猫外膝体神经元非寻常的方位调谐特性——Ⅰ、在正常猫的研究

在九只成年猫上用玻璃电极记录了单个外膝体神经元对不同方位的移动正弦光栅刺激的反应共详细测定了４００个细胞的方位调谐特性。少数外膝体神经元具有非寻常的方位调谐特性,包括：具蝴蝶状调谐曲线的方位调谐特性;双调谐的方位调谐特性和最优方位随刺激光栅空间频率的改变而变化的方位调谐特性。这些细胞非寻常的方位调谐特性往往伴随着非寻常的空间频率调谐特性。空们的方位调谐特性和空间频率调谐特性都不能用Ｓｏｏｄａｋ等提     

视觉细胞反应中方向选择性和取向选择性成分的分离

运动的光刺激常被用于研究视觉神经细胞的方向和取向选择性.但是,在细胞的反应中,两种因素同时存在且混杂在一起; 以往的各种分析方法均因未能有效地解决这一问题而不够准确,对此我们给出了理论和实例证明.本工作引入正余弦函数系对实验数据作最优回归分析.拟合程度好于以往的方法.并且从根本上分离了反应中的方向和取向选择性成分.使对这两种性质的准确定量成为可能.本文对此方法的内在含义作出了解释,并提出了对方向、取向选择性及最优方向、取向的理解.     

Simple method for developing percentile growth curves for height and weight

The present paper demonstrates the ease of use of method I by Preece and Baine ([1978] Ann Hum Biol 5:1-24) in generating smoothed growth curves for both height and weight. Using the National Center for Health Statistics (NCHS) growth curve data, smoothed curves were developed and compared to those produced using the least-squares-cubic-spline method. Based on the lower sum of squares and better fit of shape as indicated by residual examination, it was concluded that the method I curve fitting procedure by Preece and Baine ([1978] Ann Hum Biol 5:1-24) fit centile growth curves for height and weight in 2-18-year-old male and female children as well as, if not better than, the least-squares-cubic-spline method used in developing the 1979 NCHS growth curves. Further, as this paper demonstrates, smoothed curves can be generated on a desktop computer using readily available software (the SOLVER function within Microsoft EXCEL).     

The simulation of aerial movement--I. The determination of orientation angles from film data

Quantitative mechanical analyses of human movement require the time histories of the angles which specify body configuration and orientation. When these angles are obtained from a filmed performance they may be used to evaluate the accuracy of a simulation model. This paper presents a method of determining orientation angles and their rates of change from film data. The stages used comprise the synchronization of data obtained from two camera views, the determination of three-dimensional coordinates of joint centres, the calculation of an angle from a sequence of sine and cosine values and the curve fitting of angles using quintic splines. For each stage, other possible approaches are discussed. Original procedures are presented for obtaining individual error estimates of both the film data and the calculated angles to permit the automatic fitting of quintic splines for interpolation and differentiation and for deriving the time history of an angle as a continuous function from a sequence of sine and cosine values. The method is applied to a forward somersault with 1 1/2 twists and the average error estimate of 17 orientation angles is obtained as 2.1 degrees.     

Pharmfit-a Nonlinear Fitting Program for Pharmacology

A new program is presented for nonlinear fitting of data from pharmacological and chronobiological investigations. It contains functions for calculating data from ligand-binding studies and competition experiments, for the analysis of dose-response curves, for pharmacokinetic calculations, and for cosine analysis of harmonic and overlapping rhythms. In addition, it is possible to implement general equations by the user. The program allows data exchange with most spreadsheet, database, and graphics presentation programs, and accepts data from two widely used ambulatory 24-h blood-pressure monitoring systems. The fitting procedure uses the Marquardt-Levenberg algorithm. It calculates the weighted or the unweighted fit together with a great variety of statistics for estimation of goodness of fit. A graphics module permits graphical presentation of the fitted curve. Moreover, fitting of data to different models can be compared for the most likely fit and model discrimination statistics for improvement of further experiments are provided. To demonstrate the chronobiological application of the fitting program PHARMFIT, the analysis of telemetric heart rate data from rats is presented.     

PHARMFIT—a Nonlinear Fitting Program for Pharmacology

A new program is presented for nonlinear fitting of data from pharmacological and chronobiological investigations. It contains functions for calculating data from ligand-binding studies and competition experiments, for the analysis of dose-response curves, for pharmacokinetic calculations, and for cosine analysis of harmonic and overlapping rhythms. In addition, it is possible to implement general equations by the user. The program allows data exchange with most spreadsheet, database, and graphics presentation programs, and accepts data from two widely used ambulatory 24-h blood-pressure monitoring systems. The fitting procedure uses the Marquardt–Levenberg algorithm. It calculates the weighted or the unweighted fit together with a great variety of statistics for estimation of goodness of fit. A graphics module permits graphical presentation of the fitted curve. Moreover, fitting of data to different models can be compared for the most likely fit and model discrimination statistics for improvement of further experiments are provided. To demonstrate the chronobiological application of the fitting program PHARMFIT, the analysis of telemetric heart rate data from rats is presented.     

Separation of Spatio-Temporal Receptive Fields into Sums of Gaussian Components

Visual cortical simple cells have been experimentally shown to reveal non-trivial spatio-temporal orientation tuning functions comprising different phases of specifically tuned enhanced and suppressed activity. A recently developed analytical method based on nonlinear neural field models suggests that such space-time responses should be approximately separable into a sum of temporally amplitude modulated Gaussian spatial components. In the present work, we investigate this possibility by means of numerical fits of sums of Gaussians to response functions observed in experiments and computer simulations. Because the theory relates each single component to a particular connectivity kernel between the underlying cell classes shaping the response, the relative contribution of feedforward and cortex-intrinsical excitatory and inhibitory feedback mechanisms to single cell tuning can be approached and quantified in experimental data.     

Quantification of two-dimensional NOE spectra via a combined linear and nonlinear least-squares fit

Summary Determining the volumes of peaks in 2D NMR spectra can be prohibitively difficult in cases of overlapping, broad lines. Deconvolution and parameter estimation can be attempted on either the time-domain or the frequency-domain data. We present a method of estimating spectral parameters from frequency-domain data, using a combination of Lorentzian and Gaussian lineshapes for reference lines. This approach combines a previously published method of projecting the data on a linear space spanned by reference lines with a nonlinear least-squares fitting algorithm. Comparison of this method with other published methods of frequency-domain deconvolution shows that it is both more precise and more accurate when estimating 2D volumes.     

INFOS: spectrum fitting software for NMR analysis

Software for fitting of NMR spectra in MATLAB is presented. Spectra are fitted in the frequency domain, using Fourier transformed lineshapes, which are derived using the experimental acquisition and processing parameters. This yields more accurate fits compared to common fitting methods that use Lorentzian or Gaussian functions. Furthermore, a very time-efficient algorithm for calculating and fitting spectra has been developed. The software also performs initial peak picking, followed by subsequent fitting and refinement of the peak list, by iteratively adding and removing peaks to improve the overall fit. Estimation of error on fitting parameters is performed using a Monte-Carlo approach. Many fitting options allow the software to be flexible enough for a wide array of applications, while still being straightforward to set up with minimal user input.     

The gambin model provides a superior fit to species abundance distributions with a single free parameter: evidence,implementation and interpretation

The species abundance distribution (SAD) has been a central focus of community ecology for over fifty years, and is currently the subject of widespread renewed interest. The gambin model has recently been proposed as a model that provides a superior fit to commonly preferred SAD models. It has also been argued that the model's single parameter (α) presents a potentially informative ecological diversity metric, because it summarises the shape of the SAD in a single number. Despite this potential, few empirical tests of the model have been undertaken, perhaps because the necessary methods and software for fitting the model have not existed. Here, we derive a maximum likelihood method to fit the model, and use it to undertake a comprehensive comparative analysis of the fit of the gambin model. The functions and computational code to fit the model are incorporated in a newly developed free‐to‐download R package (gambin). We test the gambin model using a variety of datasets and compare the fit of the gambin model to fits obtained using the Poisson lognormal, logseries and zero‐sum multinomial distributions. We found that gambin almost universally provided a better fit to the data and that the fit was consistent for a variety of sample grain sizes. We demonstrate how α can be used to differentiate intelligibly between community structures of Azorean arthropods sampled in different land use types. We conclude that gambin presents a flexible model capable of fitting a wide variety of observed SAD data, while providing a useful index of SAD form in its single fitted parameter. As such, gambin has wide potential applicability in the study of SADs, and ecology more generally.     

Analysis of lambing distribution in the Ripollesa sheep breed. I. Development and comparison of circular von Mises models

Circular data originates in a wide range of scientific fields and can be analyzed on the basis of directional statistics and special distributions wrapped around the circumference. However, both propensity to transform non-linear to linear data and complexity of directional statistics limited the generalization of the circular paradigm in the animal breeding framework, among others. Here, we generalized a circular mixed (CM) model within the context of Bayesian inference. Three different parametrizations with different hierarchical structures were developed on basis of the von Mises distribution; moreover, both goodness of fit and predictive ability from each parametrization were compared through the analyses of 110 116 lambing distribution records collected from Ripollesa sheep herds between 1976 and 2017. The naive circular (NC) model only accounted for population mean and homogeneous circular variance, and reached the lowest goodness-of-fit and predictive ability. The CM model assumed a hierarchical structure for the population mean by accounting for systematic (ewe age and lambing interval) and permanent environmental sources of variation (flock-year-season and ewe). This improved goodness of fit by reducing both the deviance information criterion (DIC; −2520 units) and the mean square error (MSE; −12.4%) between simulated and predicted lambing data when compared against the NC model. Finally, the last parametrization expanded CM model by also assuming a hierarchical structure with systematic and permanent environmental factors for the variance parameter of the von Mises distribution (i.e. circular canalization (CC) model). This last model reached the best goodness of fit to lambing distribution data with a DIC estimate 5425 units lower than the one for NC model (MSE reduced 13.2%). The same pattern revealed when models were compared in terms of predictive ability. The superiority revealed by CC model emphasized the relevance of heteroskedasticity for the analysis of lambing distribution in the Ripollesa breed, and suggested potential applications for the sheep industry, even genetic selection for canalization. The development of CM models on the basis of the von Mises distribution has allowed to integrate flexible hierarchical structures accounting for different sources of variation and affecting both mean and dispersion terms. This must be viewed as a useful statistical tool with multiple applications in a wide range of research fields, as well as the livestock industry. The next mandatory step should be the inclusion of genetic terms in the hierarchical structure of the models in order to evaluate their potential contribution to current selection programs.     

Detecting outliers when fitting data with nonlinear regression – a new method based on robust nonlinear regression and the false discovery rate

Background  

Nonlinear regression, like linear regression, assumes that the scatter of data around the ideal curve follows a Gaussian or normal distribution. This assumption leads to the familiar goal of regression: to minimize the sum of the squares of the vertical or Y-value distances between the points and the curve. Outliers can dominate the sum-of-the-squares calculation, and lead to misleading results. However, we know of no practical method for routinely identifying outliers when fitting curves with nonlinear regression.     

Visual cells remember earlier applied target: plasticity of orientation selectivity

Background

A canonical proposition states that, in mature brain, neurons responsive to sensory stimuli are tuned to specific properties installed shortly after birth. It is amply demonstrated that that neurons in adult visual cortex of cats are orientation-selective that is they respond with the highest firing rates to preferred oriented stimuli.

Methodology/Principal Findings

In anesthetized cats, prepared in a conventional fashion for single cell recordings, the present investigation shows that presenting a stimulus uninterruptedly at a non-preferred orientation for twelve minutes induces changes in orientation preference. Across all conditions orientation tuning curves were investigated using a trial by trial method. Contrary to what has been previously reported with shorter adaptation duration, twelve minutes of adaptation induces mostly attractive shifts, i.e. toward the adapter. After a recovery period allowing neurons to restore their original orientation tuning curves, we carried out a second adaptation which produced three major results: (1) more frequent attractive shifts, (2) an increase of their magnitude, and (3) an additional enhancement of responses at the new or acquired preferred orientation. Additionally, we also show that the direction of shifts depends on the duration of the adaptation: shorter adaptation in most cases produces repulsive shifts, whereas adaptation exceeding nine minutes results in attractive shifts, in the same unit. Consequently, shifts in preferred orientation depend on the duration of adaptation.

Conclusion/Significance

The supplementary response improvements indicate that neurons in area 17 keep a memory trace of the previous stimulus properties, thereby upgrading cellular performance. It also highlights the dynamic nature of basic neuronal properties in adult cortex since repeated adaptations modified both the orientation tuning selectivity and the response strength to the preferred orientation. These enhanced neuronal responses suggest that the range of neuronal plasticity available to the visual system is broader than anticipated.     

Accuracy in estimating motor commands using neuronal population coding

We consider the problem of estimating motor commands from an ensemble of neuronal activities. The population vector algorithm proposed by Georgopoulos provides largely biased estimations when preferred directions of neurons are non-uniformly distributed. To improve this, various decoding methods have been proposed. However, dependence of decoding accuracy on the motor command and other features of neural activities, such as baseline firing rates or amplitudes of tuning curves, have not been quantitatively discussed. In this study, we propose a new method to estimate the motor command in the maximum likelihood estimation framework, which is analytically tractable. We find that the estimation accuracy is independent of the motor command. Using our estimation method, we can estimate the motor command with equal accuracy in all directions.     

Problems in Fitting a Cosine Curve: Short Communications

In fitting of cosine curves latent experimental inequalities due to a serial effect have to be excluded. Though cosinor analysis may be sufficient then, inclusion of biological time, i.e. not fitting values to time but to a function of time, will lead to further improvement.     

Problems in Fitting a Cosine Curve: Short Communications

In fitting of cosine curves latent experimental inequalities due to a serial effect have to be excluded. Though cosinor analysis may be sufficient then, inclusion of biological time, i.e. not fitting values to time but to a function of time, will lead to further improvement.