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On identification of elementary motion detectors
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Physiology. (Motion Vision)
2013 (English)In: Computational Models for Life Sciences: CMLS 2013, Melville, NY: American Institute of Physics (AIP), 2013, 14-23 p.Conference paper, Published paper (Refereed)
Abstract [en]

The classical mathematical elementary motion detector (EMD) model stimulated with sinusoidal and pulsatile input signals is treated analytically. Drifting sinusoidal gratings are often used in insect vision research, enabling direct comparison with biological data. When displayed on a cathode ray tube monitor, the sinusoidal grating is modulated by the refresh rate of the monitor. Due to the resulting pulsatile nature of the visual stimuli and the corresponding biological response, a Laguerre domain identification method for estimating the dynamics of a single EMD appears to be suitable. A pool of spatially distributed EMDs is considered as the model for the measured neural output. The weights of the contributing EMDs are evaluated by a sparse optimization method to fit the experimental data.

Place, publisher, year, edition, pages
Melville, NY: American Institute of Physics (AIP), 2013. 14-23 p.
Series
AIP Conference Proceedings, 1559
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:uu:diva-211725DOI: 10.1063/1.4824991ISI: 000331467600003ISBN: 978-0-7354-1187-6 (print)OAI: oai:DiVA.org:uu-211725DiVA: diva2:668273
Conference
4th International Symposium on Computational Models for Life Sciences
Available from: 2013-10-09 Created: 2013-11-29 Last updated: 2014-03-26Bibliographically approved

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Hidayat, EgiMedvedev, AlexanderNordström, Karin

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