Motion as a source of environmental information: a fresh view on biological motion computation by insect brains
Egelhaaf M, Kern R, Lindemann JP (2014)
Frontiers in Neural Circuits 8: 127.
Zeitschriftenaufsatz
| Veröffentlicht | Englisch
Einrichtung
Abstract / Bemerkung
Despite their miniature brains insects, such as flies, bees and wasps, are able to navigate by highly erobatic flight maneuvers in cluttered environments. They rely on spatial information that is contained in the retinal motion patterns induced on the eyes while moving around (“optic flow”) to accomplish their extraordinary performance. Thereby, they employ an active flight and gaze strategy that separates rapid saccade-like turns from translatory flight phases where the gaze direction is kept largely constant. This behavioral strategy facilitates the processing of environmental information, because information about the distance of the animal to objects in the environment is only contained in the optic flow generated by translatory motion. However, motion detectors as are widespread in biological systems do not represent veridically the velocity of the optic flow vectors, but also reflect textural information about the environment. This characteristic has often been regarded as a limitation of a biological motion detection mechanism. In contrast, we conclude from analyses challenging insect movement detectors with image flow as generated during translatory locomotion through cluttered natural environments that this mechanism represents the contours of nearby objects. Contrast borders are a main carrier of functionally relevant object information in artificial and natural sceneries. The motion detection system thus segregates in a computationally parsimonious way the environment into behaviorally relevant nearby objects and—in many behavioral contexts—less relevant distant structures. Hence, by making use of an active flight and gaze strategy, insects are capable of performing extraordinarily well even with a computationally simple motion detection mechanism.
Stichworte
insects;
spatial vision;
motion detection;
natural environments;
optic flow
Erscheinungsjahr
2014
Zeitschriftentitel
Frontiers in Neural Circuits
Band
8
Seite(n)
127
ISSN
1662-5110
eISSN
1662-5110
Finanzierungs-Informationen
Open-Access-Publikationskosten wurden durch die Deutsche Forschungsgemeinschaft und die Universität Bielefeld gefördert.
Page URI
https://pub.uni-bielefeld.de/record/2701575
Zitieren
Egelhaaf M, Kern R, Lindemann JP. Motion as a source of environmental information: a fresh view on biological motion computation by insect brains. Frontiers in Neural Circuits. 2014;8:127.
Egelhaaf, M., Kern, R., & Lindemann, J. P. (2014). Motion as a source of environmental information: a fresh view on biological motion computation by insect brains. Frontiers in Neural Circuits, 8, 127. doi:10.3389/fncir.2014.00127
Egelhaaf, Martin, Kern, Roland, and Lindemann, Jens Peter. 2014. “Motion as a source of environmental information: a fresh view on biological motion computation by insect brains”. Frontiers in Neural Circuits 8: 127.
Egelhaaf, M., Kern, R., and Lindemann, J. P. (2014). Motion as a source of environmental information: a fresh view on biological motion computation by insect brains. Frontiers in Neural Circuits 8, 127.
Egelhaaf, M., Kern, R., & Lindemann, J.P., 2014. Motion as a source of environmental information: a fresh view on biological motion computation by insect brains. Frontiers in Neural Circuits, 8, p 127.
M. Egelhaaf, R. Kern, and J.P. Lindemann, “Motion as a source of environmental information: a fresh view on biological motion computation by insect brains”, Frontiers in Neural Circuits, vol. 8, 2014, pp. 127.
Egelhaaf, M., Kern, R., Lindemann, J.P.: Motion as a source of environmental information: a fresh view on biological motion computation by insect brains. Frontiers in Neural Circuits. 8, 127 (2014).
Egelhaaf, Martin, Kern, Roland, and Lindemann, Jens Peter. “Motion as a source of environmental information: a fresh view on biological motion computation by insect brains”. Frontiers in Neural Circuits 8 (2014): 127.
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