Variations in Photoreceptor Response Dynamics Across the Fly Retina

2001 ◽  
Vol 86 (2) ◽  
pp. 950-960 ◽  
Author(s):  
Brian G. Burton ◽  
Ben W. Tatler ◽  
Simon B. Laughlin
Keyword(s):  
Temporal Resolution ◽  
Light Adaptation ◽  
Signal To Noise Ratio ◽  
Calliphora Vicina ◽  
Retinal Neuron ◽  
Response Dynamics ◽  
Signal To Noise ◽  
Spatiotemporal Resolution ◽  
Temporal Properties ◽  
Noise Ratio

Gradients in the spatial properties of retinal cells and their relation to image statistics are well documented. However, less is known of gradients in temporal properties, especially at the level of the photoreceptor for which no account exists. Using light flashes and white-noise-modulated light and current stimuli, we examined the spatial and temporal properties of a single class of photoreceptor (R1–6) within the compound eyes of male blowfly, Calliphora vicina. We find that there is a trend toward higher performance at the front of the eye, both in terms of spatiotemporal resolution and signal-to-noise ratio. The receptive fields of frontal photoreceptors are narrower than those of photoreceptors at the side and back of the eye and response speeds are 20% faster. The signal-to-noise ratio at high frequencies is also greatest at the front of the eye, allowing a 30–40% higher information rate. The power spectra of signals and noise indicate that this elevation of performance results both from shorter responses to individual photons and from a more reliable registration of photon arrival times. These distinctions are characteristic of adaptational changes that normally occur on increasing illumination. However, all photoreceptors were absorbing light at approximately the same mean photon rate during our recordings. We therefore suggest that frontal photoreceptors attain a higher state of light adaptation for a given photon rate. This difference may be achieved by a higher density of (Ca2+ permeable) light-gated channels. Consistent with this hypothesis, membrane-impedance measurements show that frontal photoreceptors have a higher specific conductance than other photoreceptors. This higher conductance provides a better temporal performance but is metabolically expensive. Across the eye, temporal resolution is not proportional to spatial (optical) resolution. Neither is it matched obviously to optic flow. Instead we examine the consequences of an improved temporal resolution in the frontal region for the tracking of small moving targets, a behavior exhibited by male flies. We conclude that the temporal properties of a given class of retinal neuron can vary within a single retina and that this variation may be functionally related to the behavioral requirements of the animal.

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

1994 ◽  
Vol 104 (3) ◽  
pp. 593-621 ◽  
Author(s):  
M Juusola ◽  
E Kouvalainen ◽  
M Järvilehto ◽  
M Weckström
Keyword(s):  
Light Adaptation ◽  
Dead Time ◽  
Signal To Noise Ratio ◽  
Coherence Function ◽  
Calliphora Vicina ◽  
Signal To Noise ◽  
Low Frequencies ◽  
Contrast Gain ◽  
Frequency Responses ◽  
Phase Functions

Response properties of short-type (R1-6) photoreceptors of the blowfly (Calliphora 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 approximately 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.

Noise and light adaptation in rods of the macaque monkey

2000 ◽  
Vol 17 (5) ◽  
pp. 659-666 ◽  
Author(s):  
D.M. SCHNEEWEIS ◽  
J.L. SCHNAPF
Keyword(s):  
Light Adaptation ◽  
Single Photon ◽  
Signal To Noise Ratio ◽  
Macaque Monkey ◽  
Membrane Voltage ◽  
Background Intensity ◽  
Signal To Noise ◽  
Voltage Fluctuations ◽  
Dark Light ◽  
Noise Ratio

Membrane voltage was recorded in rod photoreceptors in retina isolated from macaque monkey. The size of the single photon response and the magnitude of membrane voltage fluctuations were assessed in dark- and light-adapted retina. The “dark light” rate ID, defined as the rate of spontaneous photopigment isomerizations that would produce a variance equivalent to that of the noise measured in the dark, was calculated after matched filtering. The average value of 0.08 s−1 fell at the higher end of psychophysical estimates of dark light in human observers. In light-adapted rods the photon response decreased in amplitude and duration, and the magnitude of the voltage fluctuations increased with increasing background light intensity. The signal-to-noise ratio (SNR) for single rods was defined as the ratio of the peak amplitude of the photon response to the standard deviation of the noise fluctuations. The signal-to-noise ratio for dark-adapted rods SNRD was about 7. With increasing background intensity I, the SNR fell as SNRD(1 + I/ID)−1/2. This function may account for the increment thresholds measured with small brief test flashes in human psychophysical experiments.

An automatic algorithm for the detection and the characterization of cloud boundaries from BAQUNIN LIDAR signals

2020 ◽  
Author(s):  
AnnaMaria Iannarelli ◽  
Marco Cacciani ◽  
Gabriele Mevi ◽  
Stefano Casadio ◽  
Annalisa Di Bernardino
Keyword(s):  
Boundary Layer ◽  
Temporal Resolution ◽  
Signal To Noise Ratio ◽  
Threshold Value ◽  
Temporal Variations ◽  
Cloud Layer ◽  
Spatial And Temporal Variations ◽  
Quality Analysis ◽  
Signal To Noise ◽  
Noise Ratio

<p>The lidar LIDAR system is widely used in atmospheric aerosol and boundary layer (BL) studies, and for the detection of cloud boundaries. However automatic and accurate identification of cloud top and bottom heights and BL height is not trivial, especially for low signal to noise ratio values, and for cloud layers below the top of BL, because of the disentanglement of cloud and aerosol contribution to LIDAR signal.</p><p>In this work, a signal threshold approach is presented, starting from the Range Corrected Signal (RCS) and using its spatial and temporal variations. The approach has been tested using one year of acquisitions of the elastic LIDAR hosted in the BAQUNIN (Boundary-layer Air QUality analysis using Network of INstruments) Supersite(https://www.baqunin.eu) with a spatial and temporal resolution of 7.5 m and 10 s, respectively.</p><p>A minimum threshold value T<sub>c</sub> applied to the RCS values allows detecting the presence of a cloud layer. This approach could be applied to each type of acquired LIDAR elastic signal, but depends on the specific LIDAR channel characteristics, in particular the signal to noise ratio.</p><p>RCS values obtained for each acquired profile and altitude could be considered as a two-dimensional matrix M. As first step the elements M<sub>ij</sub>>T<sub>c</sub> of this matrix are labeled as possible cloud elements.</p><p>Subsequently, the algorithm excludes from the calculation the elements M<sub>ij </sub>corresponding to spike values or affected by high noise considering the spatial and temporal variations of the RCS. A labeled element is confirmed to be a cloud element if the number of its labeled neighbors is above a selected percentage threshold T<sub>perc.</sub> The grid of elements considered as neighbors can be defined according to spatial and temporal resolution of the LIDAR acquisition.</p><p>Finally, bottom and top of cloud layers are retrieved as the altitude of first and last labeled elements of each cloud layer and profile.</p><p>The accuracy of the results depends on the spatial and temporal resolution of the acquired signal, considering the BAQUNIN LIDAR characteristics the best accuracy is 15 m and 20 s.</p><p>The same approach could be used to distinguish aerosol from cloud layers, using a different threshold value for the aerosol.</p><p>This method was tested for different atmospheric conditions and results are discussed in this work.</p>

LIGHT ADAPTATION AND RELIABILITY IN BLOWFLY PHOTORECEPTORS

1996 ◽  
Vol 07 (04) ◽  
pp. 437-444 ◽  
Author(s):  
R.R. DE RUYTER VAN STEVENINCK ◽  
S.B. LAUGHLIN
Keyword(s):  
Light Adaptation ◽  
Signal To Noise Ratio ◽  
Transduction Efficiency ◽  
Statistical Efficiency ◽  
Signal To Noise ◽  
Low Light ◽  
Frequency Dependent ◽  
Light Levels ◽  
Light Intensities ◽  
Noise Ratio

We characterize the reliability of response of blowfly photoreceptors at different light levels. These cells convey their information by graded potentials. Their reliability is quantified by the frequency-dependent contrast-normalized signal to noise ratio. Independently we estimate the effective photoconversion rate of the cells by counting individual photoconversion events, or quantum bumps, at calibrated low light levels. Comparing both results we quantify the statistical efficiency of photoconversion at higher light intensities, characterizing the transduction efficiency as a function of frequency. The light intensities used in these experiments ranged from about 300 to about 5×105 photoconversions per second per photoreceptor. Over most of this range, statistical efficiencies are within 50% at frequencies up to about 100 Hz.

Determination of the Best Emulsion for the Microscopy of Crystals

1981 ◽  
Vol 39 ◽  
pp. 32-33
Author(s):  
David A. Grano ◽  
Kenneth H. Downing
Keyword(s):  
Spatial Frequency ◽  
Information Transfer ◽  
Signal To Noise Ratio ◽  
Experimental Situation ◽  
Photographic Emulsion ◽  
Modulation Transfer ◽  
Signal To Noise ◽  
Frequency Space ◽  
Noise Ratio

The retrieval of high-resolution information from images of biological crystals depends, in part, on the use of the correct photographic emulsion. We have been investigating the information transfer properties of twelve emulsions with a view toward 1) characterizing the emulsions by a few, measurable quantities, and 2) identifying the “best” emulsion of those we have studied for use in any given experimental situation. Because our interests lie in the examination of crystalline specimens, we've chosen to evaluate an emulsion's signal-to-noise ratio (SNR) as a function of spatial frequency and use this as our critereon for determining the best emulsion.The signal-to-noise ratio in frequency space depends on several factors. First, the signal depends on the speed of the emulsion and its modulation transfer function (MTF). By procedures outlined in, MTF's have been found for all the emulsions tested and can be fit by an analytic expression 1/(1+(S/S0)2). Figure 1 shows the experimental data and fitted curve for an emulsion with a better than average MTF. A single parameter, the spatial frequency at which the transfer falls to 50% (S0), characterizes this curve.

Experiments in Bright-Field Imaging with Hollow-Cone Illumination

1981 ◽  
Vol 39 ◽  
pp. 226-227
Author(s):  
W. Kunath ◽  
K. Weiss ◽  
E. Zeitler
Keyword(s):  
Signal To Noise Ratio ◽  
Carbon Support ◽  
Electronic System ◽  
Optic Axis ◽  
Hollow Cone ◽  
Signal To Noise ◽  
Bright Field ◽  
Noise Ratio ◽  
Single Field ◽  
Field Imaging

Bright-field images taken with axial illumination show spurious high contrast patterns which obscure details smaller than 15 ° Hollow-cone illumination (HCI), however, reduces this disturbing granulation by statistical superposition and thus improves the signal-to-noise ratio. In this presentation we report on experiments aimed at selecting the proper amount of tilt and defocus for improvement of the signal-to-noise ratio by means of direct observation of the electron images on a TV monitor.Hollow-cone illumination is implemented in our microscope (single field condenser objective, Cs = .5 mm) by an electronic system which rotates the tilted beam about the optic axis. At low rates of revolution (one turn per second or so) a circular motion of the usual granulation in the image of a carbon support film can be observed on the TV monitor. The size of the granular structures and the radius of their orbits depend on both the conical tilt and defocus.

Information capacity and bandwidth limitations in the SEM

1989 ◽  
Vol 47 ◽  
pp. 84-85
Author(s):  
D. C. Joy ◽  
R. D. Bunn
Keyword(s):  
Signal To Noise Ratio ◽  
Critical Dimension ◽  
Information Capacity ◽  
Acquisition Time ◽  
Signal To Noise ◽  
Sem Image ◽  
Probe Size ◽  
Minimum Number ◽  
Noise Ratio ◽  
Signal Channel

The information available from an SEM image is limited both by the inherent signal to noise ratio that characterizes the image and as a result of the transformations that it may undergo as it is passed through the amplifying circuits of the instrument. In applications such as Critical Dimension Metrology it is necessary to be able to quantify these limitations in order to be able to assess the likely precision of any measurement made with the microscope.The information capacity of an SEM signal, defined as the minimum number of bits needed to encode the output signal, depends on the signal to noise ratio of the image - which in turn depends on the probe size and source brightness and acquisition time per pixel - and on the efficiency of the specimen in producing the signal that is being observed. A detailed analysis of the secondary electron case shows that the information capacity C (bits/pixel) of the SEM signal channel could be written as :

Speech Reception in the Presence of Classroom Noise

1979 ◽  
Vol 10 (4) ◽  
pp. 221-230 ◽  
Author(s):  
Veronica Smyth
Keyword(s):  
Signal To Noise Ratio ◽  
Learning Processes ◽  
Speech Discrimination ◽  
Signal To Noise ◽  
Speech Reception ◽  
Monosyllabic Words ◽  
Noise Ratio

Three hundred children from five to 12 years of age were required to discriminate simple, familiar, monosyllabic words under two conditions: 1) quiet, and 2) in the presence of background classroom noise. Of the sample, 45.3% made errors in speech discrimination in the presence of background classroom noise. The effect was most marked in children younger than seven years six months. The results are discussed considering the signal-to-noise ratio and the possible effects of unwanted classroom noise on learning processes.

Quantifying the Effects of Background Speech Babble on Preschool Children's Novel Word Learning in a Multisession Paradigm: A Preliminary Study

2020 ◽  
Vol 63 (1) ◽  
pp. 345-356
Author(s):  
Meital Avivi-Reich ◽  
Megan Y. Roberts ◽  
Tina M. Grieco-Calub
Keyword(s):  
Word Learning ◽  
Signal To Noise Ratio ◽  
Preschool Age ◽  
Exposure Condition ◽  
Signal To Noise ◽  
Verbal Recall ◽  
Referent Selection ◽  
Main Effect ◽  
Noise Ratio ◽  
Novel Word Learning

Purpose This study tested the effects of background speech babble on novel word learning in preschool children with a multisession paradigm. Method Eight 3-year-old children were exposed to a total of 8 novel word–object pairs across 2 story books presented digitally. Each story contained 4 novel consonant–vowel–consonant nonwords. Children were exposed to both stories, one in quiet and one in the presence of 4-talker babble presented at 0-dB signal-to-noise ratio. After each story, children's learning was tested with a referent selection task and a verbal recall (naming) task. Children were exposed to and tested on the novel word–object pairs on 5 separate days within a 2-week span. Results A significant main effect of session was found for both referent selection and verbal recall. There was also a significant main effect of exposure condition on referent selection performance, with more referents correctly selected for word–object pairs that were presented in quiet compared to pairs presented in speech babble. Finally, children's verbal recall of novel words was statistically better than baseline performance (i.e., 0%) on Sessions 3–5 for words exposed in quiet, but only on Session 5 for words exposed in speech babble. Conclusions These findings suggest that background speech babble at 0-dB signal-to-noise ratio disrupts novel word learning in preschool-age children. As a result, children may need more time and more exposures of a novel word before they can recognize or verbally recall it.

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