sha256 stringlengths 64 64 | language stringclasses 28
values | size int32 1 491k | lines int32 1 23.2k | content stringlengths 1 200k |
|---|---|---|---|---|
a95968fd12f37d7d79a44669782c552d1cde32b44bb5520c54256b35190dd557 | MATLAB | 1,545 | 50 | function [spikeWindows, carTraces] = localCAR(spikeWindows, hCfg, nSitesEvt, refSites)
%LOCALCAR Subtract local common-average reference from spike windows
% spikeWindows: nSamples x nSpikes x nSites, single
if nargin < 3
nSitesEvt = [];
end
if nargin < 4 % usually (always?) the case
... |
8b2f26f85e2fcb7f914b3358941da5856b286628364357f688f329fe2ac686b4 | MATLAB | 1,552 | 39 | function writeNeuroscopeShank(clusters,samplingRate,fileBaseName)
% takes cluster IDs and spike times from loadKS (or variant) and writes two file types:
% fileBaseName.clu.n = list of cluster IDs in chronological order
% corresponding to spike times; first entry = total
% ... |
7e6cb637847ae8c8e6e2736bb5c486f4068cebd452e342fd29d00c92c2194367 | MATLAB | 1,553 | 60 | function [localMinsFinal] = iterToMin(signal, array, threshold, isOnset)
% [localMinsFinal] = iterToMin(signal, array, threshold, isOnset)
%
% Summary: This function iterates towards local minimum values,
% sequentially from a given array of indices
%
% Inputs:
%
% 'signal' - the signal in which we are lookin... |
f01b0fdda4681dac196f24e562f9cce90aa78091f714128b6cdd5d75b7e60058 | MATLAB | 1,553 | 32 | % Folding Maps back:
% This only works for 3*3 and 5*5 for now
% Can be easily extended to odd numbers.
function EMap_Ext2Ori = FoldExMap2Ori(NnEex,NnE,EMap_Ori2Ext,N_E,n_E_HC)
% from extended back to original: fold
% E
EMap_Ext2Ori = zeros(size(NnEex.X));
EMap_Ext2Ori(EMap_Ori2Ext) = 1:N_E;
CenterEHC = find(NnE.X>1*n... |
62a9a0c49ec4ac2f41a3a134c14822543894c3524bee331afb160a5dfc9b4b89 | MATLAB | 1,554 | 62 | clear all
close all
clc
if badtrls
project_dir = '.\Adults_badtrls\';
else
project_dir = '.\Adults\';
end
subs = [1:26];
for sub_i = subs
sub = sprintf('1%2d',sub_i);sub(sub == ' ') = '0'
ses_i = 1;
ses = sprintf('%3d',ses_i);ses(ses == ' ') = '0'
tic
index_pinky_Tstat_func... |
c680917d17487fe6313444563d11acfc4340b6240d2bf909cbe69658100b27a5 | MATLAB | 1,554 | 44 | function [rho,logData,pval] = computeCorrelation(data)
% computeCorrelation Characterizes a given spatial system as defined by
% a power law function y=ax^k as described in the original manuscript.
%
% [rho,logData,pval] = computeCorrelation(data) takes as input an Nx2
% vector containing the features and d... |
dca2da90cc7f8afb00a0f8d0889c4601f2e830685a206b945465c6d93d5b06ed | MATLAB | 1,554 | 68 | clear
close all
clc
load Liza_all_data_psth.mat
ctrl= all_psth(1:2:end,:);
HT = all_psth(2:2:end,:);
%% Metric ON
mean_ctrl = mean(ctrl(:,1:40),2);
std_ctrl = std(ctrl(:,1:40)')';
n = 3.5;
Resp_ctrl = ctrl > mean_ctrl + n * std_ctrl;
%%Metric OFF
mean_HT5 = mean(HT(:,1:40),2);
std_HT5 = std(HT(:,... |
7f269b347399337b650497865229f32e5944c5c05d216069214e1443546a46cc | MATLAB | 1,555 | 44 | % Function that ignores low-active cells in Ensembles
% Input
% frame_ensemble: sequence of ensembles
% Rclust: Matriz Activity above CAG threshold
% Output
% reframe_ensembles: zeros where low-active cells fired
function reframe_ensembles=ensembleCAG(frame_ensemble,Rclust)
reframe_ensembles=frame_ensembl... |
8d7905b4497eda847d185d7ec83cf8795c59e4e178c7ecf84b50d66a2612b7ba | MATLAB | 1,555 | 38 | function [data, all_strings] = get_all_data_from_level_h5_rec(filename, str, data, all_strings)
% This function recursively reads data from an HDF5 file.
%
% INPUT:
% filename: A string that identifies the HDF5 file from which to extract data.
% str: The group from which to start extracting data.
% data: A ... |
d30feafa14235b90ab13b79ffa96dc5e6d1fddedb7d79ed5d3d512bc1dd57b5c | MATLAB | 1,555 | 43 | function clusters_mapping(m, p, shrinkage_factor, borders_table, reference_probe_length_tip)
[file, path] = uigetfile('cluster_info.tsv');%When the user clicks the load data button, a window should open to enable the user to select a file.
datafile = fullfile(path, file); %save path
cd(path)
info = tdfread(datafil... |
b60a3b6130a7850ff777f2067380b6d0deb26751ce323571763989605b4d7165 | MATLAB | 1,557 | 44 | function [trainedClassifier, validationAccuracy] = trainClassifierfloor(trainingData, responseData)
% trainClassifier: Trains a classifier and returns a trained classifier and its accuracy.
% Input:
% trainingData: Matrix of predictor data.
% responseData: Vector of response data.
% Output:
... |
78bfd04a9b4f213718cf809217a6b19de5e5568c1f3773a6e90ba0a8943fbb6f | MATLAB | 1,558 | 62 | clc
clear all
close all;
addpath('E:\Programs\Baseline Wander Comparison\ECG PTB Database');
f = 1.1;
fs = 1000;
bins = fs/4;
N = 30*fs;
M = 12;
start = 0;
stop = 30;
DataFileNames;
for kk = 1:length(fname),
InputFileName = fname{kk};
h = fopen('ECGExtracter.bat','w');
fprintf(h,'... |
4ea8627413f00280cccd7ab581b95d195a73afa954827eaa17624e826ca12425 | MATLAB | 1,559 | 55 | % Test script for ecg_gen_warping
%
% This script demonstrates the usage of the ecg_gen_warping function to generate
% synthetic ECG signals using the warping transformation from the phase to time domain.
%
% Revision History:
% 2023: First release.
%
% Reza Sameni, 2023
% The Open-Source Electrophysiological Toolb... |
78e2e35615dc269fdf70ca6e288a2b41543697ebf0c9734a17049a9d7f16cf68 | MATLAB | 1,559 | 35 | function [onSets,offSets] = adjOnsetOffset(onSetsInd,offSetsInd,timeThres,vel)
%Adjust Onset and Offset vectors to adhere to time and length constraints
%
% [onSets,offSets] = adjOnsetOffset(onSetsInd,offSetsInd,timeThres,vel)
%
% Description: This function was created by Jeffrey March, so the onset
% and o... |
51cafffcfdde1296290eba2b2f833e7a815a3f337893c4b934e5b657b56b7074 | MATLAB | 1,561 | 69 | %% data prep
clear;
T = readtable("both_sites_magnitudes.csv");
rows_to_exclude = find(T.hypothesis3_include == 0);
T(rows_to_exclude, :) = [];
cols_of_interest = [...
"GestationalAgeAtStudy_weeks_",...
"magnitude_HL",...
"Site",...
];
T = T(:, cols_of_interest);
T.Site = str2double(replace(T.Sit... |
19347750689e900ba22203057049be28c9edcd188cd813f4c8e45ab235637589 | MATLAB | 1,563 | 47 | clear
close all
num_mice = 3; % Update this to the actual number of mice
% Initialize variables to store the data
all_avg_green = [];
area_under_curve_green = zeros(num_mice, 2); % Two intervals
% Define the time intervals
time_interval_1 = [-5, 0];
time_interval_2 = [0, 5];
% Loop over all mice, load ... |
c7361ca6f5a5e9da9c8b5f5d884f62d544b9fde33f0e70bd92b55de45fedfb48 | MATLAB | 1,564 | 83 | % function RunningXcorr for ECG phase wrapping analysis
% Reza Sameni, 2012
%
close all;
clear;
clc
data = load('ECG2.txt');
fs = 1000;
% data = load('16265m.mat'); data = data.val(1,:);
% fs = 128;
data = LPFilter(data - LPFilter(data,5/fs),50/fs);
% x = data(1001:11000);
% y = data(1001:11000);
x = data(1:12000)... |
94b486e2329f2d2a90a4b9676c6fa622cb86d667f53d7c60748365069db0b9c7 | MATLAB | 1,565 | 85 | function [alpha, beta, ok] = nufft_best_alpha(J, L, K_N)
%function [alpha, beta, ok] = nufft_best_alpha(J, L, K_N)
%
% return previously numerically optimized alpha and beta
% use L=0 to return best available choice of any L
%
% Copyright 2001-12-17 Jeff Fessler The University of Michigan
if nargin < 1, help(mfilenam... |
a165ceb7b6cc863db508fd7dc080111c6667c991bf8a519b1c8c6eef371aae19 | MATLAB | 1,565 | 48 | function ItrTuningIdx = tuningShuffle(nz, trans, distx, trace, MaxItr, edg1, htime1, edg2, htime2, edg3, htime3, edg4, htime4, pangle)
%initialize surrogate tuning distribution
rng('shuffle'); %random number generator will be based on time, i.e. always different
ItrTuningIdx=zeros(1,MaxItr);
parfor itr = 1:1:MaxI... |
fc061541b94c39dabd95517d90c456a8bfdc95056961645a2b0e28d675b96255 | MATLAB | 1,565 | 60 | function resizeAllInDir(runDir,targetMicsPix)
% Perform resize on all pStack files in a directory
%
% function autoROI.tools.resizeAllInDir(runDir,targetMicsPix)
%
% Purpose
% Batch run of autoROI.tools.resizePStack
% Looks for pStack structures in the current directory and all
% direct... |
5563f3add70d54a52aaf8014544373bd91ea9c9a3379ab04eaae244eca529ac2 | MATLAB | 1,567 | 45 | clear
clc
[file, path] = uigetfile('clusters.mat','MultiSelect','off');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
cd(path)
datafile = fullfile(path, file); %save path
load(datafile)
close all
%%
int_colores = {'c','k', 'm', 'r', 'g', 'y', 'b'};
for w = 1:si... |
87ea2e7e7bba40315073e42c6fe72a4c1d5df6418d858804ebf7f815ac1756c7 | MATLAB | 1,567 | 48 | function x = L2_Linf_shrink(y,t)
% This function minimizes
% 0.5*||b*x-y||_2^2 + t*||x||_inf
% where b is a scalar. Note that it suffices
% to consider the minimization
% 0.5*||x-y||_2^2 + t/b*||x||_inf
% and so we will assume that the value of b has
% been absorbed into t (= tau).
% The minimization proceeds... |
39840585a388c0f8efe510265b997d679aa1a89b1a0fe16afd00c16f466c1486 | MATLAB | 1,570 | 42 | % Kefei Liu. 2017.5.5
function [h1,h2,a1]=scatterDiagHist(x,y,dedge,varargin)
d=x-y;
rlim=[min([x(:);y(:)]),max([x(:);y(:)])];rlim(2)=rlim(2)+rlim(2)-rlim(1);
diflim=sqrt(2)/2* ((rlim(2)-rlim(1))/2);
if nargin<3 || isempty(dedge)
dedge=linspace(-diflim,diflim,13);
end
if length(dedge)==1
dedge=linspace(-... |
f165b35689c6682a2bc1b726832921ad87f03377553fb8eeeb726fbcbace1f32 | MATLAB | 1,572 | 49 | function [val, new_fp] = mread(arr, fp, count, type)
% mread: eja (almost) drop-in replacement for fread for reading uint8 arrays
% dependencies: c_str.m
[computerType, maxSize, endian] = computer; %#ok<ASGLU>
isLittleEndian = (endian == 'L');
if (strcmpi(type, 'int32-le'))
% data type is int32, little en... |
192b893fc6454177fd9f24e73840c54e783d1599e3219f73abd4c3eb5caa207a | MATLAB | 1,573 | 50 | function dist = eq_min_dist(dim,N,varargin)
%EQ_MIN_DIST Minimum distance between center points of an EQ partition
%
%Syntax
% dist = eq_min_dist(dim,N,options);
%
%Description
% DIST = EQ_MIN_DIST(dim,N) does the following:
% 1) uses the recursive zonal equal area sphere partitioning algorithm to
% partition the u... |
35596444c359d12b68b0bfca0fead3bc13cb061fafddc0c80420d9dba3956adf | MATLAB | 1,573 | 49 | %% Reproduce Fig. 1f from deposited dataset
% David Wolf, 11/2023
%
%% load dataset
clear; clc;
load('C:\Users\David\Documents\GitHub\OXT-Wolf\data\Fig2_AON_data_smooth.mat'); % for plotting (but not statistical inference) of the Euclidean distance from baseline, the population vectors were smoothed with a sliding wi... |
3689878ec7e157951270e84ed41381c3cec10fe2685927d5825d02396503cb58 | MATLAB | 1,573 | 31 | %--------------------------------------------------------------------------
%RETROICOR_defaults
%Default settings for RETROICORplus
%EJH 2011-16
%--------------------------------------------------------------------------
%Set Fourier order (3-5th order added to explained variance)
RETROICORplus_defaults.fOrder = 5;
%... |
98622a9ef7438f6541a95da6f6745f5475a67298005f6c8e3aeecc1a2deaecaf | MATLAB | 1,573 | 50 | function [Left_Scale,Right_Scale] = Scale_Calculation(I,Neural_Net,cmap)
A = I;
C = semanticseg(I, Neural_Net);
B = labeloverlay(I,C,'ColorMap',cmap,'Transparency',0);
figure;imshow(B)
[x,y,~] = size(B);
for i = 1:x
for j = 1:y
if ((B(i,j,1) == 162) && (B(i,j,2) == 20) && (B(i,j,3) == 47))
... |
d0226c0ec52740afe4563f016beff91739da72e680eca303b0815f53771e67ef | MATLAB | 1,574 | 47 | % Higlight Neuron in Raster Plot in Red
% Input
% Plot of Raster: Current Figure (from Raster_Plot_V)
% Neuron ID Neuron ID
% Ouput
% @ raster plot:
% Rectangle
function HighlightNeuronatRaster(NeuronID)
% Example:
axisfig=gcf;
NeuronIDstr=num2str(NeuronID);
LengthStr=length(NeuronIDs... |
c1d7c12de99c38e0d297d2302ceaeab95413e395518103fe4363b45b997915b5 | MATLAB | 1,576 | 44 | function [Testing_Frames,Testing_Classes] = Generate_Testing_Set(Frame_Half_Size)
TrainingSet_MaxSize = 10^6;
Testing_Frames = {}; % xTestImages.
Testing_Frames(TrainingSet_MaxSize) = {1};
Testing_Classes = []; % tTest.
Testing_Classes(2,TrainingSet_MaxSize) = 0;
Dir1 = uigetdir; % Let the user choose a dir... |
a2f4aff7d2b5ce5544285097feb3ab7553cc3f18142ec9827deee6394979e452 | MATLAB | 1,577 | 71 | function [fid raw_data] = read_raw(filename)
if ~exist('filename')
filename = spm_select([1 inf],'any','select files','',pwd)
end
for k =1:size(filename,1)
[pathstr,fname,ext] = fileparts(filename(k,:));
fp = fopen(fullfile(pathstr,[fname,'.PLOTIN']));
fid(k).spectrum.cenfreq = find_float_after('HZPPPM=',... |
ada867cdf917abf3b962e0043ce884e7480b5f2b06219c9b9b0d79ab7e400f8b | MATLAB | 1,579 | 48 | function ItrTuningIdx = tuningShuffle2(nz, textre, zse, distx, trace, MaxItr, edg1, htime1, edg2, htime2, edg3, htime3, edg4, htime4, pangle)
%initialize surrogate tuning distribution
rng('shuffle'); %random number generator will be based on time, i.e. always different
ItrTuningIdx=zeros(1,MaxItr);
parfor itr = 1... |
950fc30dce6ccccfbe2ffd3cb7c058dc83aaaf2cd19cfe7f6da0401e023de340 | MATLAB | 1,580 | 54 | function [kernel, kernel_ft] = nufft_gauss(type, J, sig)
%function [kernel, kernel_ft] = nufft_gauss(type, J, sig)
%|
%| Gaussian bell kernel functions truncated to support [-J/2,J/2]
%| for NUFFT interplation, with width parameter "sig"
%| in
%| type 'string' or 'inline'
%| J interval width
%| sig width parameter
... |
48b0283b3031281abbbef88826c740070e75d950b086271b94794dcbd2d7da67 | MATLAB | 1,586 | 49 | function [xd yd delta deltaCI] = rst_shiftdhd(x,y,nboot,plotshift)
%[xd yd delta deltaCI] = shiftdhd(x,y,nboot,plotshift)
% shiftdhd computes the 95% simultaneous confidence intervals
% for the difference between the deciles of two dependent groups
% using the Harrell-Davis estimate
% See Wilcox p.184-187
%
% GAR, U... |
de996d39b8d333e551236aef2801ad0163f0a51e1f7e13c047038c77d9c6e53a | MATLAB | 1,586 | 53 | function dist = compute_Euclidean_distance_from_baseline(data)
%% Euclidean distance from baseline
% Input:
% data: struct with binned spike counts for odor trials
% data.(odor) is a matrix with dimensions: units x time x trials
% data.time is a vector spcifying the time bins
%
% Output:
% dist is the ... |
86539d9ace37def2c0187fec4714d7b250d09eb63cac45fdd44e77dba14329e9 | MATLAB | 1,587 | 46 | function [spatial, temporal, S] = compute_pca(M, num_PCs)
% Computes the PCA factorization of the provided movie. Note that the
% movie is expected to be a 2-D matrix ([num_pixels x num_frames])!
[num_pixels, num_frames] = size(M);
% Compute the covariance matrix [time x time]
cov_mat_size = num_frames^2 * 4 / 1... |
2d7a83e59fd2e9bbe25e605103dba860ddf9e0e8896dffcce426c327c01b4a8a | MATLAB | 1,588 | 59 | function [numchannels,numtimeframes,samplingrate,thedata]=openeph(openfilename)
% openeph: opens a Cartool evoked potential data file (.ep(h))
%
% inputs: full path and name of the file to open
%
% outputs: number of channels, number of timeframes (and sampling rate for
% .eph files) as 1-D numeric arrays; data as a 2-... |
4bed68c81ba3faa3d39cd676e0a58a65372ffab47a0538d8ea4795d0fa3447fe | MATLAB | 1,588 | 39 | function nMerged = mergeBySim(obj)
%MERGEBYSIM Automatically merge clusters by similarity score
obj.hCfg.updateLog('mergeBySim', 'Merging clusters by similarity', 1, 0);
waveformSim = obj.waveformSim;
nClustersPrev = size(waveformSim, 2);
% ensure targets of merges are smaller than units merging in... |
ebacd8596e218fa8ba77e15df31ba7d4a23e141476ddd649ed89ceb56bf64e63 | MATLAB | 1,588 | 45 | clear
[file, path] = uigetfile('*.mat');%When the user clicks the load data button, a window should open to enable the user to select a file.
datafile = fullfile(path, file); %save path
load(datafile)
close all
cd(path)
clc
%%
clust_num = fieldnames(clusters.cluster_cells);
row = 0;
for i = 1:length(clust_num)
cell... |
6405589b0a97ec85ffdcd981e3e6a9983f87f7d4768607a84928ea96c0cfcbc8 | MATLAB | 1,592 | 53 | clear
close all
num_mice = 3; % Update this to the actual number of mice
% Initialize variables to store the data
all_avg_green = [];
% Loop over all mice, load the data, and concatenate it
for i = 1:num_mice
filename = sprintf('Control/Stim_Onset_Mouse%d_DAMeanData.mat', i);
load(filename, 'avg_g... |
7214576e1ac8ff8ac5e801496e49171d26e160d7550fb994aba9443281e156a0 | MATLAB | 1,592 | 57 | clear
close all
clc
data = importdata('/Users/rsameni/Downloads/FHR_values_per_recording.csv');
fs = 1000;
wlen = 10; % number of beats
hr = data(:, 2);
hr(hr <= 0) = [];
hr(~isfinite(hr)) = [];
rr = 60./ hr;
rr_samples = round(rr * fs);
peak_indexes = cumsum(rr_samples);
[rho, mov_rho] = sqi_hr_dy... |
0b76ce6226e96c8450ec87859f21e8745b14a2267364d18ee828900169cab90c | MATLAB | 1,593 | 44 | function [Training_Frames,Training_Classes] = Generate_Training_Set(Frame_Half_Size)
TrainingSet_MaxSize = 50*10^6;
Training_Frames = {}; % xTrainImages.
Training_Frames(TrainingSet_MaxSize) = {1};
Training_Classes = []; % tTrain.
Training_Classes(2,TrainingSet_MaxSize) = 0;
Dir1 = uigetdir; % Let the user ... |
4ac932b10e6247c7bcb7acf3c9901403fbdc77c229af1a962259a71f89b19256 | MATLAB | 1,593 | 62 | fnames = {'hex','iaa','two_oct','hxa','two_hep','ani',...
'msal','lcar','gua','chex','bza','ger','etha',...
'apin','one_oc3','cit','lin'};
minimum = Inf;
maximum = -Inf;
for i = 1:length(fnames)
eval(sprintf('d = jcampread("%s.jdx");',fnames{i}))
xdata = d.Blocks.XData;
minimum = min(minimum... |
f6a1bdfafce0ad960d1b9f22fad09c87608b4b066bcf803d7a04a40bd7044317 | MATLAB | 1,593 | 72 | % This script tests the goodness of fit of gaussian functions on an ECG
clear;
close all;
clc;
% load('SampleECG1kHz1.mat');
load('SampleECG1kHz2.mat');
data = data';
fs = 1000;
ch = 2;
ksigma = 4;
% x = LPFilter(data - LPFilter(data, 3/fs), 250/fs);
x = data(ch, :) - LPFilter(data(ch, :), 2/fs);
y = -[0, diff(x)].... |
563cd17df3d7b92c02969285a7b8905577cda39d70f7f29d8951e323b934e430 | MATLAB | 1,595 | 41 | function nMerged = mergeBySim(obj)
%MERGEBYSIM Automatically merge clusters by similarity score
obj.hCfg.updateLog('mergeBySim', 'Merging clusters by similarity', 1, 0);
waveformSim = obj.waveformSim;
nClustersPrev = size(waveformSim, 2);
% ensure targets of merges are smaller than units merging i... |
53a97857778ebeb9c0304a66a0219215068c275558c572a64638a90c786a014d | MATLAB | 1,599 | 31 | %% eopn3 vs control per mouse
cd('I:\My Drive\ELYASHIV\PFC_paper_results_after_revision\per_mouse\f4h')
clear
clc
control = importdata('responsive cells per exp_control.mat');
eopn3 = importdata('responsive cells per exp_eopn3.mat');
%%
T =table()
T.responsive = [control.reponsive_cells_expsT{1:end-1,2};eopn3.... |
a9486368df9ac0406cba289a4eb2ff0991213c498b480e994aa16cfab6d09cf6 | MATLAB | 1,600 | 48 | function der = getweights(layers)
n = numel(layers);
ind = 0;
der = double([]);
for l = 1 : n % layer
if strcmp(layers{l}.type, 'i') % input
if (isfield(layers{l}, 'mean'))
curlen = numel(layers{l}.mw);
%w_trans = permute(layers{l}.mw, [2 1 3 4]);
%der(ind+1:ind+curlen, 1) = w_trans(... |
b6db8c9bad424aa9c9903c9b07e8341c37ca755e90349ac42fd9bab3f6a9da3c | MATLAB | 1,600 | 42 | %% premutation test sensativity analysis
mdes = sensativity_analysis_premutation_test
%%
function mdes = sensativity_analysis_premutation_test()
desired_power = 0.80;
alpha = 0.05;
n_per_group = 60;
n_simulations = 1000;
effect_sizes = 0.3:0.01:0.6; % Adjust the range based on your context... |
cc15243623da239e930acc804746078bf51ca825807aea89c5da825b759757a4 | MATLAB | 1,600 | 45 | % Test script for white_noise_wiener_filter (white noise suppression using
% Wiener filter)
%
% Reza Sameni, 2024
% The Open-Source Electrophysiological Toolbox
% https://github.com/alphanumericslab/OSET
close all
clc
clear
% Load the input audio signal
[x, fs] = audioread('/Users/rsameni/Documents/DataFiles/Acousti... |
75d73f0d02ddc5f88a93405be9055784bc39026fb57d153c6f2d087bd9d5a568 | MATLAB | 1,602 | 52 | %% Calculate d' for neural population spike counts between two stimului
% INPUTS
% - Array of spike counts for two stimuli to compare, of the form:
% (nTrial x nCell) with each row corresponding to a
% trial (observation) and each column to an individual cell (variable)
%
% OUTPUTS
% - d' scalar (unsigned)
% d' = u1 -... |
34852a7703fc3c4b92685221313f1acfddcfcec43d54092afaee7e16b2f76844 | MATLAB | 1,604 | 68 | % Sample code for multiple delay length active noise cancellation from ECG signals
%
% Reza Sameni (C)
% Email: rsameni@shirazu.ac.ir
% Web: www.sameni.info
%
% Created May 2007
% Modified June 2018
clc;
clear;
close all;
load('SampleECG128Hz');
fs = 128;
ECG = y(:,2)';
N = length(ECG);
n = (0:N-1);
... |
33700eee002e17019cff7edb0bace27ebd8ecff7b62dcc36b33a33d1173558b9 | MATLAB | 1,606 | 51 | % A script showing a common-case use of the model's functions when multiple
% simulations are to be run. In this case, we plot simulation outputs for 5
% different multipliers of IKr (corresponding to 80, 90, 100, 110, and 120
% percent availability).
%% Setting parameters
clear
% param is the default model parametriz... |
78b52a7e6b47b30776fe097726ffae3536c061edb77707267adc166a18e8db2d | MATLAB | 1,607 | 50 | function lcs = logsumexp(X, varargin)
% LOGSUMEXP(X, dim) computes log(sum(exp(X), dim)) robustly. Care lightspeed users!
%
% lse = logsumexp(X[, dim]);
%
% This routine works with general ND-arrays and matches Matlab's default
% behavior for sum: if dim is omitted it sums over the first non-singleton
% dimension.
... |
80abe3b8a89c84d6682b0698e76ab17b3e828d77f6331c7c029536d645e2f495 | MATLAB | 1,607 | 38 | function [gsidx] = get_prediction_from_pcc(pcc,grnnet);
% GET_PREDICTION_FROM_PCC Sort TF-NTF gene interactions according to their Pearson correlation coefficients.
% GSIDX = GET_PREDICTION_FROM_PCC(PCC,GRNNET) returns interactions GSIDX (#interactions-by-3) with rows
% [TF_INDEX, NTF_INDEX, PVALUE] sorted by th... |
33c03484d95f81e7531a09fcbc359719a1f269988c6661f496ed67229000c47c | MATLAB | 1,608 | 27 | %% This script shows how to run an automated model evaluator. In this case, reportParams.reportType = 'full' determines that all Matlab-based criteria are computed and plotted
% the evaluator runs the basic version of the model. To run the dynCl
% version, please uncomment lines 10 and 18.
clear
% First, we define whi... |
9aea7bde1e62812731c6eac40c39ec9d9ec5680a70c0ee8897dfc4b650b26627 | MATLAB | 1,608 | 41 | function [ nexFile ] = nexAddContinuous( nexFile, startTime, adFreq, values, name )
% [nexFile] = nexAddContinuous( nexFile, startTime, adFreq, values, name )
% -- adds continuous variable to nexFile data structure
%
% INPUT:
% nexFile - nex file data structure created in nexCreateFileData
% startTim... |
9b0a97bc64e3cb61f30152458da0b19732bc3cd56be7512688a971c3926e347f | MATLAB | 1,609 | 43 | clear; close all; clc
order = 3; % Resampling order (2, 3, 4)
fs_input = 11025;
fs_output = 4000.0;
T = 0.5;
N = round(T * fs_input);
t_input = (0 : N - 1)/fs_input;
% Sample test of the Resampler class using the mexFunction interface
% Example 1: A mixture of sinusoidal signals
% signal_input = sin(2 * pi * 157.13... |
3a539154c66a36217252516a9f51d110b406dae6f318b784690e748b9d12acef | MATLAB | 1,610 | 40 | function spawnFigures(obj)
%SPAWNFIGURES Create the standard cadre of figures
obj.hFigs = containers.Map();
for f=1:length(obj.hCfg.figList)
figTag = obj.hCfg.figList{f};
figToolbar = 0;
figMenubar = 0;
switch figTag
case 'FigPos'
figTitle = 'Un... |
b2d22a66b7ab0c7b5ff120398442172ab77b8533c5ab99515b526986b84edcbb | MATLAB | 1,611 | 50 | % This script compares the behaviour of fixed-Cl and dynamic-Cl versions of
% ToR-ORd after 1k beats (I.e., this does not really showcase the
% instability of the fixed-Cl model, it serves mainly to show general
% similarity of action potential and calcium transient at the time when the
% model is usually evaluated.
%... |
bbb30701eb6d3886a749aabf834bf0ee9a87dc149a95ceada1006b697e8c89b6 | MATLAB | 1,611 | 63 | function F=opls(X,Y,Xtest,nOSC)
%+++ Function: orthogonal to latent sturctures(O-PLS)
%+++ Input: X: m x n (Sample matrix)
% Y: m x 1 (measured property)
%+++ Xtest: test samples
% nOSC: The number of OSC components to remove
%+++ Reference: Johan Trygg and Svante Wold, Orthogonal projections ... |
54ecb2a9d442407840ea8ac1ce77b21d0d81848b160e1fd43631da3395bac6be | MATLAB | 1,612 | 44 | function [pulseOnset, pulseOffset] = getPulseOnsetOffset(signal, threshold)
%Created by: Anya Krok
%Created on: 19 March 2019
%Description: general code for determination of onset and offset of
%optogenetic stimulation based on raw signal from pulse generator
%
% [pulseOnset, pulseOffset] = getPulseOnsetOffset(... |
94e63757daf26a9c6c7721af50e972c950e37c06e96f432971ac6e5ab1ac4fb1 | MATLAB | 1,616 | 83 | function F=ecr(X,y,A,method,alpha)
%+++ Elastic Component Regression, a bridge between PCR and PLS.
%+++ alpha: 0 PCR
% 1 PLS
% (0, 1) transitional models between PCR and PLS
%+++ Central South University, Changsha 410083, P.R. China.
%+++ Advisor: Yizeng Liang, yizeng_liang@263.net
... |
c24595913c62c1ebf28a758096d1578403fd48571b0bb2fa99093f92f8c0f742 | MATLAB | 1,616 | 44 | function [ output_args ] = preprocessMovie(p,moviePath,saveDir)
%preprocessMovie: performs all preprocessing steps on raw movies
disp([char(datetime('now')) ' loading movie'])
movie = single(loadMovie(moviePath));
disp([char(datetime('now')) ' registering movie'])
% use existing registration coord... |
85f06a438ddae0ed4e5783b06fad28a67d5d3033f920ee0c9944aaa646e79be9 | MATLAB | 1,618 | 48 | function Plot_Brains_AG_MSPoI(FinalRepPar,nodes_name,nodes_coord,at,options)
gr = options.grlabel;
for n = 1:length(nodes_name)
Name = nodes_name(n);
NodeName(n,:) = string(Name);
end
%============== PLOT BRAINS====================
% TO save data
cd /netapp/vol7_u923/SEME/SEME_... |
f60c5b64584eaeaf0df0abd983d31b7b29126280b8ceebd5c44fed6743956629 | MATLAB | 1,619 | 75 | function [suj empty_suj] = get_series(serie_name,suj,reg_ex,varargin)
ind_to_remove = [];
ser = {};
for nbsuj = 1:length(suj.sujdir)
if ~isempty(varargin)
aa = get_subdir_regex(suj.sujdir(nbsuj),reg_ex,varargin);
else
aa = get_subdir_regex(suj.sujdir(nbsuj),reg_ex);
end
if length... |
2222fdcf8432fbc2e236b6144e8d229d4d3a4415c5b11cf4c1315d1d18fa200f | MATLAB | 1,620 | 48 | function pv_nonpv_ccg(cellids,resdir,issave)
%PV_NONPV_CCG(CELLIDS, RESDIR, ISSAVE) Cross-correlation analysis.
% PV_NONPV_CCG calculates cross-correlations for PV(+) and non-tagged
% neurons in 50 ms windows. CCG results are saved for non-tetrode pairs
% and tetrode pairs separately.
%
% See also CCG.
... |
c664d3cff09fade86d7e8904c3e6dbfb07a95dd264bf8955ff61e97793d2a2a7 | MATLAB | 1,620 | 45 | function derived_cardiac_signals(app)
%DERIVED_CARDIAC_SIGNALS interpolates the hb_res.dt_instantaneous
% Detailed explanation goes here
idx = 0;
tmp = nan(1,length(app.data));
for i = 1: length(app.data)
tmp(i) = app.data(i).tic_multipl;
if strcmp (app.data(i).name,'RR Intervall')
idx = i;
end
e... |
de16abbb3b1d25b4089d47bbe2391b232792ddec502074dcfe2eeb8bff2f4908 | MATLAB | 1,620 | 45 | function x_filtered = outlier_filter(x_raw, method, half_wlen, percentile)
% outlier_filter - Detects outlier samples with diff values beyond a given
% percentile and replaces them with mean or median of a sliding window
% around the sample. Other samples remain unchanged.
%
% Syntax: x_filtered = outlier_filter(x_... |
dfdb2fd38b56fa11aa4415e4e1cdd1c2584baefe9f43b3e4e85bed6774311c4f | MATLAB | 1,620 | 41 | function [movie_corrected,bleach_filters,bleach_traces,temporal] = debleachMovie( p,movie )
% smooth movie in time
[height,width,n_frames] = size(movie);
movie = reshape(movie,[height * width,n_frames]);
smooth_win = 2000;
M = zeros(size(movie));
parfor i = 1:size(movie,1)
M(i,:) = smo... |
f75192bc7486b0c1df6c73a455aacc5e4fc2fa71085e21bd39621e7d7f994aee | MATLAB | 1,620 | 65 | function [pval,Factual,Fdist] = randanova1(m,group,num)
% function [pval,val,dist] = randANOVA1(m,group,num,mode)
%
% Estimate p-value for one-way ANOVA using permutation.
% For further information on using permutation to calculate signficance
% tests see Anderson (doi:10.1139/cjfas-58-3-626).
%
% <m> is a vecto... |
1832c5b7d88277f4a9fe2d74ba665d1f7d59280d1f62e2c2b71bb0b72c9abd98 | MATLAB | 1,621 | 70 | function write_result_to_csv(conc,resname,field_list)
if ~iscell(conc)
conc={conc};
end
if ~exist('field_list')
field_list = fieldnames(conc{1});
end
fid = fopen(resname,'a+');
nbline=0;
while fgetl(fid)~=-1
nbline=nbline+1;
end
for npool = 1:length(conc{1})
f1 = getfield(conc{1}(npool),fiel... |
d0741e5093f1ec8e2245ba870df8777d9b6c0790bd9e7a901c5a6e9ee7bed002 | MATLAB | 1,621 | 52 | function Bursts = test_criteria_set(DataBroadband, SampleRate, NarrowbandRange, CriteriaSet, Plots)
% runs burst detection with a single narrowband range and criteria set to
% see how the criteria are doing
% plots should be 3
arguments
DataBroadband
SampleRate
NarrowbandRange
CriteriaSet
Plots = [true true true];
end... |
db5348ae873a6baa344fec5cd338c5d089418ced3624e834a8685a07420c1d64 | MATLAB | 1,624 | 51 | function [ output_args ] = extractJoint( p,thisSub )
%% do path handling, etc
saveDir = fullfile(p.rootDir,'miniscope', ['subject' num2str(thisSub)],'jointExtraction','extracted');
savePath = fullfile(saveDir,'resultsPCAICA.mat');
if exist(savePath)
disp('Skipping subject (already done)')
... |
23cc6cf3711cb090a4542926b0939330cf8b1c72d12b08a7d70fbecf099afbe3 | MATLAB | 1,625 | 40 | %% plot
[file, path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
cd(path)
datafile = fullfile(path, file); %save path
w = 2;% window for ploting (2 = sustaneid)
%%
for i = 1:length(datafile)
load(datafile{1,i});
... |
926cec6191f3faf396a4478203486c38b09965d191e4929f33b5d46e421eca36 | MATLAB | 1,625 | 45 | function [phase, phasepos] = phase_calculator(peaks)
% phase_calculator - ECG phase calculation from a given set of R-peaks.
%
% Usage:
% [phase, phasepos] = phase_calculator(peaks)
%
% Inputs:
% peaks: Vector of R-peak pulse train
%
% Outputs:
% phase: The calculated phases ranging from -pi to pi. The ... |
d1815955e461f8b0acbd3945f5dbbb0fcaaf4cd5c63f8f74086391d0fa62a6d0 | MATLAB | 1,625 | 61 | function [S,G,O] = fcn_staged_multilayer(A,gbound,obound,nsamples,couplingtype)
N = length(A{1});
T = length(A);
%%
gammarange = [min(gbound),max(gbound)];
omegarange = [min(obound),max(obound)];
g = unifrnd(gammarange(1),gammarange(2),nsamples*100,1);
o = unifrnd(omegarange(1),omegarange(2),nsamples*100,1);
in = inpol... |
cb7bc8f5e3ee79f7f1d00f0c42619480679f187e18f269cea2d19c566d9c8147 | MATLAB | 1,626 | 60 | function EEG = simulate_eeg(Channels, Seconds, fs, bpfilter, hpStopfrq)
% Generates a fake EEG signal without any oscillations, to see how many
% false positives get generated.
% Channels: number of "channels" to generate
% Seconds: duration in seconds of the recording
% fs: sampling rate
% bpfilter: [high-pass, low-pa... |
10982b637ce0ff8e981158422b8af31be30061745d46e5f648d1ce417a8deaf3 | MATLAB | 1,629 | 50 | function spmup_plotmotion(motion_file,radius)
% simple routine to plot motion parameters in mm and degrees
% also added is the root mean square displacement
%
% FORMAT: spmup_plotmotion(motion_param,radius)
%
% INPUT: motion_param is the file in which the motion paramters are
% radius the head size (useful to c... |
46773dee48cf2bf77c9957ea1d55f3ec8bb4d7f81f3623379bd2951008193f0d | MATLAB | 1,629 | 54 | function [clusterIDs,centroids] = mnl_MeanShift(X,bandwidth)
%Perform Mean Shift Clustering on the input data X with the given bandwidth
%Params:
%X : Input matrix
%bandwidth: Bandwidth controlling kernel size
%Returns:
%clusterIDs, centroids
[n,p]=size(X);
%Initialize clusters to zero
clusterIDs=zeros(n,1... |
3355763ea500bcb5d5f69c2a9b65ae1ce1c772b56eb7ae65c4ce485439bb86d1 | MATLAB | 1,630 | 42 | % Read coordinates
function [XY,r]=Read_ROI_Coordinates(CurrentPath)
DeafultROIRadius=5;
SlahesIndxss=find(CurrentPath=='\');
[XYName,XYPathName] = uigetfile({'*.csv';'*.zip'},['All Coordinates (XY) of ',...
CurrentPath(SlahesIndxss(end-1)+1:SlahesIndxss(end)-1)],CurrentPath);
if ~isnumeric(XYPathName)
XYFN = c... |
cb1d5d08a7d6fe3d548bea5eb5baaac68846e9fcdec177d8420dc61b342a825d | MATLAB | 1,630 | 52 | function th=rotateticklabel(h,rot,enabled)
%ROTATETICKLABEL rotates tick labels
% TH=ROTATETICKLABEL(H,ROT) is the calling form where H is a handle to
% the axis that contains the XTickLabels that are to be rotated. ROT is
% an optional parameter that specifies the angle of rotation. The default
% angle is 90. ... |
44b7d398a91efb28004a3ae5c7a887bbb83f11d600b3aa5bbbf915e056ede7eb | MATLAB | 1,633 | 42 | %%devide_cells_by_aria
clear
clc
%%
%save only Intensity encoding + IR
row_names = {'total'; 'responsive'; 'IR'; '%_reponsive'; '%_IR' };
T = table(row_names);
[file, path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
cd... |
94a36c2f94a6a8a4aa0912dcba3902371bb33c020e3a46b26c0bc51c2250f281 | MATLAB | 1,633 | 54 | %% laser repetitions vs no laser
%% compare response per rep
clc
clear
cd('I:\My Drive\ELYASHIV\PFC_paper_results_after_revision\eopn3')
all_ints_data = importdata("all_ints_data_eopn3.mat");
all_ints_data_control = importdata("all_ints_data_control.mat");
%%
NDs = [10, 8, 6, 4,3,2,1];
for i = 1:length(NDs... |
e0ca3ab7f4067db3052cb1a19557d54010fdb316057274be203150c2993194da | MATLAB | 1,635 | 40 | function [index, spikes, thr, thrmax, noise_std_detect] = DetectSpikes_Amp(Data, handles)
% DetectSpikes_Amp Detect spikes based on amplitude thresholding. Adapted
% from WaveClus
% INPUT
% Data - raw waveform from the electrode
% handles - detection parameters
% OUTPUT
% index - spike times (the only output wri... |
e0ddd26278f5594790e3bb6f3e4b2ae4e91225eccb91f1417ca466e097ed21c2 | MATLAB | 1,637 | 51 | % Tree validation
% Measure of how faithfully the tree represents the dissimilarities among
% observations and select the best between different methods: average,
% centroid, complete, median, single, ward and weighted.
%
% HBestTree_JP(Sim, numFig)
%
% Inputs
% Sim = similarity as matrix PxP (P=#peaks).
% numFig = num... |
718e7c337b2cb1a4fe0ca4cb13f42761ac41761956c2a7d0676eabd274810146 | MATLAB | 1,639 | 48 | function [ nexFile ] = nexAddNeuron( nexFile, timestamps, name, wireNumber, unitNumber )
% [nexFile] = nexAddNeuron( nexFile, timestamps, name ) -- adds a neuron
% to nexFile data structure
%
% INPUT:
% nexFile - nex file data structure created in nexCreateFileData
% timestamps - vector of neuron... |
e1c6f3bdb187b2fdfff84e91861df60d7467f58faeb8db44d3e152363db4c2fb | MATLAB | 1,640 | 43 | %% To test the toolbox on the test image "test_data.tif":
%% download the folder and cd in it, then run this script
%% we recommend reading the README file.
clear
clc
close all
current_fold=pwd;
% TO PERFORM ESTIMATION OF OPTIMAL K uncomment lines 14-15-16
% [120 370 120 370 30 100] is a representative crop for
% tes... |
04b955bcecaaaf00db4de856e066d64d75f6f0765e8f2406cab503f0a9392166 | MATLAB | 1,641 | 39 | % plot ramp from all_data
[file, path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
cd(path)
datafile = fullfile(path, file); %save path
w = 2;% window for ploting (2 = sustaneid)
%%
for i = 1:length(datafile)
load(d... |
88c7e7e49ff5a8547bfbcdbb0a0446d8c583b0bdac170b0acae9d36a2ce38d22 | MATLAB | 1,641 | 20 |
%% cog analysis by snp
%%% what are the y variables:
%%% word pairs (PAL),
Y=cognitive.x20197_2_0;
for snp=1:length(snps.Properties.VariableNames)
Outcome=cognitive_ordered.x20197_2_0; APOE=snps(:, snp);APOE=round(APOE{:,1});APOE(CT_SNPs.FID==0)=NaN;
ix= AD_ordered.eid==0 | ~strcmp(ancestries_ordered.pop,... |
131850b3a692736fbad31dea9ee8951e371c9d2285fca5a10463138801055609 | MATLAB | 1,644 | 72 | % function to compute the spatial scaling factor, temporal scaling factor
% and scale-specific factor
% x1 and x2 are two dynamics with the same number of units, but potential different length of time (row for neuron and colomn for time)
function [SSI, TSF, SSF] = scaleFactor_mean_sz(x1,x2,tLimit,sLimit,step)
[N,... |
e1adce1b6c3367ffa2aa50d6479341670315559d2dd66062382db1f90c798ed9 | MATLAB | 1,645 | 68 | function [X,Y,Z] = fatcurve(c,r)
%FATCURVE Create a parameterized cylindrical surface at radius r from curve c
%
%Syntax
% [X,Y,Z] = fatcurve(c,r);
%
%Description
% [X,Y,Z] = FATCURVE(C, R) sets X, Y and Z to be the coordinates of a
% cylindrical surface at radius R from curve C. This function is intended
% for use wit... |
7037cf0f8affb1a8ff51dbdfe02e804699148b026a4fd5bcda497bcfb62a4c16 | MATLAB | 1,646 | 56 | function [spectrogram]=spectrogram(sd,param)
%unit of timewindow and bin is milisecond while unit of frequency is times/second.
tw=param.spectrogram_timewindow; % Integration Time Win
bin=param.sdbin; % Binsize??
fr=param.frequency_range; % frequency range [min max]
%duration = param.duration;
i... |
4378ed810ef596a97c6d22ce646f840a9053f5d2f487012f5e024a3c492d4d6d | MATLAB | 1,647 | 42 | %% plot%
[file, path] = uigetfile('*.mat','MultiSelect','on');%When the user clicks the load psetion button, a window should open to enable the user to select a file.
cd(path)
datafile = fullfile(path, file); %save path
w = 2;% window for ploting (2 = sustaneid)
%%
for i = 1:length(datafile)
load(datafile{... |
73ea9ffa188aefb6d6e75fb1bedd30df4cac4724d01791a8bb50430083b23838 | MATLAB | 1,647 | 39 | function [Beads]=mnl_ExtractBeadInfoFromICY_temp(fname)
% Function to extract the bead information
%% Pre-allocate the structure
Beads=struct('BeadLocation',[],'BeadSize',[],'BeadCentre',[],'BeadExtremes',[],'ImageLimits',[]);
%% Info from excel sheet
[~,txt,~]=xlsread(fname);
NumSpots=size(txt,1)-1;
for i=1:NumSpots
... |
170b8f0c167dc962aee70857f8c0ab1767787f76356c889f6f4fc39de5804dd3 | MATLAB | 1,648 | 46 | function [] = imwriteTFSK(Volume,name)
%% write 3D image file
%% supported formats: single/double/uint8/uint16
%% Input:
% @Volume: the 3D image
% @name: the file path
%
% [1] JIAMIN WU, ZHI LU and DONG JIANG etc,
% Iterative tomography with digital adaptive optics permits hour-long intravital obse... |
76ff91fc576d4fe89e44048833730fb0a79677114c482e7b8961e191ca0cd441 | MATLAB | 1,649 | 68 | function Plot_deepDreamImage()
Save_Predictions = 0;
D = dir('D:\Omer\Neuronalizer\Resources\CNN\Input_Samples\Good');
D(find([D.isdir])) = [];
File1 = load('D:\Omer\Neuronalizer\Resources\CNN\Runs\7.mat','My_CNN');
My_CNN = File1.My_CNN;
% Layers = {'conv_1','conv_2','conv_3','conv_4','conv_5'};
Channel... |
aae63505f348ffc968aef849a04151e888fa914444c51ae5da04e5548b8d8905 | MATLAB | 1,651 | 56 | function argsort = orderClusters(obj, by)
%ORDERCLUSTERS Arrange cluster ID numbers by some criterion
if nargin < 2 || isempty(by) || (~strcmp(by, 'Y + X') && ~isprop(obj, by))
by = 'clusterSites';
end
if strcmpi(by, 'Y + X') && ~isempty(obj.clusterCentroids)
[~, argsort] = sort(sum(obj... |
743d1445ca86ccece5170902801f2b21ffae93cbacaaf87b110f6cb18e523f24 | MATLAB | 1,652 | 52 | clear all
clc
odors = {'hex10','hex','iaa','two_oct','hxa','two_hep','ani','hex01',...
'msal','lcar','euc','gua','chex','bza','ger','etha',...
'apin','one_oc3','neem','gar','cit','lin'};
c = 1/255*[[33 125 255];[33 125 255];[33 125 255];...
[33 125 255];[33 125 255];[86 105 105];[86 105 105];...
... |
cb2f3f5623b038b068148ec8a686746a06cfefc1b5cb8453a240eb6349110c15 | MATLAB | 1,652 | 54 | % Copied from gampmatlab toolbox
% http://gampmatlab.wikia.com/wiki/Generalized_Approximate_Message_Passing
%
% Finds the flipped, circ-shifted, and phase-rot version of "in" that best matches "ref"
%
% [out,fxnvec,fxnmat]=disambig2Drfft(in,ref,n1,n2)
function [out,fxnvec,fxnmat]=disambig2Drfft(in,ref,n1,n2)
... |
171a195687d6ff6a827354777b008d1adfb4dda4cd0c85407af555587521900e | MATLAB | 1,653 | 73 | function [mean_resp, se_resp, mean_s_fr, se_s_fr] = get_mean_resp(session, channel, unit, fold, period, probe, window)
% Get mean response and mean firing rate of s-model for a specific neuron
%
% Parameters
% ----------
%
% - fold: integer scalar
% Fold number
% - period: [scalar, scalar]
% Time period from saccad... |
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