sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
da90e73672a675ea87874a6156bdf0fd5a08a66ff27292291534d6d1a999c42e | MATLAB | 6,014 | 149 | function make_Figure3bcd(plotVariables, options)
subjectListEEG = [16 18:21, 24, 26, 27, 28, 29, 31, 33, 34, 35, 42, 43, 47, 50, 51, 52, 54, 55, 57, 58]; %32 taken out
EEGpreproc = options.path.preproc.behaviour; % path to behav data all subjs
load_name = fullfile(EEGpreproc,'behav_data_all_subjs_all3');
load(load... |
36e18fd19cc56becf3c07216b7aa1669e4ba5e34fe61897adfd7aaf482ae4656 | MATLAB | 6,015 | 144 | function [self] = getBaselineKinematicsEarlyLate(self,border,condNdx,key)
% getBaselineKinematicsEarlyLate calculates the kinematics when flies
% are at baseline firing. This is split into before first entry, the
% first 2 state instances after each exit, and lateral state instances
% after each exit
%
% ... |
519f85772cd58da3785aeca02a8d02665a99f598f7535529ec8204f5a5573076 | MATLAB | 6,015 | 163 | function [mbMask] = ellipse2mask(strType, vnImageSize, varargin)
% ellipse2mask - FUNCTION Make an ellipse mask
%
% Usage: [mbMask] = ellipse2mask('bounds', vnImageSize, [fX1 fY1 fX2 fY2])
% ellipse2mask('majoraxis', vnImageSize, [fX1 fY1 fX2 fY2], fAspectRatio)
% ellipse2mask('ce... |
d29e2bd08f6e1cae85e826439674819aed29c7b3d0c62d1c6c0205dd325adfcf | MATLAB | 6,015 | 182 | function SBJ09b_TFR_plot_stats(SBJ,conditions,proc_id,an_id,plt_id,save_fig,fig_vis)
% Plots TFRs computed in SBJ09a_TFR_stats
% 3 TFRs in a row: (1) con; (2) inc; (3) inc-con with stats
% clear all; %close all;
error('not adapted to stat_id yet');
%% Check which root directory
if exist('/home/knight/hoycw/','dir');... |
39ef07a4b8f8390886959596913940bf119530210477b0430626090e47a7ce9c | MATLAB | 6,016 | 137 | function [new_response_matrix,nResponsesDiscarded] = return_new_response_matrix(observed_stimulus_stream,orig_response_matrix)
%make a copy of the original response matrix
response_matrix = orig_response_matrix;
% Remove all rows of response matrix where choice (3rd column)==2 (get rid of missed trials)
response_matr... |
f5520517ed69305d25a24e586f8ca1c8f3097c209f219bb5e0ba83ba374a7412 | MATLAB | 6,021 | 220 | %% mri_example_3d.m
%|
%| Example illustrating 3D regularized iterative reconstruction for MRI
%| from nonuniform k-space samples.
%|
%| This example does not include field inhomogeneity or relaxation
%| or sensitivity maps. All of those are possible extensions using
%| existing capabilities of MIRT.
%|
% Copyright 20... |
be75e95e8843aacde1ef53e459a76a4c61cb09df25d285a41e88fb09c7633cc8 | MATLAB | 6,031 | 164 | function trigSDFandMI_M2(sesID,tsDir,trigDir,algTrigDir,rrmDir,analDir)
% function trigSDFandMI_M1(sesID,tsDir,trigDir,algTrigDir,rrmDir,analDir)
%
% input:
% sesID session ID
% tsDir path to dir of preprocessed data for RRM
% trigDir path to dir of triggerTimes for (no-)movement ons... |
106657ba9e193bf5fe4bfe81c53505d5c6428863ae3c4b2d5f659c86d3754446 | MATLAB | 6,033 | 181 | function [xY, XYZmm, j] = spm_ROI(xY, XYZmm)
% Region of Interest specification
% FORMAT xY = spm_ROI(xY)
% xY - VOI structure
% xY.def - VOI definition [sphere, box, mask, cluster, all]
% xY.rej - cell array of disabled VOI definition options
% xY.xyz - centre of VOI {mm}
% xY.spec -... |
9d8df86bc654b0fdf2b785409bc8159f3cd7ca6d43a094f277e0f1e5c65c125b | MATLAB | 6,036 | 174 | %% Convert the vessel segments to a graph (nodes + vertices)
%{
This script takes the output of the script ~\vasculature\vesSegment\vesSegment
and then creates a graph.
%}
%% Add top-level directory of code repository to path
% Print current working directory
mydir = pwd;
% Find indices of slashes separating director... |
be5581ca3331e2842c7d6cf04b3324009f648c225422f13baa6e92bb8f81b484 | MATLAB | 6,038 | 162 | function normCSC_data = plot_timeWarpedStabilityScoreCurves(cells)
% Load Params
if ~exist('paramsPath','var')
params = readtable('./UniversalParams.xlsx');
else
params = readtable(paramsPath);
end
samplingRate = params.TimeBin;
ds_factor = params.ds_factor;
secsInMin = 60;
conversionFactor = secsInMin/(ds_f... |
176f063b70d2293aa78a32f186ccc1d7384a52d810084a0cd694c1ad9ff8689a | MATLAB | 6,039 | 184 | %% PANEL FIGURE 3
%Figure description: IC medial prefrontl maps and ERPs from SS v US and
%TFUS (none) 1st row and TFUS (STOP) 2nd row.
%ERP PLOT: Columns are groups (rIFG, S1, and control); Rows are TFUS
%conditions; Color: blue is SS and orange is US
%% Gather IC MAPS and plot central IC
addpath '/Users/user/Library... |
22d7506f6b84ce245ca58198133b0797eb4fbe600f032ecb63dd055c21e0ba8f | MATLAB | 6,039 | 175 | function [] = DataGeneration()
addpath(genpath([fileparts(which(mfilename)) '\matlab']));
addpath(genpath([fileparts(which(mfilename)) '\util']));
s=dir('Videos/*video.ufmf');
filelist={s.name};
for i = 1:length(filelist)
[readframe,~,~,~] = get_readframe_fcn(['Videos/' filelist{i}]);
end
close all
clear... |
de7251eb862ec9fb4c0d26b21e07e115606cc574bf0f081d1f1f3b41db377db2 | MATLAB | 6,045 | 178 | % interactive tps - streamlined version
clear;
close all;
delta = 0.05; %grid size
bounds=[-0.5 1.5 -0.5 1.5];
disp_force = 1;
maxpnts = 30; %Maximum number of control points
[gridrefx, gridrefy] = meshgrid(0:delta:1, 0:delta:1); %define inital grids
[gridholx, gridholy] = meshgrid(0:delta:1, 0:delta:1);
figure(1); ... |
45d491fb0e43656156681715e8d4b5a6cf3cf8ee073eebe48669187144371efd | MATLAB | 6,046 | 190 | function fig3A(analDir,rrmDir,tsDir,figDir)
% function Fig3A(analDir,rrmDir,tsDir,figDir)
%
% plot Fig3A: the spike-density-functions averaged across all the sessions,
% separated by movement and attention condition
% save figure as *fig and pdf
%
% input:
% analDir path to directory of results for model-fre... |
691520e94f9b05ac76309e9e1d5d2f13b80174ef6facc8bc2584fe39c8a257c1 | MATLAB | 6,047 | 246 | function [opt, extra] = vararg_pair(opt, varargs, varargin)
%function [opt, extra] = vararg_pair(opt, varargs, [options])
%|
%| Process name / value pairs, replacing the "default" field values
%| of the opt structure with the user-specified values.
%| This allows flexible argument order and "named arguments" somewhat ... |
b07414b3d0e3ec890b2c7b80ede0fd73f273b0ca6adf0413944e3f6d117fae2e | MATLAB | 6,049 | 160 | function [outData] = TransformPaths(Data)
%% TransformPaths
% Andrea Castegnaro, UCL, 2022 uceeaca@ucl.ac.uk
% Transform all the paths so they are all facing the positive x-axis and
% starting from (0,0). Mirrors all the right turns in the outbound
% so that all paths are left turns.
% Once flipped calculate the OoB pr... |
33e4812eb3866ecacf0fa99b8001f9167cc1177daeacdc45072b813f9d72479d | MATLAB | 6,051 | 147 | function SBJ06b_ERP_plot_stats(SBJ,conditions,proc_id,an_id,plt_id,save_fig,fig_vis)
% Plots ERPs computed in SBJ07a_ERP_stats
% clear all; %close all;
fig_filetype = 'png';
if ischar(save_fig); save_fig = str2num(save_fig); end
%% Data Preparation
% Set up paths
if exist('/home/knight/hoycw/','dir');root_dir='/home/... |
86a274e3372060188d2c17bdc75662c3f3a29dd338190dd1e283a0572c9fb7fc | MATLAB | 6,051 | 204 | classdef spm_file_template
% Text file template engine
%
% Example:
% >> tpl = spm_file_template;
% >> tpl = file(tpl,'myfile','template.txt');
% >> tpl = var(tpl,'TITLE',spm('Ver'));
% >> tpl = var(tpl,'DATE',date);
% >> tpl = parse(tpl,'OUT','myfile');
% >> get(tpl,'OUT')
%____________________________________________... |
0ddf497444939430f0f696cf3d05e0148bec57ca3f07a189ddcc779749c6a96b | MATLAB | 6,064 | 133 | function [significantVarWei,significantVarMax,pValWei,pValMax] = rsa_weighted_cluster_perm_stats(subjects,rdm_cat_flattened,rdm_dis_flattened,true_correlation,tail,if_save,numPermutations)
%RSA_WEIGHTED_CLUSTER_PERM_STATS Perform weighted cluster permutation stats to calculate the
%significance of the timepoints for th... |
9063077f45be467b04b74b8d38bc948000d9b0607eee6f319c2c875e1e180934 | MATLAB | 6,066 | 150 | function SBJ08a_corrRT_regressRT_ANOVA_terms(SBJ,an_id,stat_id)
%% Run ANOVA with potential RT regression before
% Set up paths
% Set up paths
if exist('/home/knight/hoycw/','dir');root_dir='/home/knight/hoycw/';ft_dir=[root_dir 'Apps/fieldtrip/'];
else root_dir='/Volumes/hoycw_clust/';ft_dir='/Users/colinhoy/Code/Apps... |
7c08020467394fe4af7c87e87a75915ae7ebb4c67ca4ebedaffc8fb6f284588f | MATLAB | 6,070 | 175 | %% Manually scoring the participants trajectory
% In order to the model to fit the data the participant had to demonstrate
% a clear intention of completing the triangle.
% This did not happen all of the time and therefore we had to exclude some
% data. Also we noticed by looking at the tracking data that participants
... |
a0fd0497c81be6a293c1f06f2732e0e445b639c7be613adc91e2f23f34ec0c96 | MATLAB | 6,071 | 188 | % Code responsible for generated the expression versis PI data displayed in "Ciliary
% localization of a light activated neuronal GPCR shapes behavior", PNAS,
% 2023
% Written and annotated by Krisha Aghi and Amy Winans
% Sections 1.1 and 2 by KA, sections 1.2 and 3 by AW
%% Run this first
close all
clear al... |
5d5c6916cd4ae7a8900fe9ebc0060b2587d522a504c893f235a898347a59c679 | MATLAB | 6,073 | 160 |
function [Best_pos,Best_score,CHIO_curve]=ICHIO(SearchAgents_no,Max_iteration,lb,ub,dim,fobj) %¿ªÊ¼ÓÅ»¯
if(max(size(ub)) == 1)
ub = ub.*ones(1,dim);
lb = lb.*ones(1,dim);
end
PopSize=SearchAgents_no;
MaxAge = 100;
C0 = 1; % number of solutions have corona virus
M... |
8324bd98cec3217240ded4469f8b72061adfd8409966fd92329822e9d569dbe5 | MATLAB | 6,079 | 269 | function ob = fatrix2_vertcat(blocks, varargin)
%function ob = fatrix2_vertcat(blocks, [options])
%| vertcat: B = [A1; A2; ...]
%|
%| in
%| blocks {cell} cell array of the (fatrix2) blocks
%| all blocks must have same idim and imask
%|
%| option
%| 'dim_cat' dimension along which to concatenate odims
%| all other ... |
a3b28a24811672545f2049eff607a96712fded35b46612c8a44ef1fd4934d12a | MATLAB | 6,085 | 139 | function [nll_pair,nll_ind,pfit_pair,gof_pair,gof_ind,gof_diff] = fitRogCrfNFoldCv(nFold,spikes,cont,mu_eta,cov_eta,optional)
%% fitRogCrfNFoldCv N-fold Cross Validated Fit for the Ratio of Gaussians model using the contrast response function parametrization. Fits both the pairwise and independent models.
% INPUT
... |
a7b18872fcc5d8684f98b6c97ca4f46a15084d52c6ba1dbd53de8b8d9e3d3ca4 | MATLAB | 6,087 | 146 | function handles = updateWire(handles)
%%%%% Start: Recalculate Wire Image
%---- Start: Reset Previous Version Marker
handles.editVariables.previousBackupState = 0 ;
%---- End: Reset Previous Version Marker
%---- Start: Create Vectors Necessary for Proper Neighbor Tallying
row = handles.basePic.ySize;
col = ... |
c3d8a7db5c27a5b9d77d5d64376d83f08289a1e9df546f19edfa9f17dd16e1b2 | MATLAB | 6,088 | 162 | function make_figure7(plotVariables,options)
glmFlag = 'vertical_jumps_absolute';
% subject list
subjectList = [62:64,66,68,70]; % vertical motion only
csdFlag = 0; % 1 for csd transformed data
if csdFlag %temporary fix for bug in first subjects' CSD transform
subjectList(1) = [];
end
reference = 'LMRM';
nS =... |
e16b58ba3c0361fff7fed720f189a4df403a4b2495b6f70a8707410ba26cac4f | MATLAB | 6,093 | 199 | %% PSD on Raw Data during HLL and BR
% ########################################################################
% Steps:
% 1. Load Raw Data
% 2. Perform PSD using IRASA
% 3. Save PSD for each subject
% ########################################################################
%%
clear
ft_defaults
%% Subjects
% ID 1... |
1582b18171c43486055f679d6d5822241f254c781b90e46eeaaa22713b9d0aa3 | MATLAB | 6,094 | 160 | %% Regular wave score
clear all
close all
rec_data_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath='C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
save_data_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
clusters=10;
mice_number=12;
mice=['L08M1';'L08M2';'L08M3';'L08M4';'L09M1';... |
75b8c309b0c4dee9860a5ad03e6a70fa59008e57df3e6823d902860baeae89e4 | MATLAB | 6,095 | 185 | function [xBF] = spm_get_bf(xBF)
% Fill in basis function structure
% FORMAT [xBF] = spm_get_bf(xBF)
%
% xBF.dt - time bin length {seconds}
% xBF.name - description of basis functions specified
% 'hrf'
% 'hrf (with time derivative)'
% 'hrf (with time and dispersion deri... |
ef95782ff8e706166a97eb58859fd18798c626557d0ced2725aa2dd26f3ecb21 | MATLAB | 6,095 | 227 | function [sino, orbits, used] = rebin_helix(cg, ig, proj, varargin)
%function [sino, orbits, used] = rebin_helix(cg, ig, proj, varargin)
%|
%| A single-slice rebinning (SSRB) method for cone-beam tomography data
%| collected with a helical source trajectory.
%|
%| in
%| cg ct_geom()
%| ig image_geom()
%| proj [ns ... |
43c0b0832016669a3a0a03b224409e8a5aa5b2895fae1aa79f32c9cfb0dc56e5 | MATLAB | 6,097 | 161 | function [classification, pca_r, knn, clusterMap, mv, tmdMap ] = spectralSpatialMV(model, hsCube)
% SPECTRALSPATIALMV Performs spectral-spatial classification.
%
% [classification, pca_r, knn, segmentation, mv, tmd] =
% spectralSpatialMV(model, hsCube)
%
% This function takes a hyperspectral data cube (hsCu... |
0f5b4a83ff020a1ba78c24e4446e8bda25594ca559ef52ac2e776c8a161a438f | MATLAB | 6,098 | 192 | function [r,err] = mTRFevaluate(y,pred,varargin)
%MTRFEVALUATE Evaluate the performance of a regression model.
% R = MTRFEVALUATE(Y,PRED) returns the correlation between the predicted
% output of a regression model PRED and the ground truth Y, based on
% Pearson's linear correlation coefficient.
%
% If Y or PR... |
3d5c39f07979d9364a6404271f29c756ab5c758de2b7d660505c4433a09cb44a | MATLAB | 6,103 | 250 | % xiayq @ 12/01/2022
% xiayq0121@zufe.edu.cn
% refered to Z. Yao and Y. Xia, Manifold Fitting under Unbounded Noise, arXiv:1909.10228
clear; %clc
% parameters for data
D = 3;
NumTrials = 20;
a = 2/3; b = 1/3; tau = b;
sigma = 0.01; % 0.04
n = 500;
%% hyper parameter
if n == 500
switch sigma
case 0.09
... |
0d25b6226cace788baedb8d829786099289e65ef8d0f8131a73e1ca06b53337f | MATLAB | 6,110 | 130 | function [patch_Vrange, patch_Irange, numtoelim, spikevoltage, spikeiter, spikeelectrode] ...
= burst_wc(thesespikes,fileloc,chunknum,filtereddata,chunksize,spikevoltage,spikeiter,spikeelectrode)
%rename inputs
filtchunk = filtereddata;
chunkN = chunknum;
rawfileloc = fileloc;
chunkspikes = thesespikes;
... |
39ef012c27ad64d2869a0dccb80722be48be2d3886a892f4a076d09fb3101bc6 | MATLAB | 6,111 | 189 | function im = nodeGrps_vesSegment( nodePos,nodeEdges )
%%%%%%%%%%
% TO DO:
% correct eLen (segLength) to be in um (non-cubical voxels problem) - easy
% correct segDiam to be in um (non-cubical voxels problem) - more
% complicated - we already have calculated diameters in imView in voxels
%%%%%%%%%%
% if ~isfield(im,... |
b6301e51424263f75e5f2959474941f4e43baae58a4d392cdfce4bf7d83cc530 | MATLAB | 6,115 | 191 | function [fNum,stateFigure] = plotTurnOpt2(f_orcoAll,state2Cons,tim2Cons,plotType,...
colortype,plotAdaptation,plotInterp,fNum)
k=ones(1,numel(state2Cons));
nGen_per_page = 3;
nPage_all_gen = ceil(numel(f_orcoAll)./nGen_per_page);
fNum_byState = fNum:nPage_all_gen:numel(state2Cons).*nPage_all_gen;
nGen = nu... |
beb9c5d1ed424ac7e8e1e075cea78a3cd00d54e4dd301b86db894e3eb1ec6fdb | MATLAB | 6,119 | 193 | function [Dvol,I]=check_ROI_dir(Dirname, th_pval)
%
% For all the subjects in a directory:
% check if the size of 20 ROIs is within the normal range
% The 20 following ROIs are checked: Left-Lateral-Ventricle Right-Lateral-Ventricle
% Left-Hippocampus Right-Hippocampus Left-Thalamus-Prop... |
d26ffc7711ccc343207d9f9d2526b22876629b92ba412c23a61d75b355265a2f | MATLAB | 6,120 | 170 | %% Convert the vessel segments to a graph (nodes + vertices)
%{
This script takes the output of the script ~\vasculature\vesSegment\vesSegment
and then creates a graph.
%}
%% Add top-level directory of code repository to path
% Print current working directory
mydir = pwd;
% Find indices of slashes separating director... |
6db8eec51793294b5f154487af100f869ae401b0fa8972719eab5f68b66e9f9d | MATLAB | 6,123 | 166 | function [M, I] = permn(V, N, K)
% PERMN - permutations with repetition
% Using two input variables V and N, M = PERMN(V,N) returns all
% permutations of N elements taken from the vector V, with repetitions.
% V can be any type of array (numbers, cells etc.) and M will be of the
% same type as V. If V is ... |
17b9ce65096c45e28905f903d23203d8f481cfa125c7674bd83bb1b44292b4f0 | MATLAB | 6,127 | 176 | %% --- Generate functional connectivity profiles and estimate initialization parameters
% Adapted by M.-Y. Wang, 16-Nov.-2022
%% 1.initial parameters
clear all
clc
project_dir ='/Users/wang/Desktop/Research_projects/BBSC/Functional/Parcellation/1_generate_profiles_and_ini_params';
cd (project_dir)
addpath(genpat... |
5a3aa1622bf6001f271cb24a99be4eabbe6edfeb0525b62e307369e6825f7f60 | MATLAB | 6,128 | 192 | function[]=ref_vol_stitch(id,datapath)
% mosaic parameters
Xsize=1000;
Ysize=1000;
Xoverlap=0.15;
Yoverlap=0.15;
% add path of functions
addpath('/projectnb/npbssmic/s/Matlab_code/PSOCT_code');
addpath('/projectnb/npbssmic/s/Matlab_code/ThorOCT_code');
addpath('/projectnb/npbssmic/s/Matlab_code/NIfTI_20140122');
%% ... |
21a0c83d14d0335e070a76e445182f6861d813dac0dd72ca3f5a04581797c402 | MATLAB | 6,129 | 155 | function SBJ08h_HFA_plot_grp_mLME_cat_recon(SBJ_id, proc_id, an_id, model_id, stat_id, cat_id,...
atlas_id, roi_id, rcn, varargin)
%% Plot a reconstruction with electrodes colored according to statistics
% This version uses categories based on EpnRPE model
% INPUTS:
% SBJ_id [str] - ID o... |
1b4005a89d4e2c8c990db8f2bba491ed181b6bc5635558155eb5695070c83454 | MATLAB | 6,135 | 123 | % LAP DECODING ERRROR
% MH, 05.2020
% Based on van der Meer et al(2017,Hippocampus). Optimizing for Generalization in the Decoding of Internally Generated Activity in the Hippocampus
% Calculate track decoding error by calculating the error for each lap and then averaging. Each lap is decoded using the ratemaps of all ... |
a8b0416e319e26c4f289b5f8d41d1eb59779fb2edd459e05aadd295dac7104dd | MATLAB | 6,135 | 138 | function [input_graph, varargout] = fun_graph_pruning_internal_short_hairs_masked(input_graph, th_hair_length, internal_offset, ep_not_to_ind)
% fun_graph_pruning removes all the short links that connected to
% internal endpoints from the graph
% Input:
% input_graph: structure, generated by fun_skeleton_to_graph
% ... |
ea05105fbcecb51c2732489da6d4cb5abed7ab95164d8012cf34c8446506c859 | MATLAB | 6,141 | 125 | %% CP24 Processing Variables
[root_dir, app_dir] = fn_get_root_dir(); ft_dir = [app_dir 'fieldtrip/'];
if isempty(strfind(path,'fieldtrip')); addpath(ft_dir); ft_defaults; end
%--------------------------------------
% Basics
%--------------------------------------
SBJ_vars.SBJ = 'CP24';
SBJ_vars.raw_file = {'... |
e5ea28427bf1e3c580dd8f91ccc444bde1c80c95e593d5135f3bc9ed658413a2 | MATLAB | 6,143 | 163 | function Optical_fitting_TDE(co, cross, s_seg, z_seg, datapath)
% Fitting code for the data shared by Hui.
% I: volume data for 1 tile
% s_seg: slice number
% Z_seg: tile number
% datapath: datapath for original data
% zf: focus depth matrix, X*Y dimension
I=sqrt(co.^2+cross.^2);
cd(datapath);
opts = optimset('Display... |
01fc8391a3dd226f0aea311620b492a69337b78ad4bfe6674a785fcf4b8d7986 | MATLAB | 6,149 | 201 | function [isValid, validatedMesh] = c_mesh_isValid(mesh,varargin)
% c_mesh_isValid - checks if a mesh struct is valid
%
% Mesh must at minimum specify vertices and face/volume elements. Other fields are optional
% E.g.
% mesh.Vertices: [N,3] matrix
% mesh.Faces: [M,3] matrix for triange surface mesh
% (or mesh.Eleme... |
b36b8afbe3d7f9bea092d90ff3cd9122c2f7a7884012f11bb0d53c522b2d2cea | MATLAB | 6,153 | 179 | function plot_topography_searchlight_dth_ak(subjects,task_distance,task_RT,with_stats)
%PLOT_TOPOGRAPHY_SEARCHLIGHT_DTH_AK Plot the distance-to-hyperplane searchlight results
%at peak.
%
%Input: subject IDs, task_distance and task_rt (1 for categorization, 2 for distraction),
%with or without stats (1/0)
%
%Output: on... |
4aec4006e42768b59577bbb70a92480da58c9c3b0e71c042a15eebac50fc8191 | MATLAB | 6,154 | 166 | function PlotAllFiguresSynth(genAll,meta,currDelay,currDur)
cond = ['_CWdur' strrep(num2str(currDur),'.','') ...
'_CWdelay' strrep(num2str(currDelay),'.','')];
plotFolder = char(meta.syntheticPlotFold);
%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% plotting... |
ed55a0ac783e6ab27f96b08a8956d20c761b921225df70cc3c9ae05225a63438 | MATLAB | 6,155 | 186 | clc;clear;close all
root='..\';
addpath(genpath([root,'NeuralCorrelateEvidenceAcc']))
%%
rootpath='..\dataset\Mice\spike\result\';
rootpath2=[rootpath,'total_clusterArea_paper_results_kernel_0\'];
selectivePath=[rootpath2,'_auroc\selectiveUnits\'];
firingRatePath=[rootpath,'total_clusterArea_paper_results_kernel_0\_Fir... |
6cdb21382403a4dd87ee637a5daf5af9ebab9529c5313443676605ab2323d696 | MATLAB | 6,158 | 208 | function [SharpCurv,CurvTrack,err2] = modelCurvedWalks(s,curv,Cstarts,Cstops,pltInf)
% This function takes start and end positions of sharp turns and creates an
% model of the track using sharp turn and curved walk abstractions
%
% Inputs:
% s: Cell array with s.x and s.y (x and y positions of each track)
% curv:... |
9a2972ba9d7172301974454f108d6b16c1f581d887471d6a1bc0afb6179df7c9 | MATLAB | 6,159 | 162 | function [str, tag, cind, ccnt] = gencode_item(item, tag, tagctx, stoptag, tropts)
% function [str, tag, cind, ccnt] = gencode_item(item, tag, tagctx, stoptag, tropts)
% Generate code to recreate a generic item. This code should be suitable
% for all derived classes. Derived classes that add their own fields should
% ... |
358da39219511684c4d8b9d9ec85274530226076de51d0c508296a05646959b0 | MATLAB | 6,167 | 124 | %% IR85 Processing Variables
[root_dir, app_dir] = fn_get_root_dir(); ft_dir = [app_dir 'fieldtrip/'];
if isempty(strfind(path,'fieldtrip')); addpath(ft_dir); ft_defaults; end
%--------------------------------------
% Basics
%--------------------------------------
SBJ_vars.SBJ = 'IR85';
SBJ_vars.raw_file = {'IR85_erro... |
bb5e0891994063e3d2984077973d0eeb18c458d27c65b53b1e07d8bd21e9aa49 | MATLAB | 6,169 | 218 | function hdr = load_nifti_hdr(niftifile)
% hdr = load_nifti_hdr(niftifile)
%
% Changes units to mm and msec.
% Creates hdr.sform and hdr.qform with the matrices in them.
% Creates hdr.vox2ras based on sform if valid, then qform.
% Does not and will not handle compressed. Compression is handled
% in load_nifti.m, which ... |
6b826730cf89a0c7ade8462a21674b59ff4ea3a756d9062a52eee060d8856231 | MATLAB | 6,170 | 134 | %Generates the spike matrix
clear all
dini_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
snr_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\SNR_H\SNR_flavio_new_L8\';
spath = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
mouse='L8M2'; %Name of the animal
thr_SNR=4;
res=1.5;
count=0;... |
18f188a2717b661ec860a8856a279977c751284171694fe8c0a8adfd7ec75261 | MATLAB | 6,187 | 178 | function labels = spm_vb_graphcut(labels,index,I,W,depth,grnd_type,CUTOFF,DIM)
% Recursive bi-partition of a graph using the isoperimetric algorithm
%
% FORMAT labels = spm_vb_graphcut(labels,index,I,W,depth,grnd_type,CUTOFF,DIM)
%
% labels each voxel is lableled depending on whihc segment is belongs
% index ... |
1d3868e149a9d4ed839c4e83a60bd0c46205e42ec39fcffdb36ad6d83ac322d1 | MATLAB | 6,189 | 213 | % Execute a toy pulse design problem to illustrate fast small- and
% large-tip-angle parallel RF pulse design.
% The key objects used here are Gmri_SENSE (small-tip) and
% Gocrf (large-tip).
%
% Copyright 2009-3-17, Will Grissom, Stanford University
% (based on work he initiated at University of Michigan)
% modified sl... |
7cb63211269e6c59025e9e37d16dfad86a183e8c7f1feb8e336be86b7ef14ed0 | MATLAB | 6,194 | 171 | %% Script to check the age and education difference in MCI+ and MCI-
% Zilong Ji, UCL, 2022 zilong.ji@ucl.ac.uk
% Preparing the data
GLAMPI_PrepareBaseConfig
% Preprocessing the data
GLAMPI_PreprocessData
%load('Data/HowettBrain2019_Dataset.mat');
%%
ColorPattern;
MCINeg_ID = {'A093863_13', 'A093863_35', 'A093863... |
ee6ed62d0f2ab8ea1152520dfe31072a05588351cb88f6df0e2f3960a1ddaedd | MATLAB | 6,194 | 162 | function population_vector_analysis_figure
% POPULATION VECTOR ANALYSIS FOR OVERALL PROTOCOLS AND FOR PROTOCOL SEPARATE
cd 'X:\BendorLab\Drobo\Lab Members\Marta\Analysis\HIPP\Chapter 1\Population_vector_analysis\figures\PPV_shuffles_RAW-PlField_BAYESIAN'
overall = openfig('Shuffle vs Real Cummulative frequency distr... |
aea300fc89c6d15781ccca714453fcd3445e3a23d31a6a3e4c1f2d71d7d5eee9 | MATLAB | 6,195 | 167 | %% Compare Freesurfer summaries of MRIs
%
% Vinding, M. C., & Oostenveld, R. (2022). Sharing individualised template MRI data for MEG source reconstruction: A solution for open data while keeping subject confidentiality. NeuroImage, 119165. https://doi.org/10.1016/j.neuroimage.2022.119165
%
% Read Freesurfer output st... |
d179e0dfc34ecaf8e4450e6aa8eaa579b2dfe4eadff1eaf8419badc5f0592ecf | MATLAB | 6,198 | 221 | function matrixCalculation(calibrationResults,row, col,val)
% This function is used in conversionMatrixCreator_Human and conversionMatrixCreator_Birds
% to process the resulting tracking data in a way that it can be used later
% by getMouseTracking
%
% INPUTS
% * calibrationResults : output from dotPresentationBirds... |
5bca4c93ed17de3ca1adfbd0a8ce7289382e21014f9f27ff1c6b3c85e094c200 | MATLAB | 6,199 | 157 | % Loads in all the trained concatenation models from `semantic_master_modelling_concatTasks_repo.m`
% Calculates various group and group*task stats
% Model comparison
%
% Matthew Nour, London, 2021
clear
close all
clc
% --------------------------------------------------------------------------
% Paths
%--------------... |
6981cea9e870ea4c8170f4a0e47ef409bfb6f653c434ee2a9dca2a52402b2960 | MATLAB | 6,199 | 232 | function [arclen,seglen] = arclength(px,py,varargin)
% arclength: compute arc length of a space curve, or any curve represented as a sequence of points
% usage: [arclen,seglen] = arclength(px,py) % a 2-d curve
% usage: [arclen,seglen] = arclength(px,py,pz) % a 3-d space curve
% usage: [arclen,seglen] = arc... |
d8b54d57c2aeb944ec168c411238501bea9210171c23db9adae9854a15132d9a | MATLAB | 6,200 | 200 | function err = MRIwrite(mri,fstring,datatype)
% err = MRIwrite(mri,fstring,datatype)
%
% Writes an MRI volume based on the fstring. fstring can be:
% 1. MGH file. Eg, f.mgh or f.mgz
% 2. BHDR file Eg, f.bhdr. Result will be written to a bfloat
% volume, eg f_000.bfloat.
% 3. NIFIT file, Eg, f.nii, f.nii.gz (unco... |
33b36ab9e33596642a7012e4895aa138fc6e51647becffa7980057f0ff839756 | MATLAB | 6,206 | 230 | % hole_example1.m
%
% 2D example showing the "hole in sphere" effect for OSEM SPECT
% and various regularization methods that may help overcome it.
%
% Copyright 2004-5-13, Jeff Fessler, University of Michigan
if ~has_aspire, return, end
if ~isvar('A0'), printm 'generate system matrix'
f.dir = test_dir;
f.dsc0 = [f... |
4c627810102ba1f92589fab104cc35e51b9cb1452cfbefa7eb555fe87442e684 | MATLAB | 6,210 | 124 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% generating lipofuscin distribution based on 2PM images
% using channel2 of 2PM
addpath('/projectnb/npbssmic/s/Matlab_code/fitting_code');
addpath('/projectnb/npbssmic/s/Matlab_code/PostProcessing');
addpath('/projectnb/npbssmic/s/Matlab_code/PSOCT_code');
addpath('/projectn... |
57fe801b5ee5f9aa5cf01c27d133875422c25592e773bc891aee3ed97451fb5a | MATLAB | 6,210 | 171 | function c=segregate(d,varargin)
% segregate - extracts synchronous start and end points of fields/spike events
% c=segregate(d,varargin) Reads through spike data and extracts
% start and end points of fields/spike events coherent on all
% channels.
%
% Following 'segTime', the maximal allowed intervall in ms
... |
e4c73bec052fb2c5e5bd79d4897c4638155ac3db425cd47f591c8f0a2c43279f | MATLAB | 6,211 | 166 | function fn_elec_compile_man_reref(SBJ,proc_id,view_space,reg_type,atlas_id)
%% Compile manually adjusted ROI and tissue info (adjust for BP reref)
% Main logic is by fn_combine_ROI_bipolar_logic
% INPUTS:
% SBJ [str] - name of subject
% proc_id [str] - name of analysis pipeline
% view_space [str] - {'pat','mni... |
cd0fd1752aa25fa00c9e4c4c628ca29f916e724412be242907440a4257fea43c | MATLAB | 6,214 | 153 | function Optical_fitting_Hui_SupFrontal(ref, s_seg, z_seg, datapath)
% Fitting scattering and retardance of brain tissue
% co: volume data for co pol
% cross: volume data for cross pol
% s_seg: slice number
% Z_seg: tile number
% datapath: datapath for original data
cd(datapath);
opts = optimset('Display','off... |
8c55e266a30077bd765510b727c3753de5eb0dd12b71b4bdaf293a2b21bb9b55 | MATLAB | 6,216 | 153 | function Optical_fitting_Hui_0530(ref, s_seg, z_seg, datapath)
% Fitting scattering and retardance of brain tissue
% co: volume data for co pol
% cross: volume data for cross pol
% s_seg: slice number
% Z_seg: tile number
% datapath: datapath for original data
cd(datapath);
opts = optimset('Display','off','Tol... |
22eb4d9d82d7148e55263b3a29a679b1807840a25bec643c5089ba9d6cd145f4 | MATLAB | 6,217 | 145 | %% Thomas_Yang_et al, 2023 @Nuo Li lab
%% Fig. 4c norm. FR, SC photoactivation, ALM record
clear all
close all
addpath('../func/')
load Figure_4_c_data
sig_selective(isnan(sig_selective))=0;
FR_pref = spk_count_yes_screen-spk_count_no_screen;
i_selective = (sig_selective(:,2)) & cellType_all(:,1)=... |
d0a2b0c38a0df64a6828dc9e192c40f3f35a558d76d042b6e417da6d8620afb7 | MATLAB | 6,221 | 180 | function [cond1,cond2,cond3,cond4, cond5, cond6] = GetCondData(subj,exp_type, lock, DS, fn_nm, ref)
% output: trial data in time domain for each condition
% go to ptnt dir
cd(['/mnt//yassamri/iEEG/sandra/subj_' subj])
% load trial data
if strcmp('yes',DS)
load(['trial_data_subj_' lock '_' subj '_ref_' ref '_selec... |
13117a1e23bf961afd7acff356973b35278e59ffd51daa3dd6de577dd884e6fd | MATLAB | 6,223 | 206 | function [xs, precon] = eml_osem(x, Gb, yi, ci, ri, varargin)
%function xs = eml_osem(x, Gb, yi, ci, ri, [options])
% E-ML-OSEM algorithm for image reconstruction from Poisson emission data
% (ordered subsets expectation maximization)
% model: Y_i ~ Poisson(c_i [G x]_i + r_i)
% in
% x [np,1] initial estimate
% Gb [nd,... |
5f1dd064bc60ef9d4622a940b2999cba3946b15ac8dda99ccb80144dd7e408dc | MATLAB | 6,223 | 135 | function [Class_results_merged,Class_results_category,predictResults] = NuCLearPRED(model,classNet,ClassDef,predictResults,VarNam)
% Run prediction for each nuclei for each model
predictResultsOrig = predictResults;
for xx = 1:size(model,2)
nmx = model(xx).split(".");
nmx = nmx(2);
if ClassDef(st... |
ad8306b7ec62a182eacb997bce15b4d0a4e61c9ab79d0f8be71277cf7a58d19d | MATLAB | 6,225 | 139 | % INFER_STRUCTURE Infers the structure of MRF of binary variables based on samples
%
% Input
% samples: logical matrix where each row is a sample and each column a node
% lambda: regularization factor
% options:
% 'graph_build_method': ['and', 'or', 'average', 'raw']. How to conciliate
% the fact... |
38bd91d673d3e4835c168cdaf659803338a20014d59f635169c1d6ed944662ed | MATLAB | 6,226 | 191 | % Load NIFTI or ANALYZE dataset, but not applying any appropriate affine
% geometric transform or voxel intensity scaling.
%
% Although according to NIFTI website, all those header information are
% supposed to be applied to the loaded NIFTI image, there are some
% situations that people do want to leave the origi... |
be26a3f66054355b1005800d8caa30c67b4c6f89239823f7dd0a6452a9477291 | MATLAB | 6,229 | 148 | function figurehandle= errorfill(x, y, varargin)
% Usage: figurehandle= errorfill(x, y, E1, E2, ..., LineSpec)
%
% Use this function to draw a curve and its areas of confidence.
% Draws the line y(x), then draws the areas E1(x), E2(x), ...
% (Well actually it's done in the opposite order, to minimize overlap.)
... |
e2b5c14c878c5656eb136600d6273677eae6b07096b9b39492dd60306240a10b | MATLAB | 6,241 | 153 | function Optical_fitting_Hui_0415(ref, s_seg, z_seg, datapath)
% Fitting scattering and retardance of brain tissue
% co: volume data for co pol
% cross: volume data for cross pol
% s_seg: slice number
% Z_seg: tile number
% datapath: datapath for original data
cd(datapath);
opts = optimset('Display','off','Tol... |
f28923e994b7388c124cfd8f03aca897d4b9799af42a93730bb5dad2fcf370f0 | MATLAB | 6,241 | 152 | ROI_list={'M2L1.tif', ... %Secondary Motor Cortex - Left Hem.
'MBL1.tif', ... %Primary Barrel Cortex - Right Hem.
'MFL1.tif', ... %Retrosplenial Cortex - Left Hem.
'FLL1.tif', ... %Forelimb Associated Motor Cortex - Right Hem.
'HLL1.tif', ... %Primary Barrel Cortex - Left Hem.
'BCL1.tif', ... %... |
09712da140c6e8fd7021dec15c95bc93d29ca022fb19ca7f105c0f87c823cafe | MATLAB | 6,242 | 144 | %% Travelling Salesman Problem
% Adapted from the TSP Example, Matlab Optimization Toolbox (https://mathworks.com/help/optim/ug/travelling-salesman-problem.html)
% by Santhanakrishnan Narayanan (n.santhanakrishnan@gmail.com)
% Use this code to solve both symmetrical and asymmetrical TSPs based on binary integer progra... |
6fa6adcaa6df325aa4f7ec7009d2baabc64ff9cbed7fa4ba237f3cfc33509f1f | MATLAB | 6,243 | 167 | % Determine PREICTAL Recruitment Times - Individual traces
%this script takes a matrix of calcium traces (cells by row, time by column)
%and a vector of seeds time for an event (e.g. pre-ictal spikes) and finds
%the point of recruitment by finding where the integral of first deriviate of
%the trace is largest (select... |
3a14c01f3a2df6f78c8314c92b01dce0a597300b792a627b4bbf2480b888f806 | MATLAB | 6,246 | 157 | function Optical_fitting_Hui_0505(ref, s_seg, z_seg, datapath)
% Fitting scattering and retardance of brain tissue
% co: volume data for co pol
% cross: volume data for cross pol
% s_seg: slice number
% Z_seg: tile number
% datapath: datapath for original data
cd(datapath);
opts = optimset('Display','off','Tol... |
bafcc7cf2b5c55162c88e4343a07656e729f09486f7c94bf651d2934d6cebe1a | MATLAB | 6,246 | 142 | function [timing] = control_fixation (dat, display, timing, radius, duration)
fprintf('fixation control\n')
%% get fixation radius
rad=angle2pix(display, radius);
%% get fixation information for every whole trial
% NaN out the interpolated data, because this obscures the fixation
% det... |
d5a7f08ed19bfc6112a0c922a4c276e58aa1b01b16461dc6a105861fde50e778 | MATLAB | 6,246 | 144 | %% Thomas_Yang_et al, 2023 @Nuo Li lab
%% Fig. 5b norm. FR, SC photoactivation, ipsi ALM record
clear all
close all
addpath('../func/')
load Figure_5_b_data
sig_selective(isnan(sig_selective))=0;
FR_pref = spk_count_yes_screen-spk_count_no_screen;
i_selective = (sig_selective(:,2)) & cellType_all(:,1)==1 ... |
d6ff5b3448121bae60a7033a00198b12adde9c06ff5c636cb89a54e9bb9de3c9 | MATLAB | 6,249 | 178 | function EEG = c_EEG_addEvents(varargin)
p = inputParser();
p.addRequired('EEG',@isstruct);
p.addParameter('events',struct(),@isstruct);
p.addParameter('eventLatencies',[],@c_isinteger); % in indices (assume non fractional indices, though could remove this restriction)
p.addParameter('eventPositions',[],@isnumeric);
p... |
5146ffb032735394fbb153236131f4797e7066f397638a5ff62a3a04e8ed0323 | MATLAB | 6,254 | 182 | function fmodel = mTRFtransform(bmodel,resp,varargin)
%MTRFTRANSFORM Transform a backward model into a forward model.
% FMODEL = MTRFTRANSFORM(BMODEL,RESP) transforms a backward decoding
% model (stimulus to neural response) into the corresponding forward
% encoding model (neural response to stimulus) as per Hau... |
e6400429186c1a8e3fecf5a5dcd2fdff8a6f47a374b550f727155cf2c4975d33 | MATLAB | 6,255 | 145 | clear all;close all;clc
subj_list = {'87'}
iSubj = 1
subj = subj_list{iSubj}
phase_list = { 'tuning_correct'}; %encoding, tuning_correc
reg_list = {'OFC' 'FRO' 'TEMP' 'INS' 'CING' 'EC' 'HC' 'CA3'}
lock = 'onset' %onset response
ref = 'LM'
fs = 500;
baseline ... |
d51cb1b59e468f218519cca75b83b2e3f969cf0449ea6b67a2e3deaa3ffdda09 | MATLAB | 6,266 | 225 | % Gtomo2_wtmex_test.m
% Test the Gtomo2_wtmex object
% and the Gtomo2_dscmex object
% todo: test both Fatrix and fatrix2 versions
if ~has_aspire
return
end
if 1, printm 'thread timing of Gtomo2_dscmex with large case'
igl = image_geom('nx', 512, 'ny', 496, 'dx', 1);
sgl = sino_geom('par', 'nb', 600, 'na', 100, 'dr... |
826944a1c5c184eb4fd9bb6206a26449282ff9818e52b5367198aa42a11584be | MATLAB | 6,267 | 157 | % Script to generate the EEG vector of all the 115 s blocks
% concatenated in one tall vector. A vector is generated for each phase
% (phase 1 and phase 2) of MODA.
% A NaN is added between each 115 s block.
%
% * warning : a block has not been presented to the scorers
% * then the subject 01-02-13 has only 2 ... |
0dd0e9cc3e96462a46693b8540ef8a89de1bfc2356172b75f3b90ba8ed2bda70 | MATLAB | 6,270 | 102 | % THETA SEQUENCE DECODING ERRROR
% MH, 2020
% Finds real position at the time of the theta sequence, and calculates the decoding error during the theta sequence
% INPUTS:
% decoded_thetaSeq - uses decoded theta sequences that have passed velocity and number of active units thresholds.
% If em... |
4860d6033e9aef170b925c3db3a088a61d89c79a74697b0b52a9f19a14ee5b1b | MATLAB | 6,272 | 138 | function [input_graph, varargout] = fun_graph_pruning_internal_short_hairs_masked(input_graph, th_hair_length, internal_offset, ep_not_to_ind)
% fun_graph_pruning removes all the short links that connected to
% internal endpoints from the graph
% Input:
% input_graph: structure, generated by fun_skeleton_to_grap... |
dc5fab4ffa976c7187e05fc09789d3e372d7c3760fa7f60988420f8dbc3286cd | MATLAB | 6,274 | 175 | function spm_uw_show(mode,p1,p2,p3,p4,p5,p6)
% Manage graphical output for spm_uw_estimate
%
% FORMAT spm_uw_show(mode,p1,...)
%
% mode - Verb specifying action.
% p1-p6 - Depends on mode.
%
% FORMAT spm_uw_show('FinIter',SS,beta,fot,sot,ref,q)
%
%_______________________________________________________________... |
336342491ac9b10ff382b40a3e42f343d9bc57ccd70a6b4cc9984e756ed0b35c | MATLAB | 6,279 | 160 | function strOut = createSetRequestString(dataIDString,varargin)
%CREATESETREQUESTSTRING creates the XML string to set data via the
% infoserver based on inputs. The first required input is a dataIDString.
% The other input will determine what information is set. Depending on what
% needs to be set, a parameter/value in... |
4592b1e6dd65df5b2325daa257cdbeec55a5af52f3dedd27b3c54347a15b0a46 | MATLAB | 6,282 | 127 | function [FieldAssignmentsAll, OrganoidStencilAll, Wells] = Iris_GetOrganoidFields(InPath, MetaData, CoordinatesAll, illustrate)
%extract organoid IDs from CV8000 first pass and second pass integration
% author: Paul Antony 20210213
% Coordinates: example: readtable([InPath, filesep, 'Encoding.csv'], 'ReadVariableN... |
49a6fab594b6dcc3c717def5733bd20b53d096778daeb0469f4c5b91df3e45b7 | MATLAB | 6,282 | 184 | function mappedArray = c_struct_mapToArray(structToMap,fieldMap)
% c_struct_mapToArray - extract fields from a struct (or struct array) into an array
%
% Examples:
% a_struct = struct('X',1,'Y',2,'Z',3);
% a = c_struct_mapToArray(a_struct,{'X','Y','Z'})
% b_struct = struct('X',{1 4},'Y',{2 5},'Z',{3 6});
% b = c_struct... |
7cd5c07acd94c5df165da2af477b8ff5ca860973833ab4d27330dc5cc945baf4 | MATLAB | 6,286 | 145 | function [cgm, glucose, insulinBolus, correctionBolus, insulinBasal, CHO, hypotreatments, mealAnnouncements, vo2] = replayScenario(data,modelParameters,draws,environment,model,sensors,mcmc,dss)
% function replayScenario(data,modelParameters,draws,environment,model,sensors,mcmc,dss)
% Replays the given scenario defined... |
be266fb0624a690b67c889e2d24970f5993eb64337dad9ac79344835d7b5fd03 | MATLAB | 6,288 | 261 | function [pmf xs ys] = kde_pmf2(x, y, varargin)
%function [pmf xs ys] = kde_pmf2(x, y, varargin)
%|
%| Compute a 2D empirical joint probability mass function (PMF)
%| using interpolation that is similar to a kernel density estimate.
%| This joint PMF (interpolated / smoothed histogram) is useful for
%| computing joint... |
261ab483d831ac964244171a13192d16b40e19b80fad9fbfd0068a0189ee5cc0 | MATLAB | 6,290 | 198 | function Preprocessing_PDM_full_experiment(subn,task)
% PREPROCESSING_PDM_full_experiment Preprocess the EEG data for the PDM experiment (post-pilot data) for one
% participant and one task.
%
%Input: subject ID (e.g., 1), task (1=categorization, 2=distraction)
%
%Steps include:
%-removing extra EEG data
%-removing th... |
03dc17860a06659109c285c9c93568826807fea6eb61b2b94d57415eebafb588 | MATLAB | 6,292 | 148 | % % introSVC.m $%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% introSVC.m: a script what runs the introduction to SVC tasks
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% dependencies:
% getSubInfo.m (function to collect subject info)
%
%%%%%%%%%%%%%%%%%%%%%... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.