Summation of Quantal Noise in Space and Time

Perception ◽  
1997 ◽  
Vol 26 (1_suppl) ◽  
pp. 175-175
Author(s):  
S Hemilä ◽  
T Lerber ◽  
K Donner
Keyword(s):  
Ganglion Cells ◽  
Signal To Noise Ratio ◽  
Light Flux ◽  
Equal Weight ◽  
Retinal Ganglion ◽  
Quantal Response ◽  
Visual Neurons ◽  
Space And Time ◽  
The Difference ◽  
Definition Of

Noise in visual neurons, or variability in psychophysical experiments, may be quantified in terms of photon fluctuations from an ‘equivalent’ steady illumination. The conversion requires assumptions on how photon signals are pooled in space and time, ie how to pass from the light flux to the numbers of photon events relevant to the Poisson statistics describing signal/noise. Real weighting profiles for the integration of photon events in space and time [the sensitivity distribution of the receptive field (RF) and the waveform of the impulse response (IR)] are commonly approximated by sharp-bordered apertures of ‘complete’, equal-weight summation of events. Such apertures based on signal equivalence cannot provide noise equivalence, however, because greater numbers of events summed with lower weights (as in reality) have lower variances than smaller numbers summed with full weight. Thus sharp-bordered apertures are necessarily smaller if defined for noise equivalence rather than for signal equivalence. We have calculated the difference for some commonly encountered RF and IR profiles. Summation areas, expressed as numbers of photoreceptors (cones or rods) contributing with equal weight, are denoted NS for signal and NN for noise, and sharply delimited summation times are correspondingly denoted tS and tN. We show that the relation in time is tN=0.6 tS to 0.7 tS for realistic quantal response waveforms of photoreceptors. In space, the relation is NN=0.5 NS for the Gaussian distribution (eg for the RF centre mechanism of retinal ganglion cells). For a photoreceptor in an electrically coupled network the difference is still greater, eg for rods in the toad retina NN=0.2 NS ( NS=13.7 rods and NN=2.8 rods). We introduce a third possible definition of sharp-bordered summation apertures: one that provides the same signal-to-noise ratio (SNR) for large-long stimuli as the real integration profiles. The SNR-equivalent summation area is N*= NS2/ NN and the summation time is t*= tS2/ tN.

scholarly journals Noise-equivalent and signal-equivalent visual summation of quantal events in space and time

1998 ◽  
Vol 15 (4) ◽  
pp. 731-742 ◽  
Author(s):  
SIMO HEMILÄ ◽  
TUOMO LERBER ◽  
KRISTIAN DONNER
Keyword(s):  
Ganglion Cells ◽  
Signal To Noise Ratio ◽  
Equal Weight ◽  
Quantal Response ◽  
Visual Neurons ◽  
Space And Time ◽  
Difference Of Gaussians ◽  
Total Noise ◽  
The Difference ◽  
Definition Of

Noise recorded in visual neurons, or variability in psychophysical experiments, may be quantified in terms of quantal fluctuations from an “equivalent” steady illumination. The conversion requires assumptions concerning how photon signals are pooled in space and time, i.e. how to pass from light fluxes to numbers of photon events relevant to the Poisson statistics describing signal/noise. It is usual to approximate real weighting profiles for the integration of photon events in space and time (the sensitivity distribution of the receptive field [RF] and the waveform of the impulse response [IR]) by sharp-bordered apertures of “complete,” equal-weight summation of events. Apertures based on signal-equivalence cannot provide noise-equivalence, however, because greater numbers of events summed with smaller weights (as in reality) have lower variances than smaller numbers summed with full weight. Thus sharp-bordered apertures are necessarily smaller if defined for noise- than for signal-equivalence. We here consider the difference for some commonly encountered RF and IR profiles. Summation areas, expressed as numbers of photoreceptors (cones or rods) contributing with equal weight, are denoted NS for signal and NN for noise; sharply delimited summation times are correspondingly denoted tS and tN. We show that the relation in space is NN = 0.5NS for the Gaussian distribution (e.g. for the RF center mechanism of retinal ganglion cells). For a photoreceptor in an electrically coupled network the difference is even larger, e.g., for rods in the toad retina NN = 0.2NS (NS = 13.7 rods and NN = 2.8 rods). In time, the relation is tN ≈ 0.7tS for realistic quantal response waveforms of photoreceptors. The surround input in a difference-of-Gaussians RF may either decrease or increase total noise, depending on the degree of correlation of center and surround noise. We introduce a third useful definition of sharp-bordered summation apertures: one that provides the same signal-to-noise ratio (SNR) for large-long stimuli as the real integration profiles. The SNR-equivalent summation area is N* = NS 2/NN and summation time t* = tS2/tN.

Brightness In The Photopic Range: Psychophysical Modelling With Blue-sensitive Retinal Signals

2020 ◽  
pp. 9-24
Author(s):  
Peter Bodrogi ◽  
Xue Guo ◽  
Tran Quoc Khanh
Keyword(s):  
Ganglion Cells ◽  
Light Stimulus ◽  
Spectral Radiance ◽  
Psychophysical Experiment ◽  
Retinal Ganglion ◽  
Reasonable Accuracy ◽  
Brightness Perception ◽  
Content Model ◽  
The Difference ◽  
Cone Signal

The brightness perception of a large (41°) uniform visual field was investigated in a visual psychophysical experiment. Subjects assessed the brightness of 20 light source spectra of different chromaticities at two luminance levels, Lv=267.6 cd/m2 and Lv=24.8 cd/m2. The resulting mean subjective brightness scale values were modelled by a combination of the signals of retinal mechanisms: S-cones, rods, intrinsically photosensitive retinal ganglion cells (ipRGCs) and the difference of the L-cone signal and the M-cone signal. A new quantity, “relative spectral blue content”, was also considered for modelling. This quantity was defined as “the spectral radiance of the light stimulus integrated with the range (380–520) nm, relative to luminance”. The “relative spectral blue content” model could describe the subjective brightness perception of the observers with reasonable accuracy.

scholarly journals Dependence of center radius on temporal frequency for the receptive fields of X retinal ganglion cells of cat.

1989 ◽  
Vol 94 (6) ◽  
pp. 987-995 ◽  
Author(s):  
J B Troy ◽  
C Enroth-Cugell
Keyword(s):  
Retinal Ganglion Cells ◽  
Ganglion Cells ◽  
Signal To Noise Ratio ◽  
Temporal Frequency ◽  
Receptive Fields ◽  
Retinal Ganglion ◽  
Spatial Expansion ◽  
Neuronal Membranes ◽  
Inductive Elements ◽  
X Cells

We examined the dependence of the center radius of X cells on temporal frequency and found that at temporal frequencies above 40 Hz the radius increases in a monotonic fashion, reaching a size approximately 30% larger at 70 Hz. This kind of spatial expansion has been predicted with cable models of receptive fields where inductive elements are included in modeling the neuronal membranes. Hence, the expansion of the center radius is clearly important for modeling X cell receptive fields. On the other hand, we feel that it might be of only minor functional significance, since the responsivity of X cells is attenuated at these high temporal frequencies and the signal-to-noise ratio is considerably worse than at low and midrange temporal frequencies.

scholarly journals Effect of Acupuncture on Intraocular Pressure in Glaucoma Patients: A Single-Blinded, Randomized, Controlled Trial

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Shu-Yuan Chen ◽  
Feng-Shuen Yieh ◽  
Wen-Ling Liao ◽  
Tsai-Chung Li ◽  
Ching-Liang Hsieh
Keyword(s):  
Randomized Controlled Trial ◽  
Intraocular Pressure ◽  
Sham Group ◽  
Ganglion Cells ◽  
Controlled Trial ◽  
Ocular Blood Flow ◽  
Retinal Ganglion ◽  
Randomized Controlled ◽  
Ocular Perfusion ◽  
The Difference

Glaucoma is characterized by the degeneration of retinal ganglion cells that cause progressive optic neuropathy, finally resulting in changes to the optic nerve head. Lowering intraocular pressure (IOP) is the only method proven for treating glaucoma. Several studies have discovered that acupuncture can reduce IOP and also increase ocular perfusion and ocular blood flow. Therefore, the present study investigated the effect of acupuncture on IOP in glaucoma patients. We conducted a single-blinded, randomized, controlled trial involving 45 glaucoma patients. The results indicated that the difference between the IOP 60 min after the intervention and IOP immediately before the intervention was greater in the acupuncture group (AG) and electroacupuncture group (EG) than in the sham group (SG) for all four of the interventions performed and in both eyes (all p<0.05). The IOP difference between immediately before the first intervention and after finishing the final intervention was also greater in the AG and EG than in the SG in both eyes (all p<0.05). In conclusion, IOP was reduced at 60 min after acupuncture or electroacupuncture was performed at BL1 and EX-HN7. Additionally, IOP was reduced after finishing four acupuncture or electroacupuncture sessions. Therefore, our results suggest that acupuncture and electroacupuncture are beneficial for lowering IOP in glaucoma patients. This trial is registered with NCT04157530.

scholarly journals Specificity of Cone Inputs to Macaque Retinal Ganglion Cells

2006 ◽  
Vol 95 (2) ◽  
pp. 837-849 ◽  
Author(s):  
Hao Sun ◽  
Hannah E. Smithson ◽  
Qasim Zaidi ◽  
Barry B. Lee
Keyword(s):  
Retinal Ganglion Cells ◽  
Ganglion Cells ◽  
Retinal Ganglion ◽  
Visual Neurons ◽  
Precise Method ◽  
Retinal Circuitry ◽  
Nature Of Information ◽  
The Brain ◽  
Measure Cone ◽  
Cone Adaptation

The specificity of cone inputs to ganglion cells has implications for the development of retinal connections and the nature of information transmitted to higher areas of the brain. We introduce a rapid and precise method for measuring signs and magnitudes of cone inputs to visual neurons. Colors of stimuli are modulated around circumferences of three color planes in clockwise and counterclockwise directions. For each neuron, the projection of the preferred vector in each plane was estimated by averaging the response phases to clockwise and counterclockwise modulation. The signs and weights of cone inputs were derived directly from the preferred vectors. The efficiency of the method enables us to measure cone inputs at different temporal frequencies and short-wavelength-sensitive (S) cone adaptation levels. The results show that S-cone inputs to the parvocellular and magnocellular ganglion cells are negligible, which implies underlying connectional specificity in the retinal circuitry.

Survival of retinal ganglion cells after transection of the optic nerve in adult cats: A quantitative study within two weeks

2001 ◽  
Vol 18 (1) ◽  
pp. 137-145 ◽  
Author(s):  
MASAMI WATANABE ◽  
NAOKO INUKAI ◽  
YUTAKA FUKUDA
Keyword(s):  
Optic Nerve ◽  
Retinal Ganglion Cells ◽  
Time Course ◽  
Ganglion Cells ◽  
Lucifer Yellow ◽  
Retinal Ganglion ◽  
Β Cells ◽  
Fiber Layer ◽  
The Difference ◽  
Adult Cats

We have previously reported that a small number of retinal ganglion cells (RGCs) of adult cats survive 2 months after transection of the optic nerve (ON) and that α cells have the greatest ability to survive among different types of RGCs (Watanabe et al., 1995). Here we report the time course of RGC survival within 15 days after ON transection using retrograde labeling with DiI injected into the bilateral lateral geniculate nuclei of cats. The density of DiI-labeled RGCs in the central retina as well as in the periphery did not change until day 3 after ON transection, then decreased rapidly, to 43% of the original density on day 7, and falling to 19% by day 14. We then intracellularly injected Lucifer yellow into the DiI-labeled RGCs to examine the difference in the time course between surviving α and β cells. Similar to the density change in total surviving RGCs, the proportion of surviving β cells did not change until day 3, then decreased rapidly to 65% of the original density on day 4, falling to 12% by day 14. By contrast, 64% of α cells survived for 14 days after axotomy. Analysis of regression lines for survival time courses indicated that death of β cells was characterized with a rapid period phase from day 3 to day 7 after axotomy whereas that of α cells lacked it. Axon-like sprouting from surviving β cells was first recognized in the nerve fiber layer on day 3, and were later more conspicuous.

scholarly journals Photophobia in migraine: A symptom cluster?

Cephalalgia ◽  
2021 ◽  
pp. 033310242110146
Author(s):  
Arnold J Wilkins ◽  
Sarah M Haigh ◽  
Omar A Mahroo ◽  
Gordon T Plant
Keyword(s):  
Retinal Ganglion Cells ◽  
Visual Stimulation ◽  
Ganglion Cells ◽  
Underlying Mechanism ◽  
Retinal Ganglion ◽  
Current Review ◽  
Parsimonious Explanation ◽  
Traditional Definition ◽  
Definition Of ◽  
The Relationship

Photophobia is one of the most common symptoms in migraine, and the underlying mechanism is uncertain. The discovery of the intrinsically-photosensitive retinal ganglion cells which signal the intensity of light on the retina has led to discussion of their role in the pathogenesis of photophobia. In the current review, we discuss the relationship between pain and discomfort leading to light aversion (traditional photophobia) and discomfort from flicker, patterns, and colour that are also common in migraine and cannot be explained solely by the activity of intrinsically-photosensitive retinal ganglion cells. We argue that, at least in migraine, a cortical mechanism provides a parsimonious explanation for discomfort from all forms of visual stimulation, and that the traditional definition of photophobia as pain in response to light may be too restrictive. Future investigation that directly compares the retinal and cortical contributions to photophobia in migraine with that in other conditions may offer better specificity in identifying biomarkers and possible mechanisms to target for treatment.

scholarly journals Inference of nonlinear receptive field subunits with spike-triggered clustering

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Nishal P Shah ◽  
Nora Brackbill ◽  
Colleen Rhoades ◽  
Alexandra Kling ◽  
Georges Goetz ◽  
...  
Keyword(s):  
Receptive Field ◽  
Closed Loop ◽  
Ganglion Cells ◽  
Null Space ◽  
Likelihood Estimation ◽  
Retinal Ganglion ◽  
Visual Neurons ◽  
V1 Neurons ◽  
Fixational Eye Movements ◽  
Weighted Combination

Responses of sensory neurons are often modeled using a weighted combination of rectified linear subunits. Since these subunits often cannot be measured directly, a flexible method is needed to infer their properties from the responses of downstream neurons. We present a method for maximum likelihood estimation of subunits by soft-clustering spike-triggered stimuli, and demonstrate its effectiveness in visual neurons. For parasol retinal ganglion cells in macaque retina, estimated subunits partitioned the receptive field into compact regions, likely representing aggregated bipolar cell inputs. Joint clustering revealed shared subunits between neighboring cells, producing a parsimonious population model. Closed-loop validation, using stimuli lying in the null space of the linear receptive field, revealed stronger nonlinearities in OFF cells than ON cells. Responses to natural images, jittered to emulate fixational eye movements, were accurately predicted by the subunit model. Finally, the generality of the approach was demonstrated in macaque V1 neurons.

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