Extraction of functional domains in optical imaging data using regularized nonnegative matrix factorization

Abstract

Event Abstract Back to Event Extraction of functional domains in optical imaging data using regularized nonnegative matrix factorization Jan Soelter1*, Jan Schumacher2, Antonia Strutz3, Silke Sachse3, Hartwig Spors2 and Michael Schmuker1, 4 1 Freie Universität Berlin, Institute of Biology, Germany 2 Max Planck Institute of Biophysics, Department of Molecular Neurogenetics, Germany 3 Max Planck Institute for Chemical Ecology, Department of Evolutionary Neuroethology, Germany 4 Bernstein Center for Computational Neuroscience Berlin, Germany Functional optical imaging is widely used to measure neuronal activity in the living brain. In many cases, the neuronal activity exhibits spatial structure which reflects a distinct physiological organization of the tissue. However, exact data on that organization is often not available in functional imaging. This poses the challenge of automatically estimating distinct spatial domains and their corresponding stimulus response based on functional data alone. The decomposition of observations into their generating sources is an instance of the Blind Source Separation problem. Previous approaches to this problem were based on Principal and Independent Component Analysis. However, both methods reach their limits if the number of sources lies within the range of the number of images, or even exceeds them. In this contribution, we introduce a regularized non-negative matrix factorization algorithm to overcome this problem. Using a toy dataset, we compare its performance to established approaches. In addition, we demonstrate its applicability in two natural datasets where the non-negativity condition is met: to discover (a) glomeruli, the functional domains of the olfactory bulb in mice, in intrinsic optical images and (b) inhibitory olfactory projection neurons in calcium imaging data of the lateral horn of Drosophila. To cope with the low observation to source ratio, we restricted the generative model in the introduced algorithm in several ways. The non-negative matrix factorization itself imposed the constraint of only positive contributions of the sources. Moreover, a sparseness constraint enforced localized sources. Additionally, we introduced a new modification in the Hierarchical Alternating Least Squares (HALS) algorithm to promote spatially decorrelated sources. Acknowledgements Funded by DFG grant no. SCHM2474/1-1 to M.S. (SPP 1392, principal source of funding), BMBF grant no. 01GQ1001D (BCCN Berlin) to M.S., BMBF grant no. 01GQ0807 to S.S., DFG grant no. SP 1134/2-1to H.S. (SPP 1392). Keywords: calcium imaging, data analysis and machine learning, Drosophila lateral horn, Intrinsic signal imaging, mouse olfactory bulb Conference: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011, Freiburg, Germany, 4 Oct - 6 Oct, 2011. Presentation Type: Poster Topic: data analysis and machine learning (please use "data analysis and machine learning" as keyword) Citation: Soelter J, Schumacher J, Strutz A, Sachse S, Spors H and Schmuker M (2011). Extraction of functional domains in optical imaging data using regularized nonnegative matrix factorization. Front. Comput. Neurosci. Conference Abstract: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011. doi: 10.3389/conf.fncom.2011.53.00077 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 23 Aug 2011; Published Online: 04 Oct 2011. * Correspondence: Mr. Jan Soelter, Freie Universität Berlin, Institute of Biology, Berlin, 14195, Germany, j.soelter@fu-berlin.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Jan Soelter Jan Schumacher Antonia Strutz Silke Sachse Hartwig Spors Michael Schmuker Google Jan Soelter Jan Schumacher Antonia Strutz Silke Sachse Hartwig Spors Michael Schmuker Google Scholar Jan Soelter Jan Schumacher Antonia Strutz Silke Sachse Hartwig Spors Michael Schmuker PubMed Jan Soelter Jan Schumacher Antonia Strutz Silke Sachse Hartwig Spors Michael Schmuker Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.