We present the results of two exploratory parsimony analyses of DNA sequences from 475 and 499 species of seed plants, respectively, representing all major taxonomic groups. The data are exclusively from the chloroplast gene rbcL, which codes for the large subunit of ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO or RuBPCase). We used two different state-transformation assumptions resulting in two sets of cladograms: (i) equal-weighting for the 499-taxon analysis; and (ii) a procedure that differentially weights transversions over transitions within characters and codon positions among characters for the 475-taxon analysis. The degree of congruence between these results and other molecular, as well as morphological, cladistic studies indicates that rbcL sequence variation contains historical evidence appropriate for phylogenetic analysis at this taxonomic level of sampling. Because the topologies presented are necessarily approximate and cannot be evaluated adequately for internal support, these results should be assessed from the perspective of their predictive value and used to direct future studies, both molecular and morphological. In both analyses, the three genera of Gnetales are placed together as the sister group of the flowering plants, and the anomalous aquatic Ceratophyllum (Ceratophyllaceae) is sister to all other flowering plants. Several major lineages identified correspond well with at least some recent taxonomic schemes for angiosperms, particularly those of Dahlgren and Thorne. The basalmost clades within the angiosperms are orders of the apparently polyphyletic subclass Magnoliidae sensu Cronquist. The most conspicuous feature of the topology is that the major division is not monocot versus dicot, but rather one correlated with general pollen type: uniaperturate versus triaperturate. The Dilleniidae and Hamamelidae are the only subclasses that are grossly polyphyletic; an examination of the latter is presented as an example of the use of these broad analyses to focus more restricted studies. A broadly circumscribed Rosidae is paraphyletic to Asteridae and Dilleniidae. Subclass Caryophyllidae is monophyletic and derived from within Rosidae in the 475-taxon analysis but is sister to a group composed of broadly delineated Asteridae and Rosidae in the 499-taxon study.

No abstract

Advances in recording technologies have given neuroscience researchers access to large amounts of data, in particular, simultaneous, individual recordings of large groups of neurons in different parts of the brain. A variety of quantitative techniques have been utilized to analyze the spiking activities of the neurons to elucidate the functional connectivity of the recorded neurons. In the past, researchers have used correlative measures. More recently, to better capture the dynamic, complex relationships present in the data, neuroscientists have employed causal measures—most of which are variants of Granger causality—with limited success. This paper motivates the directed information, an information and control theoretic concept, as a modality-independent embodiment of Granger's original notion of causality. Key properties include: (a) it is nonzero if and only if one process causally influences another, and (b) its specific value can be interpreted as the strength of a causal relationship. We next describe how the causally conditioned directed information between two processes given knowledge of others provides a network version of causality: it is nonzero if and only if, in the presence of the present and past of other processes, one process causally influences another. This notion is shown to be able to differentiate between true direct causal influences, common inputs, and cascade effects in more two processes. We next describe a procedure to estimate the directed information on neural spike trains using point process generalized linear models, maximum likelihood estimation and information-theoretic model order selection. We demonstrate that on a simulated network of neurons, it (a) correctly identifies all pairwise causal relationships and (b) correctly identifies network causal relationships. This procedure is then used to analyze ensemble spike train recordings in primary motor cortex of an awake monkey while performing target reaching tasks, uncovering causal relationships whose directionality are consistent with predictions made from the wave propagation of simultaneously recorded local field potentials.

No abstract

Parsimony analysis of matK and rbcL sequence data, together with a nonmolecular database, yielded a well-resolved phylogeny of Cupressaceae sensu lato. Monophyly of Cupressaceae sensu stricto is well supported, and separate northern and southern hemisphere subclades are resolved, with Tetraclinis within the northern subclade; there is no support for any of the tribes sensu Li. Taxodiaceae comprise five separate lineages. Chamaecyparis nootkatensis falls within Cupressus, clustering with a robust clade of New World species. Libocedrus Florin is paraphyletic and should incorporate Pilgerodendron. Evolution of several characters of wood and leaf anatomy and chemistry is discussed in light of this estimate of the phylogeny; numerous parallelisms are apparent. A new infrafamilial classification is proposed in which seven subfamilies are recognized: Callitroideae Saxton, Athrotaxidoideae Quinn, Cunninghamioideae (Sieb. & Zucc.) Quinn, Cupressoideae Rich. ex Sweet, Sequoioideae (Luerss.) Quinn, Taiwanioideae (Hayata) Quinn, Taxodioideae Endl. ex K. Koch. The rbcL sequence for Taxodium distichum is corrected, and the implications for a previously published estimate of the minimum rate of divergence of the gene since the Miocene are highlighted.

Cladistic analyses are presented of matK sequence data as well as a nonmolecular database for an identical set of exemplar species chosen to represent the core genera or groups of genera in Myrtaceae. Eleven robust clades are recognized on the molecular data. Polyphyly of the previously recognized Metrosideros and Leptospermum alliances is confirmed, and several smaller informal taxonomic groupings are recognized from among the members of the former alliance, i.e., the Tristania, Tristaniopsis, Metrosideros, and Lophostemon groups. The nonmolecular analysis provides only limited resolution of relationships. A degree of congruence exists between the two analyses in that two separate fleshy-fruited clades, the Acmena and Myrtoid groups, are identified, as are the Eucalypt and Tristania groups, and Psiloxylon and Heteropyxis are the first lineages to diverge in both analyses. A combined analysis recognized all 11 clades that received strong support from the molecular data. A high level of homoplasy is revealed in many of the nonmolecular characters when they are examined against the combined estimate of phylogeny.

Pericarp structure is surveyed in 29 genera. Homologous regions termed exocarp, mesocarp and endocarp are established. While exocarp and mesocarp structure show some uniformity, there are two very distinct types of endocarp, designated the Anacardium‐type and the Spondias‐type. The distribution of these indicates that the current division of the family into five tribes is artificial. The occurrence of the Spondias‐type in Canarium, a member of the sister group Burseraceae, suggests that this type is plesiomorphic in the Anacardiaceae. In addition, the presence of the Anacardium‐type in Blepharocarya (Blepharocaryaceae) and Orthopterygium Qulianiaceae) further supports the inclusion of these taxa in the Anacardiaceae.

We propose a graphical model for representing networks of stochastic processes, the minimal generative model graph. It is based on reduced factorizations of the joint distribution over time. We show that under appropriate conditions, it is unique and consistent with another type of graphical model, the directed information graph, which is based on a generalization of Granger causality. We demonstrate how directed information quantifies Granger causality in a particular sequential prediction setting. We also develop efficient methods to estimate the topological structure from data that obviate estimating the joint statistics. One algorithm assumes upper-bounds on the degrees and uses the minimal dimension statistics necessary. In the event that the upper-bounds are not valid, the resulting graph is nonetheless an optimal approximation. Another algorithm uses near-minimal dimension statistics when no bounds are known but the distribution satisfies a certain criterion. Analogous to how structure learning algorithms for undirected graphical models use mutual information estimates, these algorithms use directed information estimates.We characterize the sample-complexity of two plug-in directed information estimators and obtain confidence intervals.For the setting when point estimates are unreliable, we propose an algorithm that uses confidence intervals to identify the best approximation that is robust to estimation error. Lastly, we demonstrate the effectiveness of the proposed algorithms through analysis of both synthetic data and real data from the Twitter network. In the latter case, we identify which news sources influence users in the network by merely analyzing tweet times.