Bayesian classification with Gaussian processes

We consider the problem of assigning an input vector bfx to one of m classes by predicting P(c|bfx) for c = 1, ldots, m. For a two-class problem, the probability of class 1 given bfx is estimated by s(y(bfx)), where s(y) = 1/(1 + e^-y). A Gaussian process prior is placed on y(bfx), and is combined with the training data to obtain predictions for new bfx points. We provide a Bayesian treatment, integrating over uncertainty in y and in the parameters that control the Gaussian process prior; the necessary integration over y is carried out using Laplace's approximation. The method is generalized to multi-class problems (m >2) using the softmax function. We demonstrate the effectiveness of the method on a number of datasets.

Independent detectors for expansion and rotation, and for orthogonal components of deformation

It is well known that optic flow - the smooth transformation of the retinal image experienced by a moving observer - contains valuable information about the three-dimensional layout of the environment. From psychophysical and neurophysiological experiments, specialised mechanisms responsive to components of optic flow (sometimes called complex motion) such as expansion and rotation have been inferred. However, it remains unclear (a) whether the visual system has mechanisms for processing the component of deformation and (b) whether there are multiple mechanisms that function independently from each other. Here, we investigate these issues using random-dot patterns and a forced-choice subthreshold summation technique. In experiment 1, we manipulated the size of a test region that was permitted to contain signal and found substantial spatial summation for signal components of translation, expansion, rotation, and deformation embedded in noise. In experiment 2, little or no summation was found for the superposition of orthogonal pairs of complex motion patterns (eg expansion and rotation), consistent with probability summation between pairs of independent detectors. Our results suggest that optic-flow components are detected by mechanisms that are specialised for particular patterns of complex motion.

Advances in methods for the determination of biologically relevant lipid peroxidation products

Lipid peroxidation is recognized to be an important contributor to many chronic diseases, especially those of an inflammatory pathology. In addition to their value as markers of oxidative damage, lipid peroxidation products have also been shown to have a wide variety of biological and cell signalling effects. In view of this, accurate and sensitive methods for the measurement of lipid peroxidation products are essential. Although some assays have been described for many years, improvements in protocols are continually being reported and, with recent advances in instrumentation and technology, highly specialized and informative techniques are increasingly used. This article gives an overview of the most currently used methods and then addresses the recent advances in some specific approaches. The focus is on analysis of oxysterols, F(2)-isoprostanes and oxidized phospholipids by gas chromatography or liquid chromatography mass spectrometry techniques and immunoassays for the detection of 4-hydroxynonenal.