Neural Spike Train Synchronisation Indices: Definitions, Interpretations and Applications.

A comparison of previously defined spike train syncrhonization indices is undertaken within a stochastic point process framework. The second order cumulant density (covariance density) is shown to be common to all the indices. Simulation studies were used to investigate the sampling variability of a single index based on the second order cumulant. The simulations used a paired motoneurone model and a paired regular spiking cortical neurone model. The sampling variability of spike trains generated under identical conditions from the paired motoneurone model varied from 50% { 160% of the estimated value. On theoretical grounds, and on the basis of simulated data a rate dependence is present in all synchronization indices. The application of coherence and pooled coherence estimates to the issue of synchronization indices is considered. This alternative frequency domain approach allows an arbitrary number of spike train pairs to be evaluated for statistically significant differences, and combined into a single population measure. The pooled coherence framework allows pooled time domain measures to be derived, application of this to the simulated data is illustrated. Data from the cortical neurone model is generated over a wide range of firing rates (1 - 250 spikes/sec). The pooled coherence framework correctly characterizes the sampling variability as not significant over this wide operating range. The broader applicability of this approach to multi electrode array data is briefly discussed.

Cost-effectiveness of population-based, community, workplace and individual policies for diabetes prevention in the UK.

AIM: To analyse the cost-effectiveness of different interventions for Type 2 diabetes prevention within a common framework. METHODS: A micro-simulation model was developed to evaluate the cost-effectiveness of a range of diabetes prevention interventions including: (1) soft drinks taxation; (2) retail policy in socially deprived areas; (3) workplace intervention; (4) community-based intervention; and (5) screening and intensive lifestyle intervention in individuals with high diabetes risk. Within the model, individuals follow metabolic trajectories (for BMI, cholesterol, systolic blood pressure and glycaemia); individuals may develop diabetes, and some may exhibit complications of diabetes and related disorders, including cardiovascular disease, and eventually die. Lifetime healthcare costs, employment costs and quality-adjusted life-years are collected for each person. RESULTS: All interventions generate more life-years and lifetime quality-adjusted life-years and reduce healthcare spending compared with doing nothing. Screening and intensive lifestyle intervention generates greatest lifetime net benefit (£37) but is costly to implement. In comparison, soft drinks taxation or retail policy generate lower net benefit (£11 and £11) but are cost-saving in a shorter time period, preferentially benefit individuals from deprived backgrounds and reduce employer costs. CONCLUSION: The model enables a wide range of diabetes prevention interventions to be evaluated according to cost-effectiveness, employment and equity impacts over the short and long term, allowing decision-makers to prioritize policies that maximize the expected benefits, as well as fulfilling other policy targets, such as addressing social inequalities.

The impact of Type 2 diabetes prevention programmes based on risk-identification and lifestyle intervention intensity strategies: a cost-effectiveness analysis.

AIMS: To develop a cost-effectiveness model to compare Type 2 diabetes prevention programmes targeting different at-risk population subgroups with a lifestyle intervention of varying intensity. METHODS: An individual patient simulation model was constructed to simulate the development of diabetes in a representative sample of adults without diabetes from the UK population. The model incorporates trajectories for HbA1c , 2-h glucose, fasting plasma glucose, BMI, systolic blood pressure, total cholesterol and HDL cholesterol. Patients can be diagnosed with diabetes, cardiovascular disease, microvascular complications of diabetes, cancer, osteoarthritis and depression, or can die. The model collects costs and utilities over a lifetime horizon. The perspective is the UK National Health Service and personal social services. We used the model to evaluate the population-wide impact of targeting a lifestyle intervention of varying intensity to six population subgroups defined as high risk for diabetes. RESULTS: The intervention produces 0.0003 to 0.0009 incremental quality-adjusted life years and saves up to £1.04 per person in the general population, depending upon the subgroup targeted. Cost-effectiveness increases with intervention intensity. The most cost-effective options are to target individuals with HbA1c > 42 mmol/mol (6%) or with a high Finnish Diabetes Risk (FINDRISC) probability score (> 0.1). CONCLUSION: The model indicates that diabetes prevention interventions are likely to be cost-effective and may be cost-saving over a lifetime. In the model, the criteria for selecting at-risk individuals differentially impact upon diabetes and cardiovascular disease outcomes, and on the timing of benefits. These findings have implications for deciding who should be targeted for diabetes prevention interventions.

Neural spike train synchronization indices: definitions, interpretations, and applications.

A comparison of previously defined spike train syncrhonization indices is undertaken within a stochastic point process framework. The second-order cumulant density (covariance density) is shown to be common to all the indices. Simulation studies were used to investigate the sampling variability of a single index based on the second-order cumulant. The simulations used a paired motoneurone model and a paired regular spiking cortical neurone model. The sampling variability of spike trains generated under identical conditions from the paired motoneurone model varied from 50% to 160% of the estimated value. On theoretical grounds, and on the basis of simulated data a rate dependence is present in all synchronization indices. The application of coherence and pooled coherence estimates to the issue of synchronization indices is considered. This alternative frequency domain approach allows an arbitrary number of spike train pairs to be evaluated for statistically significant differences, and combined into a single population measure. The pooled coherence framework allows pooled time domain measures to be derived, application of this to the simulated data is illustrated. Data from the cortical neurone model is generated over a wide range of firing rates (1-250 spikes/s). The pooled coherence framework correctly characterizes the sampling variability as not significant over this wide operating range. The broader applicability of this approach to multielectrode array data is briefly discussed.

Identification of patterns of neuronal connectivity--partial spectra, partial coherence, and neuronal interactions.

The cross-correlation histogram has provided the primary tool for inferring the structure of common inputs to pairs of neurones. While this technique has produced useful results it not clear how it may be extended to complex networks. In this report we introduce a linear model for point process systems. The finite Fourier transform of this model leads to a regression type analysis of the relations between spike trains. An advantage of this approach is that the full range of techniques for multivariate regression analyses becomes available for spike train analysis. The two main parameters used for the identification of neural networks are the coherence and partial coherences. The coherence defines a bounded measure of association between two spike trains and plays the role of a squared correlation coefficient defined at each frequency lambda. The partial coherences, analogous to the partial correlations of multiple regression analysis, allow an assessment of how any number of putative input processes may influence the relation between any two output processes. In many cases analytic solutions may be found for coherences and partial coherences for simple neural networks, and in combination with simulations may be used to test hypotheses concerning proposed networks inferred from spike train analyses.

Randomised, prospective evaluation of a new pericardial heart valve: outcome after seven years.

Between 2 February 1987 and 20 March 1990, 170 patients were randomly allocated to receive a new pericardial heart valve (the Bioflo) or the Carpentier-Edwards supra-annular porcine bioprosthesis. Eighty-five patients (mean age 61 years, range 38-77) received 93 Bioflo valves, 46 having aortic valve replacement (AVR), 31 mitral valve replacement (MVR) and 8 aortic and mitral valve replacement (A+MVR); 85 patients (mean age 62.1 years, range 41-77) received 99 Carpentier-Edwards porcine valves (48 AVR, 23 MVR and 14 A+MVR). Cumulative follow-up totals 926 patient-years (mean 5.45 +/- 1.93, median 6.03, maximum 7.47 years). The overall operative mortality rate for the Bioflo group was 2.4%, and 5.9% for the Carpentier-Edwards group. At 7 years, there was no statistically significant difference in survival or in any prosthesis-related complication between the pericardial and porcine valve recipients overall, or when the data were analysed according to valve implant position. The actuarial survival rate at 7 years for the Bioflo group was 80.1 +/- 5.1% and 72.3 +/- 5.9% for the Carpentier-Edwards group. Freedom from structural valve deterioration (SVD) at 7 years for Bioflo patients was 98.5 +/- 1.5% and for Carpentier-Edwards patients 91.2 +/- 4.1%. No patient in the Bioflo group has required reoperation for SVD. The randomised prospective trial has proven practical and effective and has shown the pericardial valve to perform at least as well as the porcine valve up to 7 years when all of the standard outcome measures of valve performance are assessed.

Schistosome fecundity: influence of host genotype and intensity of infection.

The host genetic influence on the fecundity of Schistosoma mansoni was studied by measuring egg excretion and accumulation of eggs in the tissues of two inbred strains of mice. The two strains, NIH/Ola and CBA/Ca, differed in both parameters. Egg excretion after infection in the NIH/Ola reached a maximum and declined earlier than was the case for the CBA/Ca mice. More eggs accumulated in the gut and lungs of CBA/Ca, while the NIH/Ola had more eggs in the liver by 100 days post-infection. Statistical analysis of both tissue eggs and faecal eggs, using a robust, non-parametric method, indicated that there is significant evidence for a density dependent reduction in fecundity of worms in more heavily infected animals. We conclude that both the genetic constitution of the murine host and the intensity of infection affect the fecundity of Schistosoma mansoni worms.

A framework for the analysis of neuronal networks.

The object of this work is to consider the application of some methods of spike train analysis that are not widely known, and are concerned with the description of the interaction between spike trains and the determination of causal connections between them. The notation and terminology follow conventions established in the statistical literature. The examples given are based on in-continuity recordings of the spontaneous activity of single Ia afferents from the soleus muscle and single motor units from the same muscle. Cumulant densities are shown to be simple extensions of the traditional cross-correlation methods, and are useful in characterizing the pattern of activity in one spike train that influences that in another, and to reveal interactions between spike trains that would not be apparent from the correlation histogram alone. Parameters based on the Fourier transforms of the spike trains are shown to be useful in determining timing relations between them, and in inferring patterns of connectivity not possible by correlation methods alone.

Primary tissue failure in pericardial heart valves.

A number of centers have recorded a significant incidence of primary tissue failure with the standard Ionescu-Shiley pericardial valve. In most cases severe regurgitation was caused by leaflet tears adjacent to the edge of the cloth-covered stent. Our early clinical experience (up to 4 years' follow-up) with two new pericardial valves (Ionescu-Shiley low-profile and Hancock pericardial valves) has shown that primary tissue failure also occurs in these new valves. In vitro accelerated fatigue studies on seven of these valves (size 29 mm) showed that in vitro premature leaflet failure was caused by abrasion of the leaflet on the cloth-covering at the edge of the stent. Clinically, endothelialization and host tissue ingrowth on the cloth and the leaflets at the edge of the frame greatly reduced the amount of abrasion and the incidence of tissue failure. In seven of the eight explanted valves studied, leaflet tears occurred at the top of the stent posts where there was less endothelialization and tissue ingrowth, close to the points where sutures pass through the leaflets. It is likely that both abrasion and stress concentration around these sutures contributed to the tissue failures in the clinical valves.