Realization of multiple neural activity resolutions via multidimensional ensemble empirical mode decomposition of calcium imaging data: a proof of concept

Samuel Akwei-Sekyere

doi:10.7287/peerj.preprints.1441v1

1 Neuroscience Program, Michigan State University, East Lansing, Michigan, United States

2 Department of Mathematics, Michigan State University, East Lansing, Michigan, United States

DOI: 10.7287/peerj.preprints.1441v1

Published: 2015-10-21
Accepted: 2015-10-21

Subject Areas: Bioinformatics, Computational Biology, Neuroscience
Keywords: calcium imaging, multidimensional ensemble empirical mode decomposition, computational neuroscience, systems neuroscience

Copyright: © 2015 Akwei-Sekyere
Licence: This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.

Cite this article: Akwei-Sekyere S. 2015. Realization of multiple neural activity resolutions via multidimensional ensemble empirical mode decomposition of calcium imaging data: a proof of concept. PeerJ PrePrints 3:e1441v1 https://doi.org/10.7287/peerj.preprints.1441v1

Abstract

One of the goals of systems and computational neuroscience is to understand how information is processed by a single neuron and integrated by a network of neurons. A plausible approach to identifying spatial neighborhoods of the brain that host potential neural networks of interest is by observing spatially-bounded aggregates of neural activity. To this end, the potential of the multidimensional ensemble empirical mode decomposition algorithm in extracting multiple resolutions of neural activity from calcium imaging data is evaluated.