NDLI: Estimation of a mean template from spike-train data

Content Provider	IEEE Xplore Digital Library
Author	Wei Wu Srivastava, A.
Copyright Year	2012
Description	Author affiliation: Dept. of Stat., Florida State Univ., Tallahassee, FL, USA (Wei Wu; Srivastava, A.)
Abstract	Computing the template, or the mean, of a set of spike trains is a novel and important task in neural coding. Due to the random nature of spike trains taken from experimental recordings, probabilistic and statistical methods have gained prominence in examining underlying firing patterns. However, these methods focus on modeling neural activity at each given time and therefore their results depend heavily on model assumptions. Taking a model-free and metric-based approach, we analyze the space of spike trains directly and reach algorithms for estimating statistical summaries, such as the mean spike train, of a given set. In our data-driven approach the mean is defined directly in a function space in which the spike trains are viewed as individual points. Here we develop an efficient and convergence-proven algorithm to compute the mean spike train in a general scenario. Experimental result from a neural recoding in primate motor cortex indicates that the estimated means successfully capture the typical patterns in spike trains. In addition, these mean spike trains provide an accurate and efficient performance in decoding motor behaviors.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	1323
Ending Page	1326
File Size	315063
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6346181
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Measurement Computational modeling Analytical models Silicon Mathematical model Image color analysis Training
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Boosting training for myoelectric pattern recognition using Mixed-LDA

Sparse generalized volterra model of human hippocampal spike train transformation for memory prostheses

Model-based data integration in clinical environments

Analysis of local field potential signals: A systems approach

An approach for optimally extending mathematical models of signaling networks using omics data

Regression methods for parameter sensitivity analysis: Applications to cardiac arrhythmia mechanisms

Kernel Density Estimation Using Joint Spatial-Color-Depth Data for Background Modeling

Spectral models for 1D blood flow simulations

Reconstruction of neural network topology using spike train data: Small-world features of hippocampal network

Estimation of a mean template from spike-train data

Similar Documents

Boosting training for myoelectric pattern recognition using Mixed-LDA

Sparse generalized volterra model of human hippocampal spike train transformation for memory prostheses

Model-based data integration in clinical environments

Analysis of local field potential signals: A systems approach

An approach for optimally extending mathematical models of signaling networks using omics data

Regression methods for parameter sensitivity analysis: Applications to cardiac arrhythmia mechanisms

Kernel Density Estimation Using Joint Spatial-Color-Depth Data for Background Modeling

Spectral models for 1D blood flow simulations

Reconstruction of neural network topology using spike train data: Small-world features of hippocampal network

Estimation of a mean template from spike-train data