Telling time from fossils: a phylogeny-based approach to chronological ordering of paleobiotas

The potential for using fossils for temporal ordering of sedimentary rocks is as old as historical geology itself. In spite of this, however, most current biostratigraphic and biochronologic techniques do not make use of phylogenetic information, but rely instead on some measure of species' presence or absence or their turnover in the fossil record. A common phylogenetic approach to biochronology has been to use “stage of evolution” arguments, whereas more rigorous, cladogram‐based methods have been proposed but have seen little use. Cladistic biochronologic analysis (CBA) is developed here as a new method for determining biochronologic order between paleobiotas based on the phylogenetic relationships of their constituent taxa. CBA is adapted from Brooks' parsimony analysis, and analyzes syntaxon information from clades that transcend a number of paleobiotas to determine relative temporal order among these paleobiotas. Because CBA is based on phylogenetic information, it is suited to problems where a good fossil record is available, but where stratigraphic or chronologic relationships are poorly constrained, such as the terrestrial vertebrate record. A practical example, based on the Cenozoic fossil record of North America, pits CBA against a test case in which the correct temporal order of biotas is known beforehand. The method successfully recovers correct temporal order between paleobiotas with reasonable levels of support, and is also shown to outperform a previously proposed cladistic biochronologic method. In a second example, CBA is used to achieve the first empirical temporal ordination for several Late Cretaceous localities in the Gobi Desert that produce fossils crucial to the understanding of modern amniote clades, but which have poorly resolved temporal relationships. CBA is sensitive to large amounts of extinction and poor sampling of the fossil record, but problems such as gaps in the fossil record (Lazarus taxa) can be dealt with efficiently through a number of a priori and a posteriori scoring techniques. CBA offers a novel approach for biochronologic analysis that is independent of, but complementary to and readily combinable with other chronologic/stratigraphic methods. © The Willi Hennig Society 2007.     

Uncertainty in the age of fossils and the stratigraphic fit to phylogenies

The ages of first appearance of fossil taxa in the stratigraphic record are inherently associated to an interval of error or uncertainty, rather than being precise point estimates. Contrasting this temporal information with topologies of phylogenetic relationships is relevant to many aspects of evolutionary studies. Several indices have been proposed to compare the ages of first appearance of fossil taxa and phylogenies. For computing most of these indices, the ages of first appearance of fossil taxa are currently used as point estimates, ignoring their associated errors or uncertainties. The effect of age uncertainty on measures of stratigraphic fit to phylogenies is explored here for two indices based on the extension of ghost lineages (MSM* and GER). A solution based on randomization of the ages of terminal taxa is implemented, resulting in a range of possible values for measures of stratigraphic fit to phylogenies, rather than in a precise but arbitrary stratigraphic fit value. Sample cases show that ignoring the age uncertainty of fossil taxa can produce misleading results when comparing the stratigraphic fit of competing phylogenetic hypotheses. Empirical test cases of alternative phylogenies of two dinosaur groups are analyzed through the randomization procedure proposed here.     

Harnessing stratigraphic bias at the section scale: conodont diversity in the Homerian (Silurian) of the Midland Platform,England

Fossil abundance and diversity in geological successions are subject to bias arising from shifting depositional and diagenetic environments, resulting in variable rates of fossil accumulation and preservation. In simulations, this bias can be constrained based on sequence‐stratigraphic architecture. Nonetheless, a practical quantitative method of incorporating the contribution of sequence‐stratigraphic architecture in community palaeoecology and diversity analyses derived from individual successions is missing. As a model of faunal turnover affected by the stratigraphic bias, we use the ‘Mulde event’, a postulated mid‐Silurian interval of elevated conodont turnover, which coincides with global eustatic sea‐level changes and which has been based on regionally constrained observations. We test whether conodont turnover is highest at the boundary corresponding to the ‘event’ and post‐‘event’ interval against the alternative that conodont turnover reflects habitat tracking and peaks at facies shifts. Based on the previously documented, parasequence‐level stratigraphic framework of sections in the northern and central part of the Midland Platform, the relative controls of sequence‐stratigraphic architecture, time and depositional environment over conodont distribution are evaluated using permutational multivariate analysis of variance. The depositional environment controls the largest part of variability in conodont assemblage composition, whereas the postulated ‘Mulde event’, or genuine temporal change in conodont diversity, cannot be detected. Depending on the binning of the stratigraphic succession, contrasting diversity and turnover patterns can be produced. The simple approach proposed here, emulating partitioning of β diversity into spatial and temporal components, may help to constrain the stratigraphic bias, even at the scale of an individual section.     

Predicting the intelligibility of reverberant speech for cochlear implant listeners with a non-intrusive intelligibility measure

Reverberation is known to reduce the temporal envelope modulations present in the signal and affect the shape of the modulation spectrum. A non-intrusive intelligibility measure for reverberant speech is proposed motivated by the fact that the area of the modulation spectrum decreases with increasing reverberation. The proposed measure is based on the average modulation area computed across four acoustic frequency bands spanning the signal bandwidth. High correlations (r = 0.98) were observed with sentence intelligibility scores obtained by cochlear implant listeners. Proposed measure outperformed other measures including an intrusive speech-transmission index based measure.     

Conditional entropy approach for the evaluation of the coupling strength

A method that enables measurement of the degree of coupling between two signals is presented. The method is based on the definition of an uncoupling function calculating, by means of entropy rates, the minimum amount of independent information (i.e. the information carried by one signal which cannot be derived from the other). An estimator of the uncoupling function able to deal with short segments of data (a few hundred samples) is proposed, thus enabling the method to be used for usual experimental recordings. A synchronisation index is derived from the estimate of the uncoupling function by means of a minimisation procedure. It quantifies the maximum amount of information exchanged between the two signals. Simulations in which non-linear coordination schemes are produced and changes in the coupling strength are artificially induced are used to check the ability of the proposed index to measure the degree of synchronisation between signals. The synchronisation analysis is utilised to measure the coupling strength between the beat-to-beat variability of the sympathetic discharge and ventilation in decerebrate artificially ventilated cats and the degree of synchronisation between the beat-to-beat variability of the heart period and ventricular repolarisation interval in normal subjects and myocardial infarction patients. The sympathetic discharge and ventilation are strongly coupled and the coupling strength is not affected by manoeuvres capable of increasing or depressing sympathetic activity. The synchronisation is lost after spinalisation. The synchronisation analysis confirms that the heart period and ventricular repolarisation interval are well coordinated. In normal subjects, the synchronisation index is not modified by experimental conditions inducing changes in the sympathovagal balance. On the contrary, it strongly decreases after myocardial infarction, thus detecting and measuring the uncoupling between the heart period and ventricular repolarisation interval. Received: 29 October 1998 / Received in revised form: 4 March 1999     

A method for the estimation of functional brain connectivity from time-series data

A central issue in cognitive neuroscience is which cortical areas are involved in managing information processing in a cognitive task and to understand their temporal interactions. Since the transfer of information in the form of electrical activity from one cortical region will in turn evoke electrical activity in other regions, the analysis of temporal synchronization provides a tool to understand neuronal information processing between cortical regions. We adopt a method for revealing time-dependent functional connectivity. We apply statistical analyses of phases to recover the information flow and the functional connectivity between cortical regions for high temporal resolution data. We further develop an evaluation method for these techniques based on two kinds of model networks. These networks consist of coupled Rössler attractors or of coupled stochastic Ornstein–Uhlenbeck systems. The implemented time-dependent coupling includes uni- and bi-directional connectivities as well as time delayed feedback. The synchronization dynamics of these networks are analyzed using the mean phase coherence, based on averaging over phase-differences, and the general synchronization index. The latter is based on the Shannon entropy. The combination of these with a parametric time delay forms the basis of a connectivity pattern, which includes the temporal and time lagged dynamics of the synchronization between two sources. We model and discuss potential artifacts. We find that the general phase measures are remarkably stable. They produce highly comparable results for stochastic and periodic systems. Moreover, the methods proves useful for identifying brief periods of phase coupling and delays. Therefore, we propose that the method is useful as a basis for generating potential functional connective models.     

A measure of sexual dimorphism in populations which are univariate normal mixtures

Measures of sexual dimorphism have been used extensively to predict the social organization and ecology of animal and human populations. There is, however, no universally accepted measure of phenotypic differences between the sexes. Most indices of sexual dimorphism fail to incorporate all of the information contained in a random data set. In an attempt to have a better alternative, an index is proposed to measure sexual dimorphism in populations that are distributed according to a probabilistic mixture model with two normal components. The index calculates the overlap between two functions that represent the contribution of each sex in the mixture. In order to assess such an index, sample means, variances and sizes of each sex are needed. As a consequence, the sample information used is greater than that used by other indices that take intrasexual variability into account. By evaluating some examples, our proposed index appears to be a more realistic measure of sexual dimorphism than other measures currently used.     

Measuring beta‐diversity from taxonomic similarity

Question: The utility of beta (β‐) diversity measures that incorporate information about the degree of taxonomic (dis)similarity between species plots is becoming increasingly recognized. In this framework, the question for this study is: can we define an ecologically meaningful index of β‐diversity that, besides indicating simple species turnover, is able to account for taxonomic similarity amongst species in plots? Methods: First, the properties of existing measures of taxonomic similarity measures are briefly reviewed. Next, a new measure of plot‐to‐plot taxonomic similarity is presented that is based on the maximal common subgraph of two taxonomic trees. The proposed measure is computed from species presences and absences and include information about the degree of higher‐level taxonomic similarity between species plots. The performance of the proposed measure with respect to existing coefficients of taxonomic similarity and the coefficient of Jaccard is discussed using a small data set of heath plant communities. Finally, a method to quantify β‐diversity from taxonomic dissimilarities is discussed. Results: The proposed measure of taxonomic β‐diversity incorporates not only species richness, but also information about the degree of higher‐order taxonomic structure between species plots. In this view, it comes closer to a modern notion of biological diversity than more traditional measures of β‐di‐versity. From regression analysis between the new coefficient and existing measures of taxonomic similarity it is shown that there is an evident nonlinearity between the coefficients. This nonlinearity demonstrates that the new coefficient measures similarity in a conceptually different way from previous indices. Also, in good agreement with the findings of previous authors, the regression between the new index and the Jaccard coefficient of similarity shows that more than 80% of the variance of the former is explained by the community structure at the species level, while only the residual variance is explained by differences in the higher‐order taxonomic structure of the species plots. This means that a genuine taxonomic approach to the quantification of plot‐to‐plot similarity is only needed if we are interested in the residual system's variation that is related to the higher‐order taxonomic structure of a pair of species plots.     

定量地层对比常用方法的比较和适用性分析

定量地层学以生物地层学原理为核心,将地层学信息定量化,运用数学模型进行地层对比,作为传统地层学对比的重要补充。传统的生物地层学根据经验选取标准化石来建立生物地层序列,但同时也丢失了大量的化石信息。定量地层学则能够利用所有的化石信息,在传统生物地层学的基础上得到更高分辨率的地层对比结果。现阶段定量地层对比常用的方法主要有图形对比法、约束最优化法和单元组合法三种,但对于这三种方法各自适应的数据情况方面,目前成果较少。本文对这三种方法的原理进行了简要的介绍和分析,并建立数据模型,从标准化石的可对比性、数据集的物种总数、剖面间共有物种和单延限分子的比例四个方面对三种方法的适用条件进行了讨论。其中图形对比法更适用于单延限分子较少、标准化石可对比性强的数据集。单元组合法对数据集中物种间相互关系的复杂程度较为敏感,共有物种较多的数据集有更好的对比结果,但数据集中物种总数的增加会对其产生一定的负面影响,需要依靠进一步的人工调整。约束最优化法则对数据集各方面的优化均有响应,对物种总数较大的数据集有较好的对比结果,且剖面间共有物种占比越大,对比结果越理想。     

Temporal coding in vision: coding by the spike arrival times leads to oscillations in the case of moving targets

The ‘oscillations’ which have been observed in the visual cortex of cats and monkeys in the case of moving targets are discussed in relation to a temporal coding based on the arrival times of spikes or bursts. A decoding process for this temporal coding is proposed in which neurons work in a correlator mode. In the case of motion analysis, periodic resetting is needed to avoid information jamming. This resetting is proposed to be responsible for the ‘oscillations’. Good initial synchronization is required for the decoding process to be performed efficiently. A diffusive process based on interdendritic ionic currents is proposed and shown to operate efficiently, without any loss of spatial and temporal resolving powers. Received: 2 June 1994 / Accepted in revised form: 23 January 1996     

A parametric diversity measure combining the relative abundances and taxonomic distinctiveness of species

Most ecological diversity indices summarize the information about the relative abundances of species without reflecting taxonomic differences between species. Nevertheless, in environmental conservation practice, data on species abundances are mostly irrelevant and generally unknown. In such cases, to summarize the conservation value of a given site, so‐called ‘taxonomic diversity’ measures can be used. Such measures are based on taxonomic relations among species and ignore species relative abundances. In this paper, bridging the gap between traditional biodiversity measures and taxonomic diversity measures, I introduce a parametric diversity index that combines species relative abundances with their taxonomic distinctiveness. Due to the parametric nature of the proposed index, the contribution of rare and abundant species to each diversity measure is explicit.     

Spectral analysis of a Plio-Pleistocene multispecies time series using the Mantel periodogram

A simple method for the spectral analysis of multispecies microfossil data through time or stratigraphic level is presented. The method is based on the Mantel correlogram, allowing any ecological similarity measure to be used. The method can therefore be applied to binary (presence-absence) data as well as raw or normalized species counts. In contrast with spectral analysis of univariate ordination scores, this approach does not explicitly discard information. The method, referred to as the Mantel periodogram, is exemplified with a data set from the literature, demonstrating several astronomically forced periodicities in microfaunal data from the Plio-Pleistocene.     

A multilocus linkage disequilibrium measure based on mutual information theory and its applications

Evaluating the patterns of linkage disequilibrium (LD) is important for association mapping study as well as for studying the genomic architecture of human genome (e.g., haplotype block structures). Commonly used bi-allelic pairwise measures for assessing LD between two loci, such as r ² and D′, may not make full and efficient use of modern multilocus data. Though extended to multilocus scenarios, their performance is still questionable. Meanwhile, most existing measures for an entire multilocus region, such as normalized entropy difference, do not consider existence of LD heterogeneity across the region under investigation. Additionally, these existing multilocus measures cannot handle distant regions where long-range LD patterns may exist. In this study, we proposed a novel multilocus LD measure developed based on mutual information theory. Our proposed measure described LD pattern between two chromosome regions each of which may consist of multiple loci (including multi-allele loci). As such, the proposed measure can better characterize LD patterns between two arbitrary regions. As potential applications, we developed algorithms on the proposed measure for partitioning haplotype blocks and for selecting haplotype tagging SNPs (htSNPs), which were helpful for follow-up association tests. The results on both simulated and empirical data showed that our LD measure had distinct advantages over pairwise and other multilocus measures. First, our measure was more robust, and can capture comprehensively the LD information between neighboring as well as disjointed regions. Second, haplotype blocks were better described via our proposed measure. Furthermore, association tests with htSNPs from the proposed algorithm had improved power over tests on single markers and on haplotypes.     

Temporally and Spatially Constrained ICA of fMRI Data Analysis

Constrained independent component analysis (CICA) is capable of eliminating the order ambiguity that is found in the standard ICA and extracting the desired independent components by incorporating prior information into the ICA contrast function. However, the current CICA method produces constraints that are based on only one type of prior information (temporal/spatial), which may increase the dependency of CICA on the accuracy of the prior information. To improve the robustness of CICA and to reduce the impact of the accuracy of prior information on CICA, we proposed a temporally and spatially constrained ICA (TSCICA) method that incorporated two types of prior information, both temporal and spatial, as constraints in the ICA. The proposed approach was tested using simulated fMRI data and was applied to a real fMRI experiment using 13 subjects who performed a movement task. Additionally, the performance of TSCICA was compared with the ICA method, the temporally CICA (TCICA) method and the spatially CICA (SCICA) method. The results from the simulation and from the real fMRI data demonstrated that TSCICA outperformed TCICA, SCICA and ICA in terms of robustness to noise. Moreover, the TSCICA method displayed better robustness to prior temporal/spatial information than the TCICA/SCICA method.     

A model cortical circuit for the storage of temporal sequences

Despite the fact that temporal information processing is of particular significance in biological memory systems, not much has yet been explored about how these systems manage to store temporal information involved in sequences of stimuli. A neural network model capable of learning and recalling temporal sequences is proposed, based on a neural mechanism in which the sequences are expanded into a series of periodic rectangular oscillations. Thus, the mathematical framework underlying the model, to some extent, is concerned with the Walsh function series. The oscillatory activities generated by the interplay between excitatory and inhibitory neuron pools are transmitted to another neuron pool whose role in learning and retrieval is to modify the rhythms and phases of the rectangular oscillations. Thus, a basic functional neural circuit involves three different neuron pools. The modifiability of rhythms and phases is incorporated into the model with the aim of improving the quality of the retrieval. Numerical simulations were conducted to show the characteristic features of the learning as well as the performance of the model in memory recall.     

Maximum decoding abilities of temporal patterns and synchronized firings: application to auditory neurons responding to click trains and amplitude modulated white noise

Simultaneous recordings of an increasing number of neurons have recently become available, but few methods have been proposed to handle this activity. Here, we extract and investigate all the possible temporal neural activity patterns based on synchronized firings of neurons recorded on multiple electrodes, or based on bursts of single-electrode activity in cat primary auditory cortex. We apply this to responses to periodic click trains or sinusoïdal amplitude modulated noise by obtaining for each pattern its temporal modulation transfer function. An algorithm that maximizes the mutual information between all patterns and stimuli subsequently leads to the identification of patterns that optimally decode modulation frequency (MF). We show that stimulus information contained in multi-electrode synchronized firing is not redundant with single-electrode firings and leads to improved efficiency of MF decoding. We also show that the combined use of firing rate and temporal codes leads to a better discrimination of the MF.     

A biologically inspired measure for coexpression analysis

Two genes are said to be coexpressed if their expression levels have a similar spatial or temporal pattern. Ever since the profiling of gene microarrays has been in progress, computational modeling of coexpression has acquired a major focus. As a result, several similarity/distance measures have evolved over time to quantify coexpression similarity/dissimilarity between gene pairs. Of these, correlation coefficient has been established to be a suitable quantifier of pairwise coexpression. In general, correlation coefficient is good for symbolizing linear dependence, but not for nonlinear dependence. In spite of this drawback, it outperforms many other existing measures in modeling the dependency in biological data. In this paper, for the first time, we point out a significant weakness of the existing similarity/distance measures, including the standard correlation coefficient, in modeling pairwise coexpression of genes. A novel measure, called BioSim, which assumes values between -1 and +1 corresponding to negative and positive dependency and 0 for independency, is introduced. The computation of BioSim is based on the aggregation of stepwise relative angular deviation of the expression vectors considered. The proposed measure is analytically suitable for modeling coexpression as it accounts for the features of expression similarity, expression deviation and also the relative dependence. It is demonstrated how the proposed measure is better able to capture the degree of coexpression between a pair of genes as compared to several other existing ones. The efficacy of the measure is statistically analyzed by integrating it with several module-finding algorithms based on coexpression values and then applying it on synthetic and biological data. The annotation results of the coexpressed genes as obtained from gene ontology establish the significance of the introduced measure. By further extending the BioSim measure, it has been shown that one can effectively identify the variability in the expression patterns over multiple phenotypes. We have also extended BioSim to figure out pairwise differential expression pattern and coexpression dynamics. The significance of these studies is shown based on the analysis over several real-life data sets. The computation of the measure by focusing on stepwise time points also makes it effective to identify partially coexpressed genes. On the whole, we put forward a complete framework for coexpression analysis based on the BioSim measure.     

Neuronal spike train analysis in likelihood space

Background

Conventional methods for spike train analysis are predominantly based on the rate function. Additionally, many experiments have utilized a temporal coding mechanism. Several techniques have been used for analyzing these two sources of information separately, but using both sources in a single framework remains a challenging problem. Here, an innovative technique is proposed for spike train analysis that considers both rate and temporal information.

Methodology/Principal Findings

Point process modeling approach is used to estimate the stimulus conditional distribution, based on observation of repeated trials. The extended Kalman filter is applied for estimation of the parameters in a parametric model. The marked point process strategy is used in order to extend this model from a single neuron to an entire neuronal population. Each spike train is transformed into a binary vector and then projected from the observation space onto the likelihood space. This projection generates a newly structured space that integrates temporal and rate information, thus improving performance of distribution-based classifiers. In this space, the stimulus-specific information is used as a distance metric between two stimuli. To illustrate the advantages of the proposed technique, spiking activity of inferior temporal cortex neurons in the macaque monkey are analyzed in both the observation and likelihood spaces. Based on goodness-of-fit, performance of the estimation method is demonstrated and the results are subsequently compared with the firing rate-based framework.

Conclusions/Significance

From both rate and temporal information integration and improvement in the neural discrimination of stimuli, it may be concluded that the likelihood space generates a more accurate representation of stimulus space. Further, an understanding of the neuronal mechanism devoted to visual object categorization may be addressed in this framework as well.     

Phylogenetic indices for measuring the diet breadths of phytophagous insects

Prevailing methods of measuring diet breadth of phytophagous insects are not consistent between studies and generally rely on counts of a variety of higher plant taxa (e.g. genera, families, orders). Results derived from them can be inconsistent if different taxonomic levels are used between studies. In any case, such indices do not include information from the whole branching structure of the host plant phylogeny, and do not address the fact that higher taxa are not necessarily phylogenetically equivalent. Here we present novel phylogeny-based methods which address these shortcomings. Although a previously proposed index (the Phylogenetic Diversity index) may be employed, it cannot be used to measure diets of strictly monophagous insects (i.e. those which utilise a single host species). We therefore introduce a modification of this index (the Root Phylogenetic Diversity index) which may be applied to all diets. In addition, we propose a Clade Dispersion index as a branch-length-independent measure of the degree to which hosts are scattered across the host phylogeny. We describe how these indices could be employed in studies of insect diet breadth and discuss potential problems which may be encountered in their use. Received: 16 November 1998 / Accepted: 10 February 1999