On the computations analyzing natural optic flow: Quantitative model analysis of the blowfly motion vision pathway

Lindemann JP, Kern R, van Hateren JH, Ritter H, Egelhaaf M (2005)
J Neurosci. 25(27): 6435-6448.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Abstract / Bemerkung
For many animals, including humans, the optic flow generated on the eyes during locomotion is an important source of information about self-motion and the structure of the environment. The blowfly has been used frequently as a model system for experimental analysis of optic flow processing at the microcircuit level. Here, we describe a model of the computational mechanisms implemented by these circuits in the blowfly motion vision pathway. Although this model was originally proposed based on simple experimenter-designed stimuli, we show that it is also capable to quantitatively predict the responses to the complex dynamic stimuli a blowfly encounters in free flight. In particular, the model visual system exploits the active saccadic gaze and flight strategy of blowflies in a similar way, as does its neuronal counterpart. The model circuit extracts information about translation velocity in the intersaccadic intervals and thus, indirectly, about the three-dimensional layout of the environment. By stepwise dissection of the model circuit, we determine which of its components are essential for these remarkable features. When accounting for the responses to complex natural stimuli, the model is much more robust against parameter changes than when explaining the neuronal responses to simple experimenter-defined stimuli. In contrast to conclusions drawn from experiments with simple stimuli, optimization of the parameter set for different segments of natural optic flow stimuli do not indicate pronounced adaptational changes of these parameters during long-lasting stimulation.
Stichworte
gain; eye movements; natural stimuli; modeling; movement detection; optic flow; control
Erscheinungsjahr
2005
Zeitschriftentitel
J Neurosci.
Band
25
Ausgabe
27
Seite(n)
6435-6448
ISSN
0270-6474
eISSN
1529-2401
Page URI
https://pub.uni-bielefeld.de/record/1603036

Zitieren

Lindemann JP, Kern R, van Hateren JH, Ritter H, Egelhaaf M. On the computations analyzing natural optic flow: Quantitative model analysis of the blowfly motion vision pathway. J Neurosci. 2005;25(27):6435-6448.
Lindemann, J. P., Kern, R., van Hateren, J. H., Ritter, H., & Egelhaaf, M. (2005). On the computations analyzing natural optic flow: Quantitative model analysis of the blowfly motion vision pathway. J Neurosci., 25(27), 6435-6448. https://doi.org/10.1523/JNEUROSCI.1132-05.2005
Lindemann, Jens Peter, Kern, Roland, van Hateren, JH, Ritter, Helge, and Egelhaaf, Martin. 2005. “On the computations analyzing natural optic flow: Quantitative model analysis of the blowfly motion vision pathway”. J Neurosci. 25 (27): 6435-6448.
Lindemann, J. P., Kern, R., van Hateren, J. H., Ritter, H., and Egelhaaf, M. (2005). On the computations analyzing natural optic flow: Quantitative model analysis of the blowfly motion vision pathway. J Neurosci. 25, 6435-6448.
Lindemann, J.P., et al., 2005. On the computations analyzing natural optic flow: Quantitative model analysis of the blowfly motion vision pathway. J Neurosci., 25(27), p 6435-6448.
J.P. Lindemann, et al., “On the computations analyzing natural optic flow: Quantitative model analysis of the blowfly motion vision pathway”, J Neurosci., vol. 25, 2005, pp. 6435-6448.
Lindemann, J.P., Kern, R., van Hateren, J.H., Ritter, H., Egelhaaf, M.: On the computations analyzing natural optic flow: Quantitative model analysis of the blowfly motion vision pathway. J Neurosci. 25, 6435-6448 (2005).
Lindemann, Jens Peter, Kern, Roland, van Hateren, JH, Ritter, Helge, and Egelhaaf, Martin. “On the computations analyzing natural optic flow: Quantitative model analysis of the blowfly motion vision pathway”. J Neurosci. 25.27 (2005): 6435-6448.
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33 Zitationen in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

Local motion adaptation enhances the representation of spatial structure at EMD arrays.
Li J, Lindemann JP, Egelhaaf M., PLoS Comput Biol 13(12), 2017
PMID: 29281631
Peripheral Processing Facilitates Optic Flow-Based Depth Perception.
Li J, Lindemann JP, Egelhaaf M., Front Comput Neurosci 10(), 2016
PMID: 27818631
Flying Drosophila stabilize their vision-based velocity controller by sensing wind with their antennae.
Fuller SB, Straw AD, Peek MY, Murray RM, Dickinson MH., Proc Natl Acad Sci U S A 111(13), 2014
PMID: 24639532
Texture dependence of motion sensing and free flight behavior in blowflies.
Lindemann JP, Egelhaaf M., Front Behav Neurosci 6(), 2012
PMID: 23335890
Tracking improves performance of biological collision avoidance models.
Pant V, Higgins CM., Biol Cybern 106(4-5), 2012
PMID: 22744199
Spatial vision in insects is facilitated by shaping the dynamics of visual input through behavioral action.
Egelhaaf M, Boeddeker N, Kern R, Kurtz R, Lindemann JP., Front Neural Circuits 6(), 2012
PMID: 23269913
Contrast-independent biologically inspired motion detection.
Babies B, Lindemann JP, Egelhaaf M, Möller R., Sensors (Basel) 11(3), 2011
PMID: 22163800
Binocular integration of visual information: a model study on naturalistic optic flow processing.
Hennig P, Kern R, Egelhaaf M., Front Neural Circuits 5(), 2011
PMID: 21519385
Dynamics of optomotor responses in Drosophila to perturbations in optic flow.
Theobald JC, Ringach DL, Frye MA., J Exp Biol 213(pt 8), 2010
PMID: 20348349
Spatiotemporal response properties of optic-flow processing neurons.
Weber F, Machens CK, Borst A., Neuron 67(4), 2010
PMID: 20797539
Mimicking honeybee eyes with a 280 degrees field of view catadioptric imaging system.
Stürzl W, Boeddeker N, Dittmar L, Egelhaaf M., Bioinspir Biomim 5(3), 2010
PMID: 20689158
Visual control of altitude in flying Drosophila.
Straw AD, Lee S, Dickinson MH., Curr Biol 20(17), 2010
PMID: 20727759
Random stimulation of spider mechanosensory neurons reveals long-lasting excitation by GABA and muscimol.
Pfeiffer K, Panek I, Höger U, French AS, Torkkeli PH., J Neurophysiol 101(1), 2009
PMID: 19004993
Bio-inspired motion detection in an FPGA-based smart camera module.
Köhler T, Röchter F, Lindemann JP, Möller R., Bioinspir Biomim 4(1), 2009
PMID: 19258686
Robust models for optic flow coding in natural scenes inspired by insect biology.
Brinkworth RS, O'Carroll DC., PLoS Comput Biol 5(11), 2009
PMID: 19893631
Saccadic flight strategy facilitates collision avoidance: closed-loop performance of a cyberfly.
Lindemann JP, Weiss H, Möller R, Egelhaaf M., Biol Cybern 98(3), 2008
PMID: 18180948
Active sensing: matching motor and sensory space.
Schuster S., Curr Biol 18(4), 2008
PMID: 18302925
Fly vision: neural mechanisms of motion computation.
Egelhaaf M., Curr Biol 18(8), 2008
PMID: 18430633
Adaptation and information transmission in fly motion detection.
Safran MN, Flanagin VL, Borst A, Sompolinsky H., J Neurophysiol 98(6), 2007
PMID: 17928564
Adaptive motor behavior in insects.
Ritzmann RE, Büschges A., Curr Opin Neurobiol 17(6), 2007
PMID: 18308559
Encoding of naturalistic optic flow by a population of blowfly motion-sensitive neurons.
Karmeier K, van Hateren JH, Kern R, Egelhaaf M., J Neurophysiol 96(3), 2006
PMID: 16687623

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