Biomedical Engineering Reference
In-Depth Information
Chapter 14
ModellingFlyMotionVision
Alexander Borst
Max-Planck-Institute of Neurobiology, Department of Systems and Computational
Neurobiology, Am Klopferspitz 18a D-82152 Martinsried, Germany
CONTENTS
14.1 The fly motion vision system: an overview
14.2 Mechanisms of local motion detection: the correlation detector
14.2.1 Steady-state response properties
14.2.2 Dynamic response properties
14.2.3 Additional filters and adaptive properties
14.3 Spatial processing of local motion signals by Lobula plate tangential
cells
14.3.1 Compartmental models of tangential cells
14.3.2 Dendritic integration and gain control
14.3.3 Binocular interactions
14.3.4 Dendro-dendritic interactions
14.4 Conclusions
References
14.1 The fly motion vision system: an overview
Whenever an animal is moving in its environment, moves its eyes or an object moves
in front of its eyes, the visual system is confronted with motion. However, this
motion information is not explicitly represented in the two-dimensional brightness
pattern of the retinal image. Instead, motion has to be computed from the tempo-
ral brightness changes in the retinal image. This is one of the first and most basic
processing steps performed by the visual system. This primary process of motion de-
tection has become a key issue in computational neuroscience, because it represents
a neural computation well described at the algorithmic level that has not been under-
stood at the cellular level in any species so far, yet simple enough to be optimistic in
this respect for the future. The development of models of motion detection has been
experimentally driven in particular by investigations on two systems, the rabbit retina
[1] and the insect visual system [49]. Vice versa, there is probably no other field in
system neuroscience where experiments were more influenced by theory than in the
 
Search WWH ::




Custom Search