Visual sensitivity in search tasks depends on the response requirement

This paper reports a comparison between two tasks of visual search. Two observers carried out, in separate blocks, a saccade-to-target task and a manual-target-detection task. The displays, which were identical for the two tasks, consisted of a ring of eight equally spaced Gabor patches. The target could be defined by a difference from the distractors along four possible dimensions: orientation, spatial frequency, contrast or size. These four dimensions were used as variables in separate experiments. In each experiment, performance was measured over an extensive range of values of the particular dimension. Thresholds were thus obtained for the saccade and the manual response tasks. The nature of the response was found to modify the relative visual sensitivity. For orientation differences, manual response performance was better than saccade-to-target performance. The reverse was true for spatial frequency and contrast differences, where saccade-to-target performance was better than manual response performance. We conclude that saccade-selection in a search task draws on different visual information from that used for manual responding in the equivalent task. The two tasks thus differ in more than the different response systems used: the results suggest the action of different underlying neural visual mechanisms as well as different neural motor mechanisms.     

Assessment of control ability in the physically handicapped

A tracking task was developed in order to obtain parameters relevant to the design of control interfaces for the physically handicapped. Principles of construction and operation are given, and methods for obtaining parameters are described. Results are presented from evaluator use with a number of subjects covering a wide range of control abilities. Overall performance in the tracking task is compared to general physical ability and experience with other control devices. One task required a response to a target which moved between two possible positions after a constant or variable time interval; correlation was observed between variables representing overall speed and accuracy. For multi-level tasks, scores equal to total time on target were obtained for tasks of differing complexity. Their values are shown to contain information on both speed and accuracy of control. Factors affecting performance are discussed and useful parameters suggested. In particular, information derived from the first, simpler task was shown to correlate well with that from the more complex tests. This type of test provides a useful general method for the interactive design and assessment of control interfaces.     

Estimation of raw material performance in mammalian cell culture using near infrared spectra combined with chemometrics approaches

Understanding variability in raw materials and their impacts on product quality is of critical importance in the biopharmaceutical manufacturing processes. For this purpose, several spectroscopic techniques have been studied for raw material characterization, providing fast and nondestructive ways to measure quality of raw materials. However, investigations of correlation between spectra of raw materials and cell culture performance have been scarce due to their complexity and uncertainty. In this study, near-infrared spectra and bioassays of multiple soy hydrolysate lots manufactured by different vendors were analyzed using chemometrics approaches in order to address variability of raw materials as well as correlation between raw material properties and corresponding cell culture performance. Principal component analysis revealed that near-infrared spectra of different soy lots contain enough physicochemical information about soy hydrolysates to allow identification of lot-to-lot variability as well as vendor-to-vendor differences. The identified compositional variability was further analyzed in order to estimate cell growth and protein production of two mammalian cell lines under the condition of varying soy dosages using partial least square regression combined with optimal variable selection. The performance of the resulting models demonstrates the potential of near-infrared spectroscopy as a robust lot selection tool for raw materials while providing a biological link between chemical composition of raw materials and cell culture performance.     

Dynamical aspects of behavior generation under constraints

Dynamic adaptation is a key feature of brains helping to maintain the quality of their performance in the face of increasingly difficult constraints. How to achieve high-quality performance under demanding real-time conditions is an important question in the study of cognitive behaviors. Animals and humans are embedded in and constrained by their environments. Our goal is to improve the understanding of the dynamics of the interacting brain–environment system by studying human behaviors when completing constrained tasks and by modeling the observed behavior. In this article we present results of experiments with humans performing tasks on the computer under variable time and resource constraints. We compare various models of behavior generation in order to describe the observed human performance. Finally we speculate on mechanisms how chaotic neurodynamics can contribute to the generation of flexible human behaviors under constraints.     

The EEG spatial pattern and psychophysiological characteristics of divergent and convergent thinking in humans

The psychophysiological parameters of the spatial synchronization of bioelectric potentials during the nonverbal divergent, nonverbal convergent, verbal divergent and verbal convergent thinking have been analyzed. The relationships between the performances of tests for these thinking styles were different. The strongest significant correlation has been found between the productivities of the verbal divergent and verbal convergent thinking styles; the weakest correlation, between those of the nonverbal divergent and nonverbal convergent thinking styles. The thinking styles differ from one another in the topography of spatial synchronization of bioelectric potentials. They are the most pronounced during the two nonverbal tasks and the least pronounced during the two verbal tasks. The thinking styles also differ from one another in the degree of the enhancement of the coherence between bioelectric potentials during tasks compared to the baseline (with the eyes open). Some human psychophysiological characteristics facilitating the performance of divergent (creative) tasks have a negative effect on the performance of convergent (noncreative) tasks. The data are discussed in terms of the differences in the level of general activation and involvement of different types of information processing (simultaneous and successive).     

The role of primary motor cortex in goal-directed movements: insights from neurophysiological studies on non-human primates

Neurophysiological studies on non-human primates have provided a large body of information on the response patterns of neurons in primary motor cortex during volitional motor tasks. Rather than finding a single simple pattern of activity in primary motor cortex neurons, these studies illustrate that neural activity in this area reflects many different types of information, including spatial goals, hand motion, joint motion, force output and electromyographic activity. This richness in the response characteristics of neurons makes estimates of any single variable on motor performance from population signals imprecise and prone to errors. It initially seems puzzling that so many different types of information are represented in primary motor cortex. However, such richness in neural responses reflects its important role in converting high-level behavioral goals generated in other cortical regions into complex spatiotemporal patterns to control not only alpha-motoneuron activity but also other features of spinal processing.     

不同注意任务类型及难度对猕猴微眼动的影响

微眼动是视觉注视过程中幅度最大、速度最快的眼动,可以消除由于神经系统适应性而产生的视觉衰退现象,在视觉信息处理过程中发挥着重要作用.基于微眼动与视觉感知功能的相关性,设计实验研究猕猴完成显性、隐性注意任务以及不同难度显性注意任务时,视觉注视情况下微眼动的差异.通过对不同难度显性注意任务下微眼动的参数进行比较,发现随着任务难度的增加,微眼动的幅度、速率和频率都被抑制.另一方面,对比不同类型的视觉感知任务(显性注意和隐性注意),发现在相似的实验范式下,隐性注意对微眼动的频率有明显的抑制作用,但幅度和频率没有得到一致的结果,这表明视觉注意任务类型的不同或将导致猕猴完成任务的策略不同.这些工作将为今后进一步研究微眼动产生的神经机制以及视觉注意过程中眼动的作用机制奠定良好的基础.     

Multiple imputation methods for handling incomplete longitudinal and clustered data where the target analysis is a linear mixed effects model

Multiple imputation (MI) is increasingly popular for handling multivariate missing data. Two general approaches are available in standard computer packages: MI based on the posterior distribution of incomplete variables under a multivariate (joint) model, and fully conditional specification (FCS), which imputes missing values using univariate conditional distributions for each incomplete variable given all the others, cycling iteratively through the univariate imputation models. In the context of longitudinal or clustered data, it is not clear whether these approaches result in consistent estimates of regression coefficient and variance component parameters when the analysis model of interest is a linear mixed effects model (LMM) that includes both random intercepts and slopes with either covariates or both covariates and outcome contain missing information. In the current paper, we compared the performance of seven different MI methods for handling missing values in longitudinal and clustered data in the context of fitting LMMs with both random intercepts and slopes. We study the theoretical compatibility between specific imputation models fitted under each of these approaches and the LMM, and also conduct simulation studies in both the longitudinal and clustered data settings. Simulations were motivated by analyses of the association between body mass index (BMI) and quality of life (QoL) in the Longitudinal Study of Australian Children (LSAC). Our findings showed that the relative performance of MI methods vary according to whether the incomplete covariate has fixed or random effects and whether there is missingnesss in the outcome variable. We showed that compatible imputation and analysis models resulted in consistent estimation of both regression parameters and variance components via simulation. We illustrate our findings with the analysis of LSAC data.     

Assessing the Response of Seasonal Variation of Net Primary Productivity to Climate Using Remote Sensing Data and Geographic Information System Techniques in Xinjiang

Net pdmary productivity (NPP) is a key component of energy and matter transformation in the terrestrial ecosystem, and the responses of NPP to global change locally and regionally have been one of the most important aspects in climate-vegetation relationship studies. In order to isolate causal climatic factors, it is very important to assess the response of seasonal variation of NPP to climate. In this paper, NPP in Xinjiang was estimated by NOAA/AVHRR Normalized Difference Vegetation Index (NDVI) data and geographic information system (GIS) techniques. The impact of climatic factors (air temperature, precipitation and sunshine percentage) on seasonal variations of NPP was studied by time lag and serial correlation ageing analysis. The results showed that the NPP for different land cover types have a similar correlation with any one of the three climatic factors, and precipitation is the major climatic factor influencing the seasonal variation of NPP in Xinjiang. It was found that the positive correlation at 0 lag appeared between NPP and precipitation and the serial correlation ageing was 0 d in most areas of Xinjiang, which indicated that the response of NPP to precipitation was immediate. However, NPP of different land cover types showed significant positive correlation at 2 month lag with air temperature, and the impact of which could persist 1 month as a whole. No correlation was found between NPP and sunshine percentage.     

基于叶片尺度观测数据的气孔导度模型评价

气孔导度(g)是控制冠层与大气之间能量和水分交换的重要因素。空气湿度是控制植物叶片气孔导度的一个关键环境因子。在过去的十几年中,普遍得到应用的是Ball-Woodrow-Berry(BWB)模型和Leuning模型中气孔导度与湿度的关系。本研究使用一个诊断变量f(H),基于农田叶片水平的光合-气孔导度观测数据,对BWB模型、Leuning模型以及新发展的power-h模型和power-D模型进行了气孔导度模拟效果的比较和评价。结果表明:BWB模型描述的是g和相对湿度(hs)之间的一种线性关系,当空气较为湿润时,模拟结果存在较大的低估;Leuning模型中反映的是g与饱和水汽压差(Ds)的非线性函数,降低了模拟结果的误差,但仍然不能很好地描述g在较湿状况下的显著升高;相比之下,两个新的模型,即Ds的指数函数和(1-hs)的指数函数形式模型能提高模拟结果的精度。这个研究结果也表明基于Ds的模型模拟效果要好于基于hs的模型。     

Selecting predictors for discriminant analysis of species performance: an example from an amphibious softwater plant

Selecting an appropriate variable subset in linear multivariate methods is an important methodological issue for ecologists. Interest often exists in obtaining general predictive capacity or in finding causal inferences from predictor variables. Because of a lack of solid knowledge on a studied phenomenon, scientists explore predictor variables in order to find the most meaningful (i.e. discriminating) ones. As an example, we modelled the response of the amphibious softwater plant Eleocharis multicaulis using canonical discriminant function analysis. We asked how variables can be selected through comparison of several methods: univariate Pearson chi-square screening, principal components analysis (PCA) and step-wise analysis, as well as combinations of some methods. We expected PCA to perform best. The selected methods were evaluated through fit and stability of the resulting discriminant functions and through correlations between these functions and the predictor variables. The chi-square subset, at P < 0.05, followed by a step-wise sub-selection, gave the best results. In contrast to expectations, PCA performed poorly, as so did step-wise analysis. The different chi-square subset methods all yielded ecologically meaningful variables, while probable noise variables were also selected by PCA and step-wise analysis. We advise against the simple use of PCA or step-wise discriminant analysis to obtain an ecologically meaningful variable subset; the former because it does not take into account the response variable, the latter because noise variables are likely to be selected. We suggest that univariate screening techniques are a worthwhile alternative for variable selection in ecology.     

Assessment of reliability of microarray data and estimation of signal thresholds using mixture modeling

DNA microarray is an important tool for the study of gene activities but the resultant data consisting of thousands of points are error-prone. A serious limitation in microarray analysis is the unreliability of the data generated from low signal intensities. Such data may produce erroneous gene expression ratios and cause unnecessary validation or post-analysis follow-up tasks. In this study, we describe an approach based on normal mixture modeling for determining optimal signal intensity thresholds to identify reliable measurements of the microarray elements and subsequently eliminate false expression ratios. We used univariate and bivariate mixture modeling to segregate the microarray data into two classes, low signal intensity and reliable signal intensity populations, and applied Bayesian decision theory to find the optimal signal thresholds. The bivariate analysis approach was found to be more accurate than the univariate approach; both approaches were superior to a conventional method when validated against a reference set of biological data that consisted of true and false gene expression data. Elimination of unreliable signal intensities in microarray data should contribute to the quality of microarray data including reproducibility and reliability of gene expression ratios.     

Evaluation of normalization and pre-clustering issues in a novel clustering approach: global optimum search with enhanced positioning

We study the effects on clustering quality by different normalization and pre-clustering techniques for a novel mixed-integer nonlinear optimization-based clustering algorithm, the Global Optimum Search with Enhanced Positioning (EP_GOS_Clust). These are important issues to be addressed. DNA microarray experiments are informative tools to elucidate gene regulatory networks. But in order for gene expression levels to be comparable across microarrays, normalization procedures have to be properly undertaken. The aim of pre-clustering is to use an adequate amount of discriminatory characteristics to form rough information profiles, so that data with similar features can be pre-grouped together and outliers deemed insignificant to the clustering process can be removed. Using experimental DNA microarray data from the yeast Saccharomyces Cerevisiae, we study the merits of pre-clustering genes based on distance/correlation comparisons and symbolic representations such as {+, o, -}. As a performance metric, we look at the intra- and inter-cluster error sums, two generic but intuitive measures of clustering quality. We also use publicly available Gene Ontology resources to assess the clusters' level of biological coherence. Our analysis indicates a significant effect by normalization and pre-clustering methods on the clustering results. Hence, the outcome of this study has significance in fine-tuning the EP_GOS_Clust clustering approach.     

Writing in the Air: Contributions of Finger Movement to Cognitive Processing

The present study investigated the interactions between motor action and cognitive processing with particular reference to kanji-culture individuals. Kanji-culture individuals often move their finger as if they are writing when they are solving cognitive tasks, for example, when they try to recall the spelling of English words. This behavior is called kusho, meaning air-writing in Japanese. However, its functional role is still unknown. To reveal the role of kusho behavior in cognitive processing, we conducted a series of experiments, employing two different cognitive tasks, a construction task and a stroke count task. To distinguish the effects of the kinetic aspects of kusho behavior, we set three hand conditions in the tasks; participants were instructed to use either kusho, unrelated finger movements or do nothing during the response time. To isolate possible visual effects, two visual conditions in which participants saw their hand and the other in which they did not, were introduced. We used the number of correct responses and response time as measures of the task performance. The results showed that kusho behavior has different functional roles in the two types of cognitive tasks. In the construction task, the visual feedback from finger movement facilitated identifying a character, whereas the kinetic feedback or motor commands for the behavior did not help to solve the task. In the stroke count task, by contrast, the kinetic aspects of the finger movements influenced counting performance depending on the type of the finger movement. Regardless of the visual condition, kusho behavior improved task performance and unrelated finger movements degraded it. These results indicated that motor behavior contributes to cognitive processes. We discussed possible mechanisms of the modality dependent contribution. These findings might lead to better understanding of the complex interaction between action and cognition in daily life.     

Cranial capacity and performance on delay-response task correlated with principal sulcus length in monkeys

During the process of evolution, a selective advantage may have been gained by organisms that had the ability to utilize mentally stored information of a stimulus rather than the stimulus itself. The ability to temporarily store and mentally operate on stimulus information is often termed “working memory.” Within the neocortex of primates, the functional anatomic subdivision surrounding the principal (rectus) sulcus plays an important role in modulating the performance of delay-response tasks in monkeys (representing working memory). However, it appears that no study has investigated the direct relationship between the length of the principal sulcus and performance on a delay-response task. Therefore, this paper investigates the relationships between principal sulcus length and performance on delay-response tasks. However, to control for the effect of overall brain size on this relationship, cranial capacity is analyzed with both principal sulcus length and delay-response performance. Results support a consistent and significant correlation between principal sulcus length and performance on delayed-response tasks in a variety of Old World and New World monkeys. Principal sulcus length is also significantly correlated with cranial capacity; however, cranial capacity is not significantly correlated with performance on delayed-response tasks. The results of this investigation provide a method for analyzing cranial capacity and working-memory abilities in select primates based on principal sulcus length, and may prove useful for interpreting endocasts in the primate fossil record. Am J Phys Anthropol 109:33–40. © 1999 Wiley-Liss, Inc.     

GALGO: an R package for multivariate variable selection using genetic algorithms

SUMMARY: The development of statistical models linking the molecular state of a cell to its physiology is one of the most important tasks in the analysis of Functional Genomics data. Because of the large number of variables measured a comprehensive evaluation of variable subsets cannot be performed with available computational resources. It follows that an efficient variable selection strategy is required. However, although software packages for performing univariate variable selection are available, a comprehensive software environment to develop and evaluate multivariate statistical models using a multivariate variable selection strategy is still needed. In order to address this issue, we developed GALGO, an R package based on a genetic algorithm variable selection strategy, primarily designed to develop statistical models from large-scale datasets.     

Effects of restoration treatments on the diaspore bank under dense Pteridium stands in the UK

Abstract. The diaspore bank (seeds of higher plants and spores of ferns and bryophytes) was assessed between 3 and 5 yr after experiments to control Pteridium aquilinum (bracken) and restore appropriate vegetation were initiated at two contrasting locations in the UK. We tested the response of the diaspore bank using univariate and multivariate analysis of variance. The two approaches were complementary and together improved the interpretation of these results. There were considerable differences in the diaspore banks of the two sites and among the experimental locations within sites. Within each experiment there were differences in species composition, with species that were (1) common to both diaspore bank and vegetation, (2) restricted to the diaspore bank and (3) restricted to the vegetation. There is a possibility of increasing the biodiversity of the developing vegetation if some of the species present in the diaspore bank can be germinated. This was especially true for ferns where four species were found in the spore bank which were not present in the vegetation. There were few significant effects of management treatment on the diaspore bank as the experiments had been in progress for only 3 to 5 yr, but a few species had different densities in the different treatments (Betula pubescens, Juncus effusus and some bryophytes). The greatest correlation between vegetation and diaspore bank was found at the top hierarchical level (entire dataset) and this progressively reduced with scale. We interpret this as a landscape/species pool effect: as the scale of the study reduces the correlation between diaspore bank and vegetation also reduces, at least over the time scale of our study. The relevance of these results for restoration ecology is discussed briefly.     

Incorporating Surrogate Endpoints into Group Sequential Trials

Recent developments proposed by Lin (1991) which allow for the sequential analysis of multivariate failure time data, are discussed in the context of clinical trials with marker process data. In particular, a marker based response observed as a univariate failure time variable is considered in a univariate manner and in combination with the primary failure time variable through global measures of treatment effect. A weighting scheme is introduced that is designed to make greater use of the marker process responses when they are consistent with the responses for the primary endpoint. Univariate analyses and analyses based on global test statistics are evaluated with respect to duration of study and type I and type II error rates for a variety of relative risk parameter configurations. The simulation study is designed to extend the work of Machado, Gail and Ellenberg (1990) to sequential trials and to assess the performance of the global test statistics in this context. The global measures are found to be preferable over the univariate primary endpoint analyses when the treatment affects all transition intensities in a consistent manner. Further, there are advantages over the univariate marker based analysis when the treatment effects on some transition intensities are in opposite directions. Such a scenario remains problematic however with the relative error rates determined to a large extent by the baseline weighting scheme.