sha256 stringlengths 64 64 | language stringclasses 27
values | size int32 1 491k | lines int32 1 21.8k | content stringlengths 1 200k |
|---|---|---|---|---|
c95f5aac799ad0c94dc0ba1a51dea11a8f2b32a4765bf9e563465ef0a427200a | MATLAB | 16,676 | 499 |
% PLOTTING STARTS
figure()
% performance accuracy of each subject
subplot(3,3,1)
bar([1:t], Perf_Accuracy)
axis([0 t+1 0 100])
yline(45);
yline(70);
%y = [TruePos(1) FalseNeg(1) FalsePos(1) Perf_Accuracy(1); TruePos(2) FalseNeg(2) FalsePos(2) Perf_Accuracy(2); TruePos(3) FalseNeg(3) FalsePos(3) Perf_Accuracy(... |
ff1dbd8fb63e333e89095076d654b8dc2778a303fc607c9e2b1fbf3dda192d63 | MATLAB | 16,714 | 375 | function [act, inp] = nk_VisModelsPrep(act, inp, parentstr)
% =========================================================================
% function [act, inp] = nk_VisModelsPrep(act, inp, parentstr)
% =========================================================================
% Wrapper function of the NM visualization mod... |
bcb421bcfab8979aa8f8dd36fcfa7d8d5bac991b6604e45d26418add5df1801e | MATLAB | 16,860 | 397 | function all_resvect = PC_groups_f(plot_win,freqs,fr_names,PCdir,EventTypes,SubEventTypes,varargin)
%PC_GROUPS Population phase and MRL distribution
% PC_GROUPS (plot_win,freqs,fr_names,PCdir,EventTypes,SubEventTypes,...)
% plots population phase histogram (rose diagram) derived from preferred
% coupling phase... |
10f0810095d7ccda6e6f306456407f8ed285bc380347a0ff2335946a54b81cd2 | MATLAB | 16,957 | 520 | % ========================================================================
classdef behaviouralRecord < optickaCore
%> @class behaviouralRecord
%> @brief Create a GUI and update performance plots for a behavioural
%> task
%>
%>
%> Copyright ©2014-2022 Ian Max Andolina — released: LGPL3, see LICENCE.md
% ==============... |
165b244ff1018c9924bb630041aa402343b08e5a5566c07bc28c8aaf2b705f5d | MATLAB | 17,044 | 491 | <<<<<<< HEAD
function this = gifti_read(filename, this)
% Low level reader of GIfTI 1.0 files
% FORMAT this = read_gifti_file(filename, this)
% filename - XML GIfTI filename
% this - structure with fields 'metaData', 'label' and 'data'.
%___________________________________________________________________... |
de962202b3247727fb18015bfe93849d430dc0b8b3dc5272cf66c24a1628780c | MATLAB | 17,060 | 410 | % ========================================================================
%> @class MovieStimulusTest
%> @brief Class-based unit tests for movieStimulus.
%>
%> Tests construction, property defaults, filePath resolution, selection
%> indexing, circularMask, loop strategy, pixelFormat, blocking mode,
%> special flags, s... |
235089b82bda1d2c39d98aa3b80fb1f21fe49054bd45f95a8a3f43504a4a5cec | MATLAB | 17,078 | 397 | % ========================================================================
%> @class AprilTagStimulusTest
%> @brief Class-based unit tests for aprilTagStimulus.
%>
%> Tests construction, property defaults, tag constants, binary matrix
%> generation, patternMatrix handling, colour assignment, cellSize scaling,
%> custom... |
7a4267c24d3ad34db7c41880462036fa7ba5da9a599e7fb39979feaa75ae0f17 | MATLAB | 17,185 | 496 | function EEG_LFP_ETA_PD(EventTypes)
%EEG_LFP_ETA_PD Intraop EEG and LFP event-triggered averages (ETA) plotted aligned
% EEG_LFP_ETA_PD draws ETAs of EEG and LFP patient-by-patient and
% averaged across patients.
%
% Input parameter:
% EVENTTYPES cell array of event labels
%
% Johanna Petra... |
ae45acb92a5ca84945c6f7ef4681a224d2818115aedd91fd6e7771a71a08cee9 | MATLAB | 17,235 | 521 | % ========================================================================
classdef behaviouralRecord < optickaCore
%> @class behaviouralRecord
%> @brief Create a GUI and update performance plots for a behavioural
%> task
%>
%>
%> Copyright ©2014-2022 Ian Max Andolina — released: LGPL3, see LICENCE.md
% ==============... |
0788215ddf7a5d1e03423748513b24af226de3481782e82d5d3d324064fef815 | MATLAB | 17,364 | 408 | % ========================================================================
%> @class TaskSequenceTest
%> @brief Class-based unit tests for taskSequence.
%>
%> Tests block-based variable randomisation, block/trial factors,
%> dependent properties, findRun, updateTask, resetRun, validate,
%> and sequential (non-randomise... |
ee3eab817c7dc5c3d1386c67f7247777c24e384df58ef5e27ab6f2d5f08e55a0 | MATLAB | 17,370 | 472 | % ========================================================================
%> @brief checkerBoardStimulus -- using a GLSL shader to make the
%> checkerboard
%>
%> See docs for more property details
%>
%> Copyright ©2014-2022 Ian Max Andolina — released: LGPL3, see LICENCE.md
% ==========================================... |
714f3654d19a31d6bb64d389bb51d7967b86515c66bcd6158ff0c31b4877b505 | MATLAB | 17,375 | 388 | % this demo code is part of Titta, a toolbox providing convenient access to
% eye tracking functionality using Tobii eye trackers
%
% Titta can be found at https://github.com/dcnieho/Titta. Check there for
% the latest version.
% When using Titta, please cite the following paper:
%
% Niehorster, D.C., Andersson, R. & N... |
bbe7681d451a91e1345dccb72f91c1ae9814f5ba8d4382495dfeb8650225aff6 | MATLAB | 17,392 | 375 | %FIXATION TRAINING state configuration file
%
% This presents a fixation cross with a stimulus in a loop to train for
% fixation. stims should contain 2 stimuli: stims{1} is a attention
% grabber, stims{2} is the fixation cross. Adjust stimulus sizes and
% eyetracker setting values over training to refine behaviour The... |
a8a187a6ffbe4ad5fd7861846763c9eff891fe2caf57eba824ecdc53aa443789 | MATLAB | 17,445 | 428 | % ========================================================================
%> @class StateNodeTest
%> @brief Class-based unit tests for stateNode.
%>
%> Tests tree construction, addChild, ancestors, lcaWith, effectiveField,
%> resolveLeaf, findByName, isAncestorOf, hasParentCycle, inheritFrom,
%> setFromStruct, and the... |
ed6295648411b70dbf1b5d4be8e432f3081acb8c5e10a1852c28e825def68736 | MATLAB | 17,497 | 407 | % RFLOCALISER state configuration file. This protocol allows you to elicit
% visual responses from a wide range of stimulus classes while a subject
% maintains fixation.
%
% SEE keyboard mapping for the keyboard control keys to use. Basically the
% arrow keys to change variable types and values, < and > to change stimu... |
270fd23c62d8e4991d03ca2d3abc4636aead0e6b17ac484bb7b52824dda25f63 | MATLAB | 17,602 | 379 | %FIXATION TRAINING state configuration file
%
% This presents a fixation cross with a stimulus in a loop to train for
% fixation. stims should contain 2 stimuli: stims{1} is a attention
% grabber, stims{2} is the fixation cross. Adjust stimulus sizes and
% eyetracker setting values over training to refine behaviour The... |
409c45dbec18953de221ec31e92969c4de2ef4d87f1326aebbae3644e785e63e | MATLAB | 17,602 | 385 | %component maps, dipoles and power spectra in a cluster
%ver 2009/02
%% set parameters (initialize)
try
close(4001);
end
try
close(4002);
end
try
close(4003);
end
try
close(4004);
end
try
close(4009);
end
clear all;
SL = '\';
FilePath = '';
if isunix
mypath;
FilePath = '~/liang/';... |
f10c5dd2ba8e3d49442c8f267b1fb95d5ef829fa054509e1e59bfc0191969eaa | MATLAB | 17,644 | 652 | function varargout = MovieGUI(varargin)
% MOVIEGUI MATLAB code for MovieGUI.fig
% MOVIEGUI, by itself, creates a new MOVIEGUI or raises the existing
% singleton*.
%
% H = MOVIEGUI returns the handle to a new MOVIEGUI or the handle to
% the existing singleton*.
%
% MOVIEGUI('CALLBACK',hObject,ev... |
a40a223393409aa6368cd497d62b34bb904f253571a749f20527dfdde551df6e | MATLAB | 17,845 | 411 | function [ act, NM, inp ] = nk_MLInterpreterPrep(NM, act, inp, parentstr)
% =========================================================================
% FORMAT [act, inp] = nk_MLInterpreterPrep(act, inp, parentstr)
% =========================================================================
% Runtime module of interpreta... |
f3f9bbdd2d0af63b200cf2c28452c42a0fc31216727615d23d27aa9d59c547e7 | MATLAB | 17,909 | 499 | % ========================================================================
%> @brief single grating stimulus, inherits from baseStimulus
%> GRATINGSTIMULUS single grating stimulus, inherits from baseStimulus
%> The basic properties are:
%> sf = spatial frequency in degrees
%> tf = temporal frequency in degs/s
%> ... |
4dba336792020e8df70c4beee53b0cffb8643fe71c6f14ce949ca739d727aae3 | MATLAB | 17,925 | 436 | function [dcm, est, vis] = mripy_plot_DCM(dcm, est, vis)
% Plot the general DCM results (A, B, C, etc.)
%
% dcm: Basic information
% ----------------------
% The following are the only thing that you must specify for each plot:
%
% dcm.a: The 0/1 structure of connectivity
% dcm.b: The 0/1 existence of modula... |
2b83c9fe72e5629ea8d5870152203f6dcfd10f15167e4b00dcc58ec4b2be5ce8 | MATLAB | 17,963 | 498 | function [results, center, Cn, PNR, save_avi] = greedyROI_endoscope(Y, K, options,debug_on, save_avi)
%% a greedy method for detecting ROIs and initializing CNMF. in each iteration,
% it searches the one with large (peak-median)/noise level and large local
% correlation. It's the same with greedyROI_corr.m, but with so... |
03021d4bf31d5b7df2eccea8c68759b44c17430ae84b32f502deec20aa374e2e | MATLAB | 18,017 | 580 | classdef viewer < handle
% A viewer should be initialized with all of the data that is known
properties
parent_figure
spec_ax
spec_exp
spec_fit
spec_fit_2
electrode_titles
hist_ax
hist_line
hist_val
chisq_ax
chisq_ax_txt
chisq_vert_line
tent_ax
xyz_marker
vol3d_data
red_t... |
26a00b8340f85e14ca393a92c7875991ec42e282a9e50cd8926819bfdfa2fbfe | MATLAB | 18,017 | 391 | % FIXATION TRAINING state configuration file
%
% This presents a fixation spot with a flashing disk in a loop to train for
% fixation. There is a distractor that moves around and subject must ignore
% it. Adjust eyetracker setting values over training to refine behaviour
%
%
% The following class objects are already lo... |
dd7b985dff46036da8193cb3aded7469fdcc31320efc0922c79ac8ad62b941b7 | MATLAB | 18,071 | 491 | % ========================================================================
%> @class RunExperimentTest
%> @brief Class-based unit tests for runExperiment.
%>
%> Tests construction, property defaults, set methods, and many public
%> methods that do not require a PTB screen. CI-safe tests run without
%> PTB; hardware-tag... |
50b22d5a244caa9fa13122ce61d0ebcef4cd32790a743a0e7fbcf563a0a2719b | MATLAB | 18,094 | 426 | % FIGURE GROUND state configuration file, this gets loaded by opticka via
% runExperiment class. See Jones et al., 2015 PNAS for the description of
% this task
%
% State files control the logic of a behavioural task, switching between
% states and executing functions on ENTER, WITHIN and on EXIT of states. In
% additi... |
366bbc98c2a77f742df6de23d74b8fa88929f58a50686d35e2fddc4f3085913b | MATLAB | 18,201 | 553 | function result = cvRpcr(x,y,kmax,rmsecv,h,k)
%CVRPCR calculates the robust RMSECV (root mean squared error of cross-validation) curve
% for RPCR or the robust RMSEP (root mean squared error of prediction) value in a fast way.
% The R-RMSECV curve can be used to make a selection of the optimal number of
% components... |
46240e657698a5e6400825c733a738a2c770743aa75fc3f7d4b18079bc0225b9 | MATLAB | 18,253 | 509 | %% mRVM1
% authors: Ioannis Psorakis psorakis@gmail.com, Theodoros Damoulas theo@dcs.gla.ac.uk
% Copyright NCR, 2009
%
% Use of this code is subject to the Terms and Conditions of the Research License Agreement,
% agreed to when this code was downloaded, and a copy of which is available at
% http://www.dcs.... |
dfb671a12967a6f4f4db842e65a7ffd0ed7b782df471ade87dd0eb2b3ff220fc | MATLAB | 18,274 | 383 | % AREA SUMMATION state configuration file (also used by other protocols that use a
% fixation initiation then stimulus presentation with some variables changing
% on each trial, this gets loaded by opticka via runExperiment class.
%
% The following class objects (easily named handle copies) are already
% loaded and ... |
0ef1a422ddf1158d2648ede3c380f9bef8288ea7140098572d86045e6a8535ff | MATLAB | 18,390 | 418 | function [ act, NM, inp ] = nk_OOCVPrep(NM, act, inp, parentstr)
% =========================================================================
% FORMAT [act, inp] = nk_OOCVprep(act, inp, parentstr)
% =========================================================================
% Runtime model of independent test data predic... |
b1021ffc3039336e84f26987b45d43a361545d49d5aac56bad17c630ed74427a | MATLAB | 18,473 | 466 | function PA = nk_PermX(inp, strout, id, GridAct, batchflag)
global SVM RFE SAV DR GRD MULTI RAND SCALE DISCRET SYMBOL COVAR TEST MODEFL
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%% INITIALIZATION %%%%%%%%%%%%%%%%%%%%%%%%%%%%
nclass = inp.nclass; % # of binary comparisons
label = inp.label;
lx ... |
483d273388a872781bb622f34d22a2f5bd9569fb3a0a35d07d4f8829bf205bbc | MATLAB | 18,521 | 521 | function [Out1, Out2, Out3, whiteningMatrix, mixedmean] = fastica(mixedsig, varargin)
%FASTICA - Fast Independent Component Analysis
% ADAPTED by Clara Vetter (add mixedmean as output)
% FastICA for Matlab 7.x and 6.x
% Version 2.5, October 19 2005
% Copyright (c) Hugo Gävert, Jarmo Hurri, Jaakko Särelä, and Aapo Hy... |
22aea407d377223469acd18cc6e481121f1f547bcf17fd2d76ac4c3398aaa59b | MATLAB | 18,530 | 312 | function map = inferno_gray(n)
% Returns the "inferno" colourmap.
if nargin < 1
n = size(get(gcf,'Colormap'),1);
end
values = [
0.498039215686275 0.498039215686275 0.498039215686275
0.490196078431373 0.490196078431373 0.490196078431373
0.482352941176471 0.482352941176471 0.482352941176471
... |
1bdcc6fb4c25e9abe860017c43e7fbb9e63a9aca6b2574e038f8cb46ed4199db | MATLAB | 18,564 | 453 | function [act, analdim, dat, showmodalvec, brief, indanal] = nk_SelectAnalysis(dat, newflag, ...
titlestr, analind, modflag, complflag, showmodalvec, brief, stackmin, nondeterministic)
% =========================================================================
% [act, analdim, dim, showmodalvec] = nk_SelectAnalysis... |
8111c6a92540522993568d64064c459021f7b647cb666f204130f43a566ac185 | MATLAB | 18,585 | 600 | %% Demo [Analytics vs Numeric]
%
% *****NB: Only the numeric function called is modified to include multiple costfun
% options while we investigate the proper naming and reorganization of the
% analytic functions*****
% The goal of this demo is to apply eNDM to mouse data.
% Uses numerical solutions for models using ... |
9c7debdf464866d5baf516797fe2f37478b971da2b6a9ac8e7a484e7006668d7 | MATLAB | 18,604 | 383 | %> COLOUR GRATING state configuration file (also used by other protocols that use a
%> fixation initiation then stimulus presentation with some variables changing
%> on each trial, this gets loaded by opticka via runExperiment class.
%>
%> The following class objects (easily named handle copies) are already
%> loade... |
f72fd4f1c82b6b6efb2f6b6db1533c999e3ea0bfb69855d65321d24bb7f9b96b | MATLAB | 18,730 | 424 | % DOUBLESTEP SACCADE task (TOUCH SCREEN VERSION)
% Based on Thakkar et al., 2015 Brain & Cognition
%
% This paradigm should be more sensitive to online inhibition than
% anti-saccade.
%
% In nostep trials (60%), after 500-1000ms of initial fixation, a saccade
% target (target one) is flashed for 100ms in one of 8 equid... |
931462a7aea4ee2a712864937eab4eecb9ac066438810e33f9aa332da0d35d6d | MATLAB | 18,775 | 539 | % ========================================================================
%> @class imageStimulus
%> @brief Show images or directories full of images
%>
%> Class providing basic structure for image (texture) stimulus classes.
%> You can control multiple aspects of the image presentation, and scale
%> images to values ... |
e6a8620b5b7e7027b368b6daf0e1434a339706ddf596160ee56041a0cc8cf211 | MATLAB | 18,934 | 493 | classdef SplashScreen < hgsetget
%SplashScreen create a splashscreen
%
% s = SplashScreen(title,imagefile) creates a splashscreen using
% the specified image. The title is the name of the window as shown
% in the task-bar. Use "delete(s)" to remove it. Note that images
% must be in PNG,... |
7ec9c871c98942a7640e9ad10260d4ac0c339e37fd46badafda71e716fccb4c5 | MATLAB | 19,102 | 485 | % =========================================================================
% = CLASSIFICATION PLOTS =
% =========================================================================
function handles = display_classplot(h, handles)
axes(handles.axes1); cla; hold on
switch ... |
8736ca47e9dff75ae42027eaa46275d7208dfbff44a2533935d508027cc0cdf2 | MATLAB | 19,173 | 451 | function [outSummaryPath, odyn] = SummarizeResults(destMatPath, sc)
S0 = load(destMatPath);
try
VT = S0.fars.VT;
catch
VT = S0.VT;
end
samples = S0.samples;
nC = numel(sc);
nS = S0.fars.nSamples;
% ---- Header fields (keep only info derivable or neutral wrt 'stats') --... |
5b57d77b9d08047245dd874bc86979fbd49655e2668f2df9df9e6f87b2ed76eb | MATLAB | 19,192 | 497 | %% STEP1 load data
clc;
clear;
close all;
% 如果需要load不同患者的文件
% filepath = "H:\20240222\figures_k\Unit_info_SU_patients";
% filepath = "I:\930_project\paper_figure\waveform_table\Unit_info_SU\Unit_info_SU_patients\Unit_info_SU_patients_extend";
filepath ='D:\930_paper_plotting\Unit_info\Unit_info\Unit_info_SU_pat... |
41e6cd3e6330b46193c8f1528d51963b12a5dea467be0674bddf689812055f50 | MATLAB | 19,226 | 667 | function fasticag(mixedsig, InitialGuess)
%FASTICAG - Fast Independent Component Analysis, the Graphical User Interface
%
% FASTICAG gives a graphical user interface for performing independent
% component analysis by the FastICA package. No arguments are
% necessary in the function call.
%
% Optional arguments can be g... |
1f9cb15532cf10c7afd0b55dd10189a54d11ce3a4cc241849c8b45da4e217b80 | MATLAB | 19,386 | 447 | function result = csimca(x,group,varargin);
%CSIMCA performs the SIMCA method. This is a classification
% method on a data matrix x with a known group structure. On each group a
% robust PCA analysis is performed. Afterwards a classification
% rule is developped to determine the assignment of new observations.
%
% R... |
9d740ea7a174010d23b348eac815529b6d937a63714176e99b63afcf4b438f79 | MATLAB | 19,416 | 581 | function gui_cb(action)
%
% This file is used by FASTICAG
% This file holds the callbacks to the main window
% @(#)$Id: gui_cb.m,v 1.5 2003/09/10 10:33:41 jarmo Exp $
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Global variables
% Handle to the main figure
global hf_FastICA_MAI... |
05496157d5701a21b295bd3807c652eb25231e557376a2907931bc5ddf8f4c2c | MATLAB | 19,419 | 509 | <<<<<<< HEAD
function save(this,filename,encoding)
% Save GIfTI object in a GIfTI format file
% FORMAT save(this,filename,encoding)
% this - GIfTI object
% filename - name of GIfTI file to be created [Default: 'untitled.gii']
% encoding - optional argument to specify encoding format, among
% AS... |
708671b801e2f1be3af5546c5dad89eda5eff745e41bb65cd5a02979c57236dd | MATLAB | 19,454 | 626 | function PC_bursting(EventTypes,rectype,plot_win)
% PC_BURSTING Spike-phase coupling and bursting index
% PC_BURSTING(event,colors,resdir,chanmean,PC_win)
% -correlates spike-phase coupling measures with bursting index of
% significantly coupled units and of responsive units
% -separates uni... |
93262dcc5c1231da9d4eb366fca6ac035013f0545cd51e761fbbe0739d184078 | MATLAB | 19,523 | 479 | % Preprocessing for drowsiness (long-term and single trial) in BRC
% by poem
% recovered in 2008/6
% clear all;
FilePath = '';
if isunix
mypath;
FilePath = '~/Drowsiness/';
SL = '/';
end
DataFormat = '16';
SET = {
% 's18_060120';
% 's18_060121';
% 's18_060228';
% 's22_060718A';
% ... |
34ffbf2e635d54fa42c2fe61f62c25bb45d36c3614dc3a18363d84d105a58789 | MATLAB | 19,565 | 367 | function [RANK, PX] = nk_Rank_config(RANK, PX, NM, varind, defaultsfl, parentstr)
if ~exist('defaultsfl','var') || isempty(defaultsfl), defaultsfl = 0; end
ranktype = 1;
weightmethod = 1;
label = NM.label;
labeldesc = 'NM target label';
algostr = 'pearson';
act = ... |
9b1b835fa1dc4e2aeb8fa6ee1a8efff821e9da7eaff7539a0b6326fd0e2e5693 | MATLAB | 19,690 | 499 | function [center, Cn, PNR] = initComponents_parallel(obj, K, frame_range, save_avi, use_parallel, use_prev)
%% initializing spatial/temporal components for calcium imaging data
%% input:
% K: scalar, maximum number of neurons
% frame_range: 1 X 2 vector indicating the starting and ending frames
% save_avi: save ... |
9ac7167c20965c02ed4abb27dbfafb49415fa78d4627c670fd40365c02a07ade | MATLAB | 19,724 | 500 | function nm(varargin)
%
% NeuroMiner Startup and Main Interface Function
%
% *******************************************
% ****\ /****
% *****\ ~~~~~~~~~~~~~~~~~~~~~ /*****
% ******\ N e u r o M i n e r /******
% *******\ ~~~~~~~~~~~~~~~~~~~~~ /*******
% *******/ ... |
977fe0d55ae030f32b6393f74a74b0fb3581b43ce8a3bfbcb6e3ddf9281a4bf3 | MATLAB | 19,768 | 574 | % ========================================================================
%> @class imageStimulus
%> @brief Show images or directories full of images
%>
%> Class providing basic structure for image (texture) stimulus classes.
%> You can control multiple aspects of the image presentation, and scale
%> images to values ... |
a6ad8ff214385be8c24d6a6ee4019812d529c604ecfcb2ee98b1d615b84dd831 | MATLAB | 19,783 | 300 | function ProcessedData = plotStatsInEachRegion(AnalysisRegions,InjuryIndicies,ProcessedData,plotProps,sw)
%This function plots the firing count and interval histograms either by
%analysis region or before vs. after treatment based on user preference
%(instead of for the entire recording)
%% Get histogram bins
... |
b749292997a5f69bf65d6fd85543e9fbb8c55c37706dff8b49827fbd4f6a410c | MATLAB | 19,793 | 464 | function result=rpcr(x,y,varargin)
%RPCR is a 'Robust Principal Components Regression' method based on ROBPCA.
% It can be applied to both low and high-dimensional predictor variables x,
% and to one or multiple response variables y. It is resistant to outliers
% in the data. First, a robust principal components meth... |
927c33b1cb454812405ab02d01505bc96eb6be2157936e508c302422ea122e75 | MATLAB | 19,815 | 446 | % ========================================================================
%> @class ImageStimulusTest
%> @brief Class-based unit tests for imageStimulus.
%>
%> Tests construction, property defaults, checkfilePath default image
%> resolution, file path handling, selection indexing, contrast scaling,
%> crop modes, and ... |
6bbc6ddf7501da29a86a2ccafa8d9644f344fe9437f9f0f17cdff9babb6ed516 | MATLAB | 19,849 | 482 | % PRO-SACCADE and ANTI-SACCADE Task (TOUCH SCREEN VERSION)
%
% This task supports both pro and anti saccades and uses 3 stimuli:
% (1) pro-saccade target
% (2) anti-saccade target and
% (3) fixation cross.
%
% TOUCH VERSION: this protocol replaces the eyetracker (eT) with the
% touchManager (tM). Touch windows are used... |
7f2087968c76712e2554646c377d24a01e9a1e507d2eb76e1a1724bea655b0fa | MATLAB | 19,881 | 417 | function [act, analdim, p, GridAct, mapY, strout] = nk_PreprocessPrep( act, analdim, GridAct, p, parentstr)
% =========================================================================
% FORMAT function [act, analdim, p, GridAct, mapY, strout] = ...
% nk_PreprocessPrep( act, analdim, GridAct, p, parent... |
5730fef1ee396b94f99aeaddd0a9ebc444ed3ab269c68cba7219d61ac5fd9d1c | MATLAB | 19,958 | 532 | % ========================================================================
%> @brief logGaborStimulus: orientation & SF band-pass limited filter
%>
%> If you use this in published research please cite "Horizontal information drives the
%> behavioral signatures of face processing" Goffaux & Dakin (2010) Frontiers in Pe... |
0ff4b1eb37765d43953b25e6a142bfd9fe370acd39a691d4606bdad046030949 | MATLAB | 20,020 | 528 | % DR_loadcnt() - Load a Neuroscan continuous signal file.
%
% Usage:
% >> cnt = loadcnt(file, varargin)
%
% Inputs:
% filename - name of the file with extension
%
% Optional inputs:
% 't1' - start at time t1, default 0
% 'sample1' - start at sample1, default 0, overrides t1
% 'lddur' - duration ... |
9c8a520bb4c9dda55025618866638d2ff7373128f41d4620e46a175774e0027a | MATLAB | 20,122 | 566 | %% mRVM1
% authors: Ioannis Psorakis psorakis@gmail.com, Theodoros Damoulas
% theo@dcs.gla.ac.uk
% Copyright NCR, 2009
%
% Use of this code is subject to the Terms and Conditions of the Research License Agreement,
% agreed to when this code was downloaded, and a copy of which is available at
% http://www.dc... |
327ee8baf7cbf7d5c2382f58b9ec3a08aa48a285d4c938ae633b186d75a3b8d2 | MATLAB | 20,187 | 426 | function [mappedA, mapping] = compute_mapping(A, type, no_dims, varargin)
%COMPUTE_MAPPING Performs dimensionality reduction on a dataset A
%
% mappedA = compute_mapping(A, type)
% mappedA = compute_mapping(A, type, no_dims)
% mappedA = compute_mapping(A, type, no_dims, ...)
%
% Performs a technique for dimension... |
f94b8716d7e5395d56f607d5fbb0aa6b763696d97a6fd7dfc7b12aad61b14bf7 | MATLAB | 20,239 | 589 | function handles = plotSpread(varargin)
%PLOTSPREAD plots distributions of points by spreading them around the y-axis
%
% SYNOPSIS: handles = plotSpread(data,binWidth,spreadFcn,xNames,showMM,xValues)
% handles = plotSpread(ah,...)
%
% INPUT data: cell array of distributions or nDatapoints-by-mDistributions
% ... |
fe651c1df021be32934846b03fd98698937b7008965b76af0fdab63f2192eeaa | MATLAB | 20,263 | 511 | function varargout = nk_results(varargin)
% NK_RESULTS MATLAB code for nk_results.fig
% NK_RESULTS, by itself, creates a new NK_RESULTS or raises the existing
% singleton*.
%
% H = NK_RESULTS returns the handle to a new NK_RESULTS or the handle to
% the existing singleton*.
%
% NK_RESULTS('CALL... |
abe4cc477b6ce7f9946260268f5c8bc0e55d4ba515083997eeea1b65e8ea2197 | MATLAB | 20,336 | 510 | function [noise_data refscan_data image_data]=datapack_VE(twix_obj,varargin)
noise_data=[];
refscan_data=[];
image_data=[];
%setting up defaults
file_prot='meas.asc'; %default protocol file name
file_raw='meas.out'; %defualt rawdata file name
flag_debug=0;
flag_debug_file=0;
output_stem='meas';
flag_scan_mdh_o... |
500557db6db4c2532f8bd863cb54e1712b0fe8f4b8b102366f74ff5c9b20763c | MATLAB | 20,341 | 685 | % ========================================================================
%> @brief receptive field mapper
%> rfMapper is a mouse driven receptive field mapper, using various keyboard
%> commands to change the stimulus and and ability to record where the mouse is
%> (i.e. draw) in screen co-ordinates to save as a hand... |
88cfc4d14e725dc6768fe366d97d05fd518b94225555eb0af1dbfb4dc9fe4dba | MATLAB | 20,481 | 599 | classdef timeLogger < optickaCore
%> @brief Log frame timing and event annotations for a task run.
%>
%> The class stores per-frame timing values such as VBL, draw, flip, miss,
%> and stimulus state, together with timestamped messages that can include
%> time type metadata and optional HED annotations. The logged ... |
22650aa1726d41008a89a725a867c301db4f942bef4160f153095d739a967d08 | MATLAB | 20,505 | 396 | clear
%% load file
load('ProcessedData\OutputTable.mat');
load('ProcessedData\InputParameters.mat');
%% Pre-Processing
% any manual trimming of the main table or adjustments
% exmaple to drop to one animal or day
% OutputTable = OutputTable(strcmp('LEC285598', OutputTable.Animal) == true,:);
% OutputTable = Ou... |
fea622719d524ac5d675029b28f55741881d7cb19a3bc9858e4b6dec55d028b9 | MATLAB | 20,546 | 457 | % DOUBLESTEP SACCADE task, Thakkar et al., 2015 Brain & Cognition
%
% This paradigm should be more sensitive to online inhibition than
% anti-saccade.
%
% In nostep trials (60%), after 500-1000ms of intial fixation, a saccade target
% (target one) is flashed for 100ms in one of 8 equidistant positions. In
% step trial... |
630d0ab7ccd5a25f8fd0bd0a5ec212f9a30e3b023ab6e5d52f35829027836fcc | MATLAB | 20,560 | 455 | % DOUBLESTEP SACCADE task, Thakkar et al., 2015 Brain & Cognition
%
% This paradigm should be more sensitive to online inhibition than
% anti-saccade.
%
% In nostep trials (60%), after 500-1000ms of intial fixation, a saccade target
% (target one) is flashed for 100ms in one of 8 equidistant positions. In
% step trial... |
12c3059f358f071fab6951ec9afa89ae4585b84ecdd38e5a67ad3edaa31bd785 | MATLAB | 20,581 | 506 | % =========================================================================
% cv = nk_MakeCrossFolds(label, RAND, ...
% decomposeflag, modeflag, groups, groupnames, ...
% oldcv, appendfl, auto_adjust)
% =======================================================================... |
369e0b78c59f3311f8613c50c31188a65dbeaaaadfa0d16792c1388394b011b2 | MATLAB | 20,641 | 376 | % ==========================================================================
function opt = nk_matLearn_getopts_config(opt, act, algo, param, framework)
if ~exist('param','var'), param = []; end
switch act
case {'get_learners','get_sublearners'}
opt.desc = sprintf('Select %s algorithm fro... |
3dd95f027907c085950398d5ca611eab60581caaacf3036966798c0a967b2d80 | MATLAB | 20,697 | 487 | function result=cda(x,group,varargin)
%CDA performs linear and quadratic classical discriminant analysis
% on the data matrix x with known group structure.
%
% Required input arguments:
% x : training data set (matrix of size n by p).
% group : column vector containing the group numbers of the traini... |
9aee57fab225ff15a2d9eb5cfea40194f06b7d29fbc912daba067250227ef4d3 | MATLAB | 20,705 | 591 | % ========================================================================
%> @brief barStimulus single bar stimulus, inherits from baseStimulus
%>
%> Copyright ©2014-2024 Ian Max Andolina — released: LGPL3, see LICENCE.md
% ========================================================================
classdef barStimulus <... |
fc019cdc72aed60ea23cf86f69fb6f0dd781e80d15ef064f26bef690caadb2bb | MATLAB | 20,919 | 459 | function [ act, NM, inp ] = nk_OOCVPrep(NM, act, inp, parentstr)
% =========================================================================
% FORMAT [act, inp] = nk_OOCVprep(act, inp, parentstr)
% =========================================================================
% Runtime model of independent test data predic... |
fb09838bb15bbaf18d40cc7a5f1f1e9c45e1671e89f80780155f0dc6aa06f353 | MATLAB | 20,958 | 487 | % DELAYED MATCH TO SAMPLE (DMS): The subject fixates a central cross,
% then a sample image appears. After a delay period (maintaining
% fixation only), a choice array of images appears at peripheral locations.
% The subject must saccade to the image matching the sample to receive
% a reward. Distractors are guarded by... |
c57a2b0bcd53a8bd8c4cb64c1df3dc7e86a5293e51dba0a6badf3f4e32e840c4 | MATLAB | 20,971 | 534 | function Hash = DataHash(Data, varargin)
% DATAHASH - Checksum for Matlab array of any type
% This function creates a hash value for an input of any type. The type and
% dimensions of the input are considered as default, such that UINT8([0,0]) and
% UINT16(0) have different hash values. Nested STRUCTs and CELLs are par... |
4e961c16147630113b527ffd097e046be7b5d83ae288ebfffda85debf30a0638 | MATLAB | 20,989 | 635 | % ========================================================================
%> @class JzmqConnectionTest
%> @brief Class-based unit tests for jzmqConnection (ØMQ via JeroMQ).
%>
%> Tests construction/validation, endpoint generation, socket lifecycle
%> (bind/connect types, double-open guard, context ownership on close),... |
129821016f4506fe5332dab38620c2f5d5e934804b9b2d53c47690ebbbba47dc | MATLAB | 21,014 | 688 | function choice = menuN(mtitle, options, Opt)
%% MENUN A modern rewrite of menuN using uifigure and uigridlayout
%
% Syntax:
% choice = MENUN(mtitle, options)
% choice = MENUN(mtitle, options, Opt)
%
% Input:
% mtitle - [string OR cell with 2 elements] - Menu window title and message
% - {'Menu title','M... |
f0cce34b181a265b3dbb9f7d0f96c1cbb62c228fcd5bd886d4a56d255f1b9bb7 | MATLAB | 21,123 | 411 | clear
%% load file
load('OutputTable.mat');
load('InputParameters.mat');
load('Behavior_TraceTable.mat');
%% Pre-Processing
% any manual trimming of the main table or adjustments
% exmaple to drop to one animal or day
% OutputTable = OutputTable(strcmp('NEC273332', OutputTable.Animal) ~= true,:);
% OutputTable... |
d1846a27b76fe4680315a7c5b92a37f2603c5a41a36e163688af937345b698ed | MATLAB | 21,196 | 409 | clear
%% load files
load('OutputTable.mat');
load('InputParameters.mat');
%% Pre-Processing
% any manual trimming of the main table or adjustments
% exmaple to drop to one animal or day
% OutputTable = OutputTable(strcmp('LEC285598', OutputTable.Animal) == true,:);
% OutputTable = OutputTable(OutputTable.Day ==... |
db0d55c54d390d0e3a0bfa3546b425508cdaa0ef369f6d27c8e460753d2fe28d | MATLAB | 21,315 | 441 | %==========================================================================
% [IN, OUT] = FoldPerm(IN, OUT, strout, fRFE, fFull, fKX, LoopParam)
%==========================================================================
% MAIN NM TRAINING MODULE
% FoldPerm manages the logic of model training and optimization at the
%... |
1f3c3b4e36d69c3da154485f6c934613400058e26f5a6464189918b5b8ba10c9 | MATLAB | 21,321 | 581 | function rc = eyelinkCustomCallback(callArgs, msg)
% eyelinkCustomCallback implementes the EyeLink Core Graphics part
% of the EyeLink API. This "Core Graphics" part of our API is responsible
% for handling the times when the API and Host PC takes control of the eye
% tracking procedures. This includes the functionalit... |
6908cdb24066caa1537aaa6188a62888387c6f40fc4468118970680540fc89db | MATLAB | 21,348 | 426 | function varargout = palm_help(varargin)
% Shows a help text. Call palm_help('logo') to show just the logo.
% _____________________________________
% Anderson M. Winkler
% FMRIB / Univ. of Oxford
% Mar/2014
% http://brainder.org
% - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
% PALM -- Permut... |
83c8622376e98673360a3dbd09963a621c0cf55902cbe4894036b8e8babdfe61 | MATLAB | 21,423 | 452 | %> BACK-PROPAGATION -- fast full-screen receptive field mapping for many
%> channels.
%==================================================================
%------------------------General Settings--------------------------
% These settings are make changing the behaviour of the protocol easier. tS
% is just a struct(),... |
1cb5498fa0ca8320704fa032bb2652e66f3653f3aba3d90c3890b71754462658 | MATLAB | 21,493 | 516 | % Preprocessing for drowsiness (long-term and single trial) in BRC
% by poem
% ver 200809
clear all;
FilePath = '';
if isunix
mypath;
% FilePath = '~/Drowsiness/';
FilePath = '~/liang/';
HeadFilePath = '/home/eeglab5.03/eeglab5.03/plugins/dipfit2.0/standard_BESA/'; %.4
SL = '/';
end
hdmfile = [HeadFilePath ... |
dcd91a0f4684cc7ec2c250f50f11817541880e43b07be484873583df8908bd61 | MATLAB | 21,551 | 473 | function data = TDT2mat(tank, block, varargin)
%TDT2MAT TDT tank data extraction.
% data = TDT2mat(TANK, BLOCK), where TANK and BLOCK are strings, retrieve
% all data from specified block in struct format.
%
% data.epocs contains all epoc store data (onsets, offsets, values)
% data.snips contains all... |
53621ff867e691801f3039f5fd7ab9bb6ae8b27594e19c782a5346ef975ec62f | MATLAB | 21,575 | 519 | function result=rsimpls(x,y,varargin)
%RSIMPLS is a 'Robust method for Partial Least Squares Regression based on the
% SIMPLS algorithm'. It can be applied to both low and high-dimensional predictor variables x
% and to one or multiple response variables y. It is resistant to outliers in the data.
% The RSIMPLS algori... |
8d8e8b2faa0ad429e045a26da5b00e95817fbe862eb5e9c271791626b02785be | MATLAB | 21,605 | 440 | %=========================================================================
%-----------------------------General Settings----------------------------
% These settings are make changing the behaviour of the protocol easier. tS
% is just a struct(), so you can add your own switches or values here and
% use them lower dow... |
dd73057f10be5db1303e99b91548b22744325b18b2ce6da75c2841cfde2eb963 | MATLAB | 21,612 | 440 | %=========================================================================
%-----------------------------General Settings----------------------------
% These settings are make changing the behaviour of the protocol easier. tS
% is just a struct(), so you can add your own switches or values here and
% use them lower dow... |
5fd83d858ecbfe4f8ddff3ff82a2a025413fe5343af2835b549d3a3a4e4c19b7 | MATLAB | 21,630 | 445 | %=========================================================================
% This task presents a face vs. object stimulus pairs randomly placed left
% or right of fixation. The subject must initiate fixation, then the
% fixation window encompasses most of the screen to allow free viewing of
% either object or face but... |
17b6a61d879ef678801a1329923ade9c1b6a2de004771b59601acfbe5c4f5380 | MATLAB | 21,788 | 596 | close all; clc; clearvars;
%% CAP analysis for concurrent fMRI and fluorescence data
%
%% Paths
scriptDir = fileparts(mfilename('fullpath'));
if isempty(scriptDir)
scriptDir = pwd;
end
fmriFolder = fullfile(scriptDir, 'data', 'fMRI', 'cleaned');
flFolder = fullfile(scriptDir, 'data', 'FL', 'cleaned', '10Hz');... |
1d151e6e47c53435d3e130f7f407417d2baec193db80c9ecdf3fc0ad5233da9f | MATLAB | 21,815 | 504 | function outputs = stdNDM_mouse(varargin)
% Parameters to fit
% param(1) = seed rescale factor
% param(2) = alpha
% param(3) = beta
% param(4) = s
% Define defaults and set inputs
study_ = 'IbaHippInj';
costfun_ = 'LinR';
solvetype_ = 'analytic';
volcorrect_ = 0;
exclseed_costfun_ = 0;
excltpts_costfun_ = [];
normtyp... |
1dcab45e7f39c7662a2347f36b755572ac4af3ea335b9c8c283a577c5383daff | MATLAB | 21,894 | 549 | % ========================================================================
%> @class stateMachineHSM
%> @brief hierarchical state machine (HSM) with parent/child nesting.
%>
%> stateMachineHSM extends stateMachine to support hierarchical (nested)
%> states. Each state may declare a `parent` field (a state name). A stat... |
1e0912e4cd1274872f71f1dca2dde50a6419870ae2e8cfdfe36e98b84e0a7996 | MATLAB | 21,947 | 604 | % ========================================================================
%> @brief colour grating stimulus, inherits from baseStimulus
%> COLOURGRATINGSTIMULUS colour grating stimulus, inherits from baseStimulus
%> The basic properties are:
%> type = 'sinusoid' or 'square', if square you should set sigma which
%>... |
4691854b1dbe6cadafc32f7a35a0530aeebfe8a36711b32cf64530f096073ea6 | MATLAB | 21,983 | 605 | % ========================================================================
%> @brief colour grating stimulus, inherits from baseStimulus
%> COLOURGRATINGSTIMULUS colour grating stimulus, inherits from baseStimulus
%> The basic properties are:
%> type = 'sinusoid' or 'square', if square you should set sigma which
%>... |
a23556ed02e1f3a633590fad25018ddf4cbbf6cd8c9802188ef59308196f6ab0 | MATLAB | 21,993 | 471 | % DOUBLESTEP SACCADE task, Thakkar et al., 2015 Brain & Cognition
% In nostep trials (60%), after 500-1000ms intial fixation, a saccade target
% (target one) is flashed for 100ms in one of 8 equidistant positions. In
% step trials (40%) after taget one flashes after a delay (target step
% delay, TSD) a second target (... |
3e62623439380187d6d0f0095a6d0eab9eb3e8c779aa5a9f36b2c7443b9b598d | MATLAB | 22,007 | 592 | % timefreq2004() - compute time/frequency decomposition of data trials.
%
% Usage:
% >> [tf, freqs, times] = timefreq(data, srate);
% >> [tf, freqs, times, itcvals] = timefreq(data, srate, 'key1', 'val1', ...
% 'key2', 'val2' ...)
%
% Inputs:
% data = [float array] ... |
d292b37d14f17e235d03b02498083139ff78988c1089bbf25e250178d7fdfbfc | MATLAB | 22,051 | 309 | function handles = load_GDdims(handles, Params, Label, GDdims)
handles.MLparams = []; handles.grid = [];
% Add binary-classification data to handles
if isfield( GDdims,'Model')
handles.MLparams = GDdims.Model;
elseif isfield( GDdims,'MLparams' )
handles.MLparams = GDdims.MLparams;
else
handles.MLparams.Nu... |
0f12d7f96c4c5b21b1b60d974517331442b0b421c79ab06f406c2918eee7df08 | MATLAB | 22,082 | 613 | % ========================================================================
%> @brief polar checkerboard stimulus, inherits from baseStimulus
%> POLARBOARDSTIMULUS inherits from baseStimulus
%> The basic properties are:
%> type = '', 'randdrift', 'spiraldrift', 'sine'
%> colour = first grating colour
%> colour2 =... |
2fb112206cdf9fa0c8ab45588b454d3f5ef28d759035382ccb5b2f5584c073db | MATLAB | 22,084 | 613 | % ========================================================================
%> @brief polar checkerboard stimulus, inherits from baseStimulus
%> POLARBOARDSTIMULUS inherits from baseStimulus
%> The basic properties are:
%> type = '', 'randdrift', 'spiraldrift', 'sine'
%> colour = first grating colour
%> colour2 =... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.