sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
2a5f89beac66bae91916b1da90e95092ecd52aa8995a08e7221e78eade1c1a09 | MATLAB | 7,845 | 291 | function [] = ExtDataFig06_Example_AveSong()
% Code for plotting images for the example recordings in Extended Data Fig. 6a,c.
GT = 'nsybD'; % Extended Data Fig. 6a
% GT = 'nsyb'; % Extended Data Fig. 6c
switch GT
case 'nsybD'
TargetDataID = 10;
zrange = [2:9];
ylimrange1 = [0,1.7];
... |
e1fda91a4c197f49abaa9f6246845a8431d36d074b350aa3f1572789e99c1b0d | MATLAB | 7,849 | 258 | function image = readBESAimage(filename)
% readBESAimage reads information from exported BESA images (Beamformer,
% LAURA, sLORETA, swLORETA, LORETA, sSLOFO, User-Defined image, surface
% minimum norm, Probe scan, Sensitivity). The function poutput is a struct
% with fields containing all relevant information from t... |
40904684b20c816b006351052c1aed3fda30aa053c4592034f9518f878f1e30b | MATLAB | 7,850 | 167 | %% Script to obtain centiles and effect sizes between groups (relatives, PE, FEP, and chronic)
% Copyright (C) 2023 University of Seville
% Written by Natalia García San Martín (ngarcia1@us.es)
% This file is part of Neurobiology Centiles Psychosis toolkit.
%
% Neurobiology Centiles Mapping toolkit is free ... |
efe2fb38c8fa67fc9a36c3b434d8febf2cb794bf7d17e6b5b16611ab20253729 | MATLAB | 7,851 | 179 | %This script allows the user to pick a watershed region in a t-SNE map and
%finds when the animal stays in that region and plots their behaivor, not used in paper
%% STEP 1: establish plotting constants
N_rows = 10;
N_columns = 11;
N = N_rows*N_columns;
fps = 14;
frames_before = 5*fps-1;
frames_after = 10*fps;
norma... |
769514937e6a3a596a84348bc9b246055fd5915e2f7b26f262aec31371720ca1 | MATLAB | 7,856 | 150 | function [MatchTable, UniqueIDConversion] = AssignUniqueIDAlgorithm(MatchTable, UniqueIDConversion, UMparam)
%% Input:
% UniqueIDConversion (struct) with at east per cluster: OriginalClusID, GoodID & recsesAll
% A MatchTable (output table from UnitMatch)
% UMparam (struct) with at least: ProbabilityThreshold and GoodUn... |
f82ada0c335b86ac61bb09cd03b5ffad0cfa304de6da284ce0f9660f38dbfdb1 | MATLAB | 7,860 | 217 | function [] = ExtDataFig05_AveTimeCourse_OptStim_Neuron()
% Code for plotting the time course of ΔF/F recorded from TN1 in Extended Data Fig. 5c.
GT = 'TN1dsx';
%% parameters
nTrials = 6;
nStim = 6;
T = 1370; % T
PreEventImg = 72; % 10 s (71.0443)
OneTrialDur = 214; % 30 s (213.1329)
StimTarget = [3];
Thre_nTrialO... |
077df8dd871f20984c7a020306852ba35e12b36cff0f6e65219d89e75ccebec9 | MATLAB | 7,865 | 249 | clear all
close all
% Fig. 8I, compressive Stress fibers
P.y0 = 180;
P.x0 = sqrt(P.y0^2 - (P.y0/2)^2);
P.max_y0 = 17*P.y0/2;
P.max_x0 = P.x0*15;
[r_s,T_s,edges_s,edge_type] = create_mesh(P);
aux = find(r_s(:,2) == min(r_s(:,2)));
P.stress =aux;
edges_s = [edges_s;aux(1:end-1) aux(2:end)];
aux = find(r_s(:,2) == m... |
203e93dc44cc935a88953d393bb58d3678de67175551c550102e411f3166c9eb | MATLAB | 7,872 | 156 | function exp2keep = getNatImExpRef(binFile)
%%% Find the experiments associated with a binFile
if ~isstruct(binFile)
binFile = dir(binFile);
end
% Get info -- hardcoded but shouldn't change...?
info = split(binFile.folder,'\');
server = ['\\' info{3} '\' info{4}];
subject = info{5}... |
8d10e431beb9d2a0f65675fbef1a6c575b457a785b1ca0f50d00a3eb3928d869 | MATLAB | 7,876 | 210 | function [r,t,pval,hboot,CI] = Spearman(X,Y,fig_flag,level)
% Computes the Spearman correlation with its bootstrap CI.
%
% FORMAT: [r,t,p] = Spearman(X,Y)
% [r,t,p] = Spearman(X,Y,fig_flag,level)
% [r,t,p,hboot,CI] = Spearman(X,Y,fig_flag,level)
%
% INPUTS: X and Y are 2 vectors or matrices, in the... |
5ca6f40b7b476fcd5dc99f94fed6303964a7196e82f1d58be4e43276893e1830 | MATLAB | 7,877 | 219 | function [HDR] = leadidcodexyz(arg1)
% LeadIdCodeXYZ uses the Label information for computing the
% LeadIdCode and the XYZ position of the EEG Electrodes
% according to Annex A of FEF Vital Signs Format [1]
%
% HDR = leadidcodexyz(HDR);
% adds HDR.LeadIdCode and HDR.ELEC.XYZ, if needed.
%
% see also: S... |
e7099e887eb274732f8f27b6e4431b14e9d5473b8e3e699440e090854b5756fc | MATLAB | 7,882 | 222 | function plotSummaryStreaming( obj, varargin )
% Computes and plot summary of visualizations for LFP streaming recordings
% Raw data, spectrogram, and Scalogram
%
% Syntax:
% PLOTSUMMARYSTREAMING( obj, data_type, varargin );
%
% Input parameters:
% * obj - object containg data
% * data_type - type of input data (... |
fae3962a802a5d4ae3936603c892e4c7eb8e2c83fe1bd376f7c76db6f268e46b | MATLAB | 7,890 | 257 | function script03_compute_volume_fractions()
% Compute volume fractions
% This script needs results from script:
% script02_proofread_vols.m
% It also needs the information in the text file
% 000_animal_exp_axons_cells_nx_ny_nz_cclims_cglims.txt
% The results of this script will be saved in folder
% White_matter_EM_01... |
cf8867e63056eba6e87c3a3c948b50e1679f19a844136e911ca17d20a9f2f20a | MATLAB | 7,907 | 206 | %% Set up and perform Monte Carlo simulation of diffusion in randomly positioned, randomly oriented sticks
clear
restoredefaultpath
filePath = matlab.desktop.editor.getActiveFilename;
root0 = fileparts(filePath);
addpath(genpath(fullfile(root0,'lib')));
root = fullfile(root0,'data');
%% Calculate the mean length of ra... |
86f925dea7d2fea910464c96842288deb273f41291654193ae83f4a57416c3eb | MATLAB | 7,913 | 121 | % This script reads the data from paingen placebo study (demporaphic, behavioral and
% brain measures), and then runs mixed effects models for the correlations between behavioral and neural placebo-induced reductions, accounting for the
% familial structure of the data (consisting of monozygotic and dizygotic twins).
%... |
42e096635273282105ebb3954133dbdbe16abbf778ec5295aa3d0b71a70a79b7 | MATLAB | 7,919 | 168 | function group_obj = extractGroupsInformation( obj, data )
% Extract groups information from one session
%
% Syntax:
% group_obj = EXTRACTGROUPSINFORMATION( obj, data );
%
% Input parameters:
% * obj - object containg data
% * data - data from json file(s)
%
%
% Example:
% group_obj = EXTRACTGROUPSINFORMATION... |
7aea09f0f15002da3323a3b488229a34ae59d38740b8cc78b9047bc1bcb51349 | MATLAB | 7,924 | 260 | %% Open Excel File
clear;clc;
[dataTable] = readtable('G:\My Drive\Expmt Data\Max\Climbing Fiber Project\ExperimentMetadata_C.xlsx');
www = table2struct( readtable('G:\My Drive\Expmt Data\Max\Climbing Fiber Project\ExperimentMetadata_C.xlsx') );
writetable(dataTable, 'G:\My Drive\Expmt Data\Max\Climbing Fiber Projec... |
1ca35a022a34166c9c79ab0d7a2c9a5e63789b6dd1aff3043629301eb3a95ef5 | MATLAB | 7,931 | 142 | %The code for the research presented in the paper titled "Enabling inverse design of plasmon-based nonlinear square resonators with deep neural networks."
% In this code, first and second-order derivatives of transmission spectrum versus wavelength will be calculated.
% In this code, local minima and maxima will be... |
500595a5071e4a5927ef2b3204ab8fd9bbd03f1e3e4979d068913dcc6431a3c8 | MATLAB | 7,934 | 203 | % computeHeatmap_pData.m
%
% Function that takes in user-specified pData file, which has been run
% through filtering of FicTrac and spike calling for ephys data, and
% returns heatmap(s) relating spike rate/voltage to forward
% velocity and yaw velocity or the counts
%
% Note: written 9/16/20 as probably temporary... |
3ff563ed17807baef0eca46c1c0b1a577a2711cd76701b950cfb6df287bedcb9 | MATLAB | 7,938 | 218 | % saveDFFCond_bouts.m
%
% Function that saves dF/F over time for turning bouts, defined by
% yaw velocity peaks. User can specify FicTrac conditions that yaw
% velocity peaks must meet as well as the initial forward velocity range
% and the change in forward velocity between the start and peak of the
% turn
% User... |
4e5d0e12cc58aefddbe3ba65491eefffbc1a286d8290a3ea217f8c14f502a0eb | MATLAB | 7,952 | 236 | % run_subsample_and_ROC_pbase_vary.m
% note: random seeds not available for this case
%%
clear all;
close all;
clc;
%%
%% add fn paths if not added yet
% assumes script run within local directory
scriptdirs = {
'../../figures';
'../../analyze';
'../../helper_functions';
};
datadir = pwd;
%%
addpath(scriptdirs{:})
addp... |
8222dd67d5a2a2d77d70b99b82a687b84126e0bf49a673a1b0372cb9cbb83042 | MATLAB | 7,952 | 194 | %% Network Burst Propagation
clear all
clc
% Load file to compute the NB propagation
[filename, pathname] = uigetfile({'*.mat'},'Select NetworkBurstDetectionFile with all electrodes');
if isequal(filename,0)
return
else
col = ['gray ' 'green ' 'red ' 'cyan ' 'yellow ' 'violet ' 'blue '];
str_comp = inters... |
42d30ef6253c075c2dc3c90085b44377f298fbe68d471a9e66762f03d9a1d5d8 | MATLAB | 7,959 | 184 | function predictions = stPredictBOLDFromStim(params, stim)
% Main wrapper function to predict BOLD time series (% change) from visual
% stimulus array, using a spatiotemporal pRF model. This pRF model is used
% in the following papers:
% * Characteristics of spatiotemporal population receptive fields across
% hu... |
38c6f1bd5d76a414a1164fff4494dad42aa6a268dc41414e6bd50ad34bc54008 | MATLAB | 7,972 | 235 | % mglOpen: Open an mgl window
%
% $Id$
% usage: mglOpen(whichScreen, screenWidth,screenHeight,frameRate,bitDepth)
% by: justin gardner
% date: 04/10/06
% copyright: (c) 2006 Justin Gardner, Jonas Larsson (GPL see mgl/COPYING)
% purpose: Opens an openGL window
% usage: open last monito... |
58558d673de91e2724bc183ff17b0996e2540371b5b4818c73ecc50a052b2bac | MATLAB | 7,973 | 203 | % computeKernelsHeatmap_pData.m
%
% Function that takes in user-specified pData file, which has been run
% through filtering of FicTrac and spike calling for ephys data, and
% returns kernels relating spike rate and median-filtered voltage to
% FicTrac parameters and heatmap relating spike rate/voltage to forward
% ... |
e52488f81b3231461a67140da0f50050483ff970270b2d0ab01ae0296aff1c17 | MATLAB | 7,974 | 295 | %% NetworkBurstPropagation - studio forma
clear
close all
clc
rng(2)
%% Data load (brutto e manuale)
% % Involved
% flag = 'involved';
% fig1 = openfig('InvolvedElectrodesHist_Sponge_DIV18_All');
% fig2 = openfig('InvolvedElectrodesHist_ECM_DIV18_All');
% fig3 = openfig('InvolvedElectrodesHist_Geltrex_DIV18_All')... |
1aee22c1700596c1ea9c08ad5200bf1acab2202c57c4f9d5b36b93ea99542d17 | MATLAB | 7,983 | 246 | %Test FMUT ANOVA calculations against MATLAB ANOVA calculations
%
%Author: Eric Fields
%Version Date: 12 June 2020
%Simulation parameters
n_electrodes = 32;
n_time_pts = 40;
n_subs = 16;
%% RB & SP DESIGNS PARAMETRIC ANOVA
%Designs to test
anova_designs = {2, ...
5, ...
... |
d703ac2cbf0875e9ced407f2cd04531973b989edb7669c0137d2d6011e92daef | MATLAB | 7,983 | 234 | function VOR_Summary_Sriram_CycleDiff(params, post, pre, Etitle, stim)
%% Prep
type = 1;% 1 == desaccaded, 2 == good cycles SRIRAM
load('result.mat')
%% Calculations
% extract dessaccaded mean traces
eyeVel_des_cycleMean_pre = cell2mat([result.eyeVel_des_cycleMean(pre)]');
eyeVel_des_cycleMean_post = cell2mat([resul... |
2d5b56116cc53c30f6b719c2410ec0196d4bc7f903f2e300f7a912e0700b7f92 | MATLAB | 7,986 | 206 | %% Set up and perform Monte Carlo simulation of diffusion in randomly positioned, randomly oriented sticks
clear
restoredefaultpath
filePath = matlab.desktop.editor.getActiveFilename;
root0 = fileparts(filePath);
addpath(genpath(fullfile(root0,'lib')));
root = fullfile(root0,'data');
%% Calculate the mean length of ra... |
67ec24387ceebf9681e0ff9ca0230553db7945c06a7e6385e965f24c70a2454c | MATLAB | 7,988 | 203 | % mglCheckEyepos.m
%
% $Id:$
% usage: mglCheckEyepos(stimfilenames,<taskNum=1>,<phaseNum=1>,<parameter=varname>,<segNum=1>)
% by: justin gardner
% date: 04/26/12
% purpose: generic function to check eye position
% e.g.: mglCheckEyepos({'120418_stim01','120418_stim02','120418_stim03',... |
1a65d34501d1fc266e452781aaf9aa7d5534e55cb281cd88de70ade18855a34a | MATLAB | 7,990 | 227 | function fH = plotVoxelpRFLocationAndTs(roiVoxelData, prfData, varargin)
% fH = plotVoxelpRFLocationAndTs(roiVoxelData, prfData, [TR], [conditionData], [roiName], [saveFigs], [savePth])
%
% Function to plot a single vertex or vertices pRF location next to it's time series
%
% INPUTS
% roiVoxelData : matrix wit... |
b2a4eb5e9d25527f6871cff8caa25aa13184fc18a553b5275a27ea2a7c6807ad | MATLAB | 7,992 | 254 | % plotViolinCondBoutsStepParam.m
%
% Function to plot 1D step parameters for bouts aligned to yaw velocity
% peaks. From output of saveLegStepParamCond_bouts()
% One figure with 6 subplots, 1 for each leg
% Can select more than 1 output file, will plot on same graph
% Has option to plot reference step (from saveLegSte... |
e97c41854464f62320a9dea31ab321db9c077d0d643b65b1022173e22b396262 | MATLAB | 7,996 | 222 | function [ LFP_ECGdata, text ] = filterEcg( obj, data, fs )
% Filter ECG artifacts from LFP recordings - streaming
%
% Syntax:
% [ LFP_ECGdata ] = FILTERECG( obj, data, fs );
%
% Input parameters:
% * obj - object containg data
% * data - data from json file(s)
% * fs - sampling frequency
%
% Example:
% ... |
d78ec4be65be35404ce6ae7b6ab94047c6b41585dac3bf3bc75534dbf51f7c9a | MATLAB | 7,998 | 211 | function state = dss_create_state(X_or_state, parameters)
% Initializes DSS state structure based on existing state
% and given parameters.
% state = dss_create_state(X or state, parameters)
% X Mixed source, matrix with row vectors as signals.
% state New or updated persistent algorithm state... |
9822d3065519f19c74da60e435f61e7d3aae177b6180b67a752abfe72a8c2d68 | MATLAB | 7,999 | 170 | %% read_mff_event.m
% Matlab File
% author Colin Davey
% date 3/2/2012, 4/15/2014
% Copyright 2012, 2014 EGI. All rights reserved.
%
% Takes the path to the data and returns the events in the structure
% described at http://fieldtrip.fcdonders.nl/reference/ft_read_event.
%
% filePath ? The path to the .mff file... |
b7899ea9128f698acf7477499253958a20741fdd7057171a942543ffb3fca72d | MATLAB | 8,007 | 192 | function result = runPLS_smri(ANALYSIS,data_type)
% runPLS_smri
%
% ANALYSIS = 'ELO' or 'A3D'
% data_type = 'ct' or 'sa'
%
addpath /Users/mlombardo/Dropbox/matlab/spm12;
addpath /Users/mlombardo/Dropbox/matlab/Pls/plsgui;
addpath /Users/mlombardo/Dropbox/matlab/Pls/plscmd;
rootpath = '/Users/mlombardo/Drop... |
c3cd55e3eaa809b7a164b632d288225703a35f16c885709072ab6ffa124984e8 | MATLAB | 8,007 | 221 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
% This reproduces Figure 7B (average rate difference bar plot). The full
% statistics were done in R.
close all
clear all
clc
% Paths
run('../load_figure_config.m')
INPUT_FOLDER = CHENGS_TASK_2C_FIGURES_CONFIG.DATA_FOLDER;
LOCAL_O... |
bac13fc9d41573d602c7ef7515a195567db6ae09d3336dca770693e833626f35 | MATLAB | 8,010 | 217 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
% This makes Figure 2E.
%
% Note that the figures were post-processed in Adobe Illustator.
close all
clear
clc
% Paths
run('../load_figure_config.m')
INPUT_FOLDER = CHENGS_TASK_2C_FIGURES_CONFIG.DATA_FOLDER;
OUTPUT_FOLDER = CHENGS_T... |
9ee93a1d95611c9a9ae524f139cf4e7ee3225c31cd6a82575a377aed3edbcd07 | MATLAB | 8,011 | 182 | function data=st_repair_artifacts(cfg_artifacts,data)
% ST_REPAIR_ARTIFACTS repairs channels segment-wise, as specified by
% a repair grid (typically created by ST_PROCESS_DETECTOR_RESULTS). Repair methods are interpolation, replace with zeros, or replace with NaNs).
%
% Use as:
% data=st_repair_artifacts(cf... |
8966a46e23a9b519dfc3052ea70c6cf3f4eaf1b9b439cd868ab4f13299d663e3 | MATLAB | 8,014 | 178 | function [myValsFgWa, SuperFiber, weightsNormalized, weights, fgResampled, myValsFgSTD] = ...
dtiFiberGroupPropertyWeightedAverage_sd(fg, dt, numberOfNodes, valNames, p)
% Average eigenvalues across the fibers, along the bundle length
%
% [eigValFG,SuperFiber, weightsNormalized, weights, fgResampled] = ...
% ... |
b354d02b23eeb10f7eb814bd12bdd17a97976165fc6e9345ed1beb1c7d8d552b | MATLAB | 8,021 | 206 | % Performs a permutation or randomization test to assess if a sample comes from
% a population with a value given for the mean or some other location parameter
%
% -- Function File: PVAL = randtest1 (A, M)
% -- Function File: PVAL = randtest1 (A, M, NREPS)
% -- Function File: PVAL = randtest1 (A, M, NREPS)
% -- Functi... |
2a3ae1c842cf84e1869cbb6c50750d3a843a8bdab07164526ee5636a23f43da8 | MATLAB | 8,023 | 212 |
function [output, Greg] = dftregistration(buf1ft,buf2ft,usfac)
% function [output Greg] = dftregistration(buf1ft,buf2ft,usfac);
% Efficient subpixel image registration by crosscorrelation. This code
% gives the same precision as the FFT upsampled cross correlation in a
% small fraction of the computation time and wit... |
5e13ca2de84bec930ac885fcf2f4cec9ae011fb5fa4e57b823b3e2378b0f27f3 | MATLAB | 8,023 | 271 | function [] = ExtDataFig05_Example_SongPrefIdx_dPR1()
% Code for showing how to calculate a song type preference n Extended Data Fig. 5a.
GT = 'dPR1';
TargetFileID = 2;
TargetROI = 1;
%% parameters
Thre_pulse = 0.1;
Thre_sine = 0.6;
Thre_Resp = 0.05;
nTrials = 6;
T = 1370; % T
PreEventImg = 72; % 10 s (71.0443)
One... |
bc95273794b2cc27007a8e17a3990144c0225964a6571ff1dd4f293210532e3a | MATLAB | 8,035 | 186 | function predictions = stPredictBOLDFromStim(params, stim)
% Main wrapper function to predict BOLD time series (% change) from visual
% stimulus array, using a spatiotemporal pRF model. This pRF model is used
% in the following papers:
% * Characteristics of spatiotemporal population receptive fields across
% hu... |
400c33180f9d51e4b4519bd4882ea1c7e903c28f334199ea0fc298ab36f32272 | MATLAB | 8,036 | 254 | function [options]= parseoptions(varargin)
%PARSEOPTIONS Create or alter a OPTIONS structure.
%
% CALL: options = parseoptions(legalFnames,options,funcname,opts1,opts2,...,
% par1,val1,par2,val2,...);
% options = parseoptions(options,opts1,opts2,...,
% ... |
94e5df272d69c7a808c46a04f445391b8f6d2e412b5678fbc4ef6addc7e7eecc | MATLAB | 8,040 | 154 | function [] = D1_ModulationIndex_Alpha(system,subj,append,plot)
% Caculates modulation indices for each subject
% system: 1->portal 2->windows
% subj: number of subjects you want to run the function on
% append: do you want all conditions to be appended (->1) or load conditions separate (->2)
% plot: do you want to plo... |
fb2c2782717d6f284c59c9771bf99e8833e6e5f9ea85051ce179ea4beb0713c9 | MATLAB | 8,041 | 215 | %% Set up and perform Monte Carlo simulation of diffusion in randomly positioned, randomly oriented sticks
clear
restoredefaultpath
filePath = matlab.desktop.editor.getActiveFilename;
root0 = fileparts(filePath);
addpath(genpath(fullfile(root0,'lib')));
root = fullfile(root0,'data');
%% Calculate the mean length of ra... |
321abf42767a066cd5d4ac6619cad6f845c1cae940055ec9505a5b2ca3b9f7b5 | MATLAB | 8,048 | 67 | function f = cmapturbo(n)
% function f = cmapturbo(n)
%
% <n> (optional) is the desired number of entries (no more than 256).
% Default: 256.
%
% Return a jet-like colormap that is more perceptually uniform.
%
% example:
% figure; imagesc(rand(100,100)); axis equal tight; colormap(cmapturbo); colorbar;
% inputs
if ... |
7550386064f16948ae7aa487971d890a44c7b867642902417bc17e8f0e14bfc9 | MATLAB | 8,050 | 243 | function distance_duration_vs_direction_all_sessions(Sessions,Areas,threshold,Ndir,Nbins,do_plot_supp)
%% distance_duration_vs_direction_all_sessions compares the distance between
%% trajectories corresponding to different movement durations (same
%% direction) and movements of adjacent bin directions (same duration... |
099f607b16a1cff5e2b5e99db367f705c3511dc2325cbce5e8874af4a79c72fa | MATLAB | 8,055 | 198 | %% read_mff_data.m
% Matlab File
% author Colin Davey
% date 3/2/2012, 4/15/2014
% Copyright 2012, 2014 EGI. All rights reserved.
%
% Takes the path to the data and returns the 2-D matrix of size
% Nchans*Nsamples as described at
% http://fieldtrip.fcdonders.nl/reference/ft_read_data.
%
% filePath ? The path ... |
0c627adb7ae2c7eec1a3689d0f6555dca87559ee27cfc037acea4d65e925a607 | MATLAB | 8,056 | 244 | function tf = ft_platform_supports(what,varargin)
% FT_PLATFORM_SUPPORTS returns a boolean indicating whether the current platform
% supports a specific capability
%
% Usage:
% tf = ft_platform_supports(what)
% tf = ft_platform_supports('matlabversion', min_version, max_version)
%
% The following values are allowe... |
c2db78406dd9b5b6d1550b13caaf5ae158d45cfc7c11536b17c76bce496a1894 | MATLAB | 8,058 | 277 | % plotCondBoutsAEPvsPEP.m
%
% Function that takes output
function plotCondBoutsAEPvsPEP(datDir, xyScale, ref)
% legs to subplot indices
% puts left legs on left, and front legs on top
subInd = [2 4 6 1 3 5];
% prompt user to select output files from saveLegStepParamCond_bouts()
disp('Select out... |
0c5875cbe37b44c3e0c486f7e755a4941ecc79a2fd1f54aa7417b0854cac81f1 | MATLAB | 8,060 | 244 | function handle = ternary_axes( var_general, var_outline, var_grid, ...
var_tick_line, var_tick_label, var_label )
% ternary_axes create basic outline, gridlines, and labels for a ternary plot
%
% handle contains children handle groups for the outline, grid lines, tick
% marks, tick ... |
dd6bc99cc179e5cf17342aea1081350d27b42b75f5491fbbf24cc0adee0c12ad | MATLAB | 8,061 | 289 | function [] = Fig08_Plot_InputOutputHist_Single_dPR1()
% Code for plotting the histogram in Fig. 8d.
%% parameters
pIP10 = [13417,13038]; % pIP10 (L, R)
pMP2 = [11977,11987];
dPR1 = [10267,10300]; % dPR1
TN1A1 = [15521,16465,15148,12883,16207,...
16113,14581,14810,15387,17640];
TN1A2 = [13945,14401,13928,16391,160... |
86992b8d75c39e805c4e8c53b7d087c67df98474bfa59b4d7dda12c2b930ee9d | MATLAB | 8,089 | 251 | function [trackParams, frameData, plotData] = detectPupilCR2_APP( app, side, img, crxPrevious, cryPrevious, radiiPrevious, trackParams)
%% Preallocate
plotData.epx = nan;
plotData.epx2 = nan;
plotData.epy = nan;
plotData.epy2 = nan;
plotData.points = nan;
frameData.crx = [nan; nan];
frameData.cry = [nan; nan];
frameD... |
36bd66f8bba9d40864d4ab0a902df61a7e1d8454c221b932131fc50ef0a41c0a | MATLAB | 8,090 | 212 | function response=analyze_neuronal_response(wsig,rast,param_struct)
% ANALYZE_NEURONAL_RESPONSE
% written by Avner Wallach
%
% INPUT VARS:
% wsig- vector containting whisking potraction angle values.
% rast- vector of indices in wsig where a spike was detected.
% param_strcut- structure o... |
d3c354acc5af226fc12ae1dc4583ed9a7564d15a44737abb519d4798624d689f | MATLAB | 8,101 | 272 | function mri = MRIread(fstring,headeronly)
% mri = MRIread(fstring,headeronly)
%
% Reads in a volume based on the fstring. fstring can be:
% 1. A stem, in which case the format and full file name is determined
% by finding a file on disk called fstring.ext, where ext can be
% either mgh, mgz, img, bhdr, nii, o... |
e7043b433ba822e73ec1dc176c1b459c5ff4a776d63dea3f1ccb41084d4f7463 | MATLAB | 8,105 | 241 | % Calculates a smoothed version of the median.
%
% -- Function File: M = smoothmedian (X)
% -- Function File: M = smoothmedian (X, DIM)
% -- Function File: M = smoothmedian (X, DIM, TOL)
%
% If X is a vector, find the univariate smoothed median (M) of X. If X is a
% matrix, compute the univariate smoothed media... |
081716c7aab4ca50fcfca969df6cfc896bab0e2c9fe8d9ae441acfed18e0cc04 | MATLAB | 8,111 | 219 | function [r,t,pval,hboot,CI,pboot] = Pearson(X,Y,fig_flag,level)
% compute the Pearson correlation along with the bootstrap CI
%
% FORMAT: [r,t,p] = Pearson(X,Y)
% [r,t,p] = Pearson(X,Y,fig_flag,level)
% [r,t,p,hboot,CI] = Pearson(X,Y,fig_flag,level)
%
% INPUTS: X and Y are 2 vectors or matrices, i... |
a0b53a5fdc41b5e19833b16242d44b13f2aa87e1311a00fa51eb99bee891e593 | MATLAB | 8,112 | 187 | %% Neurodata Without Borders (NWB) advanced write using DataPipe
% How to utilize HDF5 compression using dataPipe
%
% authors: Ivan Smalianchuk and Ben Dichter
% contact: smalianchuk.ivan@gmail.com, ben.dichter@catalystneuro.com
% last edited: Jan 04, 2021
%%
% Neurophysiology data can be quite large, often in the 1... |
c1c22523183cbdd4cd1db91a0fc920ff901856d3839e2dbe3fb3ef94df4ab6c5 | MATLAB | 8,113 | 138 | function success = stimulus_realign(folder_name)
% tracks and saves individual worms for all the images in a directory
addpath(genpath(pwd))
parameters = load_parameters(folder_name); %load experiment parameters
relevant_fields = {'Path', 'Frames', 'Centerlines'};
%% STEP 1: initialize %%
Image... |
3b9c9d1aa1b094be5589b2626a9bed650bf717803c9de1f1c5b215a9aa83f541 | MATLAB | 8,115 | 232 | function R = VORstim(data, tstart, tstop, freq, labels, timepts,velthresh, pulseDur, ploton,mask)
% VORstepfit.m
% Input:
% data - dat structure with channels
% 'htvel'
% 'hhvel'
% 'hepos'
% 'vepos'
% 'stim pul'
% tstart - time window start times
% tstop - time wndow stop times
% sinefreq - freq... |
036f097b7cea2c2ed77f61c7cf63e6c27c33d170996e88bd2d19f8669901c008 | MATLAB | 8,120 | 343 | %% Figure 5: Low Rank SC
scale = 200;
% disp(scale);
filename = sprintf('MICA_schaefer%d_SCFC_struct.mat',scale);
load(filename);
n_subjects = length(MICA);
nroi = scale+14;
SC_all = zeros(nroi, nroi, n_subjects);
GraphMetrics = struct('Full',[],'Int',[],'Deg',[],'Seg',[]);
for sub = 1:n_subjects
... |
3631f1fdd77782746b78003c05ce5eac8aa5e5c468dcf7bb2e8adbacc2970b45 | MATLAB | 8,121 | 216 | function read_nifti_combine(nifti_dirs, cleanup, parrecflag, dcm_name)
% function read_nifti_combine(nifti_dirs, cleanup, parrecflag, dcm_name)
%
% combine multi-echo GRE data (NIFTI from dcm2niix) and read Params from json file and save to header.mat
%
% nifti_dirs: folders with nifti output from dcm2niix
% cleanup... |
9dd86774b5f9c5323d9164ca9dc11a68e8d0a503f7b71a6254f782b3d2309c13 | MATLAB | 8,132 | 199 | % This script accurately computes and displays electric fields sampled on
% a cross-section (sagittal plane) via the FMM method with accurate neighbor integration
%
% Copyright SNM/WAW 2017-2020
bem4_define_planes_zoom;
bem5_figure_scales_zoom; %_alternative;
%% Load/prepare data
planeABCD = [1 0 0 X]; ... |
7cb3df55a66cda8b2e235122b328dd581f7d81772a7370aaa4584f680dbef931 | MATLAB | 8,135 | 159 | function out = dfa_muarate_NF(index, excludeperiods, marks, tetinfo, rippleskons, trials, varargin)
% define defaults
appendindex = 1;
ripthresh = 2; % exclude events based on size (thresh of 2 includes all)
excltrigger = 0; % if 1, exclude trigger events & provide log of excluded events
excludeRWstart = 0;
% proce... |
c59f32a850107fc45f59706cfc18981d98f83ef9f26a53d1e4f0100549733c4f | MATLAB | 8,144 | 231 | function [n, fn] = dimlength(data, seldim, fld)
% DIMLENGTH(DATA, SELDIM, FLD) is a helper function to obtain n, the number
% of elements along dimension seldim from the appropriate field from the
% input data containing functional data.
%
% Use als
% [n, fn] = dimlength(data, seldim, fld)
%
% It can be called with ... |
fa4857040df87fcd1358f785b01c0973c04d26e53d4f8b7a4ad58fac8a8d9ab9 | MATLAB | 8,147 | 184 | clear;
addpath(genpath('../ANE'))
%%
dir_video='E:\1photon-small\added_refined_masks\';
list_Exp_ID = { 'c25_59_228','c27_12_326','c28_83_210',...
'c25_163_267','c27_114_176','c28_161_149',...
'c25_123_348','c27_122_121','c28_163_244'};
% list_Exp_ID = list_Exp_ID(1:5);
method = 'EXTRAC... |
3d4ff8b17af704212d796080c8abb9b3cda07727496098374a8cfb041f8d5b2d | MATLAB | 8,158 | 239 | %% LOAD
[ds_events]= utils.load_ds_events('standard');
%load('id_list.mat')
%% CLASSIFICATION
type='onsets';
param(1).type=type;param(1).stat='avg';param(1).extype='ratio';param(1).exthresh= 2;
starts=-99:1:50;
bin=10;
[output_sp]= event_classifier(starts,bin,param(1),ds_events,'SVM','noshuffle','nodecay');
[out... |
b3768eb93521ebeeaf806a641bf7686d0c55c1e04fad2992c9c95ecbb1c08183 | MATLAB | 8,162 | 234 | % Function File: filter1
%
% Usage: YF = filter1 (Y, t, HPF, LPF, method)
%
% OR: filter1 (filename, ending, HPF, LPF, method, '-file')
%
% This function combines high- and/or low-pass 1-D filtering at the
% set -3 dB cut-off frequencies, which are defined in the parameters
% HPF and ... |
3b3a259af4e067c0d5a1799c2ba214324cb9104558eb3d8157e6e4f8957ba0fa | MATLAB | 8,163 | 252 | function [] = B1_Freq_Domain_TFR_LF(sub,av_type)
%
% Freq domain analyses - TFRs - Low frequencies
% -Usage
% B4_Freq_Domain_TFR_LF(sub,av_type)
%
% where
% sub - Subject to analyse, string (e.g. 'S01')
% av_type - Averaging type, cue-locked (1) or discrimination
% target... |
46667e84c109da0a37a8ff6fd1996574d8f5eeb07082275b69594daca4c57d03 | MATLAB | 8,165 | 180 | function parameterContribution(fnBase,neuronsToFit)
%% Load the raw data
cut=strfind(fnBase,'_modelFit');
fn=[fnBase(1:cut-1) '.mat'];
rawData = load(fn);
nTrials = rawData.nTrials;
unitOfTime = 'ms';
binSize = 1000/rawData.sampleRate;
%% Convert data to parametric form
[rawDataParametric, parametrizationParams] = pa... |
931b06483ac0aa0d867c286dbc72bcc4f0d59bacfe6b5c160721a8e4d1823cfe | MATLAB | 8,166 | 177 | function mglVisualAngleCoordinates(physicalDistance,physicalSize);
% mglVisualAngleCoordinates(physicalDistance,physicalSize);
%
% copyright: (c) 2006 Justin Gardner, Jonas Larsson (GPL see mgl/COPYING)
% $Id$
% Sets view transformation to correspond to visual angles (in degrees)
% given size and distance of d... |
20f2db9c0937cd8a18e21e7c94902056d08a00ffb5cf90eca0ab0c86d49b15b4 | MATLAB | 8,188 | 254 | % cfsRead64c.m
% an example of reading a cfs file, from 64bit Matlab
% must be able to find CFS64c.dll*
% *equivalent to CED's 64 bit cfs32.dll
% jg Colebatch
% 11.10.14: made 64 bit compatible version
%
INT1=0;
WRD1=1;
INT2=2;
WRD2=3;
INT4=4;
RL4=5;
RL8=6;
LSTR=7;
EQUALSPACED=0;
MATRIX=1;
SUBSIDI... |
9a4dc27112ee29569918932ce8d2bf17fee64c6d165897fd6e2f53f7ef7a8f6d | MATLAB | 8,193 | 196 | % findFlyNotMovingMidlegsXY.m
%
% Function to find when the fly isn't moving, based on the criteria that
% the 2 midlegs are not moving in X and Y (velocity below threshold).
% Finds based on smoothed velocity below threshold and non-smoothed
% velocity also below (separate) threshold
% Returns indicies of not moving... |
b10860fafcd8b4783ad9ad70631d2269de7fd06c4fe1598afdc355162e882b90 | MATLAB | 8,200 | 320 | % Produce simulations of the coupled model
clc; clearvars
addpath("C:/Users/kn356/OneDrive - University of Exeter/Desktop/StandardMATLAB")
load('colour.mat')
load('rainbow_cmap.mat')
addpath("C:/Users/kn356/OneDrive - University of Exeter/Desktop/StandardMATLAB/KNDy_coupled")
load("par.mat")
opts = odeset('Re... |
fdb0bd5a61d5a16aa80dd22dbbedd7dfe179a3530ef4a9e459cdbde2d79175a5 | MATLAB | 8,201 | 202 | function [ LFPTrendLogs ] = extractTrendLogs( obj, data, parameters )
%Extract LFP and Event logs from Percept PC JSON files
%
% Trends: LFP power / power domain
% Sampling frequency = 2Hz
% Events: Frequency Domain
% Sampling frequency = 250Hz
%
% Syntax:
% [ LFPTrendLogs ] = EXTRACTTRENDLOGS( ob... |
704522bcb6b5905c04ac3d0b412b2691b8574d042a177ed714379b3c15c0d593 | MATLAB | 8,206 | 145 | %The code for the research presented in the paper titled "Enabling inverse design of plasmon-based nonlinear square resonators with deep neural networks."
% In this code, first and second-order derivatives of transmission spectrum versus wavelength will be calculated.
% In this code, local minima and maxima will be... |
c8c82212fe3a873af1ac53123cd3c2c4ee1e183261aa9ada17504505c387ed3c | MATLAB | 8,210 | 231 | function [hp, stats] = superviolin_Jordan(dat,emm,replicates, lineStyles, varargin)
% Basic implementation of Violin SuperPlots in MATLAB
% Please cite the original work (Kenny & Schoen 2021 Molecular Biology of
% the Cell) when using the code for your work. Thank you.
% by Ingmar Schoen, RCSI (c) 2021
% I would l... |
7a7be896f892cedd38f0609e069a197300331eea69316851a189426ae6ad4a2f | MATLAB | 8,211 | 254 | % cfsRead.m
% an example of reading a cfs file
% 01.02.09: jgc version 1
% similar to simpler.c
% must have cfs32.dll in system directory
% calls MATCFS32.dll
% 07.02.09: read specific value(s)
% 24.02.09: capitalise MATCFS32 for Matlab 7
% 27.02.09: more information on variable type
% 07.08.09: d... |
afdf560e4f63f219db1e7d672c00a97d2bbf5b31fffa55e603fc6327217fe2ee | MATLAB | 8,214 | 141 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% TITLE: Thermal isomerization of alfa-pinene
% REF: R.E. Fuguitt y J. E. Hawkins, 1947. Rate of thermal isomerization
% of ?-pinene in the liquid phase. J. A. C. S., 69:461
%
% NOTE!!!: [] indicates that the corresponding input may be ... |
a39e79128ab22daaae05dc9b5c71863eae8c38229edccb7a76a4e2bdc9d9b362 | MATLAB | 8,217 | 184 | %%
globals;
strPlt = ''; for ii=1:length(PLOT_TYPE), strPlt = [strPlt cell2mat(PLOT_TYPE(ii)) '-']; end; strPlt=strPlt(1:end-1);
strQs = ''; for ii=1:length(ShowUnitsQs), strQs = [strQs cell2mat(ShowUnitsQs(ii)) '-']; end; strQs=strQs(1:end-1);
strVars = ''; for ii=1:length(VarList), strVars = [strVars cell2mat(Var... |
78a49f81bff2c5800eb47366006b74ab2bc206934603bdc1feeaaa3af09afa40 | MATLAB | 8,232 | 209 | function [turns]=find_turns_v2(data, rot_tra, run, ID, varargin)
% FIND_TURNS_V2
% This function detects the 180 degree turns based on the pelvis
% position. The begin and end of the turn were then calculated as the
% timepoints where the pelvis orientation crossed a regression line
% with more than 5° (see also su... |
537074b3fcd9be88166e9c2d2b7b0fce2d9e34d65283f7adf5435e54d56af622 | MATLAB | 8,233 | 292 | function done=aedes_update(opt)
% AEDES_UPDATE - Aedes update tool
%
% Synopsis:
% done=aedes_update(opt)
%
% Description:
%
%
% Examples:
%
%
% See also:
% AEDES_CHECK_UPDATES, AEDES_REVISION, AEDES
% This function is a part of Aedes - A graphical tool for analyzing
% medical images
%
% Copyright (C) 200... |
6a6dee3d824c1cee4d80af8d88b8dcc4210d637875ba5b557bd5087b734679bb | MATLAB | 8,250 | 199 | % sortLegStepsByIInj.m
%
% Function that categorizes all leg steps by whether they're during a
% current injection bout (and by injection amplitude) or not.
% Labels every half step with category index number, and generates key for
% matching b/w category indices and conditions.
% Not during current injection has inp... |
24169737de7f8f1cf6197de148e79f6a1f9d28a7655de434a19909eb20eb0c9c | MATLAB | 8,256 | 168 | % Marc Normandin, Muzzio Lab, Psychological & Brain Sciences, University of Iowa, 2024
function [analysisResultsGroupAverages] = main_analysis_group_averages_compute(analysisSettings, analysisResults)
%%
% To be made populated
analysisResultsGroupAverages = [];
% Just pass it on since it is already... |
9c7c1214d1a7248fbfa919704284c1b898a68d3fe8c59c8eb557a0ec91db2ff8 | MATLAB | 8,264 | 317 | if ispc,
addpath ../Jdetect/perframe;
else
addpath /groups/branson/home/bransonk/behavioranalysis/code/Jdetect/Jdetect/perframe;
end
SetUpJAABAPath;
if ispc,
frootdir = 'FlyTrackerData';
crootdir = 'CtraxData';
jabfile = 'ChaseAR_new_v10p0.jab';
else
frootdir = '/groups/branson/home/bransonk/be... |
8268bdbca07255bb7c960e0b6935b9f7fa2f079f45b92713d49981e215c8ca0b | MATLAB | 8,267 | 254 | % Author: Zachary Chiang, Buenrostro Lab, Harvard University
% Processes a single field of view of in situ genome sequencing data
function[] = expt002_fov(exp,condition,fov,primers,ligations,img_dir)
%% Can manually set parameters here
%exp = "expt002";
%condition = "well2";
%fov = 3;
%primers = ["N","N","N","N","N-... |
eefbcddbe2285a172fb9630d06617f314f61078a75b86d3e7b1825719981e755 | MATLAB | 8,270 | 223 | function plotETA( obj, varargin )
% Plot Event Triggered average profile for the selected events
%
% Syntax:
% PLOTETA( obj, ax, n_timestamps, event_type, event_date );
%
% Input parameters:
% * obj - object containg data
% * ax (optional) - axis where you want to plot
% * n_timestamps (optional)
% * even... |
e0927c935e401a4937b5a13798ca88e40991190c976f62a9888cf0307fa3b5d2 | MATLAB | 8,271 | 197 | clear;
tbl_dir = pwd;
tbl_name = fullfile(tbl_dir,'S2_Data.xlsx');
[~, sheetNames] = xlsfinfo(tbl_name);
groupStr = {'Young','Old'};
condStr = {'Load 1','Load 2','Load 4','Load 4'};
% # The third position is included for cases where I use ss = 1:3 rather than ss = [1 2 4]
%% Fig.2A maintenance
T = readtable(tbl_name,'... |
e42104cf8e0ac2cf66a0efd47383bdd39267b20bd4ca5cbeedf1634c778c1f41 | MATLAB | 8,275 | 229 | function [rez, st3, fW, fWpc] = trackAndSort(rez, iorder)
% This is the extraction phase of the optimization.
% iorder is the order in which to traverse the batches
% Turn on sorting of spikes before subtracting and averaging in mpnu8
rez.ops.useStableMode = getOr(rez.ops, 'useStableMode', 1);
useStableMode = rez.ops... |
753baacdd9f271437d303c93d7c8bde1980ff1b477391f1494f03eafe9370553 | MATLAB | 8,282 | 213 | % MAIN_StatisticsReportMean.m
% by Michela Chiappalone (12 Aprile 2006)
% Probably it needs to be updated on the basis of the other scripts on
% burst detection, already changed
% modified by Luca Leonardo Bologna
% - in order to handle the 64 channels of MED64 Panasonic System
% changed - not able to manage the 64 c... |
84f4c2e45a2262381109becee3cbf0d18d81bc8cb60a6b49d2d7877db8dfc058 | MATLAB | 8,285 | 282 | function copy_data_to_workspace(DATA,ROI,AddInfo)
% COPY_DATA_TO_WORKSPACE - Copy (assign) DATA and ROI structures to workspace
% (this is an Aedes plugin)
%
% Synopsis:
%
% Description:
%
% Examples:
%
% See also:
%
% This function is a part of Aedes - A graphical tool for analyzing
% medical images
%
% Copyright... |
a8a8a4a07b44b955f3e29b2d6df5701bc2ce14aa6cc16b251d7b9575e90ade4f | MATLAB | 8,289 | 221 | function FigureFlick(UMDir,user,recompute, loadMATsToSave)
%%% Go through pairs to manually curate matches. Will save a .mat file
%%% with the label of the pairs (0: uncurated, 1: match, -1: non-match)
%
% Inputs:
% pathFiles: path to where the .fig files are (mandatory)
% user: user's name ... |
55b43f3400818800c6e4fccbf0f85f917f7897cba27f5b0f4204537485290640 | MATLAB | 8,305 | 187 | %% initialization
[v_it,v_kt] = deal(zeros(N,1)+v_rest); %membrane potentials
[R_yt,R_it,R_kt,sc_R] = deal(zeros(N,t_total/dt)); %rates (sc_R is spikes)
[s_yt,s_it,s_kt] = deal(zeros(N,1)); %activations
[g_Ey,g_Eyi,g_Ei,g_Ii,g_Ek] = deal(zeros(N,1)); %conductances
[t_ref_i,t_ref_k] = deal(zeros(N,t_total/dt + D));... |
7db569f559862cd30537f995546d900116496789afe7b296e7bbab9c423e5dd5 | MATLAB | 8,321 | 215 | % MAIN_StatisticsReportMean.m
% by Michela Chiappalone (12 Aprile 2006)
% Probably it needs to be updated on the basis of the other scripts on
% burst detection, already changed
% modified by Luca Leonardo Bologna
% - in order to handle the 64 channels of MED64 Panasonic System
% changed - not able to manage the 64 c... |
50b8e5bdcffad6111b250a9532f62773cdc1c32bbdca8656ce994e3d4b96498c | MATLAB | 8,324 | 244 | % GBM Code for Practical Identifiability
% Original Source: Marisa Eisenberg (marisae@umich.edu)
% This code uses: GBMFuncidentifiable.m, GBMCost.m, GBMMiniFisher.m, GBMProfLife.m
clear
%% Load Data
% Average treatment-free data from:
% Anderson, H.G., Takacs, G.P., Harris, D.C., Kuang, Y., Harriso... |
b8d814a0b3a57a8fc01e50cb972a71bd45806fc4860ce7173bc827d0e147db74 | MATLAB | 8,328 | 231 | close all
clear all
clc
tstart = tic;
% Don't change these
projectCfgFilename = fullfile(pwd, 'project_config.json');
pipeCfgFilename = fullfile(pwd, 'pipeline_config.json');
% Load the project configuration
projectConfig = mulana_json_read( projectCfgFilename );
disp(projectConfig)
% Search for mice
[featurePoor, ... |
31f6f763e0323a950dd6593e9ba4b81333a723f0b98dce77a3cf9eb6c50fb257 | MATLAB | 8,330 | 316 | function parameters = setRunParameters(parameters)
%setRunParameters sets all parameters for the algorithms used here.
% Any parameters not explicitly set will revert to their listed
% default values.
%
%
% (C) Gordon J. Berman, 2014
% Princeton University
if nargin < 1
parameters = [];
... |
658dc01427b64375dd8c97e68da7c9e166a6bb9bd09c0c86180366c8bde923b0 | MATLAB | 8,336 | 229 | %function [cleanDataLFP] = GetLFP_Realignment_Params(PtID,TTLchan,nFFT,fs_scale,smoothBetweenBlocks,lowPassFreq,doCMR);
% Realignment and zaplined LFP from Neuropixels data.
% written by R. Hardstone & W. Munoz. rhardstone@gmail.com
% Version 1.0. This version used for figures in Windolf et. al (Nature Methods, 2024)... |
fe041df5d93aeba4f54069c713820969a19cc59afa2c3065522bc0b712047125 | MATLAB | 8,340 | 223 | function hdr = read_yokogawa_header(filename)
% READ_YOKOGAWA_HEADER reads the header information from continuous,
% epoched or averaged MEG data that has been generated by the Yokogawa
% MEG system and software and allows that data to be used in combination
% with FieldTrip.
%
% Use as
% [hdr] = read_yokogawa_heade... |
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