Scheduled service maintenance on November 22


On Friday, November 22, 2024, between 06:00 CET and 18:00 CET, GIN services will undergo planned maintenance. Extended service interruptions should be expected. We will try to keep downtimes to a minimum, but recommend that users avoid critical tasks, large data uploads, or DOI requests during this time.

We apologize for any inconvenience.

The function computes the Latency of MUAes by fitting 5 cumulative Gaussian distribution parameters (mu, sigma, alpha, c, d) following (Roelfsema, Tolboom, Khayat, Neuron 2007), developed for (Ferro, van Kempen, Boyd, Panzeri, Thiele, PNAS 2021).
Ferro, D., van Kempen, J., Boyd, M., Panzeri, S. and Thiele, A., 2021. Directed information exchange between cortical layers in macaque V1 and V4 and its modulation by selective attention. Proceedings of the National Academy of Sciences, 118(12), p.e2022097118.
https://doi.org/10.1073/pnas.202209711

Demetrio Ferro a14ce1ec13 Upload files to '' 1 rok temu
LICENSE 1ca89fd363 Update 'LICENSE' 2 lat temu
README.md 01fa75ddb6 Update 'README.md' 2 lat temu
computeLatencies.m c6a8c230ba Update 'computeLatencies.m' 2 lat temu
computeLatencies_offset.m a14ce1ec13 Upload files to '' 1 rok temu
datacite.yml 2481b9f5a8 Update 'datacite.yml' 2 lat temu
demo.m 4fd553e141 Update 'demo.m' 2 lat temu
demo_offset.m a14ce1ec13 Upload files to '' 1 rok temu
sample-signal.png 029b17ab1a Subir archivos a '' 2 lat temu

README.md

Analysis-of-MUAe-latency

% COMPUTE LATENCY function written by Demetrio Ferro <demetrio.ferro@upf.edu>
% Based on (Roelfsema, Tolboom, Khayat, Neuron 2007).
% developed for (Ferro, van Kempen, Boyd, Panzeri, Thiele, PNAS 2021)


% The function computes Latency indices base don MUAes fitted by cumulative 
% gaussian function with 5 (degrees of freedom) parameters (mu, sigma, alpha, c, d).
% The best fit is assigned based on Least Squares (LS) of iterative estimation.

% Inputs:
% MuaeData          [NxT]  Multi-channel (N channels) MUAes in time (T points) 
% MuaeTimes         [1xT]  Timestamps of MUAe recordings (T points)
% lsqTimeRes        [1x1]  Resolution of time series for Latency estimation

% Outputs:
% latTimes          [1xN]  Latency indices at t*:={f(t*)=1/3*max(f(t)),t in MuaeTimes}
% lsqCurveTimes     [1x(T*lsqTimeRes)] Timestamps of fitted curves
% lsqFittedCurve    [Nx(T*lsqTimeRes)] Fitted curves at LS parameters
% lsqFittedParam    [Nx5]  LS parameters
% lsqFitErr         [1xN]  LS error of the fit

Demo with synthetic data

demo signal

datacite.yml
Title A simple tool to compute Latency for MUAe data
Authors Ferro,Demetrio;Department of Information and Communication Technologies, Universitat Pompeu Fabra, 08002 Barcelona, ES;ORCID:0000-0003-4969-1415
Description The tool allows to compute Latency for MUAe data based on Least-Square approximation.
License Creative Commons Attribution-NonCommercial-ShareAlike-4.0 International (https://creativecommons.org/licenses/by-nc-sa/4.0/)
References D. Ferro, J. van Kempen, M. Boyd, S. Panzeri and A. Thiele, PNAS 2021 [doi:10.1073/pnas.2022097118] (IsSupplementTo)
Pieter R.Roelfsema, MichielTolboom, Paul S.Khayat, Neuron 2007 [doi:10.1016/j.neuron.2007.10.006] (IsSupplementTo)
Funding
Keywords Neuroscience
Multi-Unit-Activity
Multicontact electrodes
Resource Type Software