sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
f35223be2c89be73f5f0d33948f03363f83695936e28c2e207275b9dea21d7ed | MATLAB | 3,843 | 109 | % Function File: [yf, tf, HTF] = binomialf (y, t, n, correction)
%
% Application of a binomial smoothing filter of order n to the y-vector.
%
% For filter orders upto 50, filtering is achieved by application of a
% sliding (2n+1)-point box weighted with normalised binomial coefficients.
% For ... |
f3ca4e057fad8c4f1309646bcd93528ce756c2416d71794c811022aae18d88db | MATLAB | 3,843 | 118 |
function result_info=my_gen_seg_result(seg_param, ds_info, predict_info)
result_info=[];
img_size=seg_param.img_size_input;
gt_mask=seg_param.gt_mask_input;
assert(~isempty(gt_mask));
gt_mask=uint8(gt_mask);
assert(all(img_size==size(gt_mask)));
eva_param=... |
5be9cdb3cbf6e7d064521607200c6de411a67f2a774eaae63b4663c90c0506c7 | MATLAB | 3,845 | 135 | function [] = ExtDataFig08_AveTimeCourse_OptStim_Neuron()
% Code for plotting the time course of ΔF/F in Extended Data Fig. 8a,d.
GT = 'pIP10'; Target = 'pIP10_NR'; % Extended Data Fig. 8a
% GT = 'pMP2'; Target = 'pMP2_NR'; % Extended Data Fig. 8d
switch Target
case 'pIP10_NR'
TargetROI = 3;
ylimr... |
d999bb62785b7335f7b86f937605f5a3f170ebd16eca0474dfdd1bdbee96b0ae | MATLAB | 3,846 | 120 | function [h2mm, s2mm] = openmeeg_megm(pos, vol, sens)
% OPENMEEG_MEGM computes the OpenMEEG H2MM and S2MM matrices
% i.e. the contribution to MEG from the potential and from the source
%
% Use as
% [h2mm,s2mm] = openmeeg_megm(vol, isolated)
% Copyright (C) 2010, Emmanuel Olivi
% INRIA Athena Project Te... |
1ecd98f4fea7639452aa96ff73a85b062f7013687accd404db1480b82129ea04 | MATLAB | 3,847 | 89 | function status = fillStreamingParameters( obj, data )
% Extract and visualize LFPs from online streaming mode
%
% Syntax:
% status = FILLSTREAMINGPARAMETERS( obj, data );
%
% Input parameters:
% * obj - object containg data
% * data - data from json file(s)
%
% Output parameters:
% * status
%
% Example:
% ... |
db91300be63f5137933928747992dfd09f21cb05b22f9539101de2b2807ffcb3 | MATLAB | 3,850 | 86 | % "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... |
cd7fe10085338e83b1a841705ca6c9d93d20dde0380063987cefdd7f855af611 | MATLAB | 3,851 | 109 | %Sample code
%Davor Curic, 2023, Complexity Science Group, University of Calgary
%
%This code generates avalanches with respect to a network. In this case the
%network is generated from pixels within a specified radius.
%
%IMPORTANT: the sample recording was too large to fit into github
%repository. This code sh... |
ea340a68af337940fe4d5fa1c536b1adc18b5dabe24574de162f116b22f9e6e0 | MATLAB | 3,852 | 110 | classdef file_object < handle
% Simple file object that fcloses() the fid when no longer referenced.
% Can be used just like a fid in most cases.
properties (Access = protected)
fid_ = []
%uid_ = []
%file_name_ = []
end
methods
function self = file_object(va... |
06ea490e33188cefcbbaf37292ac684ede23b5462bb51ba4159cd6998e393657 | MATLAB | 3,853 | 100 |
%% create figure 2H
%% janine.thome@zi-mannheim.de
%% paths
clear all; close all
addpath([pwd '/circularGraph/'])
%% load data
x=load('FC_ALS_HC_Fig2H.mat');
cols=[213 62 79; 154 213 148; 50 136 189]/255; %background colors
col1=cols(1,:); col2=cols(2,:); col3=cols(3,:);
nvp1=size(x.x... |
bdb09896dad632bf2f3d0daa36fd0bdfe334d73ae5eb744856c04811aff7e9df | MATLAB | 3,853 | 152 | tic
%% open/read file and set up Environment
%clear;clc;close all
activateCEDS64
% Start Time
START_TIME = 0;
%AstSamples = floor(START_TIME * 1000);
AstSamples = 1;
% Wavelength
WAVELENGTH = 999;
% path to file
files = [
%"Z:\1_Ruth Empson\151217 VOR\segment_1.smr"
%"Z:\1_Ruth Empson\151217 VOR\segment_2.sm... |
8724db31c8954619e9ff3170c25aa78f8589efa77ceb743140c2f93f8b39f7dd | MATLAB | 3,854 | 97 | % makeDiscImgSeries.m
%
% Function that generates series of disc images centered at
% user-specified center. Returns images and their corresponding sizes, in
% degrees
% For generating discs for looming stimuli on visual panels. User
% specifies dimensions of panels, in LED pixels, and the conversion factor
% to de... |
78d7dec3d65b252028143b34eeb77d3cd033c2d4276cbac25cd795451fa24017 | MATLAB | 3,855 | 110 | function [p] = ml_cai_behavcam_referenceframe_create( trialFolder, dataFolder, varargin )
p = inputParser;
p.CaseSensitive = false;
addRequired(p,'trialFolder', @isstr);
addRequired(p,'dataFolder', @isstr);
addParameter(p, 'outputFolder', dataFolder, @isstr);
addParameter(p, 'verbose',... |
8e1da7797e17cfb15a8ebade5d2162ae15e4f8072c726ad4c53f5ca06af61b59 | MATLAB | 3,855 | 121 | % ------------------------------------------------------------------------%
% compute the W2 distance between feature a and b
% code written by Lei Zhu, IPRAI, Huazhong Univ. Sci. & Tech.
% last modified time: 2013.07.11
% ------------------------------------------------------------------------%
function D = W2Dis... |
78cf49feadd411ee3df0bc3ed9db1f19e5e2f686cd2a88c29a5075e7a8bc6e52 | MATLAB | 3,856 | 86 | % mglMetalReadTexture.m
%
% usage: [im, results] = mglMetalReadTexture(tex)
% by: Ben Heasly
% date: 03/04/2022
% copyright: (c) 2021 Justin Gardner (GPL see mgl/COPYING)
% purpose: read texture data from mglMetal, back into a Matlab image.
% usage:
%
% % Create and show a ... |
de1079972caf0c92fbf43cccf26bf089dfd1a7a6c7efa44bf84937f2f43ff201 | MATLAB | 3,857 | 168 | function [val] = read_asa(filename, elem, format, number, token)
% READ_ASA reads a specified element from an ASA file
%
% val = read_asa(filename, element, type, number)
%
% where the element is a string such as
% NumberSlices
% NumberPositions
% Rows
% Columns
% etc.
%
% and format specifies the datatype a... |
c821a476bec51f6a4bd58b86beed6173db06d1ad576a449b0cc0acf4cd9af587 | MATLAB | 3,858 | 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 m... |
f7fa6ec004f120405693ba30fefc1e6c51a6744586509790ae044f11ac6951d7 | MATLAB | 3,858 | 116 | function toon_motionCorrect(baseDir, expt, session)
% toon_motionCorrect(baseDir, expt, session, motion_cutoff);
%
%
% Runs within and between scan motion correction for Toonotopy experiment
%
% Within scan motion correction relative to the 8th frame of each scan
% params.motionCompRefFrame = 8; % reference TR for mo... |
6cf940f5df6501537d3c39d52d36cdbb54c4e6077bc84d6b5a79c7a221d7b587 | MATLAB | 3,860 | 107 | function [gp_tmp,varargout] = masked_3DGP_test(grid_sz, l_scale, p_scale, mu, bin_mask, threshold, l_weights,type)
% [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 v... |
6846e71b96cb048d019ad2f8977acef57234c74067844ad9272aa9ef4c6c9225 | MATLAB | 3,861 | 86 | function [f, data, comments] = import_adicht(file_path)
% Author: Jürgen Graf
% date: 23.05.2021
% dependent on:
% Installation Simple Data File SDK (provides a Windows dll)
% found in C:\Program Files (x86)\ADInstruments\LabChart8\Extras
% ADInstruments (LabChart) SDK from Jim Hokanson
% https://git... |
a6ebff3b58ef832dd06ded27a58d1665aa8a2e94803f29e893d270051b22f0d1 | MATLAB | 3,861 | 95 | % makeTraces.m
%
% usage: myscreen = makeTraces(myscreen,<verbose>)
% by: justin gardner
% date: 02/28/07
% purpose: makes traces from event times
%
function myscreen = makeTraces(myscreen,verbose)
% check arguments
if ~any(nargin == [1 2])
help makeTraces
return
end
if nargin < 2,verbose = ... |
610c3098bcdaa2f2784c01adb828a651c958cc8d411f8c38f160f3f4a439d65a | MATLAB | 3,863 | 136 | function tests = dataPipeTest()
tests = functiontests(localfunctions);
end
function setupOnce(testCase)
rootPath = fullfile(fileparts(mfilename('fullpath')), '..', '..');
testCase.applyFixture(matlab.unittest.fixtures.PathFixture(rootPath));
end
function setup(testCase)
testCase.applyFixture(matlab.unittest.fixtures.... |
8496dba7ca4e5949cba50d72c584e12abe8aa9bd5049e877635f849ec3d61df8 | MATLAB | 3,863 | 169 | function aedes_smiswrite(data,filename,varargin)
% AEDES_SMISWRITE - Write S.M.I.S. Data Files (*.sur)
%
%
% Synopsis:
% aedes_smiswrite(data,filename,param1,value1,param2,value2,...)
%
% Description:
% Write data to S.M.I.S. SUR-Format files.
%
% Examples:
%
% See also:
% AEDES_SMISREAD, AEDES_RE... |
7f6a3ec3d53c268071249f7e86279c1b65c43ae3668cafdc8a6156b9a85d5b61 | MATLAB | 3,865 | 100 | function Video_Player(hObject,eventdata,handles,varargin)
%
tic
% global index;
% index=index+1
handles=guidata(gcf);
cal_play_index=handles.cal_play_index;
objindex=get(handles.PlayVideo,'Value');
if objindex==1
set(handles.slider1,'Value',handles.frame_index);
video_index=find(handles.video_frame_bine_2-handl... |
6a2993a41df181a74d687ff4944d203fd121a9c9e87aea7e10b2ad5c8a1280e0 | MATLAB | 3,868 | 185 | function [chm, snrk] = modskew(ch,sk,p);
% Adjust the sample skewness of a vector/matrix, using gradient projection,
% without affecting its sample mean and variance.
%
% This operation is not an orthogonal projection, but the projection angle is
% near pi/2 when sk is close to the original skewness, which is a realis... |
bf2a1d700e954e752921877013dfd26adea28487819aa9dfd788d371bcb74a49 | MATLAB | 3,871 | 118 | function [acc,left_num,right_num] = TWFB_DGFMDM(MIEEGData,label,Fs,LowFreq,UpFreq)
% Input:
% MIEEGData:The raw motor imagery data
% label: motor imagery data label, 1 and 2
% Fs: the sampling frequency (in Hz)
% LowFreq: High pass filtering parameter settings
% UpFreq:Low pass filtering parameter settings
... |
c3f36e907af449ea790281ac3b20d97e5e99aaaa476502f887ebd16b6a74634d | MATLAB | 3,871 | 135 | % run_simulations_residuals_global_local_shuf.m
% to generate a new set of
% 540 x 100 simulations
% (# param combos x # iter)
% will test residuals, global shuffling, local shuffling
%%
clear all;
close all;
clc;
%% add fn paths if not added yet
% assumes script run within local directory
scriptdirs = {
'../../analy... |
022d87de01826c6ffd2ebb188563f8800896953f8e7b1a70db89efe220a99f39 | MATLAB | 3,872 | 114 | % ephysIInj.m
%
% Trial Type Function
% Records ephys channels, performs current injection
%
% INPUTS:
% settings - struct of ephys setup settings, from ephysSettings()
% duration - duration of trial, in seconds
%
% OUTPUTS:
% rawData - raw data measured by DAQ, matrix where each column is data
% from a di... |
498d7cd5713dbf8c46262ed808be1bc07aea61d305d5fde991f3f177ae95edfd | MATLAB | 3,874 | 139 | %{
For the best clustering, generate 2D matrices for LE(t) and dFC(t) centroids by
averaging according to the clustering. Next, average while multiplying the
dFC(t) by occurrence.
Adapts code from:
https://github.com/juanitacabral/LEiDA
https://github.com/trendscenter/gift
Output:
k_LE.h5 2D centroids for LE(t).
k_... |
beaae5d27e47d2d56093459cf61ba14c35c51b321109a89905822fd6852de262 | MATLAB | 3,875 | 95 | function [b_sensitivity] = lookupBS(separation)
%LOOKUPBS Brain Sensitivity lookup table
% Returns the brain sensitivity (white + gray matter only) of a SD
% separation. Assumes a five layer slab model. If the SD separation is
% not an integer, brain sensitivity is linearly interpolated. The max SD
% separation... |
6b1274d56b43595e4779cb767f533bb406d6aa658fc861f65c0835918bf5c15f | MATLAB | 3,876 | 92 | function ms = msGenerateVideoObj(dirName, filePrefix)
%MSGENERATEMS Summary of this function goes here
% Detailed explanation goes here
ms.dirName = dirName; % Added by GE to keep track of where the files were initially
MAXFRAMESPERFILE = 1000; %This is set in the miniscope control software
% f... |
d1cdfbe5cc8c4815ae78c6df1f3929b1c40140937f3b6d462cdddf757948de28 | MATLAB | 3,878 | 175 |
% Author: Guosheng Lin (guosheng.lin@gmail.com)
% here shows an example of
% evaluating the segmentation performance of a trained model on the voc dataset:
% Before running this demo file for evaluation, you need to
% download the PASCAL VOC 2012 dataset and place it at:
% ../datasets/voc2012_trainval
function d... |
3728b0f8c37968b590b829ce1caf337e1ac0f97466a1ce8532da5ce906940241 | MATLAB | 3,883 | 128 | function create_climerics_matrix_average(obj, session)
tf = session.getAnalysisDirectory();
fn = fullfile(tf, sprintf('%s_ics.mat', session.getName()));
if ~isfile(fn)
warning('Can not create ics matrix average because (%s) was not found.\n', fn);
return;
end
fd = load(fn);
% Use cell-like cells OMG
cellClas... |
0996ce88bb11e2edecb59b8e64de2f0d0ac74bc4e330d6a1da977f359b29d451 | MATLAB | 3,885 | 99 | %% BICEPS
%% Overview
%% Example
%% Exploring the outputs
%% Rationale
%% Recommended steps in preparation to run it smoothly
%% Explore BIDS folders, get list of participants and report counts
%
% To feed the GUI_environments you need a list of participants (paths to
% BIDS formatted data). You ca... |
c92078b11920081536040a9f17ba837820e09e41be4b09675fe0fe18c11460df | MATLAB | 3,885 | 103 | function fH = plotDNST_CSTopt_CViolinPlots(params,roisToPlot,...
cmapModels, saveFigs, saveFigDir)
%% CV-R^2 violin Plots
modelName = {'CST_{fix}','CST_{opt}','DNST'};
cmapModelsCell = {cmapModels(1,:);cmapModels(2,:);cmapModels(3,:)};
mnR2 = NaN(9,3,7);
fH = figure; set(gcf,'Position',[500 1 965 9... |
321e9ab34436cf7c82249332502ccc129092e26c05cd188a5ce953ca96f6e876 | MATLAB | 3,886 | 122 | function [F_ancova, P_ancova, DF_ancova, T_post, P_post, DF_post] = gretna_ancova1(Data, Cova)
%==========================================================================
% This function is used to perform one-way ancova on independent samples.
%
%
% Syntax: function [F_ancova, P_ancova, DF_ancova, T_post, P_post, DF_... |
c3da74852885582c4e44b7673e25f5c38f9789f982866eee45a628961d18e6d4 | MATLAB | 3,887 | 100 | function fH = plotDNST_CSTopt_DiffCV_BarPlot(params, roisToPlot, cmapModels, saveFigs, saveFigDir)
% Preallocate space
mean_diffCVR2_acrossVoxels = NaN(7,length(roisToPlot),length(params));
maxNC = mean_diffCVR2_acrossVoxels;
diffCVR2_allVoxels = cell(length(roisToPlot),length(params));
ipsIdx = cellfind(... |
3aaa705f00d5dfd2f128064d908581aa3a113b5dd7d076a1502a955dc3a2a144 | MATLAB | 3,889 | 128 | % 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... |
8c52f182f94f2ff437802afc7f353e45e9f5d9b184917f0e7fc80f842c73f14f | MATLAB | 3,889 | 98 | function spm_progress_bar(action,varargin)
% Display a 'Progress Bar' in the 'Interactive' window
% FORMAT spm_progress_bar('Init',height,xlabel,ylabel,flgs)
% Initialises the bar in the 'Interactive' window.
% If flgs contains a 't', then use tex interpreter for labels.
%
% FORMAT spm_progress_bar('Set',value)
% Sets ... |
bd53f6e9ef593cb28f6a98ed8df1504061f4a7eefd04cd473d45246291c7395a | MATLAB | 3,891 | 121 | function plot_trajectories_prep_exec_after(score,idx_dir,t_from,duration_range)
%% plot_trajectories_prep_exec_after plots the trajectories corresponding to different directions (of the same duration range) during movement preparation,
%% movement execution and after movement end
%
% INPUTS
%
% score: Projection of th... |
faca63f312bd5193accc8757b2b8318007e78a7056a962a8fad52c07184c978f | MATLAB | 3,893 | 126 | % returnDFF.m
%
% Function that converts background-subtracted fluorescence signal into
% dF/F (for 1 channel data) or dR/R (for 2 channel data) for a single
% trial folder. When there is only 1 ROI, prompts user for whether it's
% left or right cell. When there are 2 ROIs, also returns sum and
% difference of dF/F... |
e56f77890d44ec39cc31014ed6125458f87d5870ff8fc7945871d43748349e83 | MATLAB | 3,894 | 94 | function [fa, md, rd, ad, cl, SuperFiber, fgClipped, cp, cs, fgResampled, myValsFgSTD] = ...
dtiComputeDiffusionPropertiesAlongFG(fg, dt, roi1, roi2, numberOfNodes, dFallOff)
% Compute a weighted average of a variable (FA/MD/RD/AD) in a track segment
%
% [fa, md, rd, ad, cl, SuperFiber,fgClipped, cp, cs, fgR... |
d3a01b81f555557de1fee443bad1d06b0b1c576cb942e8749af53a62e3de80ff | MATLAB | 3,896 | 122 | function PlotConfusionMatrix(data)
title1 = {'CSP+LDA','FBCSP+SVM','TSLDA+DGFMDM','TWFB+DGFMDM'};
for fig =1:4
Sub1 = subplot(2,2,fig); % »æͼ£¬°´1ÐÐ3ÁÐÅÅÁÐ
mat = data{fig,1};
% ±êÇ©
label = {'Right Hand','Left Hand'};
% »ìÏý¾ØÕóÖ÷ÌâÑÕÉ«
maxcolor = [50,114,189]; % ×î´óÖµÑÕ... |
6f6dff6a09e4422749c8370ff333acad74a849ed37058007732afb255bae6952 | MATLAB | 3,897 | 72 | classdef IntracellularRecordingsTable < types.hdmf_common.AlignedDynamicTable & types.untyped.GroupClass
% INTRACELLULARRECORDINGSTABLE A table to group together a stimulus and response from a single electrode and a single simultaneous recording. Each row in the table represents a single recording consisting typically ... |
59e39b051177a5fdca94ca359d4f899e209a316d96e03ad60b1bbf264e321c5c | MATLAB | 3,898 | 106 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [output] = compute_cell_rate_difference_matrix_by_context(firingRates, trialIds, contextIds, rateMatrixNumTrials)
if rateMatrixNumTrials <= 0 || length(rateMatrixNumTrials) ~= 1
error('rateMatrixNumTrials must be... |
f596214fb0ad111145c69b07f8a59be1dbb484240517656ceccb18e69876701e | MATLAB | 3,898 | 90 | % Designate Paths
[pathstr, ~, ~] = fileparts(pwd);
usedir = pathstr;
codedir = pwd;
rawdata = fullfile(usedir, 'bids', 'sourcedata', 'Scan-Investment_Game', 'logs');
sublist_file = fullfile(codedir, 'sublist_all.txt');
subjects = table2array(readtable(sublist_file));
for ii = 1:length(subjects)
try
sub... |
3a10a95d76606b7d8a645724d2940720943cd8484d00a963ada493af9ae13fcd | MATLAB | 3,900 | 120 | function names = nii_deface(job, overwrite)
% extends nii_deface to remove excess neck and face details
% Face strip images
% FORMAT names = spm_deface(job)
% job.images - cell array of NIfTI file names
%
% names - cell array of de-faced images
%
% This is a little routine for attempting to strip the face from... |
57b0ec7ab6937020eb503d841c3d8b3e2b06bdbb001d86971f7ef1004cad3ca2 | MATLAB | 3,902 | 146 | function take_snapshot(DATA,ROI,AddInfo)
% TAKE_SNAPSHOT - A snapshot plugin for Aedes
%
%
% Synopsis:
%
% Description:
%
% Examples:
%
% See also:
%
% This function is a part of Aedes - A graphical tool for analyzing
% medical images
%
% Copyright (C) 2006 Juha-Pekka Niskanen <Juha-Pekka.Niskanen@uku.fi>
%
% De... |
b1eef0a20e07ae837ac30918b0e94485f52a32e51638e35f641f663f49d23cb5 | MATLAB | 3,902 | 100 | %% Description
%{
This script detects transient neural oscillatory bursts from the mouse LFP
signals, bandpass filtered by the user-defined frequency range. The time
point and amplitude of the detected bursts, along with their binary event
markings, will be saved as an output.
%}
%% Configure Library Path
UTIL_DIR = ge... |
359548c52fa26eabf436bbb282548b5bf17a663ace6f39bc387e57e005faa955 | MATLAB | 3,906 | 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)
% OPTION... |
754f1872799afef9d7c29e1a24ecd1f09aadd82488684b39945684a44b64811a | MATLAB | 3,911 | 97 | %% Concatenate all the videos of the trials into one data set that spans the entire session.
function ml_miniscope_pipeline_concatenated_make_scopevideos(session)
numTrials = session.getNumTrials();
%fprintf('Processing session %d of %d (%s)\n', iSession, numSessions, session.getName());
sessionDirec... |
e043b9d91dcb657ad7f6a9648446f821c201b10dc2d9522aa0a495e015b54251 | MATLAB | 3,914 | 89 | function [start_index, end_index, min_dist_index] = find_next_section(binary_annotation, current_index, backwards_or_forwards, all_center_line_tips)
%finds the next section bounded by 1s going either forwards or backwards in time
if strcmp(backwards_or_forwards, 'b')
%going backwards
%find wher... |
7deb6a27a5cbee4d69b994ed7c1898ad7d8f44f0843a514887d5b88bbd8cbb25 | MATLAB | 3,915 | 118 | function alpha=krippendorff(data,scale)
% alpha=kriAlpha(data,scale)
% calculates Krippendorff's Alpha as a measure of inter-rater agreement
% data: rate matrix, each col is a rater or coder, each row is a case
% scale: level of measurement, supported are 'nominal', 'ordinal', 'interval'
% missing value... |
835fdae3cb2aedf8e0658ef553a3ceefb2413574010f13300c3a3d8badf70cf3 | MATLAB | 3,916 | 121 | %function gm_raster_vertical(data_dir, id, item_or_loc, spiketable)
%
% Mackay et al. 2024 (DOI:10.1038/s41467-024-52295-5)
% License: MIT License (see LICENSE file for details)
% -------------------------------------------------------------------------
function gm_raster_vertical(data_dir, id, item_or_loc, spiketable... |
d8d49625be7115819115991e6a5e7b09758f691ffa9738508080264b20b3524a | MATLAB | 3,916 | 82 | %first download and add the Neural Decoding Toolbox (NDT) :http://www.readout.info/downloads/
%Meyers, E. (2013). The Neural Decoding Toolbox. Frontiers in Neuroinformatics, 7:8
% dataset_design,uncertain split 3 phase
dataset_design
% train by one phase, test by other phase
stabletrain_uncertaintest
uncertain1tr... |
641a8cb3aff3f1cc0622b98922aaca0d9a901321a211947524275794eafc0249 | MATLAB | 3,917 | 97 | % function [RegressionSummary] = multivariateregression(Y,X)
%Multivariate multiple regression on DVar Y along dimensions d and IVar X along dimensions p.
%Y is the dependent variable, each row subject, each column is condition. Xmat is matrix containing IV, should be all n x p, where n is subject
%and every column p ... |
d15159c5869e3f5154588f6970d2f9225d452c3bc93c11721cac2d3a865a4b2e | MATLAB | 3,918 | 102 | function vol = ft_datatype_vol(vol, varargin)
% FT_DATATYPE_SOURCE describes the FieldTrip MATLAB structure for volume data
%
% The vol data structure represents data on a regular volumetric 3-D grid, like
% an anatomical MRI, a functional MRI, etc. It can also represent a source
% reconstructed estimate of the activi... |
5296dfcfc76502968b0676804baafe3856f8a88be37371bbe03ceba0e89085a8 | MATLAB | 3,919 | 98 | % preprocessFicTrac.m
%
% Function for preprocessing raw FicTrac voltage data acquired on the user
% DAQ. Called by preprocess(). Takes 0-10V signal of heading, intX, and
% intY and returns angular position and velocity for each dimension. For x
% and y, also returns position and velocity in distance units (mm). Raw... |
30e57039e3158bc6e6c5ac3e2a55b4e7caf335a8ac71dd1e38684c8d623588e4 | MATLAB | 3,921 | 132 | function [] = ExtDataFig05_pIP10_OptStim_TuningCurve_Neuron()
% Code for plotting the tuning curves of calcium signals of each neuron induced by optogenetics in Extended Data Fig. 5h.
GT = 'TN1dsx';
switch GT
case 'TN1dsx'
ylimrange = [-1,4];
end
%% parameters
nTrials = 3;
nStim = 6;
T = 1370; % T
Thre_... |
b2f067d5b7ff8609742520f5cc14308357c25dad3cf45050817929794de7d401 | MATLAB | 3,923 | 105 | %% msRun2018
% Version 1.0 GE
% Updated version of the msRun script originally proposed by Daniel B
% Aharoni to analyse miniscope 1p calcium imaging data.
% This version is build on top of the original package to maximize compatibility.
% It includes NormCorre for image registration, CNMF-E for source extraction,
% an... |
3284cc8d10c43ed5a0f12b70696f98f765ec015b6307333b0a270eb3a5240cf6 | MATLAB | 3,925 | 75 | function [probe] = rotateModules(probe, moduleidx, rotate_amount)
%ROTATEMODULES Rotates modules within a probe
% Rotates modules within a probe layout by rotate_amount. Modules are
% identified by their module idx. moduleidx can be a vector of module ids
% in the probe. If moduleidx is empty (ie []), then the el... |
7ee45a780ff90d290ea78a2006ca85c3f0b575fc4dda906e7ed3253e23b2f4ad | MATLAB | 3,926 | 98 | function roc = genAlgorithmPairROC(cnmf,pcaica,suite2p,est,varargin)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Input parsing
if nargin > 4
N = varargin{1};
else
N = 0.5;
end
if nargin > 5
cutoff = varargin{2};
else
cutoff = 0.5;
end
if isempty(cutoff)
cutoff ... |
bef37492cbdd3621b0c4de95c359a7f316116ca082134fb31e886d4507f6192e | MATLAB | 3,927 | 106 | function [frame_thred, noisy, final_thred] = threshold_frame(frame, thred_inten, target_area, unmasked)
[Lxm,Lym] = size(frame);
if ~exist('unmasked','var')
unmasked = true(Lxm,Lym);
end
final_thred = thred_inten;
frame_thred = frame > thred_inten;
noisy = false;
[L,nL] = bwlabe... |
41898f753a353ca7a87eb7c15355dadb53aced3bd56542ef38d149a4625e326e | MATLAB | 3,928 | 138 | % plotCondLegStepParam_allFlies.m
%
% Function that takes output files from saveLegStepParamByCond_fly() and
% generates a plot of the legStep param for each leg. Plots mean +/- SEM
% for each fly. Different conditions in different columns. Points from the
% same fly are connected by lines.
% Select output files t... |
88a8f62762314a7b411b17fd2ce8bda60ec29d243cd976f7395e09f6187cf9c3 | MATLAB | 3,929 | 80 | function tracker(videos, options, calibration_file_name, vinfo_or_video_file_name)
% Track (and calibrate) videos.
%
% To run tracker with interface, use:
%
% tracker
%
% To run tracker without interface, use:
%
% tracker(videos, [options], [f_calib], [vinfo_or_video_file_name])
%
% where [] denotes an optional par... |
cdaae8947ec0b458c4a5beb7a48da37148c510623820144b8b6d83b8e3512a3c | MATLAB | 3,929 | 145 | function [avr] = read_besa_avr(filename)
% READ_BESA_AVR reads average EEG data in BESA format
%
% Use as
% [avr] = read_besa_avr(filename)
%
% This will return a structure with the header information in
% avr.npnt
% avr.tsb
% avr.di
% avr.sb
% avr.sc
% avr.Nchan (optional)
% avr.label (optional)
%... |
debd2fe707e28fe26500978fc6f04cbd3f4864e012990aa70bf637a6c7352c23 | MATLAB | 3,929 | 128 | function [verts, faces] = mne_read_surface(fname)
%
% [verts, faces] = mne_read_surface(fname)
%
% Reads a FreeSurfer surface file
%
% fname - The file to read
% verts - Vertex coordinates in meters
% faces - The triangle descriptions
% NOTE: The quad file faces are split by this routine... |
6f49b1d366d50eb52f5f0b10f87eb29a3d88e61ec7073e5f2921f2be4dd136be | MATLAB | 3,930 | 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 ... |
cbfc1e030e7834ee2f493bceae92d3afd3ff8b9e777fe82d23516566dd38c897 | MATLAB | 3,930 | 137 | function [] = Fig01_AveTimeCourse_OptStim_Song
% Code for plotting the average time course of pulse and sine song during optogenetic activation of dPR1 and TN1A neurons in isolated male flies in Fig. 1c,d.
GT = 'dPR1_Chr'; % Fig. 1c: dPR1 > CsChrimson
% GT = 'TN1_Chr'; % Fig. 1d: TN1A > CsChrimson
switch GT
case ... |
4f409bc863829ef16264c09733efe6a3767d9a25b8691b81606e4c5e4c1dcc37 | MATLAB | 3,934 | 138 | function [R] = randomizer_bin_und(R,alpha)
%RANDOMIZER_BIN_UND Random graph with preserved in/out degree distribution
%
% R = randomizer_bin_und(A,alpha);
%
% This function randomizes a binary undirected network, while preserving
% the degree distribution. The function directly searches for rewirable
% ed... |
08c028930097acf12f4d4c85be84fbe92d98e0400e8134d93e48145d88fe6582 | MATLAB | 3,936 | 86 | % dir_SUNS_sub = fullfile('SUNS_TUnCaT_SF25','4816[1]th6');
% dir_SUNS_sub = fullfile('SUNS_FISSA_SF25','4816[1]th3');
% dir_SUNS_sub = fullfile('SUNS_TUnCaT_noSF','4816[1]th2');
% dir_SUNS_sub = fullfile('SUNS_FISSA_noSF','4816[1]th2');
addpath(genpath('.'))
%%
% name of the videos
list_Exp_ID={'Mouse_1K', 'Mouse_2K'... |
830f7b828a0589e8dcf3f2b7c742f007a8dc52452823f8cb7bb53259227169a5 | MATLAB | 3,936 | 127 | function newfig = figs2subplots( name , tiling , arr )
% FIGS2SUBLPLOTS Combine axes in many figures into subplots in one figure
%
% The syntax:
%
% >> newfig = figs2subplots(handles,tiling,arr);
%
% creates a new figure with handle "newfig", in which the axes specified
% in vector "handles" are reproduced ... |
4f1f8325fdeaf9c5da6884632bfba689dcfb7d63bfa7480995bd9cd8974e9b0d | MATLAB | 3,939 | 64 | function reorderRecordings( obj, order_indx )
% Change the streaming recordings order.
%
% Syntax:
% REORDERRECORDINGS( obj, order_indx );
%
% Input parameters:
% * obj - object containg data
% * order_indx - array with new order
%
% Example:
% REORDERRECORDINGS( obj, indx_alpha, indx_beta );
%
% Available at... |
b6ddeeedf7a753cec1102558b0943a84568e7a0a9ab71ecfd37cf901fae47fec | MATLAB | 3,941 | 107 | function CBIG_ASDf_visualizeFactorComp(sub_info_file, factorComp, K, output_name)
% CBIG_ASDf_visualizeFactorComp(sub_info_file, factorComp, K, output_name)
%
% This function plots participants' factor compositions for K = 2 and 3.
% For K = 2, the visualization is created using histogram; for K = 3, the
% visualizatio... |
09785c8636eed69df870ebe766aa2179cb2c6e3cabd1861452dea41cd22162bf | MATLAB | 3,944 | 86 | function [ISImax, pks, flags] = calcIBEImax(bins, ISIhist, mpd, voidParamTh, ISITh, elecNum)
% initialize variables
% array of ISImax threshold for burst detection
ISImax = zeros(elecNum,1);
% array of flags that tell if a channel is bursting or not
flags = zeros(elecNum,1);
% peaks detected
pks = cell(elecNum,1);
for ... |
6672237b35834c2adf318725f58b1560e5f50a0fcf3b95846d03d0985c44cf1e | MATLAB | 3,946 | 110 | %% Amplitude distribution
%% cleaning
clear
close all
%% input
[start_folder]= selectfolder('Select the source folder that contains the PeakDetectionMAT files');
if strcmp(num2str(start_folder),'0')
errordlg('Selection Failed - End of Session', 'Error');
return
end
cd(start_folder)
%% amplitude computation
... |
ccccd4959e339583abfec47108673374849571e11be45e31bd7547a69b09fa1d | MATLAB | 3,946 | 131 | %% LOAD
if ismac
load('/Volumes/Runyan2/Christian/Processed Data/Event Analysis/standard_ds_onsets.mat')
else
load('Y:\Christian\Processed Data\Event Analysis\standard_ds_onsets.mat');
end
%% MAKE VARIABLES
start=-30;
activity_length=10;
rg='yes';
corrs=cell(2,length(ds_events));
conditions={'SOM','PV'};
... |
c56ff6d4722a1c46aac85b71007b32c7d5756a9b11ee1f3f1f517c973ae037cc | MATLAB | 3,948 | 138 | %% structure parameters
num_columns = 1;
npp = 100;
ppc = 2*npp;
num_VTA = 100;
N = ppc*num_columns + num_VTA;
pop = num_columns*2;
n = N;
unit_num = 1:2:(2*num_columns);
% num_trials = 600;
num_trials = 80;
%% time parameters
dt = 1; %time step
T = 100/dt; %time stimulated
T_R = 150/dt; %time of reward
delta = 600/dt... |
b51c66f9c385e0b2e768dba11db6a32fad5049de6ac03c33af705faca1260ea8 | MATLAB | 3,950 | 88 | function mltp_plot_rate_difference_matrix_average_days(obj)
averageMatrix = {};
seqNum = [];
cids = [];
labels = {};
numSessions = obj.Experiment.getNumSessions();
for iSession = 1:numSessions
session = obj.Experiment.getSession(iSession);
sessionName = session.getName();
... |
2af8271d3503629bbae8cf439058c436076c54c8fa111b8f29a385ef11bbfefd | MATLAB | 3,953 | 135 | % run_simulations_stdFR_stdRP_splines.m
% to generate a new set of
% 540 x 100 simulations
% (# param combos x # iter)
% and create residuals PSDs using
% either indiator functions or splines
%%
clear all;
close all;
clc;
%% add fn paths if not added yet
% assumes script run within local directory
scriptdirs = {
'../... |
68ed6ea70b6728bbe1067b4275fb1c5720241d3fb025815340f6bf987461f90b | MATLAB | 3,955 | 141 | function [P, beta] = d2p_sparse(D, u, tol, maxNeighbors)
%D2P Identifies appropriate sigma's to get kk NNs up to some tolerance
%
% [P, beta] = d2p(D, kk, tol)
%
% Identifies the required precision (= 1 / variance^2) to obtain a Gaussian
% kernel with a certain uncertainty for every datapoint. The desired
% uncerta... |
ce1c8da31e91d601ddbd7a9e7e7baf59db7b5dd74cd21defdd578e43859931c4 | MATLAB | 3,959 | 152 |
function net_config=gen_network_main(train_opts)
fprintf('\n generate network...\n\n');
net_config=gen_init_net_config();
net_config.ref.group_counter=0;
net_config.ref.root_group_info=My_net_util.gen_group_info_basic(net_config, 'root');
group_output_info=gen_multi_featnet_group(train_opts, net_config);
g... |
ea55a2b25c85ac5630b56def9feb22347b279d3d6b32a33b1e41b62d7b4f41c4 | MATLAB | 3,959 | 138 | function [] = ExtDataFig04_OptStim_TuningCurve_Neuron()
% Code for plotting the tuning curves of calcium signals of each neuron induced by optogenetics in Extended Data Fig. 4f,i.
GT = 'dPR1'; % Extended Data Fig. 4f
% GT = 'TN1SG'; % Extended Data Fig. 4i
switch GT
case 'dPR1'
ylimrange = [-.5,5];
ca... |
4b03da1d58def9410af9edc1809a7b1e4c820b9df3d12f480407280c4bf4ec0e | MATLAB | 3,964 | 93 | % load all EEG and fMRI datasets
%
% 2022-08-22 Jonathan Wirsich
function [allgroup_mean_fMRI, allgroup_mean_EEG, allsub_fMRI, allsub_EEG, groups, group_idx, conf_idx, bands, atlases] = loadDatasets4eeg_fmri_tle(atl)
[confs, confs_label, groups, eeg_conn_types, bands, atlases, serialized_path] = init_serialized_co... |
57b3ff8dc6cac9975cde54bc6d77b759d4cb9d864ab5b33968e2af1d07d73133 | MATLAB | 3,968 | 136 | %{
For the specified k and participant, extract dFC(t) across and within states
and within runs, calculate mean for FC strength and std for FC variability,
average across runs.
Output:
dFC_strvar.h5 Contains dFC FC strength and variability across all states and within states.
%}
%Define command line arguments.
funct... |
0c09413849c7eb0a3c809c23d3ef0d73007f5ee76653ff1d02bf875ffcef2f57 | MATLAB | 3,969 | 90 | function [if_both_hemi_match] = CBIG_gwMRF_check_example_results(output_folder, seed)
% This function checks if the generated example results are identical with
% the reference files provided for a given seed.
%
% Input:
% - output_folder: The path under which the generated example results is saved.
% - seed: indic... |
262c1ccf72e29c00a2f328c97a9e205a34ebe1f657cb017bdea6da4826604fa1 | MATLAB | 3,973 | 90 |
% function subject_FD_parse(FD_movement_files,skip_seconds,epi_TR,brain_radius_in_mm)
% function subject_FD_parse(runs,FD_movement_files,skip_seconds,epi_TR,brain_radius_in_mm)
% POST FIDL Version to read in new FD Vector
% Iterates over range of values from 0.1 to maximum of 0.5 FD threshold
% Outputs to .mat file
... |
040ba8674012b8849f330f5f4a1cde04125749ebeb9af9840f6420948d439037 | MATLAB | 3,977 | 143 | %% For Amin's Gen Analysis
%% Prep & Pre-allocate
clear;clc;close all
% get files
files = dir([cd '\**\normGainPost.mat']);
Hz_p2 = NaN(length(files),1);
Hz_p5 = Hz_p2;
Hz_1 = Hz_p2;
Hz_2 = Hz_p2;
Hz_3 = Hz_p2;
Hz_4 = Hz_p2;
mouse = cell(length(files), 1);
cohort = mouse;
Hz_p2_goodC = NaN(length(files), 4);
Hz_p5_go... |
ec574e883f14f1ad11f6e4d4fa170fce3f8392403e8caa7a89888c1b9c60318a | MATLAB | 3,978 | 116 | %Test FmaxGRP function
%
%AUTHOR: Eric Fields
%VERSION DATE: 12 June 2020
global test_xls_output
if isempty(test_xls_output)
test_xls_output = true;
end
%Load GRP
FMUT_dir = fileparts(fileparts(which('A_setupTest')));
load(fullfile(FMUT_dir, 'testing', 'data', 'Disflu_GroupLevel.GRP'), '-mat');
%De... |
62c56237fa3894f6f0d5a359fe6f9e13e4d6a51f9d34e346c0da53093a45d8eb | MATLAB | 3,980 | 124 | %% Side prediction using rates and SVMs
% CMG
% 7/15/2022
data_path = '/Users/celia/Documents/two_context_data'; % change this
load(fullfile(data_path, 'ratemaps-2021_12_1_12_34_49_K1_d4.mat'));
minTrial = 4;
animals = extractfield(ratemaps.data, 'animal');
cPred = cell(length(animals),3);
northDigs = {'Corr'};
sout... |
6a05914f466cbac112b4f4d203492fe085ddd3b3c1dd0b53952fa63e917bfdf8 | MATLAB | 3,980 | 98 | function [event] = read_nmc_archive_k_event(eventfile)
% READ_NMC_ARCHIVE_K_EVENT extracts event-data from nmc_archive_k datasets
%
% Use as
% event = read_nmc_archive_k_event(eventfile)
%
%
% This function specifically only reads data from one of the archived
% datasets of the Neurophysiological Mechanisms of Cogni... |
dc16629aff5c24c2e4d41a6a3fc380edaa9f4577fd2f168ea584dc0773d52046 | MATLAB | 3,980 | 133 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
% Figure S16A and Figure S16B (Absolute Rate Difference for Tetrodes separated by cell type)
% This uses the min occupancy of 50%.
close all
clear all
clc
% Paths
run('../load_figure_config.m')
INPUT_FOLDER = CHENGS_TASK_2C_FIGURES... |
1af2262c3061aa102da65feb6eda39a0e1d0be0b3a265b180ea86d3bc6544cbd | MATLAB | 3,981 | 115 | function val = checkDtype(name, type, val)
%ref
%any, double, int/uint, char
persistent WHITELIST;
if isempty(WHITELIST)
WHITELIST = {...
'types.untyped.ExternalLink'...
'types.untyped.SoftLink'...
};
end
%% compound type processing
if isstruct(type)
names = fieldnames(type);
assert... |
2426d6b3f0378d7c6b6c2f76b6e7cb52bc2ad34d28fcedcda75e14c3a3d20987 | MATLAB | 3,982 | 129 | function plot_ct_event(pyr_mean_activity,som_mean_activity,pv_mean_activity,save_yn)
frames=size(pyr_mean_activity,3);
num_ds=size(pyr_mean_activity,1);
%% PYR ACTIVITY DURING EVENTS
figure(99)
hold on
set(gcf,'color','w')
% Pyr during SOM
x = linspace(1,frames,frames)';
y = squeeze(nanmean(pyr_mean_activity(:... |
da7a0fbf009514af486f8d777082f78fd551e19fb4d7609f401e4b4400fc79f0 | MATLAB | 3,986 | 131 | function [acc,left_num,right_num] = TSLDA_DGFMDM(MIEEGData,label,Fs,LowFreq,UpFreq)
% Input:
% MIEEGData:The raw motor imagery data
% label: motor imagery data label, 1 and 2
% Fs: the sampling frequency (in Hz)
% LowFreq: High pass filtering parameter settings
% UpFreq:Low pass filtering parameter settings... |
2c3cf4b3d29551a90cfda73add5b55f072af5ac98a804659d7ea1600b7953a21 | MATLAB | 3,987 | 120 | function amps = Amplitudes(stimchans)
% function amps = Amplitudes(stimchans)
%
% this program runs through amplitudes in pseudo-random but increasing
% order for the given electrode pair. It takes about 10 minutes to run.
%
% INPUTS
%
% stimchans a 1x2 matrix with the two stimulation channels
cerestim ... |
e3a3691b22c4069d47d8af7445bbafd6d1b4a5597ed906ef82d02d37bf88bc77 | MATLAB | 3,987 | 98 | function fH = makeSupplFigure2_SuppressionDeltas(ds,lmmResults,roisToPlot, ...
cmapROIs,subjnrs,useSTRetParams,temporalModel, spatialModel, ...
saveFigs,saveFigDir)
% Function to reproduce supplementary figure 2:
% panel a: Difference in suppression level (LMM slopes) vs ROI vs stimulu... |
7cb2331392101b91f40fe24a5e15a3e4b5858fb62d28477c61c7494bd5103e21 | MATLAB | 3,990 | 94 | function [task myscreen] = taskTemplateDualSubsidiary(myscreen)
% This is an example of an RSVP task at fixation
% I've taken out the parts where I keep track of
% correct and incorrect responses, for the sake of
% keeping the code simple.
%
% In this task, subjects must press a key
% when they see an 'X'
% show RS... |
ec4031886fe8086e3ab8a7598f7825baf7135fa9af65c8d56100ba53b2aff05a | MATLAB | 3,990 | 101 | function [dat, dimord] = read_shm_data(hdr, chanindx, begtrial, endtrial)
% READ_SHM_DATA reads the data in real-time from shared memory
% this is a helper function for READ_DATA
% Copyright (C) 2007-2009, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.ru.nl/neuroimaging/fieldtrip
% for the docu... |
92cbcdaee8004539420258925c9c7e296ba1b9fe839ad0f5712d48a0242442a7 | MATLAB | 3,993 | 87 | % dir_SUNS_sub = fullfile('SUNS_TUnCaT_SF25','4816[1]th4');
% dir_SUNS_sub = fullfile('SUNS_FISSA_SF25','4816[1]th3');
% dir_SUNS_sub = fullfile('SUNS_TUnCaT_noSF','4816[1]th2');
% dir_SUNS_sub = fullfile('SUNS_FISSA_noSF','4816[1]th2');
addpath(genpath('.'))
%%
% name of the videos
list_Exp_ID = { 'c25_59_228','c27_1... |
550f7bd1636e9fc4e93f42b391e88f7c412d5af673b0f2924fef7839b5f1d480 | MATLAB | 3,995 | 104 | function [version] = hasyokogawa(desired)
% HASYOKOGAWA tests whether the data input toolbox for MEG systems by
% Yokogawa (www.yokogawa.com, designed by KIT/EagleTechnology) is
% installed. Only the newest version of the toolbox is accepted.
%
% Use as
% [string] = hasyokogawa;
% which returns a string describing ... |
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