“…2C) matches that of H1 more closely (e.g. Mastebroek et al 1980;Coombe et al 1989). On the other hand, the on-off unit rectifies the signal, thus its response does not allow discriminating positive and negative contrasts.…”
Summary. 1. We recorded from spiking units in the first optic chiasm between lamina and medulla in the brain of the blowfly (Calliphora vicina). Both previously characterized neuron types, on-off units and sustaining units, were encountered. On-off units had a temporal frequency response with a lower cut-off frequency than blowfly photoreceptors. This low cut-off frequency is related to a fast temporal adaptation of the on-off units to trains of short light pulses. Temporal adaptation occurred independently for short on-and off-pulses.2. On-off units only responded to stimuli of relatively large contrast. Contrasts of less than 10% gave little or no response.
“…2C) matches that of H1 more closely (e.g. Mastebroek et al 1980;Coombe et al 1989). On the other hand, the on-off unit rectifies the signal, thus its response does not allow discriminating positive and negative contrasts.…”
Summary. 1. We recorded from spiking units in the first optic chiasm between lamina and medulla in the brain of the blowfly (Calliphora vicina). Both previously characterized neuron types, on-off units and sustaining units, were encountered. On-off units had a temporal frequency response with a lower cut-off frequency than blowfly photoreceptors. This low cut-off frequency is related to a fast temporal adaptation of the on-off units to trains of short light pulses. Temporal adaptation occurred independently for short on-and off-pulses.2. On-off units only responded to stimuli of relatively large contrast. Contrasts of less than 10% gave little or no response.
“…By confronting experimental data with predictions obtained using both schemes ("gradient" and "correlation"), Buchner (1984) provided evidence that DS motion detection in flies is based on correlation-like interactions rather than on a gradient-computing mechanism. Furthermore, the fundamental properties of the correlation model could be retraced at the level of the widefield, directionally selective HI neuron in the fly visual system (Zaagman et al 1978;Mastebroek et al 1980) that will be the subject of the following section. Several variants of the correlation model have been proposed over the years (e.g., Thorson 1966;Kirschfeld 1972;van Santen and Sperling 1985), and its basic functional structure has even been used with great success for modelling DS motion detection in the visual system of vertebrates (Schouten 1967;Foster 1971;van Doorn and Koenderink 1976;Bulthoff and Gotz 1979;van Santen and Sperling 1984;Adelson and Bergen 1985;Wilson 1985;van de Grind et al 1986;Emerson et al 1987),…”
Section: The Correlation Model Of Motion Perceptionmentioning
confidence: 99%
“…5. The array of EM D's feeding H 1 must be wired down with fine grain because HI readily responds to local motion between two points of the environment that are as little as one interommatidial angle apart (McCann and Arnett 1972;McCann 1973;Zaagman et al 1977;Mastebroek et al 1980). …”
Section: The Correlation Model Of Motion Perceptionmentioning
“…This is surprising, since, in principle time constants could have been derived on the basis of the contrast frequency optima of either the optomotor turning reaction (Grtz 1964;McCann and MacGinitie 1965;Eckert 1973;Buchner 1984;Wehrhahn 1985;Borst and Bahde 1987) or the response oflobula plate large-field tangential neurones which are involved in the control of this behavioural response component (Eckert 1980;Mastebroek et al 1980;Hausen 1982b;Maddess and Laughlin 1985). In all these studies the contrast frequency optima lie somewhere within the range between 1 and 10 Hz depending on the species and the exact stimulus conditions.…”
Section: Estimation Of the Filter Time Constantmentioning
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