scholarly journals Introgression obscures and reveals historical relationships among the American live oaks

2015 ◽  
Author(s):  
Deren Eaton ◽  
Antonio Gonzalez-Rodriguez ◽  
Andrew Hipp ◽  
Jeannine Cavender-Bares
Keyword(s):  
Model Comparison ◽  
Introgressive Hybridization ◽  
Theoretic Model ◽  
Phylogenetic Structure ◽  
Geographic Ranges ◽  
Information Theoretic ◽  
Extant Species ◽  
Show Evidence ◽  
Hybrid Introgression ◽  
Alternative Scenarios

Introgressive hybridization challenges the concepts we use to define species and our ability to infer their evolutionary relationships. Methods for inferring historical introgression from the genomes of extant species are now widely used, however, few guidelines have been articulated for how best to interpret their results. Because these tests are inherently comparative, we show that they are sensitivite to the effects of missing data (unsampled species) and to non-independence (hierarchical relationships among species). We demonstrate this using genomic RAD data sampled from populations across the geographic ranges of all extant species in the American live oaks (QuercusseriesVirentes), a group notorious for hybridization. By considering all species in the clade, and their phylogenetic relationships, we were able to distinguish true hybridizing lineages from those that falsely appear admixed due to phylogenetic structure among hybridizing relatives. Six of seven species show evidence of admixture, often with multiple other species, but which can be explained by hybrid introgression among few related lineages where they occur in close proximity. We identify the Cuban oak as a highly admixed lineage and use an information-theoretic model comparison approach to test alternative scenarios for its origin. Hybrid speciation is a poor fit compared to a model in which a population from Central America colonized Cuba and received subsequent gene flow from Florida. The live oaks form a continuous ring-like distribution around the Gulf of Mexico, connected in Cuba, across which they could effectively exchange alleles. However, introgression appears to remain localized to areas of sympatry, suggesting that oak species boundaries, and their geographic ranges have remained relatively stable over evolutionary time.

Constraint conjunction in weighted probabilistic grammar

Phonology ◽  
2017 ◽  
Vol 34 (2) ◽  
pp. 243-268 ◽  
Author(s):  
Stephanie S. Shih
Keyword(s):  
Model Comparison ◽  
Explanatory Power ◽  
Theoretic Model ◽  
Long Distance ◽  
Information Theoretic ◽  
Harmonic Grammar ◽  
Empirical Coverage ◽  
Weighted Constraint ◽  
Probabilistic Grammar

This paper examines a key difference between constraint conjunction and constraint weight additivity, arguing that the two do not have the same empirical coverage. In particular, constraint conjunction in weighted probabilistic grammar allows for superadditive constraint interaction, where the effect of violating two constraints goes beyond the additive combination of the two constraints’ weights alone. A case study from parasitic tone harmony in Dioula d'Odienné demonstrates superadditive local and long-distance segmental feature similarities that increase the likelihood of tone harmony. Superadditivity in Dioula d'Odienné is formally captured in Maximum Entropy Harmonic Grammar by weighted constraint conjunction. Counter to previous approaches that supplant constraint conjunction with weight additivity in Harmonic Grammar, information-theoretic model comparison reveals that weighted constraint conjunction improves the grammar's explanatory power when modelling quantitative natural language patterns.

scholarly journals Information-theoretic model comparison unifies saliency metrics

2015 ◽  
Vol 112 (52) ◽  
pp. 16054-16059 ◽  
Author(s):  
Matthias Kümmerer ◽  
Thomas S. A. Wallis ◽  
Matthias Bethge
Keyword(s):  
Model Comparison ◽  
Prediction Models ◽  
Information Gain ◽  
Model Performance ◽  
Saliency Map ◽  
Theoretic Model ◽  
Perfect Agreement ◽  
Information Theoretic ◽  
Center Bias ◽  
Spatiotemporal Models

Learning the properties of an image associated with human gaze placement is important both for understanding how biological systems explore the environment and for computer vision applications. There is a large literature on quantitative eye movement models that seeks to predict fixations from images (sometimes termed “saliency” prediction). A major problem known to the field is that existing model comparison metrics give inconsistent results, causing confusion. We argue that the primary reason for these inconsistencies is because different metrics and models use different definitions of what a “saliency map” entails. For example, some metrics expect a model to account for image-independent central fixation bias whereas others will penalize a model that does. Here we bring saliency evaluation into the domain of information by framing fixation prediction models probabilistically and calculating information gain. We jointly optimize the scale, the center bias, and spatial blurring of all models within this framework. Evaluating existing metrics on these rephrased models produces almost perfect agreement in model rankings across the metrics. Model performance is separated from center bias and spatial blurring, avoiding the confounding of these factors in model comparison. We additionally provide a method to show where and how models fail to capture information in the fixations on the pixel level. These methods are readily extended to spatiotemporal models of fixation scanpaths, and we provide a software package to facilitate their use.

scholarly journals Information-Theoretic Model Predictive Control: Theory and Applications to Autonomous Driving

2018 ◽  
Vol 34 (6) ◽  
pp. 1603-1622 ◽  
Author(s):  
Grady Williams ◽  
Paul Drews ◽  
Brian Goldfain ◽  
James M. Rehg ◽  
Evangelos A. Theodorou
Keyword(s):  
Control Theory ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Autonomous Driving ◽  
Theoretic Model ◽  
Information Theoretic

scholarly journals Characterizing the effects of sex, APOE ɛ4, and literacy on mid-life cognitive trajectories: Application of Information-Theoretic model-averaging and multi-model inference techniques to the Wisconsin Registry for Alzheimer’s Prevention Study

2017 ◽  
Author(s):  
Rebecca L. Koscik ◽  
Derek L. Norton ◽  
Samantha L. Allison ◽  
Erin M. Jonaitis ◽  
Lindsay R. Clark ◽  
...  
Keyword(s):  
Model Selection ◽  
Cognitive Decline ◽  
Model Averaging ◽  
Parameter Estimates ◽  
Theoretic Model ◽  
Traditional Model ◽  
Test Model ◽  
Prevention Study ◽  
Information Theoretic ◽  
Modifiable Factors

ObjectiveIn this paper we apply Information-Theoretic (IT) model averaging to characterize a set of complex interactions in a longitudinal study on cognitive decline. Prior research has identified numerous genetic (including sex), education, health and lifestyle factors that predict cognitive decline. Traditional model selection approaches (e.g., backward or stepwise selection) attempt to find models that best fit the observed data; these techniques risk interpretations that only the selected predictors are important. In reality, several models may fit similarly well but result in different conclusions (e.g., about size and significance of parameter estimates); inference from traditional model selection approaches can lead to overly confident conclusions.MethodHere we use longitudinal cognitive data from ~1550 late-middle aged adults the Wisconsin Registry for Alzheimer’s Prevention study to examine the effects of sex, Apolipoprotein E (APOE) ɛ4 allele (non-modifiable factors), and literacy achievement (modifiable) on cognitive decline. For each outcome, we applied IT model averaging to a model set with combinations of interactions among sex, APOE, literacy, and age.ResultsFor a list-learning test, model-averaged results showed better performance for women vs men, with faster decline among men; increased literacy was associated with better performance, particularly among men. APOE had less of an effect on cognitive performance in this age range (~40-70).ConclusionsThese results illustrate the utility of the IT approach and point to literacy as a potential modifier of decline. Whether the protective effect of literacy is due to educational attainment or intrinsic verbal intellectual ability is the topic of ongoing work.

scholarly journals Approaches for testing hypotheses for the hypometric scaling of aerobic metabolic rate in animals

2018 ◽  
Vol 315 (5) ◽  
pp. R879-R894 ◽  
Author(s):  
Jon F. Harrison
Keyword(s):  
Metabolic Rate ◽  
Heat Loss ◽  
Heat Dissipation ◽  
Morphological Properties ◽  
Compensatory Responses ◽  
Size Dependent ◽  
Extant Species ◽  
Show Evidence ◽  
Selection For ◽  
Interspecific Comparisons

Hypometric scaling of aerobic metabolism [larger organisms have lower mass-specific metabolic rates (MR/g)] is nearly universal for interspecific comparisons among animals, yet we lack an agreed upon explanation for this pattern. If physiological constraints on the function of larger animals occur and limit MR/g, these should be observable as direct constraints on animals of extant species and/or as evolved responses to compensate for the proposed constraint. There is evidence for direct constraints and compensatory responses to O2 supply constraint in skin-breathing animals, but not in vertebrates with gas-exchange organs. The duration of food retention in the gut is longer for larger birds and mammals, consistent with a direct constraint on nutrient uptake across the gut wall, but there is little evidence for evolving compensatory responses to gut transport constraints in larger animals. Larger placental mammals (but not marsupials or birds) show evidence of greater challenges with heat dissipation, but there is little evidence for compensatory adaptations to enhance heat loss in larger endotherms, suggesting that metabolic rate (MR) more generally balances heat loss for thermoregulation in endotherms. Size-dependent patterns in many molecular, physiological, and morphological properties are consistent with size-dependent natural selection, such as stronger selection for neurolocomotor performance and growth rate in smaller animals and stronger selection for safety and longevity in larger animals. Hypometric scaling of MR very likely arises from different mechanisms in different taxa and conditions, consistent with the diversity of scaling slopes for MR.

scholarly journals Measuring Non-Gaussianity by Phi-Transformed and Fuzzy Histograms

2012 ◽  
Vol 2012 ◽  
pp. 1-13
Author(s):  
Claudia Plant ◽  
Son Mai Thai ◽  
Junming Shao ◽  
Fabian J. Theis ◽  
Anke Meyer-Baese ◽  
...  
Keyword(s):  
Data Analysis ◽  
Data Compression ◽  
Theoretic Model ◽  
General Technique ◽  
Information Theoretic ◽  
Efficient Data ◽  
Information Theoretic Measures ◽  
Fully Automatic ◽  
Non Gaussian ◽  
Ica Algorithm

Independent component analysis (ICA) is an essential building block for data analysis in many applications. Selecting the truly meaningful components from the result of an ICA algorithm, or comparing the results of different algorithms, however, is nontrivial problems. We introduce a very general technique for evaluating ICA results rooted in information-theoretic model selection. The basic idea is to exploit the natural link between non-Gaussianity and data compression: the better the data transformation represented by one or several ICs improves the effectiveness of data compression, the higher is the relevance of the ICs. We propose two different methods which allow an efficient data compression of non-Gaussian signals: Phi-transformed histograms and fuzzy histograms. In an extensive experimental evaluation, we demonstrate that our novel information-theoretic measures robustly select non-Gaussian components from data in a fully automatic way, that is, without requiring any restrictive assumptions or thresholds.

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