sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
c6e5a37c962b88b6d67cb60a2ad20d8c766f8e25512fcd3e4f45ac71c6950b68 | MATLAB | 719 | 18 | function checked = check_software_spm5(software)
if length(software)>=3 && strcmpi(software(1:3),'spm')
try
spm_ver = spm('ver');
catch %#ok<CTCH>
error('SPM is not in your path!\nPlease add a version of SPM to your path or change cfg.software to another software')
end
if ~strcmpi(spm_v... |
1d4ee6c8e46900370a7a08c0ac19afb7fcebb7f5fa48572679e608430cc6d457 | MATLAB | 720 | 19 | function msBatchCalcSegRelations(dirName,calcCorr, calcDist, calcOverlap)
%MSBATCHSEGRELATIONS Summary of this function goes here
% Detailed explanation goes here
dataFolders = msBatchFindDataFolders(dirName,[]);
parfor folderNum = 1:length(dataFolders)
currentFolder = dataFolders{folderNum};
... |
72736a260054630db8f2754b4ea7133e225adb91fcc532f9d3435bf1dbc720bc | MATLAB | 720 | 22 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Authors : CHATENET Louis
% Date : 24/05/2018
% Version : V1.0
%
% Description : GABAa current calculation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [Isyn, r, T] = IsynGABAa(dt, Vpre, Vpost, rpre)
... |
34a108172b9df137f3e5b3666225b6c542646fdbea179d7687dedf9d61a48882 | MATLAB | 721 | 24 | function [newpat] = apply_detrend(pat, varargin)
% Detrend a pattern.
%
% [NEWPAT] = APPLY_DETREND(PAT, ...)
%
% Detrends a pattern. Used in conjunction with apply_to_runs.m.
% License:
%=====================================================================
%
% This is part of the Princeton MVPA toolbox, released und... |
5d9a18bbc0d0c51a7b59d78e7fd239a78503d9f13ab61e1b1442ac9ba2d22425 | MATLAB | 722 | 34 | function [ phi ] = RF_phase_cycle( N, arg2 )
% RF_phase_cycle(N, args) Supplies phase cycling pattern to EPG code
%
% SPGR: phi = RF_phase_cycle(N,Phi0)
% N = number of RF pulses
% Phi0 = (quadratic) spoiling phase increment DEGREES
%
% balanced: phi = RF_phase_cycle(N,'balanced')
... |
bcd1717f07ec93de6725fd3f43c7e3a7cd2e90c240b5ba7e3395a4d56bcf8ccb | MATLAB | 722 | 21 | function smart_save_figures(fig, params, title_suffix)
% create desitnatoin folder where the figure will be saved if this
% folder does not exists already
if ~exist(params.folder)
mkdir(params.folder)
end
% save the figure ion a png format
p = [params.folder filesep [params.prefix '_' t... |
0584b68132a2658548927bf832b3cbbd89fb2c08b06a7818602d7e78c12f6f7b | MATLAB | 723 | 31 | % @author Farad Khoyratee
% @date 16 Apr 2019
% @copyright
% SPDX-FileCopyrightText: © 2021 Farad Khoyratee <farad.khoyratee@gmail.com>
% SPDX-License-Identifier: GPL-3.0-or-later
function LoadSim = LoadSim(i, Imax)
LoadSim = (i*100)/(Imax-1);
switch LoadSim
case 10.0
disp('10%')... |
5666ad7e6b8577599e72e7d4bb39816f4410aabef2bed1d6ef5b92893bd7ada1 | MATLAB | 723 | 36 | function ft = FirstTime(O, TimeUnits)
% First time of the intervalSet
%
% USAGE:
% ft = FirstTime(is, TimeUnits)
%
% INPUTS:
% O - an intervalSet object
% TimeUnits (optionnal) - a units object or the abbreviation string
%
% OUTPUTS:
% ft - the first time of the intervalSet
% copyright (c) 2... |
b91d7d3a84a9412f785989fa9070c25837e86623e8d1d553357699764190bbeb | MATLAB | 723 | 29 | function [b] = bivar(x, kappa, dim)
%Compute biweight midvariance across dimension dim
%Implementation according to Wilcox; Robust Estimation
%and Hypothesis Testing (page 93-96)
if nargin<3,
dim = find(size(x)>1, 1, 'first');
end
if nargin<2 || isempty(kappa),
%this is supposed to be a good value for kappa
ka... |
c515c93140d29cb37d2417bc51f0efb32c90a31a2b4968f0a219f5664005a6d3 | MATLAB | 723 | 37 | %% Log Likelihood Function
function [logF, dlogF] = VMMix_logF(data, b)
% parse parameters
mu = b(1);
k = b(2);
p1 = b(3);
p2 = b(4);
p3 = b(5);
% logF
f = VMMix_f(data, mu, k, p1, p2, p3);
% dlogF/dmu
dfdmu = VMMix_df_dmu(data, mu, k, p1, p2, p3);
dlogFdmu = sum(dfdmu./f);
% dlogF/dk
dfdk = VMMix_df_dk(data, mu, k,... |
224a453ca6a6d84279f47ca355bfd1d42345902114352765f6352eaeda5903c3 | MATLAB | 724 | 34 | function L = CrossValidationPeerCheck(S,Q,ep)
nbEp = 10;
epV = regIntervals(ep,nbEp);
L = zeros(nbEp,1);
weights = zeros(size(Data(Q),2),nbEp);
for ii=1:nbEp
ix = (1:nbEp);
ix(ii)=[];
testEp = epV{ii};
trainingEp = epV{ix(1)};
for jj=1:nbEp-2
trainingEp = union(trainingEp,epV{ix(jj)}... |
7ae229b8aca02cdb4230381c09b9637f3ba9cd2cda3e3b5256cff1fc28a737b2 | MATLAB | 724 | 26 | function save_log(Experiment)
% Save Log Files
% Input: Struct 'Experiment' with fields 'Subject'
% Output: (1) .mat file with table 'Log' (concatenated tables from
% Subject.Log) and stuct 'Experiment' (Stimulus data is
% removed before saving to reduce file size)
% (2) .xls fi... |
ef6161872f0fd3cb341e0e9ca728f36e969ca2dc7c16b0a33af93b7722c6fd70 | MATLAB | 724 | 26 | function net = convertoldnet(net)
%CONVERTOLDNET Convert pre-2.3 release MLP and MDN nets to new format
%
% Description
% NET = CONVERTOLDNET(NET) takes a network NET and, if appropriate,
% converts it from pre-2.3 to the current format. The difference is
% simply that in MLPs and the MLP sub-net of MDNs the field AC... |
13b7f189e986c6be9c866f78a664b3ed8f241dfcb5319763ed3090fc68193126 | MATLAB | 725 | 21 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Authors : CHATENET Louis
% Date : 24/05/2018
% Version : V1.0
%
% Description : NMDA current calculation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [Isyn, r] = IsynNMDA(dt,Vpre, Vpost, rpre)
... |
e4038778244e78b7fb33d3b338551d0e1ff61b5dfb99839b0dbc3962b0d36a96 | MATLAB | 725 | 29 | function [ gx,dgdx,dgdP ] = g_softmax(x,P,u,in )
% softmax decision rule for Q-learning (2-armed bandit task)
% function [ gx,dgdx,dgdP ] = g_softmax(x,P,u,in )
% IN:
% - x : Q-values
% - P : inverse (log-) temperature and bias
% - u : [useless]
% - in : [useless]
% OUT:
% - gx : P(a=1|x)
% inverse tempera... |
8a8e264d7d41aebc34a12e2553824a38dca56cad3b117a1618b0043f45f4f72d | MATLAB | 726 | 30 | % Cost function
%
% Cost function present in the Matlab Help for fminunc function
function [f,g] = costfunction(x)
% BROWNFG Nonlinear minimization test problem
%
% Evaluate the function
n = length(x);
y = zeros(n,1);
i = 1:(n-1);
y(i)=(x(i).^2).^(x(i+1).^2+1) + (x(i+1).^2).^(x(i).^2+1);
f=sum(y);
% Evaluate the ... |
a8225b1737a0094c88cd2a954f15624f8f82d2840d79b04551432b7de6face8e | MATLAB | 726 | 27 | function [xf] = generate_alpha_damped_sin( dt, T, frequency, tau, phase_angle )
% *WAVE*
%
% GENERATE ALPHA DAMPED SINE WAVE TEST DATA generates a simple test damped
% sine wave for use with the
% functions in WAVE... |
bf7ef89601d4685c3cb03c4b071c886d336ea91e9c0380852fc232160617788a | MATLAB | 726 | 22 | function pSVR_save_temp(sub_id, p, predictions, results, suffix)
% function pSVR_save_temp(sub_id, p, predictions, results, suffix)
%
% Save temporary result file during ongoing analysis. Variables include:
% - sub_id: ID of the current subject.
% - p: Structure with analysis parameters.
% - predictions: Structu... |
36f617b1fe5e47462eac9a72c9d12bff6a5258e8751bfd6e4a55cd436d47c8f0 | MATLAB | 728 | 28 | % function out = cov2(x,y)
%
% Unlike cov(x,y) it assumes that x and y columns belong to pairs, i.e. we
% calculate a quadrant of cov([x y]), equivalent to corr(x,y) for
% correlations. cov(x,y) would calculate cov(x(:),y(:)). We always
% calculate the sample covariance.
%
% 2015/04/15 Martin Hebart
function... |
a43cbd34a0aaf20e1cb2a10ebcfbc4794f81bf7cecc2502aa6e0569961d285b2 | MATLAB | 728 | 42 | function R = Range(tsa, tsflag)
% Returns TSD timestamps
%
% USAGE:
% R = Range(tsa)
% R = Range(tsa, tsflag)
%
% OPTIONS:
% tsflag - if 'ts' returns time in timestamps (default),
% if 'sec' returns time in sec
% if 'ms' returns time in ms
% ADR
% version L4.1
% status: PROMOTED
% v4.1 28 oct 1... |
fd321d27f2c913b1b06f15ca4939113207bdef13a058d1aba82ea8a887051d9a | MATLAB | 728 | 25 | % function r = correl(x,y)
%
% Custom made correlation function, faster than Matlab versions, but less
% general (e.g. only for 1D x and y). If you want another 2-6x or more
% speed-up, download and compile fastcorr from file exchange and replace
% the content of this function with a direct call to fastcorr(x,y)... |
687ce5cbbe96eb64b4480344ed288b59043efe4d39be5d2e1c8d94c461a3cdef | MATLAB | 729 | 30 |
getREM = 0;
load(fullfile('Data','BehavEpochs'));
load(fullfile('Data','SpikeData'),'S');
[~, foldername, ~] = fileparts(pwd);
if getREM == 1
load(fullfile('Sleep',[foldername '.SleepState.states.mat'] ));
% get REM episodes
rem = SleepState.ints.REMstate;
remDur = sum(rem(:,2) - rem... |
ea4dbe7aa4352a2fd5b31e9e1d8d2e190d79f4238e4d4ad7af27e27c6115af89 | MATLAB | 730 | 32 | function [S,ix] = Start(O,tsa)
% Returns subsets of an intervalSet to which timestamps belong to
%
% USAGE:
% S = Restrict(O, TimeUnits)
%
% INPUTS:
% O - an intervalSet object
% tsa - a tsd or ts object
% TimeUnits - a units object or the abbreviation string
%
% OUTPUT:
% S - an intervals... |
686e15e7fc8cd5afb5a03caf7795c3bc11fba1dd07be395f8c1f74bd9eb74499 | MATLAB | 731 | 31 | %% Gloor SSFP function 23-5-2017
% from Gloor, M., Scheffler, K. & Bieri, O. Quantitative magnetization transfer
% imaging using balanced SSFP. Magn. Reson. Med. 60, 691–700 (2008).
function Mss = ssSSFP_Gloor(alpha,b1sqrdtau, TR, T1x,T2,f,ka,G)
M0a = (1-f);
M0b = f;
kb = ka * M0a/M0b;
R1a = 1/T1x(1);
R1b = ... |
374ba91364642efa0bba2248dba477636d35bf1990867515904fae692fb02fcd | MATLAB | 733 | 29 | function [e, varargout] = neterr(w, net, x, t)
%NETERR Evaluate network error function for generic optimizers
%
% Description
%
% E = NETERR(W, NET, X, T) takes a weight vector W and a network data
% structure NET, together with the matrix X of input vectors and the
% matrix T of target vectors, and returns the value o... |
7ff5162e694ec638727afea841b2a9d02fd39333cd3ded2613e72da54ab33543 | MATLAB | 733 | 32 | % trials is channels x time x trials
% for continuous recording where data is time x (chn x cond x chromophore)
% for new SD, should cut down from 324 to 270 channels
function [data,varargout] = selectRS_cnt(data,isSDNew,mlList,mlActAuto)
numConds = 3;
if isSDNew
% yes you can automate this list but too laz... |
dba03ab83806b5ef07c89c6833fa73c72386e6af46ff7bc0b38d73ff2b1d2be0 | MATLAB | 733 | 26 | function bfca = pSVR_load_bfca(p)
bfca_temp = zeros(numel(p.subjects), p.psvr.n_tr, p.psvr.n_perm + 1);
for i_sub = 1:numel(p.subjects)
% Get subject ID
sub_id = p.subjects(i_sub);
% Get subject ID as string
sub_str = num2str(sub_id,'%02i');
% Load reconstruction results
bfca_file = dir(ful... |
1d8d2b2282790bdae56dad8257f9fe157502c653fcab7529f188508cd37843bf | MATLAB | 734 | 24 | function mri_preprocessing(p)
% Run a number of preprocessing steps on the fMRI data. The analysis is
% based on realigned (but otherwise raw) data, so this is the only
% essential preprocessing step for the analysis. We also run coregistration
% and segmentation to estimate transformation-fields from MNI to subject
%... |
9ec529e4366bbdf9b6a5894cf4f5a3aa213226742de2b36d7937fa1e3e9206e6 | MATLAB | 735 | 32 | function [xo] = bandpass_filter(x, f1, f2, filter_order, Fs)
% *WAVE*
%
% BANDPASS FILTER filter a datacube between frequencies f1 and f2
%
% INPUT:
% x - datacube (r,c,t)
% f1 - low-frequency cutoff
% f2 - high-frequency cutoff
% filter_order - filter order (N.B. doubled for forward-reverse filter)
% Fs - sampling ... |
ba06345844f6bd694c8869e25f616cb926294dd758406048dbff855a93403a49 | MATLAB | 735 | 17 | function output = transres_RSA_dist_corr(decoding_out,chancelevel,cfg,data)
% function output = transres_RSA_dist_corr(decoding_out,chancelevel,cfg,data)
%
% Calculates the correlation between all datapoints of the full datamatrix.
%
% 2013 Martin H.
warningv('TRANSRES_RSA_DIST_CORR:DEPREC',...
['The ... |
5b4bd22c311b74d14f052713670f46e3da438d17891e006cab8de65e3576306f | MATLAB | 736 | 17 | % This function call is deprecated.
%
% Because this function does not prepare a decoding, but describes the
% data, it is now called decoding_describe_data.m.
% Otherwise nothing changed.
%
% For convenience this function calls decoding_describe_data() for you.
%
% See also DECODING_DESCRIBE_DATA
% functio... |
cb09723caa4a32ec568b02b274c19d801d3ae51326b1895b13a8c2e465c9d5a2 | MATLAB | 736 | 28 | % for continuous recording where data is time x (chn x cond x chromophore)
% this is only for sbj 08 and 10. To convert old SD to new SD
% should cut down from 378 chns to 324 chns
function [data,varargout] = convert2SD2_cnt(data,mlList,mlActAuto)
numConds = 3;
% list of both LS and SS chns to remove, 42 to 36 chns
... |
2c62af10eca142cd2c423c972fc6951837e3832e8c0af29f30f2ae313f68c273 | MATLAB | 737 | 20 | function decoding_out = ensemble_balance_test(labels_test,data_test,cfg,model)
switch lower(cfg.decoding.method)
case 'classification'
[predicted_labels, decision_values, opt] = ens_bal_te(labels_test,data_test,model,cfg); %#ok<*ASGLU>
case 'classification_kernel'
[predicted_l... |
4ca904c3bff05251270d187e6d5f2f6ccfeb69cf06df2d7c7911df99a8fde667 | MATLAB | 737 | 31 | function [xo] = analytic_signal_fir( x )
% *WAVE*
%
% ANALYTIC SIGNAL FIR returns the analytic signal representation
% using FIR filter implementation
%
% INPUT:
% x - datacube (r,c,t)
%
% OUTPUT:
% xo - output datacube
%
assert(ndims(x) == 3,'datacube input required');
[dim1,dim2,dim3] = s... |
70301db4217a091b64535b9a58ac81c37512f5bcaf25e162e84e5061341364cf | MATLAB | 738 | 28 | % run all level1 runwise all classes
% add path to this script
addpath('/home/kai/haxby01_scripts_etc/scripts');
% add path to spm
addpath('/analysis/kai/spm/spm12b');
spm fmri
%%
runjob = 1
%%
for sbj = 1:6
clear matlabbatch
% get design
matlabbatch = level1_ruwise_all_classes(sbj, 0);
% est... |
3bd89698eaeae577024eb6b196f4be1b4e1999aa2715e2aa670f797be594549d | MATLAB | 739 | 23 | function varargout = read_voxels_spm8(varargin)
% read_voxels:
% inputs: header, coordinates (n x 3 (XYZ))
% output: 1 x n vector of voxel values
hdr = varargin{1};
x = varargin{2}(:,1);
y = varargin{2}(:,2);
z = varargin{2}(:,3);
if nargin >= 3 % if subvolumes in 4D file should be selected... |
4a0558da64828d53974bb4bf37c111463279887a5163cc504a6c2d0057a08592 | MATLAB | 739 | 22 | clc
clear
resultPath1='/disk1/dan/di2/cascade_train_history/baseline_PMVS/collected_points_eval_0.75/TotalStat_binary.mat';
x1=load(resultPath1);
resultPath2='/disk1/dan/di2/cascade_train_history/baseline_PMVS/collected_points_eval_0.5/TotalStat_binary.mat';
x2=load(resultPath2);
resultPath3='/disk1/dan/di2/cascade_tr... |
4bbd0d1b19b7e2257d1fac3c282274be75c66b41a4254d3d1d34fdd8086e8d35 | MATLAB | 739 | 18 | function checked = check_software_spm8(software)
if length(software)>=3 && strcmpi(software(1:3),'spm')
try
spm_ver = spm('ver');
catch %#ok<CTCH>
error(['SPM is not in your path!' char(10) 'Please add a version of SPM to your path or change cfg.software to another software'])
end
if ~s... |
5b0d96d172bdbecf9ab05d67aaa938486e9ac1f6e101c6591395f2d85632deda | MATLAB | 739 | 26 | function [PNN_matrix,res,loc] = dominateset(aff_matrix,NR_OF_KNN);
%[res,loc] = maxk(aff_matrix, NR_OF_KNN, 2 );
%inds = repmat((1:size(loc,1))',[1 size(loc,2)]);
[A,B] = sort(aff_matrix,2,'descend');
res = A(:,1:NR_OF_KNN);
inds = repmat([1:length(aff_matrix)]',1,NR_OF_KNN);
loc = B(:,1:NR_OF_KNN);
PNN_matrix1 = z... |
947970ad43162c1925891b244a295a1ab497b67941cec014b69bd0a512dd7d05 | MATLAB | 739 | 37 | %% Super Lorentzian, interpolated as in Gloor et al, 2008
% return LUT interpolated from -1kHz to +1KHz
% Units of G are us (microseconds)
function [ff,G] = SuperLorentzian(T2b)
%%% define frequency range
n=512;
ff = linspace(-30e3,30e3,n);
%%% compute G for this range
G = zeros([n 1]);
for ii=1:n
G(ii) = SL(ff... |
a8594b252a8f372710566abc7a7481c43a8027feb7a30491752891910808bdf8 | MATLAB | 739 | 29 | function [ A12,A22,P1toP2 ] = MouseBOT_LinkConfigurationValues(A1,A2,L0,L1,RobotPosition)
P1 = zeros(2,1);
P2 = zeros(2,1);
P3 = zeros(2,1);
P1(1,1) = L1 * cos(A1) - (L0/2.0);
P1(2,1) = -L1 * sin(A1);
P2(1,1) = L1 * cos(A2) + (L0/2.0);
P2(2,1) = -L1 * sin(A2);
P3(... |
e24b58ef0dc33cae4c6fd7b8a28ba4a9b7bf569e484de0590b406a95fa19f72f | MATLAB | 740 | 23 | function varargout = read_voxels_spm12(varargin)
% read_voxels:
% inputs: header, coordinates (n x 3 (XYZ))
% output: 1 x n vector of voxel values
hdr = varargin{1};
x = varargin{2}(:,1);
y = varargin{2}(:,2);
z = varargin{2}(:,3);
if nargin >= 3 % if subvolumes in 4D file should be selecte... |
1220d78be67790558044e6764beb87a8ea8f056e3324f215fc82beb94966d14b | MATLAB | 741 | 21 | function msBatchExtractBehavior( dirName, trackLength)
%MSBATCHEXTRACTBEHAVIOR Summary of this function goes here
% Detailed explanation goes here
dataFolders = msBatchFindBehavFolders(dirName,[]);
for folderNum = 1:length(dataFolders)
currentFolder = dataFolders{folderNum};
dirData = dir(curre... |
1721df370684515df862bafb6d6b0cc5c92bc3064f91623490e5d045fe2a70f6 | MATLAB | 741 | 28 | function sliderMoving_spotsthresh
global thresholds
global sizes
global sigmas
global framenum
global slice
global text_threshold
global text_size
global text_sigma
global text_timepoint
global text_slice
global text_spot_num
global I
global wholestack
global ax
set(text_threshold,'String',['threshold ... |
258b4c33947e6a0cb5e0a1baeb26e5eae88dcbf1b391ba6e52fe5ed5e4825ca6 | MATLAB | 741 | 23 | function varargout = read_voxels_spm12b(varargin)
% read_voxels:
% inputs: header, coordinates (n x 3 (XYZ))
% output: 1 x n vector of voxel values
hdr = varargin{1};
x = varargin{2}(:,1);
y = varargin{2}(:,2);
z = varargin{2}(:,3);
if nargin >= 3 % if subvolumes in 4D file should be select... |
00be46c9a22195291673e21ced65396f459d8074ec937ef7b0de7e89915ebbc7 | MATLAB | 743 | 25 | function s_model = init_model(analysis_folder)
%% CREATION OF THE STRUCTURE WHO COLLECT EVERYTHING
s_model = struct();
% ANALYSIS PARAMETERS ON THE OUTPUTS (main_structure : s)
% step1
s_model.figure.savepng = 1;
s_model.figure.savefig = 1;
s_model.figure.closefig = 1;
s_model.debug.mode = 0;
s_model.debug.folder =... |
63b3c63a52122f33cb3754bdcd23d24d57d6e0494818b88dba1653d5d078e1b7 | MATLAB | 743 | 26 | % @title Ornstein-Uhlenbeck process to mimic synaptic noise
% @file OUproc.m
% @author Farad Khoyratee
% @date 22 Feb 2018
% @copyright
% SPDX-FileCopyrightText: © 2018 Farad Khoyratee <farad.khoyratee@gmail.com>
% SPDX-License-Identifier: GPL-3.0-or-later
%
% @details
% > **22 Feb 2018** : file c... |
7a9b70b60dfa9c56648e36d0eea4fbc80aedb22b2d00de0def9cecce41e6f46a | MATLAB | 743 | 41 | function [Qns] = computeQnsFromGivenNetForNewData(Y, net)
if isempty(net)
error('net obejct is invalid')
end
Ycell = Y;
Y = cell2mat(Y);
psii = net.hparams.psii;
Xm = net.hidden.Xm;
Lm = net.params.Lm;
Xcov = net.hidden.Xcov;
Lcov = net.params.Lcov;
n = size(Y,2);
p = size(Y,1);
s = size(Lm,2);
stran = net.params.... |
98c46a935a442031a859bcd3f57e12c812a5ed70956b95ccb89b2473b4b004cc | MATLAB | 744 | 23 | function varargout = read_voxels_spm8b(varargin)
% read_voxels:
% inputs: header, coordinates (n x 3 (XYZ))
% output: 1 x n vector of voxel values
hdr = varargin{1};
x = varargin{2}(:,1);
y = varargin{2}(:,2);
z = varargin{2}(:,3);
if nargin >= 3 % if subvolumes in 4D file should be selecte... |
05f935c603b4f42aad4f327d2c484e416fd767d31b1427afb869378919c37722 | MATLAB | 746 | 26 | function [S1,S2,S3,M]=Demod(X0,X1,X2,phasex0,phasex1,phasex2)
%This function solves the linear equation system for HELM
%
% Reto Fiolka, 17.07.2007
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
X=[X0; X1; X2];
i=sqrt(-1);
m=2;
M=[m exp(i*phasex0) exp(-i*phasex0);
m exp(i*phasex1) exp... |
3b0b57f0b68c128dd684f64a8a16b6f7eb556335fcd8a5c27f820ed8c627022d | MATLAB | 747 | 20 | function msBatchSelectPropsForTracking(dirName)
%MSBATCHSELECTPROPSFORTRACKING Summary of this function goes here
% Detailed explanation goes here
dataFolders = msBatchFindBehavFolders(dirName,[]);
for folderNum = 1:length(dataFolders)
currentFolder = dataFolders{folderNum};
dirData = dir(curr... |
82a7045a76a56a9f5c985d4fc30db772f77daf41c64e46c182fb2b442b2c53eb | MATLAB | 747 | 24 | function X = squeeze1(X)
% Like squeeze but prevents unwanted transposes. This deals with
% cases where e.g. size(X) = [1, 1, 20] and size(squeeze(X)) = [20, 1]
% whereas size(squeeze(X)) = [1, 20] would be desirable. The latter case is
% relevant e.g. in leaveout cross-validation where the first dimension is
% the sam... |
91c85f5c84d40bc93540fc300fc38c1708a7c7e8e55b4d21088db44aa128d8bb | MATLAB | 747 | 20 | function BN2brainmap(brainmeasure,mask_path,output_name)
% V = spm_vol(fullfile(filesep,'Volumes','menon','projects','jinliu5','2021_Longt_math_gene','data','imaging','roi','Reslice_BN_Atlas_246_3mm.nii'));
% V = spm_vol(fullfile(filesep,'oak','stanford','groups','menon','projects','jinliu5','2021_Longt_math_gene','da... |
0de845866694e9934ed4fc4bd1be7907bd0ff36e6c6ad37d81737141cb246feb | MATLAB | 748 | 40 | function [dataout, B_PE] = filterExponential(tau, dt, datain, sines, delay)
if ~exist('delay','var')
delay = 0;
end
tt = (0:dt:(tau*5 + delay))';
if tau ==0
% Add a delay
B_PE = zeros(size(tt));
B_PE(end) = 1;
else
% Filter and add a delay
B_PE = exp(-(tt-delay)/tau);
B_PE(... |
00e8b5a0c235ac9c9db0503d1b401513e961152f1a514130881d4e1f24b1f090 | MATLAB | 749 | 30 | %
% report time in experiment
%
clear all;
CMBHome_path = "/comp_neuro/Software/Github/CMBHOME_github/";
addpath(CMBHome_path);
load filenames;
load tetrodes;
load cells;
file_number=15;
load(filenames(file_number));
root.cel = [tetrodes(file_number),cells(file_number)];
ts_per_sec=50; % timesteps per second
ms_per_ts=... |
21a99ebfdf07f7823346a5010bb409fd4966aa0974997d08721927de37cc45d7 | MATLAB | 749 | 18 | function output = transres_RSA_dist_euclidean(decoding_out,chancelevel,cfg,data)
% function output = transres_RSA_dist_euclidean(decoding_out,chancelevel,cfg,data)
%
% Calculates the euclidean distance between all datapoints of the full
% datamatrix.
%
% 2013 Martin H.
warningv('TRANSRES_RSA_DIST_CORR:DEPR... |
5c9657d24c6b8b1082b45531b65189fbb419dd08d05d12b336da5a6ed9a33588 | MATLAB | 749 | 32 | function ep = LoadDatEpoch(varargin)
%
% ep = LoadDatEpoch(epname)
% or
% ep = LoadDatEpoch(fbasename,epname)
% if you need to specify the path to merged folder
%Adrien Peyrache, 2012
if length(varargin)==1
epname = varargin{1};
fbasename = [];
elseif length(varargin)==2
epname = varargin{2};
fbasename = [vararg... |
33bf3347ba4231fc83bf0490651180d74292c55a296c8b8f130ec4c2474d5f0a | MATLAB | 750 | 34 | function UnitTestsAll()
global cfg
t1 = tic;
setNamespace('Homer3')
UnitTests_Init(true, true, 'UnitTestsAll');
cleanupObj = onCleanup(@()userInterrupt_Callback(true));
cfg.SetValue('Regression Test Active','true');
cfg.SetValue('Include Archived User Functions','Yes');
cfg.SetValue('Default Processing Stream Styl... |
adedf24ebb9dd9cf1ed5954a080afd14ff64b2bc809398369251da4c688d8aff | MATLAB | 752 | 25 | % @title d state for Channel Rhodospin 2 (3 states model)
% @file d_RhCh2_3states.m
% @author Romain Beaubois
% @date 09 Aug 2021
% @copyright
% SPDX-FileCopyrightText: © 2021 Romain Beaubois <refbeaubois@yahoo.com>
% SPDX-License-Identifier: GPL-3.0-or-later
%
% @details
% > **09 Aug 2021** : fil... |
bd08bdd3f29a2288e6146a460d7f6ba39fe7827e553b5dca1ba0d4cd71276a57 | MATLAB | 752 | 30 | function R = Restrict_int(tsa, t0, t1)
% tsd/Restrict
% R = Restrict(tsa, t0, t1)
% Returns a new tsa R so that tsa.data is between timestamps t0 and t1
%
% ADR
% version L4.1
% status: PROMOTED
% v4.1 29 oct 1998 now can handle nargin=2
% v4.2 23 jan 1999 now can handle t0 and t1 as arrays
switch nargin
case 2 ... |
fd0e3f3e8a253779c4e6ad679f5bf083aba45c21ee21697a8089797118b5999c | MATLAB | 753 | 21 | function tracklist=build_tracks(segment_links)
origin_id=1;
tracklist{origin_id}=[];
while ~isempty(segment_links)
current_index=segment_links(1,1);
target_index=segment_links(1,2);
tracklist{origin_id}=[current_index, target_index];
segment_links(1,:)=[];
next_segment=find(segment_links... |
01c49c1cdd658bf2bf6d73cff2bb1fcfe2e6d9820c25b165c240bab11f8fceb4 | MATLAB | 755 | 24 | function vels = CalculateVelocities(tracks_in, pxPerMicron, timeBtwFrames)
a = unique(tracks_in(:,4));
b = cell(size(a));
e1 = zeros(size(a));
e2 = zeros(size(a));
for i = 1:length(a)
c = tracks_in(tracks_in(:,4) == a(i),[1,2]);
d = nan;
for j = 1:size(c,1)-1
p1... |
481de976356632262f525ecda4097770fb86c982fc5544ae615c91637ac690ce | MATLAB | 755 | 29 | function res_table =get_PEATS_table(params)
[~, c_info] = size(params.info_table);
varTypes = [""];
varNames={};
for i=1:c_info
varTypes(i)="string";
varNames{i}= params.info_table.Properties.VariableNames{i};
end
varNum = c_info;
varTypes(end+1)="string"; varNam... |
e059b83e8cc430514aae049477918e95e8416e5babdbac8fd5f1331ccad71ea9 | MATLAB | 755 | 22 | %This analysis code was used in:
%Mares I, Ewing L, Papasavva E, Ducrocq E, Smith FW, Smith MLS (in press).
%Face recognition ability is manifest in early dynamic decoding of face-orientation
%selectivity – evidence from multi-variate pattern analysis of the neural
%response. Cortex.
%The code was originally cre... |
f9440819519029cccdcf8785a71c2b6a14fc3f758c560f6586ae4fc5e4d61c94 | MATLAB | 758 | 38 | function [x,yp,P,K,xm,Pm]=kalmanfilter(y,M);
% Implentation of Kalman filter
% y=oxT observables
% M=structure:
% M.A:transtion
% M.C:Observation
% M.Q:state Noise
% M.R:Observation noise
% M.x0: guess in beginning
% M.P0: Uncertainty in beginning
Pm=M.P0;
xm=M.x0;
for n=1:size(y,2)
% Deal with time... |
70f1b7b985d6c20dce99bd62a93b755adaaf04ab554d9cd37ef502e0563a3960 | MATLAB | 759 | 24 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Authors : CHATENET Louis
% Date : 24/05/2018
% Updated : 30/05/2018
% Version : V2.0
%
% Description : GABAb current calculation
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [Isyn, r, s] = IsynGABAb2... |
15ddd5216b7faf5831b2665a7d3c22aeae06d07c25c874f839ca18ff56626c76 | MATLAB | 761 | 25 | function p = MD_vmpdf(x, mu, ka, Ik)
% _
% Probability Density Function for a von Mises Distribution
% FORMAT p = MD_vmpdf(x, mu, ka)
%
% x - an N x 1 vector of angles (domain: -pi <= x_i <= +pi)
% mu - a scalar, the mean of the von Mises distribution
% ka - a scalar, the precision of the von Mises distri... |
6b08b9c1aa01924dfae873a8e00aa24ee4d1ab87701f1fd7eddcdd1ec5c4e1be | MATLAB | 763 | 35 | function ok = belong(is,t)
% Tells whether timestamps belong to a intervalSet
%
% USAGE:
% ok = belong(is,t)
%
% returns 1 if t belongs to the interval is, 0 otherwise
%
% INPUTS:
% is - an interval set
% t - a time expressed in the same Time_Unit, or a vector of times
%
% OUTPUTS:
% ok ... |
1e50c09beb745b0bec08e470e883500ae89b614afce004be2e6eba575ccc39a9 | MATLAB | 764 | 30 | function req_params = reqParamsEffectSize(task,monkey)
if nargin<2 || monkey=="both"
if task=="floc"
req_params.ID = 3000:4000;
else
req_params.ID = 4000:6000;
end
elseif monkey=="albert"
req_params.ID = 4000:5000;
elseif monkey=="golda"
req_params.ID = 5001:6000;
else
return
en... |
b0d76d4e9fa619b0fa608077c98049078285ec5e445068cdda6b91b8438588dc | MATLAB | 764 | 29 | function [res, fmt] = detCosinor(actigraphy, epoch, varargin)
%DETCOSINOR do cosinor analysis
%
% [RES, FMT] = DETCOSINOR(ACTIGRAPHY, EPOCH, STARTTIME, QUALITY, COSINORINFO)
% performs ACTIGRAPHY of epoch length EPOCH and
% return results to the caller.
% FMT request the format to write RE... |
901bfe0b12c6426f70428ffa30b67340abbfb2e41ff097c2f7bbbd60c71ce5fa | MATLAB | 765 | 14 | function model = RFEselect_train(labels_train,vectors_train,cfg)
switch lower(cfg.decoding.method)
case 'classification'
model = svmtrain(labels_train,vectors_train,cfg.decoding.train.classification.model_parameters);
if isempty(model), error('svmtrain returned an empty model - please check ... |
4e9e8cf81700971e46d46bb2e729fa4681a1fdde3e7bd4165d96a9adacc46730 | MATLAB | 766 | 27 | function msSaveVideo(ms,frameLimit, downSample, columnCorrect, align, dFF, outFile)
%MSSAVEVIDEO Summary of this function goes here
% Detailed explanation goes here
mindFF = 0.1;
maxdFF = 0.7;
if isempty(frameLimit)
frameLimit = [1 ms.numFrames];
end
writerObj = VideoWriter([outFile ... |
a241d05186a44e6034b69f2b120aff6d70c72cb9a3e3b17564a8b6f0abab6f4f | MATLAB | 766 | 24 | function disc = PT_disc(theta,type,varargin)
% a function that converts Prospect Theory weighting function and amount function into discounting functions
% varargin can provide alpha, gamma, delta, which would be instantiated as a, g, d respectively
for i = 1:2:length(varargin)
eval([varargin{i}(1),'=',num2str(var... |
a7a6cbc8c61e3ffcac1a53c235943d30ff2ece08f8666152bb61178dba5532bc | MATLAB | 767 | 33 |
fitFunc = @(b,x) b(1) * exp( b(2) * cosd( x - b(3) ) );
errorFunc = @(b,x,y) sum((fitFunc(b,x)-y).^2);
opts = optimset('Display','off');
DIRECTIONS = 0:45:315;
REPEATS = 1;
BASELINES = 1:100;
for i = BASELINES
for r=1:REPEATS
cosFun = i*cosd(DIRECTIONS-180);
currErrorFunc = @(b) errorFunc(b,... |
bcf585ed5ed6b5c337b79580629bb6991a5764110730a064b57603ac9f525ada | MATLAB | 767 | 30 | function [IQDataS] = LoadIQ(folder, filename)
% Output: IQDataS - Inphase/quadrature ultrasound data
f = fopen(fullfile(folder,filename),'r');
IQData = fread(f,'double');
fclose(f);
if isfile(fullfile(folder,'IQSizeInfo.mat'))
load(fullfile(folder,'IQSizeInfo.mat'));
elseif isfile(fullfile(folder,'SizeI... |
781311db3608e0216d0949d4c1c169cb1452b5ef13cd0eba0b964180bc9c67ec | MATLAB | 768 | 36 | function writeTsv(filename, tsv, options)
global logger
if ~exist('filename', 'var')
filename = '';
end
if ~exist('options', 'var')
options = '';
end
if optionExists(options, logger)
logger = InitLogger(logger);
logger.Write('Exporting stim to %s\n', filename);
else
fprintf('Exporting stim to ... |
833218b9ef4b5fcb95d292f80269eb1455d51398607b60934423d0b44254c3c6 | MATLAB | 769 | 29 | %This function feeds all your deltaF/F traces in dff variable through
%T_star_loop, outputting a list of TStars
T_star_temps = [];
total_dff_amps = [];
for i = 1:length(dff(1,:))
T_star_temp = [];
Image_Time = 1:length(Temperature);
raw_temperature = Temperature;
steep_points = []; ... |
c2d8ecb6bff1c35a3734735c3f1ef44d06beb13ae4048df6038e3340463fa832 | MATLAB | 770 | 37 | function resultFlag = IsOSX(is64)
% resultFlag = IsOSX([is64=0])
%
% Returns true if the operating system is Mac OS X.
% If the optional 'is64' flag is set to one, returns
% true if the runtime is 64 bit and on OSX.
%
% See also: IsWin, IsLinux, OSName, computer
% HISTORY
% ??/??/?? awi Wrote it.
% 6/30/06 awi Fixed... |
18d492a304353cb1e114f8686bea6a08c16b7631320d607655dd8d298ebc113a | MATLAB | 771 | 31 | function [vox,n_idx,ep] = pk_follow_link(skel,node,k,j,idx,cans,c2n)
vox = [];
n_idx = [];
ep = 0;
% assign start node to first voxel
vox(1) = node(k).idx(j);
i=1;
isdone = false;
while(~isdone) % while no node reached
i=i+1; % next voxel
next_cand = c2n(idx);
cand = cans(next_cand,2);
... |
da054eee0e3967ec2a8b4bf5644a22fb453cc482f6d1ef2bf65d0b8c774b56be | MATLAB | 771 | 32 | % *WAVE*
%
% PHASE GRADIENT TEST SCRIPT takes the phase gradient of a test
% test signal (here, a 2d target wave)
%
clear all; clc %#ok<CLSCR>
% parameters
T = 1; %s
Fs = 1000; freq = 13.5; %Hz
image_size = 8; %px
pixel_spacing = 1; %a.u.
direction = +1; % +1/-1
% generate data
... |
12d0fb2a4f394e6d9c052f4021118f0d5d97c45064789b712bc4d27a9d8f210f | MATLAB | 772 | 31 | function val = HDF5_DatasetLoad(gid, name, val0, options)
if ~exist('val0','var')
val0 = [];
end
if ~exist('options','var')
options = '';
end
try
dsetid = H5D.open(gid, name);
% NOTE: HDF5 stores contiguous muti-dimensional arrays in row-major order.
% Matlab stores them in row-major order. We wa... |
e14ba76c7f99087797bbfa201aa640a0f2b88827bf0725d57692d58318564ebd | MATLAB | 772 | 27 | % function dist = cveuclidean2(X,Y)
%
% A function to calculate the cross-validated version of the squared
% Euclidean distance between multiple matrices. This is equivalent to
% d(i,j) = (X(:,i)-X(:,j))'*(Y(:,i)-Y(:,j)) for all pairs of i and j.
% Negative squared distances are possible because of cross-validati... |
43203f4bdb4577565405977be9ed0e5b6af8200e8be24e031183b534f5a4acb7 | MATLAB | 774 | 22 | function val = HDF5_Transpose(val, options)
if ~exist('options','var')
options = '';
end
% Matlab stores contiguous muti-dimensional arrays in column-major order.
% HDF5 stores them in row-major order. We want to transpose the data to agree
% with the file format's storage order.
if (~isrow(val) && ~iscolumn(val)... |
0c56ebef2c03407ec3dca15365651516a2b1b10ce065ffe41580143407634396 | MATLAB | 775 | 38 | function S = Start(O, TimeUnits)
% Starting times of for each interval in the set
%
% USAGE:
% S = Start(O, TimeUnits)
%
% INPUTS:
% O - an intervalSet object
% TimeUnits (optionnal) - a units object or the abbreviation string
%
% OUTPUT:
% S = an array of starting points for each interval in t... |
223c6885a4cdc63016f8a31b3bedbf5d38a34fb750787d85959078fae173793e | MATLAB | 775 | 36 | function L = CrossValidationSpatialCheck_Cells(S,ang,ep)
nbEp = 10;
% dispBar = 1;
epV = regIntervals(ep,nbEp);
L = NaN(nbEp,length(S));
fprintf('Launching Cross-validated HD info\n')
for ii=1:nbEp
fprintf('.')
ix = (1:nbEp);
ix(ii)=[];
testEp = epV{ii};
trainingEp = epV{ix(1)};
for jj=2:nbE... |
679e37d13867687c24591031b14053ffa0e42043f536015f69a69ef71726e92c | MATLAB | 775 | 25 | % @title o state for Channel Rhodospin 2 (3 states model)
% @file o_RhCh2_3states.m
% @author Romain Beaubois
% @date 09 Aug 2021
% @copyright
% SPDX-FileCopyrightText: © 2021 Romain Beaubois <refbeaubois@yahoo.com>
% SPDX-License-Identifier: GPL-3.0-or-later
%
% @details
% > **09 Aug 2021** : fil... |
6c13c715ea761b0a0485d5758732ba0a205d80c207b94d7fae133db60d730b96 | MATLAB | 775 | 29 | function [h, varargout] = nethess(w, net, x, t, varargin)
%NETHESS Evaluate network Hessian
%
% Description
%
% H = NETHESS(W, NET, X, T) takes a weight vector W and a network data
% structure NET, together with the matrix X of input vectors and the
% matrix T of target vectors, and returns the value of the Hessian
% e... |
2f6314657d6650fdb2112756fd7a03d01428c46fdbb45f2ea8dd1f3c7f5245b7 | MATLAB | 777 | 33 | function y = gauss(mu, covar, x)
%GAUSS Evaluate a Gaussian distribution.
%
% Description
%
% Y = GAUSS(MU, COVAR, X) evaluates a multi-variate Gaussian density
% in D-dimensions at a set of points given by the rows of the matrix X.
% The Gaussian density has mean vector MU and covariance matrix COVAR.
%
% See also
% ... |
7c89afef9b48058e6d40efafe2d5adcbc8d1b37ca52125e137e85b7c0d6a0b64 | MATLAB | 777 | 23 | function [histologyToOCTT, octPixelSize_um, topLeftCornerXmm, topLeftCornerZmm] = getHist2OCTTransformFromApp(app)
% Get OCT Volume Pixel size
x = app.jsons.sectionIterationConfig.data_um.x.values;
z = app.jsons.sectionIterationConfig.data_um.z.values;
dx = diff(x(1:2));
dz = diff(z(1:2));
if std(diff(x))>1... |
2700fb17f50f81ebfb45f88a1be1142ec18b407e74c51614f6f94cb9dda833f2 | MATLAB | 779 | 32 | function [newmap] = darkgray(m)
% DARKGRAY- A darker gray colormap than GRAY.
%
% SEE ALSO
% GRAY, COLORMAP
% License:
%=====================================================================
%
% This is part of the Princeton MVPA toolbox, released under
% the GPL. See http://www.csbmb.princeton.edu/mvpa for more
% in... |
0469b69ee551b5aa50b242d6df74a79c862335da965d6ea8e601a013e6fe7ed6 | MATLAB | 781 | 34 | function datatype = GetDatatype(handles)
global maingui
datatype=0;
if nargin==0
return
end
if isempty(handles)
return
end
plotRawVal = get(handles.radiobuttonPlotRaw, 'value');
plotODVal = get(handles.radiobuttonPlotOD, 'value');
plotConcVal = get(handles.radiobuttonPlotConc, 'value');
plotHRFVal = get(... |
9fce20c4368f3955298ba20d14a14a1325cf8eea31bb9eb1da90367cc682fc03 | MATLAB | 781 | 32 | function filename = get_filename(sub_id, p)
% function filename = get_filename(sub_id, p)
%
% Create filename for final result file.
%
% Input:
% - sub_id: ID of the current subject.
% - p: Structure with analysis parameters.
%
% Output:
% - filename: Filename (including file path, excluding timestamp) of
% ... |
b22e690963f54d8401305d9d8cb0ed87a9bd3a1ddb7eb67f44e17a8972f66cb7 | MATLAB | 781 | 35 | function [errs, msgs] = exeShellCmds(cmds, preview, quiet)
% Change #2
errs = zeros(length(cmds),1) - 1;
msgs = cell(length(cmds),1);
if nargin==0
return;
end
if ~exist('preview','var')
preview = false;
end
if ~exist('quiet','var')
quiet = false;
end
for ii = 1:length(cmds)
if preview == false
... |
f3517790f30a19f0a8d665722add6635b161a3638529a8d47fb08ed2870909f4 | MATLAB | 781 | 24 | function PlotTwoVelocityDistributions(xVec, yVec1, yVec2, fileName, xTick, xTickLabel)
h = figure;
xData = xVec(2:(end - 1));
xData = [xData; xData];
xData = [0; xData(:); max(xVec)];
yData1 = [yVec1; yVec1];
yData2 = [yVec2; yVec2];
yData1 = yData1(:)/sum(yData1(:)/2);
yData2 = yData2(:)/sum(yData2(:)/2);
plot(xData, ... |
7356fa32a71bc08e2baa23a13f81180c8297ef24106547de0d66fb574c31fb6c | MATLAB | 782 | 18 | function [diffIm, diffImBack] = CreateFinalImage(imageStack, corrPeaks)
diffIm = zeros(size(imageStack, 1), size(imageStack, 2), size(imageStack, 3) - 1);
factorArray = GetFactorArray(mean(corrPeaks), 1, std(corrPeaks)/mean(corrPeaks));
for i = 1:size(diffIm, 3)
tempArray = factorArray(1:min(length(factorArray), si... |
774264169beb372aea614f3718e769e5d91d6b5a769c317f933ee626da49cbe6 | MATLAB | 782 | 32 | function y = bhvr_preproc(y)
% function y = bhvr_preproc(y)
%
% Pre-processing of behavioral orientation labels for a von Mises mixture
% model. Takes as input values in degrees between 0° and 180° and
% returns as output the corresponding values in radians in the range -pi to
% pi.
%
% Input:
% - y: an N x 1 vecto... |
af2dfa357b64291ee3e679f69967051c9f7083a19ac29a0542f9cf0dea26a366 | MATLAB | 782 | 38 |
smoothTC = 3; % smoothing of tuning curves (3 used in Duszkiewicz et al., 2024)
%% load data
load(fullfile('Analysis','MeanFR'));
load(fullfile('Data','WaveformFeatures'));
load(fullfile('Analysis','HdTuning_moveEp'));
%load(fullfile('Analysis','CellDepth'));
goodSpk = ~isnan(tr2pk);
%frate = rateO; % for Opto d... |
e8e086d6ffa2f4e160d1a4d8ee465f565550af2444f84622c1f54a884b8f0b7e | MATLAB | 782 | 25 | function [ROImatchBinA, ROImatchAinB] = ROIMapMatching(Amap, Bmap)
% use anchor points to map ROI from 2 different map
% For each ROI in Bmap is caclulate with the largest overlapping ROI in
% Amap, overlappying is excluding nan area
% [BId, AId, CoveredA(%), CoveredB(%)]
assert(sum(size(Amap)-size... |
c09dcf3093e7ff2d7f1ff826836ecdbd395eda08bb583b1d21ec7f6fe8fc7f74 | MATLAB | 783 | 27 | function [approx detail] = dwt1(X, g, h)
% Performs a single level discrete wavelet transform.
%
% [approx detail] = dwt1(X, g, h)
% License:
%=====================================================================
%
% This is part of the Princeton MVPA toolbox, released under
% the GPL. See http://www.csbmb.princeton.e... |
0c7529f8799a2bfa0d2df6049125d675377726e38de94807dddea47986f23f42 | MATLAB | 785 | 34 | %% Plot V4 MI firing rates cued vs cue-opp (moving window plots locked to cue onset/offset)
%% Code
load('V4_FR.mat')
monkey = ["G","B","Combined"];
metric = "MI_FR";
trial_type = "all";
yl = [-0.02,0.06];
close all
cueMI = eval(sprintf("cue%s",metric));
oppMI = eval(sprintf("opp%s",metric));
sum_metric = "mean";
... |
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