Elementary movement detectors in an insect visual system

Buchner, Erich

doi:10.1007/bf00360648

Cited by 305 publications

(235 citation statements)

References 41 publications

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“…42). In particular, the optomotor response of flies (22,23,43) and recordings from the motion-sensitive interneurons H1 (44) provided strong evidence that the velocity optimum indeed shifts as predicted with the wavelength of the pattern. Whereas most of these studies used low light levels with , presumably, low SNRs, pattern dependency was also found in Drosophila optomotor behavior at high mean luminance levels of Ϸ320 cd͞m 2 and a pattern contrast of 100% (24).…”

Section: Discussionmentioning

confidence: 86%

“…Strong evidence for the Reichardt model and against the gradient detector had also been provided by behavioral measurements of the fly optomotor response (22,23) showing that the optimal stimulus velocity increased with pattern wavelength. Again, however, apart from one study (24), mean luminance levels were rather low, leaving room for alternative interpretations (see above).…”

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confidence: 91%

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Fly motion vision is based on Reichardt detectors regardless of the signal-to-noise ratio

Haag

Denk

Borst

2004

Proc. Natl. Acad. Sci. U.S.A.

124

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The computational structure of an optimal motion detector was proposed to depend on the signal-to-noise ratio (SNR) of the stimulus: At low SNR, the optimal motion detector should be a correlation or ''Reichardt'' type, whereas at high SNR, the detector would employ a gradient scheme [ Although a large body of experiments supports the Reichardt detector as the processing scheme leading to direction selectivity in fly motion vision, in most of these studies the SNR was rather low. We therefore reinvestigated the question over a much larger SNR range. Using 2-photon microscopy, we found that local dendritic [Ca 2؉ ] modulations, which are characteristic of Reichardt detectors, occur in response to drifting gratings over a wide range of luminance levels and contrasts. We also explored, as another fingerprint of Reichardt detectors, the dependence of the velocity optimum on the pattern wavelength. Again, we found Reichardt-typical behavior throughout the whole luminance and contrast range tested. Our results, therefore, provide strong evidence that only a single elementary processing scheme is used in fly motion vision.calcium imaging ͉ computational model ͉ motion detection I n motion vision, two distinct models have been proposed to account for direction selectivity: the Reichardt detector and the gradient detector (Fig. 1). In the Reichardt detector (also called Hassenstein-Reichardt detector or correlation-type motion detector), the luminance levels of two neighboring image locations are multiplied after being filtered asymmetrically (Fig. 1a). This operation is performed twice in a mirror-symmetrical fashion before the outputs of both multipliers are subtracted from one another (1-4). The spatial or temporal average of such local motion detector signals is proportional to the image velocity within a range set by the detector time constant (5). It is one of the hallmarks of this model, however, that the output of the individual velocity detectors depends on the spatial structure of the moving pattern (in addition to the stimulus velocity) in a characteristic way. In response to drifting gratings, for example, the local Reichardt detector output consists of two components: a sustained [direct current (DC)] component, which indicates by its sign the direction of the moving stimulus, and an alternating current (AC) component, which follows the local intensity modulation and, thus, carries no directional information at all. Because the local intensity modulations are phase-shifted with respect to each other, the AC components in the local signals are cancelled by the spatial integration of many adjacent detectors. Unlike the AC component, the DC component survives spatial or temporal averaging (integration). The global output signal, therefore, is purely directional. It is predicted to exhibit a distinct optimum as a function of stimulus velocity for each pattern wavelength. The ratio of velocity and spatial wavelength at this optimum corresponds to a certain temporal frequency, which is the number of spatial patter...

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Section: Discussionmentioning

confidence: 86%

mentioning

confidence: 91%

Fly motion vision is based on Reichardt detectors regardless of the signal-to-noise ratio

Haag

Denk

Borst

2004

Proc. Natl. Acad. Sci. U.S.A.

124

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“…In principle, the locomotion simulator was the same as described in previous studies 8,25 . According to the procedure described in the next section, a subject fly was tethered with a metal wire on its dorsal thorax and positioned over an air-supported Styrofoam ball of 6 mm in diameter.…”

Section: Nature Communications | Doimentioning

confidence: 99%

Visually induced initiation of Drosophila innate courtship-like following pursuit is mediated by central excitatory state

2015

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“…The correlational EMD produces a motion-related output without computing derivatives (a process that would amplify noise). Evidence suggests that EMDs are formed between at least nearest neighbors and next-nearest neighbors on the hexagonal lattice (Buchner, 1976), and are thus aligned with various directions in visual space. The output of the correlational EMD in response to a moving visual scene is typically unsteady, with transients generated in response to the passage of edges or contrast gradients.…”

Section: Elementary Motion Detectionmentioning

confidence: 99%

Velocity constancy and models for wide-field visual motion detection in insects

2005

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Abstract. The tangential neurons in the lobula plate region of the flies are known to respond to visual motion across broad receptive fields in visual space. When intracellular recordings are made from t angential neurons while the intact animal is stimulated visually with moving natural imagery, we find that neural response depends upon speed of motion but is nearly invariant with respect to variations in natural scenery. We refer to this invariance as velocity constancy. It is remarkable because natural scenes, in spite of similarities in spatial structure, vary considerably in contrast, and contrast dependence is a feature of neurons in the early visual pathway as well as of most models for the elementary operations of visual motion detection. Thus, we expect that operations must be present in the processing pathway that reduce contrast dependence in order to approximate velocity constancy. We consider models for such operations, including spatial filtering, motion adaptation, saturating nonlinearities, and nonlinear spatial integration by the tangential neurons themselves, and evaluate their effects in simulations of a tangential neuron and precursor processing in response to animated natural imagery. We conclude that all such features reduce interscene variance in response, but that the model system does not approach velocity constancy as closely as the biological tangential cell.

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Elementary movement detectors in an insect visual system

Cited by 305 publications

References 41 publications

Fly motion vision is based on Reichardt detectors regardless of the signal-to-noise ratio

Fly motion vision is based on Reichardt detectors regardless of the signal-to-noise ratio

Visually induced initiation of Drosophila innate courtship-like following pursuit is mediated by central excitatory state

Velocity constancy and models for wide-field visual motion detection in insects

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