Evolutionary processes and its environmental correlates in the cranial morphology of western chipmunks (Tamias).

The importance of the environment in shaping phenotypic evolution lies at the core of evolutionary biology. Chipmunks of the genus Tamias (subgenus Neotamias) are part of a very recent radiation, occupying a wide range of environments with marked niche partitioning among species. One open question is if and how those differences in environments affected phenotypic evolution in this lineage. Herein we examine the relative importance of genetic drift versus natural selection in the origin of cranial diversity exhibited by clade members. We also explore the degree to which variation in potential selective agents (environmental variables) are correlated with the patterns of morphological variation presented. We found that genetic drift cannot explain morphological diversification in the group, thus supporting the potential role of natural selection as the predominant evolutionary force during Neotamias cranial diversification, although the strength of selection varied greatly among species. This morphological diversification, in turn, was correlated with environmental conditions, suggesting a possible causal relationship. These results underscore that extant Neotamias represent a radiation in which aspects of the environment might have acted as the selective force driving species' divergence

Aerospace Medicine and Biology. A continuing bibliography (Supplement 226)

This bibliography lists 129 reports, articles, and other documents introduced into the NASA scientific and technical information system in November 1981

Mechanism of glycan receptor recognition and specificity switch for avian, swine, and human adapted influenza virus hemagglutinins: a molecular dynamics perspective.

Hemagglutinins (HA's) from duck, swine, and human influenza viruses have previously been shown to prefer avian and human glycan receptor analogues with distinct topological profiles, pentasaccharides LSTa (alpha-2,3 linkage) and LSTc (alpha-2,6 linkage), in comparative molecular dynamics studies. On the basis of detailed analyses of the dynamic motions of the receptor binding domains (RBDs) and interaction energy profiles with individual glycan residues, we have identified approximately 30 residue positions in the RBD that present distinct profiles with the receptor analogues. Glycan binding constrained the conformational space sampling by the HA. Electrostatic steering appeared to play a key role in glycan binding specificity. The complex dynamic behaviors of the major SSE and trimeric interfaces with or without bound glycans suggested that networks of interactions might account for species specificity in these low affinity and high avidity (multivalent) interactions between different HA and glycans. Contact frequency, energetic decomposition, and H-bond analyses revealed species-specific differences in HA-glycan interaction profiles, not readily discernible from crystal structures alone. Interaction energy profiles indicated that mutation events at the set of residues such as 145, 156, 158, and 222 would favor human or avian receptor analogues, often through interactions with distal asialo-residues. These results correlate well with existing experimental evidence, and suggest new opportunities for simulation-based vaccine and drug development

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Where do statistical models come from? Revisiting the problem of specification

R. A. Fisher founded modern statistical inference in 1922 and identified its fundamental problems to be: specification, estimation and distribution. Since then the problem of statistical model specification has received scant attention in the statistics literature. The paper traces the history of statistical model specification, focusing primarily on pioneers like Fisher, Neyman, and more recently Lehmann and Cox, and attempts a synthesis of their views in the context of the Probabilistic Reduction (PR) approach. As argued by Lehmann [11], a major stumbling block for a general approach to statistical model specification has been the delineation of the appropriate role for substantive subject matter information. The PR approach demarcates the interrelated but complemenatry roles of substantive and statistical information summarized ab initio in the form of a structural and a statistical model, respectively. In an attempt to preserve the integrity of both sources of information, as well as to ensure the reliability of their fusing, a purely probabilistic construal of statistical models is advocated. This probabilistic construal is then used to shed light on a number of issues relating to specification, including the role of preliminary data analysis, structural vs. statistical models, model specification vs. model selection, statistical vs. substantive adequacy and model validation.Comment: Published at http://dx.doi.org/10.1214/074921706000000419 in the IMS Lecture Notes--Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org

Perception of the Body in Space: Mechanisms

The principal topic is the perception of body orientation and motion in space and the extent to which these perceptual abstraction can be related directly to the knowledge of sensory mechanisms, particularly for the vestibular apparatus. Spatial orientation is firmly based on the underlying sensory mechanisms and their central integration. For some of the simplest situations, like rotation about a vertical axis in darkness, the dynamic response of the semicircular canals furnishes almost enough information to explain the sensations of turning and stopping. For more complex conditions involving multiple sensory systems and possible conflicts among their messages, a mechanistic response requires significant speculative assumptions. The models that exist for multisensory spatial orientation are still largely of the non-rational parameter variety. They are capable of predicting relationships among input motions and output perceptions of motion, but they involve computational functions that do not now and perhaps never will have their counterpart in central nervous system machinery. The challenge continues to be in the iterative process of testing models by experiment, correcting them where necessary, and testing them again

Detecting adaptive evolution in phylogenetic comparative analysis using the Ornstein-Uhlenbeck model

Phylogenetic comparative analysis is an approach to inferring evolutionary process from a combination of phylogenetic and phenotypic data. The last few years have seen increasingly sophisticated models employed in the evaluation of more and more detailed evolutionary hypotheses, including adaptive hypotheses with multiple selective optima and hypotheses with rate variation within and across lineages. The statistical performance of these sophisticated models has received relatively little systematic attention, however. We conducted an extensive simulation study to quantify the statistical properties of a class of models toward the simpler end of the spectrum that model phenotypic evolution using Ornstein-Uhlenbeck processes. We focused on identifying where, how, and why these methods break down so that users can apply them with greater understanding of their strengths and weaknesses. Our analysis identifies three key determinants of performance: a discriminability ratio, a signal-to-noise ratio, and the number of taxa sampled. Interestingly, we find that model-selection power can be high even in regions that were previously thought to be difficult, such as when tree size is small. On the other hand, we find that model parameters are in many circumstances difficult to estimate accurately, indicating a relative paucity of information in the data relative to these parameters. Nevertheless, we note that accurate model selection is often possible when parameters are only weakly identified. Our results have implications for more sophisticated methods inasmuch as the latter are generalizations of the case we study.Comment: 38 pages, in press at Systematic Biolog

A hierarchical anti-Hebbian network model for the formation of spatial cells in three-dimensional space.

Three-dimensional (3D) spatial cells in the mammalian hippocampal formation are believed to support the existence of 3D cognitive maps. Modeling studies are crucial to comprehend the neural principles governing the formation of these maps, yet to date very few have addressed this topic in 3D space. Here we present a hierarchical network model for the formation of 3D spatial cells using anti-Hebbian network. Built on empirical data, the model accounts for the natural emergence of 3D place, border, and grid cells, as well as a new type of previously undescribed spatial cell type which we call plane cells. It further explains the plausible reason behind the place and grid-cell anisotropic coding that has been observed in rodents and the potential discrepancy with the predicted periodic coding during 3D volumetric navigation. Lastly, it provides evidence for the importance of unsupervised learning rules in guiding the formation of higher-dimensional cognitive maps