TY  - JOUR
AB  - 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.
DA  - 2005
DO  - 10.1523/JNEUROSCI.1132-05.2005
KW  - gain
KW  - eye movements
KW  - natural stimuli
KW  - modeling
KW  - movement detection
KW  - optic flow
KW  - control
LA  - eng
IS  - 27
M2  - 6435
PY  - 2005
SN  - 0270-6474
SP  - 6435-6448
T2  - J Neurosci.
TI  - On the computations analyzing natural optic flow: Quantitative model analysis of the blowfly motion vision pathway
UR  - https://nbn-resolving.org/urn:nbn:de:0070-pub-16030362
Y2  - 2024-11-22T03:28:56
ER  -