The Optokinetic Reflex as a Tool for Quantitative Analyses of Nervous System Function in Mice: Application to Genetic and Drug-Induced Variation

The optokinetic reflex (OKR), which serves to stabilize a moving image on the retina, is a behavioral response that has many favorable attributes as a test of CNS function. The OKR requires no training, assesses the function of diverse CNS circuits, can be induced repeatedly with minimal fatigue or adaptation, and produces an electronic record that is readily and objectively quantifiable

The Morphology and Intrinsic Excitability of Developing Mouse Retinal Ganglion Cells

The retinal ganglion cells (RGCs) have diverse morphology and physiology. Although some studies show that correlations between morphological properties and physiological properties exist in cat RGCs, these properties are much less distinct and their correlations are unknown in mouse RGCs. In this study, using three-dimensional digital neuron reconstruction, we systematically analyzed twelve morphological parameters of mouse RGCs as they developed in the first four postnatal weeks. The development of these parameters fell into three different patterns and suggested that contact from bipolar cells and eye opening might play important roles in RGC morphological development. Although there has been a general impression that the morphological parameters are not independent, such as RGCs with larger dendritic fields usually have longer but sparser dendrites, there was not systematic study and statistical analysis proving it. We used Pearson's correlation coefficients to determine the relationship among these morphological parameters and demonstrated that many morphological parameters showed high statistical correlation. In the same cells we also measured seven physiological parameters using whole-cell patch-clamp recording, focusing on intrinsic excitability. We previously reported the increase in intrinsic excitability in mouse RGCs during early postnatal development. Here we showed that strong correlations also existed among many physiological parameters that measure the intrinsic excitability. However, Pearson's correlation coefficient revealed very limited correlation across morphological and physiological parameters. In addition, principle component analysis failed to separate RGCs into clusters using combined morphological and physiological parameters. Therefore, despite strong correlations within the morphological parameters and within the physiological parameters, postnatal mouse RGCs had only limited correlation between morphology and physiology. This may be due to developmental immaturity, or to selection of parameters

A robust VaR model under different time periods and weighting schemes

This paper analyses several volatility models by examining their ability to forecast Value-at-Risk (VaR) for two different time periods and two capitalization weighting schemes. Specifically, VaR is calculated for large and small capitalization stocks, based on Dow Jones (DJ) Euro Stoxx indices and is modeled for long and short trading positions by using non parametric, semi parametric and parametric methods. In order to choose one model among the various forecasting methods, a two-stage backtesting procedure is implemented. In the first stage the unconditional coverage test is used to examine the statistical accuracy of the models. In the second stage a loss function is applied to investigate whether the differences between the models, that calculated accurately the VaR, are statistically significant. Under this framework, the combination of a parametric model with the historical simulation produced robust results across the sample periods, market capitalization schemes, trading positions and confidence levels and therefore there is a risk measure that is reliable. Copyright Springer Science+Business Media, LLC 2007Asymmetric power ARCH, Backtesting, Extreme value theory, Filtered historical simulation, Value-at-risk,