Sleep State Analysis Using Calcium Imaging Data by Non-negative Matrix Factorization

Mizuo Nagayama, Toshimitsu Aritake, Hideitsu Hino, Takeshi Kanda, Takehiro Miyazaki, Masashi Yanagisawa, Shotaro Akaho, Noboru Murata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Sleep is an essential process for the survival of animals. However, its phenomenon is poorly understood. To understand the phenomenon of sleep, the analysis should be made from the activities of a large number of cortical neurons. Calcium imaging is a recently developed technique that can record a large number of neurons simultaneously, however, it has a disadvantage of low time resolution. In this paper, we aim to discover phenomena which characterize sleep/wake states from calcium imaging data. We made an assumption that groups of neurons become active simultaneously and the neuronal activities of groups differ between sleep and wake states. We used non-negative matrix factorization (NMF) to identify those groups and their neuronal activities in time from calcium imaging data. NMF was used because neural activity can be expressed by the sum of individual neuronal activity and fluorescence intensity data are always positive values. We found that there are certain groups of neurons that behave differently between sleep and wake states.

Original languageEnglish
Title of host publicationArtificial Neural Networks and Machine Learning – ICANN 2019
Subtitle of host publicationTheoretical Neural Computation - 28th International Conference on Artificial Neural Networks, 2019, Proceedings
EditorsIgor V. Tetko, Pavel Karpov, Fabian Theis, Vera Kurková
PublisherSpringer-Verlag
Pages102-113
Number of pages12
ISBN (Print)9783030304867
DOIs
Publication statusPublished - 2019 Jan 1
Event28th International Conference on Artificial Neural Networks, ICANN 2019 - Munich, Germany
Duration: 2019 Sep 172019 Sep 19

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11727 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference28th International Conference on Artificial Neural Networks, ICANN 2019
CountryGermany
CityMunich
Period19/9/1719/9/19

Fingerprint

Non-negative Matrix Factorization
Sleep
Factorization
Calcium
Imaging
Neurons
Neuron
Imaging techniques
Wake
Matrix Factorization
Fluorescence
Animals

Keywords

  • Calcium imaging
  • Non-negative matrix factorization
  • Sleep state analysis

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Nagayama, M., Aritake, T., Hino, H., Kanda, T., Miyazaki, T., Yanagisawa, M., ... Murata, N. (2019). Sleep State Analysis Using Calcium Imaging Data by Non-negative Matrix Factorization. In I. V. Tetko, P. Karpov, F. Theis, & V. Kurková (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation - 28th International Conference on Artificial Neural Networks, 2019, Proceedings (pp. 102-113). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11727 LNCS). Springer-Verlag. https://doi.org/10.1007/978-3-030-30487-4_8

Sleep State Analysis Using Calcium Imaging Data by Non-negative Matrix Factorization. / Nagayama, Mizuo; Aritake, Toshimitsu; Hino, Hideitsu; Kanda, Takeshi; Miyazaki, Takehiro; Yanagisawa, Masashi; Akaho, Shotaro; Murata, Noboru.

Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation - 28th International Conference on Artificial Neural Networks, 2019, Proceedings. ed. / Igor V. Tetko; Pavel Karpov; Fabian Theis; Vera Kurková. Springer-Verlag, 2019. p. 102-113 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11727 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nagayama, M, Aritake, T, Hino, H, Kanda, T, Miyazaki, T, Yanagisawa, M, Akaho, S & Murata, N 2019, Sleep State Analysis Using Calcium Imaging Data by Non-negative Matrix Factorization. in IV Tetko, P Karpov, F Theis & V Kurková (eds), Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation - 28th International Conference on Artificial Neural Networks, 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11727 LNCS, Springer-Verlag, pp. 102-113, 28th International Conference on Artificial Neural Networks, ICANN 2019, Munich, Germany, 19/9/17. https://doi.org/10.1007/978-3-030-30487-4_8
Nagayama M, Aritake T, Hino H, Kanda T, Miyazaki T, Yanagisawa M et al. Sleep State Analysis Using Calcium Imaging Data by Non-negative Matrix Factorization. In Tetko IV, Karpov P, Theis F, Kurková V, editors, Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation - 28th International Conference on Artificial Neural Networks, 2019, Proceedings. Springer-Verlag. 2019. p. 102-113. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-30487-4_8
Nagayama, Mizuo ; Aritake, Toshimitsu ; Hino, Hideitsu ; Kanda, Takeshi ; Miyazaki, Takehiro ; Yanagisawa, Masashi ; Akaho, Shotaro ; Murata, Noboru. / Sleep State Analysis Using Calcium Imaging Data by Non-negative Matrix Factorization. Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation - 28th International Conference on Artificial Neural Networks, 2019, Proceedings. editor / Igor V. Tetko ; Pavel Karpov ; Fabian Theis ; Vera Kurková. Springer-Verlag, 2019. pp. 102-113 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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