Saturation in a wide-field, directionally selective movement detection system in fly vision

Lenting, B. P. M.; Mastebroek, H. A. K.; Zaagman, W. H.

doi:10.1016/0042-6989(84)90189-5

Cited by 11 publications

(7 citation statements)

References 25 publications

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“…These values correspond to mean firing rates of 65 and 40 spikes/s respectively. In 8 flies tested under comparable conditions (contrast, velocity and stimulated area) we never get rates below 120 spikes/s, consistent with the findings of Lenting et al (1984).…”

Section: Responses To Static and Dynamic Stimulisupporting

confidence: 88%

Real-Time Encoding of Motion: Answerable Questions and Questionable Answers from the Fly’s Visual System

2001

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In the past decade, a small corner of the fly's visual system has become an important testing ground for ideas about coding and computation in the nervous system. A number of results demonstrate that this system operates with a precision and efficiency near the limits imposed by physics, and more generally these results point to the reliability and efficiency of the strategies that nature has selected for representing and processing visual signals. A recent series of papers by Egelhaaf and coworkers, however, suggests that almost all these conclusions are incorrect. In this contribution we place these controversies in a larger context, emphasizing that the arguments are not just about flies, but rather about how we should quantify the neural response to complex, naturalistic inputs. As an example, Egelhaaf et al. (and many others) compute certain correlation functions and use the apparent correlation times as a measure of temporal precision in the neural response. This analysis neglects the structure of the correlation function at short times, and we show how to analyze this structure to reveal a temporal precision 30 times better than suggested by the correlation time; this precision is confirmed by a much more detailed information theoretic analysis. In reviewing other aspects of the controversy, we find that the analysis methods used by Egelhaaf et al. suffer from some mathematical inconsistencies, and that in some cases we are unable to reproduce their experimental results. Finally, we present results from new experiments that probe the neural response to inputs that approach more closely the natural context for freely flying flies. These new experiments demonstrate that the fly's visual system is even more precise and efficient under natural conditions than had been inferred from our earlier work.

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Section: Responses To Static and Dynamic Stimulisupporting

confidence: 88%

Real-Time Encoding of Motion: Answerable Questions and Questionable Answers from the Fly’s Visual System

2001

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“…Moreover, not only the luminance but also other stimulus parameters such as the contrast of structures in the environment change during dusk. The decrease in contrast on its own may have contributed to the slightly decreased response rate during dusk (Egelhaaf & Borst, 1989;Lenting, Mastebroek, & Zaagman, 1984). In addition, the response amplitude during dusk might have been affected by circadian rhythms that modulate the sensitivity of the H1-neuron.…”

Section: Discussionmentioning

confidence: 99%

Outdoor performance of a motion-sensitive neuron in the blowfly

et al. 2001

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We studied an identified motion-sensitive neuron of the blowfly under outdoor conditions. The neuron was stimulated by oscillating the fly in a rural environment. We analysed whether the motion-induced neuronal activity is affected by brightness changes ranging between bright sunlight and dusk. In addition, the relationship between spike rate and ambient temperature was determined. The main results are: (1) The mean spike rate elicited by visual motion is largely independent of brightness changes over several orders of magnitude as they occur as a consequence of positional changes of the sun. Even during dusk the neuron responds strongly and directionally selective to motion. (2) The neuronal spike rate is not significantly affected by short-term brightness changes caused by clouds temporarily occluding the sun. (3) In contrast, the neuronal activity is much affected by changes in ambient temperature.

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“…They increase, depending on the temporal frequency of the stimulus, up to much higher contrasts and, therefore, are similar in this regard to corresponding behavioral data3l 47 and electrophysiological findings on another motion-sensitive large-field neuron in the fly. 48 The simplest way to account for these results is to assume saturation nonlinearities before multiplication of the movement-detector input signals. Interestingly, when studying apparent motion phenomena in flies, Bfilthoff and G6tz 49 also proposed a saturation nonlinearity in the movement-detector input channels.…”

Section: Saturation Nonlinearities In the Movement-detection System Amentioning

confidence: 99%

Transient and steady-state response properties of movement detectors: errata

Egelhaaf¹,

Borst²

1990

J. Opt. Soc. Am. A

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The transient and steady-state responses of movement detectors are studied at various pattern contrasts (i) by intracellularly recording from an identified movement-sensitive interneuron in the fly's brain and (ii) by comparing these results with computer simulations of an array of movement detectors of the correlation type. At the onset of stimulus motion, the membrane potential oscillates with a frequency corresponding to the temporal frequency of the stimulus pattern before it settles at its steady-state level. Both the transient and the steady-state response amplitudes show a characteristic contrast dependence. As is shown by computer modeling, the transient behavior that we found in the experiments reflects an intrinsic property of the general scheme of movement detectors of the correlation type. To account for the contrast dependence, however, this general scheme has to be elaborated by (i) a subtraction stage, which eliminates the background light intensity from the detector input signal, and (ii) saturation characteristics in both branches of each movement-detector subunit.

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Saturation in a wide-field, directionally selective movement detection system in fly vision

Cited by 11 publications

References 25 publications

Real-Time Encoding of Motion: Answerable Questions and Questionable Answers from the Fly’s Visual System

Real-Time Encoding of Motion: Answerable Questions and Questionable Answers from the Fly’s Visual System

Outdoor performance of a motion-sensitive neuron in the blowfly

Transient and steady-state response properties of movement detectors: errata

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