subnetwork
[confs, confs_label, groups, eeg_c... |
07c579ee64ec8dba2d0977668803e1bee71356639589c9cdfebe9f802e4734a7 | MATLAB | 4,296 | 121 | %% LCMV Source Reconstruction example script.[Helped provided by Marius Krösche]
clearvars;
clc;
% path settings
ft_path = '/home/rasfay01/fieldtrip-20230503'; %fieltrip path
addpath(ft_path);
ft_defaults;
subject_path = '/data/raw/hirsch/RestHoldMove_anon/sub-0cGdk9/ses-PeriOp/'; % example for only one subject and on... |
9925114175ac5d113b87667bc727b219e9791bc1b801214e8b33b5509b193b6c | MATLAB | 4,297 | 109 | function [event] = read_shm_event(filename, varargin);
% READ_SHM_EVENT reads the events in real-time from shared memory
% this is a helper function for READ_EVENT
% Copyright (C) 2007, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% for the documentation and detail... |
bd3a4d557da0352fff7e5422dd29bf4ae9ed7c573474fd9b14c18b2fb720105a | MATLAB | 4,299 | 135 | function salopt = saliencyPropagation(im_d, imsegs, inimap,...
alpha, gamma, sigma, mask, maskmap, imgplane)
%% get segments info
nseg = imsegs.nseg; adjcMatrix = imsegs.adjmat;
pixelList = imsegs.pixelList;
%% get features an annotated labels
fgWeight = zeros(nseg, 1); mskweight = zeros(nseg, 1);
for i = 1 : nseg... |
ff779ae144fcdcf8c361dce2ed9ad5d40139181b8315302a468114d2abdefd17 | MATLAB | 4,300 | 113 | % This script assigns coil position, dIdt (for
% electric field), I0 (for magnetic field), and displays the resulting
% head-coil geometry. It may be be executed several times to adjust the
% coil position
%
% Copyright SNM/WAW 2017-2020
showfig = 0;
addpath('../../../../FMM3D/matlab');
%% Defi... |
fb131a741e65abff30a1bf72bca9951882fd942d8a9527d1d3a3a928f0c89251 | MATLAB | 4,302 | 109 | function UMparam = DefaultParametersUnitMatch(UMparam)
% Checks if all required parameters are there, and will fill in default
% parameters if not wherever possible
%% Check if path information is given
% Kilosortversion?
if any(strfind(UMparam.KSDir{1},'KS4'))||any(strfind(UMparam.KSDir{1},'kilosort4'))
UMparam.Ki... |
6f4683799e31ec12c1531ba4dbff4cacf5ba9ee63b47375a302fd79e946e708c | MATLAB | 4,304 | 92 | function dspec=dspecBuild_lab(dspec,includeInModel,numNeuron)
durationH=200;
durationP=200;
durationI=460;
durationO=460;
durationL=360;
durationR=360;
durationG=2000;
durationM=1500;
if ismember('H',includeInModel)
bs = basisFactory.makeNonlinearRaisedCosMine(10, dspec.expt.binSize, [0 durationH], 1);
dspe... |
3ab08898938ac4225bd178e27263c7b14d549cac73f6d466669ac0d023f80e98 | MATLAB | 4,306 | 97 | % run amapOFshow
clear all; runMode = 'batch';
globals; initglobals;
PRINT_ERRORS = 0; PRINT_INFO=0; PRINT_NAN=0;
GDEBUGNEW.on = 0; GDEBUGNEW.fig = 33;
if GDEBUGNEW.on, figure(GDEBUGNEW.fig); clf; end;
COMPUTE.sta = 0; % what to compute in amap
DATA_TYPE = 'OF';
DATA_TYPE = 'EM';
PLOT_TYPE = {'tuning'}; %... |
86df47e38fcb4650049acf47eec71174cae9072405b46a7e21c0ad3c8d1aaf9e | MATLAB | 4,306 | 123 | function [varargout] = ndgrid(varargin)
% NDGRID Generation of arrays for N-D functions and interpolation.
% [X1,X2,X3,...] = NDGRID(x1,x2,x3,...) transforms the domain
% specified by vectors x1,x2,x3, etc. into arrays X1,X2,X3, etc. that
% can be used for the evaluation of functions of N variables and N-D
% interpola... |
deabb1d44f8693a05dd6ffd78c72490642f6aac3d5caff37aaece21ffb86323b | MATLAB | 4,318 | 144 | function [] = ExtDataFig04_TuningCurve_OptStim_Song_HighMagSine
% Code for plotting the tuning curves of pulse and sine songs induced by optogenetics in Extended Data Fig. 4b–d.
GT = 'pIP10_Chr'; % Extended Data Fig. 4c
% GT = 'w_LChr'; % Extended Data Fig. 4d
% GT = 'pIP10L_Chr'; % Extended Data Fig. 4b
% GT = 'pIP10... |
6c2dc511acc6578cbd1d77473c1915ed1b63fd8722ca9572282befc761a991dd | MATLAB | 4,320 | 138 | % ----------------------------------------------------------------
% Load Dataset
% ----------------------------------------------------------------
unzip datasetImages.zip
data = load('vehicleDatasetGroundTruth.mat');
vehicleDataset = data.vehicleDataset;
rng(0)
shuffledIndices = randperm(height(vehicleDataset));
id... |
aa7e5873b67cb122dec3ec2044cbe70e8275d8bce78c3162ca639598d2ac9686 | MATLAB | 4,320 | 163 | %
% Plot the evolution of a network statistic over time.
%
% PARAMETERS
% $type "full" or "split"
% $network
% $statistic
% $disable_runtime "1" to not generate the runtime plots
% (runtime data is not generated for
% spectral statistics)
%
% INPUT
% dat/statistic_time.$type.$statistic.$network
% dat/sta... |
6bfebf7e0615874f432516d2ea671ef567c36d3c9a30e6c1ef50610856bed95a | MATLAB | 4,321 | 129 | function [spike] = read_neurosim_spikes(filename,headerOnly)
% READ_NEUROSIM_SPIKES reads the "spikes" file that is written by Jan
% van der Eerden's NeuroSim software. The output is represented in a
% structure that is consistent with the FieldTrip spike representation.
%
% OUTPUT
% spike: A fieldtrip raw spike stru... |
b05eaabb26fae665cca0e2995d25502d5c2edf89665f294f93cf6d67fa97968c | MATLAB | 4,322 | 134 | addpath(genpath('gifti-master'));
f = fopen('datasets/testSet.txt');
subs = fscanf(f,'%c');
fclose(f);
subs = strsplit(subs);
subs(end) = [];
shp = [254 126];
DTIsubs = [];
n=0;
for s = 1:length(subs)
for LR = 'LR'
n=n+1;
midthick{n} = ['datasets/HCP1200/results/sub-' subs{s} '/surf_T2w/sub-' su... |
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