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Data Modelling for Analysis of Adaptive Changes in Fly Photoreceptors

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Neural Information Processing (ICONIP 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5863))

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Abstract

Adaptation is a hallmark of sensory processing. We studied neural adaptation in intracellular voltage responses of the R1-R6 photoreceptors, of the fruit fly Drosophila, subjected to light patterns of naturalistic distribution at varying intensity levels. We use experimental data in a stepwise empirical modelling procedure to estimate a non-linear dynamical model (NARMAX) with variable gain. This model can describe accurately the observed adaptation process at each new level of changing light inputs. Generalized frequency response functions were used to visualize and quantify adaptation in the frequency domain.

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Author information

Authors and Affiliations

  1. Department of Automatic Control and Systems Engineering, University of Sheffield, Mappin Street, Sheffield, S1 3JD

    Uwe Friederich, Daniel Coca & Stephen Billings

  2. Department of Biomedical Science, Western Bank, Sheffield, S10 2TN, UK

    Uwe Friederich & Mikko Juusola

Authors
  1. Uwe Friederich
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  2. Daniel Coca
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  3. Stephen Billings
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  4. Mikko Juusola
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Editor information

Editors and Affiliations

  1. Department of Electronic Engineering, City University of Hong Kong, Hong Kong,  

    Chi Sing Leung

  2. School of Electrical Engineering and Computer Science, Kyungpook National University, 1370 Sankyuk-Dong, Puk-Gu, 702-701, Taegu, Korea

    Minho Lee

  3. School of Information Technology, King Mongkut’s University of Technology Thonburi, 126 Pracha-U-Thit Rd., Bangmod, Thungkru, 10140, Bangkok, Thailand

    Jonathan H. Chan

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© 2009 Springer-Verlag Berlin Heidelberg

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Friederich, U., Coca, D., Billings, S., Juusola, M. (2009). Data Modelling for Analysis of Adaptive Changes in Fly Photoreceptors. In: Leung, C.S., Lee, M., Chan, J.H. (eds) Neural Information Processing. ICONIP 2009. Lecture Notes in Computer Science, vol 5863. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10677-4_5

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  • DOI: https://doi.org/10.1007/978-3-642-10677-4_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10676-7

  • Online ISBN: 978-3-642-10677-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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