Adaptive strategy for the statistical analysis of connectomes.

We study an adaptive statistical approach to analyze brain networks represented by brain connection matrices of interregional connectivity (connectomes). Our approach is at a middle level between a global analysis and single connections analysis by considering subnetworks of the global brain network. These subnetworks represent either the inter-connectivity between two brain anatomical regions or by the intra-connectivity within the same brain anatomical region. An appropriate summary statistic, that characterizes a meaningful feature of the subnetwork, is evaluated. Based on this summary statistic, a statistical test is performed to derive the corresponding p-value. The reformulation of the problem in this way reduces the number of statistical tests in an orderly fashion based on our understanding of the problem. Considering the global testing problem, the p-values are corrected to control the rate of false discoveries. Finally, the procedure is followed by a local investigation within the significant subnetworks. We contrast this strategy with the one based on the individual measures in terms of power. We show that this strategy has a great potential, in particular in cases where the subnetworks are well defined and the summary statistics are properly chosen. As an application example, we compare structural brain connection matrices of two groups of subjects with a 22q11.2 deletion syndrome, distinguished by their IQ scores.

Testing the predictive adaptive response in a host-parasite system

1. Harsh environmental conditions experienced during development can reduce the performance of the same individuals in adulthood. However, the 'predictive adaptive response' hypothesis postulates that if individuals adapt their phenotype during development to the environments where they are likely to live in the future, individuals exposed to harsh conditions in early life perform better when encountering the same harsh conditions in adulthood compared to those never exposed to these conditions before. 2. Using the common vole (Microtus arvalis) as study organism, we tested how exposure to flea parasitism during the juvenile stage affects the physiology (haematocrit, resistance to oxidative stress, resting metabolism, spleen mass, and testosterone), morphology (body mass, testis mass) and motor performance (open field activity and swimming speed) of the same individuals when infested with fleas in adulthood. According to the 'predictive adaptive response' hypothesis, we predicted that voles parasitized at the adult stage would perform better if they had already been parasitized with fleas at the juvenile stage. 3. We found that voles exposed to fleas in adulthood had a higher metabolic rate if already exposed to fleas when juvenile, compared to voles free of fleas when juvenile and voles free of fleas in adulthood. Independently of juvenile parasitism, adult parasitism impaired adult haematocrit and motor performances. Independently of adult parasitism, juvenile parasitism slowed down crawling speed in adult female voles. 4. Our results suggest that juvenile parasitism has long-term effects that do not protect from the detrimental effects of adult parasitism. On the contrary, experiencing parasitism in early-life incurs additional costs upon adult parasitism measured in terms of higher energy expenditure, rather than inducing an adaptive shift in the developmental trajectory. 5. Hence, our study provides experimental evidence for long term costs of parasitism. We found no support for a predictive adaptive response in this host-parasite system.

Individual vocal signatures in barn owl nestlings: does individual recognition have an adaptive role in sibling vocal competition?

To compete over limited parental resources, young animals communicate with their parents and siblings by producing honest vocal signals of need. Components of begging calls that are sensitive to food deprivation may honestly signal need, whereas other components may be associated with individual-specific attributes that do not change with time such as identity, sex, absolute age and hierarchy. In a sib-sib communication system where barn owl (Tyto alba) nestlings vocally negotiate priority access to food resources, we show that calls have individual signatures that are used by nestlings to recognize which siblings are motivated to compete, even if most vocalization features vary with hunger level. Nestlings were more identifiable when food-deprived than food-satiated, suggesting that vocal identity is emphasized when the benefit of winning a vocal contest is higher. In broods where siblings interact iteratively, we speculate that individual-specific signature permits siblings to verify that the most vocal individual in the absence of parents is the one that indeed perceived the food brought by parents. Individual recognition may also allow nestlings to associate identity with individual-specific characteristics such as position in the within-brood dominance hierarchy. Calls indeed revealed age hierarchy and to a lower extent sex and absolute age. Using a cross-fostering experimental design, we show that most acoustic features were related to the nest of origin (but not the nest of rearing), suggesting a genetic or an early developmental effect on the ontogeny of vocal signatures. To conclude, our study suggests that sibling competition has promoted the evolution of vocal behaviours that signal not only hunger level but also intrinsic individual characteristics such as identity, family, sex and age.

Combining molecular evolution and environmental genomics to unravel adaptive processes of MHC class IIB diversity in European minnows (Phoxinus phoxinus)

Host-pathogen interactions are a major evolutionary force promoting local adaptation. Genes of the major histocompatibility complex (MHC) represent unique candidates to investigate evolutionary processes driving local adaptation to parasite communities. The present study aimed at identifying the relative roles of neutral and adaptive processes driving the evolution of MHC class IIB (MHCIIB) genes in natural populations of European minnows (Phoxinus phoxinus). To this end, we isolated and genotyped exon 2 of two MHCIIB gene duplicates (DAB1 and DAB3) and 1665 amplified fragment length polymorphism (AFLP) markers in nine populations, and characterized local bacterial communities by 16S rDNA barcoding using 454 amplicon sequencing. Both MHCIIB loci exhibited signs of historical balancing selection. Whereas genetic differentiation exceeded that of neutral markers at both loci, the populations' genetic diversities were positively correlated with local pathogen diversities only at DAB3. Overall, our results suggest pathogen-mediated local adaptation in European minnows at both MHCIIB loci. While at DAB1 selection appears to favor different alleles among populations, this is only partially the case in DAB3, which appears to be locally adapted to pathogen communities in terms of genetic diversity. These results provide new insights into the importance of host-pathogen interactions in driving local adaptation in the European minnow, and highlight that the importance of adaptive processes driving MHCIIB gene evolution may differ among duplicates within species, presumably as a consequence of alternative selective regimes or different genomic context.

Intellectual Property Rights and Crop-Improving R&D under Adaptive Destruction, June 2007

This paper studies how the strength of intellectual property rights (IPRs) affects investments in biological innovations when the value of an innovation is stochastically reduced to zero because of the evolution of pest resistance. We frame the problem as a research and development (R&D) investment game in a duopoly model of sequential innovation. We characterize the incentives to invest in R&D under two competing IPR regimes, which differ in their treatment of the follow-on innovations that become necessary because of pest adaptation. Depending on the magnitude of the R&D cost, ex ante firms might prefer an intellectual property regime with or without a “research exemption” provision. The study of the welfare function that also accounts for benefit spillovers to consumers—which is possible analytically under some parametric conditions, and numerically otherwise—shows that the ranking of the two IPR regimes depends critically on the extent of the R&D cost.

Adaptive learning in models with lagged variables

In this work I study the stability of the dynamics generated by adaptivelearning processes in intertemporal economies with lagged variables. Iprove that determinacy of the steady state is a necessary condition for the convergence of the learning dynamics and I show that the reciprocal is not true characterizing the economies where convergence holds. In the case of existence of cycles I show that there is not, in general, a relationship between determinacy and convergence of the learning process to the cycle. I also analyze the expectational stability of these equilibria.

Rational reasoning or adaptive behavior? Evidence from two-person beauty contest games

Many experiments have shown that human subjects do not necessarily behave in line with game theoretic assumptions and solution concepts. The reasons for this non-conformity are multiple. In this paper we study the argument whether a deviation from game theory is because subjects are rational, but doubt that others are rational as well, compared to the argument that subjects, in general, are boundedly rational themselves. To distinguish these two hypotheses, we study behavior in repeated 2-person and many-person Beauty-Contest-Games which are strategically different from one another. We analyze four different treatments and observe that convergence toward equilibrium is driven by learning through the information about the other player s choice and adaptation rather than self-initiated rational reasoning.

Scale-dependent adaptive evolution and morphological convergence to climatic niche in Californian eriogonoids (Polygonaceae)

Aim Macroevolutionary patterns and processes change substantially depending on levels of taxonomic and ecological organization, and the resolution of environmental and spatial variability. In comparative methods, the resolution of environmental and spatial variability often defines the number of selective regimes used to test whether phenotypic characteristics are adaptively correlated with the environment. Here, we examine how investigator choice of the number of selective regimes, determined by varying the resolution of among-species variability in the species climatic niche (hereafter called ecological scale'), influences trait morphological diversification among Eriogonoideae species. We assess whether adaptive or neutral processes drive the evolution of several morphological traits in these species. Location South-western North America. Methods We applied a phylogenetic framework of three evolutionary models to four morphological traits and the climatic niches of Eriogonoideae (in the buckwheat family, Polygonaceae). We tested whether morphological traits evolve in relation to climate by adaptive or neutral process, and whether the resulting patterns of morphological variability are conserved or convergent across the clade. We inspected adaptive models of evolution under different levels of resolution of among-species variability of the climatic niche. Results We show that morphological traits and climate niches of Eriogonoideae species are not phylogenetically conserved. Further, adaptive evolution of phenotypic traits is specific to climatic niche occupancy across this clade. Finally, the likely evolutionary process and the level of detectable niche conservatism change depending on the resolution of environmental variability of the climatic niche. Main conclusions Our study demonstrates the need to consider both the resolution of environmental variability and alternative evolutionary models to understand the morphological diversification that accompanies divergent adaptive evolution of lineages to climatic conditions.

Improved statistical evaluation of group differences in connectomes by screening-filtering strategy with application to study maturation of brain connections between childhood and adolescence.

Detecting local differences between groups of connectomes is a great challenge in neuroimaging, because the large number of tests that have to be performed and the impact on multiplicity correction. Any available information should be exploited to increase the power of detecting true between-group effects. We present an adaptive strategy that exploits the data structure and the prior information concerning positive dependence between nodes and connections, without relying on strong assumptions. As a first step, we decompose the brain network, i.e., the connectome, into subnetworks and we apply a screening at the subnetwork level. The subnetworks are defined either according to prior knowledge or by applying a data driven algorithm. Given the results of the screening step, a filtering is performed to seek real differences at the node/connection level. The proposed strategy could be used to strongly control either the family-wise error rate or the false discovery rate. We show by means of different simulations the benefit of the proposed strategy, and we present a real application of comparing connectomes of preschool children and adolescents.

Statistical learning theory for geospatial data. Case study: Aral sea

In recent years there has been an explosive growth in the development of adaptive and data driven methods. One of the efficient and data-driven approaches is based on statistical learning theory (Vapnik 1998). The theory is based on Structural Risk Minimisation (SRM) principle and has a solid statistical background. When applying SRM we are trying not only to reduce training error ? to fit the available data with a model, but also to reduce the complexity of the model and to reduce generalisation error. Many nonlinear learning procedures recently developed in neural networks and statistics can be understood and interpreted in terms of the structural risk minimisation inductive principle. A recent methodology based on SRM is called Support Vector Machines (SVM). At present SLT is still under intensive development and SVM find new areas of application (www.kernel-machines.org). SVM develop robust and non linear data models with excellent generalisation abilities that is very important both for monitoring and forecasting. SVM are extremely good when input space is high dimensional and training data set i not big enough to develop corresponding nonlinear model. Moreover, SVM use only support vectors to derive decision boundaries. It opens a way to sampling optimization, estimation of noise in data, quantification of data redundancy etc. Presentation of SVM for spatially distributed data is given in (Kanevski and Maignan 2004).

Adaptive frequency tracking of the baseline ECG identifies the site of atrial fibrillation termination by catheter ablation

Multiple organization indices have been used to predict the outcome of stepwise catheter ablation in long-standing persistent atrial fibrillation (AF), however with limited success. Our study aims at developinginnovative organization indices from baseline ECG (i.e. during the procedure, before ablation) in orderto identify the site of AF termination by catheter ablation. Seventeen consecutive male patients (age60 ± 5 years, AF duration 7 ± 5 years) underwent a stepwise catheter ablation. Chest lead V6 was placedin the back (V6b). QRST cancelation was performed from chest leads V1 to V6b. Using an innovativeadaptive harmonic frequency tracking, two measures of AF organization were computed to quantify theharmonics components of ECG activity: (1) the adaptive phase difference variance (APD) between theAF harmonic components as a measure of AF regularity, and (2) and adaptive organization index (AOI)evaluating the cyclicity of the AF oscillations. Both adaptive indices were compared to indices computedusing a time-invariant approach: (1) ECG AF cycle length (AFCL), (2) the spectrum based organizationindex (OI), and (3) the time-invariant phase difference TIPD. Long-standing persistent AF was terminatedinto sinus rhythm or atrial tachycardia in 13/17 patients during stepwise ablation, 11 during left atriumablation (left terminated patients - LT), 2 during the right atrium ablation (right terminated patients -RT), and 4 were non terminated (NT) and required electrical cardioversion. Our findings showed that LTpatients were best separated from RT/NT before ablation by the duration of sustained AF and by AOI onchest lead V1 and APD from the dorsal lead V6b as compared to ECG AFCL, OI and TIPD, respectively. Ourresults suggest that adaptive measures of AF organization computed before ablation perform better thantime-invariant based indices for identifying patients whose AF will terminate during ablation within theleft atrium. These findings are indicative of a higher baseline organization in these patients that could beused to select candidates for the termination of AF by stepwise catheter ablation.© 2013 Elsevier Ltd. All rights reserved.

Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation.

Identifying adaptive genetic variation is a challenging task, in particular in non-model species for which genomic information is still limited or absent. Here, we studied distribution patterns of amplified fragment length polymorphisms (AFLPs) in response to environmental variation, in 13 alpine plant species consistently sampled across the entire European Alps. Multiple linear regressions were performed between AFLP allele frequencies per site as dependent variables and two categories of independent variables, namely Moran's eigenvector map MEM variables (to account for spatial and unaccounted environmental variation, and historical demographic processes) and environmental variables. These associations allowed the identification of 153 loci of ecological relevance. Univariate regressions between allele frequency and each environmental factor further showed that loci of ecological relevance were mainly correlated with MEM variables. We found that precipitation and temperature were the best environmental predictors, whereas topographic factors were rarely involved in environmental associations. Climatic factors, subject to rapid variation as a result of the current global warming, are known to strongly influence the fate of alpine plants. Our study shows, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps.

Evolutionary dynamics of molecular markers during local adaptation: a case study in Drosophila subobscura

Background: Natural selection and genetic drift are major forces responsible for temporal genetic changes in populations. Furthermore, these evolutionary forces may interact with each other. Here we study the impact of an ongoing adaptive process at the molecular genetic level by analyzing the temporal genetic changes throughout 40 generations of adaptation to a common laboratory environment. Specifically, genetic variability, population differentiation and demographic structure were compared in two replicated groups of Drosophila subobscura populations recently sampled from different wild sources. Results: We found evidence for a decline in genetic variability through time, along with an increase in genetic differentiation between all populations studied. The observed decline in genetic variability was higher during the first 14 generations of laboratory adaptation. The two groups of replicated populations showed overall similarity in variability patterns. Our results also revealed changing demographic structure of the populations during laboratory evolution, with lower effective population sizes in the early phase of the adaptive process. One of the ten microsatellites analyzed showed a clearly distinct temporal pattern of allele frequency change, suggesting the occurrence of positive selection affecting the region around that particular locus. Conclusion: Genetic drift was responsible for most of the divergence and loss of variability between and within replicates, with most changes occurring during the first generations of laboratory adaptation. We also found evidence suggesting a selective sweep, despite the low number of molecular markers analyzed. Overall, there was a similarity of evolutionary dynamics at the molecular level in our laboratory populations, despite distinct genetic backgrounds and some differences in phenotypic evolution.

Adaptive colour polymorphism of Acrida ungarica H. (Orthoptera: Acrididae) in a spatially heterogeneous environment

Intra-specific colour polymorphism provides a cryptic camouflage from predators in heterogeneous habitats. The orthoptera species, Acrida ungarica (Herbst, 1786) possess two well-distinguished colour morphs: brown and green and displays several disruptive colouration patterns within each morph to improve the crypsis. This study focused on how the features of the background environment relate to the proportion of the two morphs and to the intensity of disruptive colouration patterns in A. ungarica. As the two sexes are very distinct with respect to mass and length, we also distinctively tested the relationship for each sex. In accordance with the background matching hypothesis, we found that, for both sexes, the brown morph was in higher proportion at sites with a brown-dominant environment, and green morphs were in higher proportion in green-dominant environments. Globally, individuals in drier sites and in the drier year also had more intense disruptive colouration patterns, and brown morphs and females were also more striped. Colour patterns differed largely between populations and were significantly correlated with relevant environmental features. Even if A. ungarica is a polymorphic specialist, disruptive colouration still appears to provide strong benefits, particularly in some habitats. Moreover, because females are larger, they are less able to flee, which might explain the difference between sexes

Molecular insights into T cell activation : study of the TRAF, Bcl10 and Carma 1 proteins

Abstract : Activation of naïve T lymphocytes is essential for the onset of an adaptive immune response against a pathogenic threat. T lymphocytes are activated through the engagement of their highly specific cell surface antigen-receptor (TCR), together with co-stimulatory receptors, by activated antigen-presenting cells that display antigenic peptide fragments from the pathogen that they have detected. Dissection of the mechanisms that modulate TCR- and co-stimulation- induced signals is therefore crucial for the understanding of the molelcular basis of adaptive immune responses. Following antigen-receptor triggering, the Carma1, Bcl10 and Malt1 (CBM) proteins assemble into an oligomeric complex, which is essential for activation of the NF-κB and JNK signaling pathways in lymphocytes. In this work, by using human epithelial and lymphocytic cell lines, we identified the TNF-receptor-associated factor (TRAF) proteins TRAF3 and TRAF7 as new binding partners of Bcl10 and Carma1, respectively. We could show that TRAF3 is required for the proper transcriptional upregulation of IL-2 in activated T cells, and that endogenous TRAF3 is recruited to Bcl10 following TCR engagement. Although the mechanisms used by TRAF3 to modulate the transcriptional activation of the IL-2 promoter are not elucidated, the stimulus-dependent association ofTRAF3 with its direct binding partner Bcl10 suggests that TRAF3 is regulating Bcl10 function in TCR-activated lymphocytes. We also demonstrated that TRAF7 acts as a negative regulator of Carma1-induced NFκB-and AP1-dependent transcription by overexpression in 293T cells. These data suggest that TRAF7 could contribute to the negative regulation of TCR-dependent Carma1 functions. Finally, we showed that Carma1 is processed upon antigen-receptor triggering in B and T cell lines, as well as in primary human CTLs, and that this processing is dependent on the proteolytic activity of Malt1. Collectively, this work contributes to describe new proteins and regulatory mechanisms that modulate CBM-dependent functions in activated lymphocytes. Furthermore, it uncovers new tracks that could lead to a better molecular understanding of the complex interplay between the activatory and inhibitory regulators associated with the CBM complex. Résumé : L'activation des lymphocytes T naifs est une étape essentielle à la mise en place d'une réponse immunitaire adaptative pour combattre une infection. Après la détection d'un pathogène, les cellules présentatrices d'antigènes exposent à leur surface des fragments peptidiques provenant du pathogène, qui activent le récepteur à antigène (TCR) spécifique des lymphocytes T, ainsi que des molécules co-stimulatrices qui contribuent à l'activation complète des lymphocytes T. La caractérisation des mécanismes qui modulent les cascades de signaux émanant du TCR et des récepteurs de co-stimulation est essentielle à la compréhension du fonctionnement moléculaire de la réponse immunitaire adaptative. La ligation du TCR induit la formation d'un complexe oligomérique comprenant les protéines Carma1, Bcl10 et Malt1, qui est essentiel à l'activation des voies de signalisation cellulaires NF-κB et JNK induisant l'activation complète des lymphorctes T. Dans cette étude, à l'aide de lignées de cellules humaines épithéliales et lymphocytaires, nous avons identifié que deux protéines de la famille des TRAF (Tumor Necrosis Factor Receptor-Associated Factor), TRAF3 et TRAF7, s'associent à Bc110 et à Carma1, respectivement. Les TRAFs sont d'importants régulateurs des voies de signalisation dans les cellules du système immunitaire inné et adaptatif. Nous avons démontré que TRAF3 était important pour permettre la transcription de l'interleukine-2 (IL-2) dans les lymphocytes T activés, et que TRAF3 s'associait à Bc110 à la suite de la stimulation du TCR Les mécanismes que TRAF3 utilise pour moduler l'activation du promoteur de l'IL-2 ne sont pas connus, mais l'association de TRAF3 à Bc110 suite à la stimulation du TCR suggère que TRAF3 régule la fonction de Bc110. Nous avons également identifié TRAF7 comme un nouveau régulateur négatif des voies NF-κB et JNK induites par surexpression de la protéine Carma1. Nos données suggèrent que TRAF7 pourrait également contribuer à la régulation négative de la fonction de Carma1 dans les lymphocytes activés. Enfin, nous avons découvert que Carma1 était clivé suite à la stimulation du TCR, et que ce clivage dépendait de l'activité protéolytique de Malt1. Cette étude contribue ainsi à la description de nouvelles protéines et de nouveaux mécanismes qui modulent l'activité du complexe CBM dans les lymphocytes activés, et ouvre la voie à la caractérisation moléculaire de ces nouveaux mécanismes importants pour la régulation de la réponse immunitaire adaptative.