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Data modelling for analysis of adaptive changes in fly photoreceptors

Friederich, U., Coca, D., Billings, S.A. and Juusola, M. (2009) Data modelling for analysis of adaptive changes in fly photoreceptors. Research Report. ACSE Research Report no. 995 . Automatic Control and Systems Engineering, University of Sheffield

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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 modeling 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.

Item Type: Monograph (Research Report)
Copyright, Publisher and Additional Information: The Department of Automatic Control and Systems Engineering research reports offer a forum for the research output of the academic staff and research students of the Department at the University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. Some papers in the series may have been subsequently published elsewhere and you are advised to cite the later published version in these instances.
Keywords: Non-linear system identification;NARMAX;Generalized frequency response functions; Neural adaptation; Gain adaptation; Drosophila; Naturalistic stimulation
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) > ACSE Research Reports
Depositing User: Miss Anthea Tucker
Date Deposited: 16 Oct 2012 09:49
Last Modified: 06 Jun 2014 06:46
Status: Published
Publisher: Automatic Control and Systems Engineering, University of Sheffield
URI: http://eprints.whiterose.ac.uk/id/eprint/74648

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