Scaled FitzHugh-Nagumo equations as building blocks for modelling dynamics adjusted to measurable biophysical data

Eugene B. Postnikov, Olga V. Titkova, Anastasia I. Lavrova

Результат исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаярецензирование

Выдержка

We apply the method of scaling fitting of the FitzHugh-Nagumo equation to describe a circuit consisting of the two coupled neurons aimed to reproduce non-stationary EEG modulations of theta-rhythm emerging during a rat's run along a linear track. It is shown that such an approach allows a quantitative reproduction of recorded oscillations and, therefore, may be used for a further development of computational models describing the spatial navigation in a rat brain.

Язык оригиналаанглийский
Название основной публикацииICIIBMS 2017 - 2nd International Conference on Intelligent Informatics and Biomedical Sciences
ИздательInstitute of Electrical and Electronics Engineers Inc.
Страницы13-14
Число страниц2
Том2018-January
ISBN (электронное издание)9781509066643
ISBN (печатное издание)9781509066643
DOI
СостояниеОпубликовано - 2 фев 2018
Событие2nd International Conference on Intelligent Informatics and Biomedical Sciences, ICIIBMS 2017 - Okinawa, Япония
Продолжительность: 23 ноя 201725 ноя 2017

Серия публикаций

НазваниеICIIBMS 2017 - 2nd International Conference on Intelligent Informatics and Biomedical Sciences
Том2018-January

Конференция

Конференция2nd International Conference on Intelligent Informatics and Biomedical Sciences, ICIIBMS 2017
СтранаЯпония
ГородOkinawa
Период23/11/1725/11/17

Отпечаток

FitzHugh-Nagumo Equations
Dynamic Modeling
Building Blocks
Rats
Electroencephalography
Computational Model
Neurons
Navigation
Neuron
Brain
Modulation
Scaling
Oscillation
Networks (circuits)
Electroencephalogram

Предметные области Scopus

  • Искусственный интеллект
  • Компьютерные сети и коммуникации
  • Информационные системы
  • Биомедицинская техника
  • Безопасность, риски, качество и надежность
  • Теория оптимизации

Цитировать

Postnikov, E. B., Titkova, O. V., & Lavrova, A. I. (2018). Scaled FitzHugh-Nagumo equations as building blocks for modelling dynamics adjusted to measurable biophysical data. В ICIIBMS 2017 - 2nd International Conference on Intelligent Informatics and Biomedical Sciences (Том 2018-January, стр. 13-14). (ICIIBMS 2017 - 2nd International Conference on Intelligent Informatics and Biomedical Sciences; Том 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIIBMS.2017.8279687
Postnikov, Eugene B. ; Titkova, Olga V. ; Lavrova, Anastasia I. / Scaled FitzHugh-Nagumo equations as building blocks for modelling dynamics adjusted to measurable biophysical data. ICIIBMS 2017 - 2nd International Conference on Intelligent Informatics and Biomedical Sciences. Том 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. стр. 13-14 (ICIIBMS 2017 - 2nd International Conference on Intelligent Informatics and Biomedical Sciences).
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abstract = "We apply the method of scaling fitting of the FitzHugh-Nagumo equation to describe a circuit consisting of the two coupled neurons aimed to reproduce non-stationary EEG modulations of theta-rhythm emerging during a rat's run along a linear track. It is shown that such an approach allows a quantitative reproduction of recorded oscillations and, therefore, may be used for a further development of computational models describing the spatial navigation in a rat brain.",
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Postnikov, EB, Titkova, OV & Lavrova, AI 2018, Scaled FitzHugh-Nagumo equations as building blocks for modelling dynamics adjusted to measurable biophysical data. в ICIIBMS 2017 - 2nd International Conference on Intelligent Informatics and Biomedical Sciences. том. 2018-January, ICIIBMS 2017 - 2nd International Conference on Intelligent Informatics and Biomedical Sciences, том. 2018-January, Institute of Electrical and Electronics Engineers Inc., стр. 13-14, Okinawa, Япония, 23/11/17. https://doi.org/10.1109/ICIIBMS.2017.8279687

Scaled FitzHugh-Nagumo equations as building blocks for modelling dynamics adjusted to measurable biophysical data. / Postnikov, Eugene B.; Titkova, Olga V.; Lavrova, Anastasia I.

ICIIBMS 2017 - 2nd International Conference on Intelligent Informatics and Biomedical Sciences. Том 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. стр. 13-14 (ICIIBMS 2017 - 2nd International Conference on Intelligent Informatics and Biomedical Sciences; Том 2018-January).

Результат исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаярецензирование

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PY - 2018/2/2

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N2 - We apply the method of scaling fitting of the FitzHugh-Nagumo equation to describe a circuit consisting of the two coupled neurons aimed to reproduce non-stationary EEG modulations of theta-rhythm emerging during a rat's run along a linear track. It is shown that such an approach allows a quantitative reproduction of recorded oscillations and, therefore, may be used for a further development of computational models describing the spatial navigation in a rat brain.

AB - We apply the method of scaling fitting of the FitzHugh-Nagumo equation to describe a circuit consisting of the two coupled neurons aimed to reproduce non-stationary EEG modulations of theta-rhythm emerging during a rat's run along a linear track. It is shown that such an approach allows a quantitative reproduction of recorded oscillations and, therefore, may be used for a further development of computational models describing the spatial navigation in a rat brain.

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KW - FitzHugh-Nagumo model

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Postnikov EB, Titkova OV, Lavrova AI. Scaled FitzHugh-Nagumo equations as building blocks for modelling dynamics adjusted to measurable biophysical data. В ICIIBMS 2017 - 2nd International Conference on Intelligent Informatics and Biomedical Sciences. Том 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. стр. 13-14. (ICIIBMS 2017 - 2nd International Conference on Intelligent Informatics and Biomedical Sciences). https://doi.org/10.1109/ICIIBMS.2017.8279687