sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
800a4d733853749b9e377f2c232d0d84c3672b6510c73024d4ddb7ec19ac5935 | MATLAB | 5,746 | 150 | %% Figure 5c
clear
morph_path = '/oak/stanford/groups/kalanit/biac2/kgs/projects/babybrains/mri/code/morphology_allparameters/';
addpath(morph_path)
cd(morph_path)
set_participant_information
hemi = 'rh';
R1_data=[]; CU_data=[]; SD_data=[]; CT_data=[];
ALL_profiles_SD = []; ALL_profiles_CT = []; ALL_profiles_CU = [];... |
d77afe0150d30d4879e5c74ac84e89f64914b395c65f8e906d9296a43c175020 | MATLAB | 5,747 | 135 | %{
stack.StackMotion (imported) # motion correction
-> stack.StackInfo
-----
raw_motion_xy : longblob # (pixels) y,x motion correction offsets
motion_xy : longblob # (pixels) y,x motion correction offsets after detrending
%}
classdef StackMotion... |
b392a0d62c9154dae3f9e6deb4c47fc5097fe148e96451948f9f651aec2c9d96 | MATLAB | 5,751 | 119 | function plot_RNN_recurrent_synaptic_weights
close all
clear all
clc
% Plot RNN recurrent synaptic weights.
% Select a folder containing data.
folder_name = uigetdir;
cd(folder_name)
load('RNN_recurrent_synaptic_weights.mat');
% Get mean of absolute recurrent weight matrices for control RNNs.
control_weights_mean =... |
7b0887034de5d8e2ab053b09ddc728991765c282194385b11d1eeef09d5e7ab1 | MATLAB | 5,752 | 197 | %% Linlin Data
close all
clear all
filename = 'C:\Users\Harnettlab\OneDrive\Desktop\Voltage_Data\Sq_camera.bin';
nrow = 96;
ncol = 200;
mov = readBinMov(filename, nrow, ncol);
figure(100); imshow(imadjust(uint16(mean(mov(:, :, 1:100), 3))));
rois = load('C:\Users\Harnettlab\OneDrive\Desktop\Voltage_Data\ROI.mat');
ro... |
33b9d035849d3a8f9906fd99188d1d95fe8db2b465b1456010e7988e4205d709 | MATLAB | 5,755 | 152 | function colors = distinguishable_colors(n_colors,bg,func)
% DISTINGUISHABLE_COLORS: pick colors that are maximally perceptually distinct
%
% When plotting a set of lines, you may want to distinguish them by color.
% By default, Matlab chooses a small set of colors and cycles among them,
% and so if you have more than ... |
80d20078881a778c00fb1d33da7035804fe9690bab7709bd647d690ffb3809c0 | MATLAB | 5,755 | 144 | %% get_set_TotalField_ROMEO(h,mode,input)
%
% Input
% --------------
% h : structure contains all handles of SEPIA
% mode : 'set' - extract information from GUI to config file
% 'get' - extract information from config file to GUI
% input : if mode is 'set' then input should ... |
c943204175f867a71658d3a8ff08d334b4ecf2b24b860dca81aac9bcc71d257c | MATLAB | 5,757 | 145 | %% Parameter
% Distance threshold
distTh = 90 % nm
% Synapse filters
LowerThSynSigma_nm_ = 80;
UpperThSynSigma_nm_ = 800;
LowerThSynIntensity_photon_ = 200;
input_folder =uigetdir()
%% Analysis based on Thunderstorm output
mutant = [];
exp = [];
ratio75 = []
at180 =[]
syn = []
folder = input_fol... |
9b4d45c6b0a374433bb3b880cd40f04da57dc2371f29c7e5c1d4cc03e0835cdd | MATLAB | 5,759 | 158 | function plotPCA(a,b,c,d, chanlocs, i12, i16,i21, coeff,lambda, outputFolder)
toi = linspace(-1, 1,size(a{1},2));
a = cat(4, a{:});
b = cat(4, b{:});
c = cat(4, c{:});
A = [a;b;c];
corr = find(contains(d(1).alignements, 'FIC'));
incorr = find(contains(d(1).alignements, 'FIW'));
... |
a93774c835b0300055f126445d0ee4f88e8dcaecd5fd429fd244d0ce1cf86379 | MATLAB | 5,759 | 143 | %FIX_LINES Improves the line style of eps files generated by print
%
% Examples:
% fix_lines fname
% fix_lines fname fname2
% fstrm_out = fixlines(fstrm_in)
%
% This function improves the style of lines in eps files generated by
% MATLAB's print function, making them more similar to those seen on
% screen. Grid ... |
7f775e876d47152b59ddcd8fa7b9da29d0969eb0296f59e7741ac2c3344a83b0 | MATLAB | 5,761 | 202 | function ARTwarp_cli_builder()
% This file creates the CLI command based on the input parameters.
% --- Required inputs (enforced) ---
% Input folder
while true
% strtrim to ensure there are no leading or trailing spaces.
inputFolder = strtrim(input('Enter input folder name: ', 's'));
if ~isempty(inputFol... |
f7daf23f4d559e604d6922ba9a7904eaa1961b3c0bd24f5ee0da3ead3cc784d7 | MATLAB | 5,761 | 145 | % EEG_MATCHCHANS - find closest channels in a larger EEGLAB chanlocs structure
% to channels in a smaller chanlocs structure
% Usage:
% >> [selchans,distances,selocs] = eeg_matchchans(BIGlocs,smalllocs,'noplot');
% Inputs:
% BIGlocs - larger (or equal-sized) EEG.chanlocs structure ... |
610f098af9568e3969c44a0ae0f190fa28fabd94987d3c8bdd5e84b67e079759 | MATLAB | 5,764 | 179 | function biomk = extractBiomarkers2(window)
% Computes Ca-transient biomarkers
% minCa, maxCa, CaT_Duration (CTD10), CTD80,
% RT10topeak, RT1050, RT1090, DT9010, Rate_Cai (Hz)
%
% Inputs (required fields in 'window'):
% window.Time : time in ms
% window.Cai : Ca concentration (mM)
%
% Output (struct):
% bio... |
0bf53d3c7f41d825c6b3a57a9d469a72127dadad373f08796df2ac530c997621 | MATLAB | 5,765 | 143 | function newFileName = TS_FilterData(whatData,ts_keepIDs,op_keepIDs,newFileName)
% TS_FilterData Filters data in the hctsa data file, and saves to a new file
%
% Can use TS_GetIDs to search keywords in hctsa data structures to get IDs
% matching keyword constraints, and use them to input into this function to
% genera... |
f810856bd2674bbde25be374f0b49671a06f80e61e71b3bdaeef1212a2ea4109 | MATLAB | 5,769 | 191 | function varargout = physionet_hea(filename, hdr, begsample, endsample, chanindx)
% PHYSIONET_HEA reads data from PhysioNet .hea and .dat files
%
% Use as
% hdr = motion_c3d(filename);
% dat = motion_c3d(filename, hdr, begsample, endsample, chanindx);
% evt = motion_c3d(filename, hdr);
%
% This is for data hoste... |
76cb0f64145b29e39b8cd661e6840bc7e198d68a6db3666cf362c8b1c7d94240 | MATLAB | 5,770 | 135 | function ok = compile_ripser()
% compile_ripser Compiles and installs the ripser persistent-homology tool.
%
% This script must be run in the Toolboxes directory (same requirement as
% compile_mex.m, which calls this as part of its own build sequence).
%
% Split out from compile_mex.m into its own function so that, i... |
e422e9b861c14ab28020cf34748bc8dcff48e1e0908208fdc30788cd8ade0927 | MATLAB | 5,774 | 142 | function out = DN_FitKernelSmooth(x, varargin)
% DN_FitKernelSmooth Statistics of a kernel-smoothed distribution of the data.
%
% ---INPUTS:
% x, the input data vector
% <can also produce additional outputs with the following optional settings>
% [opt] 'numcross': number of times the distribution crosses the given t... |
0006d6f15c382b004ecbed481b3428473ec97e4809bff050c8ad2e519b6aa28e | MATLAB | 5,778 | 126 | %% Load data
data_path = 'Y:\Alice\0012_NeuroGI\NeuroGI_ephys_data\2024-11_all_ex-vivo_experiments\20241119_ExVivo-12\';
load([data_path 'datafile0024.mat'], 'data')
%% Preprocess data
reorder = (1:32:64)' + (0:31);
reorder = reorder(:);
y = single(data(2200001:4600000, :)); % get middle 10 minutes
y =... |
46decf17b7c9d54e18fab96e91c59c68806645532ff828ad6f00b60830b593aa | MATLAB | 5,782 | 135 | % =============== parameters section ===============
% Required args:
% out: output file prefix
% pheno: file with phenotyes
% bfile: plink bfile prefix
if ~exist('out', 'var'), error('out file prefix is required'); end
if ~exist('pheno', 'var'), error('pheno file is required'); end
if ~exist('bfil... |
3eaa22d6801ccbc811659d1baef93c0401c48c1669f2dfeeb1cff9bef326e336 | MATLAB | 5,783 | 124 | function chGroups = ch2roi_getSelChnls(params, subjTag)
% returns selected channels for subjTag
% based in criteria in params.connectivity.selectedChnls, where:
% - params.connectivity.selectedChnls{nn,1} = brainAtlas (e.g., 'Yeo7', 'Yeo17', 'Mars', ...)
% - params.connectivity.selectedChnls{nn,2} = aaName (e.g., 'D... |
0d7a9d06b92301ec9b1af56d7cd330d96b5d646d12023eea0f33a05afaa08b3a | MATLAB | 5,785 | 151 | % STD_SUBSTUDY - create a sub-STUDY set by removing datasets, conditions, groups, or
% subjects.
% Usage:
% >> [ STUDY ALLEEG ] = std_substudy(STUDY, ALLEEG, 'key', 'val', ...);
%
% Optional Inputs:
% STUDY - existing study structure.
% ALLEEG - vector of EEG data... |
711069a5c194e85d733a7bb3ed665a6aaf437a06124f4d545a2a71c2d98f5279 | MATLAB | 5,787 | 143 | function [C2,cfg] = mahal_twoclass_trialwise(dat,labels,cfg)
% [C2,cfg] = mahal_twoclass_trialwise(dat,labels,cfg)
% authors: M Stokes, E Spaak, N Myers
if nargin < 2
help mahal_twoclass_trialwise
error('missing input arguments!')
end
ntrl = size(dat,1); % number of timepoints
nsens =... |
e12d3bdcf2f6b7301221649346643faa883ba2ce762a264e7faa37c9afbecc98 | MATLAB | 5,787 | 90 | function aaName = getLargerAnatomicalArea(ass_cytarch, mode)
% based on the cytoarchitectonic assignment 'ass_cytarch' by SPM Anatomy toolbox,
% returns larger anatomical structure 'aaName'.
% Useful for getting more channels into anatomical areas.
% (c) Jiri, May17
% current version of SPM Anatomy toolbox: 22c or 18 ... |
ade0cb494496a0396013a453abb23fbfd530e580da32e61e67cc9e03f51fe97c | MATLAB | 5,790 | 100 | % eegplugin_dipfit() - DIPFIT is the dipole fitting Matlab Toolbox of
% Robert Oostenveld and Arnaud Delorme
%
% Usage:
% >> eegplugin_dipfit(fig, trystrs, catchstrs);
%
% Inputs:
% fig - [integer] eeglab figure.
% trystrs - [struct] "try" strings for menu callbacks.
% catchstrs ... |
40ca1b6bb04222e0f2c4f594f442c37afbb269103a5e9d2ffcc43b6758fecbd5 | MATLAB | 5,791 | 177 | function PhilipsDeIdentify(fnames)
% PhilipsDeIdentify
% Reads Philips SPAR files and removes participant information. Newly
% de-identified SPAR files are then output, with filenames appended with
% '_noID'. The original files are not overwritten.
%
% PhilipsDeIdentify will also create copies of the SDAT files... |
b611c707147bfc2fc0876db92c2fdcbfcf7b6df72a994de411896e399fdbc084 | MATLAB | 5,797 | 160 | function out = ST_MomentCorr(x, windowLength, wOverlap, mom1, mom2, whatTransform)
% ST_MomentCorr Correlations between simple statistics in local windows of a time series.
%
% The idea to implement this was that of Prof. Nick S. Jones (Imperial College London).
%
% ---INPUTS:
% x, the input time series
%
% windowLen... |
5c854b656d68b74e9c33d115ae84ad9a5739941f1cb6492cdd6b6ce76c9b81a7 | MATLAB | 5,799 | 168 | function grad = getGradient(problem, x, storedb, key)
% Computes the gradient of the cost function at x.
%
% function grad = getGradient(problem, x)
% function grad = getGradient(problem, x, storedb)
% function grad = getGradient(problem, x, storedb, key)
%
% Returns the gradient at x of the cost function described in ... |
b169a73ab24e52ea0cb8017247067c5ec3f30e54824d3099a7688bb95c22013f | MATLAB | 5,800 | 167 | function slowWaveDetection(basename,varargin)
%Vyazpvskiy et al., Tononi, 2007 Sleep,
%Vyazpvskiy et al., Tononi, 2009 Neuron
% band pass at 0.5-4Hz (stopband edge 0.1-10 Hz,Chebyshev Type II)
% Slow waves were detected as positive deflections between 2 consecutive negative deflections below the zero-crossing separated... |
0d658b7be70f8af8f2b05ad291671a87ff061aff9323b7aba31aaea8e9deb7fa | MATLAB | 5,802 | 116 | function RNN_variable = get_example_choice_mode_activity_RNN
close all
clear all
clc
% Extract RNN variables.
% Select a folder containing data.
folder_name = uigetdir;
cd(folder_name)
load('example_RNN.mat');
% Control.
L = example_RNN.example_distractor_2_5_no_ablation_control.L;
L_pos = example_RNN.example_distr... |
bfe43235c942434a0205241ad483b8a3a13790c8ae7a152c73b1bda310d2d5e1 | MATLAB | 5,804 | 181 | function [ccg,x,y] = ShortTimeCCG(times1,times2,varargin)
%ShortTimeCCG - Time-varying auto/cross-correlograms of point processes.
%
% Determine how xcorrelograms vary in time, i.e. repeatedly compute xcorrelogram
% over successive short time windows.
%
% USAGE
%
% [ccg,bins,time] = ShortTimeCCG(times1,times2,<opt... |
f6aae85367fdcb48c1a0107a5a857f36f84ea93dbb3db5f0d55a30503e690124 | MATLAB | 5,808 | 151 | % createTextures - Generate stimuli for acquiring pSFT
% Generates a set of bandpass filtered noise textures for a given image size and ppd.
%
% Syntax
% [textures, filters] = createTextures(diameter_px, contrast, noise_filter_count, noise_sample_count, ppd, save_textures, texture_filepath)
%
% Input Arguments
% ... |
1056c42894f914f039977b06506943359bb429766b3479be871a3277e739303a | MATLAB | 5,810 | 113 | % Database and batch processing functions for FMAToolbox.
%
% These functions can be used to perform batch data processing and store data
% and figures into one or more databases.
%
% Batch Processing
%
% Batch processing is useful if you need to repeatedly perform a given analysis
% on different data sets. This can be... |
ea4618308c6644b52cb41891df91859b30c33a5086eb031147b9c6cdb03e7785 | MATLAB | 5,813 | 159 | function out = IN_AutoMutualInfoStats(y, maxTau, estMethod, extraParam)
% IN_AutoMutualInfoStats Statistics on automutual information function
% of a time series.
%
% ---INPUTS:
% y, column vector of time series data
%
% maxTau, maximal time delay
%
% estMethod, extraParam -- cf. inputs to IN_A... |
8cf1db6b193f7631cc803c320f8ee8c7fc8e458a3095651643c87ce373d13bdb | MATLAB | 5,814 | 163 | function plotPolarHist2axes_realVals(ampPhiBins, plotInfo)
% plots the tuning bins in: ampPhiBins [ampBin x phiBin] of real values
% into polar histogram, axes position spec. in 'plotInfo'
% (c) Jiri, Mar12
%% plot colorbar
if plotInfo.colorbar
% vals
nCols = 2;
nRows = 359;
...aRes = 1/nCols;
aVe... |
de49b65219c414175da65b810e3da6659319c4a58022cefdfb55ee4542076f2f | MATLAB | 5,814 | 137 | %io_writerda.m
%Georg Oeltzschner, Johns Hopkins University 2019.
%
% USAGE:
% RF=io_writerda(in,outfile);
%
% DESCRIPTION:
% Takes MRS jeader data in matlab structure format and writes it to a pair
% of Siemens RDA files that can be read by LCModel, jMRUI etc.
%
% The written RDA file header information will be enti... |
7eace6b56b835411c94246da5919073b11745bebe698303fd8cc880e518dce36 | MATLAB | 5,815 | 179 | function [varargout] = maus_textgrid(filename, hdr, begsample, endsample, chanindx)
% MAUS_TEXTGRID reads speech segments from a file that has been processed with MAUS
% see https://clarin.phonetik.uni-muenchen.de/BASWebServices
%
% Use as
% hdr = maus_textgrid(filename);
% dat = maus_textgrid(filename, hdr, begsa... |
37690c799c7f8f20b363a2d6b6a8e26cd67eae17ec9c746491530fc2b4cff2cd | MATLAB | 5,817 | 143 | function out = SY_LocalDistributions(y, numSegs, eachOrPar, numPoints)
% SY_LocalDistributions Compares the distribution in consecutive time-series segments
%
% Returns the sum of differences between each kernel-smoothed distributions
%
% ---INPUTS:
%
% y, the input time series
%
% numSegs, the number of segments to b... |
5a71ae00c180edeec317e32438b39ef42374f4d789d62367aade2df118d80c42 | MATLAB | 5,820 | 140 | % Main script for computing group-mean fsaverage surface maps of
% fraction-weighted laminar SANDI metrics for supragranular and
% infragranular layers across subjects
%
% Reference:
% Lee H, ..., Huang S, Communications Biology, 2026
%
% Requirements:
% - FreeSurfer installed and configured
% - Subject-specific SANDI ... |
74df90c32b14fa5fc798bd66b3e674907b574ef63c02adf0ec3bd08263426732 | MATLAB | 5,820 | 130 | %% h = sepia_handle_panel_qsm_MEDI(hParent,h,position)
%
% Input
% --------------
% hParent : parent handle of this panel
% h : global structure contains all handles
% position : position of this panel
%
% Output
% --------------
% h : global structure contains all new and other handl... |
e333396166950af916f5f6287d55d336e6e3d0780af0079c36281e1e4807907d | MATLAB | 5,821 | 173 | % COMPPLOT - plot a data epoch and maps its scalp topography at a given time
%
% Usage: To plot the projection of an ICA component onto the scalp
% >> projdata = icaproj(data,weights,compindex);
%
% then >> compplot(projdata);
%
% else to plot an EEG epoch with a topoplot at one selected time point
% >>... |
599d3a9631d887a3f1465580808d0dfb988697a9a794fac2e1f3e71d2049ffb4 | MATLAB | 5,824 | 150 | % BIOSIG2EEGLABEVENT - convert biosig events to EEGLAB event structure
%
% Usage:
% >> eeglabevent = biosig2eeglabevent( biosigevent, interval)
%
% Inputs:
% biosigevent - BioSig event structure
% interval - Period to extract events for, in frames.
% Default [] is all.
%
% Outputs:
% ... |
d7c85ff314524d39486d2367c6c8a248ab92bb6cd0242d2cef886799ccb899d1 | MATLAB | 5,824 | 183 | function [msi] = read_bti_m4d(filename)
% READ_BTI_M4D
%
% Use as
% msi = read_bti_m4d(filename)
% Copyright (C) 2007, Robert Oostenveld
%
% This file is part of FieldTrip, see http://www.fieldtriptoolbox.org
% for the documentation and details.
%
% FieldTrip is free software: you can redistribute it and/or modi... |
751bdb6e426a98045a965a43dc56006bc44eaabb57aa26f2c2af30acede14efd | MATLAB | 5,829 | 157 | % genStimCalcResp.m - wrapper function for generating a set of grating stimuli and calculating a set of RF responses to generated stimuli
function [responseP1, responseP2, complex_response] = genStimCalcRespBar(stimParams,rfParams,rfsP1,rfsP2,stimOriIdx,stimLocIdx,splitByColumns)
if ~exist('splitByColumns','var'); sp... |
450a17e599e22c52869fcc597b76fb7678c5892de46d277bffa15b0caf7c5b43 | MATLAB | 5,838 | 157 | function [stepsize, newx, newkey, lsstats] = ...
linesearch_adaptive(problem, x, d, f0, df0, options, storedb, key)
% Adaptive line search algorithm (step size selection) for descent methods.
%
% function [stepsize, newx, newkey, lsstats] =
% linesearch_adaptive(problem, x, d, f0, df0, options, storedb, key)
... |
834e2453e04825525bf433734da0cdacd5697686cd82c7e46d09dd1ab5ae2f89 | MATLAB | 5,839 | 205 | %% MMX - Multithreaded matrix operations on N-D matrices
% mmx treats an N-D matrix of double precision values as a set of pages
% of 2D matrices, and performs various matrix operations on those pages.
% mmx uses multithreading over the higher dimensions to achieve good
% performance. Full singleton expansion is ava... |
b9d3602f986ca20aabf220695f2a77cd315b7f6372fb44fc9693c38c84bdca2f | MATLAB | 5,840 | 135 | %%% 提取指定路径下Control ROI下的RSA分析结果，当前为提取CA层的结果，计算了是否控制featureRDM的两部分结果，结果已经过**FisherZ**转换
clear;clc;
addpath(genpath('/data0/user/lxguo/Downloads/DPABI_V8.1_240101'));
addpath(genpath('/data0/user/lxguo/Downloads/REST_V1.8_130615'));
addpath('/data0/user/lxguo/Downloads/spm');
load("./featureRDM.mat");
addpath... |
fa9ab4de79416bf3157e6635b0bf09b8e4730002b1e702b38ea921698511a320 | MATLAB | 5,847 | 145 | function [ModelOutput] = fit_OspreyParamsToModel_nophase(inputData, inputSettings, fitParams)
% This function applies a set of LCModel fit parameters to a basis set of
% metabolite basis functions, and a set of cubic baseline spline basis
% functions.
%
% The function returns the complete fit, the baseline, the... |
7635a12c6f6eacc21b6de05e70dc66f609a531d0408daacda1e92fc605ae70e6 | MATLAB | 5,848 | 181 | clc;
clear;
addpath('C:\work\code\download\freesurfer\matlab');
addpath('C:\work\code\download\cifti-matlab-master');
% load brain atlas
num_roi = 400;
num_roi_str = num2str(num_roi);
atlas_file = ['C:\Users\lihon\Desktop\abcd_study\atlas\Schaefer2018_', num_roi_str, 'Parcels_17Networks_order.dlabel.nii'];
atlas_ci... |
c0f829de729685e56ba23715c097905cd6ffd24e83f11e7f1a09eac8691ef19c | MATLAB | 5,848 | 137 | function [ recoveredLocData ] = recoverLocData( originalLocData, X_RANGE, Y_RANGE )
% tracking loss·Î ÀÎÇÑ µ¥ÀÌÅÍ ¼Õ½Ç ºÎºÐÀ» ÁÖº¯ µ¥ÀÌÅ͸¦ Åä´ë·Î ÃßÃøÇؼ À籸¼º.
% ÇöÀç »ìÆ캻 ¹Ù¿¡ µû¸£¸é trackingÀÌ ²÷±â´Â °æ¿ì X µ¥ÀÌÅÍ´Â -1, Y µ¥ÀÌÅÍ´Â 481ÀÇ °ªÀ» ÃëÇÏ°Ô µÈ´Ù.
% ÀÌ·¯ÇÑ °ªÀÌ Áß°£¿¡ µîÀåÇÏ°Ô µÇ¸é ±× ÀüÈÄ µ¥ÀÌÅ͸¦ Åä´ë·... |
bd87996946c0c66052b4949c52be2c7ed9692c40d88fd60299668e48201047f8 | MATLAB | 5,852 | 131 | function [data] = iEEG_func_generate_noise(fsetup)
%% ########################################################################
% - [data] = iEEG_func_generate_noise(fsetup)
% #########################################################################
% ... |
ec1b5475e008bfd246fdf8a6efe41b9ba7d56fd9340c935c4adc66fb831ab4e2 | MATLAB | 5,854 | 140 | function OutputToCSV(whatData,writeTimeSeriesData,writeMasterFeatures)
% OutputToCSV Outputs data to csv for external analysis
%
%---INPUTS:
% whatData, which hctsa .mat file to use (default: HCTSA.mat)
% writeTimeSeriesData, (logical)[false] whether to also output time-series data to file
% writeMasterFeatures, (l... |
e81cc6d572468bf44bb7f29628268b4f28cbc8af144880531626629ba088cf17 | MATLAB | 5,859 | 160 | function [response,stimParams,rfParams] = simulateBarStimuli(barOrientation,barType,boundType,stimParams,rfParams)
pixSize = 1200;
% set stimulus parameters
if ieNotDefined('stimParams')
% defaults if not user-specified
stimParams.size = pixSize;
stimParams.barWidth = 2; % in degrees
stimParams.stepSiz... |
2078d4a2ac9e9c9ab78ce8b23f4ad2189b4333a3bbb9480c135f2a17e70d577f | MATLAB | 5,863 | 160 | % Compute rivalry onset data
%
% From the condition logfile of the binocular rivalry paradigm, onsets and
% durations for the following GLM analysis are computed. Onsets are split
% into rest, left eye, right eye or piecemeal periods. Double button
% presses are defined as same button presses falling within a defined ... |
9bcf50a0d6dd56fdca0eb552dcbcbe2d377fb8b60023a02a103b1e764444e6a4 | MATLAB | 5,864 | 92 | function [ons,dur,tr_names,values,missing_onsets] = onsetMaker(fname,startISI)
% Analysis script for Responsibility_fMRI
% rearranges the onsets of the important events of the fMRI experiment into
% a cell array according to their distinctive trial types
% Number of Trial types: 19
figFlag = 0;
load(fname);
% define... |
745ab0feaebdf8a51cab2de45c0218ddacd6eb8fac696adbc95f905f4cf83669 | MATLAB | 5,865 | 154 | function [eta, Heta, hesscalls, stop_str, stats] = arc_gradient_descent(problem, x, grad, gradnorm, sigma, options, storedb, key)
% Subproblem solver for ARC based on gradient descent.
%
% [eta, Heta, hesscalls, stop_str, stats] =
% arc_gradient_descent(problem, x, grad, gradnorm, sigma, options, storedb, key)
%
%... |
be4b1d49e5af34678979d50c96a1ea9b466169e30fc423441cfd2e9df3eddb24 | MATLAB | 5,865 | 121 | function [ripplepeaks, rippletrough, sharptransient] = iEEG_ripplechar(data,locs,maxsamples)
%% ########################################################################
% - [ripplepeaks, rippletrough, sharptransient] = iEEG_ripplechar(data,locs, maxsamples)
% ##############################... |
2f9d6efd02ca813f91a0a28efc551c75b04844af2626f76f6800e42dffb9fd57 | MATLAB | 5,868 | 139 | % Matlab script to export to BIDS
% This is a simple example to export the tutorial EEGLAB dataset
% You can run this example and checks that the data passes the BIDS
% validator, then modify it for your own purpose
%
% Arnaud Delorme - Oct 2021
data = [];
p =fileparts(which('eeglab'));
data(end+1).file = { fullfile(... |
a8b0967fae8462428bf9787bf918a52eb699b3f6a03a27c6dbf35fedbab33a5e | MATLAB | 5,870 | 166 | function output = rtClassifier(data, config)
% Params
nFolds = 1;
nPartitions = 5;
% PCA neural data, keep top 10 PCs
[data, ~, ~] = pca4Regression(data, 10, 0, 0);
% Average data over -100 to -10 and 10 to 100 ms
preBins = ismember(config.tPts, -100:10);
postBins = ismember(config.tPts, 10:100);
for tr = 1:length(d... |
0307c42e6047602aa58dd1f6da87e617e84dc2cae2aab04be34280ce73ecb6bb | MATLAB | 5,873 | 162 | function [occupancy] = SimulationFunction(params)
%SimulationFunction Performs a stochastic simulation of cell
%migration/proliferation in a brain with both white matter tracts and blood
%vessels.
% @params: params(1) = Pm (migration)
% params(2) = Pp_base (proliferation)
% params... |
cc3d594a08d96c930f3efed1f2ba6fca9a9caa5e116affe5ace6be62b3f65173 | MATLAB | 5,873 | 115 | function [datac,datafit,Amps,freqs]=rmlinesmovingwinc(data,movingwin,tau,params,p,plt,f0,fscanbw)
% fits significant sine waves to data (continuous data) using overlapping windows.
%
% Usage: [datac,datafit]=rmlinesmovingwinc(data,movingwin,tau,params,p,plt)
%
% Inputs:
% Note that units of Fs, fpass have to be cons... |
790c564789965c563d6ac74fc5287ddb3c438873bbb86a23f55278dec7bdfc32 | MATLAB | 5,874 | 157 | %%%%%% THIS IS JUST VERY SIMILAR TO PLACES, should write more general code
setenv('SUBJECTS_DIR','/home/surly-raid4/kendrick-data/nsd/nsddata/freesurfer');
%% %%%%% transfer all current ROIs to fsaverage
files = {'floc-bodies'};
hemis = {'lh' 'rh'};
vals = zeros(163842,2,8,1); % V x hemis x 8 x quantities
for f... |
5fbb0e6f6ee613825666993065fa109d938861495b38f456b118046d6b07f709 | MATLAB | 5,875 | 187 | function sR=icassoProjection(sR, method, varargin)
%function sR=icassoProjection(sR,[method],['identifier1',val1,'identifier2',val2,...]))
%
%PURPOSE
%
%To project points on plane so that Euclidean distances between the
%projected points correspond to the similarity matrix between IC
%estimates in the Icasso result str... |
f063b2e8c24e1b27b3bb3fe6949ad4f67e6dafca2df965982f0106be2674573c | MATLAB | 5,884 | 147 | function ITIbyBlock = ITIbyBlock_females(f_ratlist, RatBehaviorData)
%Create variables
nback = 7;
prctile_cutoff = 98;
frats = length(f_ratlist);
%Create functions
block_avg = @(x, blocks) arrayfun(@(y) mean(x(blocks==y), 'omitnan'), 1:3);
block_err = @(x, blocks) arrayfun(@(y)...
std(x(blocks==y), 'omitnan')./sq... |
090c34c5b2fe6dd928a678a851983324f22d9176429fc45d1f02cd606e6b7b2d | MATLAB | 5,887 | 160 | function getFet_KS2(baseName,datFile)
% Read dat file and generate Fet on each shank.
% results will be saved in [analysesdir]/CluFetRes/sessionname.spikefet.sahnk##.mat
% Also mean wave forms were calculated and saved in [basicMetaData.Basename,'.waveform.mat']]
%
% Hiro Miyawaki, @OCU
% 2019 June
%
%% test data
% ba... |
d170de5f6e202dff27da4540ee323dfd2d18ff8b65aa687c041d0d6285865551 | MATLAB | 5,887 | 165 | function [R] = McRetroTS(varargin)
% McRetroTS calls RetroTS to generate slice based regressors
% using respiration and pulse oximetry data.
% Compilable function
% Non-compiled version example (inside Matlab) :
% McRetroTS(Opt.Respfile=resp4444.1D,Opt.Cardfile=card2222.1D,\
% Opt.VolTR=2, Opt.Nslices=34, O... |
5703fcb07c81d1d378737f47bfe533ce0db8f349e40157d4a70519dcc4aba6af | MATLAB | 5,891 | 167 | function [positions, axesHandles] = divideAxes(varargin)
% DIVIDEAXES Divide figure into custom grid of axes with specified spacing
%
% Syntax:
% positions = divideAxes(divX, divY)
% positions = divideAxes(divX, divY, bounds)
% positions = divideAxes(divX, divY, bounds, sepX, sepY)
% [positions, axesHand... |
2026fb6ce3f7bab0d4614a7ce891bc8fc9cd0dcfc1cc1c070b89163a8926fbe2 | MATLAB | 5,894 | 140 | function TOL_fig_muir2004(config,params,dat)
% TOL_fig_muir2004, figure of Muir and Taube's (2004) apparatus and design
% Figure S9 for: Duvelle and Grieves (2026) Tolman's Sunburst Maze 80
% years on: A meta-analysis reveals poor replicability and little evidence for
% shortcutting. European Journal of Neuroscience.... |
5517a7b4493461d8a5f1158ad4da68847d0a585c40aa322076512289b3fbfe18 | MATLAB | 5,894 | 189 | % op_addVoxel.m
% Helge Zoellner, The Johns Hopkins University 2020.
%
% USAGE:
% out=op_takeVoxel(in1,in2,index);
%
% DESCRIPTION:
% Adds a certain voxel with indices corresponding to the 'index' input
% array. For multivoxel it is a single input, for 2D-MRSI a vector with 2 indices
% corresponding to the x- and y... |
8ce3506d2e9770470e22dfeb47f1d9aecc0a44566faea168f109e53fdf23611b | MATLAB | 5,895 | 109 | function Volume=polygon2voxel_double(FacesA,FacesB,FacesC,VerticesX,VerticesY,VerticesZ,VolumeSize,Wrap)
Vertices=[VerticesX(:) VerticesY(:) VerticesZ(:)]-1;
% List with all vertices coordinates of a face
FaceVertices=[Vertices(FacesA,:) Vertices(FacesB,:) Vertices(FacesC,:)];
Volume=false(VolumeSize);
Volume=Dr... |
57e64c97be47210c9b64538a14ba6edc60172262a7231d7692fbaf8077fe3cad | MATLAB | 5,896 | 152 | function res = permutation_expression_null_brain(geneset, expressions, gene_symbols, background)
% PERMUTATION_EXPRESSION_NULL_BRAIN(GENESET, EXPRESSIONS, GENE_SYMBOLS)
% performs permutation testing to examine in which regions the input gene
% set is overexpressed.
%
% INPUT
% geneset -- a cell array of gene symbo... |
747ccdef3f8f5d97e9dcd960e4596de69abf75bde61a719198ad1f841a314009 | MATLAB | 5,902 | 192 | function [ltom, htom, mtol, mtoh, ltom_incong, htom_incong, sems] =...
block_dynamics_wt_noNormalization(A, twin, binSize, smoothfactor, ...
volType, varargin)
%computes the change in raw wait time around each block transition. **Does not include
% violation trials**. adapted from block_dynamics_wt_binTrials... |
db738ca89538f50592c70c47f8923dc8526876d1944a79a800db24847b96745f | MATLAB | 5,902 | 138 | function out = generate_physiological_properties()
%GENERATE_PHYSIOLOGICAL_PROPERTIES Build maps, filters, and weights, then save to /data.
% Syntax
% out = generate_physiological_properties()
%
% Description
% - Adds src/simulation to path and loads network/constants via neuronConstants()
% - Generates orientati... |
41314f77a41fb25dfab186e8addd88efb1792793ac0e7a19a7b307ab8af3a17e | MATLAB | 5,906 | 168 | function [opts, args] = vl_argparse(opts, args, varargin)
%VL_ARGPARSE Parse list of parameter-value pairs.
% OPTS = VL_ARGPARSE(OPTS, ARGS) updates the structure OPTS based on
% the specified parameter-value pairs ARGS={PAR1, VAL1, ... PARN,
% VALN}. If a parameter PAR cannot be matched to any of the fields
% ... |
fba393bfcdb0f0dd0aeab6b302f03853ec8bae8c5cb69a03bc40ec5c5f0c9891 | MATLAB | 5,907 | 185 | function [ltom, htom, mtol, mtoh, ltom_incong, htom_incong, sems] =...
block_dynamics_wt(A, twin, smoothfactor, varargin)
%computes the change in z-scored wait time, normalized to mean wait time
% for each reward volume around each block transition. cmc 10/19/21.
% inputs: A struct
% twin = time window t... |
f7487997da7ada610df54b15f7ac490aa3a43c3b6ec0faa822f506ae5112c278 | MATLAB | 5,908 | 155 | function out = MF_CompareAR(y, orders, testHow)
% MF_CompareAR Compares model fits of various orders to a time series.
%
% Uses functions from Matlab's System Identification Toolbox: iddata, arxstruc,
% and selstruc
%
% ---INPUTS:
% y, vector of time-series data
% orders, a vector of possible model orders
% testHow, s... |
4092cc526bc3436fa00788748433dd9ad00dfec5d9e24868842ad83d358cfc79 | MATLAB | 5,910 | 186 | %% ConcatAllBehaviors
% Concat all behaviors (HW and Licks) in all sessions
basePath = 'E:\Data\Lobster\BehaviorData';
filelist = dir(basePath);
sessionPaths = regexp({filelist.name},'^#\S*','match');
sessionPaths = sessionPaths(~cellfun('isempty',sessionPaths));
fprintf('%d sessions detected.\n', numel(sessionPaths)... |
ab4b014094ff04e9a5e1df4c8dc86be1413deb7c1ab59a06eee1237fcc421f44 | MATLAB | 5,913 | 149 | function [maxpar maxind silhAll idxAll]=nodalclusternew(nodalEg_All_Node,Distmetric,Startmethod,numclu,Reptimes,fname);
Allpar=[];silhAll=[];idxAll=[];
for i=2:numclu
idx=[];
for j=1:1
rmpath('H:\Dpan\Program Files\MATLAB\R2011b\toolbox\stats\');
rmpath('H:\Dpan\Program Files\MATLAB\R2011b\toolbox\stats\s... |
5d74e65d4ad93252b4062ab66b2e2edbbe492bc3fc65cb754d26ffbc8172cb02 | MATLAB | 5,919 | 128 | function sched = hlp_beginschedule(tasks,varargin)
% Begin the scheduling of some set of tasks across a pool of (possibly remote) workers.
% Id = hlp_beginschedule(Tasks,Options...)
%
% Returns a scheduler handle to wait for and obtain results upon completion.
%
% In:
% Tasks : cell array of tasks; each cell can be f... |
87390713d8e3d87812e2344dd6398ff49e49a7a6168b61a41f8320f1c4065cff | MATLAB | 5,920 | 169 | % Use like: h = rm_raincloud(data, colours, plot_top_to_bottom, density_type, bandwidth)
% Where 'data' is an M x N cell array of N data series and M measurements
% And 'colours' is an N x 3 array defining the colour to plot each data series
% plot_top_to_bottom: Default plots left-to-right, set to 1 to rotate.
% densi... |
5dfe8c0451cf48e93d7a09a44855a0982aff28b28e4d31fdeaf0a78018515406 | MATLAB | 5,921 | 148 | function start_segmentation(input_img, T2_optional)
%
% Input: input_img <string> fullpath to T1 MRI image to be segmented
% T2_optional <string> fullpath to T2 weighted MRI image.
% Supports SPM during segmentation.
%
% This function calls step-by-step the full s... |
6a69d8b4e5059428729eda92d35766c44543c36bb0b18a447ed8526738d6f490 | MATLAB | 5,921 | 151 | function deltaWaves = DetectDeltaWaves(channel,spikes,doSave,opt)
%DetectDeltaWaves - Detect cortical delta waves from LFP and refine selection using local spiking activity.
%
% Detects delta waves (1–6 Hz) from LFP signals by:
% 1) Extracting LFP from the specified channel (GetLFP)
% 2) Cleaning the sign... |
c6c83cea563d5187ca90b72a4656a12f24d245e9efc76ae9bc3d174afe95d22d | MATLAB | 5,923 | 72 | function [matlabbatch] = batch_anat_job(path_anat, filter)
selector = strcat({'File Selector (Batch Mode): Selected Files'}, {' '}, {'('}, filter, {')'});
matlabbatch{1}.cfg_basicio.file_dir.file_ops.file_fplist.dir = {path_anat};
matlabbatch{1}.cfg_basicio.file_dir.file_ops.file_fplist.filter = strcat('^', filter);
... |
fe59a787da960c598b7ffa55ba3cf27a890f2a1140d1889913bbf2a3d9e93d5c | MATLAB | 5,924 | 116 | %% get_set_qsm_Chi_separation(h,mode,input)
%
% Input
% --------------
% h : structure contains all handles of SEPIA
% mode : 'set' - extract information from GUI to config file
% 'get' - extract information from config file to GUI
% input : if mode is 'set' then input shoul... |
7ec0f62d7ae6d8b0bc548a8cf7129ec06296351090dd9bca7e71ba22c3c21b67 | MATLAB | 5,925 | 191 | function [Iq,in_avg,ext_avg,in_min,ext_max]=icassoStability(sR,L,graphmode)
%function Iq=icassoStability(sR,L,graphmode)
%
%PURPOSE
%
%To compute and/or plot the stability (quality) indices of the ICA
%estimate-clusters.
%
% Iq=avg(intra-cluster similarity) - avg(extra-cluster similarity)
%
%See publication Himberg et... |
a0072d0cdb3cda28001f710a7b1f550b4bad7688f3cf8052e575138a907b36c3 | MATLAB | 5,930 | 69 | function contrasts = calc_contrasts_level1_controlled(condition_names)
contrasts = cell(1, 28);
contrasts{1}.tcon.name = 'attend_animal';
contrasts{1}.tcon.weights = contains(condition_names, "animal"... |
458c1334291569e3f04322acb9d98197d7868bb0453452b30acbb6bc4387e18c | MATLAB | 5,932 | 190 | function [X,Zf] = filter_fast(B,A,X,Zi,dim)
% Like filter(), but faster when both the filter and the signal are long.
% [Y,Zf] = filter_fast(B,A,X,Zi,Dim)
%
% Uses FFT convolution. The function is faster than filter when approx. length(B)>256 and
% size(X,Dim)>1024, otherwise slower (due size-testing overhead).
%
% See... |
8edb569dafc6ea8ac93328cff31208bd4c07f18977b2a9d3efa0c7ed3d16073f | MATLAB | 5,932 | 195 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Setup
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% What I need to do - convolve each person's task timeseries with the HRF.
% I can read in each peron's EV text file, make a boxcar function with it,
% convolve i
% t with the HRF,... |
cc8a95b8091bd698ffd022c0b42466913773dcab95f9fd1affabcf4097be2de7 | MATLAB | 5,932 | 124 | function out = SP_SinusoidFit(y, model)
% SP_SinusoidFit Fit sinusoids or a Fourier series to the time series.
%
% Fits a sum of 1-3 sinusoids, or a Fourier series with 1-3 terms, to the time
% series y as a function of its time index t = 1:N (the values are fitted in the
% order in which they occur, so the result dep... |
de43d3153cbd078a2025a5784184044ff6364ea4fdb1d3bf05e8231a35581e57 | MATLAB | 5,937 | 210 | function [merged unused] = tapas_physio_propval(propvals, defaults, varargin)
% Create a structure combining property-value pairs with default values.
%
% [MERGED UNUSED] = PROPVAL(PROPVALS, DEFAULTS, ...)
%
% Given a cell array or structure of property-value pairs
% (i.e. from VARARGIN or a structure of parameters), ... |
42907243867f2a1baf4135ba02be41cbf34db1005a5056d3d46ba8bf69ca2b0c | MATLAB | 5,940 | 112 | function [post nlZ dnlZ] = infKL(hyp, mean, cov, lik, x, y, opt)
% Approximation to the posterior Gaussian Process by direct minimization of the
% KL-divergence.
%
% The optimisation procedure is an implementation of the CVI algorithm for GP
% models, based on Algorithm 1 and Equation 13 in [1].
% To estimate ... |
619edb63712ca4ae449f0d2061166537d63c5e079555d6791e9b3cdd747117ba | MATLAB | 5,946 | 165 | %{
stack.SliceAlignment (imported) # my newest table
-> preprocess.PrepareGalvoAverageFrame
-> experiment.Stack
-----
score: float # cross correlation score
depth: float # depth in the stack in microns
x_shift: float # shift in x direction in microns
y_shift: float # shift in y direction in micr... |
af3300169290cefbef65206782506c48e2d53911ceb6d615109b535bb1239a87 | MATLAB | 5,947 | 157 | function [spectrum,f,s] = MTSpectrum(lfp,varargin)
%MTSpectrum - Compute LFP spectrum by multi-taper estimation.
%
% The spectrum is computed as the average spectrogram, using the <a href="http://www.chronux.org">chronux</a> toolbox.
%
% USAGE
%
% [spectrum,f,s] = MTSpectrum(lfp,<options>)
%
% lfp u... |
4d7196f4a081205f6f52c9353ad66337dd5ce38649bbbba03a5f918b26391f11 | MATLAB | 5,949 | 167 | function ft_write_spike(filename, spike, varargin)
% FT_WRITE_SPIKE writes animal electrophysiology spike timestamps and/or waveforms
% to file
%
% Use as
% ft_write_spike(filename, spike, ...)
%
% Additional options should be specified in key-value pairs and can be
% 'dataformat' string, see below
% 'f... |
39236bd19afd19b40e0125f9b5b81a6779f03c2083b3e63be8b7633cbb2edf79 | MATLAB | 5,950 | 182 | %% %%%%% From the hrfbasis fit (to all runs), visualize and record coordinates on unit sphere
%% [do a GLM fit in the special hrfbasis(3PCs) and then look at distribution of the loadings for good voxels]
nsdsetup;
ns = [];
allpoints = {};
for p=1:size(sessmatrix,1)
for q=1:size(sessmatrix,2)
if sessmatrix(p,q)~... |
6e9100972a242f5ec30e89d254ccd1c96a376600d61c82e564f03f2bc44f3d9c | MATLAB | 5,951 | 205 | function sphere_handles = addspheres(surface_handles, DB, varargin)
% DB database struct
% - must have xyz, contrast, condf
% optional args:
% 'contrast_num' vector of contrast numbers, for averaging coords
% 'average_nearby' average nearby clusters from same contrast
%... |
4e3f947fadcd4a623a735c7c0e7bf841478baa651be38d61af82e09aed9f6ce5 | MATLAB | 5,957 | 91 | % BIDS_METADATA_STATS - Check the BIDS metadata content
%
% Usage:
% >> stats = bids_metadata_stats(bids);
%
% Inputs:
% bids - [struct] BIDS structure (for example ALLEEG(1).BIDS)
%
% Outputs:
% stats - BIDS metadata statistics structure
%
% Authors: Arnaud Delorme and Dung Truong, SCCN, INC, UCSD, February, 2... |
5ec32c006c3bf68adbcd58795382b16ef698d4a7e27245c22055725bd6c97196 | MATLAB | 5,957 | 166 | %{
pre.SliceAlignment (imported) # my newest table
-> pre.AverageFrame
-> rf.Stack
-----
score: float # cross correlation score
depth: float # depth in the stack in microns
x_shift: float # shift in x direction in microns
y_shift: float # shift in y direction in microns
%}
classdef SliceAlignme... |
cd417e2eb791da45dccdbef56c5512975978d1e8d6defc0eb1ca3b648d2554bc | MATLAB | 5,958 | 129 | function out = EN_PermEnComplexity(y, m, tau)
% EN_PermEnComplexity Jensen-Shannon statistical complexity of ordinal patterns.
%
% Computes the Bandt-Pompe ordinal-pattern distribution (as in EN_PermEn) and
% pairs its normalized Shannon entropy with the Jensen-Shannon statistical
% complexity of Rosso, Larrondo, Mar... |
55082f651c617f2bec5aed28f0b4ef94472118ae3a3ec39b69d183871a6e97d1 | MATLAB | 5,960 | 145 | %{
pre.AlignMotion (imported) # motion correction
-> pre.AlignRaster
-> pre.Slice
---
-> pre.Channel
motion_xy : longblob # (pixels) y,x motion correction offsets
motion_rms : float # (um) stdev of motion
align_times=CURRENT_TIMESTAMP: time... |
ec9cf3f3f559143131f6ca8bbfaf0488f0f3500ef2b66467f640c1cf75a73f9a | MATLAB | 5,960 | 171 | function out = CO_HistogramAMI(y, tau, meth, numBins)
% CO_HistogramAMI The automutual information of the distribution using histograms.
%
% The approach used to bin the data is provided.
%
% ---INPUTS:
%
% y, the input time series
%
% tau, the time-lag (1 by default)
%
% meth, the method of computing automutual i... |
d32ad0a3c2550c193a8dd00d37d7661161916fb1aae511005205a1da733e7fbd | MATLAB | 5,961 | 162 | function Behaviour_analysis(path_to_data)
% Get the path to the behavioural data, calculates the relevant variables
% and plots figures.
%
% Kakaei, Schlecht, Hauser 2025
%
% See also Pupil_analysis
if nargin<1
path_to_data = pwd;
end
for exper = 1:2 % experiment counter
if exper==1
arms = 3; % numbe... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.