sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
dca556263b36f0c84a821ff82c07dfad5b31be2fcd980dac99306934417ac663 | MATLAB | 7,917 | 217 | function IPEMGeneratePitchShiftScript(varargin)
% Usage:
% IPEMGeneratePitchShiftScript(inFileName,inFilePath,inCentsToRaise,...
% inCentsPerStep,inScriptFilePath,inOnlyShift)
%
% Description:
% Generates a CoolEdit2000 script for creating a sound file containing
% appended p... |
3f4a94f7493d6ad4e59822da90278d766d576106d6b465f95a5ebd344cac06b4 | MATLAB | 7,919 | 206 | %aim to calculate the latency of the response, find the time and CI, and
%the bootstrap
% close all;
clearvars;
addpath ('/data/local/u0114568/ephysio/test');
cn1={'sp','color', 'con', 'incon', 'att', 'congruency','fac','int'}; % condition names length=8
cn={ [cn1{5}],[cn1{7}]};
condnames='Att-Faci-Int'; % note the ... |
7827793ff4f42dc473472cf8476c8bf022ba7440c91fd654f4a97c52caf14fc2 | MATLAB | 7,919 | 206 | %aim to calculate the latency of the response, find the time and CI, and
%the bootstrap
% close all;
clearvars;
addpath ('/data/local/u0114568/ephysio/test');
cn1={'sp','color', 'con', 'incon', 'att', 'congruency','fac','int'}; % condition names length=8
cn={ [cn1{5}],[cn1{7}]};
condnames='Att-Faci-Int'; % note the ... |
a54e353cd561f16eb54d021723836ebc90dea8a5aa064c0d03bd4d889bbbedf9 | MATLAB | 7,920 | 228 | %% Non-negative least-squares (NNLS) using L-BFBS-B
%
% Non-negative least-squares solves the following problem:
% $$ \min_x \|Ax \textrm{--} b\|^2_2 \quad\textrm{such that}\quad x \ge 0 $$
%
% The matrix 'A' may have more columns than rows (the 'underdetermined' case),
% or more rows than columns (the 'overdeterm... |
941aa4ccd25ce538494ff932c318e790bdf3a8d9547e11560d29d538e87c57ac | MATLAB | 7,925 | 205 |
%aim to calculate the latency of the response, find the time and CI, and
%the bootstrap
% close all;
clearvars;
addpath ('/data/local/u0114568/ephysio/test');
listname= 'allIncon';
cn1={'sp','color', 'con', 'incon', 'att', 'congruency','fac','int'}; % condition names length=8
cn={ [cn1{1}],[cn1{2}]};
condnames=listn... |
b469b3abede0f3f291dc203a60ba0d147e37e94f12d74c0b8bfadb6d62503259 | MATLAB | 7,926 | 279 | function out = spm_dartel_resids(job)
% Generate residuals in a form suitable for generating a Fisher kernel
% FORMAT spm_dartel_residuals(job)
% job.flowfields
% job.images
% job.template
% job.K
%
% The aim is to obtain better pattern recognition through using
% Fisher kernels. See Bishop's PRML or the work of Jaak... |
dc406b2812aca3552dacdad603fe7c296e2901aca225a506d559c0c79712ef09 | MATLAB | 7,926 | 205 |
%aim to calculate the latency of the response, find the time and CI, and
%the bootstrap
% close all;
clearvars;
addpath ('/data/local/u0114568/ephysio/test');
listname= 'allIncon';
cn1={'sp','color', 'con', 'incon', 'att', 'congruency','fac','int'}; % condition names length=8
cn={ [cn1{1}],[cn1{2}]};
condnames=listn... |
cf0a67d04c1571b233b9018868ee036daa4ffb5e060f62bc90f988b17dd3580a | MATLAB | 7,927 | 214 | function AssembliesVsSurrogate()
[filename,pathname] = uigetfile({'*_CLUSTERS.mat';'*_CLUSTERS.MAT'},'Open file with assemblies data', 'MultiSelect', 'off');
filenameCLUSTER=fullfile(pathname,filename);
clust=load(filenameCLUSTER);
assembliesCells=clust.assembliesCells;
cutName=strfind(filenameCLUSTER,'_CLUSTERS.ma... |
afd9fcdc060b87c46f5e2fe0b9d98f7becd5ed3712286d79241ccfbe47e3c78f | MATLAB | 7,930 | 236 | function spm_dcm_display(varargin)
% Region and anatomical graph display
% FORMAT spm_dcm_display(xY,a,c,h)
% xY - cell of region structures (see spm_regions)
% a - connections of directed graph a(i,j,1) = p value;
% a(i,j,2) = MAP estimate value
% c - node-specific inp... |
a86fa2d29a6e427ebcacdd6d137d0f78da9f892341b48030c5f6e3e9251196aa | MATLAB | 7,931 | 187 | %Process Data
%Inputs: app, Data, Data time
%Outputs:updated Data and Data time
function [DataTime,Data]=ProcessingData(app,Data,DataTime)
Order=app.ProcessOrderListBox.ItemsData;
%ItemData 8 == Rectify
RectifyPres= Order == 8;
if any(RectifyPres) %if rectify is present in the process order
if length(Order) == 1... |
e12de65d2c79648df64aec0ccad59a8194927dcd8af579d2e98b307817d02162 | MATLAB | 7,934 | 132 | function [shuffled_track,all_shuffles] = run_shuffles_final_lap(shuffle_choice,analysis_type,num_shuffles,decoded_replay_events)
% computes shuffles on replay events
% shuffle_choice- determines what type of shuffles will be performed, entered as a string
%
% analysis type- vector of 0's and 1's for which replaying sco... |
d86ecf406499f3bbc3adbbcbf31aaca79c0fc9bb6d7e1e586be511a2ee361d73 | MATLAB | 7,935 | 254 | % cfsRead64c.m
% an example of reading a cfs file, from 64bit Matlab
% must be able to find CFS64c.dll*
% *equivalent to CED's 64 bit cfs32.dll
% jg Colebatch
% 11.10.14: made 64 bit compatible version
%
INT1=0;
WRD1=1;
INT2=2;
WRD2=3;
INT4=4;
RL4=5;
RL8=6;
LSTR=7;
EQUALSPACED=0;
MATRIX=1;
SUBSIDIARY=2;
FILEVAR=0;
... |
db2d0544bbb8518903300236a94da209b1fcdeee766f0e6d94ab421f4f2f0c74 | MATLAB | 7,935 | 294 | function shat = de_ftab_invert(ftab, fhat, varargin)
%|function shat = de_ftab_invert(ftab, fhat, [options])
%|
%| given fhat (log transmission data),
%| estimate shat (component density line integrals)
%|
%| in
%| ftab strum BH "table" built by de_ftab.m
%| fhat [(n?) M] log measurements
%| option
%| smin {LL}
%| s... |
5d1f807284f3a4210d8beb797761954967f7fb3881c85a92a6a25b1d32bd3180 | MATLAB | 7,940 | 199 | function IPEMMECReSynthUI(varargin)
% Usage:
% IPEMMECReSynthUI(inAction,inData)
%
% Description:
% User Interface callback function for interactively handling the resynthesis
% of MEC analysis results.
%
% Input arguments:
% inAction = string representing the type of action to take
% (sh... |
4040307e1682bfb6b184155226b0708171f58416f463922fd97b5756665d8957 | MATLAB | 7,947 | 202 | function IPEMAnimateSlices(varargin)
% Usage:
% IPEMAnimateSlices(inSignal,inSampleFreq,XAxisLabel,YAxisLabel,...
% inXData,inXRange,inYRange,inTimeRange,...
% inTimeStep,inAnimationInterval,inScales,inGraphicsHandle)
%
% Description:
% Displays animated plots of a 2D ... |
cf16e1bae1a41cb823daa5462579de5f963d94521cd6c66c6b4877f856980935 | MATLAB | 7,952 | 242 | function montage = spm_eeg_montage_ui(montage)
% GUI for EEG montage (rereference EEG data to new reference channel(s))
% FORMAT montage = spm_eeg_montage_ui(montage)
%
% montage - structure with fields:
% tra - MxN matrix
% labelnew - Mx1 cell-array - new labels
% labelorg - Nx1 cell-array - original... |
d70f2212550b41d18fb51878bf1eeb4fcb10be1c970d39afdc0fa00ea99fc6d1 | MATLAB | 7,964 | 262 | close all
load ../data/Diffusion_vs_Age_WMlabels_mean_NODDI90_expanded.mat
load in.mat
ord_sel = 2;
pval_level = 0.05;
age = age';
% This are the representative areas that I dediced to include in
% supplementary Fig. C.1 and supplementary Fig. C.2
%roi = [17, 18]; %ALIC (Area with large age effect that maturates late... |
d09c7c1b0d70ac84f898b0f708c8a34f9b3f807db0b8cc3758a2639a4850a945 | MATLAB | 7,971 | 247 | %
% This code reproduce the fingerprinting analisys of the article 'The
% evolution of information transmission in mammalian brain networks' -
% Alessandra Griffa, Mathieu Mach, Julien Dedelley, Daniel Gutierrez-Barragan,
% Gutierrez-Barragan, Alessandro Gozzi, Gilles Allali, Joanes Grandjean,
% Dimitri Van De Ville... |
155bfc24c5a757c39bc50e429fb199e017b43edf594216cc354806df4241c42a | MATLAB | 7,979 | 136 | function [Objects] = f_imageAnalysis(Label, ch1, ch2, ch3, PreviewPath, MetaTable)
%vol(ch1, 0, 5000) Hoechst
%vol(ch2, 0, 4000) 647 Sox2
%vol(ch3, 0, 5000) 568 Edu
%vol(ch4, 0, 5000) 488 Ki67
ObjectsThisOrganoid = table();
%% Max projections
%NucMax = max(ch1, [],3); imtool(NucMax,[])
... |
981cd4545622c582772c3e2bfaaf8e72b7f46314cf37c1279075f6fac9a67706 | MATLAB | 7,980 | 241 | %% Script that comparing leaky integration with time and distance
% Zilong Ji, UCL, 2022 zilong.ji@ucl.ac.uk
% We calculated different generative angular-linear models with different
% types of source errors to find the candidate for our model (please see
% online methods for details. We chose healthy elderly group to ... |
1e0df5ac660cf773ff023c66b1c0d6f8d6d656a32d38cca8937989048bc0ad17 | MATLAB | 7,986 | 242 | %% Figure S1 a & b
% this script rungs additional analysis required for the plots of figure
% S1a & b.
%%
clear
rng('default')
%% - SUBJECTS - %%
% ID 18 missing because of LP at 50Hz
subjects = {'OSL13', 'OSL14', 'OSL17', 'OSL18', 'OSL21', 'OSL24', 'OSL26', 'OSL27', 'OSL28', ...
'OSL29', 'OSL30', 'OSL31', 'OS... |
09ed03d0e9126d76f86ae592756a23247b7e3c01cea51c31ed4f36c3454e85f6 | MATLAB | 7,992 | 228 | function varargout = clickableLegend(varargin)
% clickableLegend Interactive legend for toggling or highlighting graphics
%
% clickableLegend is a wrapper around the LEGEND function that provides
% interactive display toggling or highlighting of lines or patches in a MATLAB
% plot. It enables you to,
% * Toggle (hide/... |
de9fea042eaa34e3ce47d7a92c3148b22bc79e802eb1d7568ce0f00190926586 | MATLAB | 7,993 | 277 | function [ibi, indx, peak_indx, ADD, REM] = processing_ecg(ECG, time, fsample)
% This code performs heartbeats detection from ECG or ICA-ECG. The
% procedure includes heartbeat template, peaks
% detection and manual edition of misdetections.
% This function requires the function editpeaks.m
% Inputs:
% ECG: ECG array
%... |
a3bc8ad79cb0694e392e5c37a469ad607d3fa0ba959a8314c81e39ba70188c0e | MATLAB | 7,995 | 190 | function [data, timestamps, info] = load_open_ephys_data_faster(filename, varargin)
%
% [data, timestamps, info] = load_open_ephys_data(filename, [outputFormat])
%
% Loads continuous, event, or spike data files into Matlab.
%
% Inputs:
%
% filename: path to file
% outputFormat: (optional) If omitted, contin... |
c97febe2d62d831a73ab9e9bf94b6f6a4d7b8cc08f8b15e5565afd764ed5299c | MATLAB | 7,997 | 320 | master_startup;
load(path.mat_save + "summary_most_recent_aug17_2022.mat")
saving = 1;
% compute number of params
nparams.nohistory = 10;
nparams.initpt = 14;
nparams.inattention = 14;
fits.labels = {"nohistory", "initpt", "inattention"};
% lets first augment summary with logllpertrial, bic, aic etc.
for l = 1:leng... |
a33a47cb71bb2bf5e55120c535e68848ee234c96b592952c7033d25aa6b8da17 | MATLAB | 7,999 | 217 | function closeWindow(varargin)
% Use this function to close the stimulus window, normally at the end
% of your experiment. Requires global WINDOW, see initWindow.m.
% This function can also be used to close the toolbox windows if the
% handles have accidentally been deleted (e.g. after a `clear all`).
% All functions o... |
bdc07bed5a8fd95ce1084bf9c51f58ff7958ad49508c117fcc525b6546b9a7aa | MATLAB | 8,002 | 102 | % DATA FOLDERS FOR ANALYSE ORGANIZED BY SESSIONS
function sessions = replay_ctrl_data_folders(option)
if strcmp(option,'first')
%16x8
sessions.S16_8 = [{'X:\BendorLab\Drobo\Lab Members\Marta\Analysis\HIPP\M-BLU\M-BLU_Day4_16x8\replay_control_short_exposures'},...
{'X:\BendorLab\Drobo\Lab Members\Marta\An... |
2323d3d9fb5957e7319733ffdcefdc45436b729c049ee89a716c60128f2e2b6f | MATLAB | 8,010 | 197 | clear all; close all; clc
fn_ext = 'cue_resp' %
phase = 'retrieval' %'encoding' 'retrieval'
lock = 'onset' %'onset' 'response'
reg1_name = 'TEMP' % OFC, FRO, TEMP
reg2_name = 'HC';
DS = 'yes';
ref = 'LM';
clinical = 'yes';
lag = '';
subj_list = {'39' '44' '57' ... |
b445c335b88283c94916c4fd4f76f08e22d7675940242d3320994da3285a76da | MATLAB | 8,016 | 226 | %
% 'overseer' function for performing & logging subtraction in a tapered
% approach.
%
% [data,cfg]=m_do_taperedhann(data,cfg)
function [data,cfg]=m_do_taperedhann(data,cfg)
% this code needs some severe cleanup.
% several variables are unused, and some matrices could be defined as a bit
% smaller.
verbose=0;
cw... |
a9996c2cef38bd48091b7b728827b17cb4e77417245ddea494708abeaefff9c5 | MATLAB | 8,017 | 269 | function M = spm_maff(varargin)
% Affine registration to MNI space using mutual information
% FORMAT M = spm_maff(P,samp,x,b0,MF,M,regtyp,ff)
% P - filename or structure handle of image
% x - cell array of {x1,x2,x3}, where x1 and x2 are
% co-ordinates (from ndgrid), and x3 is a list of
% ... |
509408b62cd9801fba687e1c22d090510cd034aee5127a0c511f48ab4bfa6a9b | MATLAB | 8,019 | 154 | % CREATE NEW PLACE FIELDS FOR TRACK 1
% MH_2020
% Takes the rate maps of T1 for the same number of laps than for T2 (e.g. If T2 is 2 Laps, then it takes ratemaps after 2
% laps in T1). Depending on the control that is being run, it will modify general parametrs of the session, such as all tracks good cells, unique
% ce... |
c0fcde1dce98ef53a36800fe773acf1fe104fed42627257607f07cf66e50ca71 | MATLAB | 8,020 | 217 | function x = beeswarm(x,y,varargin)
%function xbee = beeswarm(x,y)
%
% Input arguments:
% x column vector of groups (only tested for integer)
% y column vector of data
%
% Optional input arguments:
% sort_style ('nosort' - default | 'up' | 'down' | 'fan' | 'rand' | 'square' | 'hex... |
3d9cde87500387cae56542af3ef3f1d57176b152cf049f7d08521036cc162f96 | MATLAB | 8,021 | 236 | % Script to plot Figure 8, calculate statistics reported, and save data to
% Excel spreadsheets that are then imported into the Source Data file.
% 'exp_...' denotes variable for expansion, and 'con_...' for contraction
% Kit Longden 2023.
addpath ../../src/Shared_functions/
% Figure properties
% -----------------
fi... |
98af156ea9258e1a02af2cdfb162a9a99404906707ebdb49f289071bd8cdb9dd | MATLAB | 8,022 | 292 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% SC retinotopy modelling:
% Simulation to estimate how many RGC inputs SC neurons integrate.
%
% Assumption 1: Poisson distribution to definte the number of inputs
% Assumption 2: Integrate RGC axonal inputs with weights depending on the
% overlap of den... |
2ef4b9413161894be893dcb5439c718a009e3aea5e61a9e9f4196543a2e0bb9c | MATLAB | 8,026 | 203 | % BATCH ANALYSIS PIPELIN
function batch_analysis(option,varargin)
% option: 1- spikes & video ; 2 - position & laps ; 3 - sleep ; 4 - CSC & PSD ;
% 5 - Place cells, bayesian & replay decoding ; 6 - replay section(scores, shuffles) ; 7 - see replay
% varargin: [] or 'all'
if any(ismember(option,1)) || strcmp(v... |
76b362ef22eb7c1ce1066f5c9e26a2a44776cbd506d624037a0d638e95b826c1 | MATLAB | 8,026 | 315 | function report = makeReport(obj, plotFigures, DWgrid)
if(~exist('plotFigures'))
plotFigures = 1;
else
r.plotFigures = plotFigures;
end
if(~exist('DWgrid'))
disp('Not using DW grid')
DWgrid = false;
end
fontSize = 4;
% Return some info to the caller
report.simName = obj.simName; ... |
3c3d99640b60148cbfd9a4d65a844c4ed256504fb7a64028ae8a8212dc7048bc | MATLAB | 8,031 | 200 |
function create_diff_cum_replay_figures
% PLOT DIFFERENCE IN CUMULATIVE REPLAY FOR TRACKS 1+3 VS 2+4
cd 'X:\BendorLab\Drobo\Lab Members\Marta\Analysis\HIPP\Chapter 2\Raw_replay_analysis\figures\Diff cumulative replay'
awake = openfig('Cumulative replay events diff between tracks -1 3 2 4during all sleep periods ... |
5abbdcbd9db42060354ab840ef8f51d32facecd9d8dc00bdc6357448ce846dfe | MATLAB | 8,031 | 274 | % This function fits a curve to virtual segregation experiments for
% each iteration, and sees which one fits best to the given data.
function [age,bestIter] = matchIterationToAgeSegregationExperimentDist(obj,normaliseSize)
if(~exist('normaliseSize'))
normaliseSize = true;
end
% Internally we only work ... |
99c6b7faffbb93702813ddd83312a046d90ee2b68107f5cb518fbb32f8ebfbcd | MATLAB | 8,031 | 127 | function [Ca, h, IP3, I_WM, array_I_neuro, Gli_local, Gli_global, I_WM_OHM] = ...
step_astrocytes(neuron_astrozone_activity,neuron_astrozone_activity_OHM, spike, array_I_neuro, i, Ca, h, IP3, I_WM, Gli_local, I_sr, Gli_global)
params = model_parameters();
diffusion_Ca = zeros(params.mastro,... |
aa009c2ad53157b0daa7c17ba4e736e6d951ffdd21b804555254dc3d714b9fc9 | MATLAB | 8,032 | 185 | function [ outDetecVector ] = mergeAndCutEvents( inDetecVector, samplingRate, ...
maxSpindleLengthSec, minSpindleLengthSec, minSpindleStepSec2Merge )
% Purpose : to merge and cut too short or too long events.
%
% Note about the merge:
% From (Warby 2014) no merging rule were applied to automated detected spind... |
a2e6e6a93c39aafeafc868a9d8876ded0ae852fa4134fffa4c1fa09cd81fb519 | MATLAB | 8,033 | 217 | function predict_gprML(scan_dir,subjectscan,target_dir,sl_radius,ffs,c1,c2)
% this function start the GPR prediction on preprocessed beta-images of
% fMRI data. The prediction is performed by applying multivariate MLE on
% 1) the continuous activity pattern (mup) and
% 2) the estimated spatial covariance (S2_est) in a ... |
6eaf1bfba1f896ee2971f3e320ff463e5e769dd2530334b6ad7cf29396b5acad | MATLAB | 8,036 | 303 | function ob = Gblur2(mask, varargin)
%function ob = Gblur(mask, options)
%|
%| Construct Gblur object for image restoration.
%|
%| See Gblur_test.m for example usage.
%|
%| in
%| mask size(image) logical array of object support.
%|
%| options
%| 'chat' verbose printing of debug messages
%| 'psf' point spread functio... |
69e2d6e18a2743801138352691b91f387a88e941a13cd535258afd3b1ce0c4c1 | MATLAB | 8,042 | 213 | function rsa_feedforward_eeg_subject_by_subject(subjects,model_type,with_stats,with_error_bars,rsa_in_matlab)
%RSA_FEEDFORWARD_EEG_SUBJECT_BY_SUBJECT Compute and plot the RSA between DNN and EEG with stats, if desired.
%RSA is computed by correlating each of the subject-specific EEG RDMs with
%the RNN RDM and averagin... |
6fad8d7eabfc0ac7099932763bc5442e4c583fa0d48af2a9819d60b97fd39ce4 | MATLAB | 8,045 | 185 | function out = startQuestionnaireTable(trial, text, ansText, topText)
% This is the main function for plotting tables that are used in the
% questionnaires.
%
%
% Copyright: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
% Contact: OTBR-Toolbox@ruhr-uni-bochum.de
% Source Code: https://gitlab.ruhr-uni-bo... |
da1a187c04d52fb4198761d6840575326cca67161ddde6a94096b030f5c9bf8a | MATLAB | 8,054 | 211 | function SBJ07a_ERP_stats(SBJ,conditions,pipeline_id,an_id)
% Calculates ERPs, computes cluster-based statistics, and plots the results
% clear all; %close all;
%% Data Preparation
% Set up paths
addpath('/home/knight/hoycw/PRJ_Stroop/scripts/');
addpath('/home/knight/hoycw/PRJ_Stroop/scripts/utils/');
addpath('/home/... |
b7ac84ab4a7ae0071b61b5205516e1958955077a6d476941d80990ea20938cc0 | MATLAB | 8,055 | 187 | function plot_topography_searchlight_decoding(subjects,analysis,with_stats)
%PLOT_TOPOGRAPHY_SEARCHLIGHT_DECODING Plot the decoding searchlight results
%at peak decoding accuracy.
%
%Input: subject IDs, analysis ('object_decoding' or 'category_decoding',
%with or without stats (1/0))
%
%Output: one topography plot
%
... |
3c7f7c88d792e03ca9c77b45a483b56916176c85c5188c387eed145f627964fb | MATLAB | 8,063 | 213 | function MIP_stitch_8921(target, P2path,datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the retardance using the coordinates from AIP stitch
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
id=islice;
filepath=strcat(datapath,'mip/vol',num2str(islice),'/');
cd(filepath);
xx=dis... |
62faf91666e843aaeeac3602ab4610af9f9fcfe49a3725d7995b8714e8e217a6 | MATLAB | 8,065 | 299 | function [sinit, bodycoil] = ir_mri_sensemap_init(ykj, varargin)
%function [sinit, bodycoil] = ir_mri_sensemap_init(ykj, varargin)
%|
%| Form initial sensitivity map estimates from surface coils and bodycoil.
%|
%| in
%| ykj [(N) ncoil] surface coil data (2D or 3D)
%|
%| option
%| 'type' initialization method (def: ''... |
655a09477e55b07726f2fc7121789e934a3bb213c91c62ae1d8acd7cf6d5387b | MATLAB | 8,068 | 221 | % PLOTTING PARAMETERS
% Marta Huelin
function plot_param = plotting_parameters_old
% protocol colors from viridis palette
plot_param.viridis_colormap = [0.26700401 0.00487433 0.32941519;...
0.501960784313725 0.180392156862745 0.549019607843137;...
0.301960784313725 0.349019607843137 0.650980392156863;...
... |
ca3071772ab06f527423a8f0b8c573b7ae655ddc331275f45a89cb89ea0bc91e | MATLAB | 8,087 | 290 | filename= sprintf('stk_0026_pos7_FullMovie.czi kept stack.tif');
info=imfinfo(filename);
numframe=length(info);
%image size
flength=2203;
fwidth=2203;
f=1;
Raw(:,:,:,f) = imread(filename,f);
cooked=mat2gray(Raw(1:floor(fwidth),1:floor(flength),:,:));
%Find initial centroids
Iin=cooked(:,:,:,f);
Amax=[8000]... |
ba4a37676b0caae8a04dd20ebcc14b8cb2f8ce50362ef3dc9e8be7e475aac53b | MATLAB | 8,089 | 266 | function nvr_recorder()
%
% This is the initialization function for the v2 neural/vocal
% recorder system. It will open the figure file nvr_recorder_fig,
% and initialize the display to the default settings.
%
% Created 6/20/03 by Steven Eliades
%
% Updated: 8/9/05 upgraded to 33 channels.
global nvr
g... |
1197b5fa2dfd74e38f579d1aafdd6af0a83da436814ba8e5e50e14ac9eab022c | MATLAB | 8,090 | 216 | function [minimum,fval] = anneal(loss, parent, options)
% ANNEAL Minimizes a function with the method of simulated annealing
% (Kirkpatrick et al., 1983)
%
% ANNEAL takes three input parameters, in this order:
%
% LOSS is a function handle (anonymous function or inline) with a loss
% function, which may be of any t... |
57081ac7d02aba3cfbcc26b1f44962aa41041e028d3f76659ffe603fbde9971c | MATLAB | 8,095 | 266 | function varargout = spm_jsonwrite(varargin)
% Serialize a JSON (JavaScript Object Notation) structure
% FORMAT spm_jsonwrite(filename,json)
% filename - JSON filename
% json - JSON structure
%
% FORMAT S = spm_jsonwrite(json)
% json - JSON structure
% S - serialized JSON structure (string)
%
% FORMAT [.... |
6047970b1ef63ac2128da7dbea2bb47b273ae570b684e2666c46a122cbe2776a | MATLAB | 8,101 | 200 | % internal function
% - Jimmy Shen (jimmy@rotman-baycrest.on.ca)
function hdr = load_nii_hdr_bis(fileprefix, machine)
fn = sprintf('%s.hdr',fileprefix);
fid = fopen(fn,'r',machine);
if fid < 0,
msg = sprintf('Cannot open file %s.',fn);
error(msg);
else
fseek(fid,0,'bof');
h... |
fdaa1ae1c2fa5eea315b27152336517d336a6953c3bfedc5e60b92e932e499b0 | MATLAB | 8,102 | 272 | function mri = MRIread(fstring,headeronly)
% mri = MRIread(fstring,headeronly)
%
% Reads in a volume based on the fstring. fstring can be:
% 1. A stem, in which case the format and full file name is determined
% by finding a file on disk called fstring.ext, where ext can be
% either mgh, mgz, img, bhdr, nii, o... |
8ad285b81d812027f9434039d34e8687f3940178f050e6187d63ac0b1a1eb817 | MATLAB | 8,103 | 184 | function dth_pseudotrials_SVM_full_experiment_cross_validated_sl(subject,task)
%DTH_PSEUDOTRIALS_SVM_FULL_EXPERIMENT_CROSS_VALIDATED Performs the distance-to-hyperplane analysis using SVM on
%a balanced dataset. Instead of creating pseudoconditions out of scenes,
%the trials from across conditions are lumped into pseud... |
924b21be1070a0820d82668b4db5fa0e9745ae51a631a4437c733387f927cf9e | MATLAB | 8,105 | 214 | function MIP_stitch_7688(target, P2path,datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the retardance using the coordinates from AIP stitch
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
id=islice;
filepath=strcat(datapath,'mip/vol',num2str(islice),'/');
cd(filepath);
xx=dis... |
92abd681dd5ab5b2cc059d488fdd2ffe46191936d5cd3bd957ba64efd090278c | MATLAB | 8,105 | 214 | function MIP_stitch_7694(target, P2path,datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the retardance using the coordinates from AIP stitch
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
id=islice;
filepath=strcat(datapath,'mip/vol',num2str(islice),'/');
cd(filepath);
xx=dis... |
17b7775c33867935387ae922e25747eb8f0b4966fbf44aeedd8bd4e45bd269f5 | MATLAB | 8,106 | 214 | function MIP_stitch_PTSD1(target, P2path,datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the retardance using the coordinates from AIP stitch
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
id=islice;
filepath=strcat(datapath,'mip/vol',num2str(islice),'/');
cd(filepath);
xx=di... |
55e6af6bd50f64dd12e7d476107ba5c8ebb66e38d78fd70de9b0bfa8aa135d3d | MATLAB | 8,109 | 243 | function nvr_beginrecording
%
% This function will setup and begin data acquisition. It will generate a header file
% and log file entries, as well as the .wav data file format. Data from device 2
% will be automatically logged to disk using native toolbox functions. Once data
% acquisition is completed, it will... |
3fcefbf9d2aeba760c9c225d068a6fef7944d86c1707eb0abbb8c04ab83e59c3 | MATLAB | 8,111 | 214 | function MIP_stitch_6692(target, P2path,datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the retardance using the coordinates from AIP stitch
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
id=islice;
filepath=strcat(datapath,'mip/vol',num2str(islice),'/');
cd(filepath);
xx=dis... |
105f7a3d54fc24e32770982c6a9c4525bcecc10388f7a53aa1884cb1e2a419b4 | MATLAB | 8,113 | 187 | function SBJ08b_HFA_plot_crRT_mGLM(SBJ, proc_id, an_id, model_id, stat_id, plt_id, save_fig, varargin)
%% Plots mass GLM beta time series per electrode
% INPUTS:
% SBJ [str] - ID of subject
% proc_id [str] - ID of preprocessing pipeline
% an_id [str] - ID of the analysis parameters to use
% model_id [str] - ID ... |
e71fac8f35810651c7cb7c55f61738cd174f9a9913357038d835cb08fe0fca3f | MATLAB | 8,126 | 219 | function [minimum,fval] = anneal(loss, parent, options)
% ANNEAL Minimizes a function with the method of simulated annealing
% (Kirkpatrick et al., 1983)
%
% ANNEAL takes three input parameters, in this order:
%
% LOSS is a function handle (anonymous function or inline) with a loss
% function, which may be of any t... |
9260a14c7a53ca6873fa61c6a09fe38f5fbf517c733f23a68ddca0a971d3dc2a | MATLAB | 8,139 | 275 | function x = spm_load(f,v,hdr)
% Load text and numeric data from file
% FORMAT x = spm_load(f,v,hdr)
% f - filename (can be gzipped) {txt,mat,csv,tsv,json,npy}
% v - name of field to return if data stored in a structure [default: '']
% or index of column if data stored as an array
% hdr - detect the presence ... |
86b323d0f3322f5b3a926ede51d46a8164d3517d318d3f9685ad9387fbf23674 | MATLAB | 8,147 | 153 | function [warningLst] = convertEpochScores2Block(pathOutput, annotScoreFolderName, ...
nSamplesInEpoch, nSamplesInBlock, nTotEpochs, nEpochsInBlock, nSamplesOverlap)
% Convert the scores per epoch (including the 2.5 s overlap
% between consecutive epochs) into scores per block of 115 s.
%
% Select the highest sc... |
582372d80f6ba1aae9aa06a1edd4ff2ce6f6cdc0b593b6b608d3baf7cc2dafbb | MATLAB | 8,150 | 296 | function fsino = rebin_par2fan(psino, pgeom, fgeom, varargin)
%function fsino = rebin_par2fan(psino, pgeom, fgeom, varargin)
%|
%| Rebin parallel-beam (or mojette) sinogram into fan-beam sinogram.
%| Also useful for mojette-to-parallel rebinning.
%|
%| in
%| psino [nr nphi] parallel-beam sinogram
%| pgeom sino_geom(... |
7c0f52961d3c4b2444729c8d035c20e4dac057e74209bc02fccf2f0bbedec2d9 | MATLAB | 8,150 | 272 | function R = Robject(kappa, varargin)
%function R = Robject(kappa, [options])
%|
%| Build roughness penalty regularization "object" based on C = Cdiff() object,
%| for regularized solutions to inverse problems.
%|
%| General form of nonquadratic penalty function:
%| R(x) = \sumk w_k \pot([Cx]_k), where [Cx]_k = \sum_j... |
fd15c1a4f52a7a43f8796cdc2ce9c0f55528b10cbeaa7917c830a8370cf47d81 | MATLAB | 8,152 | 187 | function target_voxel_str = fun_graph_get_nearest_skl_ind(vessel_image, vessel_mask, vessel_skl, ep_sub, ep_all_sub, return_local_arrayQ)
% fun_graph_get_nearest_skl_ind use threshold relaxation to find the
% closest skeleton voxels that locates in a connected component other than
% the connected component that ep_1_su... |
e93a75a5cea104428aab3320011207d15defd167b87f9cc56342e51e789aa640 | MATLAB | 8,157 | 224 | %% ============================================================
% Improved Simulated-Online LOTO (Leave-One-Trial-Out)
% Key improvement: train features also extracted from 25-sample windows
% Baseline = in-between rests
% Target: push average accuracy into the 60s
%% ==============================================... |
6493b6cc723b16c80a326185a8f3d69e976b06dd29501e564190702008a515b5 | MATLAB | 8,165 | 175 | % PHASE CIRCULAR SHUFFLE
% MH 2020
% Circular shuffle of starting phase, shifiting all columns together.
% Maintains relationship between phase and cell assembly spike probability, but not phase/position.
% INPUT:
% decoded_thetaSeq, directional_place_fields - data structs. If empty, loads them
% num_shuffles: ... |
026ca2bb0f38978d66ad71b4adb85706e5d88f2da32ba6b5a070bb18e9270210 | MATLAB | 8,169 | 198 | function Optical_fitting_intralipids(co, cross, 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','... |
1a66ba5f77013a2a7dd948cd4385ab21401eeb7e3988db79c484c6061cd62be8 | MATLAB | 8,172 | 161 | function [hfd,cfreq,ord]=hifi(d,si,cfreq,varargin)
% ** function [hfd,cfreq,ord]=hifi(d,si,cfreq,varargin)
% Passes data d through butterworth highpass filter using double reverse
% filtering routine 'filtfilt'. Double reverse filtering has the advantage
% of zero phase shift of the resulting signal. See no... |
04cfd09fb90b70fac2206e68e01e2b8bbcda6b1ebd89c476d6d44391865866de | MATLAB | 8,173 | 210 | function analyze_SI_bimodal_Fig2_Sfig3
rootdir = 'C:\TKlab_agingPFC\';
cd(rootdir)
load SI_bimodal
num2period = {'Bsl','Smp','eDly','lDly','Fbc'};
%% plotting data
figure( ...
'Position', [0 100 1450 1000], ...
'PaperOrientation', 'landscape', ...
... |
8beec8142fbbb36adeb6ba8c117cb686c5403c31a20ba3f21a94e56892b502ce | MATLAB | 8,180 | 189 | function [allData] = plotSignificanceChangeByROINew(allMat,t1,t2,t3,baseline,type,thresh)
SynergyIdx = 11;
MuIdx = [4:5];
%plot
nGen2Cons = 3;
pBaseline = zeros(nGen2Cons);
pGen(1,:) = [1,0];
pGen(2,:) = [0,1];
pGen(3,:) = [1,1];
pGen = [pBaseline,pGen];
pCovGen(:,1) = [0;0;1];
ROIPos{1} = [-200... |
c585434c7f2f3b23e0bd263cfb655f281edbdae6389bf53e3715008b116f08aa | MATLAB | 8,181 | 215 | function MIP_stitch_NC(target, P2path,datapath,disp,mosaic,pxlsize,islice,pattern,sys)
%% stitch the retardance using the coordinates from AIP stitch
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
id=islice;
filepath=strcat(datapath,'mip/vol',num2str(islice),'/');
cd(filepath);
xx=disp(... |
674d47072c49536312114c27ed8367b6503a6ddd6933afb66a61608ced5a5e71 | MATLAB | 8,183 | 260 | %Uninterrupted oscillations
clear all
close all
dbeh_path='C:\Users\xscogno\MATLAB\Flavio2\Waves\Tracking data\';
rec_data_path = 'C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath_spikes='C:\Users\xscogno\MATLAB\Flavio2\Preprocessed_data\';
dpath_sorting='C:\Users\xscogno\MATLAB\Flavio2\Waves\Sorting\';
dpa... |
d69cb509148d04ec6108c225926144e9b2f3788d0643cabb6d6759d13e13d013 | MATLAB | 8,185 | 227 | function [z,a,it,ord,s,fct] = backcor(n,y,ord,s,fct)
% BACKCOR Background estimation by minimizing a non-quadratic cost function.
%
% [EST,COEFS,IT] = BACKCOR(N,Y,ORDER,THRESHOLD,FUNCTION) computes and estimation EST
% of the background (aka. baseline) in a spectroscopic signal Y with wavelength N.
% The backg... |
b309d9e96e9a3e15bb50b33144cd83c5bab186c394b58ed769bb44dc66c8e663 | MATLAB | 8,189 | 209 | function [Mlog,Q]=community_louvain_lex(W,gamma,M0,B)
%COMMUNITY_LOUVAIN Optimal community structure
%
% M = community_louvain(W);
% [M,Q] = community_louvain(W,gamma);
% [M,Q] = community_louvain(W,gamma,M0);
% [M,Q] = community_louvain(W,gamma,M0,'potts');
% [M,Q] = community_louvain(W,gamma,M0,'neg... |
596266eff2057e3deb21454948dfb498034589659e6c53c91a29c42de62b3d16 | MATLAB | 8,201 | 201 |
function create_rate_replay_figures
% PLOT RATE REPLAY FOR 1+3 vs 2+4
cd 'X:\BendorLab\Drobo\Lab Members\Marta\Analysis\HIPP\Chapter 2\Raw_replay_analysis\figures\Replay rate'
awake = openfig('awake Replay - Difference in T1+T3 vs T2+T4 replay rate during first 30min between PRE and INTER on periods of -awake.fig')... |
da6413674e112d3881f99e3b4857e492bcf7fb0ddac739df4eda8178d3fa5e5d | MATLAB | 8,202 | 350 | function [kspace, omega, gradxy] = mri_kspace_spiral(varargin)
%function [kspace, omega, gradxy] = mri_kspace_spiral(varargin)
%|
%| k-space spiral trajectory based on GE 3T scanner constraints
%| options (name / value pairs)
%| fov field of view in cm; default 22
%| gamp max gradient amplitude; default 2.2 G/cm
%| gs... |
ea98dcc3837003ca007592bef77acf032721ac13aaafbc5a496b0f6b4d49e622 | MATLAB | 8,213 | 152 | function [kp, iop, rfp] = example_spsp_param1()
%function [kp, iop, rfp] = example_spsp_param1()
% setup parameters for spectral-spatial pulse design.
%
%Chun-yu Yip, 4/7/09
kp = kparametersSPSP(); % k-space trajectory parameters
iop = ioparametersSPSP(); % input/ouput parameters
rfp = r... |
0a302ad522dc5129b7c1b4bc223ab101209cbfa08031fc2a6b77f4c889626ddb | MATLAB | 8,219 | 226 | function varargout = spm_help(varargin)
% SPM help and manual facilities
% FORMAT spm_help
%
% The "Help" facilities are about software and implementation. The
% underlying mathematics, concepts and operational equations have been (or
% will be) published in the peer reviewed literature and the interested
% user is ref... |
e195e123e8d02632270d0050943da2ba9615890a24b98443903662e37656821b | MATLAB | 8,220 | 238 | % With this script, test the MoCsEFC-signal-extraction-pipeline
%
% MoCsEFC uses two simple Hjorth/Surface-Laplacian-Montages (C3-,
% C4-Hjorth), the signal from which is spectrally filtered to 8-15Hz, and
% functional connectivity is then estimated by the PLV (from the Hilbert
% transform of the 500Hz-signal).
%% ... |
38c3a3ea889144076611197bbbe0902befbd5d1e3aa38ab1247e68c4023240b1 | MATLAB | 8,223 | 142 | %% Create Average Structural MR Image across all individuals & a Binary Grey & White Matter Mask for analysis
% (c) Carys Evans, UCL
% carys.evans@ucl.ac.uk
% October 2019
%This script requires SPM12
% To run this script MR images must have already been converted from native
% to standard space. This script ... |
e793e2a4e5d2291b1e8df18bdabaa60adbba0e815a761649329b14859e7ce2e2 | MATLAB | 8,231 | 235 | %% Phase-Slope Index using the Peak-Frequencies from the PLV Spectrum
% Compute the PSI between a seed motor electrode that explains most of the
% behavioral variance and electrodes within frontal cortex
% ########################################################################
% Input:
% - cleaned and segmented dat... |
29f5442353a4870059ebff690e3646275e9f82d4ab29fff115d2d86e861b5324 | MATLAB | 8,235 | 168 | function [h, mu, sigma, q, notch] = al_goodplot(x, pos, boxw, col, type, bw, p)
% Violin and box plots for visualization of data distribution.
%
% Inputs:
% - x: NxP, data (P plots) (sample data if empty).
% - pos: 1xP, position of the graphs in x-axis, default: 1.
% - boxw: width of the graphs, def... |
b575b113405847f4f02e42ce8c635a309ff0cc1dcf8f774e2dc90d7f1bd08994 | MATLAB | 8,239 | 271 | function [seqs,params] = check_suspicious_sequences(dataperfly,annname,seqs,varargin)
[MINERRJUMPFRAC,CLOSELENGTH,MINORIENTCHANGE,MAXMAJORFRAC,MINWALKVEL,MATCHERRCLOSE,...
MINANGLEDIFF] = ...
myparse(varargin,'minerrjumpfrac',.2,'closelength',20,'minorientchange',pi/4,...
'maxmajorfac',2,'minwalkvel',1,'matcherr... |
25b0cf99af23bd44a24eb5bbaf88b528c1d98dc8ce244cc9a1d02081fbf5cca6 | MATLAB | 8,247 | 267 | function [smap, sinit, cost] = mri_sensemap_denoise(ykj, varargin)
%| Regularized estimation of (smooth) sensitivity maps for parallel MRI.
%function [smap, sinit, cost] = mri_sensemap_denoise(ykj, [options])
%|
%| Signal model: y_kj = s_kj f_j + noise_kj
%| s_kj sensitivity map (relative to "bodycoil" reference image... |
0fcf97b4120d946e4a5385c44dd43410a6e0c1c09cf651321d26bfa4c71e6aec | MATLAB | 8,257 | 229 | clc; clear;
addpath('/data/hu_esraal/Documents/eeglab2019_0/')
addpath('/data/pt_02333/esra_codes/')
addpath('/data/hu_esraal/Documents/TMSEEG-4.0')
addpath('/data/p_02186/TMS_ECG2/analyses/EEGtms/merge/')
eeglab
%%
eegfolder= '/data/p_02186/TMS_ECG2/analyses/EEGtms/merge/old_analyses_tmseeg'; cd(eegfolder);
save2fold... |
df0809e4926b07e55314d977aaf1583c4ba5918c0d8dfb98159884f80fff58b1 | MATLAB | 8,260 | 288 | %Code for obtaining myonuclei and myocyte counts and density from
%pericentrin and DAPI nuclei staining.
%Includes estimate of cell width and BTX staining
clearvars -except MCmean0
%input image variables
prompt = {'Pixel width (microns):','Day:','Start Position:','Enhancement factor:','image length:','Dila... |
8a88b22dbe1c9816c1b42e53a5838e2381a7f1b7cbb562b2599ee287150f5b54 | MATLAB | 8,262 | 210 | function SBJ11f_HFA_conn_plot_grp_mLME_recon(SBJ_id, proc_id, an_id, model_id, conn_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 of subject list to load
% proc... |
d42b8bc9f9f4a1496a54bfcc5f53e2afe720e043ae6b0205d5609aafa5d2d36a | MATLAB | 8,264 | 258 | function [Dl, Dr,I]=cortical_label_dir_adf(dirname, p_val)
% Computes the area of the different cortical labels
% and compare them to the normal range for all the
% subjects in directory "dirname"
% Uses the p_values to detect the abnormal structures
% Uses the lh/rh.parc.txt files
%
%
% cortical_labeling_dir_afd_t... |
41c22b55576aae67ed2e9abeb07fce43f1084006a2400fb4500b1129d0752944 | MATLAB | 8,269 | 233 | function [N,cdf] = spm_mnc2nifti(fname,opts)
% Import MINC images into NIfTI
% FORMAT spm_mnc2nifti(fname)
% fname - a MINC filename
% opts - options structure
%
% N - NIfTI object (written in current directory)
% cdf - NetCDF data structure
%
% The MINC file format was developed by Peter Neelin at the Montreal... |
67a6967a0decd5d7cf9b690ac05e4e5ba7d07fd09a0a19573dc3f4b405d9a758 | MATLAB | 8,276 | 188 | function ieegStructAll = extractRawDataWithROI(Subject, options)
% Extracts raw data based on specified options for each subject in the Subject structure
% and returns the extracted data in the ieegStructAll structure.
%
% Arguments:
% Subject: struct
% Subject structure containing data for each subject
% opt... |
33b5d05b6e01fc924281d1052014a8c605854f4faccf2df37ad3a0299a74bc56 | MATLAB | 8,277 | 211 | function rsa_rnn_eeg_subject_by_subject_averaged_timesteps(subjects,with_stats,with_error_bars)
%RSA_RNN_EEG_SUBJECT_BY_SUBJECT_AVERAGED_TIMESTEPS Compute and plot the RSA between RNN and EEG with stats, if desired.
%RSA is computed by correlating each of the subject-specific EEG RDMs with
%the RNN RDM and averaging o... |
e21cc2831f69a5af5093ca0ba76cb54cbdf02af98996e7584ec1ad4e3452880a | MATLAB | 8,283 | 203 | function [b_spdLeave,b_curvLeave,b_spdEnter,b_curvEnter] = ...
linearFilterAnalysisSpeedCurvature(f_orco,meta,plotFigure)
% linearFilterAnalysisSpeedCurvature wrapper function for calculating the
% linear filters for speed and curvature at crossing (defined by delta
% firing rate)
%
% Inputs: f_orco = fly ob... |
89d00eafb9fc4d090142af98fdc73e8ae5e5bb38a8a6f38d90fe7648cfc251ae | MATLAB | 8,288 | 254 | function [GUESSmat]=multiZplot(P,Sim,T,w_x,Z_x,popt,pci)
%MULTIZFIT simultaneous multiple Z-spectra plotting, e.g. Z(B1)
%
% GUESSmat = multiZplot(P,Sim,T,w_x,Z_x,popt,pci)
% simulated and plots multiple Z-spectra generated by parameters P, Sim and T
% using Bloch-McConnell solutions
% if given, the function plots also... |
5a83a41bbcfd3cfdaf81ad4ab927cbd9508f9c7c37f89234b0eee10303bfe51d | MATLAB | 8,299 | 229 | function Mub_stitch(target, P2path, datapath,disp,mosaic,pxlsize,islice,pattern,sys,ds,stitch)
%% define grid pattern
% add subfunctions for the script
addpath('/projectnb/npbssmic/s/Matlab_code');
result=target;
id=islice;
xx=disp(1);
xy=disp(2);
yy=disp(3);
yx=disp(4);
% mosaic parameters
numX=mosaic(1);
numY=mosaic... |
1493645bb49dfb7117adccc256749c6d4245708957156f4b8140109be65fd212 | MATLAB | 8,300 | 231 | function fn_view_recon_stat(SBJ, proc_id, stat_id, an_id, view_space, reg_type, show_labels, hemi, mirror, plot_out, varargin)
%% Plot a reconstruction with electrodes colored according to statistics
% FUTURE 1: this is a static brain, need to adapt to a movie!
% FUTURE 2: add option for stat_var to be a cell with ... |
1c80ab417c097ec93808323cd1fc24fab61537331e4f3a827eded87cf53f74fb | MATLAB | 8,306 | 202 | function SBJ02_preproc(SBJ,proc_id)
%% Preprocess data using fieldtrip
% Inputs:
% SBJ [str]- name of the subject
% proc_id [str] - name of the pipeline containing proc_vars struct
% Parameters
psd_bp = 'yes'; % plot psds after filtering?
psd_reref = 'yes'; % plot psds after rereferencin... |
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