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
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