Limits to visual processing: non-linearities, noise and integration

在任何感觉系统中，处理过程都有三个基本阶段：初始过滤、非线性转导和整合。神经信号受到内部噪声的干扰，这限制了可检测性。以前的方法通常假设视觉系统是线性的，神经噪声是加性的。然而，现在认识到人类视觉系统具有也影响这些测量的非线性。此外，如果不考虑这些影响，这种非线性的差异可能会与内部噪声电平的差异混淆。这些影响需要一种新的综合方法，将非线性与内部噪声区分开来。在这个建议中，我开发了新的方法，将有长期的适用性，了解在皮层的视觉处理的功能限制。这将在短期内应用于对比处理，并在中期应用于形式和运动的处理。 我将主要使用心理物理学方法进行调查。这些是精心控制的行为实验，当与计算建模相结合时，使我们能够研究视觉系统如何处理其输入以驱动人类行为。我对非线性的研究将基于成熟的基座掩蔽范式。该方法测量应用于大脑中的输入信号的任何非线性变换的导数。我还提出了一个新的范例，将允许一个测量范围内的神经噪声集成在不同的大脑区域有关的不同的刺激功能。 短期目标是提供一个完整的理解的限制，以对比度检测在正常健康的观察者和如何从早期视觉区域的对比度输入集成在整个空间，以允许全球的对比度处理。对于空间频率、时间频率、色度、场偏心率和平均亮度的每个维度。我将从非线性转换、内部噪声和时空整合来确定相对限制。这将作为后续工作的基础，研究这些基本限制中的每一个如何随着健康观察者的年龄和患者人群的疾病而变化。 我们的研究计划的长期目标是调查，如何三个基本因素-非线性，噪声源和时空整合-有助于检测的刺激功能，从对比运动，轮廓，形状，形状从运动，光流和立体声，无论是本地计算通常在纹状皮层进行，以及更多的全球计算典型的外纹状皮层。 这里所采取的方法既基本又新颖。它涉及到一个基于模型的原则性框架，在这个框架中回答了视觉中的一些基本问题

In any sensory system there are three fundamental stages in processing; the initial filtering, non-linear transduction and integration. Neural signals are perturbed by internal noise that limits detectability. Previous approaches have often assumed the visual system is linear and the neural noise is additive. However, it is now recognized that the human visual system has nonlinearities that also affect these measurements. Furthermore, differences in this nonlinearity can be confused with differences in internal noise level if these effects are not accounted for. These effects require a new comprehensive approach that will distinguish nonlinearities from internal noise. In this proposal I develop novel methods that will have long term applicability for understanding the functional limits of visual processing in the cortex. This will be applied in the short term to contrast processing, and to the processing of form and motion in the intermediate term. I will principally use psychophysical methods for my investigations. These are carefully-controlled behavioural experiments which, when combined with computational modelling, allow us to investigate how the visual system processes its input in order to drive human behaviour. My investigations into the non-linearities present will be based on the well-established pedestal masking paradigm. This method measures the derivative of any non-linear transformation that is applied to the input signal in the brain. I also propose a novel paradigm that will allow one to measure the range over which neural noise is integrated at the various brain areas relating to different stimulus features. The short-term objectives are to provide a complete understanding of the limits to contrast detection in normal healthy observers and how contrast inputs from early visual areas are integrated across space to allow for the global processing of contrast. For each of the dimensions of spatial frequency, temporal frequency, chromaticity, field eccentricity and mean luminance. I will determine the relative limitations from non-linear transduction, internal noise, and spatiotemporal integration. This will serve as a foundation for subsequent work on how each of these fundamental limitations changes with age in healthy observers and with disease in patient populations. The longer term objective of our program of research is to investigate, how three fundamental factors - nonlinearities, noise sources, and spatiotemporal integration - contribute to the detection of stimulus features from contrast to motion, contours, shape, shape-from-motion, optic flow and stereo, both for local computations typically carried out in striate cortex as well as more global computations typical of extra-striate cortex. The approach taken here is both fundamental and novel. It involves a principled model-based framework in which to answer some of the basic questions in vision