sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
80bbfcf7474ef4de67ce18dfad808fdc5a063d23c96d7ddf1679894de9cd170e | MATLAB | 6,229 | 155 | %% Create intepolated MIC patterns and plot raw points (Figures 3A, S3)
repo_path = 'Path_to\Manuscript_repository';
addpath('Path_to\wjn_toolbox_tsbinns');
addpath(genpath('Path_to\spm12'));
addpath(genpath('Path_to\leaddbs'));
folderpath_analysis = 'Path_to\Project\Analysis\Results\BIDS_01_Berlin_Neurophys\sub-mult... |
1cd60ec878386750ac97e4c84a14ab9875f97256cbdaa2f53279da28c84c5ef0 | MATLAB | 6,230 | 155 | %% Create interpolated MIC patterns and plot raw points (Figures 3A, S3)
repo_path = 'Path_to\Manuscript_repository';
addpath('Path_to\wjn_toolbox_tsbinns');
addpath(genpath('Path_to\spm12'));
addpath(genpath('Path_to\leaddbs'));
folderpath_analysis = 'Path_to\Project\Analysis\Results\BIDS_01_Berlin_Neurophys\sub-mul... |
044be4776b6ca81a0fc580f39407c0b868c806938a2414878dffe20278e6b406 | MATLAB | 6,233 | 176 | function ret = aqua_extract( inputPath, options )
% AQUA_EXTRACT Extract AQuA events from a res file; called by AQUA_EXPORT
% ret = AQUA_EXTRACT(inputPath) loads the res-file at `inputPath` and
% puts all of the data for export into the structure `ret`
%
% TODO This doesn't handle the no-uncaging case wi... |
a715bb9ee5ff29eca86485f284e66331d800c0b08efbe7714789d20ad8f9dca2 | MATLAB | 6,260 | 212 | function [s,mxy,M] = isochromat_GRE(theta,phi,TR,T1,T2,Niso,varargin)
% [F0,Fn,Zn,F] = isochromat_GRE(theta,phi,TR,T1,T2,Niso,varargin)
%
% Single pool ISOCHROMAT simulation for gradient echo sequences
%
% arguments:
% theta: vector of flip angles (rad) - length = #pulses
% ... |
cae8fe826f024d15701354143a61a188dfc109e53b902266803f261bba06c478 | MATLAB | 6,268 | 159 | function [scratchpad] = train_adaboost(trainpats,traintargs,in_args,cv_args)
% [scratchpad] =
% TRAIN_ADABOOST(TRAINPATS,TRAINTARGS,IN_ARGS,CV_ARGS);
%
% AdaBoost.MH/AdaBoost.MO classifier. Equivalent to BoosTexter for
% continuous numeric data.
%
% NOTE: rest conditions (sum(traintargs,1) == 0) are exluded from trai... |
49d7c80796bc0ba65a00921bf0e7613735c7f45cffb962e42422720eb0325b32 | MATLAB | 6,269 | 271 | function Duszkiewicz2024_Figure_AnticipatoryFiring
% This script reporoduces panels from:
% Extended Data Figure 3
% Dependencies:
% TStoolbox
%TODO: script dependencies, links to external functions
% Copyright (C) 2023 by Adrian Duszkiewicz and Adrien Peyrache
%
% This program is free software; you can redistribu... |
b8b5af50cce37e6a0cc488129f5010097a1ec7173e957254d35388c6f4029715 | MATLAB | 6,269 | 194 | function [errs warns] = unit_afni(errs, warns)
% [ERRS WARNS] = UNIT_AFNI()
%
% This is a unit test for the SPM ANALYZE import/export
% functions, LOAD_ANALYZE_MASK.M, LOAD_ANALYZE_PATTERN and
% WRITE_TO_ANALYZE.M.
%
% It requires several data files to function properly, which
% it loads and writes out in var... |
9c013dd83895f817933a153a4e31cbc74d0d52df8b83df981826ede6c8eddec7 | MATLAB | 6,276 | 283 | function Duszkiewicz2024_Figure_SingleRec_CueRotation
% This script reporoduces panels from:
% Extended Data Figure 2
% Run in folder A3707-200318 to reproduce manuscript figure
% Dependencies:
% TStoolbox
%TODO: script dependencies, links to external functions
% Copyright (C) 2023 by Adrian Duszkiewicz and Adrien... |
38b237b3ebaab4cf3343f6a8be21c232996515146af01b8d68ee56c8dcf1f72b | MATLAB | 6,281 | 190 | function [scratch] = train_svm(trainpats,traintargs,in_args,cv_args)
% USAGE :
% [SCRATCH] = TRAIN_SVM(TRAINPATS,TRAINTARGS,IN_ARGS,CV_ARGS)
%
% N.B. Please read Ryan Moore's instructions in
% mvpa/core/learn/MVPA_SVM_setup.rtf for info on setting up
% SVMs in the toolbox.
%
% This is a support vector machine training... |
e68958eb63e86f823f98a04c4a354eb230eab66fb0221de564df67b7c32f8ab9 | MATLAB | 6,282 | 179 | function [figOut] = plot_PAC_neuron(spike_times,datMat,srate,low_fb,HF_steps,tcutEdge)
%% plot_PAC_neuron(spike_times,datMat,srate,low_fb,HF_steps,tcutEdge)
% Plots the data table used to compute the GLMs for PAC neuron selection
%
% Input:
% spike_times: matrix containing the spike times from a given neuron (samples... |
fcacb1d3a1bec06cd5185efb01f939adcced2c07c5c1c51e6ccdb946d46b0286 | MATLAB | 6,284 | 205 | function registration_example2d(varargin)
% REGISTRATION_EXAMPLE2D 2D example for image registration
%
% registration_example2d()
%
% See also REGISTRATION_EXECUTE
% Copyright (c) 2012 Daniel Forsberg
% danne.forsberg@outlook.com
%
% This program is free software: you can redistribute it and/or modify
% it under the t... |
c38fa84395dcea400bfd55191f180bcc9f568710fff95870244fa21588e8f931 | MATLAB | 6,289 | 157 | % [tInc,tIncCh] = hmrR_MotionArtifactByChannel(data, probe, mlActMan, mlActAuto, tIncMan, tMotion, tMask, STDEVthresh, AMPthresh)
%
% UI NAME:
% Motion_Artifacts_By_Channel
%
%
% Identifies motion artifacts in an input data matrix d. If any active
% data channel exhibits a signal change greater than std_thresh or
%... |
140789e37afc155ef3b31253af5103b83d4d1021ff2d629b5961dd04f08a5d76 | MATLAB | 6,290 | 211 | %DEMMDN1 Demonstrate fitting a multi-valued function using a Mixture Density Network.
%
% Description
% The problem consists of one input variable X and one target variable
% T with data generated by sampling T at equal intervals and then
% generating target data by computing T + 0.3*SIN(2*PI*T) and adding
% Gaussian n... |
3c72213b369baca1835679d76b48aab663720c991f94964253884ff44049a0d6 | MATLAB | 6,291 | 155 | function res = bpass(image_array,lnoise,lobject,threshold)
%
% NAME:
% bpass
% PURPOSE:
% Implements a real-space bandpass filter that suppresses
% pixel noise and long-wavelength image variations while
% retaining information of a characteristic size.
%
% CAT... |
e12f8cf77a522e07155304863e61c61080549ebb1931ed2a6fa9608b2101864c | MATLAB | 6,293 | 183 |
% Data location
data_location = TFR_Clustered_Data;
save_data_location = TFR_Clustered_Data;
% Condition name
Condition_Name = cond_labels;
% Channel list
Channels = cluster_labels;
%% PT vs. Color
%
figure; clf
idx_subplot = [3,11,15,7,9];
for chan=1:length(Channels)
% Average PT vs.... |
c9de0808ead7bc34a68bf32779914cb29cf0efeeee5e8fa5551e001f879496c0 | MATLAB | 6,297 | 210 | %%
%% Exp1 vs Exp2 non-linear vs. linear mixing 1) construct the choice matrix
clear all;
clc;
mdir=pwd;
cd('../Data')
load MainChoiceData.mat
load TrainingBlock_IX.mat
load ExcludedSubjects.mat
cd(mdir);
Exps=[1 2];
OriColorMat=(1:36);
JNDs=[.6 .7 .8];
OriClrResmat=[0 0;1 0;0 1;1 1];
OriColorMa... |
fab56ca79aa945f4bb10ed307cf5bef915db57ed6ac6e045a98c57149b9797c8 | MATLAB | 6,298 | 159 | function [H, pValue, CM_limiting_stat] = cmtest2(x1 , x2 , alpha)
%CMTEST2 Two-sample Cramer-von Mises goodness-of-fit hypothesis test.
% H = CMTEST2(X1,X2,ALPHA,TAIL) performs a Cramer-von Mises (K-S) test
% to determine if independent random samples, X1 and X2, are drawn from
% the same underlying continuous po... |
8b031f70cd58341f437e83c2d8b8dc99cce267917abc0b2b7295980e28fc4ce2 | MATLAB | 6,307 | 154 | %**************************************************************************
%
% This is a simple extension of the bar plot to include error bars. It
% is called in exactly the same way as bar but with an extra input
% parameter "errors" passed first.
%
% Parameters:
% errors - the errors to be plotted (extra... |
a1dfad7779ad75fb44ecbe2fabea4f93d86926e880c8630c4165c3288e1aaba6 | MATLAB | 6,314 | 154 | % Tutorial script for predicting the EBC data - "Advanced" Version
%
% This tutorial will guide you in a step-by-step fashion through all
% of the analysis necessary to recreate one of the Princeton EBC
% Team's submissions to the competition. Unlike the first tutorial,
% we will analyze all thirteen primary regressor... |
47f00ce64db3d47ea0ee1790886f9434cd223b267562632a78e2e5130e275542 | MATLAB | 6,319 | 224 | function [efield,slice,smear,Q,T] = FieldSynthesisTheorem(efield)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Small program to illustrate a new Field Synthesis Theorem.
%
% In essence it says that the projection of the absolute modulus of a
% complex field is the same as when one... |
ca90d5d7bddb546022ce8f9e130c9f73e59d249cd5c81e59375c567205de4f05 | MATLAB | 6,320 | 187 | % STATUS: analysis. For internal report.
%
% SYNTAX:
% [snr,snr_Mean,snr_Std,cardiacSize,cardiac_Mean,cardiac_Std] = ...
% calc_AvgSNR_Welch(sbjNum)
%
% DESCRIPTION:
% calculate different estimates of SNR and some other stats related to
% noise analysis.
%
% RESTRICTION:
% Only for sbj 12 and afterward.
%
% INP... |
72336c121e07e539dc4ac52f96fe467f54a8af6118858e2a05083f611ad61689 | MATLAB | 6,321 | 192 | % Classifier unit test
%
% Classifier: libsvm
% Note: the classifier itself is not being tested since it's external but
% rather the MVPA-Light interface.
rng(42) %% do not change - might affect the results
tol = 10e-10;
mf = mfilename;
%% first check whether LIBSVM is available
check = which('svmtrain','-all');... |
62b482c1c76fec174789ddbc3c905d72320bb768b52ed418537ead462aede18d | MATLAB | 6,322 | 207 | function [subj] = zscore_runs(subj,patname,selname,varargin)
% Zscore each voxel, separately for each run
%
% [SUBJ] = ZSCORE_RUNS(SUBJ,PATNAME,SELNAME,...)
%
% For each voxel in each run, subtract the mean activity and scale
% so that the variance is 1.
%
% Adds the following objects:
% - pattern object
%
% This func... |
ed7f4d825463aa58b142df95316d72732d0d8e85378f466a1d95d4045faae5c6 | MATLAB | 6,322 | 109 | function Dataset = generate_dataset(animal_folder_listing,analysis_folder,geno_names,rec_type,events_names)
Dataset.info.geno_names = geno_names;
Dataset.info.rec_types = rec_type;
Dataset.info.mice_list = cell(length(rec_type),length(geno_names));
Dataset.whole_dff.data = cell(length(rec_type),length(geno_names));
Da... |
1a06b58206288ac3f859fdf601a3508d7841092d9b52165573d7669c150fbbc8 | MATLAB | 6,329 | 179 | function [subj] = feature_select(subj,data_patin,regsname,selsgroup,varargin)
% No-peeking feature selection
%
% [SUBJ] = FEATURE_SELECT(SUBJ,DATA_PATIN,REGSNAME,SELSGROUP,...)
%
% Calls a statmap generation function multiple times, using
% a different selector each time. This creates a group of
% statmaps, which are ... |
735ea7f358c27dde3ee5cab585e344b3f1486863aa5a2b895b0f8ff6e87da5b6 | MATLAB | 6,343 | 153 | function [taskStruct, dispStruct] = initTask()
% some initial global setup
RandStream.setGlobalStream(RandStream('mt19937ar','Seed','shuffle'));
KbName('UnifyKeyNames');
RestrictKeysForKbCheck( [] );
% Screen('Preference', 'SkipSyncTests', 1);
% general task info
taskStruct = struct();
... |
83406ce046083e84a71220a7a12ef6b29f4dccc6a0f9ff830eae1e373b4e2f2a | MATLAB | 6,343 | 159 | function [fs_index,n_vox_steps,output] = feature_selection_filter(cfg,fs_data,labels,data_scaled,n_vox,i_step,i_train)
output = []; % init
% create field if non-existent
if ~isfield(fs_data,'external'), fs_data.external = []; end
% Rank features for feature selection
[ranks,ind] = rank_features(cfg,fs_data.e... |
b641bc1cc5fc26362a2dfea50dadc2e82af88abc8867bab3fb48f0bea24d6598 | MATLAB | 6,349 | 194 | function guess=find_bpn2_7(sv_var,coords,C,guessed,combinations,final_time)
top_num = 20;
num_neu = 3;
selection = zeros(1,numel(guessed).*top_num + 1);
for i = guessed
[~, corrRanking] = sort(C(i,:),'descend');
selection = [selection, corrRanking(1:top_num)];
end
selection = unique(selection);
sel... |
650f55bfaabe904dfdba72c70b61996a5d84c4e2301db2914168d61adc5115e2 | MATLAB | 6,353 | 184 | %LoadBinary - Load data from a binary file.
%
% USAGE
%
% data = LoadBinary(filename,<options>)
%
% filename file to read
% <options> optional list of property-value pairs (see table below)
%
% =========================================================================
% Properties Values
%... |
b604485d2c8102d43c3349104ad4dd63a005b84d3c3fecb1b73a52b9cc10139f | MATLAB | 6,354 | 233 | function [F0,Fn,Zn,F] = EPG_TSE(theta,ESP,T1,T2,varargin)
% Single pool EPG (classic version) for TSE sequences
% [F0,Fn,Zn,F] = EPG_TSE(theta,ESP,T1,T2,varargin)
%
% arguments:
% theta: vector of flip angles (rad) including excitation
% ESP: Echo spacing, ms
% ... |
047b508d92bd501207e5482db84cd24af3a6e309a346d4df621a4c4466bda4b5 | MATLAB | 6,360 | 178 | clear; close all; clc;
%%
position = -40:4:40;
radius = 40; % in um
pixel2um = 2;
nonlineartype = 1; % std
[X, Y] = meshgrid(position, position);
gridposi = [X(:), Y(:)]/pixel2um;
ngridposi = size(gridposi, 1);
Act = @(MaxAmp, Alpha, Tau_r, Tau_f, t) MaxAmp * Alpha * (exp(- t/Tau_f) - exp(- t/Tau_r)) /(Tau... |
f64eb36041e56e1bd8cf01af94153db529812cf8561d31a690f6aadb6c70ff1e | MATLAB | 6,360 | 229 | function [errmsgs warnmsgs] = test_zscore_mvpa()
% USAGE : [ERRMSGS WARNMSGS] = TEST_ZSCORE_MVPA()
% Tests ZSCORE_MVPA against the Stats toolbox zscore
%
% OUTPUT ARGUMENT: ERRMSGS
% The output argument, 'errmsgs' holds the error strings that the
% function gives out if it fails any of the tests.
%
% WARNMSGS = cell ... |
f3fdee8c9e075451550e8fc189f7bf0c69d47113219bd147c606d84761b6d757 | MATLAB | 6,366 | 161 | % This script reslices an OCT volume for a specific iteration, assumes the
% following was already run:
% 1) 01 OCT Preprocess - pre-process volume (optional, this script can
% reprocess)
% 2) 11 Align OCT to Flourecence Imaging - alignment was calculated
appendToDimensions.note = [...
'Y directio... |
77c70ec67653dccf2bf08b8c9b9a2fcea6df8d3b242e9c4144ba5a3f925fb160 | MATLAB | 6,372 | 175 | function [LFP_PAC_figs] = NWB_samplePAC_LFP(nwbAll, paths)
%% NWB_SAMPLEPAC_LFP Calculates phase-amplitude coupling metrics for a sample electrode (Fig 2d, Daume et al)
% in:
% - nwbAll: a cell array of all nwb files imported in NWB_SBCAT_import_main
% operation:
% - paths: Paths defined in NWB_SBCAT_import_main. The ... |
0f736b314bdd02716e2a5ed905840886f2925aade5de14be9561b43f47c39626 | MATLAB | 6,381 | 149 | function [coh, C, Cc, Corig, Corig1, c, c0, hl] = reconstruct_coh_new(freq, freqnoise, leadfield, opts)
if nargin<4
opts = [];
end
N = ft_getopt(opts, 'N', 100); % number of sensors in the subsample
nrand = ft_getopt(opts, 'nrand', 0);
refindx = ft_getopt(opts, 'refindx', []);
lambda = ft_getopt(opts... |
5c88ebe8d1e0e0dfa225a34015cffb51121718d0ed97a8fae44b4926d8eaa96a | MATLAB | 6,384 | 236 |
clear all;
close all;
%spm('defaults','eeg');
spmfile = 'D:\home\Data\DBS-MEG\Phantom\090715\SPMstim\spmeeg_uespmeeg_phantom090715_BrainampDBS_20150709_02.mat';
%spmfile = 'D:\home\Data\DBS-MEG\LN_C54\100316\SPMrest\LN_C54_on.mat';
%spmfile = 'D:\home\Data\DBS-MEG\SW\190207\SPMrest\SW_off.mat';
D = spm_eeg_load(spmfil... |
2d6b83066cae85f16a87a81ac89956d74798aa947bdf6c4eb2390e6d4b4f3eb0 | MATLAB | 6,392 | 194 | % This script analyzes images latent space
%% Inputs
datasetBaseDirectory = s3SubjectPath('','_MLModels');
baseMLFolder = [datasetBaseDirectory '2020-08-15 10x Yonatan Pix2Pix'];
% Path to the specific model results
modelName = 'pix2pix'; % 'pix2pix_2to1_ratio','pix2pix_256px256px'
testImagesPath = [baseMLFol... |
c47d97a60baa57e72875ba908223b6f043863fcd530f3a87f0bde25a7294ddd7 | MATLAB | 6,393 | 168 | function outputFolder=generatePatchesFromImages(alignedImagesFolder,outputFolder, patchSize_pix, aspectRatio)
% This function takes image pairs and generates patches
%% Inputs
% Folder with aligned images (input folder)
if ~exist('alignedImagesFolder','var') || isempty(alignedImagesFolder)
alignedImagesFolde... |
f2022ba4a4435db29e930c10ae0a3a41619a3f8fc8970907a7b9193075d2b4e4 | MATLAB | 6,394 | 200 | function Experiment = run_vwm(Experiment)
% Run Experiment
% Input: Struct 'Experiment' with fields 'Subject', 'Display', 'Stimulus', 'Timing', 'Keys'
% Output: Struct 'Experiment' with updated field 'Subject.Log'
nRuns = Experiment.Design.nRuns;
mainPath = Experiment.mainPath;
Mode = Experiment.Mode;
Subject = Exp... |
d779838f78796207e24c7a74dd7835a5a53a1c7e182e20669973ee955d7bfe48 | MATLAB | 6,399 | 203 | function [net, options] = rbftrain(net, options, x, t)
%RBFTRAIN Two stage training of RBF network.
%
% Description
% NET = RBFTRAIN(NET, OPTIONS, X, T) uses a two stage training
% algorithm to set the weights in the RBF model structure NET. Each row
% of X corresponds to one input vector and each row of T contains th... |
3fbec620882e92c7540badc3746c96f5e036aa380472a0f8fa5b67e65cb85957 | MATLAB | 6,406 | 134 | % function output = transres_accuracy_matrix(decoding_out, chancelevel, varargin)
%
% Get a matrix of the accuracies of all pairwise comparisons (i.e. chance =
% 50 %) from a multiclass classification. Libsvm doesn't provide this
% directly. The diagonal is not defined and set to NaN.
% IMPORTANT:
% This function is NO... |
4bf5c4bec596545b643c754d063386171bd6ba9dc015bd272e33884fdaa50194 | MATLAB | 6,412 | 206 | function [tform, isHistImageFlipped] = HistFM_xcorr(imFM, imPB, imHist)
%This uses normalized cross correlation to align the input
%the histology slices with input flourecence microscopy images
%
%It finds the correct rotation, translation, and horiztonal flip which
%maximizes the normalized cross correlation.
% ... |
294b88f24d7791ed78c89c93495e00cdc8df7a263c2050b2ad41237d5b64ead3 | MATLAB | 6,414 | 210 | %DEMGMM4 Demonstrate density modelling with a Gaussian mixture model.
%
% Description
% The problem consists of modelling data generated by a mixture of
% three Gaussians in 2 dimensions with a mixture model using full
% covariance matrices. The priors are 0.3, 0.5 and 0.2; the centres
% are (2, 3.5), (0, 0) and (0,2... |
aa037913c88e5fa0464728a32b36ca904f1ca851e0b4e165271e7b8213bb6198 | MATLAB | 6,417 | 227 | function [data, metadata, c] = yOCTFromTif (varargin)
% This function tiff file.
% USAGE:
% [data, metadata, clim] = yOCTFromTif (filepath [, parameters])
% INPUTS:
% filpath - filepath to load. Can be a .tif file or a tif stack folder.
% For each file in the tif stack, image dimensions are z-x.
% ... |
e82e29d150b9095a87ab088545329c6513565ba5b3ce0fc060a488738d3d6c5d | MATLAB | 6,420 | 197 | function [returnVar,msg] = RemoveNoiseFromSpk(fbasename,shankIx)
% USAGE:
% RemoveDCfromDat(fbasename,shankIx,chanIx)
% This function removes DC from dat files by computing the average of
% the first 1e6 samples (or less if file is smaller)
% INPUTS:
% fbasename: file base name
% shankIx: vectors o... |
1e0217a09e8d20c1967757af32ac133ae9b15fd8ce742479dbebfd38966ce5c9 | MATLAB | 6,422 | 156 | function Experiment = set_up_subject(Experiment)
% Set Up Subject
% Input: Struct 'Experiment' with fields 'mainPath'
% Output: Struct 'Experiment' with field 'Subject'
% 'Subject' contains fields:
% 'id' - subject ID <- from input prompt
% 'age' - age of subject <- from input prompt
% 'group' - ex... |
e97ae63bdbee2bcaac487b2b7345a95f5d84671db2ea4c1fbcbc8e60e916df0d | MATLAB | 6,422 | 182 | function hpol = polar(varargin)
%POLAR Polar coordinate plot.
% POLAR(THETA, RHO) makes a plot using polar coordinates of
% the angle THETA, in radians, versus the radius RHO.
% POLAR(THETA, RHO, S) uses the linestyle specified in string S.
% See PLOT for a description of legal linestyles.
... |
f336408a3459474664d1b993e049fe6eb064cf853d2b49855129831e71bdb83d | MATLAB | 6,459 | 116 | % Copyright (c) 2014, Trustees of Boston University All rights reserved.
% Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and t... |
806926f62ae45b0b5a84cea4af961c1c97699e765a0f44f4fa739e1d002d28c8 | MATLAB | 6,464 | 174 | %% Main Flow Tracking Analysis Script
% The goal of this analysis is to track actin dynamics in actin
% fluorescence movies using Optical Flow and Crocker-Grier Least-Squares
% Minimization Particle Tracking.
function MainAnalysisScript(fileParameters, mainAnalysisParams)
%% Start MainAnalysisScript
fprintf('\n- - -... |
78eff0edcb9d4f8726705240899b4372ed8c2a00ec5278f1d1b4b99160ac07fc | MATLAB | 6,473 | 166 | function X = simulate_erp_peak(n_sample, n_time_point, pos, width, amplitude, weight, shape, scale)
% Simulates ERP data.
%
% Usage: X = simulate_erp_peak(n_sample, n_time_point, pos, width, amplitude, weight, shape, scale)
%
% Parameters:
% n_sample [int] total number of samples (e.g. trials)
% n_time point ... |
ca907d11fcdc0cd86fe10d6a74a96559114a8917dd37f54d0c820636a8d6df92 | MATLAB | 6,480 | 199 | function [updateField, updateCertainty] = ...
morphon2d(moving, movingCertainty, fixed, fixedCertainty, ...
scale, varargin)
% MORPHON2D Estimates a displacement field between moving and fixed using the Morphon
%
% [updateField, updateCertainty] = morphon2d(...
% moving, movingCertainty, fixed, fixedCertain... |
a2dfd4363ba7b6b4ff4edf9849a44a8fb35e795c7d5806e379605c13c971fde8 | MATLAB | 6,484 | 166 |
% Data location
data_location = TFR_Data;
save_data_location = TFR_Clustered_Data;
% Find indices of the channels
count=1;
for i=1:length(midfrontal)
if isempty(find(strcmp({channel_location.labels}, midfrontal{i})))
warning(['Warning: no electrode: ' midfrontal{i}]);
else
mi... |
ffd1f979c71404121017b33b6628775737f96cb89deda34a3a962852d2b15d3a | MATLAB | 6,489 | 182 | function alignHistFM(slidePaths,histRawPaths,isDelayedUpload,tmpFolderSubjectFilePath, isRunAutomatic)
%This function alignes histology slices with flourecence microscopy images
%INPUTS:
% - slidePaths - cell array of s3 path of the slides
% - histRawPaths - cell array of where the histology raw data is located,
%... |
0a1a9d8d31f386627ebe383a1dd0e6a6566e55dbe0adb8a2ad4988237a124b53 | MATLAB | 6,492 | 218 | function [] = view_montage(subj,anat_type,anat_name,funct_type,funct_name,varargin)
% View your data in a montage of slices
%
% [] = VIEW_MONTAGE(SUBJ,ANAT_TYPE,ANAT_NAME,FUNCT_TYPE,FUNCT_NAME,...)
%
% Uses Keith Schneider's MR_MONTAGE to do the main
% displaying work.
%
% ANAT_NAME = the name of the pattern that you ... |
1a9624c903b8be5057c4d92446c0bc0536e1f2688310e67a3ad0b09f0d64c018 | MATLAB | 6,492 | 116 |
% Hi there!
%
% This is the complete pipeline to recreate the analysis and plots in
% "Working memory and imagery in early visual cortex" by Weber,
% Christophel, Görgen, Soch and Haynes. To create the figures from the
% paper, just complete a few file paths below (look for '...') and then hit
% run (ignore the warnin... |
19764b87d749d7fd378af9cece45dc0689fd3eda734af6908c4bedb3ef51bba0 | MATLAB | 6,495 | 185 | function [OUT] = getBehavior_vp_eegCAT(IN,locking,trialnums,set_fb,pos,set_stim,pos_stim,rt_stim)
%aggregate variables
valueP1 = [IN.value1_p1 IN.value2_p1];
valueP2 = [IN.value1_p2 IN.value2_p2];
difficultyP1 = [IN.diff1_p1 IN.diff2_p1];
difficultyP2 = [IN.diff1_p2 IN.diff2_p2];
valueP1_old = [IN.value1_p1_old ... |
7dd6ebe92aaf053a5a4bb84959b9ce2a2a7f6bbc59418946a1187939a24309b1 | MATLAB | 6,505 | 191 | close all;
clc
% DATA = {NREMSoundallTrialsControl*100, NREMSoundallTrials*100};
DATA = {NREMSoundallTrials*100};
s2n = [];
incLatency = [];
Fs = round(1/(eventT(2)-eventT(1)));
for i = 1:length(DATA)
data = DATA{i};
w = size(data,1);
for j = 2:2:w
%initialize
s2n(... |
a171298634c48cc9131f3ad73b7dfd5803e884f44567b7176ffc2041b22d6a5c | MATLAB | 6,509 | 192 | function Experiment = set_up_stimuli(Experiment)
% Set Up Stimuli
% Input: Struct 'Experiment' with fields 'mainPath', 'Display', 'Subject'
% Output: Struct 'Experiment' with field 'Present'
% 'Present' contains one field per run 'R[run]'
% 'R[run]' contain fields:
% 'Rand' - randomization info (order ... |
2ae344664f2de5d5d836cb826c4e61810a4604a71488e89150913ee1ea1f7aa6 | MATLAB | 6,510 | 261 | function [errmsgs warnmsgs] = unit_adj_sphere2(varargin)
% Unit tests for ADJ_SPHERE2.M
%
% [ERRMSGS WARNMSGS] = UNIT_ADJ_SPHERE2(...)
%
% See UNIT_TEMPLATE.M and UNIT_ADJ_CUBE.M for more info
defaults.doplot = false;
args = propval(varargin,defaults);
errmsgs = {};
warnmsgs = {};
simple = ones(5,5,5);
s_radius = ... |
492ba64a7792ae0cb1d3fdf0253688c0cb9dce2226e5919d9cf4969cd5d8cbb1 | MATLAB | 6,512 | 147 | function [qScore,...
isOCTImageQualityGood, isHistologyImageQualityGood, alignmentQuality, ...
areaOfQualityData_mm2 ...
] = computeOverallSectionQuality (input1)
% This function computes an overall quality score for the section. Possible
% USAGE (2 options):
% [...] = computeOverallSectionQuality(s... |
40aa2df39e0aaf36c3f197341025f9f20cb369622ae4f48f44f3e0faa58cbe6a | MATLAB | 6,518 | 184 | function hpol = polar(varargin)
%POLAR Polar coordinate plot.
% POLAR(THETA, RHO) makes a plot using polar coordinates of
% the angle THETA, in radians, versus the radius RHO.
% POLAR(THETA, RHO, S) uses the linestyle specified in string S.
% See PLOT for a description of legal linestyles.
... |
046c66296d5995bb9e133074e4b867130265b913d9303ef69e509784a7105b8f | MATLAB | 6,519 | 218 | classdef acti < timeseries
%ACTI create actigraphy objects
%
% R = ACTI(DATA, 'Epoch', epochVal) returns an ACTI object
% containing the data in DATA. EPOCHVAL determines how many seconds
% one point stands for. Note that the EPOCH property is immutable.
% R = ACTI(..., 'StartTime'... |
c71a094460d0bea2f95204f4a18c9cf3bf1bd17d418ea63c5d492ded0b6cbd48 | MATLAB | 6,520 | 114 | % Extract single HRF from dcNew variable, the output of GLM fitting function
% save to mat file.
function createSingleTrialHRF_Updated(sbjNum,respData,numClasses)
%saveDir = ['C:\Users\mn0mn\Documents\ResearchProjects\spatailAttentionProject\ProcessedDatafNIRS\Experiment' num2str(sbjNum)];
processedDataDir = ['C:\Users... |
925565cb415aa82fe75729569a5f6972768a292af097b27ca946ca1da09f580f | MATLAB | 6,524 | 164 | function as = analysis_step2(params, as, step1, iFile)
info_table=params.info_table;
info_struct = params.info_struct;
info_fields = fieldnames(info_struct);
nFields = max(size(info_fields));
[r_res,~]=size(as.metadata);
if (iFile==1), i_res=0; else, i_res=r_res; end
t = step1.... |
110eb01bdea7ee8061ae5519d6916665ba9c9a91dac079e67e6f8b6e91f57b98 | MATLAB | 6,532 | 202 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Written by James N Ingram, 2023
clear all;
close all;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Current to Torque gain and offset calculated from: TeenScienceSingleAxisCalibration.m
CurrentTorqu... |
57fdf4cc073d13e0d30183cf874b95300c627ea75d49df24e92645b6a70a1c9a | MATLAB | 6,534 | 174 | function varargout = load_data(varargin)
% LOAD_DATA M-file for load_data.fig
% LOAD_DATA, by itself, creates a new LOAD_DATA or raises the existing
% singleton*.
%
% H = LOAD_DATA returns the handle to a new LOAD_DATA or the handle to
% the existing singleton*.
%
% LOAD_DATA('CALLBACK'... |
0a7fad69c8ebc8ed354135b4c5e95f13d09614e9177f076689160d3ac3ae3aa5 | MATLAB | 6,539 | 196 | clear all
load ('C:\noga\TD complex spike analysis\task_info');
tasks = {'saccade_8_dir_75and25','pursuit_8_dir_75and25'}
req_params.grade = 7;
req_params.ID = 4000:5000;
req_params.remove_question_marks = 1;
req_params.num_trials = 20;
cell_type1 = 'CRB|PC ss';
cell_type2 = 'CRB|PC ss';
pairs = [];
counter = 0;
for ... |
b38de0ac1187f8096b32add899b3a53f5a9e3b4514fc00df772ae9f7c40d38c1 | MATLAB | 6,550 | 173 | % function [out, regressor_names] = display_regressor_names(beta_loc, compress)
%
% This function gives you an overview over the possible regressor names
% that can be used as labels for a decoding analysis. This is helpful if
% you don't want to look inside the SPM.mat (e.g. with the SPM GUI) or do
% not have the... |
b7ac4315c30b1066eaccd8a4154ef1b875ef216becf860512a71bafd69e1bb09 | MATLAB | 6,550 | 139 |
function phantom_lcmv_job
MNI_roi = [40 -20 50]; % this is the simulated dipole of interest
D = spm_eeg_load('D:\home\Data\4AshO\Phantom Images\ROI_sim.mat');
%%
S = [];
S.D = D;
S.tsss = 0;
S.t_window = 5;
S.xspace = 0;
D2 = tsss_spm_enm(S);
%%
trans ... |
a1a82c7c07fd77edf5d7197069058a7477bfc8395b5ad5da97279aecafa020f4 | MATLAB | 6,559 | 110 | %Performs ERP analysis on spep preprocessed LFP.
%2024/02/25
function spep_ERPanalysis(fnames)
%define filenames and load data:
outputFolder=[fnames.preprocdata_folder '/LFP/spep_erp'];
disp('Loading trials timestamp data...')
load(fnames.trials_filename);
%run ERP analysis:
if ~exist... |
8cbce6686ee17992643f3b7f5d7fa494fd0d4cbccabc962f85f8854e4d6cce5b | MATLAB | 6,562 | 189 | function [comdlgrm, comdlgrm_z, phase2power] = cfc_tort_comodulogram(datMat,srate,n_surrogates,n_bins,LF_steps,LF_bw,HF_steps,tcutEdge)
%% [comdlgrm, comdlgrm_z] = cfc_tort_comodulogram(LFP,fs,n_surrogates,n_bins,LF_steps,LF_bw,HF_steps,tcutEdge)
%
% Compute PAC comodulogram with Tort's method (Tort et al, 2009, 2010)... |
a1168ffa5cd38054bd2a8fe836712a2a27df03437ab0e9c80698d3630396d53f | MATLAB | 6,578 | 181 | for q = 1:2
filename = sprintf('/Translation/Ai148_AAV-Grm6Cre_Translation_%s_%d%03d', Daystr, Cel, expids(q));
load([NatMovPath filename], 'I');
Mov = std(I, [], 3);
Mov = Mov/quantile(Mov(:), 0.99);
savename = sprintf('Ai148_AAV-Grm6Cre_CPRegistration_%s_%d%03d.mat', Daystr, Cel, expids(q));
... |
59c56128eff711bbf63b45ea024f7cb453aae306de5b68f7589878597aa64912 | MATLAB | 6,579 | 111 | % function [n_decodings,decoding_subindex] = get_n_decodings(cfg,mask_index,mask_index_each,sz)
%
% This is a subfunction of The Decoding Toolbox. It determines number of
% times a full classification is performed (e.g. number of searchlights or
% number of ROIs).
%
% Martin Hebart & Kai G?rgen, 2013
functio... |
ad2661dd7f5fffbe72d0d0d2afd746e8dc378becbbea192fd1844522682fca0e | MATLAB | 6,587 | 206 | % 1. Add the path of the current script to the search path
% 2. Change the current folder to "Supp Fig9 CFstimulation"
% 3. Using ctrl+enter within each function to run each section
%% Section 1: Open files
% 1. ctrl+enter to run this section
% 2. analyze the data within the folder of "Supp Fig9 CFstimulation... |
88bbc4215983759458bb9decc60aefb14aeb8b6818f7afc92dc499af2c117961 | MATLAB | 6,591 | 192 | %% Main Flow Tracking Analysis Script
% The goal of this analysis is to track actin dynamics in actin
% fluorescence movies using Optical Flow and Crocker-Grier Least-Squares
% Minimization Particle Tracking.
clear
% close all
clc
%% Define Global Parameters
% % % % % --------- File Parameters --------- % % % ... |
9905e7d4ec44d7600d7824019adc14607800c851e7164f16b28badab5acc729e | MATLAB | 6,598 | 158 | %CALCULATE THE EXPECTED SHAPE DISTORTION BASED ON SLANT PERCIEVED
%I am estimating the aspect ratio based on the reported slants
%that people percieved in the experiment. We take into account inferences
%from disparity and the retinal image shape.
%order the slants so that the shape estimation is ready to plot a... |
a5bec967556e2b05fc409837315ce169998e6f53dd928363381320b9429df722 | MATLAB | 6,599 | 176 | %% Main Flow Tracking Analysis Script
% The goal of this analysis is to track actin dynamics in actin
% fluorescence movies using Optical Flow and Crocker-Grier Least-Squares
% Minimization Particle Tracking.
function MainAnalysisScript_GuvenPaperModified(fileParameters, mainAnalysisParams)
%% Start MainAnalysisScri... |
abe7791b46df13c0fccedb22c280e4865574d08a558f54e9ebba4668c6d3c102 | MATLAB | 6,618 | 216 | %for plotting averages of all dff traces in a condition as well as
%standard error shading
%requires https://www.mathworks.com/matlabcentral/fileexchange/27485-boundedline-m
%Use after THexporttraces_xlsx.m and THGCaMP_ampsdffsingle.m
prompt='How many traces?';
blank=input(prompt); %decide how many data sets you want... |
77490ee344217859d34e9b5232c7dc4a1690853e80db0ae4eba036bb5dd7beb0 | MATLAB | 6,629 | 217 |
%%%%%% STARTING with just CB data!
participant_CB_3_mo_dir = '/Users/tawnytsang/Desktop/Projects/ETdataFiles/infantSibs/CB-SST Data/matlab/CB/3/';
participant_CB_6_mo_dir = '/Users/tawnytsang/Desktop/Projects/ETdataFiles/infantSibs/CB-SST Data/matlab/CB/6/';
participant_CB_9_mo_dir = '/Users/tawnytsang/Desktop/Project... |
923a3acefe0f75f8b77e167eabae2ee541c0edae728f05003c98ed037f1db454 | MATLAB | 6,635 | 207 | %%
addpath('\\storage1.ris.wustl.edu\kerschensteinerd\Active\Emily\BasicFunctions');
nIter = 5000;
%%
IsEncodingSpace = 1;
if IsEncodingSpace
cResp = Y(:, 1:3);
else
cResp = Resp;
end
TypeDiff_val = nan(nType, nType);
TypeDiff_p = nan(nType, nType);
rng('shuffle');
for i = 1:nType
for j = 1:... |
300f35acd3a64bcdcc193974a1bd60da93d0510bb5d31f553e49e05a0fca051f | MATLAB | 6,637 | 195 | % references: https://www.mathworks.com/matlabcentral/answers/180778-plotting-a-3d-gaussian-function-using-surf
% https://www.mathworks.com/help/symbolic/rotation-matrix-and-transformation-matrix.html
% https://www.mathworks.com/matlabcentral/answers/430093-rotation-about-a-point
% params
output_filename = "ext_dir_in... |
ba2e233f0935fae2806bf6e439315f7fc882901e7cb66044969cc0ad28b46cba | MATLAB | 6,640 | 106 | function [XSecBinsPrePost_PermMean,XSecBinsChangeAvgBaseline_PermMean] = MeanFt_XSecStatBins_PermEventOnsetByAreaBand(mydata, CONDITION, TSERIES,...
time_window, ExcludeBaseline, perm_num, param_name, WhichEvents, NBinsPre, NBinsPost,...
AB, lmk_idx, bin)
% MeanFt_XSecStatBins_PermEventOnsetByAreaBand modifi... |
8729ba6d91edf0e49863b4ec3a8828e8fb19702d6829a25e3e844f0cf794e7ad | MATLAB | 6,644 | 205 | classdef MetaDataTagsClass < FileLoadSaveClass
properties
tags
end
methods
% -------------------------------------------------------
function obj = MetaDataTagsClass(varargin)
% Set class properties not part of the SNIRF format
obj.SetFileFormat('h... |
63a8aa638d5ca9e97a544aa838cadf9ab1dd379e411e391d73ceaed604e2cc5c | MATLAB | 6,648 | 138 | % function [cfg,trans_results,data_train_trans,data_test_trans] = decoding_transform_features(cfg,data_train,data_test)
%
% This function transforms features of decoding data and is an integral
% part of the decoding toolbox. This function is called from decoding.m
% and should not be called directly. Feature tr... |
804ad2882b0153106626e8c784587a804607105ec2eb54faa14198a424ef3822 | MATLAB | 6,649 | 232 | clear; clc
[task_info,supPath] = loadDBAndSpecifyDataPaths('Vermis');
POPULATIONS = {'BG|SNR','BG|SNR';...
'BG|SNR','PC ss|CRB';...
'PC ss|CRB','PC ss|CRB'};
BIN_SIZE_FOR_NOISE = 100;
EPOCH = 'cue';
raster_params.time_before = 199;
raster_params.time_after = 800;
raster_params.smoothing_margins = 200;
raste... |
d7b5486f2d2f9f31872cc1f882f36b441dae09037652889c97095dd7ff21d630 | MATLAB | 6,654 | 230 | %% Figure 3A - VSD Response Timeline
% Size: 8x6
% load('M16D20160203_Orimask_OriMask.mat');
BLK = WideField.BLKPlus('Data/M16D20160127_Orimask_StabDown004.mat','Data/M16D20160127_Orimask_TS.mat');
BLANK = BLK.getDataTrial('TypeCond',0);
BLANK = BLANK - mean(BLANK,4);
BLANK = reshape(BLANK,size(BLANK,1),size(... |
f0b9b400c8d8e043cdfe9b5f743c60d3d6001aab9b831daf30a8bdd4ac78515a | MATLAB | 6,662 | 239 | % tCFS_E3_figure4_v2
% this version condenses the plots to include example trials:
% job=[];
% job.concatGFX= 1;
% job.plotPFX=0;
% job.plotGFX=0;
% plotType==1; % as per other MS figure
%% set up some directories.
% homedir = 'C:\Users\mdav0285\OneDrive - The University of Sydney (Staff)\Desktop\track... |
457dcb6822b76cca0b1c3744cd14668da5bd36cfaeaf34bb6f086c5cd6089624 | MATLAB | 6,667 | 216 | function PLS_bootstrap(GENEdata_root, MRIdata_root, ncomp, bootnum, working_dir)
% PLS regression and boostrapping
%% ------------------------- SCRIPT INFORMATION ---------------------------
%
% PLS Regression and bootstrapping
%
% This script will perform a PLS regression analysis for relative gene
% expression in 180... |
816ada8f67585ef24448de654b54dccef5340308f8bc5285a830fc47f9399818 | MATLAB | 6,667 | 234 | function rendersurface_aal90_gifti(aalvector, symm, rangemin, rangemax, inv, clmap, surfacetype)
% script to render aal90 on inflated brain
% ML Kringelbach April 2020
%
% Parameters:
%
% aalvector : 1x90 vector
%
% symm : 1 if ordering is symmetrical
% rangemin, rangemax : limits for colorscheme
%
% inv :
% 0 colo... |
9cb4f4086a8323fdfc8b89975c895fb271ce123ac74b72d1266d5a2b910230e2 | MATLAB | 6,674 | 170 | %% Read data from DRC analysis results
% and compile into a table "data"
% columns include: sp,np,err,PRF,CGF,wtf_reg_params, wtauphi_reg_params,
% strfpp, ctxtpp
function [data,pairTable] = DRC_load_data()
%
datapaths
% STRF parameters
K = 61; J = 8;
freq = logspace(log10(2),log10(64),K);
delay = 5.... |
36077c456f91f45d09825ce06b58c0993fb39217a2be8ac97eadd234bae8c90e | MATLAB | 6,677 | 202 | % Run after @GenerateExpectedGC6fResponseNoise
% Get the filename for the batch loop
clear; close all; clc;
ChopClipL = 60;
UpSamplingFz = 100;
Txcorr = [-95 -5];
radius = 40; %
Addnoise = 0.002;
IsDisplay = 0;
%% load comparison grids
Topic = 'Ai148_Grm6Cre';
Day = '110318';
Cell = 1;
Exp = 5;
NoisePath ... |
d1ac9d7bdb34f3575aaa63d643f863234347a85d7416ebf275b98a52d6161bae | MATLAB | 6,684 | 196 | clear,clc
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This code was written by Dr Petra Vértes and is taken from Whitaker and Vértes, PNAS 2016
% please cite that paper if you this code in your own work.
%
% Jin Liu modified to fit the data in this study
% 20... |
d3a7dd0b152034550626b95fe19315a325fe1a8b4539aeb78a09a0c06b47658a | MATLAB | 6,685 | 230 | function [F0,Fn,Zn,F] = EPG_GRE(theta,phi,TR,T1,T2,varargin)
% [F0,Fn,Zn,F] = EPG_GRE(theta,phi,TR,T1,T2,varargin)
%
% Single pool EPG (classic version) for gradient echo sequences
%
% arguments:
% theta: vector of flip angles (rad) - length = #pulses
% phi: phase pe... |
d8b80670f2e3ea55e570d771f106bf687f3ec55fe5129b38916ab59449694490 | MATLAB | 6,692 | 233 | clear; clc
[task_info,supPath] = loadDBAndSpecifyDataPaths('Vermis');
POPULATIONS = {'BG msn|SNR','BG msn|SNR';...
'BG msn|SNR','PC ss|CRB';...
'PC ss|CRB','PC ss|CRB'};
BIN_SIZE = 100;
SHIFT_CONTROL = 1;
INCLUDE_PREV_OUTCOME = true;
raster_params.time_before = 199;
raster_params.time_after = 800;
raster_para... |
5cb3ea226185e278e574fa0354d77ce88b6079b8c6d2eb5bfd84151b433da666 | MATLAB | 6,698 | 231 | function rendersurface_schaefer1000(schaefer1000vector,rangemin,rangemax, inv,clmap,surfacetype)
% script for rendering a schaefer1000vector
% ML Kringelbach April 2020
% schaefer1000vector : the schaefer1000vector values to be rendered
%
% rangemin, rangemax : limits for colorscheme
%
% inv:
% 0 colormap, interp
% ... |
d2a1a751b10000aa6d236beea830d87240a9c35f2bf376b0b34ef26d9f7d2092 | MATLAB | 6,698 | 171 | %% Bar Plot of d' and LR Bias (Pooled + JK errorbars)
%% Code
monkey = ["G","B"];
global Trials
Trials = ["All","RF"];
parameter = ["sens","LR","MB"];
sessions_list = {[4:15 18 20:24], [34:45]};
flag_scatter = 0;
for RF = 0:1
par_all = cell(1,2);
par_all_mi = cell(1,2);
par_jk = ... |
e6fe3a72fe6181eeb49affd6f66b8a35ce97700bb0a04f184f33a0b01bb78e49 | MATLAB | 6,699 | 265 | function [errmsgs warnmsgs] = unit_create_adj_list(varargin)
% This is a script that tests the adjacency list code.
%
% [ERRMSGS WARNMSGS] = UNIT_GET_ADJACENCY(...)
%
% INPUT ARGUMENTS:
%
% STDOUT (optional, default = true) If true, prints errors and
% warnings to screen as they occur.
%
% OUTPUT ARGUMENTS:
%
% ERRM... |
bcb8379cc278cdeac80756f0e4072fd36c88b254fbfec669d356adfd9757c228 | MATLAB | 6,707 | 166 | clear,clc
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% This code was written by Dr Petra Vértes and is taken from Whitaker and Vértes, PNAS 2016
% please cite that paper if you this code in your own work.
%
% Jin Liu modified to fit the data format in this stud... |
18b489aaf9032cb47af77213ad4152dfc303add6e362af61e564310670c6d46d | MATLAB | 6,710 | 188 | clear; close all; clc;
%%
position = -40:4:40;
radius = 40; % in um
pixel2um = 2;
nonlineartype = 1; % std
[X, Y] = meshgrid(position, position);
gridposi = [X(:), Y(:)]/pixel2um;
ngridposi = size(gridposi, 1);
Act = @(MaxAmp, Alpha, Tau_r, Tau_f, t) MaxAmp * Alpha * (exp(- t/Tau_f) - exp(- t/Tau_r)) /(Tau... |
eada55a5ca5c7a518fe8c75245837370185247ecd393c1d55f9ea28fde66cea2 | MATLAB | 6,712 | 225 | %% Test 4: Comparison of multislice and single slice TSE
% 2017-09-13
% version 2 - multiple slices as per in-vivo experiments
addpath(genpath('EPGX-src'))
addpath(genpath('lib'))
%%% Sequence
%%% Number of refocusing pulses
nrefocus = 25;
%%% have 8 different scenarios
nslice = 1:2:15;
nn = length(nsl... |
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