 |
The Journal of Neuroscience, July 6, 2005, 25(27):6435-6448; doi:10.1523/JNEUROSCI.1132-05.2005
Previous Article | Next Article 
Behavioral/Systems/Cognitive
On the Computations Analyzing Natural Optic Flow: Quantitative Model Analysis of the Blowfly Motion Vision Pathway
J. P. Lindemann,1
R. Kern,1
J. H. van Hateren,3
H. Ritter,2 and
M. Egelhaaf1
1Department of Neurobiology, Faculty for Biology, and 2Department of Neuroinformatics, Technical Faculty, Bielefeld University, D-33501 Bielefeld, Germany, and 3Department of Neurobiophysics, University of Groningen, 9747 AG Groningen, The Netherlands
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.
Key words: natural stimuli; movement detection; optic flow; eye movements; gain control; modeling
Received Dec 30, 2004;
revised May 20, 2005;
accepted May 20, 2005.
This article has been cited by other articles:

|
 |

|
 |
 
S. N. Fry, N. Rohrseitz, A. D. Straw, and M. H. Dickinson
Visual control of flight speed in Drosophila melanogaster
J. Exp. Biol.,
April 15, 2009;
212(8):
1120 - 1130.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
K. Pfeiffer, I. Panek, U. Hoger, A. S. French, and P. H. Torkkeli
Random Stimulation of Spider Mechanosensory Neurons Reveals Long-Lasting Excitation by GABA and Muscimol
J Neurophysiol,
January 1, 2009;
101(1):
54 - 66.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
M. N. Safran, V. L. Flanagin, A. Borst, and H. Sompolinsky
Adaptation and Information Transmission in Fly Motion Detection
J Neurophysiol,
December 1, 2007;
98(6):
3309 - 3320.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
A. D. Straw, E. J. Warrant, and D. C. O'Carroll
A `bright zone' in male hoverfly (Eristalis tenax) eyes and associated faster motion detection and increased contrast sensitivity
J. Exp. Biol.,
November 1, 2006;
209(21):
4339 - 4354.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
K. Karmeier, J. H. van Hateren, R. Kern, and M. Egelhaaf
Encoding of Naturalistic Optic Flow by a Population of Blowfly Motion-Sensitive Neurons
J Neurophysiol,
September 1, 2006;
96(3):
1602 - 1614.
[Abstract]
[Full Text]
[PDF]
|
 |
|

|
 |

|
 |
 
P. Neri
Spatial Integration of Optic Flow Signals in Fly Motion-Sensitive Neurons
J Neurophysiol,
March 1, 2006;
95(3):
1608 - 1619.
[Abstract]
[Full Text]
[PDF]
|
 |
|
|