sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
831e0cdbdee52a55a8fb92f12325a0eb8e6575795de2409e52291e086c3a8f46 | MATLAB | 11,451 | 309 | %% Spike trigerred power plots
clear all
%close all
%% Load files
cell_id=[];Is_ratio3=[];d_id=[];
pT=[];pT2=[]; nn=0;nn1=0;
CHANNEL=1; DD=[]; EE=[];
i_motion_threshold=300; % image motion threshold
sw_t=3;
for gh=[ 1 2 ]
if gh==1
%cd('/home/hanlabadmins/eng_handata/eng_research_handata2/Hua-an_Tse... |
5cc6ea9c765af252c7279ef519892be041a8a15c23fa1f317b67d679bcc3b4d2 | MATLAB | 11,512 | 292 | function h = biplot2(coefs,varargin)
%BIPLOT Biplot of variable/factor coefficients and scores.
% BIPLOT(COEFS) creates a biplot of the coefficients in the matrix
% COEFS. The biplot is 2D if COEFS has two columns, or 3D if it has
% three columns. COEFS usually contains principal component coefficients
% ... |
154501438878606be47eee6b611df0ae1c574d11aaacf5d2addd66c1862828ee | MATLAB | 11,627 | 366 | %filename is a binary file acquired with spikeGLX (imec or NI)
%ch is channel numbers to apply gain correction to (1 based). Other
%channels will be loaded but not gain corrected
%sSec is start time of data to pull, in sec
%nSec is number of seconds to pull
function [dataArray,tVec, meta]=readSGLXData(file... |
457815ffd7c6639cd17ded988c7b4ece26e6581237b64c457f9de8df8dc7347e | MATLAB | 11,807 | 364 | %addpath(genpath('\\engnas.bu.edu\Research\eng_research_handata\EricLowet\Scripts\'))
%addpath(genpath('Z:\EricLowet\Scripts\'))
clear all
pT=[];pT2=[]; nn=0;
INT1=[];INT2=[];
sw_t=2;
for gh=[1 2 ]
if gh==1
%cd('/home/hanlabadmins/eng_handata/eng_research_handata2/Hua-an_Tseng/Data/SomArchon_S... |
6f738a195422d8d6a8118033182e76f8ec976950e569ab110f3181d504c41af6 | MATLAB | 11,830 | 257 | % Preprocessing script that will segment data and filter data, allowing for
% artifact rejection and independent component analysis
%
% Copyright (C) 2019, Thomas Kustermann and Marzia De Lucia
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of th... |
5be991faab47a67792dc52e7900cbbb636c72e7aca7b8f03a9556b7a23ae9bc8 | MATLAB | 11,866 | 337 | %% Spike trigerred power plots
clear all
%close all
%% Load files
cell_id=[];Is_ratio3=[];d_id=[];
pT=[];pT2=[]; nn=0;nn1=0;
CHANNEL=3;sw_t=3;
i_motion_threshold=0.05; % image motion threshold microns/ms
for gh=[1 2]
if gh==1
%cd('/home/hanlabadmins/eng_handata/eng_research_handata2/Hua-an_Tseng... |
c672ddcd74e44f2d91e2c7afbaa1007939f0f0eaed4d97a942bcf693fcc0bf85 | MATLAB | 11,894 | 388 | %must run the following
%Fig8_relateconnectivityToPath.m
%Fig8_matchSubToPathInfo
H2=figure(2)
clf
plotg1=[1 2 3 4];
panelAll = panel();
panelAll.pack(4,6);
panelAll.de.margin = 1;
panelAll.marginbottom = 0;
panelAll.margin = [1 1 1 1];
Tau1TDP0=strcmp(PathInfo_T.Group,'tau');
PSP1= strcmp(PathInfo_T.subgroup(Tau... |
e9f13695d9e6d0c5db2ca2903a09b40ae9cfc72f42cf20bbe5c43f369932e7c7 | MATLAB | 11,963 | 238 | % plot behavior profiles under different LED intensities
load('reference_embedding.mat')
relevant_track_fields = {'BehavioralTransition','Frames','TapVoltages','LEDVoltages'};
%select folders
folders_optotap = getfoldersGUI();
% specify tracks of stimuli condition
LED_and_Tap=1;
LED_only=0;
Tap_only=0;
%Global calib... |
ecfed6b8565de5caaab169c1da576b63b860a34186abbba626741ff4cbb2dd7b | MATLAB | 12,022 | 249 | function [] = PlotBehavioralMappingExperimentGroup (LNPStats, meanLEDPower, stdLEDPower, L, density, xx)
%Takes in structure LNPStats and plots them depending on the settings
% Detailed explanation goes here
fps = 14;
BTA_seconds_before_and_after = 10;
BTA_seconds_before = BTA_seconds_before_and_after;
... |
9f1153c1f8905ff169cad73ac5a0569a650193dcc36837bea326167737a23f44 | MATLAB | 12,030 | 338 | function [ P, Tx, Ty, Tz] = dTrilinears(T,x,y,z,hx,hy,hz,bc)
% Rena 02/20/2017: allows mass to enter/leave through boundaries so mass is
% not necessarily conserved.
% Use linear interpolation to evaluate (approximate) the values of T in the
% grid (x,y,z)
% That = T(x,y,z) to be moved, necessary nly for the derivative... |
e4ea16b7e6a4837bded5ccf8b445efdc84fef7903f5bc8f676375e2634897942 | MATLAB | 12,140 | 219 | function logOddsLR = GLMMultiModels(obj, tag, P)
if ~exist('P', 'var'); obj.modelString = tag; end
[obj.blockData.audValues, uniA] = deal(unique(obj.blockData.tri.stim.audDiff));
[obj.blockData.visValues, uniV] = deal(unique(obj.blockData.tri.stim.visDiff));
uniA = sort(uniA, 'descend'); uniV = sort(uniV, 'descend');
... |
4e272460491384419047c01464b4314cc1311b522cc40d8f838b1a6351deec14 | MATLAB | 12,168 | 440 | %dorsAttnLabels = contains(LabelLUT.Label_Name2,'DorsAttn')';
%ventAttnLabels = contains(LabelLUT.Label_Name2,'VentAttn')';
%limbicAttnLabels = contains(LabelLUT.Label_Name2,'Limbic')';
%currNetwork=dorsAttnLabels;
%saveName='DorsalAttn';
%currNetwork=ventAttnLabels;
%saveName='VentralAttn';
%currNetwork=limbicAt... |
da2d028fcfc4a787adf0c175a0854041a4482b307411a6b936a0ccf3fde46062 | MATLAB | 12,197 | 306 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Calculate spike train distances
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%Extract the spike trains for the metrics.
Hold = cell(size(allspiketimes,2),size(allspiketimes,3));
Check = cell(size(allspiketimes,2),size(allspiketimes,3));
for i = 1:size(allspiketimes,2) %# of trials
f... |
925ef7d8aadbf7779568ef9a814a3888d80bd45ff3051de00a4b7e2b9002a5da | MATLAB | 12,271 | 249 | % Predict outcome from power spectra in training and test sets
% Preprocessing script that will segent data, filter the, allow for
% artifact rejection and independent component analysis
%
% Copyright (C) 2019, Thomas Kustermann and Marzia De Lucia
%
% This program is free software: you can redist... |
4077a67c713edb0287f43f23e638ccd52923502a5967271dff0d6bc88a35f32b | MATLAB | 12,283 | 254 | function EMG_proper = BWfilt(sigToFilt, varargin)
%% Based on Fasano, A., & Villani, V. (2014). Baseline wander removal for bioelectrical signals by quadratic variation reduction. Signal Processing, 99, 48-57.
% This function filter out baseline wander also called baseline fluctation
% from classic EMG signal
% Con... |
c45b3ac7e1af7a71f077fe6971996d4b044fc80e2e64e64912cf970538944362 | MATLAB | 12,283 | 439 | %dorsAttnLabels = contains(LabelLUT.Label_Name2,'DorsAttn')';
%ventAttnLabels = contains(LabelLUT.Label_Name2,'VentAttn')';
%limbicAttnLabels = contains(LabelLUT.Label_Name2,'Limbic')';
%currNetwork=dorsAttnLabels;
%saveName='DorsalAttn';
%currNetwork=ventAttnLabels;
%saveName='VentralAttn';
%currNetwork=limbicAt... |
2e2a1919e2bf2dcc6fe8c764f4598ad6679ba7260370391ad1056f9955999829 | MATLAB | 12,310 | 212 | function dateRange = keyDates(subjectID, dataTag)
%% A funciton to get the "key dates" for a mouse, based on a tag for the type of data requested.
%NOTE: These are manually defined date ranges (by Pip) based on which mice were used for which experiments, and when they were used.
%INPUTS(default values)
%subjectID(requ... |
11dafde493968052a3e3ad845e1627a042ecadacee0b7fb36af361b9d8449ffe | MATLAB | 12,375 | 316 | function [X,ndx,dbg] = natsort(X,xpr,varargin) %#ok<*SPERR>
% Alphanumeric / Natural-Order sort the strings in a cell array of strings.
%
% (c) 2017 Stephen Cobeldick
%
% Alphanumeric sort of a cell array of strings: sorts by character order
% and also by the values of any numbers that are within the strings. The
% def... |
9caed0c17852642e3caf1a232b7756c14be9b0de95629e64f83e34f2000d2c18 | MATLAB | 12,616 | 253 | function gladpar = getGLADpar(tag,type)
% Created by Xinan Chen on 03/24/2021.
% This function returns parameters corresponding to the input 'data_name' and analysis type
% Input: type := 's' if run for speed and Peclet maps; 'v' if run for pathlines w./w.o. endowed values
% Output: 'glad_par' := structure contai... |
c80b12742a2576ff725222c1927e8b54baf3e7818b6b341a68ae8c5a12203ec7 | MATLAB | 12,656 | 245 | load('reference_embedding.mat')
load('C:\Users\mochil\Dropbox\LeiferShaevitz\Papers\mec-4\AML67\behavior_map_no_subsampling\Embedding_LNPFit\LNPfit_behaviors_reordered_20171030.mat')
LNPStats = LNPStats_directional_ret;
meanLEDPower = meanLEDPower_directional_ret;
fps = 14;
number_of_behaviors = max(L(:))-1;
BTA_secon... |
27b3c101a9674f41be1382e9b6c6be2a63337d61366bfd4aad1f4ca5c13aa8b0 | MATLAB | 12,672 | 280 | %2.4. Statistical analysis
%2.4.1. Functional connectivity and ICC calculation
% In this code, functional connectivity and its reliability were calculated for the following
% manuscript: "" using the following dataset: https://openneuro.org/datasets/ds004386
% NOTE:
% run this script x4 times with different input da... |
5e790c646f7a7a036ffc09d056aeaa96e0fd09247ae26f6bca5d010111a26974 | MATLAB | 12,778 | 502 | function [c,imap,xm,ym] = dspCMap(map,ChanPos,varargin)
% dspCMaocp - Display topographic scalp maps
% ----------------------------------------
% Copyright 2009-2011 Thomas Koenig
% distributed under the terms of the GNU AFFERO General Public License
%
% Usage: dspCMap(map,ChanPos,CStep)
%
% map is the 1xN voltage map ... |
e6b9cf0ec2ccb5afc068805ad0c9c05d19527512be3b04ad9824e822ca4efa9e | MATLAB | 12,810 | 151 | function moto = MotoTrak_Controller_V1p4_Serial_Functions(moto)
%MotoTrak_Controller_V1p4_Serial_Functions.m - Vulintus, Inc., 2015
%
% MotoTrak_Controller_V1p4_Serial_Functions defines and adds the Arduino
% serial communication functions to the "moto" structure. These functions
% are for sketch version 1.4 and... |
86b69b6089960ee4b37f3eda1bc38dcf0950256636276c831e47635fc8ec4225 | MATLAB | 12,903 | 254 | function DynamicPredictions_STATS_ERFdynamicRSA_ROIsource(cfg,~,iroi)
restoredefaultpath
% You can run this function locally (by looping over subjects), or send to a cluster (which I did using the accompanying "cluser_shell.m" function)
% set some directories depending on running this locally or on a cluster:
if ... |
8a5610e5f005ad92fce0eb40736dd1116e202606589ce6894b2a3c2da5fb9bfd | MATLAB | 13,037 | 411 | function [img, info]=read_nifty(filename)
% [image info ] = read_nifty(filename)
% Adapted from the code
% "Tools for NIfTI and ANALYZE image"
% by Jimmy Shen
% Available at http://www.mathworks.com/matlabcentral/fileexchange/8797-tools-for-nifti-and-analyze-image
if ~exist('filename','var')
error('Usage: nii =... |
3118f301ea25ef4d7c661a396f2d3ebb20265658bdb1b50205458985a9b998e0 | MATLAB | 13,041 | 369 | %% Compare tuned chans on a few different days
binSize = 20;
kinI = [2,7]; %1D position and velocity
kinTitles = {'Index Position', 'Index Velocity',};
monkey = 'Batman';
date = '2021-08-18'; %wrist
runs = 3:5;
synced = 0;
includeEMG = 0;
useCAR = 1;
runGroup{1} = [1,2,1]; % Label each run by no... |
1154533fe9e8aab77c535aa041cbe3999a92b9579bc3b99d7109a6a61f027bca | MATLAB | 13,112 | 292 | % Written by Aleh Sudakou (https://www.researchgate.net/profile/Aleh-Sudakou)
% Nałęcz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences
% This is one of the codes shared on https://github.com/asudakou/Analyzing_TD-NIRS
% Last updated: 20 May 2023
%% Description:
% This funct... |
7b83ecda5f957c3570f73e4124bd8ed0eabf60534465456f5a34d14bb02b3bf0 | MATLAB | 13,193 | 327 | function [theta_frustum,circles,points]= intersect_meshSphere(frustum, sphere_radius, mesh)
%
%%
% from the mesh select elegible vertices to intersect. That happens only if
% at least two points of a triangle are at different sides of the spherical
% surface.
th_dist = 1E-06;
th_angle = 0.5; % 0.5 degrees
points = NaN... |
ead347ea56f405be6d0fb1a31b92489aded7405f9feb275a74c555a137ddfcfa | MATLAB | 13,255 | 409 | %% Anaysis scripts in support to:
% Despite impaired binocular function, binocular disparity integration
% across the visual field is spared in normal aging and glaucoma
% Maiello, G. and Kwon, MY
%% Disparity Selection and Integration Model Comparison
% Author GM; Nov 2022
clearvars -except fid
% For rep... |
83108fae84fd11e082b55b9119beb0c6cd17b8cdcba68ba1387d475ec88554e7 | MATLAB | 13,308 | 244 | %
% For all the decoding goodies ...
%
function figure_7_decoding
[all_dat settings] = get_all_data_pstim;
% --- setup plots
fh = figure ('Position',[0 0 1200 600]);
example_mouse_auc_red_ax = subplot('Position', [0.05 0.5 .15 .4]);
example_mouse_auc_red_zoom_ax = subplot('Position', [0.75... |
4afb0285bbf58238feb8ae85daff0c0e6f368a6a0ec1166df59f0dd21930c4bd | MATLAB | 13,373 | 193 | function [warped] = ft_warp_apply(M, input, method, tol)
% FT_WARP_APPLY performs a 3D linear or nonlinear transformation on the input
% coordinates, similar to those in AIR 3.08. You can find technical
% documentation on warping in general at http://bishopw.loni.ucla.edu/AIR3
%
% Use as
% [warped] = ft_warp_apply(M... |
e7120cbaf2f330b85e60186b17dbf0349044fbf1e3b93af1fc1111f18e09b289 | MATLAB | 13,471 | 359 | % Compute statistical contrast of two groups (e.g. survivors and
% non-survivors of coma)
% - requires input of subjects from rs_psd_subjects_for_study.m
%%
% Preprocessing script that will segent data, filter the, allow for
% artifact rejection and independent component analysis
%
% Copyright (C) 2019, ... |
64862b3cc14ae62decfb15c1f9dff9a26c7aec6e58920269d9345e6b390cc633 | MATLAB | 13,537 | 309 | %not used in paper
folders_tri_ret = getfoldersGUI();
load('reference_embedding.mat')
relevant_track_fields = {'BehavioralTransition','Path','Frames','LEDPower','LEDVoltages','Embeddings','Velocity', 'LEDVoltage2Power'};
[allTracks_tri_ret, folder_indecies, track_indecies ] = loadtracks(folders_tri_ret,relevant_track... |
a78fd1a5c4c21f3f62b8558fa57cbce2cdd48ada525518a8a42618894b46218e | MATLAB | 13,596 | 281 | % In this code, the thermal noise removal step which is listed for the following
% manuscript: "" section: 2.3.3.2 Thermal noise
% In order to run this code the Spinal Cord Toolbox (version 4.2.2 or higher -
% note that for the manuscript version 4.2.2 was used)
% and FSL should be added to the bash profile of the u... |
25abd1912a2fa614febd04c48a698e1ead699dce0609823be8889d3f24a570fb | MATLAB | 13,615 | 364 | clear
close all
clc
chanlocs = readlocs('cap64.loc');
path_temp = 'D:\Participant Folders_new\'; %TCD Laptop
% save_path = 'D:\Participant Folders_new\';
%% Create paths for subjects
subject_folder = {'LK_07_04_14','AR_08_04_14','MH_14_04_14','AA_15_04_14','NT_16_04_14', ...
'OF_28_04_14','RO_25_04_14','PR_20_04... |
a26705c0e28bba3e4eee39de24db2a072ced1514cfa73969fd3bf0118950f753 | MATLAB | 13,623 | 339 | % Script to define all Inputs for PLS for Medical Image Processing Toolbox
%
% Parameters to be defined in this script are:
%
% - input : struct containing input data for the analysis
% - .X : N x M matrix, N is #subjects, M is #imaging variables
% - .Y : N x B matrix, B is #behav... |
dc7377bbe304271ae1f82dd42e51ec9d346653e83c60fbe6fbd08f3d1df29d22 | MATLAB | 13,655 | 343 | % This script calculates the average response to a bar of varying widths
% traversing vertically through two user defined analysis windows
% User input required to the direction to analyse and start positions for analysis windows
clear all
selpath=uigetdir; % Select the folder containing the single dataset to analyse... |
f5c10729dc8a9a37fe92641101b910c8c57c7e8dec608b4bc532f3b098bc327f | MATLAB | 13,702 | 251 | function figure_5_intraday_stability (force_redo)
if (nargin < 1) ; force_redo = 0 ; end
% --- get data
[all_dat settings] = get_all_data_pstim;
rep_drift_dat = get_representational_drift_data(all_dat, settings, force_redo);
% --- setup figures
ax = [];
fh = figure ('Position',[0 0 ... |
78ab3a92b53cef4833f48045b98b9029857f45ea26a2015fe90a4fee96fa41c0 | MATLAB | 13,746 | 399 | function [toa_diff,toa,IACC,Obj] = SOFAcalculateITD(Obj,varargin)
% SOFAcalculateITD: Estimate ITD from a binaural signal
% Usage: itd = SOFAcalculateITD(data,mode,threshlvl,lowpass,butterpoly,upper_cutfreq)
%
% Input parameters:
%
% data: SOFA object or IR matrix with dimensions:
% ... |
18bd69a89b0939efba3939ed74f2e97edb4f5ceb68b6d8c0d57a989eaf307e8d | MATLAB | 13,869 | 319 | %LoadDataSarah
%this sets which mode of analysis we're doing
%Set to 1 for Figures 4a & 4b
%Set to 2 for Figures 4c & 4d (and then run Fig4cd_EdgeConnectedToHubs.m)
ModeOrig1_HubAnalysis2 = 2;
%this flag determines if we're looking at adjacent or
%epicenter relationships (Figure 4a/c vs 4b/d)
flagEpi0Adj... |
3a18cfe89c8e86e0b365b3d093a2e10d6e4b425ab8c10f74ec1e417826fd1953 | MATLAB | 14,007 | 364 | % pop_loadbv() - load Brain Vision Data Exchange format dataset and
% return EEGLAB EEG structure
%
% Usage:
% >> [EEG, com] = pop_loadbv; % pop-up window mode
% >> [EEG, com] = pop_loadbv(path, hdrfile);
% >> [EEG, com] = pop_loadbv(path, hdrfile, srange);
% >> [EEG, com] = pop_loadbv(path, hdrf... |
a34c5e6e8d1d1014b4a1d5b9fbb149d4380a4254064293a650fd5299c4297f60 | MATLAB | 14,136 | 379 | function [sens] = ft_read_sens(filename, varargin)
% FT_READ_SENS read sensor positions from various manufacturer
% specific files. The following acsuisition system and analysis
% platform EEG and MEG file formats are currently supported:
%
% asa_elc besa_elp besa_pos besa_sfp yokogawa_ave yokogawa_con
% yokogawa_... |
862189bba9395bc7e02f5259f62fb680edc43e632fd835afe8b25c481d1d948e | MATLAB | 14,276 | 171 | function moto = MotoTrak_Controller_V1p4_Serial_Functions_Deprecated(moto)
%MotoTrak_Controller_V1p4_Serial_Functions_Deprecated.m - Vulintus, Inc., 2015
%
% MotoTrak_Controller_V1p4_Serial_Functions_Deprecated is the deprecated
% version of MotoTrak_Controller_V2pX_Serial_Functions, which defines and
% adds th... |
ce2a039a3bcc063c56fc06fd568f137b0cf76802b8c930694698af43d0efd28e | MATLAB | 14,384 | 518 | %3. Results
% In this code, results and figures associated with the sub-sections of following section are created
% Section 3.2. Impact of noise sources on resting-state functional connectivity and its reliability
% Please see:
% manuscript: ""
% and for the following dataset: https://openneuro.org/datasets/ds0043... |
7dcc9e4949d037902f76181a2cebd0b8e0f2ad67ad06b04be8d322d718764c79 | MATLAB | 14,410 | 222 | function figure_4gh_activity_and_behavior
top_frac = 1; % take ALL neurons
single_plot (top_frac, 1:3); % early
single_plot (top_frac, 6:8); % late
function single_plot (top_frac, stat_di)
% --- pull data
[all_dat settings] = get_all_data_pstim;
disp(sprintf('Top frac: %0.2f day %d to %d', to... |
8aa29e2453e1cb6ad8f4bb68f4041064fbf4c3bbb8d667b5f0793fdb6c218823 | MATLAB | 14,438 | 508 | clear all; close all; clc
rng('default')
addpath('results/roc_aucs')
addpath(genpath('utils'))
%metadata
results_reg_meta = load('regression_metadata.mat');
%EHG
results_reg_EHG = load('EHG_regression.mat');
%combined
results_reg_combined = load('regression_combined.mat');
%% Open figure
linewidth ... |
2ce4d2d8ff7a8fcbfb95872ab1436cf5c1346ec1549750e7e8b1e18beeea14b9 | MATLAB | 14,472 | 397 | networkNames={'DorsAttn','VentAttn','Limbic','SomMot','Default','Cont','_Vis_','All'};
H2=figure(10)
%clf
panelAll = panel();
panelAll.pack(2,4);
panelAll.de.margin = 1;
panelAll.marginbottom = 1;
panelAll.marginleft = -10;
panelAll.margin = [0 0 0 0];
NN = 1000;
NetworkNames=cell(NN,1);
ROIName1=cell(NN,1);
ROINam... |
d033dc35710413e9f0394de85481006619545a8df3d66734581e2088b4381298 | MATLAB | 14,525 | 258 | % [op Jan 2023] extract metrics from the output of the neurodynamic model
% by running over all images in a set (which_task = 'extract_statistics'),
% or extract the full model activity for a selection of images
% (which_task = 'extract_full_activity';)
% ===== choose task =====
which_task = 'extract_statistics'... |
eee59bcee45517f78f1f03f0a4607dd4a5a126fd6a116b4f35b1f46e4201e62c | MATLAB | 14,526 | 196 | %Script to plot Extended Data Figure 5: behavioral performance segregated by trial type
%
%To use this script, set path to animal_behavioral_data.mat file
%% Parameters
[all_dat settings] = get_all_data_pstim;
behavioral_data_path = [settings.base_dir filesep];
%% Get data
%Load animal behavioral data
try
load(... |
a2836cb8c541b76d3300881fe60530da46bb5000dea885cbfc5b8a37c1d40a9f | MATLAB | 14,611 | 327 | % This script loads saved outputs from Figure8_HorizontalBarSizeTuning_SpikeHistograms,
% Figure10_VerticalBarSizeTuning_SpikeHistograms and Expt_Screen_Info
% Using this data it plots the average response to a bar of varying heights
% traversing horizontally along multiple trajectory heights and the average
% respons... |
17e70edc1118a4f06a6973b790b144d4c8100e8301ecb12faaa6594aecb35cba | MATLAB | 14,717 | 626 | function [V,nr,nre]=lcon2vert(A,b,Aeq,beq,TOL,checkbounds)
%An extension of Michael Kleder's con2vert function, used for finding the
%vertices of a bounded polyhedron in R^n, given its representation as a set
%of linear constraints. This wrapper extends the capabilities of con2vert to
%also handle cases where the ... |
77cb0d78d76f34798ebb5be1a9cd7fe9195420512fde6f9602ca6684a7dd68b3 | MATLAB | 14,765 | 416 | %%%%%%%%%%%%%%%%%%%%%%%%%%
% Calulate Firing Rate
%%%%%%%%%%%%%%%%%%%%%%%%%%
FR = zeros(size(allspiketimes,2),size(allspiketimes,3));
%Count number of spikes per trial for each neuron
for i = 1:size(allspiketimes,2) %# of trials
for j = 1:size(allspiketimes,3) %# of neurons
a = allspiketimes(:,i,j);
... |
fcd035460a7c9b07d5ff213e1012051080621d0d61c3365d32ce5f6950554640 | MATLAB | 14,815 | 715 | clear all
close all
rng shuffle
clc
T=100;
time=1:T;
a=zeros(1,T);
o=zeros(1,T);
ml=zeros(1,T);
mr=zeros(1,T);
pl=zeros(1,T);
pr=zeros(1,T);
Gl=zeros(1,T);
Gr=zeros(1,T);
fl=zeros(1,T);
fr=zeros(1,T);
tt=1:T;
Pl=(tt<=T/2)*0.5+(tt>T/2)*0.5;
Pr=(tt<=T/2)*1+(tt>T/2)*1;
vw=0.4;
am=0.05;
po=0.1;
mo=0;
%initial valu... |
2b053dadbc9d4ed569553a9c514cab52f6543a06dce0ffb04b57f5589b00b701 | MATLAB | 14,829 | 392 | function DynamicPredictions_PLOTS_ERFdynamicRSA_ROIsource(cfg)
addpath('\\XXX\ActionPrediction\toolboxes\fieldtrip-20191113');
addpath(genpath('\\XXX\ActionPrediction\code'));
addpath(genpath('\\XXX\matlab_toolboxes\CoSMoMVPA-master'));
cfg.path = '\\XXX\ActionPrediction';
ft_defaults
%% some parameters for... |
9e55326a4e46029d654fe93f733d4b2da97c21bfbb402460b079bdb0acd322b0 | MATLAB | 14,837 | 287 | function figure_6_interday_stability
% --- get data
[all_dat settings] = get_all_data_pstim;
to_dat = get_pstim_turnover_data;
to_dat_pstim = to_dat.to_dat_pstim_presp;
% --- setup figure
fsize = 10;
% example data get
ex_ani = find(strcmp(all_dat.settings.anims, 'an293157'));
... |
2054c896840000720976c1c61b692155211f402b033142ad0d6044f27667d1b1 | MATLAB | 14,904 | 343 | close all;
% load data
load('contrast_vals_g_brc');
% global contrast
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% mean (not included in figure)
figure; hold on; setupfig(2,1.5,8);
air_h = histogram(air.meanLinC,linspace(-0.1,0.1,10),'facecolor',[0.1 0.45 0]);
w... |
e79ac2848d2528beba3df35bfca28427f5124c4290e1fc84c0151e5952ec4da7 | MATLAB | 15,070 | 546 | function syncData = jbsi_synchrony(a, b, sw)
% jbsi_synchrony JBSI synchrony analysis of Aric Agmon
%
% syncData = jbsi_synchrony(a, b, sw) computes the Jitter-Based
% Synchrony Index between spike trains a and b for the synchrony
% window sw.
%
% a and b are vectors of spike times, in seconds.... |
33a5b383168f78d2efb5086211cb76c3ddaa4330d9414a298fcad0865761b663 | MATLAB | 15,093 | 718 | clear all
close all
rng shuffle
clc
T=100;
time=1:T;
a=zeros(1,T);
o=zeros(1,T);
ml=zeros(1,T);
mr=zeros(1,T);
pl=zeros(1,T);
pr=zeros(1,T);
Gl=zeros(1,T);
Gr=zeros(1,T);
fl=zeros(1,T);
fr=zeros(1,T);
tt=1:T;
Pl=(tt<=T/2)*0+(tt>T/2)*0;
Pr=(tt<=T/2)*0.5+(tt>T/2)*0.5;
vw=0.4;
am=0.05;
po=0.1;
mo=0;
%initial value
a... |
38865e3cae43c069c484b0e2c929853059cf9ed30f3273c413cd8ba76db01eb9 | MATLAB | 15,137 | 370 | classdef VectorImageType < ImageType
properties(GetAccess = 'public', SetAccess = 'public')
datax=[];
datay=[];
dataz=[];
end
methods(Access = public)
%constructor
function obj = VectorImageType(size,origin,spacing,orientation)
%obj = obj@ImageTy... |
f324ed7b316689e942d326d966202bfe02936dbce175f64f0988e7dcf57e8105 | MATLAB | 15,173 | 421 | %% Spike trigerred power plots
clear all
%close all
%% Load files
cell_id=[];Is_ratio3=[];d_id=[];
pT=[];pT2=[]; nn=0;nn1=0;
CHANNEL=1;
i_motion_threshold=300; % image motion threshold
sw_t=3;
for gh=[ 1 2 ]
if gh==1
%cd('/home/hanlabadmins/eng_handata/eng_research_handata2/Hua-an_Tseng/Data/SomArch... |
abf0a0f61e26b8ca27347b51e46b82f6f9d423d704ea835ff8ffa3a8d8c8115a | MATLAB | 15,202 | 507 | function [bb,dev,stats,loglikeli,iter,b_stack] = glmfit_YC(x,y,distr,varargin)
if nargin < 2
error(message('stats:glmfit:TooFewInputs'));
end
if nargin < 3 || isempty(distr)
distr = 'normal';
else
distr = lower(distr);
end
% Determine the syntax.
if nargin < 4
newSyntax = false;
else
arg = vararg... |
95e0c51a1888eb0a555767cd381d89c71f2f7a6cf187c83b58317b9a55eec7a0 | MATLAB | 15,368 | 407 | clear
close all
clc
chanlocs = readlocs('cap64.loc');
path_temp = 'D:\Participant Folders_new\'; %TCD Laptop
% save_path = 'D:\Participant Folders_new\';
%% Create paths for subjects
subject_folder = {'LK_07_04_14','AR_08_04_14','MH_14_04_14','AA_15_04_14','NT_16_04_14', ...
'OF_28_04_14','RO_25_04_14','PR_20_04... |
4c0983caf6f77b829d4444d10282ec3a2b4a3cbca3d47a4cac281703b6974ed1 | MATLAB | 15,468 | 450 | function [mri] = ft_read_mri(filename, varargin)
% FT_READ_MRI reads anatomical and functional MRI data from different
% file formats. The output data is structured in such a way that it is
% comparable to a FieldTrip source reconstruction.
%
% Use as
% [mri] = ft_read_mri(filename)
%
% Additional options should be ... |
1da58b9f1e0b1006691f713b31e4686bdd83e46947e453989dcb4325ed8f7a12 | MATLAB | 15,473 | 244 | %% 3DEPI distortion correction piplines at 7T for phantom data
% No-correction, B0 field mapping and reversed-PE (fsl_topup) techniques
% V Malekian, FIL Physics
clc;clear;close all;
addpath('/export/home/vmalekian/MI_Distortion/NIfTI_20140122/')
addpath('/export/data/vmalekian/MI_Distortion/mi/')
addpath('/export/dat... |
dadae78166265b97e9349e79c4475eecf6121595b0d5ca33a3bf91d5e9665953 | MATLAB | 15,719 | 283 | load('reference_embedding.mat')
%load tracks
% relevant_track_fields = {'BehavioralTransition','Path','Frames','LEDPower','LEDVoltages','Embeddings','Velocity', 'LEDVoltage2Power'};
relevant_track_fields = {'BehavioralTransition','Frames'};
%select foldersta
folders_optotap = getfoldersGUI();
num_stimuli = 1;
normali... |
50da06c0922a3d1641f5b39f1bf5538cdb7a45e9209d69d0b6aeacf8d98cc842 | MATLAB | 15,745 | 385 | % clear
% close all
% clc
% subject_folder = {'AR_08_04_14'};
% allsubj = {'AR'};
%
% s = 1;
% blocks = [1:9,11:16];
% badchans = [14,15,43];
% path_temp = 'D:\Participant Folders_new\';
%
% clear files matfiles ET_files ET_matfiles; k=0;
% for n=1:length(blocks)
% k=k+1;
% files{k} = [path_temp subject_folde... |
4f4a051b8575af83ad191327bb86ef5494a7e47f3e97f28c58224d750f6def62 | MATLAB | 15,750 | 386 | close all
clear all
% Some parameters
samprate = 50000; % 50k sampling rate
fband = 32; % Frequency band in Hz
twindow = 1000*6/(fband*2.0*pi); % Window length in ms - 6 times the standard dev of the gaussian window
winLength = fix(twindow*samprate/1000... |
a3d6a120c9a1b7ee8288122a1de867b395ff2e219a91edf5527b64b0bc24001d | MATLAB | 15,840 | 536 | function dispSpont_saccade_spikeinfo_MIandtiming
%% AGGREGATE DATA
token1 = '_probe_spont_saccade';
token2 = '_probe_spont_saccade_kernvar';
token3 = '_probe_spont_waveform';
fnames1 = dir(['*' token1 '.mat']);
fnames2 = dir(['*' token2 '.mat']);
fnames3 = dir(['*' token3 '.mat']);
FR_pop = [];
conf95_pop = [];
FR_bt... |
be6220f2170ee548a26225e194a3bfa880e8b1aad4c6e70c3cfaf95f44943675 | MATLAB | 16,059 | 452 | function [M,meta,h]=SOFAplotHRTF(Obj,type,varargin)
% SOFAplotHRTF(OBJ, TYPE, R, DIR, COLOR) plots the R receiver of HRTFs given in OBJ.
% The following TYPEs are supported:
% 'EtcHorizontal' energy-time curve in the horizontal plane (+/- THR)
% 'EtcMedian' energy-time curve in the median plane (+/- THR)
% 'M... |
ddb3c86d97d33055c19b9b122225a339e61eef1e946d62ee7ea2658400a6af9e | MATLAB | 16,183 | 403 | function result=movingmean(data,window,dim,option)
%Calculates the centered moving average of an n-dimensional matrix in any direction.
% result=movingmean(data,window,dim,option)
% Inputs:
% 1) data = The matrix to be averaged.
% 2) window = The window size. This works best as an odd number. If an even... |
6ab7daae007d0a5f7cd2becec12e534b76500a0e2ba5e093ee127e11b9720601 | MATLAB | 16,190 | 451 | function dispSpont_saccade_power
%% AGGREGATE DATA
% this one takes a while so I saved the output to a separate file that can
% just be loaded on its own: 'saccade_power_pop.mat'
token = 'power_200ms';
fnames = dir(['*' token '.mat']);
spectrogram_sess = cell(1,4);
spectrogram_sacc = cell(1,4);
spectrum_sess = cell(... |
4dca59480219f349d01e52ee099e59e2934311ea65462e24a630f8d943fbc05c | MATLAB | 16,244 | 441 | function sound_out = modfilter(sound_in, samprate, fband, method, wf_high, wt_high, wf_it, wt_it, filter)
% % Filters the sound by filtering the modulation spectrum of the sound.
% % Sound_in is the sound pressure waveform.
% % samprate is the sampling rate
% % fband is the width of the frequency band - use 32 Hz for s... |
376c9090086c939bb4dafb3fed445bd97957c0482a83ebbb657bd95c72d24c61 | MATLAB | 16,278 | 458 | function varargout = sRev(varargin)
% SREV MATLAB code for sRev.fig
% SREV, by itself, creates a new SREV or raises the existing
% singleton*.
%
% H = SREV returns the handle to a new SREV or the handle to
% the existing singleton*.
%
% SREV('CALLBACK',hObject,eventData,handles,...) calls the l... |
759052616622dd5dc8221e8c71f50bfd37b39090f52f4b89d74d4c0ebdd3bbb3 | MATLAB | 16,295 | 462 | clc;
close all;
clearvars;
%% Input
sourcepath ='/path2test_data'; % Full path to the experiments
nFrames = 720; % numebr of frames per time-lapse
time_pattern = ["--LO", "_T"];
nClasses = 8;
Allclasses = ["NORMAL", "NODAL", "BMP", "WNT", "FGF", "SHH", "PCP", "RA", "BOOM", "UNKNOWN", "CUT"];
MainClasses = ["NOR... |
bf531101f965aee6424aaffba323b398ee4239275f013444b176a01e84d63952 | MATLAB | 16,372 | 427 | %% Anaysis scripts in support to:
% Despite impaired binocular function, binocular disparity integration
% across the visual field is spared in normal aging and glaucoma
% Maiello, G. and Kwon, MY
%% DSF Parameters
% Author GM; Nov 2022
clearvars -except fid
Color_Young=[166,206,227]./256;
Color_AMC=[0,1... |
d4bbb2b14418cf2b65c9a03a6676684dbf3957f32ec6f1b06578373260913601 | MATLAB | 16,424 | 396 | % This script calculates the average response to a bar of varying heights
% traversing horizontally along multiple trajectory heights, within a user
% defined analysis window
% User input required to determine Y positions to analyse and start
% position for the analysis window
clear all
selpath=uigetdir; % Select ... |
de480cdf1bb103fac9f3f0111f20e0019a3438b6ce24a878b14484ab8b42ee36 | MATLAB | 16,438 | 389 | %% Spike trigerred power plots
%7274886
% 6478633
% 1700991
% 34.3%
% 10.95
% 26.26%
clear all
%close all
%% Load files =[];
Is_ratio=[];Is_ratio2=[];P_ratio=[];cell_id=[];Is_ratio3=[];d_id=[];
nn=0;nn1=0;
amount_of_timepoints=0; amount_of_timepointsMOV=0;
COH_LFP=[]; A_LFP=[]; A_Vm=[];
COH_Vm=[]... |
47f94414e925b7d14983aef0751cf833dd11cc0374750cd3058e05a098c1b028 | MATLAB | 16,477 | 578 | function [gx_final] = Rmodelinductiond_v0_1(Iitheta,struct)
%-------------------------------------------------------
% scale=wav.scale;
% orient=wav.orient;
wave=struct.wave;
use_fft=struct.compute.use_fft;
n_scales=wave.n_scales;
% make the structure explicit
zli=struct.zli;
% compute=struct.compute;
% struct.z... |
5cf19908e1bd511433a034e6422d8e322e32e400a53b034e2b5f82940b885e6c | MATLAB | 16,787 | 427 | function [type] = ft_senstype(input, desired)
% FT_SENSTYPE determines the type of acquisition device by looking at the
% channel names and comparing them with predefined lists.
%
% Use as
% [type] = ft_senstype(sens)
% [flag] = ft_senstype(sens, desired)
%
% The output type can be any of the following
% 'ctf64'... |
594128fe7dd0481bad8996105904d43c6cb32ee9d1490fd3ca09940d525eb826 | MATLAB | 16,798 | 387 | clear all
close all
clc
path = 'S:\R-MNHS-SPP\Bellgrove-data\4. Dan Newman\Participant Folders_new\';
% for i = 1:length(conditiondescrip)
% disp(conditiondescrip{i})
% end
% SW:
% par.patchloc = [-10 -6; 10 -6;]; 1 = lower left, 2 = lower
% right
% Trigger 1: coherence 30, patch 1, motion dir 270, coh motion ons... |
7e8e36288e848a45ef172461992bbc464d4c1486b68b448c9413875cd34e8fe5 | MATLAB | 17,121 | 418 | % clear
% close all
% clc
% subject_folder = {'059M_HP','093M_BR','331M_CL'};
% allsubj = {'HP1M','BR2M','CL21M'};
%
% s = 3;
% blocks = [1:16]; % 1:16
% badchans = [];
% path_temp = 'D:\Participant Folders_new\';
%
% clear paths files matfiles ET_files ET_matfiles; k=0;
% for n=1:length(blocks)
% k=k+1;
% pa... |
052414f5fa717542c629c2e2de495cd67e608a02e7322b7abf7cce681d151af6 | MATLAB | 17,139 | 458 | classdef Optimizer
properties
atlas
scan
transform_ref
scale_factor
aT
aTmap
skull_mask
initial_qual
end % properties
methods
function obj = Optimizer( a_obj, scale_factor, gaussian_px)
import electroslice.*;
% default values
if ~exist('scale_factor',... |
1271a5790a12836d6f34b85594b995dedb8004665cadfd587baafab1e65ce697 | MATLAB | 17,329 | 378 | %% EVOLUTION ALGORITHM
% to find global weights for members of population across stimulus
% conditions
% use this code with DR* data-files
% what it does:
% find global weight vector for all conditions (control only) that
% minimizes RMSE betwen population response and behavioral response accross
% condition... |
3fe7b3612736c64d8d3ffe89643224545faf3b3929d8546350657339fde329ad | MATLAB | 17,341 | 305 | function fMRI_RunFirstLevel_HGF(group)
% Process the 1st level analyses for each group
% Model used: Standard whole-brain (event-related) GLM
%
% Inputs:
% - group = 'NT' or 'ASD'
%
% Conditions:
% - Tone (in Mat_onset(:,1)
% > with 3 parametric modulators
% - Tilt (in Mat_onset(:,2)
% > ... |
69660e45b5d8e19223e053a2a0c55981b5d0defda8df6efed8bfd2e1d5e9180f | MATLAB | 17,421 | 331 | function DynamicPredictions_RUN_ERFdynamicRSA_simulations(cfg,simmod,eyeSub,iterbatch)
% You can run this function locally (by looping over subjects), or send to a cluster (which I did using the accompanying "cluser_shell.m" function)
% set some directories depending on running this locally or on a cluster:
if isf... |
a076647ca94b3418fd928e1fa1e944c10234ab2810b9ab31d54d899f3ef09373 | MATLAB | 17,426 | 520 | % GLM analysis for the Gnomes project
% Separate regressors for each cue type
%
% Other m-files required:
% EEGLAB toolbox https://github.com/sccn/eeglab
% Unfold toolbox: https://github.com/unfoldtoolbox/unfold
% /private/num2bv.m
% Author: Cameron Hassall, Department of Psychiatry, University of Oxford
% email add... |
e9b246ce0fb7f6c1185102bfdbde3ee52bd65bd4151f6404f0fe1c54a5f625ff | MATLAB | 17,513 | 448 | %% Runing the model on the condition specified by cond
tic
n_stim = 120; % Total no. of stimuli (Best take a product of 4)
t_prot = n_stim*(duration + ISI) + 2*post_stim; % Total time of the protocol (in seconds)
tmax_tot = t_eq + t_prot; % Maximum time that the simulation will reach (in seconds)
num_steps = floor... |
dcf266cd5b3f20434119ba777012fd4036fb0a2145ffdc5f5e608e311eef3916 | MATLAB | 17,597 | 440 | %% Spike trigerred power plots
clear all
%close all
%% Load files
cell_id=[];Is_ratio3=[];d_id=[];
pT=[];pT2=[]; nn=0;nn1=0;
CHANNEL=1;
i_motion_threshold=300; % image motion threshold
sw_t=3;
for gh=[ 1 2 ]
if gh==1
%cd('/home/hanlabadmins/eng_handata/eng_research_handata2/Hua-an_Tseng/Data/SomArc... |
0fc0562f433ec85fb0ee73147781ca387d3f058e5f53b44eb192a1806a5e2526 | MATLAB | 17,757 | 467 | close all
clear all
% Some parameters
samprate = 50000; % 50k sampling rate
fband = 32; % Frequency band in Hz
twindow = 1000*6/(fband*2.0*pi); % Window length in ms - 6 times the standard dev of the gaussian window
winLength = fix(twindow*samprate/1000... |
f0ea0104051eddf1e10a76c018195bb4babe1edd71ca9c6b5aa17fc60753c54a | MATLAB | 17,934 | 312 | auto_stimulus_period = true; %stimulus_period is found by autocorrelation if this is true
BTA_playback = true;
stimulus_period = 60*14-1;
starting_shift = 0;
relevant_track_fields = {'BehavioralTransition','Frames'};
load('reference_embedding.mat')
load('C:\Users\mochil\Dropbox\LeiferShaevitz\Papers\mec-4\AML67\behav... |
a58bd168a9c0586e2726a69099572c6dd66df88f66139bb6de12b5faff491197 | MATLAB | 18,057 | 339 | % This script is used to create the pictograms,raw data trace and spike
% histograms in response to a looming stimulus and a small target.
clear all
% Data shown in Figure 1 is from 201026_N03P01 (loom_filename_toload=1 and target_filename_toload=9)
selpath=uigetdir; % Select folder containing example data
cd(selpa... |
927e77769715d62393f8ef137c7558c216e8b951de2495e6ed3e82b01fc78624 | MATLAB | 18,063 | 410 | % This script crudely maps a receptive field in response to a full screen
% leading edge stimulus traversing the entire dimensions of the screen in 4
% different directions.
clear all
selpath=uigetdir; % Select the folder containing the single dataset to analyse
cd(selpath)
search_term='*-LeadingEdge_4Directi... |
dbab742fcc34bc0da1732a2d907929c1262286af2554eadd32431fabe95e7933 | MATLAB | 18,200 | 461 | function SOFAplotGeometry(Obj,varargin)
% SOFAplotGeometry(Obj) plots the geometry found in the Obj.
%
% SOFAplotGeometry(Obj, index) plots the geometry for the measurements
% given in the index.
%
% Supported conventions:
% SimpleFreeFieldHRIR
% SimpleFreeFieldHRTF
% SingleRoomDRIR
% FreeFieldDirectivit... |
bc9bb5a01f3b0d3d19c28bac8cd24cd91c41ea8591661e56385b0086fc6dc56e | MATLAB | 18,394 | 529 | function [outphase, outanatomy, patientdata] = read_parrec2DFlow(filename)
par_survey = parread(filename );
rec_survey = readrec([filename(1:end-3) 'REC' ]);
% Split the 5D 2Dflow data
data_mag = rec_survey(:,:,:,1,1);
if ndims(rec_survey)>3 && size(rec_survey,4)>1
data_oth = rec_survey(:,:,:,2,1); % ?
else
... |
83912b323d3be27ddbe29ceeaf987c0f544ec303f2983915b4a0552f5b198467 | MATLAB | 18,413 | 438 | function amplitude = ICMSandCapture(ChN, charge, choice, layer, exp_name, attempt, trial, layer1, layer2, layer3, layer4, layer5, layer6)
% Stimulation Parameters
NRep = 208; % Number of pulses in stim train
Rate = 320; % Stimulating frequency (Hz)
pulse_width = 200; % Pulse width (us)
interphase_delay = 40; % Interph... |
a3259b20a2da42fb767ef9fa8b0947c8c1d511c851ee7a23f5301c3d7b260c13 | MATLAB | 18,681 | 568 | % Prepare data for dPCA
clearvars
%% Load data
monkey = {'Joker','Joker','Joker','Batman','Batman'};
dates = {'2022-02-23','2022-03-09','2022-04-26','2021-10-12','2021-10-18'};
runsAll = {[3,4,7,8],[2,3,4,5,6],[2,3,4,5,6],[5:9],[4:7]};
runGroup = {[1,2,3,1],[1,2,3,4,1],[1,4,2,3,1],[1,2,1,2,1],[1,4,1,4]}... |
75c6ac9c30dff8fb4630c329e1036f86e806dd15281e350291c6aae9929cfd26 | MATLAB | 18,722 | 537 | function [h,ax,BigAx,hhist,pax] = plotmatrix(varargin)
%PLOTMATRIX Scatter plot matrix.
% PLOTMATRIX(X,Y) scatter plots the columns of X against the columns
% of Y. If X is P-by-M and Y is P-by-N, PLOTMATRIX will produce a
% N-by-M matrix of axes. PLOTMATRIX(Y) is the same as PLOTMATRIX(Y,Y)
% except that... |
f653b99d2463c41eb71234a9ecc50652ba500a9ac1823fcb25afeb7d95c8d700 | MATLAB | 18,970 | 453 | function amplitude = ICMSandCapture(ChN, charge, choice, layer, exp_name, attempt, trial, layer1, layer2, layer3, layer4, layer5, layer6)
% Stimulation Parameters
NRep = 208; % Number of pulses in stim train
Rate = 320; % Stimulating frequency (Hz)
pulse_width = 200; % Pulse width (us)
interphase_delay = 40; % Interph... |
7638cd2ff581b8404a1dc2fab81d92411b3330e0318e07af65205b7cffdda327 | MATLAB | 19,035 | 483 | classdef Aligner < handle
properties
n_ROIs
scan_data;
scan_size;
scan_ROI;
scan_points;
scan_pointsC;
scan_ref;
scan_resolution;
atlas_data;
atlas_size;
atlas_ROI;
atlas_points;
atlas_pointsC;
atlas_ref;
atlas_resolution_nominal;
atlas_resolution_estima... |
6a6a38b2111bbf2a30671f745d496f037b61f26b00abed6378e6916cd42b0679 | MATLAB | 19,092 | 550 | classdef Bundle < handle
properties
bundle_index;
wireN;
wires;
align_helper;
end %properties
methods
function obj = Bundle( wireN, planesN, bundle_index, ...
ROI_data, image_data, truncate, truncate_lim, min_dist)
import electroslice.*;
% optional adju... |
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