Abstract
The classical Hassenstein-Reichardt mathematical elementary motion detector (EMD) model is treated analytically. The EMD is stimulated with drifting sinusoidal gratings, which are often used in motion vision research, thus enabling direct comparison with neural responses from motion-sensitive neurones in the fly brain. When sinusoidal gratings are displayed on a cathode ray tube monitor, they are modulated by the refresh rate of the monitor. This generates a pulsatile signature of the visual stimulus, which is also seen in the neural response. Such pulsatile signals make a Laguerre domain identification method for estimating the parameters of a single EMD suitable, allowing estimation of both finite and infinite-dimensional dynamics. To model the response of motion-sensitive neurones with large receptive fields, a pool of spatially distributed EMDs is considered, with the weights of the contributing EMDs fitted to the neural data by a sparse estimation method. Such an EMD-array is more reliably estimated by stimulating with multiple sinusoidal gratings, since these provide higher spatial excitation than a single sinusoidal grating. Consequently, a way of designing the visual stimuli for a certain order of spatial resolution is suggested.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
A. Borst, M. Egelhaaf, Principles of visual motion detection. Trends Neurosci. 12, 297–306 (1989)
A. Borst, T. Euler, Seeing things in motion: models, circuits, and mechanisms. Neuron 71, 974–994 (2011)
M. Egelhaaf, A. Borst, W. Reichardt, Computational structure of a biological motion-detection system as revealed by local detector analysis in the fly’s nervous system. Vis. Res. 20, 397–407 (1989)
B. Fischer, A. Medvedev, L 2 time delay estimation by means of Laguerre functions, in American Control Conference, ACC’99, San Diego, June 1999
N. Franceschini, A. Riehle, A. Le Nestour, Directionally selective motion detection by insect neurons, in Facets of Vision, ed. by D.G. Stavenga, R.C. Hardie (Springer, Berlin/Heidelberg, 1989), pp. 360–390
C. Glader, G. Hönäs, P.M. Mäkilä, H.T. Toivonen, Approximation of delay systems – a case study. Int. J. Control 53, 369–390 (1991)
B. Hassenstein, W. Reichardt, Systemtheoretische Analyse der Zeit-, Reihenfolgen- und Vorzeichenauswertung bei der Bewegungsperzeption des Rüsselkäfers Chlorophanus. Zeitschrift für Naturforschung 11, 513–524 (1956)
E. Hidayat, A. Medvedev, Laguerre domain identification of continuous linear time-delay systems from impulse response data. Automatica 48(11), 2902–2907 (2012)
E. Hidayat, A. Medvedev, K. Nordström, Laguerre domain identification of the elementary motion detector model in insect vision, in 11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, ALCOSP 2013, Caen, July 2013
E. Hidayat, A. Medvedev, K. Nordström, On identification of elementary motion detectors, in International Symposium on Computational Models for Life Sciences, Sydney, Nov 2013, vol. 1559, pp. 14–23
A.C. James, D. Osorio, Characterisation of columnar neurons and visual signal processing in the medulla of the locust optic lobe by system identification techniques. J. Compar. Physiol. A 178(2), 183–199 (1996)
P.M. Mäkilä, J.R. Partington, Laguerre and Kautz shift approximations of delay systems. Int. J. Control 72(10), 932–946 (1999)
P.Z. Marmarelis, G.D. McCann, Development and application of white-noise modeling techniques for studies of insect visual nervous system. Kybernetik 12, 74–89 (1973)
J.M. Zanker, M.V. Srinivasan, M. Egelhaaf, Speed tuning in elementary motion detectors of the correlation type. Biol. Cybern. 80(2), 109–116 (1999)
Acknowledgements
This work was supported by European Research Council via the Advanced Grant 247035 (to EH, AM, SysTEAM), and the Swedish Research Council (to KN, VR 2008-2933).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Hidayat, E., Medvedev, A., Nordström, K. (2015). Identification of the Reichardt Elementary Motion Detector Model. In: Sun, C., Bednarz, T., Pham, T., Vallotton, P., Wang, D. (eds) Signal and Image Analysis for Biomedical and Life Sciences. Advances in Experimental Medicine and Biology, vol 823. Springer, Cham. https://doi.org/10.1007/978-3-319-10984-8_5
Download citation
DOI: https://doi.org/10.1007/978-3-319-10984-8_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10983-1
Online ISBN: 978-3-319-10984-8
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)