Size matters: non-numerical magnitude affects the spatial coding of response

It is known that small and large numbers facilitate left/right respectively (the SNARC effect). Recently, it has been proposed that numerical magnitude is just one example of a range of quantities, which have a common cognitive/neural representation. To investigate this proposition, response congruency effects were explored for stimuli which differed according to their: (a) numerical size, (b) physical size, (c) luminance, (d) conceptual size and (e) auditory intensity. In a series of experiments, groups of undergraduate participants made two-alternative forced choice discriminations with their left or right hands. There were clear interactions between magnitude and responding hand whereby right hand responses were faster for stimuli with (a) large numbers, (b) large physical size, (c) low luminance, and (d) a reference to large objects. There was no congruency effect for the auditory stimuli. The data demonstrate that the response congruency effect observed for numbers also occurs for a variety of other non-numerical visual quantities. These results support models of general magnitude representation and suggest that the association between magnitude and the left/right sides of space may not be related to culture and/or directional reading habits.     

Microsatellite Genetic Distances with Range Constraints: Analytic Description and Problems of Estimation

Statistical properties of the symmetric stepwise-mutation model for microsatellite evolution are studied under the assumption that the number of repeats is strictly bounded above and below. An exact analytic expression is found for the expected products of the frequencies of alleles separated by k repeats. This permits characterization of the asymptotic behavior of our distances D(1) and (δμ)(2) under range constraints. Based on this characterization we develop transformations that partially restore linearity when allele size is restricted. We show that the appropriate transformation cannot be applied in the case of varying mutation rates (β) and range constraints (R) because of statistical difficulties. In the special case of no variation in β and R across loci, however, the transformation simplifies to a usable form and results in a distance much more linear with time than distances developed for an infinite range. Although analytically incorrect in the case of variation in β and R, the simpler transformation is surprisingly insensitive to variation in these parameters, suggesting that it may have considerable utility in phylogenetic studies.     

A variance-stabilizing transformation for gene-expression microarray data

MOTIVATION: Standard statistical techniques often assume that data are normally distributed, with constant variance not depending on the mean of the data. Data that violate these assumptions can often be brought in line with the assumptions by application of a transformation. Gene-expression microarray data have a complicated error structure, with a variance that changes with the mean in a non-linear fashion. Log transformations, which are often applied to microarray data, can inflate the variance of observations near background. RESULTS: We introduce a transformation that stabilizes the variance of microarray data across the full range of expression. Simulation studies also suggest that this transformation approximately symmetrizes microarray data.     

Abundance patterns of European breeding birds

The frequency distribution of national population sizes of breeding birds was examined for each of 48 European countries, including autonomous regions, using data from the European Bird Database. The frequency distribution of logarithmically transformed abundance was left skewed in 40 countries: there was significant left skew in 10, and positive skew, in 2 countries. The inclusion of data classed as of low quality did not alter the conclusion that abundance patterns were predominantly left skewed. Abundance patterns of resident and migrant breeding birds differed; residents were left skewed, migrants were lognormal. Skewness was correlated negatively the number of species within a country. At low sample size, both left and right skews were evident, but left skews predominated at larger samples sizes. This pattern was driven partly by a difference between breeding populations on islands and on continental countries. Resampling procedures with fixed sample size showed that resident and migrant birds differed consistently in their patterns of skew, independent of sample size. If the birds of Europe were treated as a single assemblage, their abundance pattern was left skewed but this was driven by a very small number of vagrant breeders.     

Endogenous cortical rhythms determine cerebral specialization for speech perception and production

Across multiple timescales, acoustic regularities of speech match rhythmic properties of both the auditory and motor systems. Syllabic rate corresponds to natural jaw-associated oscillatory rhythms, and phonemic length could reflect endogenous oscillatory auditory cortical properties. Hemispheric lateralization for speech could result from an asymmetry of cortical tuning, with left and right auditory areas differentially sensitive to spectro-temporal features of speech. Using simultaneous electroencephalographic (EEG) and functional magnetic resonance imaging (fMRI) recordings from humans, we show that spontaneous EEG power variations within the gamma range (phonemic rate) correlate best with left auditory cortical synaptic activity, while fluctuations within the theta range correlate best with that in the right. Power fluctuations in both ranges correlate with activity in the mouth premotor region, indicating coupling between temporal properties of speech perception and production. These data show that endogenous cortical rhythms provide temporal and spatial constraints on the neuronal mechanisms underlying speech perception and production.     

A comparison of methods for fitting allometric equations to field metabolic rates of animals

We re-examined data for field metabolic rates of varanid lizards and marsupial mammals to illustrate how different procedures for fitting the allometric equation can lead to very different estimates for the allometric coefficient and exponent. A two-parameter power function was obtained in each case by the traditional method of back-transformation from a straight line fitted to logarithms of the data. Another two-parameter power function was then generated for each data-set by non-linear regression on values in the original arithmetic scale. Allometric equations obtained by non-linear regression described the metabolic rates of all animals in the samples. Equations estimated by back-transformation from logarithms, on the other hand, described the metabolic rates of small species but not large ones. Thus, allometric equations estimated in the traditional way for field metabolic rates of varanids and marsupials do not have general importance because they do not characterize rates for species spanning the full range in body size. Logarithmic transformation of predictor and response variables creates new distributions that may enable investigators to perform statistical analyses in compliance with assumptions underlying the tests. However, statistical models fitted to transformations should not be used to estimate parameters of equations in the arithmetic domain because such equations may be seriously biased and misleading. Allometric analyses should be performed on values expressed in the original scale, if possible, because this is the scale of interest.     

Needs and benefits of empirical power transformations for production and quality traits in forest tree breeding

Non-normality in the distribution of individual observations of production and quality traits in forest tree breeding may cause inaccurate selection and overestimation of predicted selection gain. The distribution of individual observations of traits such as height, diameter, branch diameter, branch angle and number of branches per whorl is not always normal. We investigated how the observations were distributed and to what degree it is possible to improve normality, homogeneity of error variance and additivity by using empirical power transformations. Computer simulations showed that a seriously skewed distribution impairs selection efficiency and exaggerates selection gain expectations. If the distribution is heavily skewed, transformation might be worthwhile. It does not seem possible to offer any general advice about which varities should be transformed, but in most cases there seems to be no need of any transformation.     

Analysis of covariance with incomplete data via semiparametric model transformations

We propose a method for fitting semiparametric models such as the proportional hazards (PH), additive risks (AR), and proportional odds (PO) models. Each of these semiparametric models implies that some transformation of the conditional cumulative hazard function (at each t) depends linearly on the covariates. The proposed method is based on nonparametric estimation of the conditional cumulative hazard function, forming a weighted average over a range of t-values, and subsequent use of least squares to estimate the parameters suggested by each model. An approximation to the optimal weight function is given. This allows semiparametric models to be fitted even in incomplete data cases where the partial likelihood fails (e.g., left censoring, right truncation). However, the main advantage of this method rests in the fact that neither the interpretation of the parameters nor the validity of the analysis depend on the appropriateness of the PH or any of the other semiparametric models. In fact, we propose an integrated method for data analysis where the role of the various semiparametric models is to suggest the best fitting transformation. A single continuous covariate and several categorical covariates (factors) are allowed. Simulation studies indicate that the test statistics and confidence intervals have good small-sample performance. A real data set is analyzed.     

Winter range compression of migrants in Central America

Where there is seasonal disparity among opportunities, the season with those in shortest supply is most likely to limit populations. Among migrant birds that travel between different breeding and winter ranges, any of breeding, migratory or winter conditions could exclusively constitute such population-limiting factors. In both the New and Old Worlds, landmass is disproportionately concentrated in temperate latitudes. In the Americas, most passerine bird species that breed in the USA and Canada spend the winter further south, commonly in parts of the tropics where landmass is significantly less. Using a sample of 89 migratory species (eight passerine families) that breed in eastern North America, I considered patterns of geographic breeding range size, winter range size and winter distribution. Winter range size is usually smaller than breeding range size (84 of 89 species), often substantially so (minimum 8%, mean 52%). Wintering latitude explains significant variation in both breeding range size and winter range size, as well as in winter range size relative to breeding range size. In particular, all three measures vary latitudinally in patterns similar to latitudinal variation in landmass. These patterns collectively suggest that the reduction in landmass in the latitudes of Central America and the Caribbean is a limiting factor for migrant bird populations, adding to other research concluding that winter conditions sometimes prevail over breeding conditions in the limitation of populations. Hectare for hectare, habitat destruction in the tropics is likely to have the greater impact on the welfare of passerine populations breeding in North America.     

Winter range compression of migrants in Central America

Where there is seasonal disparity among opportunities, the season with those in shortest supply is most likely to limit populations. Among migrant birds that travel between different breeding and winter ranges, any of breeding, migratory or winter conditions could exclusively constitute such population‐limiting factors. In both the New and Old Worlds, landmass is disproportionately concentrated in temperate latitudes. In the Americas, most passerine bird species that breed in the USA and Canada spend the winter further south, commonly in parts of the tropics where landmass is significantly less. Using a sample of 89 migratory species (eight passerine families) that breed in eastern North America, I considered patterns of geographic breeding range size, winter range size and winter distribution. Winter range size is usually smaller than breeding range size (84 of 89 species), often substantially so (minimum 8%, mean 52%). Wintering latitude explains significant variation in both breeding range size and winter range size, as well as in winter range size relative to breeding range size. In particular, all three measures vary latitudinally in patterns similar to latitudinal variation in landmass. These patterns collectively suggest that the reduction in landmass in the latitudes of Central America and the Caribbean is a limiting factor for migrant bird populations, adding to other research concluding that winter conditions sometimes prevail over breeding conditions in the limitation of populations. Hectare for hectare, habitat destruction in the tropics is likely to have the greater impact on the welfare of passerine populations breeding in North America.     

Circadian rhythm of the grip strength of the right and left hands: desynchronization in some shift workers

38 male shift workers and former shift workers volunteered to self-measure 4 to 8 times/24 hrs. their oral temperature (OT) as well as right and left hand grip strength (HGS) best performance during a 16 to 30 day span. Time series were analyzed individually according to two methods: day by day circadian acrophase drift and power spectrum. Mainly, but not exclusively, subjects with poor tolerance to shift work exhibited an internal desynchronization with a circadian period tau different from 24 hrs. which was the case for OT as well as right and left HGS; each could be different in tau between one another and from 24 hrs. These results suggest that oscillatory systems may be influenced by the neocortex apparently with difference between right and left side.     

Energetics of B-Z junction formation in a sixteen base-pair duplex DNA

We report analysis of the NaCl-induced B-Z transition in a 16 base-pair duplex DNA with sequence designed such that when NaCl is increased the left half of the molecule undergoes the B-Z transition while the right half remains in the B-form. An equilibrium thermodynamic model based on the body of available published experimental data and the recent theoretical work of Soumpasis, which indicate, in the salt range above approximately 0.9 M-NaCl, the transition free-energy of B-Z conversion in DNA is a linear function of the NaCl concentration, is employed. Analysis of the B-Z transition of the junction-containing molecule indicates the B-Z junction formed in this 16 base-pair DNA is composed of approximately three base-pairs and has a free energy of formation of approximately 4.7 kcal/mol junction. These values for the junction are in excellent agreement with published estimates of B-Z junction size and energy derived from much longer DNA pieces.     

Variance stabilization applied to microarray data calibration and to the quantification of differential expression

We introduce a statistical model for microarray gene expression data that comprises data calibration, the quantification of differential expression, and the quantification of measurement error. In particular, we derive a transformation h for intensity measurements, and a difference statistic Deltah whose variance is approximately constant along the whole intensity range. This forms a basis for statistical inference from microarray data, and provides a rational data pre-processing strategy for multivariate analyses. For the transformation h, the parametric form h(x)=arsinh(a+bx) is derived from a model of the variance-versus-mean dependence for microarray intensity data, using the method of variance stabilizing transformations. For large intensities, h coincides with the logarithmic transformation, and Deltah with the log-ratio. The parameters of h together with those of the calibration between experiments are estimated with a robust variant of maximum-likelihood estimation. We demonstrate our approach on data sets from different experimental platforms, including two-colour cDNA arrays and a series of Affymetrix oligonucleotide arrays.     

On rethinking allometry

Analysis of sets of intra-species and inter-species allometric relationships reveals that the inter-species data generally fit an exponential model better than a linear model. The intra-species data seem equally suited to either model. Skewness of the data and the effect of logarithmic transformations on correlation coefficients are examined in the light of these findings. Inter-species data are approximately lognormally distributed and logarithmic transformations are necessary to produce linear relationships. As a consequence, correlation coefficients usually increase after logarithmic transformation of inter-species data.     

Fibre size in the left and right recurrent laryngeal nerves (RLNs) in the man

Some morphological data of the right and left human RLNs were evaluated with the aim of verifying possible differences in the fibre composition of the two nerves. The following parameters were evaluated in the right and left RLNs of five human cases: 1) the maximum diameter of the fibres; 2) the axon diameter and area; 3) the myelin sheath area obtained substracting the axon area from the total area of each fibre. The obtained data were plotted on histograms for each case: moreover, histograms of all fibres of both left and right nerves of all five cases were made. The results show that the values of the maximum diameter of the fibres and of the myelin sheath area are always greater in a statistically significant way in the left RLNs than in the right RLNs. On the other hand the axon diameter is nearly the same in the nerves of both sides. These data suggest that the greater calibre of the myelin sheath in the fibres of the left inferior laryngeal nerve can be responsible of the faster conduction speed in this nerve. This fact might explain the simultaneous arrival of the impulses to the laryngeal muscles of the two sides in spite to the different length of the two nerves.     

Exploring virtual environments with an EEG-based BCI through motor imagery.

In this paper, we describe the possibility of navigating in a virtual environment using the output signal of an EEG-based Brain-Computer Interface (BCI). The graphical capabilities of virtual reality (VR) should help to create new BCI-paradigms and improve feedback presentation. The objective of this combination is to enhance the subject's learning process of gaining control of the BCI. In this study, the participant had to imagine left or right hand movements while exploring a virtual conference room. By imaging a left hand movement the subject turned virtually to the left inside the room and with right hand imagery to the right. In fact, three trained subjects reached 80% to 100% BCI classification accuracy in the course of the experimental sessions. All subjects were able to achieve a rotation in the VR to the left or right by approximately 45 degrees during one trial.     

Genetic algorithm optimization for pre-processing and variable selection of spectroscopic data

MOTIVATION: The major difficulties relating to mathematical modelling of spectroscopic data are inconsistencies in spectral reproducibility and the black box nature of the modelling techniques. For the analysis of biological samples the first problem is due to biological, experimental and machine variability which can lead to sample size differences and unavoidable baseline shifts. Consequently, there is often a requirement for mathematical correction(s) to be made to the raw data if the best possible model is to be formed. The second problem prevents interpretation of the results since the variables that most contribute to the analysis are not easily revealed; as a result, the opportunity to obtain new knowledge from such data is lost. METHODS: We used genetic algorithms (GAs) to select spectral pre-processing steps for Fourier transform infrared (FT-IR) spectroscopic data. We demonstrate a novel approach for the selection of important discriminatory variables by GA from FT-IR spectra for multi-class identification by discriminant function analysis (DFA). RESULTS: The GA selects sensible pre-processing steps from a total of approximately 10(10) possible mathematical transformations. Application of these algorithms results in a 16% reduction in the model error when compared against the raw data model. GA-DFA recovers six variables from the full set of 882 spectral variables against which a satisfactory DFA model can be formed; thus inferences can be made as to the biochemical differences that are reflected by these spectral bands.     

棘尾虫对折右纵断片的再生和纤毛模式形成的研究

应用切割嫁接方法获得的棘尾虫完全对折和部分对拆右纵断片都经历了一面调整极性、一面再生和形态发生的过程。推测这两种断片在纤毛模式形成中发生的诸多现象可能与所在断片再生时的极性调整变化状态有关。     

Estimation of the maximum change in stability of globular proteins upon mutation of a hydrophobic residue to another of smaller size.

Although the hydrophobic effect is generally considered to be one of the most important forces in stabilizing the folded structure of a globular protein molecule, there is a lack of consensus on the precise magnitude of this effect. The magnitude of the hydrophobic effect is most directly measured by observing the change in stability of a protein molecule when an internal hydrophobic residue is mutated to another of smaller size. Results of such measurements have, however, been confusing because they vary greatly and are generally considerably larger than expected from the transfer free energies of corresponding small molecules. In this article, a thermodynamic argument is presented to show (1) that the variation is mainly due to that in the flexibility of the protein molecule at the site of mutation, (2) that the maximum destabilization occurs when the protein at the site of mutation is rigid, in which case the value of the destabilization is approximately given by the work of cavity formation in water, and (3) that the transfer free energy approximately gives the minimum of the range of variations. The best numerical agreements between the small molecule and the protein systems are obtained when the data from the small molecule system are expressed as the molarity-based standard free energies without other corrections.     

Power of three multitrait methods for QTL detection in crossbred populations

The multitrait detections of QTL applied to a mixture of full- and half-sib families require specific strategies. Indeed, the number of parameters estimated by the multivariate methods is excessive compared with the size of the population. Thus, only multitrait methods based on a univariate analysis of a linear combination (LC) of the traits can be extensively performed. We compared three strategies to obtain the LC of the traits. Two linear transformations were performed on the overall population. The last one was performed within each half-sib family. Their powers were compared on simulated data depending on the frequency of the two QTL alleles in each of the grand parental populations of an intercross design. The transformations from the whole population did not lead to a large loss of power even though the frequency of the QTL alleles was similar in the two grand parental populations. In these cases, applying the within-sire family transformation improved the detection when the number of progeny per sire was greater than 100.