Voltage Noise in
            <i>Limulus</i>
            Visual Cells

Dodge, F. A.; Knight, Bruce W.; Toyoda, Jun‐Ichi

doi:10.1126/science.160.3823.88

Cited by 232 publications

(166 citation statements)

References 11 publications

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“…The procedure has been described in detail earlier (Dodge, Knight, and Toyota, 1968;Roebroek, van Tjonger, and Stavenga, 1990;Suss-Toby et al, 1991). Shortly, assuming a bump shape given by the F-distribution: F(t;n,'r) n!…”

Section: Calculation Of the Effective Duration Of The Quantum Bumpsmentioning

confidence: 99%

Contrast gain, signal-to-noise ratio, and linearity in light-adapted blowfly photoreceptors.

Juusola

Kouvalainen

Järvilehto

et al. 1994

The Journal of General Physiology

102

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Response properties of short-type (RI-6) photoreceptors of the blowfly (CaUiphora vicina) were investigated with intracellular recordings using repeated sequences of pseudorandomly modulated light contrast stimuli at adapting backgrounds covering 5 log intensity units. The resulting voltage responses were used to determine the effects of adaptational regulation on signal-to-noise ratios (SNR), signal induced noise, contrast gain, linearity and the dead time in phototransduction. In light adaptation the SNR of the photoreceptors improved more than 100-fold due to (a) increased photoreceptor voltage responses to a contrast stimulus and (b) reduction of voltage noise at high intensity backgrounds. In the frequency domain the SNR was attenuated in low frequencies with an increase in the middle and high frequency ranges. A pseudorandom contrast stimulus by itself did not produce any additional noise. The contrast gain of the photoreceptor frequency responses increased with mean illumination and the gain was best fitted with a model consisting of two second order and one double pole of first order. The coherence function (a normalized measure of linearity and SNR) of the frequency responses demonstrated that the photoreceptors responded linearly (from 1 to 150 Hz) to the contrast stimuli even under fairly dim conditions. The theoretically derived and the recorded phase functions were used to calculate phototransduction dead time, which decreased in light adaptation from ~5-2.5 ms. This analysis suggests that the ability of fly photoreceptors to maintain linear performance under dynamic stimulation conditions results from the high early gain followed by delayed compressive feed-back mechanisms.

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Section: Calculation Of the Effective Duration Of The Quantum Bumpsmentioning

confidence: 99%

Contrast gain, signal-to-noise ratio, and linearity in light-adapted blowfly photoreceptors.

Juusola

Kouvalainen

Järvilehto

et al. 1994

The Journal of General Physiology

102

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“…Method 1 is insensitive to the presence of a filter (for instance a screening pigment) interposed between the light source and the membrane, provided the density of the filter is the same when low-and high-intensity stimuli are presented. Since the number of quantal events can be estimated from the response noise (Dodge et al, 1968), Method 1 should be applicable even in cells which produce no observable discrete waves.…”

Section: Number Of Rhodopsin Molecules Per Cellmentioning

confidence: 99%

Electrophysiological measurement of the number of rhodopsin molecules in single Limulus photoreceptors.

Lisman¹,

Bering²

1977

The Journal of General Physiology

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Two partly independent electrophysiological methods are described for measuring the number of rhodopsin molecules (R) in single ventral photoreceptors. Method 1 is based on measurements of the relative intensity required to elicit a quantal response and the relative intensity required to half-saturate the early receptor potential (ERP). Method 2 is based on measurements of the absolute intensity required to elicit a quantal response. Both methods give values of R approximately equal to 10(9). From these and other measurements, estimates are derived for the surface density of rhodopsin (8,000/micrometer2), the charge movement during the ERP per isomerized rhodopsin (20 X 10(-21) C), and the half-time for thermal isomerization of rhodopsin (36yr).

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“…Notice that if we have an ensemble of many trials with the same input, then we can define a different "fluctuation" in the signal ρ by subtracting off the time dependent mean ρ(t) = λ(t). Thus if we write ∆ρ(t) = ρ(t) − λ(t), then the equations analogous to (11) and (12) above are as follows:…”

Section: Correlation Functions and Spectramentioning

confidence: 99%

“…Because single photon responses are more or less standardized it seems a good idea to model the photoreceptor voltage as a shot noise process, consisting of a stream of photon induced events often referred to as "quantum bumps" (Dodge et al 1968, Wong et al 1980, de Ruyter van Steveninck and Laughlin 1996a,b). However, we are dealing with a highly adaptive system.…”

Section: Reliability and Adaptationmentioning

confidence: 99%

“…We could choose to apply Eqn. 23 to the quantities we measure, and then consider the result as a measurement of an effective Poisson rate (see also Dodge et al 1968). This can then be compared to the rate we expect from an independent measurement of photon flux (which we can make-see the experimental sections) to assess how close the real system comes to being ideal.…”

Section: Shot Noisementioning

confidence: 99%

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Timing and Counting Precision in the Blowfly Visual System

Ruyter¹,

Bialek

2002

Models of Neural Networks IV

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We measure the reliability of signals at three levels within the blowfly visual system, and present a theoretical framework for analyzing the experimental results, starting from the Poisson process. We find that blowfly photoreceptors, up to frequencies of 50-100 Hz and photon capture rates of up to about 3 · 10 5 /s, operate well within an order of magnitude from ideal photon counters. Photoreceptors signals are transmitted to LMCs through an array of chemical synapses. We quantify a lower bound on LMC reliability, which in turn provides a lower bound on synaptic vesicle release rate, assuming Poisson statistics. This bound is much higher than what is found in published direct measurements of vesicle release rates in goldfish bipolar cells, suggesting that release statistics may be significantly sub-Poisson. Finally we study H1, a motion sensitive tangential cell in the fly's lobula plate, which transmits information about a continuous signal by sequences of action potentials. In an experiment with naturalistic motion stimuli performed on a sunny day outside in the field, H1 transmits information at about 50% coding efficiency down to millisecond spike timing precision. Comparing the measured reliability of H1's response to motion steps with the bounds on the accuracy of motion computation set by photoreceptor noise, we find that the fly's brain makes efficient use of the information available in the photoreceptor array.

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Voltage Noise in Limulus Visual Cells

Cited by 232 publications

References 11 publications

Contrast gain, signal-to-noise ratio, and linearity in light-adapted blowfly photoreceptors.

Contrast gain, signal-to-noise ratio, and linearity in light-adapted blowfly photoreceptors.

Electrophysiological measurement of the number of rhodopsin molecules in single Limulus photoreceptors.

Timing and Counting Precision in the Blowfly Visual System

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