Point process analysis of noise in early invertebrate vision.
Point process analysis of noise in early invertebrate vision.
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DOI：
10.1371/journal.pcbi.1005687
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发表时间：
2017-10
影响因子：
4.3
通讯作者：
Vinnicombe G
中科院分区：
文献类型：
--
作者：
Parag KV;Vinnicombe G
噪声是许多生物过程中普遍存在的，有时甚至是占主导地位的方面。虽然许多自然系统已经适应了衰减甚至有效地整合噪声，但它引入的可变性通常仍然限制了生物功能之间可实现的精度。这对于视觉光传导尤其如此，该过程负责将光子转换为可用的电信号（量子点）。在这里，光子输入（被视为外部噪声）和转换过程（内部噪声）的随机性被视为视觉可靠性的两个不同、独立且重要的限制。过去的研究试图量化这些噪声源的相对影响，使用近似方法，不完全考虑离散，点过程和时间顺序的性质的问题。因此，从这些不同的方法得出的结论导致了不一致的光转导噪声性能的曝光。本文提供了一个新的和完整的分析的内在和外在的噪声在无脊椎动物光转导的相对影响，使用最小均方误差重建技术的基础上贝叶斯点过程（斯奈德）过滤器。一个集成的火灾为基础的算法开发，可靠地估计光子时间从量子凸点和斯奈德过滤器，然后使用因果关系估计随机光强度的前端和后端的光转导级联。这些估计的比较表明，占主导地位的噪声源的过渡从外在的内在的光强度的增加。通过扩展滤波技术以考虑延迟，进一步发现在包括碰撞延迟（平均延迟和抖动）和形状（幅度和宽度）方差的固有噪声分量中，平均延迟对噪声性能至关重要。由于视觉信息的及时性对实时行动很重要，这种延迟可能会限制无脊椎动物对刺激的反应速度。因此，如果想要增加视觉保真度，减少光转换滞后比改善电信号的规律性重要得多。无脊椎动物的光转换系统捕获环境光输入并将其转换为电信号，用于以后的视觉处理。因此，人们希望以某种方式对其进行优化，以确保在转换过程中仅丢失最少量的环境信息。为了说明这一点，需要理解和量化性能限制噪声源。光子本身是随机和离散的，会引入外部噪声。将光子转换成具有非确定性形状的电凸块和激光的光传导级联贡献了固有噪声。以前的工作特点的相对影响，所有这些来源没有考虑到离散的，因果关系，点过程的性质的问题，因此结果往往是不确定的。在这里，我们使用非线性泊松过程滤波表明，光子噪声是主导在低光强和级联噪声限制在高强度。此外，我们的分析表明，平均碰撞延迟是最有害的方面的固有噪声。我们的工作强调了一种新的方法来评估感官噪声，并提供了第一个完整的描述和评估的相对影响，噪声在光转导，不依赖于连续性，线性或高斯近似。
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. The invertebrate phototransduction system captures and converts environmental light inputs into electrical signals for use in later visual processing. Consequently, one would expect it to be optimised in some way to ensure that only a minimal amount of environmental information is lost during conversion. Confirming this requires an understanding and quantification of the performance limiting noise sources. Photons, which are inherently random and discrete, introduce extrinsic noise. The phototransduction cascade, which converts photons into electrical bumps possessing non-deterministic shapes and latencies, contributes intrinsic noise. Previous work on characterising the relative impact of all these sources did not account for the discrete, causal, point process nature of the problem and thus results were often inconclusive. Here we use non-linear Poisson process filtering to show that photon noise is dominant at low light intensity and cascade noise limiting at high intensity. Further, our analysis reveals that mean bump delay is the most deleterious aspect of the intrinsic noise. Our work emphasises a new approach to assessing sensory noise and provides the first complete description and evaluation of the relative impact of noise in phototransduction that does not rely on continuity, linearity or Gaussian approximations.
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