ArticlePLoS computational biology2017
Point process analysis of noise in early invertebrate vision.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
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- Fiddler crab electroretinograms reveal vast circadian shifts in visual sensitivity and temporal summation in dim light.The Journal of experimental biology · 2022Article
- Improved estimation of time-varying reproduction numbers at low case incidence and between epidemic waves.PLoS computational biology · 2021Article
- An exact method for quantifying the reliability of end-of-epidemic declarations in real time.PLoS computational biology · 2020Article
- Speed of phototransduction in the microvillus regulates the accuracy and bandwidth of the rhabdomeric photoreceptor.PLoS computational biology · 2020Article
- Overcoming randomness does not rule out the importance of inherent randomness for functionality.Journal of biosciences · 2019Review
- Generating randomness: making the most out of disordering a false order into a real one.Journal of translational medicine · 2019Review
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2 authors.
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Abstract
Noise is a prevalent and sometimes even dominant aspect of many biological processes. While many natural systems have adapted to attenuate or even usefully integrate noise, the variability it introduces often still delimits the achievable precision across biological functions. This is particularly so for visual phototransduction, the process responsible for converting photons of light into usable electrical signals (quantum bumps). Here, randomness of both the photon inputs (regarded as extrinsic noise) and the conversion process (intrinsic noise) are seen as two distinct, independent and significant limitations on visual reliability. Past research has attempted to quantify the relative effects of these noise sources by using approximate methods that do not fully account for the discrete, point process and time ordered nature of the problem. As a result the conclusions drawn from these different approaches have led to inconsistent expositions of phototransduction noise performance. This paper provides a fresh and complete analysis of the relative impact of intrinsic and extrinsic noise in invertebrate phototransduction using minimum mean squared error reconstruction techniques based on Bayesian point process (Snyder) filters. An integrate-fire based algorithm is developed to reliably estimate photon times from quantum bumps and Snyder filters are then used to causally estimate random light intensities both at the front and back end of the phototransduction cascade. Comparison of these estimates reveals that the dominant noise source transitions from extrinsic to intrinsic as light intensity increases. By extending the filtering techniques to account for delays, it is further found that among the intrinsic noise components, which include bump latency (mean delay and jitter) and shape (amplitude and width) variance, it is the mean delay that is critical to noise performance. As the timeliness of visual information is important for real-time action, this delay could potentially limit the speed at which invertebrates can respond to stimuli. Consequently, if one wants to increase visual fidelity, reducing the photoconversion lag is much more important than improving the regularity of the electrical signal.
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