Noise creates polarization artefacts.

The accuracy of calculations of both the degree and angle of polarization depend strongly on the noise in the measurements used. The noise in the measurements recorded by both camera based systems and spectrometers can lead to significant artefacts and incorrect conclusions about high degrees of polarization when in fact none exist. Three approaches are taken in this work: firstly, the absolute error introduced as a function of the signal to noise ratio for polarization measurements is quantified in detail. An important finding here is the reason for why several studies incorrectly suggest that black (low reflectivity) objects are highly polarized. The high degree of polarization is only an artefact of the noise in the calculation. Secondly, several simple steps to avoid such errors are suggested. Thirdly, if these points can not be followed, two methods are presented for mitigating the effects of noise: a maximum likelihood estimation method and a new denoising algorithm to best calculate the degree of polarization of natural polarization information.

Artificial neural network analysis of noisy visual field data in glaucoma.

This paper reports on the application of an artificial neural network to the clinical analysis of ophthalmological data. In particular a 2-dimensional Kohonen self-organising feature map (SOM) is used to analyse visual field data from glaucoma patients. Importantly, the paper addresses the problem of how the SOM can be utilised to accommodate the noise within the data. This is a particularly important problem within longitudinal assessment, where detecting significant change is the crux of the problem in clinical diagnosis. Data from 737 glaucomatous visual field records (Humphrey Visual Field Analyzer, program 24-2) are used to train a SOM with 25 nodes organised on a square grid. The SOM clusters the data organising the output map such that fields with early and advanced loss are at extreme positions, with a continuum of change in place and extent of loss represented by the intervening nodes. For each SOM node 100 variants, generated by a computer simulation modelling the variability that might be expected in a glaucomatous eye, are also classified by the network to establish the extent of noise upon classification. Field change is then measured with respect to classification of a subsequent field, outside the area defined by the original field and its variants. The significant contribution of this paper is that the spatial analysis of the field data, which is provided by the SOM, has been augmented with noise analysis enhancing the visual representation of longitudinal data and enabling quantification of significant class change.

Spatial classification of glaucomatous visual field loss.

AIMS: To develop and describe an objective classification system for the spatial patterns of visual field loss found in glaucoma. METHODS: The 560 Humphrey visual field analyser (program 24-2) records were used to train an artificial neural network (ANN). The type of network used, a Kohonen self organising feature map (SOM), was configured to organise the visual field defects into 25 classes of superior visual field loss and 25 classes of inferior visual field loss. Each group of 25 classes was arranged in a 5 by 5 map. RESULTS: The SOM successfully classified the defects on the basis of the patterns of loss. The maps show a continuum of change as one moves across them with early loss at one corner and advanced loss at the opposite corner. CONCLUSIONS: ANNs can classify visual field data on the basis of the pattern of loss. Once trained the ANN can be used to classify longitudinal visual field data which may prove valuable in monitoring visual field loss.

A pharmacological comparison of [3H]-granisetron binding sites in brain and peripheral tissues of the mouse.

The affinities of a range of structurally diverse 5-HT3 receptor agonists and antagonists for [3H]-granisetron binding sites have been measured in membrane homogenates prepared from central and peripheral tissues of the mouse. By comparing the affinities of compounds across these tissues, the question of whether intra-species 5-HT3 receptor subtypes exist in the mouse has been addressed. In entorhinal cortex and brainstem, [3H]-granisetron bound to a single high affinity saturable binding site (Kd 0.47 +/- 0.14 and 0.60 +/- 0.05 nM; Bmax 20 +/- 6 and 7 +/- 2 fmol (mg protein)-1 respectively; mean +/- SEM; n = 3). In distal and proximal colon, the specific binding of [3H]-granisetron was best fitted to a 2-site model. Kd values obtained for the high affinity site were similar to those obtained in brain tissue (distal colon: 0.47 +/- 0.09 nM, n = 4; proximal colon: 0.39 +/- 0.09 nM, n = 4). In salivary gland, 2-sites were evident in 2 out of 4 experiments. The Kd value (calculated from the high affinity site in the 2-site model) was approximately 10-fold less than in brain or colon (3.3 +/- 1.1 nM, n = 4). Bmax values were 7 +/- 2, 4 +/- 1 and 71 +/- 16 fmol (mg protein)-1 for distal colon, proximal colon and salivary gland respectively. For all tissues the estimated affinity of the low affinity site was variable, and Bmax values could not be reliably calculated.(ABSTRACT TRUNCATED AT 250 WORDS)

Visual field analysis using artificial neural networks.

There have been several reports on the application of artificial neural networks (ANNs) to visual field classification. While these have demonstrated that neural networks can be used with good results they have not explored the effects that the training set can have upon network performance nor emphasized the unique value of ANNs in visual field analysis. This paper considers the problem of differentiating normal and glaucomatous visual fields and explores different training set characteristics using field data collected from a Henson CFS2000 perimeter. Training set properties including size, balance between normals and glaucomas, extent of field loss and the spatial location of glaucomatous defects are explored. A multilayer network with 132 input nodes, 20 hidden layer nodes and 2 output nodes in trained using an error backpropagation algorithm. Both sensitivity and specificity are measured during testing. The results demonstrate that large random sets are better than small random sets since sensitivity improves with size and specificity is not adversely affected. The variability in performance also reduces as training set size increases. In addition, sets that are biased towards glaucoma examples are more sensitive and less specific, while sets biased with normal examples are more specific and less sensitive than balanced sets. Thus large training sets with class balance are generally desirable for good sensitivities and specificities. The actual glaucoma examples contained in the set are also important. A training set deficient in examples has no detrimental effect on sensitivity or specificity. The spatial distribution of defects is also crucial. Spatially biased sets are unable to recognize defects that occur in locations where no previous defect has been presented while more balanced sets lead to better performance. In conclusion the 'ideal' training set should contain many examples of early defects that represent the full range of locations where these defects may occur.

Characterization of dopamine autoreceptors in the amygdala: a fast cyclic voltammetric study in vitro.

The present study has employed the technique of fast cyclic voltammetry to measure electrically-evoked dopamine release within the central amygdaloid complex in a rat brain slice. Local electrical stimulation caused the release of an electroactive substance which was identified, biochemically and pharmacologically, as being neuronal dopamine. Dopamine release could be inhibited by the dopamine D2 receptor agonist, quinpirole, but not by the D1 receptor agonist, SKF38393. Quinpirole-induced inhibitions were antagonized by sulpiride, metoclopramide and clozapine but not by SCH23390. It is concluded that dopamine release in the amygdala can be modulated by presynaptic D2 receptors which appear to be the same type as those found in striatum and nucleus accumbens.

Detection of internal fixation plate loosening by means of an analysis of vibratory responses.

This paper reports an in vitro investigation of a non-invasive method for detecting the loosening of internal fixation plates. The technique involves the electromechanical vibration of the fixation plate and the electromagnetic detection of its vibratory response. Frequency domain analysis of both fixed and loosened plates are compared and spectral artefacts are suggested as a means of classifying the mode and extent of plate loosening. An algorithm for the diagnosis of loose plates using the new approach is included.

Presynaptic regulation of electrically evoked dopamine overflow in nucleus accumbens: a pharmacological study using fast cyclic voltammetry in vitro.

Fast cyclic voltammetry has been used to measure electrically evoked dopamine overflow from slices of rat nucleus accumbens in vitro. The substance detected was shown voltammetrically and biochemically to be dopamine of neuronal origin. Enough dopamine was released by a single electrical pulse to be easily detectable, and under these conditions there was no auto-inhibition by the endogenous transmitter (as demonstrated by the failure of dopamine antagonists to increase the amount released). There was no significant inhibition, or enhancement, of release by agonists at the following receptor types: dopamine D1, 5-hydroxytryptamine, cholinoceptors, alpha 1-, alpha 2-, beta-adrenoceptors, cholecystokinin or neurotensin receptors. However, the dopamine D2 receptor agonist, quinpirole, was capable of totally inhibiting the release; this effect was concentration-dependently antagonized by the D2 antagonists haloperidol, sulpiride, metoclopramide and clozapine, with potencies which corresponded to their affinities for D2 receptors in striatal tissue. The results show that the presynaptic receptors on dopaminergic nerve terminals are of the D2 type and apparently identical to those in the corpus striatum.

Application of fast cyclic voltammetry to measurement of electrically evoked dopamine overflow from brain slices in vitro.

Fast cyclic voltammetry at a carbon fibre microelectrode was used to monitor the time course of dopamine overflow in slices of rat corpus striatum incubated in a brain slice chamber. Dopamine release occurred in response to electrical stimulation. Electrochemical, physiological and pharmacological evidence indicates that release of endogenous dopamine can be measured reliably for up to 9 h and that fast cyclic voltammetry can be used in brain slices for quantitative studies of dopamine release in the CNS.

Presynaptic regulation of dopamine release in corpus striatum monitored in vitro in real time by fast cyclic voltammetry.

Dopamine release was evoked by single electrical pulses in slices of rat corpus striatum, and measured by fast cyclic voltammetry in real time. The magnitude of the release varied in the expected way to agents which modify dopamine storage, release and re-uptake. The presence of functional dopamine D2 autoreceptors was demonstrated by showing that the release was potently and completely inhibited by the selective agonists quinpirole and N,N-dipropyl-5,6-ADTN. The selective D1 agonist SKF 38393 was ineffective. The inhibition by quinpirole was competitively antagonised by haloperidol and metoclopramide with potencies which correspond closely to published values at postsynaptic striatal D2 receptors. Thus, the D2 autoreceptors on striatal nerve terminals appear to be indistinguishable from those on the postsynaptic neurons.