Binocular Integration of Visual Information: A Model Study on Naturalistic Optic Flow Processing.

Hennig P, Kern R, Egelhaaf M (2011)
Frontiers in Neural Circuits 5.

Download
OA
Journal Article | Published | English
Abstract
The computation of visual information from both visual hemispheres is often of functional relevance when solving orientation and navigation tasks. The vCH-cell is a motion-sensitive wide-field neuron in the visual system of the blowfly Calliphora, a model system in the field of optic flow processing. The vCH-cell receives input from various other identified wide-field cells, the receptive fields of which are located in both the ipsilateral and the contralateral visual field. The relevance of this connectivity to the processing of naturalistic image sequences, with their peculiar dynamical characteristics, is still unresolved. To disentangle the contributions of the different input components to the cell?s overall response, we used electrophysiologically determined responses of the vCH-cell and its various input elements to tune a model of the vCH-circuit. Their impact on the vCH-cell response could be distinguished by stimulating not only extended parts of the visual field of the fly, but also selected regions in the ipsi- and contralateral visual field with behaviorally generated optic flow. We show that a computational model of the vCH-circuit is able to account for the neuronal activities of the counterparts in the blowfly?s visual system. Furthermore, we offer an insight into the dendritic integration of binocular visual input.
Publishing Year
ISSN
eISSN
PUB-ID

Cite this

Hennig P, Kern R, Egelhaaf M. Binocular Integration of Visual Information: A Model Study on Naturalistic Optic Flow Processing. Frontiers in Neural Circuits. 2011;5.
Hennig, P., Kern, R., & Egelhaaf, M. (2011). Binocular Integration of Visual Information: A Model Study on Naturalistic Optic Flow Processing. Frontiers in Neural Circuits, 5.
Hennig, P., Kern, R., and Egelhaaf, M. (2011). Binocular Integration of Visual Information: A Model Study on Naturalistic Optic Flow Processing. Frontiers in Neural Circuits 5.
Hennig, P., Kern, R., & Egelhaaf, M., 2011. Binocular Integration of Visual Information: A Model Study on Naturalistic Optic Flow Processing. Frontiers in Neural Circuits, 5.
P. Hennig, R. Kern, and M. Egelhaaf, “Binocular Integration of Visual Information: A Model Study on Naturalistic Optic Flow Processing.”, Frontiers in Neural Circuits, vol. 5, 2011.
Hennig, P., Kern, R., Egelhaaf, M.: Binocular Integration of Visual Information: A Model Study on Naturalistic Optic Flow Processing. Frontiers in Neural Circuits. 5, (2011).
Hennig, Patrick, Kern, Roland, and Egelhaaf, Martin. “Binocular Integration of Visual Information: A Model Study on Naturalistic Optic Flow Processing.”. Frontiers in Neural Circuits 5 (2011).
Main File(s)
Access Level
OA Open Access
Last Uploaded
2012-07-26 19:37:15

This data publication is cited in the following publications:
This publication cites the following data publications:

11 Citations in Europe PMC

Data provided by Europe PubMed Central.

Self-motion perception in the elderly.
Lich M, Bremmer F., Front Hum Neurosci 8(), 2014
PMID: 25309379
Texture dependence of motion sensing and free flight behavior in blowflies.
Lindemann JP, Egelhaaf M., Front Behav Neurosci 6(), 2012
PMID: 23335890
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
Binocular interactions underlying the classic optomotor responses of flying flies.
Duistermars BJ, Care RA, Frye MA., Front Behav Neurosci 6(), 2012
PMID: 22375108

61 References

Data provided by Europe PubMed Central.

Coding efficiency of fly motion processing is set by firing rate, not firing precision.
Spavieri DL Jr, Eichner H, Borst A., PLoS Comput. Biol. 6(7), 2010
PMID: 20661305
Function and coding in the blowfly H1 neuron during naturalistic optic flow.
van Hateren JH, Kern R, Schwerdtfeger G, Egelhaaf M., J. Neurosci. 25(17), 2005
PMID: 15858060
Blowfly flight and optic flow. II. Head movements during flight
Hateren JH, Schilstra C., J. Exp. Biol. 202 (Pt 11)(), 1999
PMID: 10229695
Flight performance and visual control of flight of the free-flying housefly (Musca domestica). I. Organization of the flight motor
Wagner H.., 1986
“Neuronal encoding of visual motion in real-time,”
Warzecha A., Egelhaaf M.., 2001
Temporal precision of the encoding of motion information by visual interneurons.
Warzecha AK, Kretzberg J, Egelhaaf M., Curr. Biol. 8(7), 1998
PMID: 9545194
Reliability of a fly motion-sensitive neuron depends on stimulus parameters.
Warzecha AK, Kretzberg J, Egelhaaf M., J. Neurosci. 20(23), 2000
PMID: 11102498
Performance of a bio-inspired model for the robust detection of moving targets in high dynamic range natural scenes
Wiederman S., Brinkworth R., O'Carroll D.., 2010

Export

0 Marked Publications

Open Data PUB

Web of Science

View record in Web of Science®

Sources

PMID: 21519385
PubMed | Europe PMC

Search this title in

Google Scholar