Many-to-one form-to-function mapping weakens parallel morphological evolution.

PubMed

Thompson, Cole J; Ahmed, Newaz I; Veen, Thor; Peichel, Catherine L; Hendry, Andrew P; Bolnick, Daniel I; Stuart, Yoel E

2017-11-01

Evolutionary ecologists aim to explain and predict evolutionary change under different selective regimes. Theory suggests that such evolutionary prediction should be more difficult for biomechanical systems in which different trait combinations generate the same functional output: "many-to-one mapping." Many-to-one mapping of phenotype to function enables multiple morphological solutions to meet the same adaptive challenges. Therefore, many-to-one mapping should undermine parallel morphological evolution, and hence evolutionary predictability, even when selection pressures are shared among populations. Studying 16 replicate pairs of lake- and stream-adapted threespine stickleback (Gasterosteus aculeatus), we quantified three parts of the teleost feeding apparatus and used biomechanical models to calculate their expected functional outputs. The three feeding structures differed in their form-to-function relationship from one-to-one (lower jaw lever ratio) to increasingly many-to-one (buccal suction index, opercular 4-bar linkage). We tested for (1) weaker linear correlations between phenotype and calculated function, and (2) less parallel evolution across lake-stream pairs, in the many-to-one systems relative to the one-to-one system. We confirm both predictions, thus supporting the theoretical expectation that increasing many-to-one mapping undermines parallel evolution. Therefore, sole consideration of morphological variation within and among populations might not serve as a proxy for functional variation when multiple adaptive trait combinations exist. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Growing up with Down syndrome: Development from 6 months to 10.7 years.

PubMed

Marchal, Jan Pieter; Maurice-Stam, Heleen; Houtzager, Bregje A; Rutgers van Rozenburg-Marres, Susanne L; Oostrom, Kim J; Grootenhuis, Martha A; van Trotsenburg, A S Paul

2016-12-01

We analysed developmental outcomes from a clinical trial early in life and its follow-up at 10.7 years in 123 children with Down syndrome. To determine 1) strengths and weaknesses in adaptive functioning and motor skills at 10.7 years, and 2) prognostic value of early-life characteristics (early developmental outcomes, parental and child characteristics, and comorbidity) for later intelligence, adaptive functioning and motor skills. We used standardized assessments of mental and motor development at ages 6, 12 and 24 months, and of intelligence, adaptive functioning and motor skills at 10.7 years. We compared strengths and weaknesses in adaptive functioning and motor skills by repeated-measures ANOVAs in the total group and in children scoring above-average versus below-average. The prognostic value of demographics, comorbidity and developmental outcomes was analysed by two-step regression. Socialisation was a stronger adaptive skill than Communication followed by Daily Living. Aiming and catching was a stronger motor skill than Manual dexterity, followed by Balance. Above-average and below-average scoring children showed different profiles of strengths and weaknesses. Gender, (the absence or presence of) infantile spasms and particularly 24-month mental functioning predicted later intelligence and adaptive functioning. Motor skills, however, appeared to be less well predicted by early life characteristics. These findings provide a reference for expected developmental levels and strengths and weaknesses in Down syndrome. Copyright © 2016 Elsevier Ltd. All rights reserved.

Genetic algorithm based adaptive neural network ensemble and its application in predicting carbon flux

USGS Publications Warehouse

Xue, Y.; Liu, S.; Hu, Y.; Yang, J.; Chen, Q.

2007-01-01

To improve the accuracy in prediction, Genetic Algorithm based Adaptive Neural Network Ensemble (GA-ANNE) is presented. Intersections are allowed between different training sets based on the fuzzy clustering analysis, which ensures the diversity as well as the accuracy of individual Neural Networks (NNs). Moreover, to improve the accuracy of the adaptive weights of individual NNs, GA is used to optimize the cluster centers. Empirical results in predicting carbon flux of Duke Forest reveal that GA-ANNE can predict the carbon flux more accurately than Radial Basis Function Neural Network (RBFNN), Bagging NN ensemble, and ANNE. ?? 2007 IEEE.

Predictive Models for Regional Hepatic Function Based on 99mTc-IDA SPECT and Local Radiation Dose for Physiologic Adaptive Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Hesheng, E-mail: hesheng@umich.edu; Feng, Mary; Frey, Kirk A.

2013-08-01

Purpose: High-dose radiation therapy (RT) for intrahepatic cancer is limited by the development of liver injury. This study investigated whether regional hepatic function assessed before and during the course of RT using 99mTc-labeled iminodiacetic acid (IDA) single photon emission computed tomography (SPECT) could predict regional liver function reserve after RT. Methods and Materials: Fourteen patients treated with RT for intrahepatic cancers underwent dynamic 99mTc-IDA SPECT scans before RT, during, and 1 month after completion of RT. Indocyanine green (ICG) tests, a measure of overall liver function, were performed within 1 day of each scan. Three-dimensional volumetric hepatic extraction fraction (HEF)more » images of the liver were estimated by deconvolution analysis. After coregistration of the CT/SPECT and the treatment planning CT, HEF dose–response functions during and after RT were generated. The volumetric mean of the HEFs in the whole liver was correlated with ICG clearance time. Three models, dose, priori, and adaptive models, were developed using multivariate linear regression to assess whether the regional HEFs measured before and during RT helped predict regional hepatic function after RT. Results: The mean of the volumetric liver HEFs was significantly correlated with ICG clearance half-life time (r=−0.80, P<.0001), for all time points. Linear correlations between local doses and regional HEFs 1 month after RT were significant in 12 patients. In the priori model, regional HEF after RT was predicted by the planned dose and regional HEF assessed before RT (R=0.71, P<.0001). In the adaptive model, regional HEF after RT was predicted by regional HEF reassessed during RT and the remaining planned local dose (R=0.83, P<.0001). Conclusions: 99mTc-IDA SPECT obtained during RT could be used to assess regional hepatic function and helped predict post-RT regional liver function reserve. This could support individualized adaptive radiation treatment strategies to maximize tumor control and minimize the risk of liver damage.« less

Predictive models for regional hepatic function based on 99mTc-IDA SPECT and local radiation dose for physiologic adaptive radiation therapy.

PubMed

Wang, Hesheng; Feng, Mary; Frey, Kirk A; Ten Haken, Randall K; Lawrence, Theodore S; Cao, Yue

2013-08-01

High-dose radiation therapy (RT) for intrahepatic cancer is limited by the development of liver injury. This study investigated whether regional hepatic function assessed before and during the course of RT using 99mTc-labeled iminodiacetic acid (IDA) single photon emission computed tomography (SPECT) could predict regional liver function reserve after RT. Fourteen patients treated with RT for intrahepatic cancers underwent dynamic 99mTc-IDA SPECT scans before RT, during, and 1 month after completion of RT. Indocyanine green (ICG) tests, a measure of overall liver function, were performed within 1 day of each scan. Three-dimensional volumetric hepatic extraction fraction (HEF) images of the liver were estimated by deconvolution analysis. After coregistration of the CT/SPECT and the treatment planning CT, HEF dose-response functions during and after RT were generated. The volumetric mean of the HEFs in the whole liver was correlated with ICG clearance time. Three models, dose, priori, and adaptive models, were developed using multivariate linear regression to assess whether the regional HEFs measured before and during RT helped predict regional hepatic function after RT. The mean of the volumetric liver HEFs was significantly correlated with ICG clearance half-life time (r=-0.80, P<.0001), for all time points. Linear correlations between local doses and regional HEFs 1 month after RT were significant in 12 patients. In the priori model, regional HEF after RT was predicted by the planned dose and regional HEF assessed before RT (R=0.71, P<.0001). In the adaptive model, regional HEF after RT was predicted by regional HEF reassessed during RT and the remaining planned local dose (R=0.83, P<.0001). 99mTc-IDA SPECT obtained during RT could be used to assess regional hepatic function and helped predict post-RT regional liver function reserve. This could support individualized adaptive radiation treatment strategies to maximize tumor control and minimize the risk of liver damage. Published by Elsevier Inc.

Predicting Adaptive Functioning of Mentally Retarded Persons in Community Settings.

ERIC Educational Resources Information Center

Hull, John T.; Thompson, Joy C.

1980-01-01

The impact of a variety of individual, residential, and community variables on adaptive functioning of 369 retarded persons (18 to 73 years old) was examined using a multiple regression analysis. Individual characteristics (especially IQ) accounted for 21 percent of the variance, while environmental variables, primarily those related to…

Spatial segregation of adaptation and predictive sensitization in retinal ganglion cells

PubMed Central

Kastner, David B.; Baccus, Stephen A.

2014-01-01

Sensory systems change their sensitivity based upon recent stimuli to adjust their response range to the range of inputs, and to predict future sensory input. Here we report the presence of retinal ganglion cells that have antagonistic plasticity, showing central adaptation and peripheral sensitization. Ganglion cell responses were captured by a spatiotemporal model with independently adapting excitatory and inhibitory subunits, and sensitization requires GABAergic inhibition. Using a simple theory of signal detection we show that the sensitizing surround conforms to an optimal inference model that continually updates the prior signal probability. This indicates that small receptive field regions have dual functionality—to adapt to the local range of signals, but sensitize based upon the probability of the presence of that signal. Within this framework, we show that sensitization predicts the location of a nearby object, revealing prediction as a new functional role for adapting inhibition in the nervous system. PMID:23932000

Low Boom Configuration Analysis with FUN3D Adjoint Simulation Framework

NASA Technical Reports Server (NTRS)

Park, Michael A.

2011-01-01

Off-body pressure, forces, and moments for the Gulfstream Low Boom Model are computed with a Reynolds Averaged Navier Stokes solver coupled with the Spalart-Allmaras (SA) turbulence model. This is the first application of viscous output-based adaptation to reduce estimated discretization errors in off-body pressure for a wing body configuration. The output adaptation approach is compared to an a priori grid adaptation technique designed to resolve the signature on the centerline by stretching and aligning the grid to the freestream Mach angle. The output-based approach produced good predictions of centerline and off-centerline measurements. Eddy viscosity predicted by the SA turbulence model increased significantly with grid adaptation. Computed lift as a function of drag compares well with wind tunnel measurements for positive lift, but predicted lift, drag, and pitching moment as a function of angle of attack has significant differences from the measured data. The sensitivity of longitudinal forces and moment to grid refinement is much smaller than the differences between the computed and measured data.

Dopamine Modulates Adaptive Prediction Error Coding in the Human Midbrain and Striatum.

PubMed

Diederen, Kelly M J; Ziauddeen, Hisham; Vestergaard, Martin D; Spencer, Tom; Schultz, Wolfram; Fletcher, Paul C

2017-02-15

Learning to optimally predict rewards requires agents to account for fluctuations in reward value. Recent work suggests that individuals can efficiently learn about variable rewards through adaptation of the learning rate, and coding of prediction errors relative to reward variability. Such adaptive coding has been linked to midbrain dopamine neurons in nonhuman primates, and evidence in support for a similar role of the dopaminergic system in humans is emerging from fMRI data. Here, we sought to investigate the effect of dopaminergic perturbations on adaptive prediction error coding in humans, using a between-subject, placebo-controlled pharmacological fMRI study with a dopaminergic agonist (bromocriptine) and antagonist (sulpiride). Participants performed a previously validated task in which they predicted the magnitude of upcoming rewards drawn from distributions with varying SDs. After each prediction, participants received a reward, yielding trial-by-trial prediction errors. Under placebo, we replicated previous observations of adaptive coding in the midbrain and ventral striatum. Treatment with sulpiride attenuated adaptive coding in both midbrain and ventral striatum, and was associated with a decrease in performance, whereas bromocriptine did not have a significant impact. Although we observed no differential effect of SD on performance between the groups, computational modeling suggested decreased behavioral adaptation in the sulpiride group. These results suggest that normal dopaminergic function is critical for adaptive prediction error coding, a key property of the brain thought to facilitate efficient learning in variable environments. Crucially, these results also offer potential insights for understanding the impact of disrupted dopamine function in mental illness. SIGNIFICANCE STATEMENT To choose optimally, we have to learn what to expect. Humans dampen learning when there is a great deal of variability in reward outcome, and two brain regions that are modulated by the brain chemical dopamine are sensitive to reward variability. Here, we aimed to directly relate dopamine to learning about variable rewards, and the neural encoding of associated teaching signals. We perturbed dopamine in healthy individuals using dopaminergic medication and asked them to predict variable rewards while we made brain scans. Dopamine perturbations impaired learning and the neural encoding of reward variability, thus establishing a direct link between dopamine and adaptation to reward variability. These results aid our understanding of clinical conditions associated with dopaminergic dysfunction, such as psychosis. Copyright © 2017 Diederen et al.

Family functioning mediates adaptation in caregivers of individuals with Rett syndrome.

PubMed

Lamb, Amanda E; Biesecker, Barbara B; Umstead, Kendall L; Muratori, Michelle; Biesecker, Leslie G; Erby, Lori H

2016-11-01

The objective of this study was to investigate factors related to family functioning and adaptation in caregivers of individuals with Rett syndrome (RS). A cross-sectional quantitative survey explored the relationships between demographics, parental self-efficacy, coping methods, family functioning and adaptation. A forward-backward, step-wise model selection procedure was used to evaluate variables associated with both family functioning and adaptation. Analyses also explored family functioning as a mediator of the relationship between other variables and adaptation. Bivariate analyses (N=400) revealed that greater parental self-efficacy, a greater proportion of problem-focused coping, and a lesser proportion of emotion-focused coping were associated with more effective family functioning. In addition, these key variables were significantly associated with greater adaptation, as was family functioning, while controlling for confounders. Finally, regression analyses suggest family functioning as a mediator of the relationships between three variables (parental self-efficacy, problem-focused coping, and emotion-focused coping) with adaptation. This study demonstrates the potentially predictive roles of expectations and coping methods and the mediator role of family functioning in adaptation among caregivers of individuals with RS, a chronic developmental disorder. A potential target for intervention is strengthening of caregiver competence in the parenting role to enhance caregiver adaptation. Published by Elsevier Ireland Ltd.

Associations between conceptual reasoning, problem solving, and adaptive ability in high-functioning autism.

PubMed

Williams, Diane L; Mazefsky, Carla A; Walker, Jon D; Minshew, Nancy J; Goldstein, Gerald

2014-11-01

Abstract thinking is generally highly correlated with problem-solving ability which is predictive of better adaptive functioning. Measures of conceptual reasoning, an ecologically-valid laboratory measure of problem-solving, and a report measure of adaptive functioning in the natural environment, were administered to children and adults with and without autism. The individuals with autism had weaker conceptual reasoning ability than individuals with typical development of similar age and cognitive ability. For the autism group, their flexible thinking scores were significantly correlated with laboratory measures of strategy formation and rule shifting and with reported overall adaptive behavior but not socialization scores. Therefore, in autism, flexibility of thought is potentially more important for adaptive functioning in the natural environment than conceptual reasoning or problem-solving.

Model-driven discovery of underground metabolic functions in Escherichia coli.

PubMed

Guzmán, Gabriela I; Utrilla, José; Nurk, Sergey; Brunk, Elizabeth; Monk, Jonathan M; Ebrahim, Ali; Palsson, Bernhard O; Feist, Adam M

2015-01-20

Enzyme promiscuity toward substrates has been discussed in evolutionary terms as providing the flexibility to adapt to novel environments. In the present work, we describe an approach toward exploring such enzyme promiscuity in the space of a metabolic network. This approach leverages genome-scale models, which have been widely used for predicting growth phenotypes in various environments or following a genetic perturbation; however, these predictions occasionally fail. Failed predictions of gene essentiality offer an opportunity for targeting biological discovery, suggesting the presence of unknown underground pathways stemming from enzymatic cross-reactivity. We demonstrate a workflow that couples constraint-based modeling and bioinformatic tools with KO strain analysis and adaptive laboratory evolution for the purpose of predicting promiscuity at the genome scale. Three cases of genes that are incorrectly predicted as essential in Escherichia coli--aspC, argD, and gltA--are examined, and isozyme functions are uncovered for each to a different extent. Seven isozyme functions based on genetic and transcriptional evidence are suggested between the genes aspC and tyrB, argD and astC, gabT and puuE, and gltA and prpC. This study demonstrates how a targeted model-driven approach to discovery can systematically fill knowledge gaps, characterize underground metabolism, and elucidate regulatory mechanisms of adaptation in response to gene KO perturbations.

AptRank: an adaptive PageRank model for protein function prediction on   bi-relational graphs.

PubMed

Jiang, Biaobin; Kloster, Kyle; Gleich, David F; Gribskov, Michael

2017-06-15

Diffusion-based network models are widely used for protein function prediction using protein network data and have been shown to outperform neighborhood-based and module-based methods. Recent studies have shown that integrating the hierarchical structure of the Gene Ontology (GO) data dramatically improves prediction accuracy. However, previous methods usually either used the GO hierarchy to refine the prediction results of multiple classifiers, or flattened the hierarchy into a function-function similarity kernel. No study has taken the GO hierarchy into account together with the protein network as a two-layer network model. We first construct a Bi-relational graph (Birg) model comprised of both protein-protein association and function-function hierarchical networks. We then propose two diffusion-based methods, BirgRank and AptRank, both of which use PageRank to diffuse information on this two-layer graph model. BirgRank is a direct application of traditional PageRank with fixed decay parameters. In contrast, AptRank utilizes an adaptive diffusion mechanism to improve the performance of BirgRank. We evaluate the ability of both methods to predict protein function on yeast, fly and human protein datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA. We design four different validation strategies: missing function prediction, de novo function prediction, guided function prediction and newly discovered function prediction to comprehensively evaluate predictability of all six methods. We find that both BirgRank and AptRank outperform the previous methods, especially in missing function prediction when using only 10% of the data for training. The MATLAB code is available at https://github.rcac.purdue.edu/mgribsko/aptrank . gribskov@purdue.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

More About Vector Adaptive/Predictive Coding Of Speech

NASA Technical Reports Server (NTRS)

Jedrey, Thomas C.; Gersho, Allen

1992-01-01

Report presents additional information about digital speech-encoding and -decoding system described in "Vector Adaptive/Predictive Encoding of Speech" (NPO-17230). Summarizes development of vector adaptive/predictive coding (VAPC) system and describes basic functions of algorithm. Describes refinements introduced enabling receiver to cope with errors. VAPC algorithm implemented in integrated-circuit coding/decoding processors (codecs). VAPC and other codecs tested under variety of operating conditions. Tests designed to reveal effects of various background quiet and noisy environments and of poor telephone equipment. VAPC found competitive with and, in some respects, superior to other 4.8-kb/s codecs and other codecs of similar complexity.

Adolescent Attachment Security, Family Functioning, and Suicide Attempts

PubMed Central

Sheftall, Arielle H.; Mathias, Charles W.; Furr, R. Michael; Dougherty, Donald M.

2013-01-01

Theories of suicidal behavior suggest that the desire to die can arise from disruption of interpersonal relationships. Suicide research has typically studied this from the individual's perspective of the quality/frequency of their social interactions; however, the field of attachment may offer another perspective on understanding an individual’s social patterns and suicide risk. This study examined attachment along with broader family functioning (family adaptability and cohesion) among 236 adolescent psychiatric inpatients with (n = 111) and without (n = 125) histories of suicide attempts. On average, adolescents were 14 years of age and Hispanic (69%). Compared to those without suicide attempts, adolescent attempters had lower self-reported maternal and paternal attachment and lower familial adaptability and cohesion. When comparing all 3 types of attachment simultaneously in the logistic regression model predicting suicide attempt status, paternal attachment was the only significant predictor. Suicide attempt group was also significantly predicted by self-rated Cohesion and Adaptability; neither of the parent ratings of family functioning were significant predictors. These findings are consistent with the predictions of the Interpersonal Theory of Suicide about social functioning and support the efforts to develop attachment-based interventions as a novel route towards suicide prevention. PMID:23560608

Adolescent attachment security, family functioning, and suicide attempts.

PubMed

Sheftall, Arielle H; Mathias, Charles W; Furr, R Michael; Dougherty, Donald M

2013-01-01

Theories of suicidal behavior suggest that the desire to die can arise from disruption of interpersonal relationships. Suicide research has typically studied this from the individual's perspective of the quality/frequency of their social interactions; however, the field of attachment may offer another perspective on understanding an individual's social patterns and suicide risk. This study examined attachment along with broader family functioning (family adaptability and cohesion) among 236 adolescent psychiatric inpatients with (n = 111) and without (n = 125) histories of suicide attempts. On average, adolescents were 14 years of age and Hispanic (69%). Compared to those without suicide attempts, adolescent attempters had lower self-reported maternal and paternal attachment and lower familial adaptability and cohesion. When comparing all three types of attachment simultaneously in the logistic regression model predicting suicide attempt status, paternal attachment was the only significant predictor. Suicide attempt group was also significantly predicted by self-rated Cohesion and Adaptability; neither of the parent ratings of family functioning were significant predictors. These findings are consistent with the predictions of the Interpersonal Theory of Suicide about social functioning and support the efforts to develop attachment-based interventions as a novel route towards suicide prevention.

[Adaptive behaviour and learning in children with neurodevelopmental disorders (autism spectrum disorders and attention deficit hyperactivity disorder). Effects of executive functioning].

PubMed

Rosello-Miranda, B; Berenguer-Forner, C; Miranda-Casas, A

2018-03-01

Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) present difficulties in adaptive functioning and learning, possibly associated with failures in executive functioning characteristic of both disorders. To analyze the impact of executive functioning in the adaptive behaviors of socialization and daily life and in learning behaviors in children with ASD and children with ADHD. The participants were 124 children matched in age and intellectual quotient: 37 children with typical development, 52 children with ASD and 35 children with ADHD. Parents reported on their children's adaptive behaviors, while teachers provided information on learning behaviors and executive functioning in daily life. There are significant differences between the groups with ASD and ADHD with the typical development group in all domains evaluated. In addition, the group with ASD had worse socialization skills while persistence in learning was more affected in children with ADHD. Finally, the metacognitive index of executive functioning predicted the socialization and persistence of children with ASD. On the other hand, the index of behavioral regulation and the educational level of the parents predicted the socialization skills in children with ADHD. The results highlight the need to include differentiated executive strategies in the intervention of children with ASD and children with ADHD.

A novel and simple test of gait adaptability predicts gold standard measures of functional mobility in stroke survivors.

PubMed

Hollands, K L; Pelton, T A; van der Veen, S; Alharbi, S; Hollands, M A

2016-01-01

Although there is evidence that stroke survivors have reduced gait adaptability, the underlying mechanisms and the relationship to functional recovery are largely unknown. We explored the relationships between walking adaptability and clinical measures of balance, motor recovery and functional ability in stroke survivors. Stroke survivors (n=42) stepped to targets, on a 6m walkway, placed to elicit step lengthening, shortening and narrowing on paretic and non-paretic sides. The number of targets missed during six walks and target stepping speed was recorded. Fugl-Meyer (FM), Berg Balance Scale (BBS), self-selected walking speed (SWWS) and single support (SS) and step length (SL) symmetry (using GaitRite when not walking to targets) were also assessed. Stepwise multiple-linear regression was used to model the relationships between: total targets missed, number missed with paretic and non-paretic legs, target stepping speed, and each clinical measure. Regression revealed a significant model for each outcome variable that included only one independent variable. Targets missed by the paretic limb, was a significant predictor of FM (F(1,40)=6.54, p=0.014,). Speed of target stepping was a significant predictor of each of BBS (F(1,40)=26.36, p<0.0001), SSWS (F(1,40)=37.00, p<0.0001). No variables were significant predictors of SL or SS asymmetry. Speed of target stepping was significantly predictive of BBS and SSWS and paretic targets missed predicted FM, suggesting that fast target stepping requires good balance and accurate stepping demands good paretic leg function. The relationships between these parameters indicate gait adaptability is a clinically meaningful target for measurement and treatment of functionally adaptive walking ability in stroke survivors. Copyright © 2015 Elsevier B.V. All rights reserved.

Examining health-related quality of life, adaptive skills, and psychological functioning in children and adolescents with epilepsy presenting for a neuropsychological evaluation.

PubMed

Clary, Lauren E; Vander Wal, Jillon S; Titus, Jeffrey B

2010-11-01

The purpose of this study was to characterize 132 children and adolescents (mean age = 10 years, 11 months) with epilepsy in terms of psychosocial functioning and to determine the extent to which adaptive skills and psychological functioning predict health-related quality of life (HRQOL), above and beyond demographic and epilepsy-specific characteristics. A chart review was conducted to obtain demographic and epilepsy-specific information as well as caregiver responses on the Behavior Assessment System for Children, Second Edition (BASC-2) Parent Report and the Quality of Life in Childhood Epilepsy Questionnaire (QOLCE). In addition to Full Scale IQ and age at seizure onset, the BASC-2 Clinical and Adaptive Skills subscales also predicted HRQOL, indicating that this measure may be particularly helpful in predicting HRQOL above and beyond information routinely collected in a medical setting. It is imperative to evaluate children with epilepsy for psychosocial difficulties and diminished HRQOL to ensure the provision of comprehensive quality care and intervention services. Copyright © 2010 Elsevier Inc. All rights reserved.

Remembering forward: Neural correlates of memory and prediction in human motor adaptation

PubMed Central

Scheidt, Robert A; Zimbelman, Janice L; Salowitz, Nicole M G; Suminski, Aaron J; Mosier, Kristine M; Houk, James; Simo, Lucia

2011-01-01

We used functional MR imaging (FMRI), a robotic manipulandum and systems identification techniques to examine neural correlates of predictive compensation for spring-like loads during goal-directed wrist movements in neurologically-intact humans. Although load changed unpredictably from one trial to the next, subjects nevertheless used sensorimotor memories from recent movements to predict and compensate upcoming loads. Prediction enabled subjects to adapt performance so that the task was accomplished with minimum effort. Population analyses of functional images revealed a distributed, bilateral network of cortical and subcortical activity supporting predictive load compensation during visual target capture. Cortical regions - including prefrontal, parietal and hippocampal cortices - exhibited trial-by-trial fluctuations in BOLD signal consistent with the storage and recall of sensorimotor memories or “states” important for spatial working memory. Bilateral activations in associative regions of the striatum demonstrated temporal correlation with the magnitude of kinematic performance error (a signal that could drive reward-optimizing reinforcement learning and the prospective scaling of previously learned motor programs). BOLD signal correlations with load prediction were observed in the cerebellar cortex and red nuclei (consistent with the idea that these structures generate adaptive fusimotor signals facilitating cancellation of expected proprioceptive feedback, as required for conditional feedback adjustments to ongoing motor commands and feedback error learning). Analysis of single subject images revealed that predictive activity was at least as likely to be observed in more than one of these neural systems as in just one. We conclude therefore that motor adaptation is mediated by predictive compensations supported by multiple, distributed, cortical and subcortical structures. PMID:21840405

Adjoint-Based, Three-Dimensional Error Prediction and Grid Adaptation

NASA Technical Reports Server (NTRS)

Park, Michael A.

2002-01-01

Engineering computational fluid dynamics (CFD) analysis and design applications focus on output functions (e.g., lift, drag). Errors in these output functions are generally unknown and conservatively accurate solutions may be computed. Computable error estimates can offer the possibility to minimize computational work for a prescribed error tolerance. Such an estimate can be computed by solving the flow equations and the linear adjoint problem for the functional of interest. The computational mesh can be modified to minimize the uncertainty of a computed error estimate. This robust mesh-adaptation procedure automatically terminates when the simulation is within a user specified error tolerance. This procedure for estimating and adapting to error in a functional is demonstrated for three-dimensional Euler problems. An adaptive mesh procedure that links to a Computer Aided Design (CAD) surface representation is demonstrated for wing, wing-body, and extruded high lift airfoil configurations. The error estimation and adaptation procedure yielded corrected functions that are as accurate as functions calculated on uniformly refined grids with ten times as many grid points.

φ-evo: A program to evolve phenotypic models of biological networks.

PubMed

Henry, Adrien; Hemery, Mathieu; François, Paul

2018-06-01

Molecular networks are at the core of most cellular decisions, but are often difficult to comprehend. Reverse engineering of network architecture from their functions has proved fruitful to classify and predict the structure and function of molecular networks, suggesting new experimental tests and biological predictions. We present φ-evo, an open-source program to evolve in silico phenotypic networks performing a given biological function. We include implementations for evolution of biochemical adaptation, adaptive sorting for immune recognition, metazoan development (somitogenesis, hox patterning), as well as Pareto evolution. We detail the program architecture based on C, Python 3, and a Jupyter interface for project configuration and network analysis. We illustrate the predictive power of φ-evo by first recovering the asymmetrical structure of the lac operon regulation from an objective function with symmetrical constraints. Second, we use the problem of hox-like embryonic patterning to show how a single effective fitness can emerge from multi-objective (Pareto) evolution. φ-evo provides an efficient approach and user-friendly interface for the phenotypic prediction of networks and the numerical study of evolution itself.

Constraint shapes convergence in tetrodotoxin-resistant sodium channels of snakes.

PubMed

Feldman, Chris R; Brodie, Edmund D; Brodie, Edmund D; Pfrender, Michael E

2012-03-20

Natural selection often produces convergent changes in unrelated lineages, but the degree to which such adaptations occur via predictable genetic paths is unknown. If only a limited subset of possible mutations is fixed in independent lineages, then it is clear that constraint in the production or function of molecular variants is an important determinant of adaptation. We demonstrate remarkably constrained convergence during the evolution of resistance to the lethal poison, tetrodotoxin, in six snake species representing three distinct lineages from around the globe. Resistance-conferring amino acid substitutions in a voltage-gated sodium channel, Na(v)1.4, are clustered in only two regions of the protein, and a majority of the replacements are confined to the same three positions. The observed changes represent only a small fraction of the experimentally validated mutations known to increase Na(v)1.4 resistance to tetrodotoxin. These results suggest that constraints resulting from functional tradeoffs between ion channel function and toxin resistance led to predictable patterns of evolutionary convergence at the molecular level. Our data are consistent with theoretical predictions and recent microcosm work that suggest a predictable path is followed during an adaptive walk along a mutational landscape, and that natural selection may be frequently constrained to produce similar genetic outcomes even when operating on independent lineages.

Adaptation, acclimation, and assembly: How optimality principles govern the scaling of form, function, and diversity of ecosystem function in the light of climate change.

NASA Astrophysics Data System (ADS)

Enquist, B. J.

2016-12-01

The link between variation in species-specific traits - due to acclimation, adaptation, and how ecological communities assemble in time and space - and larger scale ecosystem processes is an important focus for global change research. Understanding such linkages requires synthesis of evolutionary, biogeograpahic, and biogeochemical approaches. Recent observations reveal several paradoxical patterns across ecosystems. Optimality principles provide a novel framework for generating numerous predictions for how ecosystems have and will reorganize and respond to climate change. Tropical elevation gradients are natural laboratories to assess how changing climate can ramify to influence tropical forest diversity and ecosystem functioning. We tested several new predictions from trait- and metabolic scaling theories by assessing the covariation between climate, traits, biomass and gross and net primary productivity (GPP and NPP) across tropical forest plots spanning elevation gradients. We measured multiple leaf physiological, morphological, and stoichiometric traits linked to variation in tree growth. Consistent with theory, observed decreases in NPP and GPP with temperature were best predicted by forest biomass, and scaled allometrically as predicted by theory but the effect of temperature was much less, characterized by a kinetic response much lower ( 0.1eV) than predicted ( 0.65eV). This is likely due to an observed exponential increase in the mean community leaf P:N ratio and photosynthetic nutrient use efficiency with decreases in temperature. Our results are consistent with predictions from Trait Driver Theory, where adaptive/acclamatory shifts in plant traits compensate for the kinetic effects of temperature on tree growth. Further, most of the traits measured showed significantly skewed trait distributions consistent with recent observations that observed shifts in species composition. The development of trait-based scaling theory provides a robust basis to predict how shifts in climate have and will influence functional composition and ecosystem functioning. Together, these results highlight the potential critical importance optimality principles for understanding the role of the biosphere within the integrated earth system.

Information theory of adaptation in neurons, behavior, and mood.

PubMed

Sharpee, Tatyana O; Calhoun, Adam J; Chalasani, Sreekanth H

2014-04-01

The ability to make accurate predictions of future stimuli and consequences of one's actions are crucial for the survival and appropriate decision-making. These predictions are constantly being made at different levels of the nervous system. This is evidenced by adaptation to stimulus parameters in sensory coding, and in learning of an up-to-date model of the environment at the behavioral level. This review will discuss recent findings that actions of neurons and animals are selected based on detailed stimulus history in such a way as to maximize information for achieving the task at hand. Information maximization dictates not only how sensory coding should adapt to various statistical aspects of stimuli, but also that reward function should adapt to match the predictive information from past to future. Copyright © 2013 Elsevier Ltd. All rights reserved.

Neural mechanisms underlying spatial realignment during adaptation to optical wedge prisms.

PubMed

Chapman, Heidi L; Eramudugolla, Ranmalee; Gavrilescu, Maria; Strudwick, Mark W; Loftus, Andrea; Cunnington, Ross; Mattingley, Jason B

2010-07-01

Visuomotor adaptation to a shift in visual input produced by prismatic lenses is an example of dynamic sensory-motor plasticity within the brain. Prism adaptation is readily induced in healthy individuals, and is thought to reflect the brain's ability to compensate for drifts in spatial calibration between different sensory systems. The neural correlate of this form of functional plasticity is largely unknown, although current models predict the involvement of parieto-cerebellar circuits. Recent studies that have employed event-related functional magnetic resonance imaging (fMRI) to identify brain regions associated with prism adaptation have discovered patterns of parietal and cerebellar modulation as participants corrected their visuomotor errors during the early part of adaptation. However, the role of these regions in the later stage of adaptation, when 'spatial realignment' or true adaptation is predicted to occur, remains unclear. Here, we used fMRI to quantify the distinctive patterns of parieto-cerebellar activity as visuomotor adaptation develops. We directly contrasted activation patterns during the initial error correction phase of visuomotor adaptation with that during the later spatial realignment phase, and found significant recruitment of the parieto-cerebellar network--with activations in the right inferior parietal lobe and the right posterior cerebellum. These findings provide the first evidence of both cerebellar and parietal involvement during the spatial realignment phase of prism adaptation. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

A Further Look at the Prognostic Power of Young Children's Reports of Depressed Mood and Feelings.

ERIC Educational Resources Information Center

Ialongo, Nicholas S.; Edelsohn, Gail; Kellam, Sheppard G.

2001-01-01

Examined the predictive validity of urban first-graders' self-reports of depressed mood and feelings with respect to later psychopathology and adaptive functioning. Found that subjects' self-reports of depressed mood predicted later academic functioning, the need for and use of mental health services, suicidal ideation, and major depressive…

Classification of intellectual disability using the Wechsler Intelligence Scale for Children: Full Scale IQ or General Abilities Index?

PubMed

Koriakin, Taylor A; McCurdy, Mark D; Papazoglou, Aimilia; Pritchard, Alison E; Zabel, T Andrew; Mahone, E Mark; Jacobson, Lisa A

2013-09-01

We examined the implications of using the Full Scale IQ (FSIQ) versus the General Abilities Index (GAI) for determination of intellectual disability using the Wechsler Intelligence Scales for Children, fourth edition (WISC-IV). Children referred for neuropsychological assessment (543 males, 290 females; mean age 10y 5mo, SD 2y 9mo, range 6-16y) were administered the WISC-IV and the Adaptive Behavior Assessment System, second edition (ABAS-II). GAI and FSIQ were highly correlated; however, fewer children were identified as having intellectual disability using GAI (n=159) than when using FSIQ (n=196). Although the 44 children classified as having intellectual disability based upon FSIQ (but not GAI) had significantly higher adaptive functioning scores than those meeting intellectual disability criteria based upon both FSIQ and GAI, mean adaptive scores still fell within the impaired range. FSIQ and GAI were comparable in predicting impairments in adaptive functioning. Using GAI rather than FSIQ in intellectual disability diagnostic decision-making resulted in fewer individuals being diagnosed with intellectual disability; however, the mean GAI of the disqualified individuals was at the upper end of criteria for intellectual impairment (standard score 75), and these individuals remained adaptively impaired. As GAI and FSIQ were similarly predictive of overall adaptive functioning, the use of GAI for intellectual disability diagnostic decision-making may be of limited value. © 2013 Mac Keith Press.

Exploring the read-write genome: mobile DNA and mammalian adaptation.

PubMed

Shapiro, James A

2017-02-01

The read-write genome idea predicts that mobile DNA elements will act in evolution to generate adaptive changes in organismal DNA. This prediction was examined in the context of mammalian adaptations involving regulatory non-coding RNAs, viviparous reproduction, early embryonic and stem cell development, the nervous system, and innate immunity. The evidence shows that mobile elements have played specific and sometimes major roles in mammalian adaptive evolution by generating regulatory sites in the DNA and providing interaction motifs in non-coding RNA. Endogenous retroviruses and retrotransposons have been the predominant mobile elements in mammalian adaptive evolution, with the notable exception of bats, where DNA transposons are the major agents of RW genome inscriptions. A few examples of independent but convergent exaptation of mobile DNA elements for similar regulatory rewiring functions are noted.

Adaptive radiation by waves of gene transfer leads to fine-scale resource partitioning in marine microbes

PubMed Central

Hehemann, Jan-Hendrik; Arevalo, Philip; Datta, Manoshi S.; Yu, Xiaoqian; Corzett, Christopher H.; Henschel, Andreas; Preheim, Sarah P.; Timberlake, Sonia; Alm, Eric J.; Polz, Martin F.

2016-01-01

Adaptive radiations are important drivers of niche filling, since they rapidly adapt a single clade of organisms to ecological opportunities. Although thought to be common for animals and plants, adaptive radiations have remained difficult to document for microbes in the wild. Here we describe a recent adaptive radiation leading to fine-scale ecophysiological differentiation in the degradation of an algal glycan in a clade of closely related marine bacteria. Horizontal gene transfer is the primary driver in the diversification of the pathway leading to several ecophysiologically differentiated Vibrionaceae populations adapted to different physical forms of alginate. Pathway architecture is predictive of function and ecology, underscoring that horizontal gene transfer without extensive regulatory changes can rapidly assemble fully functional pathways in microbes. PMID:27653556

A Combined Adaptive Neural Network and Nonlinear Model Predictive Control for Multirate Networked Industrial Process Control.

PubMed

Wang, Tong; Gao, Huijun; Qiu, Jianbin

2016-02-01

This paper investigates the multirate networked industrial process control problem in double-layer architecture. First, the output tracking problem for sampled-data nonlinear plant at device layer with sampling period T(d) is investigated using adaptive neural network (NN) control, and it is shown that the outputs of subsystems at device layer can track the decomposed setpoints. Then, the outputs and inputs of the device layer subsystems are sampled with sampling period T(u) at operation layer to form the index prediction, which is used to predict the overall performance index at lower frequency. Radial basis function NN is utilized as the prediction function due to its approximation ability. Then, considering the dynamics of the overall closed-loop system, nonlinear model predictive control method is proposed to guarantee the system stability and compensate the network-induced delays and packet dropouts. Finally, a continuous stirred tank reactor system is given in the simulation part to demonstrate the effectiveness of the proposed method.

Functional Abdominal Pain Patient Subtypes in Childhood Predict Functional Gastrointestinal Disorders with Chronic Pain and Psychiatric Comorbidities in Adolescence and Adulthood

PubMed Central

Walker, Lynn S.; Sherman, Amanda L.; Bruehl, Stephen; Garber, Judy; Smith, Craig A.

2012-01-01

Although pediatric functional abdominal pain (FAP) has been linked to abdominal pain later in life, childhood predictors of long-term outcomes have not been identified. This study evaluated whether distinct FAP profiles based on patterns of pain and adaptation in childhood could be identified and whether these profiles predicted differences in clinical outcomes and central sensitization (wind-up) on average 9 years later. In 843 pediatric FAP patients, cluster analysis was used to identify subgroups at initial FAP evaluation based on profiles of pain severity, gastrointestinal (GI) and non-GI symptoms, pain threat appraisal, pain coping efficacy, catastrophizing, negative affect, and activity impairment. Three profiles were identified: High Pain Dysfunctional, High Pain Adaptive, and Low Pain Adaptive. Logistic regression analyses controlling for age and sex showed that, compared to pediatric patients with the Low Pain Adaptive profile, those with the High Pain Dysfunctional profile were significantly more likely at long-term follow-up to meet criteria for pain-related functional gastrointestinal disorder (FGID) (OR: 3.45; CI: 1.95–6.11), FGID with comorbid non-abdominal chronic pain (OR: 2.6; CI:1.45–4.66), and FGID with comorbid anxiety or depressive psychiatric disorder (OR: 2.84; CI: 1.35–6.00). Pediatric patients with the High Pain Adaptive profile had baseline pain severity comparable to the High Pain Dysfunctional profile, but had outcomes as favorable as the Low Pain Adaptive profile. In laboratory pain testing at follow-up, High Pain Dysfunctional patients exhibited significantly greater thermal wind-up than Low Pain Adaptive patients, suggesting that a subgroup of FAP patients has outcomes consistent with widespread effects of heightened central sensitization. PMID:22721910

Modeling adaptive kernels from probabilistic phylogenetic trees.

PubMed

Nicotra, Luca; Micheli, Alessio

2009-01-01

Modeling phylogenetic interactions is an open issue in many computational biology problems. In the context of gene function prediction we introduce a class of kernels for structured data leveraging on a hierarchical probabilistic modeling of phylogeny among species. We derive three kernels belonging to this setting: a sufficient statistics kernel, a Fisher kernel, and a probability product kernel. The new kernels are used in the context of support vector machine learning. The kernels adaptivity is obtained through the estimation of the parameters of a tree structured model of evolution using as observed data phylogenetic profiles encoding the presence or absence of specific genes in a set of fully sequenced genomes. We report results obtained in the prediction of the functional class of the proteins of the budding yeast Saccharomyces cerevisae which favorably compare to a standard vector based kernel and to a non-adaptive tree kernel function. A further comparative analysis is performed in order to assess the impact of the different components of the proposed approach. We show that the key features of the proposed kernels are the adaptivity to the input domain and the ability to deal with structured data interpreted through a graphical model representation.

Developing Personalized Sensorimotor Adaptability Countermeasures for Spaceflight

NASA Technical Reports Server (NTRS)

Mulavara, A. P.; Seidler, R. D.; Peters, B.; Cohen, H. S.; Wood, S.; Bloomberg, J. J.

2016-01-01

Astronauts experience sensorimotor disturbances during their initial exposure to microgravity and during the re-adaptation phase following a return to an Earth-gravitational environment. Interestingly, astronauts who return from spaceflight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts would be affected would improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. In this paper we will be presenting results from our ground-based study that show how behavioral, brain imaging and genomic data may be used to predict individual differences in sensorimotor adaptability to novel sensorimotor environments. This approach will allow us to better design and implement sensorimotor adaptability training countermeasures against decrements in post-mission adaptive capability that are customized for each crewmember's sensory biases, adaptive capacity, brain structure, functional capacities, and genetic predispositions. The ability to customize adaptability training will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to ensure expected outcomes.

Dimensional assessment of self- and interpersonal functioning in adolescents: implications for DSM-5's general definition of personality disorder.

PubMed

DeFife, Jared A; Goldberg, Melissa; Westen, Drew

2015-04-01

Central to the proposed DSM-5 general definition of personality disorder (PD) are features of self- and interpersonal functioning. The Social Cognition and Object Relations Scale-Global Rating Method (SCORS-G) is a coding system that assesses eight dimensions of self- and relational experience that can be applied to narrative data or used by clinically experienced observers to quantify observations of patients in ongoing psychotherapy. This study aims to evaluate the relationship of SCORS-G dimensions to personality pathology in adolescents and their incremental validity for predicting multiple domains of adaptive functioning. A total of 294 randomly sampled doctoral-level clinical psychologists and psychiatrists described an adolescent patient in their care based on all available data. Individual SCORS-G variables demonstrated medium-to-large effect size differences for PD versus non-PD identified adolescents (d = .49-1.05). A summary SCORS-Composite rating was significantly related to composite measurements of global adaptive functioning (r = .66), school functioning (r = .47), externalizing behavior (r = -.49), and prior psychiatric history (r = -.31). The SCORS-Composite significantly predicted variance in domains of adaptive functioning above and beyond age and DSM-IV PD diagnosis (ΔR(2)s = .07-.32). As applied to adolescents, the SCORS-G offers a framework for a clinically meaningful and empirically sound dimensional assessment of self- and other representations and interpersonal functioning capacities. Our findings support the inclusion of self- and interpersonal capacities in the DSM-5 general definition of personality disorder as an improvement to existing PD diagnosis for capturing varied domains of adaptive functioning and psychopathology.

An Adaptive Handover Prediction Scheme for Seamless Mobility Based Wireless Networks

PubMed Central

Safa Sadiq, Ali; Fisal, Norsheila Binti; Ghafoor, Kayhan Zrar; Lloret, Jaime

2014-01-01

We propose an adaptive handover prediction (AHP) scheme for seamless mobility based wireless networks. That is, the AHP scheme incorporates fuzzy logic with AP prediction process in order to lend cognitive capability to handover decision making. Selection metrics, including received signal strength, mobile node relative direction towards the access points in the vicinity, and access point load, are collected and considered inputs of the fuzzy decision making system in order to select the best preferable AP around WLANs. The obtained handover decision which is based on the calculated quality cost using fuzzy inference system is also based on adaptable coefficients instead of fixed coefficients. In other words, the mean and the standard deviation of the normalized network prediction metrics of fuzzy inference system, which are collected from available WLANs are obtained adaptively. Accordingly, they are applied as statistical information to adjust or adapt the coefficients of membership functions. In addition, we propose an adjustable weight vector concept for input metrics in order to cope with the continuous, unpredictable variation in their membership degrees. Furthermore, handover decisions are performed in each MN independently after knowing RSS, direction toward APs, and AP load. Finally, performance evaluation of the proposed scheme shows its superiority compared with representatives of the prediction approaches. PMID:25574490

An adaptive handover prediction scheme for seamless mobility based wireless networks.

PubMed

Sadiq, Ali Safa; Fisal, Norsheila Binti; Ghafoor, Kayhan Zrar; Lloret, Jaime

2014-01-01

We propose an adaptive handover prediction (AHP) scheme for seamless mobility based wireless networks. That is, the AHP scheme incorporates fuzzy logic with AP prediction process in order to lend cognitive capability to handover decision making. Selection metrics, including received signal strength, mobile node relative direction towards the access points in the vicinity, and access point load, are collected and considered inputs of the fuzzy decision making system in order to select the best preferable AP around WLANs. The obtained handover decision which is based on the calculated quality cost using fuzzy inference system is also based on adaptable coefficients instead of fixed coefficients. In other words, the mean and the standard deviation of the normalized network prediction metrics of fuzzy inference system, which are collected from available WLANs are obtained adaptively. Accordingly, they are applied as statistical information to adjust or adapt the coefficients of membership functions. In addition, we propose an adjustable weight vector concept for input metrics in order to cope with the continuous, unpredictable variation in their membership degrees. Furthermore, handover decisions are performed in each MN independently after knowing RSS, direction toward APs, and AP load. Finally, performance evaluation of the proposed scheme shows its superiority compared with representatives of the prediction approaches.

A genomic perspective on the generation and maintenance of genetic diversity in herbivorous insects

PubMed Central

Gloss, Andrew D.; Groen, Simon C.; Whiteman, Noah K.

2017-01-01

Understanding the processes that generate and maintain genetic variation within populations is a central goal in evolutionary biology. Theory predicts that some of this variation is maintained as a consequence of adapting to variable habitats. Studies in herbivorous insects have played a key role in confirming this prediction. Here, we highlight theoretical and conceptual models for the maintenance of genetic diversity in herbivorous insects, empirical genomic studies testing these models, and pressing questions within the realm of evolutionary and functional genomic studies. To address key gaps, we propose an integrative approach combining population genomic scans for adaptation, genome-wide characterization of targets of selection through experimental manipulations, mapping the genetic architecture of traits influencing fitness, and functional studies. We also stress the importance of studying the maintenance of genetic variation across biological scales—from variation within populations to divergence among populations—to form a comprehensive view of adaptation in herbivorous insects. PMID:28736510

Pupil diameter tracks changes in control state predicted by the adaptive gain theory of locus coeruleus function

PubMed Central

Gilzenrat, Mark S.; Nieuwenhuis, Sander; Jepma, Marieke; Cohen, Jonathan D.

2010-01-01

An important dimension of cognitive control is the adaptive regulation of the balance between exploitation (pursuing known sources of reward) and exploration (seeking new ones) in response to changes in task utility. Recent studies have suggested that the locus coeruleus–norepinephrine system may play an important role in this function and that pupil diameter can be used to index locus coeruleus activity. On the basis of this, we reasoned that pupil diameter may correlate closely with control state and associated changes in behavior. Specifically, we predicted that increases in baseline pupil diameter would be associated with decreases in task utility and disengagement from the task (exploration), whereas reduced baseline diameter (but increases in task-evoked dilations) would be associated with task engagement (exploitation). Findings in three experiments were consistent with these predictions, suggesting that pupillometry may be useful as an index of both control state and, indirectly, locus coeruleus function. PMID:20498349

Classification of intellectual disability using the Wechsler Intelligence Scale for Children: Full Scale IQ or General Abilities Index?

PubMed Central

KORIAKIN, TAYLOR A; MCCURDY, MARK D; PAPAZOGLOU, AIMILIA; PRITCHARD, ALISON E; ZABEL, T ANDREW; MAHONE, E MARK; JACOBSON, LISA A

2013-01-01

Aim We examined the implications of using the Full Scale Intelligence Quotient (FSIQ) versus the General Abilities Index (GAI) for determination of intellectual disability using the Wechsler Intelligence Scales for Children, fourth edition (WISC-IV). Method Children referred for neuropsychological assessment (543 males, 290 females; mean age 10y 5mo, SD 2y 9mo, range 6–16y) were administered the WISC-IV and the Adaptive Behavior Assessment System, Second Edition (ABAS-II). Results GAI and FSIQ were highly correlated; however, fewer children were identified as having intellectual disability using GAI (n=159) than when using FSIQ (n=196). Although the 44 children classified as having intellectual disability based upon FSIQ (but not GAI) had significantly higher adaptive functioning scores than those meeting intellectual disability criteria based upon both FSIQ and GAI, mean adaptive scores still fell within the impaired range. FSIQ and GAI were comparable in predicting impairments in adaptive functioning. Interpretation Using GAI rather than FSIQ in intellectual disability diagnostic decision making resulted in fewer individuals being diagnosed with intellectual disability; however, the mean GAI of the disqualified individuals was at the upper end of criteria for intellectual impairment (standard score 75), and these individuals remained adaptively impaired. As GAI and FSIQ were similarly predictive of overall adaptive functioning, the use of GAI for intellectual disability diagnostic decision making may be of limited value. PMID:23859669

Predicting Adolescent Mothers' Transition to Adulthood.

ERIC Educational Resources Information Center

Mylod, Deirdre E.; Whitman, Thomas L.; Borkowski, John G.

1997-01-01

Investigated relationships among prenatal maternal resources, perceptions about parenting, and children's temperament at 6 months, and adaptation of 90 adolescent mothers three years after the birth of their first child. Found that maternal resources uniquely predicted later maternal cognitive functioning, personal adjustment, and child abuse…

Enhanced prefrontal-amygdala connectivity following childhood adversity as a protective mechanism against internalizing in adolescence.

PubMed

Herringa, Ryan J; Burghy, Cory A; Stodola, Diane E; Fox, Michelle E; Davidson, Richard J; Essex, Marilyn J

2016-07-01

Much research has focused on the deleterious neurobiological effects of childhood adversity that may underlie internalizing disorders. While most youth show emotional adaptation following adversity, the corresponding neural mechanisms remain poorly understood. In this longitudinal community study, we examined the associations among childhood family adversity, adolescent internalizing symptoms, and their interaction on regional brain activation and amygdala/hippocampus functional connectivity during emotion processing in 132 adolescents. Consistent with prior work, childhood adversity predicted heightened amygdala reactivity to negative, but not positive, images in adolescence. However, amygdala reactivity was not related to internalizing symptoms. Furthermore, childhood adversity predicted increased fronto-amygdala connectivity to negative, but not positive, images, yet only in lower internalizing adolescents. Childhood adversity also predicted increased fronto-hippocampal connectivity to negative images, but was not moderated by internalizing. These findings were unrelated to adolescence adversity or externalizing symptoms, suggesting specificity to childhood adversity and adolescent internalizing. Together, these findings suggest that adaptation to childhood adversity is associated with augmentation of fronto-subcortical circuits specifically for negative emotional stimuli. Conversely, insufficient enhancement of fronto-amygdala connectivity, with increasing amygdala reactivity, may represent a neural signature of vulnerability for internalizing by late adolescence. These findings implicate early childhood as a critical period in determining the brain's adaptation to adversity, and suggest that even normative adverse experiences can have significant impact on neurodevelopment and functioning. These results offer potential neural mechanisms of adaptation and vulnerability which could be used in the prediction of risk for psychopathology following childhood adversity.

Rational Adaptation under Task and Processing Constraints: Implications for Testing Theories of Cognition and Action

ERIC Educational Resources Information Center

Howes, Andrew; Lewis, Richard L.; Vera, Alonso

2009-01-01

The authors assume that individuals adapt rationally to a utility function given constraints imposed by their cognitive architecture and the local task environment. This assumption underlies a new approach to modeling and understanding cognition--cognitively bounded rational analysis--that sharpens the predictive acuity of general, integrated…

Neuropsychological Predictors of Everyday Functioning in Adults with Intellectual Disabilities

ERIC Educational Resources Information Center

Su, C. Y.; Chen, C. C.; Wuang, Y. P.; Lin, Y. H.; Wu, Y. Y.

2008-01-01

Background: Very little is known about the neuropsychological correlates of adaptive functioning in people with intellectual disabilities (ID). This study examined whether specific cognitive deficits and demographic variables predicted everyday functioning in adults with ID. Method: People with ID (n = 101; ages 19-41 years; mean education = 11…

Concomitant prediction of function and fold at the domain level with GO-based profiles.

PubMed

Lopez, Daniel; Pazos, Florencio

2013-01-01

Predicting the function of newly sequenced proteins is crucial due to the pace at which these raw sequences are being obtained. Almost all resources for predicting protein function assign functional terms to whole chains, and do not distinguish which particular domain is responsible for the allocated function. This is not a limitation of the methodologies themselves but it is due to the fact that in the databases of functional annotations these methods use for transferring functional terms to new proteins, these annotations are done on a whole-chain basis. Nevertheless, domains are the basic evolutionary and often functional units of proteins. In many cases, the domains of a protein chain have distinct molecular functions, independent from each other. For that reason resources with functional annotations at the domain level, as well as methodologies for predicting function for individual domains adapted to these resources are required.We present a methodology for predicting the molecular function of individual domains, based on a previously developed database of functional annotations at the domain level. The approach, which we show outperforms a standard method based on sequence searches in assigning function, concomitantly predicts the structural fold of the domains and can give hints on the functionally important residues associated to the predicted function.

Application of Parallel Adjoint-Based Error Estimation and Anisotropic Grid Adaptation for Three-Dimensional Aerospace Configurations

NASA Technical Reports Server (NTRS)

Lee-Rausch, E. M.; Park, M. A.; Jones, W. T.; Hammond, D. P.; Nielsen, E. J.

2005-01-01

This paper demonstrates the extension of error estimation and adaptation methods to parallel computations enabling larger, more realistic aerospace applications and the quantification of discretization errors for complex 3-D solutions. Results were shown for an inviscid sonic-boom prediction about a double-cone configuration and a wing/body segmented leading edge (SLE) configuration where the output function of the adjoint was pressure integrated over a part of the cylinder in the near field. After multiple cycles of error estimation and surface/field adaptation, a significant improvement in the inviscid solution for the sonic boom signature of the double cone was observed. Although the double-cone adaptation was initiated from a very coarse mesh, the near-field pressure signature from the final adapted mesh compared very well with the wind-tunnel data which illustrates that the adjoint-based error estimation and adaptation process requires no a priori refinement of the mesh. Similarly, the near-field pressure signature for the SLE wing/body sonic boom configuration showed a significant improvement from the initial coarse mesh to the final adapted mesh in comparison with the wind tunnel results. Error estimation and field adaptation results were also presented for the viscous transonic drag prediction of the DLR-F6 wing/body configuration, and results were compared to a series of globally refined meshes. Two of these globally refined meshes were used as a starting point for the error estimation and field-adaptation process where the output function for the adjoint was the total drag. The field-adapted results showed an improvement in the prediction of the drag in comparison with the finest globally refined mesh and a reduction in the estimate of the remaining drag error. The adjoint-based adaptation parameter showed a need for increased resolution in the surface of the wing/body as well as a need for wake resolution downstream of the fuselage and wing trailing edge in order to achieve the requested drag tolerance. Although further adaptation was required to meet the requested tolerance, no further cycles were computed in order to avoid large discrepancies between the surface mesh spacing and the refined field spacing.

Identifiability, reducibility, and adaptability in allosteric macromolecules.

PubMed

Bohner, Gergő; Venkataraman, Gaurav

2017-05-01

The ability of macromolecules to transduce stimulus information at one site into conformational changes at a distant site, termed "allostery," is vital for cellular signaling. Here, we propose a link between the sensitivity of allosteric macromolecules to their underlying biophysical parameters, the interrelationships between these parameters, and macromolecular adaptability. We demonstrate that the parameters of a canonical model of the mSlo large-conductance Ca 2+ -activated K + (BK) ion channel are non-identifiable with respect to the equilibrium open probability-voltage relationship, a common functional assay. We construct a reduced model with emergent parameters that are identifiable and expressed as combinations of the original mechanistic parameters. These emergent parameters indicate which coordinated changes in mechanistic parameters can leave assay output unchanged. We predict that these coordinated changes are used by allosteric macromolecules to adapt, and we demonstrate how this prediction can be tested experimentally. We show that these predicted parameter compensations are used in the first reported allosteric phenomena: the Bohr effect, by which hemoglobin adapts to varying pH. © 2017 Bohner and Venkataraman.

Identifiability, reducibility, and adaptability in allosteric macromolecules

PubMed Central

Bohner, Gergő

2017-01-01

The ability of macromolecules to transduce stimulus information at one site into conformational changes at a distant site, termed “allostery,” is vital for cellular signaling. Here, we propose a link between the sensitivity of allosteric macromolecules to their underlying biophysical parameters, the interrelationships between these parameters, and macromolecular adaptability. We demonstrate that the parameters of a canonical model of the mSlo large-conductance Ca2+-activated K+ (BK) ion channel are non-identifiable with respect to the equilibrium open probability-voltage relationship, a common functional assay. We construct a reduced model with emergent parameters that are identifiable and expressed as combinations of the original mechanistic parameters. These emergent parameters indicate which coordinated changes in mechanistic parameters can leave assay output unchanged. We predict that these coordinated changes are used by allosteric macromolecules to adapt, and we demonstrate how this prediction can be tested experimentally. We show that these predicted parameter compensations are used in the first reported allosteric phenomena: the Bohr effect, by which hemoglobin adapts to varying pH. PMID:28416647

Adapting Social Neuroscience Measures for Schizophrenia Clinical Trials, Part 3: Fathoming External Validity

PubMed Central

Olbert, Charles M.

2013-01-01

It is unknown whether measures adapted from social neuroscience linked to specific neural systems will demonstrate relationships to external variables. Four paradigms adapted from social neuroscience were administered to 173 clinically stable outpatients with schizophrenia to determine their relationships to functionally meaningful variables and to investigate their incremental validity beyond standard measures of social and nonsocial cognition. The 4 paradigms included 2 that assess perception of nonverbal social and action cues (basic biological motion and emotion in biological motion) and 2 that involve higher level inferences about self and others’ mental states (self- referential memory and empathic accuracy). Overall, social neuroscience paradigms showed significant relationships to functional capacity but weak relationships to community functioning; the paradigms also showed weak correlations to clinical symptoms. Evidence for incremental validity beyond standard measures of social and nonsocial cognition was mixed with additional predictive power shown for functional capacity but not community functioning. Of the newly adapted paradigms, the empathic accuracy task had the broadest external validity. These results underscore the difficulty of translating developments from neuroscience into clinically useful tasks with functional significance. PMID:24072806

Adapting social neuroscience measures for schizophrenia clinical trials, part 3: fathoming external validity.

PubMed

Olbert, Charles M; Penn, David L; Kern, Robert S; Lee, Junghee; Horan, William P; Reise, Steven P; Ochsner, Kevin N; Marder, Stephen R; Green, Michael F

2013-11-01

It is unknown whether measures adapted from social neuroscience linked to specific neural systems will demonstrate relationships to external variables. Four paradigms adapted from social neuroscience were administered to 173 clinically stable outpatients with schizophrenia to determine their relationships to functionally meaningful variables and to investigate their incremental validity beyond standard measures of social and nonsocial cognition. The 4 paradigms included 2 that assess perception of nonverbal social and action cues (basic biological motion and emotion in biological motion) and 2 that involve higher level inferences about self and others' mental states (self-referential memory and empathic accuracy). Overall, social neuroscience paradigms showed significant relationships to functional capacity but weak relationships to community functioning; the paradigms also showed weak correlations to clinical symptoms. Evidence for incremental validity beyond standard measures of social and nonsocial cognition was mixed with additional predictive power shown for functional capacity but not community functioning. Of the newly adapted paradigms, the empathic accuracy task had the broadest external validity. These results underscore the difficulty of translating developments from neuroscience into clinically useful tasks with functional significance.

Disciplinary style and child abuse potential: association with indicators of positive functioning in children with behavior problems.

PubMed

Rodriguez, Christina M; Eden, Ann M

2008-06-01

Reduction of ineffective parenting is promoted in parent training components of mental health treatment for children with externalizing behavior disorders, but minimal research has considered whether disciplinary style and lower abuse risk could also be associated with positive functioning in such children. The present study examined whether lower dysfunctional disciplinary style and child abuse risk was associated with children's positive self-concept, adaptive attributional style, and hopefulness. Recruited from children undergoing treatment for disruptive behavior disorders, 69 mother-child dyads participated, with maternal caregivers reporting on their disciplinary style and abuse potential and children reporting independently on their positive functioning (adaptive attributional style, overall self-concept, and hopelessness). Findings supported the hypothesized association, with lower scores on mothers' dysfunctional discipline style and abuse potential significantly predicting children's reported positive functioning. Future research directions pertaining to more adaptive functioning in children with behavior problems are discussed.

Genetically informed ecological niche models improve climate change predictions.

PubMed

Ikeda, Dana H; Max, Tamara L; Allan, Gerard J; Lau, Matthew K; Shuster, Stephen M; Whitham, Thomas G

2017-01-01

We examined the hypothesis that ecological niche models (ENMs) more accurately predict species distributions when they incorporate information on population genetic structure, and concomitantly, local adaptation. Local adaptation is common in species that span a range of environmental gradients (e.g., soils and climate). Moreover, common garden studies have demonstrated a covariance between neutral markers and functional traits associated with a species' ability to adapt to environmental change. We therefore predicted that genetically distinct populations would respond differently to climate change, resulting in predicted distributions with little overlap. To test whether genetic information improves our ability to predict a species' niche space, we created genetically informed ecological niche models (gENMs) using Populus fremontii (Salicaceae), a widespread tree species in which prior common garden experiments demonstrate strong evidence for local adaptation. Four major findings emerged: (i) gENMs predicted population occurrences with up to 12-fold greater accuracy than models without genetic information; (ii) tests of niche similarity revealed that three ecotypes, identified on the basis of neutral genetic markers and locally adapted populations, are associated with differences in climate; (iii) our forecasts indicate that ongoing climate change will likely shift these ecotypes further apart in geographic space, resulting in greater niche divergence; (iv) ecotypes that currently exhibit the largest geographic distribution and niche breadth appear to be buffered the most from climate change. As diverse agents of selection shape genetic variability and structure within species, we argue that gENMs will lead to more accurate predictions of species distributions under climate change. © 2016 John Wiley & Sons Ltd.

Neural Predictors of Visuomotor Adaptation Rate and Multi-Day Savings

NASA Technical Reports Server (NTRS)

Cassady, Kaitlin; Ruitenberg, Marit; Koppelmans, Vincent; Reuter-Lorenz, Patricia; De Dios, Yiri; Gadd, Nichole; Wood, Scott; Riascos Castenada, Roy; Kofman, Igor; Bloomberg, Jacob;

Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory

PubMed Central

Tao, Qing

2017-01-01

Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM. PMID:29391864

Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory.

PubMed

Yang, Haimin; Pan, Zhisong; Tao, Qing

2017-01-01

Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM.

Temperament as a Predictor of Symptomotology and Adaptive Functioning in Adolescents with High-Functioning Autism

PubMed Central

Schwartz, Caley B.; Henderson, Heather A.; Inge, Anne P.; Zahka, Nicole E.; Coman, Drew C.; Kojkowski, Nicole M.; Hileman, Camilla M.; Mundy, Peter C.

2009-01-01

Variation in temperament is characteristic of all people but is rarely studied as a predictor of individual differences among individuals with autism. Relative to a matched comparison sample, adolescents with High-Functioning Autism (HFA) reported lower levels of Surgency and higher levels of Negative Affect. Variability in temperament predicted symptomotology, social skills, and social-emotional outcomes differently for individuals with HFA than for the comparison sample. This study is unique in that temperament was measured by self-report, while all outcome measures were reported by parents. The broader implications of this study suggest that by identifying individual variability in constructs, such as temperament, that may influence adaptive functioning, interventions may be developed to target these constructs and increase the likelihood that individuals with HFA will achieve more adaptive life outcomes. PMID:19165586

Continental cichlid radiations: functional diversity reveals the role of changing ecological opportunity in the Neotropics.

PubMed

Arbour, Jessica Hilary; López-Fernández, Hernán

2016-08-17

Adaptive radiations have been hypothesized to contribute broadly to the diversity of organisms. Models of adaptive radiation predict that ecological opportunity and ecological release, the availability of empty ecological niches and the response by adapting lineages to occupy them, respectively, drive patterns of phenotypic and lineage diversification. Adaptive radiations driven by 'ecological opportunity' are well established in island systems; it is less clear if ecological opportunity influences continent-wide diversification. We use Neotropical cichlid fishes to test if variation in rates of functional evolution is consistent with changing ecological opportunity. Across a functional morphological axis associated with ram-suction feeding traits, evolutionary rates declined through time as lineages diversified in South America. Evolutionary rates of ram-suction functional morphology also appear to have accelerated as cichlids colonized Central America and encountered renewed opportunity. Our results suggest that ecological opportunity may play an important role in shaping patterns of morphological diversity of even broadly distributed lineages like Neotropical cichlids. © 2016 The Author(s).

Continental cichlid radiations: functional diversity reveals the role of changing ecological opportunity in the Neotropics

PubMed Central

López-Fernández, Hernán

2016-01-01

Adaptive radiations have been hypothesized to contribute broadly to the diversity of organisms. Models of adaptive radiation predict that ecological opportunity and ecological release, the availability of empty ecological niches and the response by adapting lineages to occupy them, respectively, drive patterns of phenotypic and lineage diversification. Adaptive radiations driven by ‘ecological opportunity’ are well established in island systems; it is less clear if ecological opportunity influences continent-wide diversification. We use Neotropical cichlid fishes to test if variation in rates of functional evolution is consistent with changing ecological opportunity. Across a functional morphological axis associated with ram–suction feeding traits, evolutionary rates declined through time as lineages diversified in South America. Evolutionary rates of ram–suction functional morphology also appear to have accelerated as cichlids colonized Central America and encountered renewed opportunity. Our results suggest that ecological opportunity may play an important role in shaping patterns of morphological diversity of even broadly distributed lineages like Neotropical cichlids. PMID:27512144

Mothers' psychological adaptation to Duchenne/Becker muscular dystrophy

PubMed Central

Peay, Holly L; Meiser, Bettina; Kinnett, Kathleen; Furlong, Pat; Porter, Kathryn; Tibben, Aad

2016-01-01

Duchenne and Becker muscular dystrophy (DBMD) cause significant emotional and care-related burden on caregivers, but no studies have evaluated predictors of positive caregiver outcomes, including disorder-specific psychological adaptation. Using a community-engaged approach focused on supporting mothers in positive aspects of caregiving, this prospective study aims to assess (i) the association between child's baseline functional status and mothers' illness perceptions, resilience, and coping self-efficacy; and (ii) predictors of mothers' psychological adaptation to caring for a child with DBMD. Biological mothers with at least one living child with DBMD completed a baseline survey (n=205) with 1-year (n=147) and 2-year (n=144) follow-up surveys. Worse child's baseline function was associated not only with increased caregiver burden and reduced maternal resilience, but also with perception of positive disease impact on the family. At two follow-ups, increased psychological adaptation to DBMD was predicted by resilience (β=0.264, P=0.001) and perceived positive impact (β=0.310, P<0.001), controlling for mother's age (β=−0.305, P<0.001) and income (β=−0.088, P=0.245). Child's functional status and caregiver burden of DBMD did not predict DBMD-specific adaptation. Though clinicians caring for families with DBMD should anticipate increased caregiver burden as the disorder progresses, interventions focused on caregiver burden are not expected to influence mothers' psychosocial adaptation. Efforts to improve mothers' well-being should focus on fostering mothers' resilience and enhancing perceptions of positive disease impact (benefit finding). Results suggest that psychosocial interventions can highlight strengths and well-being rather than burden and deficit. PMID:26306645

Rare ecomorphological convergence on a complex adaptive landscape: Body size and diet mediate evolution of jaw shape in squirrels (Sciuridae).

PubMed

Zelditch, Miriam Leah; Ye, Ji; Mitchell, Jonathan S; Swiderski, Donald L

2017-03-01

Convergence is widely regarded as compelling evidence for adaptation, often being portrayed as evidence that phenotypic outcomes are predictable from ecology, overriding contingencies of history. However, repeated outcomes may be very rare unless adaptive landscapes are simple, structured by strong ecological and functional constraints. One such constraint may be a limitation on body size because performance often scales with size, allowing species to adapt to challenging functions by modifying only size. When size is constrained, species might adapt by changing shape; convergent shapes may therefore be common when size is limiting and functions are challenging. We examine the roles of size and diet as determinants of jaw shape in Sciuridae. As expected, size and diet have significant interdependent effects on jaw shape and ecomorphological convergence is rare, typically involving demanding diets and limiting sizes. More surprising is morphological without ecological convergence, which is equally common between and within dietary classes. Those cases, like rare ecomorphological convergence, may be consequences of evolving on an adaptive landscape shaped by many-to-many relationships between ecology and function, many-to-one relationships between form and performance, and one-to-many relationships between functionally versatile morphologies and ecology. On complex adaptive landscapes, ecological selection can yield different outcomes. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Cognitive and adaptive correlates of an ADOS-derived joint attention composite

PubMed Central

Harrison, Ashley Johnson; Lu, Zhenqiu (Laura); McLean, Rebecca L.; Sheinkopf, Stephen J.

2016-01-01

Joint attention skills have been shown to predict language outcomes in children with autism spectrum disorder (ASD). Less is known about the relationship between joint attention (JA) abilities in children with ASD and cognitive and adaptive abilities. In the current study, a subset of items from the Autism Diagnostic Observation Schedule (ADOS), designed to quantify JA abilities, were used to investigate social attention among an unusually large cross-sectional sample of children with ASD (n = 1061). An examination of the association between JA and a range of functional correlates (cognitive and adaptive) revealed JA was significantly related to verbal (VIQ) and non-verbal (NVIQ) cognitive ability as well as all domains of adaptive functioning (socialization, communication, and daily living skills). Additional analyses examined the degree to which the relation between adaptive abilities (socialization, communication, and daily living skills) and JA was maintained after taking into account the potentially mediating role of verbal and nonverbal cognitive ability. Results revealed that VIQ fully mediated the relation between JA and adaptive functioning, whereas the relation between these adaptive variables and JA was only partially mediated by NVIQ. Moderation analyses were also conducted to examine how verbal and non-verbal cognitive ability and gender impacted the relation between JA and adaptive functioning. In line with research showing a relation between language and JA, this indicates that while JA is significantly related to functional outcomes, this appears to be mediated specifically through a verbal cognitive pathway. PMID:28168003

The role of stimulus-specific adaptation in songbird syntax generation

NASA Astrophysics Data System (ADS)

Wittenbach, Jason D.

Sequential behaviors are an important part of the behavioral repertoire of many animals and understanding how neural circuits encode and generate such sequences is a long-standing question in neuroscience. The Bengalese finch is a useful model system for studying variable action sequences. The songs of these birds consist of well-defined vocal elements (syllables) that are strung together to form sequences. The ordering of the syllables within the sequence is variable but not random - it shows complex statistical patterns (syntax). While often thought to be first-order, the syntax of the Bengalese finch song shows a distinct form of history dependence where the probability of repeating a syllable decreases as a function of the number of repetitions that have already occurred. Current models of the Bengalese finch song control circuitry offer no explanation for this repetition adaptation. The Bengalese finch also uses real-time auditory feedback to control the song syntax. Considering these facts, we hypothesize that repetition adaptation in the Bengalese finch syntax may be caused by stimulus-specific adaptation - a wide-spread phenomenon where neural responses to a specific stimulus become weaker with repeated presentations of the same stimulus. We begin by proposing a computational model for the song-control circuit where an auditory feedback signal that undergoes stimulus-specific adaptation helps drive repeated syllables. We show that this model does indeed capture the repetition adaptation observed in Bengalese finch syntax; along the way, we derive a new probabilistic model for repetition adaptation. Key predictions of our model are analyzed in light of experiments performed by collaborators. Next we extend the model in order to predict how the syntax will change as a function of brain temperature. These predictions are compared to experimental results from collaborators where portions of the Bengalese finch song circuit are cooled in awake and behaving birds. Finally we show that repetition adaptation persists even in a simplified dynamical system model when a parameter controlling the repeat probability changes slowly over repetitions.

Functional Outcome Trajectories After Out-of-Hospital Pediatric Cardiac Arrest.

PubMed

Silverstein, Faye S; Slomine, Beth S; Christensen, James; Holubkov, Richard; Page, Kent; Dean, J Michael; Moler, Frank W

2016-12-01

To analyze functional performance measures collected prospectively during the conduct of a clinical trial that enrolled children (up to age 18 yr old), resuscitated after out-of-hospital cardiac arrest, who were at high risk of poor outcomes. Children with Glasgow Motor Scale score less than 5, within 6 hours of resuscitation, were enrolled in a clinical trial that compared two targeted temperature management interventions (THAPCA-OH, NCT00878644). The primary outcome, 12-month survival with Vineland Adaptive Behavior Scale, second edition, score greater or equal to 70, did not differ between groups. Thirty-eight North American PICUs. Two hundred ninety-five children were enrolled; 270 of 295 had baseline Vineland Adaptive Behavior Scale, second edition, scores greater or equal to 70; 87 of 270 survived 1 year. Targeted temperatures were 33.0°C and 36.8°C for hypothermia and normothermia groups. Baseline measures included Vineland Adaptive Behavior Scale, second edition, Pediatric Cerebral Performance Category, and Pediatric Overall Performance Category. Pediatric Cerebral Performance Category and Pediatric Overall Performance Category were rescored at hospital discharges; all three were scored at 3 and 12 months. In survivors with baseline Vineland Adaptive Behavior Scale, second edition scores greater or equal to 70, we evaluated relationships of hospital discharge Pediatric Cerebral Performance Category with 3- and 12-month scores and between 3- and 12-month Vineland Adaptive Behavior Scale, second edition, scores. Hospital discharge Pediatric Cerebral Performance Category scores strongly predicted 3- and 12-month Pediatric Cerebral Performance Category (r = 0.82 and 0.79; p < 0.0001) and Vineland Adaptive Behavior Scale, second edition, scores (r = -0.81 and -0.77; p < 0.0001). Three-month Vineland Adaptive Behavior Scale, second edition, scores strongly predicted 12-month performance (r = 0.95; p < 0.0001). Hypothermia treatment did not alter these relationships. In comatose children, with Glasgow Motor Scale score less than 5 in the initial hours after out-of-hospital cardiac arrest resuscitation, function scores at hospital discharge and at 3 months predicted 12-month performance well in the majority of survivors.

Predator and prey functional traits: understanding the adaptive machinery driving predator–prey interactions

PubMed Central

Schmitz, Oswald

2017-01-01

Predator–prey relationships are a central component of community dynamics. Classic approaches have tried to understand and predict these relationships in terms of consumptive interactions between predator and prey species, but characterizing the interaction this way is insufficient to predict the complexity and context dependency inherent in predator–prey relationships. Recent approaches have begun to explore predator–prey relationships in terms of an evolutionary-ecological game in which predator and prey adapt to each other through reciprocal interactions involving context-dependent expression of functional traits that influence their biomechanics. Functional traits are defined as any morphological, behavioral, or physiological trait of an organism associated with a biotic interaction. Such traits include predator and prey body size, predator and prey personality, predator hunting mode, prey mobility, prey anti-predator behavior, and prey physiological stress. Here, I discuss recent advances in this functional trait approach. Evidence shows that the nature and strength of many interactions are dependent upon the relative magnitude of predator and prey functional traits. Moreover, trait responses can be triggered by non-consumptive predator–prey interactions elicited by responses of prey to risk of predation. These interactions in turn can have dynamic feedbacks that can change the context of the predator–prey interaction, causing predator and prey to adapt their traits—through phenotypically plastic or rapid evolutionary responses—and the nature of their interaction. Research shows that examining predator–prey interactions through the lens of an adaptive evolutionary-ecological game offers a foundation to explain variety in the nature and strength of predator–prey interactions observed in different ecological contexts. PMID:29043073

Predator and prey functional traits: understanding the adaptive machinery driving predator-prey interactions.

PubMed

Schmitz, Oswald

2017-01-01

Predator-prey relationships are a central component of community dynamics. Classic approaches have tried to understand and predict these relationships in terms of consumptive interactions between predator and prey species, but characterizing the interaction this way is insufficient to predict the complexity and context dependency inherent in predator-prey relationships. Recent approaches have begun to explore predator-prey relationships in terms of an evolutionary-ecological game in which predator and prey adapt to each other through reciprocal interactions involving context-dependent expression of functional traits that influence their biomechanics. Functional traits are defined as any morphological, behavioral, or physiological trait of an organism associated with a biotic interaction. Such traits include predator and prey body size, predator and prey personality, predator hunting mode, prey mobility, prey anti-predator behavior, and prey physiological stress. Here, I discuss recent advances in this functional trait approach. Evidence shows that the nature and strength of many interactions are dependent upon the relative magnitude of predator and prey functional traits. Moreover, trait responses can be triggered by non-consumptive predator-prey interactions elicited by responses of prey to risk of predation. These interactions in turn can have dynamic feedbacks that can change the context of the predator-prey interaction, causing predator and prey to adapt their traits-through phenotypically plastic or rapid evolutionary responses-and the nature of their interaction. Research shows that examining predator-prey interactions through the lens of an adaptive evolutionary-ecological game offers a foundation to explain variety in the nature and strength of predator-prey interactions observed in different ecological contexts.

Functional ecology and evolution of hominoid molar enamel thickness: Pan troglodytes schweinfurthii and Pongo pygmaeus wurmbii.

PubMed

Vogel, Erin R; van Woerden, Janneke T; Lucas, Peter W; Utami Atmoko, Sri S; van Schaik, Carel P; Dominy, Nathaniel J

2008-07-01

The divergent molar characteristics of Pan troglodytes and Pongo pygmaeus provide an instructive paradigm for examining the adaptive form-function relationship between molar enamel thickness and food hardness. Although both species exhibit a categorical preference for ripe fruit over other food objects, the thick enamel and crenulated occlusal surface of Pongo molar teeth predict a diet that is more resistant to deformation (hard) and fracture (tough) than the diet of Pan. We confirm these predictions with behavioral observations of Pan troglodytes schweinfurthii and Pongo pygmaeus wurmbii in the wild and describe the mechanical properties of foods utilized during periods when preferred foods are scarce. Such fallback foods may have exerted a selective pressure on tooth evolution, particularly molar enamel thinness, which is interpreted as a functional adaptation to seasonal folivory and a derived character trait within the hominoid clade. The thick enamel and crenulated occlusal surface of Pongo molars is interpreted as a functional adaptation to the routine consumption of relatively tough and hard foods. We discuss the implications of these interpretations for inferring the diet of hominin species, which possessed varying degrees of thick molar enamel. These data, which are among the first reported for hominoid primates, fill an important empirical void for evaluating the mechanical plausibility of putative hominin food objects.

Ground-based adaptive optics coronagraphic performance under closed-loop predictive control

NASA Astrophysics Data System (ADS)

Males, Jared R.; Guyon, Olivier

2018-01-01

The discovery of the exoplanet Proxima b highlights the potential for the coming generation of giant segmented mirror telescopes (GSMTs) to characterize terrestrial-potentially habitable-planets orbiting nearby stars with direct imaging. This will require continued development and implementation of optimized adaptive optics systems feeding coronagraphs on the GSMTs. Such development should proceed with an understanding of the fundamental limits imposed by atmospheric turbulence. Here, we seek to address this question with a semianalytic framework for calculating the postcoronagraph contrast in a closed-loop adaptive optics system. We do this starting with the temporal power spectra of the Fourier basis calculated assuming frozen flow turbulence, and then apply closed-loop transfer functions. We include the benefits of a simple predictive controller, which we show could provide over a factor of 1400 gain in raw point spread function contrast at 1 λ/D on bright stars, and more than a factor of 30 gain on an I=7.5 mag star such as Proxima. More sophisticated predictive control can be expected to improve this even further. Assuming a photon-noise limited observing technique such as high-dispersion coronagraphy, these gains in raw contrast will decrease integration times by the same large factors. Predictive control of atmospheric turbulence should therefore be seen as one of the key technologies that will enable ground-based telescopes to characterize terrestrial planets.

Computational identification of miRNAs, their targets and functions in three-spined stickleback (Gasterosteus aculeatus).

PubMed

Chaturvedi, Anurag; Raeymaekers, Joost A M; Volckaert, Filip A M

2014-07-01

An intriguing question in biology is how the evolution of gene regulation is shaped by natural selection in natural populations. Among the many known regulatory mechanisms, regulation of gene expression by microRNAs (miRNAs) is of critical importance. However, our understanding of their evolution in natural populations is limited. Studying the role of miRNAs in three-spined stickleback, an important natural model for speciation research, may provide new insights into adaptive polymorphisms. However, lack of annotation of miRNA genes in its genome is a bottleneck. To fill this research gap, we used the genome of three-spined stickleback to predict miRNAs and their targets. We predicted 1486 mature miRNAs using the homology-based miRNA prediction approach. We then performed functional annotation and enrichment analysis of these targets, which identified over-represented motifs. Further, a database resource (GAmiRdb) has been developed for dynamically searching miRNAs and their targets exclusively in three-spined stickleback. Finally, the database was used in two case studies focusing on freshwater adaptation in natural populations. In the first study, we found 44 genomic regions overlapping with predicted miRNA targets. In the second study, we identified two SNPs altering the MRE seed site of sperm-specific glyceraldehyde-3-phosphate gene. These findings highlight the importance of the GAmiRdb knowledge base in understanding adaptive evolution. © 2014 John Wiley & Sons Ltd.

Asymmetric generalization in adaptation to target displacement errors in humans and in a neural network model.

PubMed

Westendorff, Stephanie; Kuang, Shenbing; Taghizadeh, Bahareh; Donchin, Opher; Gail, Alexander

2015-04-01

Different error signals can induce sensorimotor adaptation during visually guided reaching, possibly evoking different neural adaptation mechanisms. Here we investigate reach adaptation induced by visual target errors without perturbing the actual or sensed hand position. We analyzed the spatial generalization of adaptation to target error to compare it with other known generalization patterns and simulated our results with a neural network model trained to minimize target error independent of prediction errors. Subjects reached to different peripheral visual targets and had to adapt to a sudden fixed-amplitude displacement ("jump") consistently occurring for only one of the reach targets. Subjects simultaneously had to perform contralateral unperturbed saccades, which rendered the reach target jump unnoticeable. As a result, subjects adapted by gradually decreasing reach errors and showed negative aftereffects for the perturbed reach target. Reach errors generalized to unperturbed targets according to a translational rather than rotational generalization pattern, but locally, not globally. More importantly, reach errors generalized asymmetrically with a skewed generalization function in the direction of the target jump. Our neural network model reproduced the skewed generalization after adaptation to target jump without having been explicitly trained to produce a specific generalization pattern. Our combined psychophysical and simulation results suggest that target jump adaptation in reaching can be explained by gradual updating of spatial motor goal representations in sensorimotor association networks, independent of learning induced by a prediction-error about the hand position. The simulations make testable predictions about the underlying changes in the tuning of sensorimotor neurons during target jump adaptation. Copyright © 2015 the American Physiological Society.

Asymmetric generalization in adaptation to target displacement errors in humans and in a neural network model

PubMed Central

Westendorff, Stephanie; Kuang, Shenbing; Taghizadeh, Bahareh; Donchin, Opher

2015-01-01

Different error signals can induce sensorimotor adaptation during visually guided reaching, possibly evoking different neural adaptation mechanisms. Here we investigate reach adaptation induced by visual target errors without perturbing the actual or sensed hand position. We analyzed the spatial generalization of adaptation to target error to compare it with other known generalization patterns and simulated our results with a neural network model trained to minimize target error independent of prediction errors. Subjects reached to different peripheral visual targets and had to adapt to a sudden fixed-amplitude displacement (“jump”) consistently occurring for only one of the reach targets. Subjects simultaneously had to perform contralateral unperturbed saccades, which rendered the reach target jump unnoticeable. As a result, subjects adapted by gradually decreasing reach errors and showed negative aftereffects for the perturbed reach target. Reach errors generalized to unperturbed targets according to a translational rather than rotational generalization pattern, but locally, not globally. More importantly, reach errors generalized asymmetrically with a skewed generalization function in the direction of the target jump. Our neural network model reproduced the skewed generalization after adaptation to target jump without having been explicitly trained to produce a specific generalization pattern. Our combined psychophysical and simulation results suggest that target jump adaptation in reaching can be explained by gradual updating of spatial motor goal representations in sensorimotor association networks, independent of learning induced by a prediction-error about the hand position. The simulations make testable predictions about the underlying changes in the tuning of sensorimotor neurons during target jump adaptation. PMID:25609106

Cancer-specific self-efficacy and psychosocial and functional adaptation to early stage breast cancer.

PubMed

Manne, Sharon L; Ostroff, Jamie S; Norton, Tina R; Fox, Kevin; Grana, Generosa; Goldstein, Lori

2006-04-01

Although self-efficacy is considered a key psychological resource in adapting to chronic physical illness, this construct has received less attention among individuals coping with cancer. To examine changes in cancer self-efficacy over time among women with early stage breast cancer and associations between task-specific domains of self-efficacy and specific psychological, relationship, and functional outcomes. Ninety-five women diagnosed with early stage breast cancer completed surveys postsurgery and 1 year later. Cancer-related self-efficacy was relatively stable over 1 year, with only 2 domains of efficacy-(a) Activity Management and (b) Self-Satisfaction-evidencing significant increases over the 1-year time period. Cross-sectional findings were relatively consistent with predictions and suggested that specific domains of self-efficacy were more strongly related to relevant domains of adaptation. Longitudinal findings were not as consistent with the domain-specificity hypothesis but did suggest several predictive associations between self-efficacy and outcomes. Personal Management self-efficacy was associated with higher relationship satisfaction, higher Communication Self-Efficacy was associated with less functional impairment, and higher Affective Management self-efficacy was associated with higher self-esteem 1 year later. Specific domains of cancer-related self-efficacy are most closely related to relevant areas of adaptation when considered cross-sectionally, but further study is needed to clarify the nature of these relationships over time.

Molecular specificity, convergence and constraint shape adaptive evolution in nutrient-poor environments.

PubMed

Hong, Jungeui; Gresham, David

2014-01-01

One of the central goals of evolutionary biology is to explain and predict the molecular basis of adaptive evolution. We studied the evolution of genetic networks in Saccharomyces cerevisiae (budding yeast) populations propagated for more than 200 generations in different nitrogen-limiting conditions. We find that rapid adaptive evolution in nitrogen-poor environments is dominated by the de novo generation and selection of copy number variants (CNVs), a large fraction of which contain genes encoding specific nitrogen transporters including PUT4, DUR3 and DAL4. The large fitness increases associated with these alleles limits the genetic heterogeneity of adapting populations even in environments with multiple nitrogen sources. Complete identification of acquired point mutations, in individual lineages and entire populations, identified heterogeneity at the level of genetic loci but common themes at the level of functional modules, including genes controlling phosphatidylinositol-3-phosphate metabolism and vacuole biogenesis. Adaptive strategies shared with other nutrient-limited environments point to selection of genetic variation in the TORC1 and Ras/PKA signaling pathways as a general mechanism underlying improved growth in nutrient-limited environments. Within a single population we observed the repeated independent selection of a multi-locus genotype, comprised of the functionally related genes GAT1, MEP2 and LST4. By studying the fitness of individual alleles, and their combination, as well as the evolutionary history of the evolving population, we find that the order in which these mutations are acquired is constrained by epistasis. The identification of repeatedly selected variation at functionally related loci that interact epistatically suggests that gene network polymorphisms (GNPs) may be a frequent outcome of adaptive evolution. Our results provide insight into the mechanistic basis by which cells adapt to nutrient-limited environments and suggest that knowledge of the selective environment and the regulatory mechanisms important for growth and survival in that environment greatly increase the predictability of adaptive evolution.

Adaptive fuzzy predictive sliding control of uncertain nonlinear systems with bound-known input delay.

PubMed

Khazaee, Mostafa; Markazi, Amir H D; Omidi, Ehsan

2015-11-01

In this paper, a new Adaptive Fuzzy Predictive Sliding Mode Control (AFP-SMC) is presented for nonlinear systems with uncertain dynamics and unknown input delay. The control unit consists of a fuzzy inference system to approximate the ideal linearization control, together with a switching strategy to compensate for the estimation errors. Also, an adaptive fuzzy predictor is used to estimate the future values of the system states to compensate for the time delay. The adaptation laws are used to tune the controller and predictor parameters, which guarantee the stability based on a Lyapunov-Krasovskii functional. To evaluate the method effectiveness, the simulation and experiment on an overhead crane system are presented. According to the obtained results, AFP-SMC can effectively control the uncertain nonlinear systems, subject to input delays of known bound. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Failing to learn from negative prediction errors: Obesity is associated with alterations in a fundamental neural learning mechanism.

PubMed

Mathar, David; Neumann, Jane; Villringer, Arno; Horstmann, Annette

2017-10-01

Prediction errors (PEs) encode the difference between expected and actual action outcomes in the brain via dopaminergic modulation. Integration of these learning signals ensures efficient behavioral adaptation. Obesity has recently been linked to altered dopaminergic fronto-striatal circuits, thus implying impairments in cognitive domains that rely on its integrity. 28 obese and 30 lean human participants performed an implicit stimulus-response learning paradigm inside an fMRI scanner. Computational modeling and psycho-physiological interaction (PPI) analysis was utilized for assessing PE-related learning and associated functional connectivity. We show that human obesity is associated with insufficient incorporation of negative PEs into behavioral adaptation even in a non-food context, suggesting differences in a fundamental neural learning mechanism. Obese subjects were less efficient in using negative PEs to improve implicit learning performance, despite proper coding of PEs in striatum. We further observed lower functional coupling between ventral striatum and supplementary motor area in obese subjects subsequent to negative PEs. Importantly, strength of functional coupling predicted task performance and negative PE utilization. These findings show that obesity is linked to insufficient behavioral adaptation specifically in response to negative PEs, and to associated alterations in function and connectivity within the fronto-striatal system. Recognition of neural differences as a central characteristic of obesity hopefully paves the way to rethink established intervention strategies: Differential behavioral sensitivity to negative and positive PEs should be considered when designing intervention programs. Measures relying on penalization of unwanted behavior may prove less effective in obese subjects than alternative approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

Relationship of Temporal Lobe Volumes to Neuropsychological Test Performance in Healthy Children

ERIC Educational Resources Information Center

Wells, Carolyn T.; Mahone, E. Mark; Matson, Melissa A.; Kates, Wendy R.; Hay, Trisha; Horska, Alena

2008-01-01

Ecological validity of neuropsychological assessment includes the ability of tests to predict real-world functioning and/or covary with brain structures. Studies have examined the relationship between adaptive skills and test performance, with less focus on the association between regional brain volumes and neurobehavioral function in healthy…

Beyond the pleistocene: using phylogeny and constraint to inform the evolutionary psychology of human mating.

PubMed

Eastwick, Paul W

2009-09-01

Evolutionary psychologists explore the adaptive function of traits and behaviors that characterize modern Homo sapiens. However, evolutionary psychologists have yet to incorporate the phylogenetic relationship between modern Homo sapiens and humans' hominid and pongid relatives (both living and extinct) into their theorizing. By considering the specific timing of evolutionary events and the role of evolutionary constraint, researchers using the phylogenetic approach can generate new predictions regarding mating phenomena and derive new explanations for existing evolutionary psychological findings. Especially useful is the concept of the adaptive workaround-an adaptation that manages the maladaptive elements of a pre-existing evolutionary constraint. The current review organizes 7 features of human mating into their phylogenetic context and presents evidence that 2 adaptive workarounds played a critical role as Homo sapiens's mating psychology evolved. These adaptive workarounds function in part to mute or refocus the effects of older, previously evolved adaptations and highlight the layered nature of humans' mating psychology. (c) 2009 APA, all rights reserved.

The adaptive evolution of the mammalian mitochondrial genome

PubMed Central

da Fonseca, Rute R; Johnson, Warren E; O'Brien, Stephen J; Ramos, Maria João; Antunes, Agostinho

2008-01-01

Background The mitochondria produce up to 95% of a eukaryotic cell's energy through oxidative phosphorylation. The proteins involved in this vital process are under high functional constraints. However, metabolic requirements vary across species, potentially modifying selective pressures. We evaluate the adaptive evolution of 12 protein-coding mitochondrial genes in 41 placental mammalian species by assessing amino acid sequence variation and exploring the functional implications of observed variation in secondary and tertiary protein structures. Results Wide variation in the properties of amino acids were observed at functionally important regions of cytochrome b in species with more-specialized metabolic requirements (such as adaptation to low energy diet or large body size, such as in elephant, dugong, sloth, and pangolin, and adaptation to unusual oxygen requirements, for example diving in cetaceans, flying in bats, and living at high altitudes in alpacas). Signatures of adaptive variation in the NADH dehydrogenase complex were restricted to the loop regions of the transmembrane units which likely function as protons pumps. Evidence of adaptive variation in the cytochrome c oxidase complex was observed mostly at the interface between the mitochondrial and nuclear-encoded subunits, perhaps evidence of co-evolution. The ATP8 subunit, which has an important role in the assembly of F0, exhibited the highest signal of adaptive variation. ATP6, which has an essential role in rotor performance, showed a high adaptive variation in predicted loop areas. Conclusion Our study provides insight into the adaptive evolution of the mtDNA genome in mammals and its implications for the molecular mechanism of oxidative phosphorylation. We present a framework for future experimental characterization of the impact of specific mutations in the function, physiology, and interactions of the mtDNA encoded proteins involved in oxidative phosphorylation. PMID:18318906

Validity of prototype diagnosis for mood and anxiety disorders.

PubMed

DeFife, Jared A; Peart, Joanne; Bradley, Bekh; Ressler, Kerry; Drill, Rebecca; Westen, Drew

2013-02-01

CONTEXT With growing recognition that most forms of psychopathology are best represented as dimensions or spectra, a central question becomes how to implement dimensional diagnosis in a way that is empirically sound and clinically useful. Prototype matching, which involves comparing a patient's clinical presentation with a prototypical description of the disorder, is an approach to diagnosis that has gained increasing attention with forthcoming revisions to both the DSM and the International Classification of Diseases. OBJECTIVE To examine prototype diagnosis for mood and anxiety disorders. DESIGN, SETTING, AND PATIENTS In the first study, we examined clinicians' DSM-IV and prototype diagnoses with their ratings of the patients' adaptive functioning and patients' self-reported symptoms. In the second study, independent interviewers made prototype diagnoses following either a systematic clinical interview or a structured diagnostic interview. A third interviewer provided independent ratings of global adaptive functioning. Patients were recruited as outpatients (study 1; N = 84) and from primary care clinics (study 2; N = 143). MAIN OUTCOME MEASURES Patients' self-reported mood, anxiety, and externalizing symptoms along with independent clinical ratings of adaptive functioning. RESULTS Clinicians' prototype diagnoses showed small to moderate correlations with patient-reported psychopathology and performed as well as or better than DSM-IV diagnoses. Prototype diagnoses from independent interviewers correlated on average r = .50 and showed substantial incremental validity over DSM-IV diagnoses in predicting adaptive functioning. CONCLUSIONS Prototype matching is a viable alternative for psychiatric diagnosis. As in research on personality disorders, mood and anxiety disorder prototypes outperformed DSM-IV decision rules in predicting psychopathology and global functioning. Prototype matching has multiple advantages, including ease of use in clinical practice, reduced artifactual comorbidity, compatibility with naturally occurring cognitive processes in diagnosticians, and ready translation into both categorical and dimensional diagnosis.

Do Demographic Factors, School Functioning, and Quality of Student-Teacher Relationships as Rated by Teachers Predict Internalising and Externalising Problems among Norwegian Schoolchildren?

ERIC Educational Resources Information Center

Drugli, May Britt; Klokner, Christian; Larsson, Bo

2011-01-01

The present study explored the association between child internalising and externalising problems in schools and demographic factors (sex and age), school functioning (academic performance and adaptive functioning) and teacher-reported student-teacher relationship quality in a cross-sectional study using structural equation modelling. The study…

Sensorimotor and Cognitive Predictors of Impaired Gait Adaptability in Older People.

PubMed

Caetano, Maria Joana D; Menant, Jasmine C; Schoene, Daniel; Pelicioni, Paulo H S; Sturnieks, Daina L; Lord, Stephen R

2017-09-01

The ability to adapt gait when negotiating unexpected hazards is crucial to maintain stability and avoid falling. This study investigated whether impaired gait adaptability in a task including obstacle and stepping targets is associated with cognitive and sensorimotor capacities in older adults. Fifty healthy older adults (74±7 years) were instructed to either (a) avoid an obstacle at usual step distance or (b) step onto a target at either a short or long step distance projected on a walkway two heel strikes ahead and then continue walking. Participants also completed cognitive and sensorimotor function assessments. Stroop test and reaction time performance significantly discriminated between participants who did and did not make stepping errors, and poorer Trail-Making test performance predicted shorter penultimate step length in the obstacle avoidance condition. Slower reaction time predicted poorer stepping accuracy; increased postural sway, weaker quadriceps strength, and poorer Stroop and Trail-Making test performances predicted increased number of steps taken to approach the target/obstacle and shorter step length; and increased postural sway and higher concern about falling predicted slower step velocity. Superior executive function, fast processing speed, and good muscle strength and balance were all associated with successful gait adaptability. Processing speed appears particularly important for precise foot placements; cognitive capacity for step length adjustments; and early and/or additional cognitive processing involving the inhibition of a stepping pattern for obstacle avoidance. This information may facilitate fall risk assessments and fall prevention strategies. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Validity of an adaptation of the Framingham cardiovascular risk function: the VERIFICA study

PubMed Central

Marrugat, Jaume; Subirana, Isaac; Comín, Eva; Cabezas, Carmen; Vila, Joan; Elosua, Roberto; Nam, Byung‐Ho; Ramos, Rafel; Sala, Joan; Solanas, Pascual; Cordón, Ferran; Gené‐Badia, Joan; D'Agostino, Ralph B

2007-01-01

Background To assess the reliability and accuracy of the Framingham coronary heart disease (CHD) risk function adapted by the Registre Gironí del Cor (REGICOR) investigators in Spain. Methods A 5‐year follow‐up study was completed in 5732 participants aged 35–74 years. The adaptation consisted of using in the function the average population risk factor prevalence and the cumulative incidence observed in Spain instead of those from Framingham in a Cox proportional hazards model. Reliability and accuracy in estimating the observed cumulative incidence were tested with the area under the curve comparison and goodness‐of‐fit test, respectively. Results The Kaplan–Meier CHD cumulative incidence during the follow‐up was 4.0% in men and 1.7% in women. The original Framingham function and the REGICOR adapted estimates were 10.4% and 4.8%, and 3.6% and 2.0%, respectively. The REGICOR‐adapted function's estimate did not differ from the observed cumulated incidence (goodness of fit in men, p = 0.078, in women, p = 0.256), whereas all the original Framingham function estimates differed significantly (p<0.001). Reliabilities of the original Framingham function and of the best Cox model fit with the study data were similar in men (area under the receiver operator characteristic curve 0.68 and 0.69, respectively, p = 0.273), whereas the best Cox model fitted better in women (0.73 and 0.81, respectively, p<0.001). Conclusion The Framingham function adapted to local population characteristics accurately and reliably predicted the 5‐year CHD risk for patients aged 35–74 years, in contrast with the original function, which consistently overestimated the actual risk. PMID:17183014

Emergent Neutrality in Adaptive Asexual Evolution

PubMed Central

Schiffels, Stephan; Szöllősi, Gergely J.; Mustonen, Ville; Lässig, Michael

2011-01-01

In nonrecombining genomes, genetic linkage can be an important evolutionary force. Linkage generates interference interactions, by which simultaneously occurring mutations affect each other’s chance of fixation. Here, we develop a comprehensive model of adaptive evolution in linked genomes, which integrates interference interactions between multiple beneficial and deleterious mutations into a unified framework. By an approximate analytical solution, we predict the fixation rates of these mutations, as well as the probabilities of beneficial and deleterious alleles at fixed genomic sites. We find that interference interactions generate a regime of emergent neutrality: all genomic sites with selection coefficients smaller in magnitude than a characteristic threshold have nearly random fixed alleles, and both beneficial and deleterious mutations at these sites have nearly neutral fixation rates. We show that this dynamic limits not only the speed of adaptation, but also a population’s degree of adaptation in its current environment. We apply the model to different scenarios: stationary adaptation in a time-dependent environment and approach to equilibrium in a fixed environment. In both cases, the analytical predictions are in good agreement with numerical simulations. Our results suggest that interference can severely compromise biological functions in an adapting population, which sets viability limits on adaptive evolution under linkage. PMID:21926305

Graded-threshold parametric response maps: towards a strategy for adaptive dose painting

NASA Astrophysics Data System (ADS)

Lausch, A.; Jensen, N.; Chen, J.; Lee, T. Y.; Lock, M.; Wong, E.

2014-03-01

Purpose: To modify the single-threshold parametric response map (ST-PRM) method for predicting treatment outcomes in order to facilitate its use for guidance of adaptive dose painting in intensity-modulated radiotherapy. Methods: Multiple graded thresholds were used to extend the ST-PRM method (Nat. Med. 2009;15(5):572-576) such that the full functional change distribution within tumours could be represented with respect to multiple confidence interval estimates for functional changes in similar healthy tissue. The ST-PRM and graded-threshold PRM (GT-PRM) methods were applied to functional imaging scans of 5 patients treated for hepatocellular carcinoma. Pre and post-radiotherapy arterial blood flow maps (ABF) were generated from CT-perfusion scans of each patient. ABF maps were rigidly registered based on aligning tumour centres of mass. ST-PRM and GT-PRM analyses were then performed on overlapping tumour regions within the registered ABF maps. Main findings: The ST-PRMs contained many disconnected clusters of voxels classified as having a significant change in function. While this may be useful to predict treatment response, it may pose challenges for identifying boost volumes or for informing dose-painting by numbers strategies. The GT-PRMs included all of the same information as ST-PRMs but also visualized the full tumour functional change distribution. Heterogeneous clusters in the ST-PRMs often became more connected in the GT-PRMs by voxels with similar functional changes. Conclusions: GT-PRMs provided additional information which helped to visualize relationships between significant functional changes identified by ST-PRMs. This may enhance ST-PRM utility for guiding adaptive dose painting.

Model-on-Demand Predictive Control for Nonlinear Hybrid Systems With Application to Adaptive Behavioral Interventions

PubMed Central

Nandola, Naresh N.; Rivera, Daniel E.

2011-01-01

This paper presents a data-centric modeling and predictive control approach for nonlinear hybrid systems. System identification of hybrid systems represents a challenging problem because model parameters depend on the mode or operating point of the system. The proposed algorithm applies Model-on-Demand (MoD) estimation to generate a local linear approximation of the nonlinear hybrid system at each time step, using a small subset of data selected by an adaptive bandwidth selector. The appeal of the MoD approach lies in the fact that model parameters are estimated based on a current operating point; hence estimation of locations or modes governed by autonomous discrete events is achieved automatically. The local MoD model is then converted into a mixed logical dynamical (MLD) system representation which can be used directly in a model predictive control (MPC) law for hybrid systems using multiple-degree-of-freedom tuning. The effectiveness of the proposed MoD predictive control algorithm for nonlinear hybrid systems is demonstrated on a hypothetical adaptive behavioral intervention problem inspired by Fast Track, a real-life preventive intervention for improving parental function and reducing conduct disorder in at-risk children. Simulation results demonstrate that the proposed algorithm can be useful for adaptive intervention problems exhibiting both nonlinear and hybrid character. PMID:21874087

Adaptive reliance on the most stable sensory predictions enhances perceptual feature extraction of moving stimuli.

PubMed

Kumar, Neeraj; Mutha, Pratik K

2016-03-01

The prediction of the sensory outcomes of action is thought to be useful for distinguishing self- vs. externally generated sensations, correcting movements when sensory feedback is delayed, and learning predictive models for motor behavior. Here, we show that aspects of another fundamental function-perception-are enhanced when they entail the contribution of predicted sensory outcomes and that this enhancement relies on the adaptive use of the most stable predictions available. We combined a motor-learning paradigm that imposes new sensory predictions with a dynamic visual search task to first show that perceptual feature extraction of a moving stimulus is poorer when it is based on sensory feedback that is misaligned with those predictions. This was possible because our novel experimental design allowed us to override the "natural" sensory predictions present when any action is performed and separately examine the influence of these two sources on perceptual feature extraction. We then show that if the new predictions induced via motor learning are unreliable, rather than just relying on sensory information for perceptual judgments, as is conventionally thought, then subjects adaptively transition to using other stable sensory predictions to maintain greater accuracy in their perceptual judgments. Finally, we show that when sensory predictions are not modified at all, these judgments are sharper when subjects combine their natural predictions with sensory feedback. Collectively, our results highlight the crucial contribution of sensory predictions to perception and also suggest that the brain intelligently integrates the most stable predictions available with sensory information to maintain high fidelity in perceptual decisions. Copyright © 2016 the American Physiological Society.

Adaptive strategies for materials design using uncertainties

DOE PAGES

Balachandran, Prasanna V.; Xue, Dezhen; Theiler, James; ...

2016-01-21

Here, we compare several adaptive design strategies using a data set of 223 M2AX family of compounds for which the elastic properties [bulk (B), shear (G), and Young’s (E) modulus] have been computed using density functional theory. The design strategies are decomposed into an iterative loop with two main steps: machine learning is used to train a regressor that predicts elastic properties in terms of elementary orbital radii of the individual components of the materials; and a selector uses these predictions and their uncertainties to choose the next material to investigate. The ultimate goal is to obtain a material withmore » desired elastic properties in as few iterations as possible. We examine how the choice of data set size, regressor and selector impact the design. We find that selectors that use information about the prediction uncertainty outperform those that don’t. Our work is a step in illustrating how adaptive design tools can guide the search for new materials with desired properties.« less

An insula-frontostriatal network mediates flexible cognitive control by adaptively predicting changing control demands

PubMed Central

Jiang, Jiefeng; Beck, Jeffrey; Heller, Katherine; Egner, Tobias

2015-01-01

The anterior cingulate and lateral prefrontal cortices have been implicated in implementing context-appropriate attentional control, but the learning mechanisms underlying our ability to flexibly adapt the control settings to changing environments remain poorly understood. Here we show that human adjustments to varying control demands are captured by a reinforcement learner with a flexible, volatility-driven learning rate. Using model-based functional magnetic resonance imaging, we demonstrate that volatility of control demand is estimated by the anterior insula, which in turn optimizes the prediction of forthcoming demand in the caudate nucleus. The caudate's prediction of control demand subsequently guides the implementation of proactive and reactive attentional control in dorsal anterior cingulate and dorsolateral prefrontal cortices. These data enhance our understanding of the neuro-computational mechanisms of adaptive behaviour by connecting the classic cingulate-prefrontal cognitive control network to a subcortical control-learning mechanism that infers future demands by flexibly integrating remote and recent past experiences. PMID:26391305

Adaptive strategies for materials design using uncertainties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Balachandran, Prasanna V.; Xue, Dezhen; Theiler, James

Here, we compare several adaptive design strategies using a data set of 223 M2AX family of compounds for which the elastic properties [bulk (B), shear (G), and Young’s (E) modulus] have been computed using density functional theory. The design strategies are decomposed into an iterative loop with two main steps: machine learning is used to train a regressor that predicts elastic properties in terms of elementary orbital radii of the individual components of the materials; and a selector uses these predictions and their uncertainties to choose the next material to investigate. The ultimate goal is to obtain a material withmore » desired elastic properties in as few iterations as possible. We examine how the choice of data set size, regressor and selector impact the design. We find that selectors that use information about the prediction uncertainty outperform those that don’t. Our work is a step in illustrating how adaptive design tools can guide the search for new materials with desired properties.« less

The specificity of stimulus-specific adaptation in human auditory cortex increases with repeated exposure to the adapting stimulus.

PubMed

Briley, Paul M; Krumbholz, Katrin

2013-12-01

The neural response to a sensory stimulus tends to be more strongly reduced when the stimulus is preceded by the same, rather than a different, stimulus. This stimulus-specific adaptation (SSA) is ubiquitous across the senses. In hearing, SSA has been suggested to play a role in change detection as indexed by the mismatch negativity. This study sought to test whether SSA, measured in human auditory cortex, is caused by neural fatigue (reduction in neural responsiveness) or by sharpening of neural tuning to the adapting stimulus. For that, we measured event-related cortical potentials to pairs of pure tones with varying frequency separation and stimulus onset asynchrony (SOA). This enabled us to examine the relationship between the degree of specificity of adaptation as a function of frequency separation and the rate of decay of adaptation with increasing SOA. Using simulations of tonotopic neuron populations, we demonstrate that the fatigue model predicts independence of adaptation specificity and decay rate, whereas the sharpening model predicts interdependence. The data showed independence and thus supported the fatigue model. In a second experiment, we measured adaptation specificity after multiple presentations of the adapting stimulus. The multiple adapters produced more adaptation overall, but the effect was more specific to the adapting frequency. Within the context of the fatigue model, the observed increase in adaptation specificity could be explained by assuming a 2.5-fold increase in neural frequency selectivity. We discuss possible bottom-up and top-down mechanisms of this effect.

Development and psychometric testing of the Adaptive Capacity Index, an instrument to measure adaptive capacity in individuals with advanced cancer.

PubMed

Olson, K; Rogers, W T; Cui, Y; Cree, M; Baracos, V; Rust, T; Mellott, I; Johnson, L; Macmillan, K; Bonville, N

2011-08-01

We have proposed that declines in adaptive capacity, defined as the ability to adapt to multiple stressors, may serve as an indicator of risk for fatigue. A comprehensive measure of adaptive capacity does not exist. In this paper we describe construction of an instrument to measure adaptive capacity, the Adaptive Capacity Index (ACI). Descriptive and psychometric. Six sites providing palliative care in Western Canada. ≥18 years old, diagnosed with advanced cancer, able to read and write English, Mini-Mental Status Exam score ≥22. Pilot study n=48; Main study n=225 stratified using the Edmonton Symptom Assessment Scale (ESAS) tiredness score (≥0 to ≤2 n=60; ≥3 to ≤6 n=108; ≥7 and ≤10 n=57). Following ethics approval, 17 experts in symptom management assisted with content validation and consenting individuals completed the Functional Assessment of Cancer Therapy-Fatigue (FACT-F), the Profile of Mood States-Vigor short form (POMS-Vsf), and the ACI. A research assistant collected demographic information and assigned an Eastern Cooperative Oncology Group (ECOG) score. Data were analyzed using descriptive and inferential statistics (i.e., exploratory factor analyses, correlation, multivariate analyses of variance, and multiple regression). Five 6-item ACI factors/subscales (Cognitive Function, Stamina/Muscle Endurance, Sleep Quality, Emotional Reactivity, and Social Interaction) were identified. The ACI-total scale and its subscales were internally consistent (Cronbach's alpha 0.76-0.89), and were significantly correlated with each other, and with each fatigue measure (Pearson's r ranging from -0.724 to 0.634). The ACI total score was sensitive to changes in the ESAS tiredness score. Stamina/Muscle Endurance, Cognitive Function, and Sleep Quality predicted 60.8% of the variance in FACT-F. Stamina/Muscle Endurance and Social Interaction predicted 36.8% of the variance in POMS-Vsf. Stamina/Muscle Endurance and Sleep Quality predicted 8% of the variance in ECOG. The ACI is reliable and has beginning evidence of validity. In future studies we will examine relationships between ACI subscale scores and subsequent increases in fatigue and explore linkages to physiological processes. We will also establish ACI norms for early and late stage cancers and explore variations in ACI subscale scores base on age or gender. Copyright © 2011 Elsevier Ltd. All rights reserved.

Niche convergence suggests functionality of the nocturnal fovea.

PubMed

Moritz, Gillian L; Melin, Amanda D; Tuh Yit Yu, Fred; Bernard, Henry; Ong, Perry S; Dominy, Nathaniel J

2014-01-01

The fovea is a declivity of the retinal surface associated with maximum visual acuity. Foveae are widespread across vertebrates, but among mammals they are restricted to haplorhine primates (tarsiers, monkeys, apes, and humans), which are primarily diurnal. Thus primates have long contributed to the view that foveae are functional adaptations to diurnality. The foveae of tarsiers, which are nocturnal, are widely interpreted as vestigial traits and therefore evidence of a diurnal ancestry. This enduring premise is central to adaptive hypotheses on the origins of anthropoid primates; however, the question of whether tarsier foveae are functionless anachronisms or nocturnal adaptations remains open. To explore this question, we compared the diets of tarsiers (Tarsius) and scops owls (Otus), taxa united by numerous anatomical homoplasies, including foveate vision. A functional interpretation of these homoplasies predicts dietary convergence. We tested this prediction by analyzing stable isotope ratios that integrate dietary information. In Borneo and the Philippines, the stable carbon isotope compositions of Tarsius and Otus were indistinguishable, whereas the stable nitrogen isotope composition of Otus was marginally higher than that of Tarsius. Our results indicate that species in both genera consumed mainly ground-dwelling prey. Taken together, our findings support a functional interpretation of the many homoplasies shared by tarsiers and scops owls, including a retinal fovea. We suggest that the fovea might function similarly in tarsiers and scops owls by calibrating the auditory localization pathway. The integration of auditory localization and visual fixation during prey detection and acquisition might be critical at low light levels.

Niche convergence suggests functionality of the nocturnal fovea

PubMed Central

Moritz, Gillian L.; Melin, Amanda D.; Tuh Yit Yu, Fred; Bernard, Henry; Ong, Perry S.; Dominy, Nathaniel J.

2014-01-01

The fovea is a declivity of the retinal surface associated with maximum visual acuity. Foveae are widespread across vertebrates, but among mammals they are restricted to haplorhine primates (tarsiers, monkeys, apes, and humans), which are primarily diurnal. Thus primates have long contributed to the view that foveae are functional adaptations to diurnality. The foveae of tarsiers, which are nocturnal, are widely interpreted as vestigial traits and therefore evidence of a diurnal ancestry. This enduring premise is central to adaptive hypotheses on the origins of anthropoid primates; however, the question of whether tarsier foveae are functionless anachronisms or nocturnal adaptations remains open. To explore this question, we compared the diets of tarsiers (Tarsius) and scops owls (Otus), taxa united by numerous anatomical homoplasies, including foveate vision. A functional interpretation of these homoplasies predicts dietary convergence. We tested this prediction by analyzing stable isotope ratios that integrate dietary information. In Borneo and the Philippines, the stable carbon isotope compositions of Tarsius and Otus were indistinguishable, whereas the stable nitrogen isotope composition of Otus was marginally higher than that of Tarsius. Our results indicate that species in both genera consumed mainly ground-dwelling prey. Taken together, our findings support a functional interpretation of the many homoplasies shared by tarsiers and scops owls, including a retinal fovea. We suggest that the fovea might function similarly in tarsiers and scops owls by calibrating the auditory localization pathway. The integration of auditory localization and visual fixation during prey detection and acquisition might be critical at low light levels. PMID:25120441

Assessment of right ventricular adaptability to loading conditions can improve the timing of listing to transplantation in patients with pulmonary arterial hypertension.

PubMed

Dandel, Michael; Knosalla, Christoph; Kemper, Dagmar; Stein, Julia; Hetzer, Roland

2015-03-01

Right ventricle (RV) performance is load dependent, and right-sided heart failure (RHF) is the main cause of death in pulmonary arterial hypertension (PAH). Prediction of RV worsening for timely identification of patients needing transplantation (Tx) is paramount. Assessment of RV adaptability to load has proved useful in certain clinical circumstances. This study assessed its predictive value for RHF-free and Tx-free outcome with PAH. Between 2006 and 2012, all potential Tx candidates with PAH, without RHF at the first evaluation, were selected for follow-up (except congenital heart diseases). At selection and at each follow-up, N-terminal prohormone brain natriuretic peptide (NT-proBNP) and the 6-minute walk distance were measured, and RV adaptability to load was assessed by echocardiography. Collected data were tested for the ability to predict RV stability and Tx-free survival. During a 12-month to 92-month follow-up, RHF developed in 23 of 79 evaluated patients, despite similar medication and no differences in initial RV size and ejection fraction compared with the patients who remained stable. However, unstable patients had an initially lower RV load-adaptation index and afterload-corrected peak global systolic longitudinal strain-rate values as well as higher RV dyssynchrony, tricuspid regurgitation, and NT-proBNP levels (p ≤ 0.01). At certain cutoff values, these variables appeared predictive for 1-year and 3-year freedom from RHF and 3-year Tx-free survival. An RV load-adaptation index reduction of ≥20% showed the highest predictive value (90.0%) for short-term (≤1 year) RV decompensation. Assessment of RV adaptability to load allows prediction of RV function and Tx-free survival with severe PAH during the next 1 to 3 years. This can improve the timing of listing for Tx. Copyright © 2015 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

Modeling gravity-dependent plasticity of the angular vestibuloocular reflex with a physiologically based neural network.

PubMed

Xiang, Yongqing; Yakushin, Sergei B; Cohen, Bernard; Raphan, Theodore

2006-12-01

A neural network model was developed to explain the gravity-dependent properties of gain adaptation of the angular vestibuloocular reflex (aVOR). Gain changes are maximal at the head orientation where the gain is adapted and decrease as the head is tilted away from that position and can be described by the sum of gravity-independent and gravity-dependent components. The adaptation process was modeled by modifying the weights and bias values of a three-dimensional physiologically based neural network of canal-otolith-convergent neurons that drive the aVOR. Model parameters were trained using experimental vertical aVOR gain values. The learning rule aimed to reduce the error between eye velocities obtained from experimental gain values and model output in the position of adaptation. Although the model was trained only at specific head positions, the model predicted the experimental data at all head positions in three dimensions. Altering the relative learning rates of the weights and bias improved the model-data fits. Model predictions in three dimensions compared favorably with those of a double-sinusoid function, which is a fit that minimized the mean square error at every head position and served as the standard by which we compared the model predictions. The model supports the hypothesis that gravity-dependent adaptation of the aVOR is realized in three dimensions by a direct otolith input to canal-otolith neurons, whose canal sensitivities are adapted by the visual-vestibular mismatch. The adaptation is tuned by how the weights from otolith input to the canal-otolith-convergent neurons are adapted for a given head orientation.

Adaptation of social and non-social cues to direction in adults with autism spectrum disorder and neurotypical adults with autistic traits.

PubMed

Lawson, Rebecca P; Aylward, Jessica; Roiser, Jonathan P; Rees, Geraint

2018-01-01

Perceptual constancy strongly relies on adaptive gain control mechanisms, which shift perception as a function of recent sensory history. Here we examined the extent to which individual differences in magnitude of adaptation aftereffects for social and non-social directional cues are related to autistic traits and sensory sensitivity in healthy participants (Experiment 1); and also whether adaptation for social and non-social directional cues is differentially impacted in adults with Autism Spectrum Disorder (ASD) relative to neurotypical (NT) controls (Experiment 2). In Experiment 1, individuals with lower susceptibility to adaptation aftereffects, i.e. more 'veridical' perception, showed higher levels of autistic traits across social and non-social stimuli. Furthermore, adaptation aftereffects were predictive of sensory sensitivity. In Experiment 2, only adaptation to eye-gaze was diminished in adults with ASD, and this was related to difficulties categorizing eye-gaze direction at baseline. Autism Diagnostic Observation Schedule (ADOS) scores negatively predicted lower adaptation for social (head and eye-gaze direction) but not non-social (chair) stimuli. These results suggest that the relationship between adaptation and the broad socio-cognitive processing style captured by 'autistic traits' may be relatively domain-general, but in adults with ASD diminished adaptation is only apparent where processing is most severely impacted, such as the perception of social attention cues. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Adaptive style and differences in parent and child report of health-related quality of life in children with cancer.

PubMed

Jurbergs, Nichole; Russell, Kathryn M W; Long, Alanna; Phipps, Sean

2008-01-01

The objective of this study was to examine the self-reported health-related quality of life (HRQL) of children with cancer, and the consistency between child and parent reports of child HRQL, as a function of the child's adaptive style. Participants included 199 children with cancer, 108 healthy children, and their parents. Children completed self-report measures of HRQL and adaptive style. Measures of adaptive style were used to categorize children as high anxious, low anxious, defensive high anxious or repressor. Parents completed measures reporting their children's HRQL. Adaptive style was a significant predictor of child-reported HRQL, particularly on the psychosocial scales, with children identified as repressors reporting the best HRQL. Adaptive style was also predictive of discrepancies between parent and child report of child HRQL. Repressor and low anxious children reported better HRQL than did their parents, while high anxious children reported poorer HRQL, regardless of health status. Adaptive style is a significant determinant of self-reported HRQL in children, particularly in psychosocial domains, while health status (i.e. cancer patient vs healthy control) is predictive only of physical health domains. Researchers and clinicians should be aware of the impact of child adaptive style when assessing HRQL outcomes using self- or parent report.

Desired Accuracy Estimation of Noise Function from ECG Signal by Fuzzy Approach

PubMed Central

Vahabi, Zahra; Kermani, Saeed

2012-01-01

Unknown noise and artifacts present in medical signals with non-linear fuzzy filter will be estimated and then removed. An adaptive neuro-fuzzy interference system which has a non-linear structure presented for the noise function prediction by before Samples. This paper is about a neuro-fuzzy method to estimate unknown noise of Electrocardiogram signal. Adaptive neural combined with Fuzzy System to construct a fuzzy Predictor. For this system setting parameters such as the number of Membership Functions for each input and output, training epochs, type of MFs for each input and output, learning algorithm and etc. is determined by learning data. At the end simulated experimental results are presented for proper validation. PMID:23717810

Conceptual change and preschoolers' theory of mind: evidence from load-force adaptation.

PubMed

Sabbagh, Mark A; Hopkins, Sydney F R; Benson, Jeannette E; Flanagan, J Randall

2010-01-01

Prominent theories of preschoolers' theory of mind development have included a central role for changing or adapting existing conceptual structures in response to experiences. Because of the relatively protracted timetable of theory of mind development, it has been difficult to test this assumption about the role of adaptation directly. To gain evidence that cognitive adaptation is particularly important for theory of mind development, we sought to determine whether individual differences in cognitive adaptation in a non-social domain predicted preschoolers' theory of mind development. Twenty-five preschoolers were tested on batteries of theory of mind tasks, executive functioning tasks, and on their ability to adapt their lifting behavior to smoothly lift an unexpectedly heavy object. Results showed that children who adapted their lifting behavior more rapidly performed better on theory of mind tasks than those who adapted more slowly. These findings held up when age and performance on the executive functioning battery were statistically controlled. Although preliminary, we argue that this relation is attributable to individual differences in children's domain general abilities to efficiently change existing conceptual structures in response to experience. Copyright © 2010 Elsevier Ltd. All rights reserved.

Time Frame and Justice Motive: Future Perspective Moderates the Adaptive Function of General Belief in a Just World

PubMed Central

Wu, Michael Shengtao; Sutton, Robbie M.; Yan, Xiaodan; Zhou, Chan; Chen, Yiwen; Zhu, Zhuohong; Han, Buxin

2013-01-01

Background The human ability to envision the future, that is, to take a future perspective (FP), plays a key role in the justice motive and its function in transcending disadvantages and misfortunes. The present research investigated whether individual (Study 1) and situational (Study 2) differences in FP moderated the association of general belief in a just world (GBJW) with psychological resilience. Methodology/Principal Findings We investigated FP, GBJW, and resilience in sample of adolescents (n = 223) and disaster survivors (n = 218) in China. In Study 1, adolescents revealed stronger GBJW than PBJW, and GBJW uniquely predicted resilience in the daily lives of those with high FP (but not those with low FP). In Study 2, natural priming of FP (vs. no FP) facilitated the association of GBJW with resilience after disaster. Conclusions/Significance Supporting predictions, participants endorsed GBJW more strongly than PBJW. Further, GBJW interacted with FP in both studies, such that there was an association between GBJW and resilience at high but not low levels of FP. The results corroborate recent findings suggesting that GBJW may be more psychologically adaptive than PBJW among some populations. They also confirm that focusing on the future is an important aspect of the adaptive function of just-world beliefs. PMID:24312235

Adaptive constructive processes and the future of memory.

PubMed

Schacter, Daniel L

2012-11-01

Memory serves critical functions in everyday life but is also prone to error. This article examines adaptive constructive processes, which play a functional role in memory and cognition but can also produce distortions, errors, and illusions. The article describes several types of memory errors that are produced by adaptive constructive processes and focuses in particular on the process of imagining or simulating events that might occur in one's personal future. Simulating future events relies on many of the same cognitive and neural processes as remembering past events, which may help to explain why imagination and memory can be easily confused. The article considers both pitfalls and adaptive aspects of future event simulation in the context of research on planning, prediction, problem solving, mind-wandering, prospective and retrospective memory, coping and positivity bias, and the interconnected set of brain regions known as the default network. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Performance prediction evaluation of ceramic materials in point-focusing solar receivers

NASA Technical Reports Server (NTRS)

Ewing, J.; Zwissler, J.

1979-01-01

A performance prediction was adapted to evaluate the use of ceramic materials in solar receivers for point focusing distributed applications. System requirements were determined including the receiver operating environment and system operating parameters for various engine types. Preliminary receiver designs were evolved from these system requirements. Specific receiver designs were then evaluated to determine material functional requirements.

An efficient algorithm for building locally refined hp - adaptive H-PCFE: Application to uncertainty quantification

NASA Astrophysics Data System (ADS)

Chakraborty, Souvik; Chowdhury, Rajib

2017-12-01

Hybrid polynomial correlated function expansion (H-PCFE) is a novel metamodel formulated by coupling polynomial correlated function expansion (PCFE) and Kriging. Unlike commonly available metamodels, H-PCFE performs a bi-level approximation and hence, yields more accurate results. However, till date, it is only applicable to medium scaled problems. In order to address this apparent void, this paper presents an improved H-PCFE, referred to as locally refined hp - adaptive H-PCFE. The proposed framework computes the optimal polynomial order and important component functions of PCFE, which is an integral part of H-PCFE, by using global variance based sensitivity analysis. Optimal number of training points are selected by using distribution adaptive sequential experimental design. Additionally, the formulated model is locally refined by utilizing the prediction error, which is inherently obtained in H-PCFE. Applicability of the proposed approach has been illustrated with two academic and two industrial problems. To illustrate the superior performance of the proposed approach, results obtained have been compared with those obtained using hp - adaptive PCFE. It is observed that the proposed approach yields highly accurate results. Furthermore, as compared to hp - adaptive PCFE, significantly less number of actual function evaluations are required for obtaining results of similar accuracy.

Attachment as an organizer of behavior: implications for substance abuse problems and willingness to seek treatment

PubMed Central

Caspers, Kristin M; Yucuis, Rebecca; Troutman, Beth; Spinks, Ruth

2006-01-01

Background Attachment theory allows specific predictions about the role of attachment representations in organizing behavior. Insecure attachment is hypothesized to predict maladaptive emotional regulation whereas secure attachment is hypothesized to predict adaptive emotional regulation. In this paper, we test specific hypotheses about the role of attachment representations in substance abuse/dependence and treatment participation. Based on theory, we expect divergence between levels of maladaptive functioning and adaptive methods of regulating negative emotions. Methods Participants for this study consist of a sample of adoptees participating in an ongoing longitudinal adoption study (n = 208). The Semi-Structured Assessment of the Genetics of Alcohol-II [41] was used to determine lifetime substance abuse/dependence and treatment participation. Attachment representations were derived by the Adult Attachment Interview [AAI; [16

Macrocell path loss prediction using artificial intelligence techniques

NASA Astrophysics Data System (ADS)

Usman, Abraham U.; Okereke, Okpo U.; Omizegba, Elijah E.

2014-04-01

The prediction of propagation loss is a practical non-linear function approximation problem which linear regression or auto-regression models are limited in their ability to handle. However, some computational Intelligence techniques such as artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFISs) have been shown to have great ability to handle non-linear function approximation and prediction problems. In this study, the multiple layer perceptron neural network (MLP-NN), radial basis function neural network (RBF-NN) and an ANFIS network were trained using actual signal strength measurement taken at certain suburban areas of Bauchi metropolis, Nigeria. The trained networks were then used to predict propagation losses at the stated areas under differing conditions. The predictions were compared with the prediction accuracy of the popular Hata model. It was observed that ANFIS model gave a better fit in all cases having higher R2 values in each case and on average is more robust than MLP and RBF models as it generalises better to a different data.

Emotion Regulation Predicts Pain and Functioning in Children With Juvenile Idiopathic Arthritis: An Electronic Diary Study

PubMed Central

Bromberg, Maggie H.; Anthony, Kelly K.; Gil, Karen M.; Franks, Lindsey; Schanberg, Laura E.

2012-01-01

Objectives This study utilized e-diaries to evaluate whether components of emotion regulation predict daily pain and function in children with juvenile idiopathic arthritis (JIA). Methods 43 children ages 8–17 years and their caregivers provided baseline reports of child emotion regulation. Children then completed thrice daily e-diary assessments of emotion, pain, and activity involvement for 28 days. E-diary ratings of negative and positive emotions were used to calculate emotion variability and to infer adaptive emotion modulation following periods of high or low emotion intensity. Hierarchical linear models were used to evaluate how emotion regulation related to pain and function. Results The attenuation of negative emotion following a period of high negative emotion predicted reduced pain; greater variability of negative emotion predicted higher pain and increased activity limitation. Indices of positive emotion regulation also significantly predicted pain. Conclusions Components of emotion regulation as captured by e-diaries predict important health outcomes in children with JIA. PMID:22037006

Targeting Metabolic Plasticity in Breast Cancer Cells via Mitochondrial Complex I Modulation

PubMed Central

Xu, Qijin; Biener-Ramanujan, Eva; Yang, Wei; Ramanujan, V Krishnan

2016-01-01

Purpose Heterogeneity commonly observed in clinical tumors stems both from the genetic diversity as well as from the differential metabolic adaptation of multiple cancer types during their struggle to maintain uncontrolled proliferation and invasion in vivo. This study aims to identify a potential metabolic window of such adaptation in aggressive human breast cancer cell lines. Methods With a multidisciplinary approach using high resolution imaging, cell metabolism assays, proteomic profiling and animal models of human tumor xenografts and via clinically-relevant, pharmacological approach for modulating mitochondrial complex I function in human breast cancer cell lines, we report a novel route to target metabolic plasticity in human breast cancer cells. Results By a systematic modulation of mitochondrial function and by mitigating metabolic switch phenotype in aggressive human breast cancer cells, we demonstrate that the resulting metabolic adaptation signatures can predictably decrease tumorigenic potential in vivo. Proteomic profiling of the metabolic adaptation in these cells further revealed novel protein-pathway interactograms highlighting the importance of antioxidant machinery in the observed metabolic adaptation. Conclusions Improved metabolic adaptation potential in aggressive human breast cancer cells contribute to improving mitochondrial function and reducing metabolic switch phenotype –which may be vital for targeting primary tumor growth in vivo. PMID:25677747

Anxiety symptoms in young people with autism spectrum disorder attending special schools: Associations with gender, adaptive functioning and autism symptomatology.

PubMed

Magiati, Iliana; Ong, Clarissa; Lim, Xin Yi; Tan, Julianne Wen-Li; Ong, Amily Yi Lin; Patrycia, Ferninda; Fung, Daniel Shuen Sheng; Sung, Min; Poon, Kenneth K; Howlin, Patricia

2016-04-01

Anxiety-related problems are among the most frequently reported mental health difficulties in autism spectrum disorder. As most research has focused on clinical samples or high-functioning children with autism spectrum disorder, less is known about the factors associated with anxiety in community samples across the ability range. This cross-sectional study examined the association of gender, age, adaptive functioning and autism symptom severity with different caregiver-reported anxiety symptoms. Participants were caregivers of 241 children (6-18 years old) with autism spectrum disorder attending special schools in Singapore. Measures included the Spence Children's Anxiety Scale and assessments of overall emotional, behavioural and adaptive functioning. Caregivers reported more anxiety symptoms in total, but fewer social anxiety symptoms, than Spence Children's Anxiety Scale Australian/Dutch norms. There were no gender differences. Variance in total anxiety scores was best explained by severity of repetitive speech/stereotyped behaviour symptoms, followed by adaptive functioning. Severity of repetitive speech/behaviour symptoms was a significant predictor of separation anxiety, generalized anxiety, panic/agoraphobia and obsessive-compulsive subscale symptoms, but not of social phobia and physical injury fears. Adaptive functioning and chronological age predicted social phobia and generalized anxiety symptoms only. Severity of social/communication autism symptoms did not explain any anxiety symptoms, when the other variables were controlled for. Findings are discussed in relation to the existing literature. Limitations and possible implications for prevention, assessment and intervention are also discussed. © The Author(s) 2015.

Algorithm for Lossless Compression of Calibrated Hyperspectral Imagery

NASA Technical Reports Server (NTRS)

Kiely, Aaron B.; Klimesh, Matthew A.

2010-01-01

A two-stage predictive method was developed for lossless compression of calibrated hyperspectral imagery. The first prediction stage uses a conventional linear predictor intended to exploit spatial and/or spectral dependencies in the data. The compressor tabulates counts of the past values of the difference between this initial prediction and the actual sample value. To form the ultimate predicted value, in the second stage, these counts are combined with an adaptively updated weight function intended to capture information about data regularities introduced by the calibration process. Finally, prediction residuals are losslessly encoded using adaptive arithmetic coding. Algorithms of this type are commonly tested on a readily available collection of images from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral imager. On the standard calibrated AVIRIS hyperspectral images that are most widely used for compression benchmarking, the new compressor provides more than 0.5 bits/sample improvement over the previous best compression results. The algorithm has been implemented in Mathematica. The compression algorithm was demonstrated as beneficial on 12-bit calibrated AVIRIS images.

A computer simulation of an adaptive noise canceler with a single input

NASA Astrophysics Data System (ADS)

Albert, Stuart D.

1991-06-01

A description of an adaptive noise canceler using Widrows' LMS algorithm is presented. A computer simulation of canceler performance (adaptive convergence time and frequency transfer function) was written for use as a design tool. The simulations, assumptions, and input parameters are described in detail. The simulation is used in a design example to predict the performance of an adaptive noise canceler in the simultaneous presence of both strong and weak narrow-band signals (a cosited frequency hopping radio scenario). On the basis of the simulation results, it is concluded that the simulation is suitable for use as an adaptive noise canceler design tool; i.e., it can be used to evaluate the effect of design parameter changes on canceler performance.

Prediction of biological functions on glycosylation site migrations in human influenza H1N1 viruses.

PubMed

Sun, Shisheng; Wang, Qinzhe; Zhao, Fei; Chen, Wentian; Li, Zheng

2012-01-01

Protein glycosylation alteration is typically employed by various viruses for escaping immune pressures from their hosts. Our previous work had shown that not only the increase of glycosylation sites (glycosites) numbers, but also glycosite migration might be involved in the evolution of human seasonal influenza H1N1 viruses. More importantly, glycosite migration was likely a more effectively alteration way for the host adaption of human influenza H1N1 viruses. In this study, we provided more bioinformatics and statistic evidences for further predicting the significant biological functions of glycosite migration in the host adaptation of human influenza H1N1 viruses, by employing homology modeling and in silico protein glycosylation of representative HA and NA proteins as well as amino acid variability analysis at antigenic sites of HA and NA. The results showed that glycosite migrations in human influenza viruses have at least five possible functions: to more effectively mask the antigenic sites, to more effectively protect the enzymatic cleavage sites of neuraminidase (NA), to stabilize the polymeric structures, to regulate the receptor binding and catalytic activities and to balance the binding activity of hemagglutinin (HA) with the release activity of NA. The information here can provide some constructive suggestions for the function research related to protein glycosylation of influenza viruses, although these predictions still need to be supported by experimental data.

Adaptive support ventilation may deliver unwanted respiratory rate-tidal volume combinations in patients with acute lung injury ventilated according to an open lung concept.

PubMed

Dongelmans, Dave A; Paulus, Frederique; Veelo, Denise P; Binnekade, Jan M; Vroom, Margreeth B; Schultz, Marcus J

2011-05-01

With adaptive support ventilation, respiratory rate and tidal volume (V(T)) are a function of the Otis least work of breathing formula. We hypothesized that adaptive support ventilation in an open lung ventilator strategy would deliver higher V(T)s to patients with acute lung injury. Patients with acute lung injury were ventilated according to a local guideline advising the use of lower V(T) (6-8 ml/kg predicted body weight), high concentrations of positive end-expiratory pressure, and recruitment maneuvers. Ventilation parameters were recorded when the ventilator was switched to adaptive support ventilation, and after recruitment maneuvers. If V(T) increased more than 8 ml/kg predicted body weight, airway pressure was limited to correct for the rise of V(T). Ten patients with a mean (±SD) Pao(2)/Fio(2) of 171 ± 86 mmHg were included. After a switch from pressure-controlled ventilation to adaptive support ventilation, respiratory rate declined (from 31 ± 5 to 21 ± 6 breaths/min; difference = 10 breaths/min, 95% CI 3-17 breaths/min, P = 0.008) and V(T) increased (from 6.5 ± 0.8 to 9.0 ± 1.6 ml/kg predicted body weight; difference = 2.5 ml, 95% CI 0.4-4.6 ml/kg predicted body weight, P = 0.02). Pressure limitation corrected for the rise of V(T), but minute ventilation declined, forcing the user to switch back to pressure-controlled ventilation. Adaptive support ventilation, compared with pressure-controlled ventilation in an open lung strategy setting, delivers a lower respiratory rate-higher V(T) combination. Pressure limitation does correct for the rise of V(T), but leads to a decline in minute ventilation.

The role of repetitive thought in determining posttraumatic growth and distress following interpersonal trauma.

PubMed

Allbaugh, Lucy Jane; Wright, Margaret O'Dougherty; Folger, Susan F

2016-01-01

Repetitive thought (RT) strategies have been linked to a range of negative outcomes following traumatic interpersonal events but are proposed to serve an adaptive function under particular circumstances. This study examined outcomes following RT within a transdiagnostic framework, and explored the potentially adaptive nature of trait-like and event-related RT. The centrality of a traumatic event to one's identity was explored as a context under which the adaptive nature of RT might change. Young adults with interpersonal violence experiences (N = 163) reported use of trait-like and event-related RT, centrality of the event, depressive, anxious, and posttraumatic stress symptoms (PTSS), posttraumatic depreciation and posttraumatic growth. Hierarchical multiple regression analyses were used to examine main and moderating effects of four types of RT and event centrality on outcome variables. Centrality positively predicted depressive symptoms and PTSS, depreciation, and growth. Brooding RT positively predicted all negative outcomes. Reflecting RT positively predicted anxious symptoms and PTSS and depreciation. Only deliberate RT positively predicted growth. Centrality did not moderate any examined relationships. Findings highlight the importance of addressing specific types of RT in interventions with survivors and of considering centrality as a robust contributor to outcomes following interpersonal violence.

Prediction Study on Anti-Slide Control of Railway Vehicle Based on RBF Neural Networks

NASA Astrophysics Data System (ADS)

Yang, Lijun; Zhang, Jimin

While railway vehicle braking, Anti-slide control system will detect operating status of each wheel-sets e.g. speed difference and deceleration etc. Once the detected value on some wheel-set is over pre-defined threshold, brake effort on such wheel-set will be adjusted automatically to avoid blocking. Such method takes effect on guarantee safety operation of vehicle and avoid wheel-set flatness, however it cannot adapt itself to the rail adhesion variation. While wheel-sets slide, the operating status is chaotic time series with certain law, and can be predicted with the law and experiment data in certain time. The predicted values can be used as the input reference signals of vehicle anti-slide control system, to judge and control the slide status of wheel-sets. In this article, the RBF neural networks is taken to predict wheel-set slide status in multi-step with weight vector adjusted based on online self-adaptive algorithm, and the center & normalizing parameters of active function of the hidden unit of RBF neural networks' hidden layer computed with K-means clustering algorithm. With multi-step prediction simulation, the predicted signal with appropriate precision can be used by anti-slide system to trace actively and adjust wheel-set slide tendency, so as to adapt to wheel-rail adhesion variation and reduce the risk of wheel-set blocking.

Adaptive prognosis of lithium-ion batteries based on the combination of particle filters and radial basis function neural networks

NASA Astrophysics Data System (ADS)

Sbarufatti, Claudio; Corbetta, Matteo; Giglio, Marco; Cadini, Francesco

2017-03-01

Lithium-Ion rechargeable batteries are widespread power sources with applications to consumer electronics, electrical vehicles, unmanned aerial and spatial vehicles, etc. The failure to supply the required power levels may lead to severe safety and economical consequences. Thus, in view of the implementation of adequate maintenance strategies, the development of diagnostic and prognostic tools for monitoring the state of health of the batteries and predicting their remaining useful life is becoming a crucial task. Here, we propose a method for predicting the end of discharge of Li-Ion batteries, which stems from the combination of particle filters with radial basis function neural networks. The major innovation lies in the fact that the radial basis function model is adaptively trained on-line, i.e., its parameters are identified in real time by the particle filter as new observations of the battery terminal voltage become available. By doing so, the prognostic algorithm achieves the flexibility needed to provide sound end-of-discharge time predictions as the charge-discharge cycles progress, even in presence of anomalous behaviors due to failures or unforeseen operating conditions. The method is demonstrated with reference to actual Li-Ion battery discharge data contained in the prognostics data repository of the NASA Ames Research Center database.

Is Episodic Future Thinking Important for Instrumental Activities of Daily Living? A Study in Neurological Patients and Healthy Older Adults.

PubMed

Brunette, Amanda M; Calamia, Matthew; Black, Jenah; Tranel, Daniel

2018-06-11

Episodic future thinking is the ability to mentally project oneself into the future. This construct has been explored extensively in cognitive neuroscience and may be relevant for adaptive functioning. However, it has not been determined whether the measurement of episodic future thinking might be valuable in a clinical neuropsychological setting. The current study investigated (1) the relationship between episodic future thinking and instrumental activities of daily living (IADLs); and (2) whether episodic future thinking is related to IADLs over and above standard measures of cognition. Sixty-one older adults with heterogeneous neurological conditions and 41 healthy older adults completed a future thinking task (the adapted Autobiographical Interview), a performance-based measure of instrumental activities of daily living (the Independent Living Scales), and standard clinical measures of memory and executive functioning. Episodic future thinking significantly predicted IADLs after accounting for age, education, gender, and depression (increase in R2 = .050, p = .010). Episodic future thinking significantly predicted IADLs over and above executive functioning (increase in R2 = .025, p = .030), but was not predictive of IADLs over and above memory (p = .157). This study suggests that episodic future thinking is significantly associated with IADLs, beyond what can be accounted for by executive functioning. However, episodic future thinking did not predict IADLs over and above memory. Overall, there is limited evidence for the clinical utility of episodic future thinking. The findings suggest that an episodic future thinking task does not provide enough valuable information about IADLs to justify its inclusion in a clinical neuropsychological setting.

Adaptive method for electron bunch profile prediction

DOE PAGES

Scheinker, Alexander; Gessner, Spencer

2015-10-15

We report on an experiment performed at the Facility for Advanced Accelerator Experimental Tests (FACET) at SLAC National Accelerator Laboratory, in which a new adaptive control algorithm, one with known, bounded update rates, despite operating on analytically unknown cost functions, was utilized in order to provide quasi-real-time bunch property estimates of the electron beam. Multiple parameters, such as arbitrary rf phase settings and other time-varying accelerator properties, were simultaneously tuned in order to match a simulated bunch energy spectrum with a measured energy spectrum. Thus, the simple adaptive scheme was digitally implemented using matlab and the experimental physics and industrialmore » control system. Finally, the main result is a nonintrusive, nondestructive, real-time diagnostic scheme for prediction of bunch profiles, as well as other beam parameters, the precise control of which are important for the plasma wakefield acceleration experiments being explored at FACET.« less

Adaptive method for electron bunch profile prediction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Scheinker, Alexander; Gessner, Spencer

2015-10-01

We report on an experiment performed at the Facility for Advanced Accelerator Experimental Tests (FACET) at SLAC National Accelerator Laboratory, in which a new adaptive control algorithm, one with known, bounded update rates, despite operating on analytically unknown cost functions, was utilized in order to provide quasi-real-time bunch property estimates of the electron beam. Multiple parameters, such as arbitrary rf phase settings and other time-varying accelerator properties, were simultaneously tuned in order to match a simulated bunch energy spectrum with a measured energy spectrum. The simple adaptive scheme was digitally implemented using matlab and the experimental physics and industrial controlmore » system. The main result is a nonintrusive, nondestructive, real-time diagnostic scheme for prediction of bunch profiles, as well as other beam parameters, the precise control of which are important for the plasma wakefield acceleration experiments being explored at FACET. © 2015 authors. Published by the American Physical Society.« less

Personality Subtypes of Suicidal Adults

PubMed Central

Westen, Drew; Bradley, Rebekah

2009-01-01

Research into personality factors related to suicidality suggests substantial variability among suicide attempters. A potentially useful approach that accounts for this complexity is personality subtyping. As part of a large sample looking at personality pathology, this study used Q-factor analysis to identify subtypes of 311 adult suicide attempters using SWAP-II personality profiles. Identified subtypes included Internalizing, Emotionally Dysregulated, Dependent, Hostile-Isolated, Psychopathic, and Anxious-Somatizing. Subtypes differed in hypothesized ways on criterion variables that address their construct validity, including adaptive functioning, Axis I and II comorbidity, and etiology-related variables (e.g., history of abuse). Furthermore, dimensional ratings of the subtypes predicted adaptive functioning above DSM-based diagnoses and symptoms. PMID:19752649

Neuro-fuzzy and neural network techniques for forecasting sea level in Darwin Harbor, Australia

NASA Astrophysics Data System (ADS)

Karimi, Sepideh; Kisi, Ozgur; Shiri, Jalal; Makarynskyy, Oleg

2013-03-01

Accurate predictions of sea level with different forecast horizons are important for coastal and ocean engineering applications, as well as in land drainage and reclamation studies. The methodology of tidal harmonic analysis, which is generally used for obtaining a mathematical description of the tides, is data demanding requiring processing of tidal observation collected over several years. In the present study, hourly sea levels for Darwin Harbor, Australia were predicted using two different, data driven techniques, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural network (ANN). Multi linear regression (MLR) technique was used for selecting the optimal input combinations (lag times) of hourly sea level. The input combination comprises current sea level as well as five previous level values found to be optimal. For the ANFIS models, five different membership functions namely triangular, trapezoidal, generalized bell, Gaussian and two Gaussian membership function were tested and employed for predicting sea level for the next 1 h, 24 h, 48 h and 72 h. The used ANN models were trained using three different algorithms, namely, Levenberg-Marquardt, conjugate gradient and gradient descent. Predictions of optimal ANFIS and ANN models were compared with those of the optimal auto-regressive moving average (ARMA) models. The coefficient of determination, root mean square error and variance account statistics were used as comparison criteria. The obtained results indicated that triangular membership function was optimal for predictions with the ANFIS models while adaptive learning rate and Levenberg-Marquardt were most suitable for training the ANN models. Consequently, ANFIS and ANN models gave similar forecasts and performed better than the developed for the same purpose ARMA models for all the prediction intervals.

The metabolic pace-of-life model: incorporating ectothermic organisms into the theory of vertebrate ecoimmunology.

PubMed

Sandmeier, Franziska C; Tracy, Richard C

2014-09-01

We propose a new heuristic model that incorporates metabolic rate and pace of life to predict a vertebrate species' investment in adaptive immune function. Using reptiles as an example, we hypothesize that animals with low metabolic rates will invest more in innate immunity compared with adaptive immunity. High metabolic rates and body temperatures should logically optimize the efficacy of the adaptive immune system--through rapid replication of T and B cells, prolific production of induced antibodies, and kinetics of antibody--antigen interactions. In current theory, the precise mechanisms of vertebrate immune function oft are inadequately considered as diverse selective pressures on the evolution of pathogens. We propose that the strength of adaptive immune function and pace of life together determine many of the important dynamics of host-pathogen evolution, namely, that hosts with a short lifespan and innate immunity or with a long lifespan and strong adaptive immunity are expected to drive the rapid evolution of their populations of pathogens. Long-lived hosts that rely primarily on innate immune functions are more likely to use defense mechanisms of tolerance (instead of resistance), which are not expected to act as a selection pressure for the rapid evolution of pathogens' virulence. © The Author 2014. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

The Cerebellum: Adaptive Prediction for Movement and Cognition

PubMed Central

Sokolov, Arseny A.; Miall, R. Chris; Ivry, Richard B.

2017-01-01

Over the past 30 years, cumulative evidence has indicated that cerebellar function extends beyond sensorimotor control. This view has emerged from studies of neuroanatomy, neuroimaging, neuropsychology and brain stimulation, with the results implicating the cerebellum in domains as diverse as attention, language, executive function and social cognition. Although the literature provides sophisticated models of how the cerebellum helps refine movements, it remains unclear how the core mechanisms of these models can be applied when considering a broader conceptualization of cerebellar function. In light of recent multidisciplinary findings, we consider two key concepts that have been suggested as general computational principles of cerebellar function, prediction and error-based learning, examining how these might be relevant in the operation of cognitive cerebro-cerebellar loops. PMID:28385461

Vector Adaptive/Predictive Encoding Of Speech

NASA Technical Reports Server (NTRS)

Chen, Juin-Hwey; Gersho, Allen

1989-01-01

Vector adaptive/predictive technique for digital encoding of speech signals yields decoded speech of very good quality after transmission at coding rate of 9.6 kb/s and of reasonably good quality at 4.8 kb/s. Requires 3 to 4 million multiplications and additions per second. Combines advantages of adaptive/predictive coding, and code-excited linear prediction, yielding speech of high quality but requires 600 million multiplications and additions per second at encoding rate of 4.8 kb/s. Vector adaptive/predictive coding technique bridges gaps in performance and complexity between adaptive/predictive coding and code-excited linear prediction.

Adaptive dynamics of cuticular hydrocarbons in Drosophila

PubMed Central

Rajpurohit, Subhash; Hanus, Robert; Vrkoslav, Vladimír; Behrman, Emily L.; Bergland, Alan O.; Petrov, Dmitri; Cvačka, Josef; Schmidt, Paul S.

2016-01-01

Cuticular hydrocarbons (CHCs) are hydrophobic compounds deposited on the arthropod cuticle that are of functional significance with respect to stress tolerance, social interactions, and mating dynamics. We characterized CHC profiles in natural populations of Drosophila melanogaster at five levels: across a latitudinal transect in the eastern U.S., as a function of developmental temperature during culture, across seasonal time in replicate years, and as a function of rapid evolution in experimental mesocosms in the field. Furthermore, we also characterized spatial and temporal change in allele frequencies for SNPs in genes that are associated with the production and chemical profile of CHCs. Our data demonstrate a striking degree of parallelism for clinal and seasonal variation in CHCs in this taxon; CHC profiles also demonstrate significant plasticity in response to rearing temperature, and the observed patterns of plasticity parallel the spatiotemporal patterns observed in nature. We find that these congruent shifts in CHC profiles across time and space are also mirrored by predictable shifts in allele frequencies at SNPs associated with CHC chain length. Finally, we observed rapid and predictable evolution of CHC profiles in experimental mesocosms in the field. Together, these data strongly suggest that CHC profiles respond rapidly and adaptively to environmental parameters that covary with latitude and season, and that this response reflects the process of local adaptation in natural populations of D. melanogaster. PMID:27718537

Brief Report: IQ Split Predicts Social Symptoms and Communication Abilities in High-Functioning Children with Autism Spectrum Disorders

PubMed Central

Wallace, Gregory L.; Sokoloff, Jennifer L.; Kenworthy, Lauren

2011-01-01

We investigated the relationship of discrepancies between VIQ and NVIQ (IQ split) to autism symptoms and adaptive behavior in a sample of high-functioning (mean FSIQ = 98.5) school-age children with autism spectrum disorders divided into three groups: discrepantly high VIQ (n = 18); discrepantly high NVIQ (n = 24); and equivalent VIQ and NVIQ (n = 36). Discrepantly high VIQ and NVIQ were associated with autism social symptoms but not communication symptoms or repetitive behaviors. Higher VIQ and NVIQ were associated with better adaptive communication but not socialization or Daily Living Skills. IQ discrepancy may be an important phenotypic marker in autism. Although better verbal abilities are associated with better functional outcomes in autism, discrepantly high VIQ in high-functioning children may also be associated with social difficulties. PMID:19572193

Behavior and adaptive functioning in adolescents with Down syndrome: specifying targets for intervention.

PubMed

Jacola, Lisa M; Hickey, Francis; Howe, Steven R; Esbensen, Anna; Shear, Paula K

2014-01-01

Research suggests that adolescents with Down syndrome experience increased behavior problems as compared to age matched peers; however, few studies have examined how these problems relate to adaptive functioning. The primary aim of this study was to characterize behavior in a sample of adolescents with Down syndrome using two widely-used caregiver reports: the Behavioral Assessment System for Children, 2 nd Edition (BASC-2) and Child Behavioral Checklist (CBCL). The clinical utility of the BASC-2 as a measure of behavior and adaptive functioning in adolescents with Down syndrome was also examined. Fifty-two adolescents with Down syndrome between the ages of 12 and 18 (24 males) completed the Peabody Picture Vocabulary Test, 4 th Edition (PPVT-IV) as an estimate of cognitive ability. Caregivers completed the BASC-2 and the CBCL for each participant. A significant proportion of the sample was reported to demonstrate behavior problems, particularly related to attention and social participation. The profile of adaptive function was variable, with caregivers most frequently rating impairment in skills related to activities of daily living and functional communication. Caregiver ratings did not differ by gender and were not related to age or estimated cognitive ability. Caregiver ratings of attention problems on the BASC-2 accounted for a significant proportion of variance in Activities of Daily Living ( Adj R 2 = 0.30) , Leadership ( Adj R 2 = 0.30) Functional Communication ( Adj R 2 = 0.28, Adaptability ( Adj R 2 = 0.29), and Social Skills ( Adj R 2 = 0.17). Higher frequencies of symptoms related to social withdrawal added incremental predictive validity for Functional Communication, Leadership, and Social Skills. Convergent validity between the CBCL and BASC-2 was poor when compared with expectations based on the normative sample. Our results confirm and extend previous findings by describing relationships between specific behavior problems and targeted areas of adaptive function. Findings are novel in that they provide information about the clinical utility of the BASC-2 as a measure of behavior and adaptive skills in adolescents with Down syndrome. The improved specification of behavior and adaptive functioning will facilitate the design of targeted intervention, thus improving functional outcomes and overall quality of life for individuals with Down syndrome and their families.

Behavior and adaptive functioning in adolescents with Down syndrome: specifying targets for intervention

PubMed Central

Jacola, Lisa M.; Hickey, Francis; Howe, Steven R.; Esbensen, Anna; Shear, Paula K.

2016-01-01

Background Research suggests that adolescents with Down syndrome experience increased behavior problems as compared to age matched peers; however, few studies have examined how these problems relate to adaptive functioning. The primary aim of this study was to characterize behavior in a sample of adolescents with Down syndrome using two widely-used caregiver reports: the Behavioral Assessment System for Children, 2nd Edition (BASC-2) and Child Behavioral Checklist (CBCL). The clinical utility of the BASC-2 as a measure of behavior and adaptive functioning in adolescents with Down syndrome was also examined. Methods Fifty-two adolescents with Down syndrome between the ages of 12 and 18 (24 males) completed the Peabody Picture Vocabulary Test, 4th Edition (PPVT-IV) as an estimate of cognitive ability. Caregivers completed the BASC-2 and the CBCL for each participant. Results A significant proportion of the sample was reported to demonstrate behavior problems, particularly related to attention and social participation. The profile of adaptive function was variable, with caregivers most frequently rating impairment in skills related to activities of daily living and functional communication. Caregiver ratings did not differ by gender and were not related to age or estimated cognitive ability. Caregiver ratings of attention problems on the BASC-2 accounted for a significant proportion of variance in Activities of Daily Living (Adj R2 = 0.30), Leadership (Adj R2 = 0.30) Functional Communication (Adj R2 = 0.28, Adaptability (Adj R2 = 0.29), and Social Skills (Adj R2 = 0.17). Higher frequencies of symptoms related to social withdrawal added incremental predictive validity for Functional Communication, Leadership, and Social Skills. Convergent validity between the CBCL and BASC-2 was poor when compared with expectations based on the normative sample. Conclusion Our results confirm and extend previous findings by describing relationships between specific behavior problems and targeted areas of adaptive function. Findings are novel in that they provide information about the clinical utility of the BASC-2 as a measure of behavior and adaptive skills in adolescents with Down syndrome. The improved specification of behavior and adaptive functioning will facilitate the design of targeted intervention, thus improving functional outcomes and overall quality of life for individuals with Down syndrome and their families. PMID:28539987

A case study of evolutionary computation of biochemical adaptation

NASA Astrophysics Data System (ADS)

François, Paul; Siggia, Eric D.

2008-06-01

Simulations of evolution have a long history, but their relation to biology is questioned because of the perceived contingency of evolution. Here we provide an example of a biological process, adaptation, where simulations are argued to approach closer to biology. Adaptation is a common feature of sensory systems, and a plausible component of other biochemical networks because it rescales upstream signals to facilitate downstream processing. We create random gene networks numerically, by linking genes with interactions that model transcription, phosphorylation and protein-protein association. We define a fitness function for adaptation in terms of two functional metrics, and show that any reasonable combination of them will yield the same adaptive networks after repeated rounds of mutation and selection. Convergence to these networks is driven by positive selection and thus fast. There is always a path in parameter space of continuously improving fitness that leads to perfect adaptation, implying that the actual mutation rates we use in the simulation do not bias the results. Our results imply a kinetic view of evolution, i.e., it favors gene networks that can be learned quickly from the random examples supplied by mutation. This formulation allows for deductive predictions of the networks realized in nature.

Design of a completely model free adaptive control in the presence of parametric, non-parametric uncertainties and random control signal delay.

PubMed

Tutsoy, Onder; Barkana, Duygun Erol; Tugal, Harun

2018-05-01

In this paper, an adaptive controller is developed for discrete time linear systems that takes into account parametric uncertainty, internal-external non-parametric random uncertainties, and time varying control signal delay. Additionally, the proposed adaptive control is designed in such a way that it is utterly model free. Even though these properties are studied separately in the literature, they are not taken into account all together in adaptive control literature. The Q-function is used to estimate long-term performance of the proposed adaptive controller. Control policy is generated based on the long-term predicted value, and this policy searches an optimal stabilizing control signal for uncertain and unstable systems. The derived control law does not require an initial stabilizing control assumption as in the ones in the recent literature. Learning error, control signal convergence, minimized Q-function, and instantaneous reward are analyzed to demonstrate the stability and effectiveness of the proposed adaptive controller in a simulation environment. Finally, key insights on parameters convergence of the learning and control signals are provided. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Towards a neuro-computational account of prism adaptation.

PubMed

Petitet, Pierre; O'Reilly, Jill X; O'Shea, Jacinta

2017-12-14

Prism adaptation has a long history as an experimental paradigm used to investigate the functional and neural processes that underlie sensorimotor control. In the neuropsychology literature, prism adaptation behaviour is typically explained by reference to a traditional cognitive psychology framework that distinguishes putative functions, such as 'strategic control' versus 'spatial realignment'. This theoretical framework lacks conceptual clarity, quantitative precision and explanatory power. Here, we advocate for an alternative computational framework that offers several advantages: 1) an algorithmic explanatory account of the computations and operations that drive behaviour; 2) expressed in quantitative mathematical terms; 3) embedded within a principled theoretical framework (Bayesian decision theory, state-space modelling); 4) that offers a means to generate and test quantitative behavioural predictions. This computational framework offers a route towards mechanistic neurocognitive explanations of prism adaptation behaviour. Thus it constitutes a conceptual advance compared to the traditional theoretical framework. In this paper, we illustrate how Bayesian decision theory and state-space models offer principled explanations for a range of behavioural phenomena in the field of prism adaptation (e.g. visual capture, magnitude of visual versus proprioceptive realignment, spontaneous recovery and dynamics of adaptation memory). We argue that this explanatory framework can advance understanding of the functional and neural mechanisms that implement prism adaptation behaviour, by enabling quantitative tests of hypotheses that go beyond merely descriptive mapping claims that 'brain area X is (somehow) involved in psychological process Y'. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Optimizing the learning rate for adaptive estimation of neural encoding models

PubMed Central

2018-01-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel analytical approach to predictably achieve a desired level of error and convergence time in adaptive learning, with application to closed-loop neurotechnologies and other signal processing domains. PMID:29813069

Optimizing the learning rate for adaptive estimation of neural encoding models.

PubMed

Hsieh, Han-Lin; Shanechi, Maryam M

2018-05-01

Closed-loop neurotechnologies often need to adaptively learn an encoding model that relates the neural activity to the brain state, and is used for brain state decoding. The speed and accuracy of adaptive learning algorithms are critically affected by the learning rate, which dictates how fast model parameters are updated based on new observations. Despite the importance of the learning rate, currently an analytical approach for its selection is largely lacking and existing signal processing methods vastly tune it empirically or heuristically. Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. We formulate the problem through a fundamental trade-off that learning rate introduces between the steady-state error and the convergence time of the estimated model parameters. We derive explicit functions that predict the effect of learning rate on error and convergence time. Using these functions, our calibration algorithm can keep the steady-state parameter error covariance smaller than a desired upper-bound while minimizing the convergence time, or keep the convergence time faster than a desired value while minimizing the error. We derive the algorithm both for discrete-valued spikes modeled as point processes nonlinearly dependent on the brain state, and for continuous-valued neural recordings modeled as Gaussian processes linearly dependent on the brain state. Using extensive closed-loop simulations, we show that the analytical solution of the calibration algorithm accurately predicts the effect of learning rate on parameter error and convergence time. Moreover, the calibration algorithm allows for fast and accurate learning of the encoding model and for fast convergence of decoding to accurate performance. Finally, larger learning rates result in inaccurate encoding models and decoders, and smaller learning rates delay their convergence. The calibration algorithm provides a novel analytical approach to predictably achieve a desired level of error and convergence time in adaptive learning, with application to closed-loop neurotechnologies and other signal processing domains.

Conflicts of thermal adaptation and fever--a cybernetic approach based on physiological experiments.

PubMed

Werner, J; Beckmann, U

1998-01-01

Cold adaptation aims primarily at a better economy, i.e., preservation of energy often at the cost of a lower mean body temperature during cold stress, whereas heat adaptation whether achieved by exposure to a hot environment or by endogenous heat produced by muscle exercise, often brings about a higher efficiency of control, i.e., a lower mean body temperature during heat stress, at the cost of a higher water loss. While cold adaptation is beneficial in a cold environment, it may constitute a detrimental factor for exposure to a hot environment, mainly because of morphological adaptation. Heat adaptation may be maladaptive for cold exposure, mainly because of functional adaptation. Heat adaptation clearly is best suited to avoid higher body temperatures in fever, no matter which environmental conditions prevail. On the other hand, cold adaptation is detrimental for coping with fever in hot environment. Yet, in the cold, preceding cold adaptation may, because of reduced metabolic heat production, result in lower febrile increase of body temperature. Apparently controversial effects and results may be analyzed in the framework of a cybernetic approach to the main mechanisms of thermal adaptation and fever. Morphological adaptations alter the properties of the heat transfer characteristics of the body ("passive system"), whereas functional adaptation and fever concern the subsystems of control, namely sensors, integrative centers and effectors. In a closed control-loop the two types of adaptation have totally different consequences. It is shown that the experimental results are consistent with the predictions of such an approach.

Functional genetic divergence in high CO2 adapted Emiliania huxleyi populations.

PubMed

Lohbeck, Kai T; Riebesell, Ulf; Collins, Sinéad; Reusch, Thorsten B H

2013-07-01

Predicting the impacts of environmental change on marine organisms, food webs, and biogeochemical cycles presently relies almost exclusively on short-term physiological studies, while the possibility of adaptive evolution is often ignored. Here, we assess adaptive evolution in the coccolithophore Emiliania huxleyi, a well-established model species in biological oceanography, in response to ocean acidification. We previously demonstrated that this globally important marine phytoplankton species adapts within 500 generations to elevated CO2 . After 750 and 1000 generations, no further fitness increase occurred, and we observed phenotypic convergence between replicate populations. We then exposed adapted populations to two novel environments to investigate whether or not the underlying basis for high CO2 -adaptation involves functional genetic divergence, assuming that different novel mutations become apparent via divergent pleiotropic effects. The novel environment "high light" did not reveal such genetic divergence whereas growth in a low-salinity environment revealed strong pleiotropic effects in high CO2 adapted populations, indicating divergent genetic bases for adaptation to high CO2 . This suggests that pleiotropy plays an important role in adaptation of natural E. huxleyi populations to ocean acidification. Our study highlights the potential mutual benefits for oceanography and evolutionary biology of using ecologically important marine phytoplankton for microbial evolution experiments. © 2012 The Author(s). Evolution © 2012 The Society for the Study of Evolution.

Dynamic Filtering Improves Attentional State Prediction with fNIRS

NASA Technical Reports Server (NTRS)

Harrivel, Angela R.; Weissman, Daniel H.; Noll, Douglas C.; Huppert, Theodore; Peltier, Scott J.

2016-01-01

Brain activity can predict a person's level of engagement in an attentional task. However, estimates of brain activity are often confounded by measurement artifacts and systemic physiological noise. The optimal method for filtering this noise - thereby increasing such state prediction accuracy - remains unclear. To investigate this, we asked study participants to perform an attentional task while we monitored their brain activity with functional near infrared spectroscopy (fNIRS). We observed higher state prediction accuracy when noise in the fNIRS hemoglobin [Hb] signals was filtered with a non-stationary (adaptive) model as compared to static regression (84% +/- 6% versus 72% +/- 15%).

A possible correlation between performance IQ, visuomotor adaptation ability and mu suppression.

PubMed

Anwar, Muhammad Nabeel; Navid, Muhammad Samran; Khan, Mushtaq; Kitajo, Keiichi

2015-04-07

Psychometric, anatomical and functional brain studies suggest that individuals differ in the way that they perceive and analyze information and strategically control and execute movements. Inter-individual differences are also observed in neural correlates of specific and general cognitive ability. As a result, some individuals perceive and adapt to environmental conditions and perform motor activities better than others. The aim of this study was to identify a common factor that predicts adaptation of a reaching movement to a visual perturbation and suppression of movement-related brain activity (mu rhythms). Twenty-eight participants participated in two different experiments designed to evaluate visuomotor adaptation and mu suppression ability. Performance intelligence quotient (IQ) was assessed using the revised Wechsler Adult Intelligence Scale. Performance IQ predicted adaptation index of visuomotor performance (r=0.43, p=0.02) and suppression of mu rhythms (r=-0.59; p<0.001). Participants with high performance IQ were faster at adapting to a visuomotor perturbation and better at suppressing mu activity than participants with low performance IQ. We found a possible link between performance IQ and mu suppression, and performance IQ and the initial rate of adaptation. Individuals with high performance IQ were better in suppressing mu rhythms and were quicker at associating motor command and required movement than individuals with low performance IQ. Copyright © 2015 Elsevier B.V. All rights reserved.

The genomic basis of adaptation to the fitness cost of rifampicin resistance in Pseudomonas aeruginosa

PubMed Central

Toll-Riera, Macarena; Heilbron, Karl

2016-01-01

Antibiotic resistance carries a fitness cost that must be overcome in order for resistance to persist over the long term. Compensatory mutations that recover the functional defects associated with resistance mutations have been argued to play a key role in overcoming the cost of resistance, but compensatory mutations are expected to be rare relative to generally beneficial mutations that increase fitness, irrespective of antibiotic resistance. Given this asymmetry, population genetics theory predicts that populations should adapt by compensatory mutations when the cost of resistance is large, whereas generally beneficial mutations should drive adaptation when the cost of resistance is small. We tested this prediction by determining the genomic mechanisms underpinning adaptation to antibiotic-free conditions in populations of the pathogenic bacterium Pseudomonas aeruginosa that carry costly antibiotic resistance mutations. Whole-genome sequencing revealed that populations founded by high-cost rifampicin-resistant mutants adapted via compensatory mutations in three genes of the RNA polymerase core enzyme, whereas populations founded by low-cost mutants adapted by generally beneficial mutations, predominantly in the quorum-sensing transcriptional regulator gene lasR. Even though the importance of compensatory evolution in maintaining resistance has been widely recognized, our study shows that the roles of general adaptation in maintaining resistance should not be underestimated and highlights the need to understand how selection at other sites in the genome influences the dynamics of resistance alleles in clinical settings. PMID:26763710

Analysis of Bioactive Amino Acids from Fish Hydrolysates with a New Bioinformatic Intelligent System Approach.

PubMed

Elaziz, Mohamed Abd; Hemdan, Ahmed Monem; Hassanien, AboulElla; Oliva, Diego; Xiong, Shengwu

2017-09-07

The current economics of the fish protein industry demand rapid, accurate and expressive prediction algorithms at every step of protein production especially with the challenge of global climate change. This help to predict and analyze functional and nutritional quality then consequently control food allergies in hyper allergic patients. As, it is quite expensive and time-consuming to know these concentrations by the lab experimental tests, especially to conduct large-scale projects. Therefore, this paper introduced a new intelligent algorithm using adaptive neuro-fuzzy inference system based on whale optimization algorithm. This algorithm is used to predict the concentration levels of bioactive amino acids in fish protein hydrolysates at different times during the year. The whale optimization algorithm is used to determine the optimal parameters in adaptive neuro-fuzzy inference system. The results of proposed algorithm are compared with others and it is indicated the higher performance of the proposed algorithm.

Analysis prediction of Indonesian banks (BCA, BNI, MANDIRI) using adaptive neuro-fuzzy inference system (ANFIS) and investment strategies

NASA Astrophysics Data System (ADS)

Trianto, Andriantama Budi; Hadi, I. M.; Liong, The Houw; Purqon, Acep

2015-09-01

Indonesian economical development is growing well. It has effect for their invesment in Banks and the stock market. In this study, we perform prediction for the three blue chips of Indonesian bank i.e. BCA, BNI, and MANDIRI by using the method of Adaptive Neuro-Fuzzy Inference System (ANFIS) with Takagi-Sugeno rules and Generalized bell (Gbell) as the membership function. Our results show that ANFIS perform good prediction with RMSE for BCA of 27, BNI of 5.29, and MANDIRI of 13.41, respectively. Furthermore, we develop an active strategy to gain more benefit. We compare between passive strategy versus active strategy. Our results shows that for the passive strategy gains 13 million rupiah, while for the active strategy gains 47 million rupiah in one year. The active investment strategy significantly shows gaining multiple benefit than the passive one.

Biophysically defined and cytocompatible covalently adaptable networks as viscoelastic 3D cell culture systems.

PubMed

McKinnon, Daniel D; Domaille, Dylan W; Cha, Jennifer N; Anseth, Kristi S

2014-02-12

Presented here is a cytocompatible covalently adaptable hydrogel uniquely capable of mimicking the complex biophysical properties of native tissue and enabling natural cell functions without matrix degradation. Demonstrated is both the ability to control elastic modulus and stress relaxation time constants by more than an order of magnitude while predicting these values based on fundamental theoretical understanding and the simulation of muscle tissue and the encapsulation of myoblasts. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Functional network architecture predicts psychologically mediated analgesia related to treatment in chronic knee pain patients.

PubMed

Hashmi, Javeria Ali; Kong, Jian; Spaeth, Rosa; Khan, Sheraz; Kaptchuk, Ted J; Gollub, Randy L

2014-03-12

Placebo analgesia is an indicator of how efficiently the brain translates psychological signals conveyed by a treatment procedure into pain relief. It has been demonstrated that functional connectivity between distributed brain regions predicts placebo analgesia in chronic back pain patients. Greater network efficiency in baseline brain networks may allow better information transfer and facilitate adaptive physiological responses to psychological aspects of treatment. Here, we theorized that topological network alignments in resting state scans predict psychologically conditioned analgesic responses to acupuncture treatment in chronic knee osteoarthritis pain patients (n = 45). Analgesia was induced by building positive expectations toward acupuncture treatment with verbal suggestion and heat pain conditioning on a test site of the arm. This procedure induced significantly more analgesia after sham or real acupuncture on the test site than in a control site. The psychologically conditioned analgesia was invariant to sham versus real treatment. Efficiency of information transfer within local networks calculated with graph-theoretic measures (local efficiency and clustering coefficients) significantly predicted conditioned analgesia. Clustering coefficients in regions associated with memory, motivation, and pain modulation were closely involved in predicting analgesia. Moreover, women showed higher clustering coefficients and marginally greater pain reduction than men. Overall, analgesic response to placebo cues can be predicted from a priori resting state data by observing local network topology. Such low-cost synchronizations may represent preparatory resources that facilitate subsequent performance of brain circuits in responding to adaptive environmental cues. This suggests a potential utility of network measures in predicting placebo response for clinical use.

Refinement and testing of analysis nudging in MPAS-A

EPA Science Inventory

The Model for Prediction Across Scales - Atmosphere (MPAS-A) is being adapted to serve as the meteorological driver for EPA’s “next-generation” air-quality model. To serve that purpose, it must be able to function in a diagnostic mode where past meteorological ...

NASA Langley developments in response calculations needed for failure and life prediction

NASA Technical Reports Server (NTRS)

Housner, Jerrold M.

1993-01-01

NASA Langley developments in response calculations needed for failure and life predictions are discussed. Topics covered include: structural failure analysis in concurrent engineering; accuracy of independent regional modeling demonstrated on classical example; functional interface method accurately joins incompatible finite element models; interface method for insertion of local detail modeling extended to curve pressurized fuselage window panel; interface concept for joining structural regions; motivation for coupled 2D-3D analysis; compression panel with discontinuous stiffener coupled 2D-3D model and axial surface strains at the middle of the hat stiffener; use of adaptive refinement with multiple methods; adaptive mesh refinement; and studies on quantity effect of bow-type initial imperfections on reliability of stiffened panels.

Family Functioning and the Course of Adolescent Bipolar Disorder

PubMed Central

Sullivan, Aimee E.; Judd, Charles M.; Axelson, David A.; Miklowitz, David J.

2012-01-01

The symptoms of bipolar disorder affect and are affected by the functioning of family environments. Little is known, however, about the stability of family functioning among youth with bipolar disorder as they cycle in and out of mood episodes. This study examined family functioning and its relationship to symptoms of adolescent bipolar disorder, using longitudinal measures of family cohesion, adaptability and conflict. Parent and adolescent-reported symptom and family functioning data were collected from 58 families of adolescents with bipolar disorder (mean age =14.48 + 1.60; 33 female, 25 male) who participated in a 2-year randomized trial of family-focused treatment for adolescents (FFT-A). Cohesion and adaptability scores did not significantly change over the course of the study. Parent-reported conflict prior to psychosocial treatment moderated the treatment responses of families, such that high-conflict families participating in FFT-A demonstrated greater reductions in conflict over time than low-conflict families. Moreover, adolescent mania symptoms improved more rapidly in low-conflict than in high-conflict families. For all respondents, cohesion, adaptability, and conflict were longitudinally correlated with adolescents’ depression scores. Finally, decreases in parent-reported conflict also predicted decreases in adolescents’ manic symptoms over the 2-year study. Findings suggest that family cohesion, adaptability, and conflict may be useful predictors of the course of adolescent mood symptoms. Family conflict may be an important target for family intervention in early-onset bipolar disorder. PMID:23046785

Generating Adaptive Behaviour within a Memory-Prediction Framework

PubMed Central

Rawlinson, David; Kowadlo, Gideon

2012-01-01

The Memory-Prediction Framework (MPF) and its Hierarchical-Temporal Memory implementation (HTM) have been widely applied to unsupervised learning problems, for both classification and prediction. To date, there has been no attempt to incorporate MPF/HTM in reinforcement learning or other adaptive systems; that is, to use knowledge embodied within the hierarchy to control a system, or to generate behaviour for an agent. This problem is interesting because the human neocortex is believed to play a vital role in the generation of behaviour, and the MPF is a model of the human neocortex. We propose some simple and biologically-plausible enhancements to the Memory-Prediction Framework. These cause it to explore and interact with an external world, while trying to maximize a continuous, time-varying reward function. All behaviour is generated and controlled within the MPF hierarchy. The hierarchy develops from a random initial configuration by interaction with the world and reinforcement learning only. Among other demonstrations, we show that a 2-node hierarchy can learn to successfully play “rocks, paper, scissors” against a predictable opponent. PMID:22272231

mPLR-Loc: an adaptive decision multi-label classifier based on penalized logistic regression for protein subcellular localization prediction.

PubMed

Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

2015-03-15

Proteins located in appropriate cellular compartments are of paramount importance to exert their biological functions. Prediction of protein subcellular localization by computational methods is required in the post-genomic era. Recent studies have been focusing on predicting not only single-location proteins but also multi-location proteins. However, most of the existing predictors are far from effective for tackling the challenges of multi-label proteins. This article proposes an efficient multi-label predictor, namely mPLR-Loc, based on penalized logistic regression and adaptive decisions for predicting both single- and multi-location proteins. Specifically, for each query protein, mPLR-Loc exploits the information from the Gene Ontology (GO) database by using its accession number (AC) or the ACs of its homologs obtained via BLAST. The frequencies of GO occurrences are used to construct feature vectors, which are then classified by an adaptive decision-based multi-label penalized logistic regression classifier. Experimental results based on two recent stringent benchmark datasets (virus and plant) show that mPLR-Loc remarkably outperforms existing state-of-the-art multi-label predictors. In addition to being able to rapidly and accurately predict subcellular localization of single- and multi-label proteins, mPLR-Loc can also provide probabilistic confidence scores for the prediction decisions. For readers' convenience, the mPLR-Loc server is available online (http://bioinfo.eie.polyu.edu.hk/mPLRLocServer). Copyright © 2014 Elsevier Inc. All rights reserved.

Prenatal stress effects in a wild, long-lived primate: predictive adaptive responses in an unpredictable environment.

PubMed

Berghänel, Andreas; Heistermann, Michael; Schülke, Oliver; Ostner, Julia

2016-09-28

Prenatal maternal stress affects offspring phenotype in numerous species including humans, but it is debated whether these effects are evolutionarily adaptive. Relating stress to adverse conditions, current explanations invoke either short-term developmental constraints on offspring phenotype resulting in decelerated growth to avoid starvation, or long-term predictive adaptive responses (PARs) resulting in accelerated growth and reproduction in response to reduced life expectancies. Two PAR subtypes were proposed, acting either on predicted internal somatic states or predicted external environmental conditions, but because both affect phenotypes similarly, they are largely indistinguishable. Only external (not internal) PARs rely on high environmental stability particularly in long-lived species. We report on a crucial test case in a wild long-lived mammal, the Assamese macaque (Macaca assamensis), which evolved and lives in an unpredictable environment where external PARs are probably not advantageous. We quantified food availability, growth, motor skills, maternal caretaking style and maternal physiological stress from faecal glucocorticoid measures. Prenatal maternal stress was negatively correlated to prenatal food availability and led to accelerated offspring growth accompanied by decelerated motor skill acquisition and reduced immune function. These results support the 'internal PAR' theory, which stresses the role of stable adverse internal somatic states rather than stable external environments. © 2016 The Author(s).

ADAPT: The Agent Development and Prototyping Testbed.

PubMed

Shoulson, Alexander; Marshak, Nathan; Kapadia, Mubbasir; Badler, Norman I

2014-07-01

We present ADAPT, a flexible platform for designing and authoring functional, purposeful human characters in a rich virtual environment. Our framework incorporates character animation, navigation, and behavior with modular interchangeable components to produce narrative scenes. The animation system provides locomotion, reaching, gaze tracking, gesturing, sitting, and reactions to external physical forces, and can easily be extended with more functionality due to a decoupled, modular structure. The navigation component allows characters to maneuver through a complex environment with predictive steering for dynamic obstacle avoidance. Finally, our behavior framework allows a user to fully leverage a character's animation and navigation capabilities when authoring both individual decision-making and complex interactions between actors using a centralized, event-driven model.

The influence of a prediction display on the quasi-linear describing function and remnant measured with an adaptive analog-pilot in a closed loop

NASA Technical Reports Server (NTRS)

Dey, D.

1972-01-01

The effect of a prediction display on the human transfer characteristics is explained with the aid of a quasi-linear model. The prediction display causes an increase of the gain factor and the lead factor, a diminishing of the lag factor and a decrease of the remnant. Altogether, these factors yield a smaller mean square value of the control deviation and a simultaneous decrease of the mean square value of the stick signal.

Inhibitory control and adaptive behaviour in children with mild intellectual disability.

PubMed

Gligorović, M; Buha Ðurović, N

2014-03-01

Inhibitory control, as one of the basic mechanisms of executive functions, is extremely important for adaptive behaviour. The relation between inhibitory control and adaptive behaviour is the most obvious in cases of behavioural disorders and psychopathology. Considering the lack of studies on this relation in children with disabilities, the aim of our research is to determine the relation between inhibitory control and adaptive behaviour in children with mild intellectual disability. The sample consists of 53 children with mild intellectual disability. Selection criteria were: IQ between 50 and 70, age between 10 and 14, absence of bilingualism, and with no medical history of neurological impairment, genetic and/or emotional problems. Modified Day-Night version of the Stroop task, and Go-no-Go Tapping task were used for the assessment of inhibitory control. Data on adaptive behaviour were obtained by applying the first part of AAMR (American Association on Mental Retardation) Adaptive Behaviour Scale-School, Second Edition (ABS-S:2). Significant relationships were determined between some aspects of inhibitory control and the most of assessed domains of adaptive behaviour. Inhibitory control measures, as a unitary inhibition model, significantly predict results on Independent Functioning, Economic Activity, Speech and Language Development, and Number and Times domains of the ABS-S:2. Inhibitory control, assessed by second part of the Stroop task, proved to be a significant factor in practical (Independent Functioning) and conceptual (Economic Activity, Speech and Language Development, and Numbers and Time) adaptive skills. The first part of the Stroop task, as a measure of selective attention, proved to be a significant factor in language and numerical demands, along with second one. Inhibitory control through motor responses proved to be a significant factor in independent functioning, economic activities, language and self-direction skills. We can conclude that inhibitory control represents a significant developmental factor of different adaptive behaviour domains in children with mild intellectual disability. © 2012 The Authors. Journal of Intellectual Disability Research © 2012 John Wiley & Sons Ltd, MENCAP & IASSIDD.

Evolutionary and Functional Relationships in the Truncated Hemoglobin Family.

PubMed

Bustamante, Juan P; Radusky, Leandro; Boechi, Leonardo; Estrin, Darío A; Ten Have, Arjen; Martí, Marcelo A

2016-01-01

Predicting function from sequence is an important goal in current biological research, and although, broad functional assignment is possible when a protein is assigned to a family, predicting functional specificity with accuracy is not straightforward. If function is provided by key structural properties and the relevant properties can be computed using the sequence as the starting point, it should in principle be possible to predict function in detail. The truncated hemoglobin family presents an interesting benchmark study due to their ubiquity, sequence diversity in the context of a conserved fold and the number of characterized members. Their functions are tightly related to O2 affinity and reactivity, as determined by the association and dissociation rate constants, both of which can be predicted and analyzed using in-silico based tools. In the present work we have applied a strategy, which combines homology modeling with molecular based energy calculations, to predict and analyze function of all known truncated hemoglobins in an evolutionary context. Our results show that truncated hemoglobins present conserved family features, but that its structure is flexible enough to allow the switch from high to low affinity in a few evolutionary steps. Most proteins display moderate to high oxygen affinities and multiple ligand migration paths, which, besides some minor trends, show heterogeneous distributions throughout the phylogenetic tree, again suggesting fast functional adaptation. Our data not only deepens our comprehension of the structural basis governing ligand affinity, but they also highlight some interesting functional evolutionary trends.

Evolutionary and Functional Relationships in the Truncated Hemoglobin Family

PubMed Central

Bustamante, Juan P.; Radusky, Leandro; Boechi, Leonardo; Estrin, Darío A.; ten Have, Arjen; Martí, Marcelo A.

2016-01-01

Predicting function from sequence is an important goal in current biological research, and although, broad functional assignment is possible when a protein is assigned to a family, predicting functional specificity with accuracy is not straightforward. If function is provided by key structural properties and the relevant properties can be computed using the sequence as the starting point, it should in principle be possible to predict function in detail. The truncated hemoglobin family presents an interesting benchmark study due to their ubiquity, sequence diversity in the context of a conserved fold and the number of characterized members. Their functions are tightly related to O2 affinity and reactivity, as determined by the association and dissociation rate constants, both of which can be predicted and analyzed using in-silico based tools. In the present work we have applied a strategy, which combines homology modeling with molecular based energy calculations, to predict and analyze function of all known truncated hemoglobins in an evolutionary context. Our results show that truncated hemoglobins present conserved family features, but that its structure is flexible enough to allow the switch from high to low affinity in a few evolutionary steps. Most proteins display moderate to high oxygen affinities and multiple ligand migration paths, which, besides some minor trends, show heterogeneous distributions throughout the phylogenetic tree, again suggesting fast functional adaptation. Our data not only deepens our comprehension of the structural basis governing ligand affinity, but they also highlight some interesting functional evolutionary trends. PMID:26788940

The Cerebellum: Adaptive Prediction for Movement and Cognition.

PubMed

Sokolov, Arseny A; Miall, R Chris; Ivry, Richard B

2017-05-01

Over the past 30 years, cumulative evidence has indicated that cerebellar function extends beyond sensorimotor control. This view has emerged from studies of neuroanatomy, neuroimaging, neuropsychology, and brain stimulation, with the results implicating the cerebellum in domains as diverse as attention, language, executive function, and social cognition. Although the literature provides sophisticated models of how the cerebellum helps refine movements, it remains unclear how the core mechanisms of these models can be applied when considering a broader conceptualization of cerebellar function. In light of recent multidisciplinary findings, we examine how two key concepts that have been suggested as general computational principles of cerebellar function- prediction and error-based learning- might be relevant in the operation of cognitive cerebro-cerebellar loops. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Focus on Reward Prediction and the Lateral Habenula: Functional Alterations and the Behavioral Outcomes Induced by Drugs of Abuse.

PubMed

Graziane, Nicholas M; Neumann, Peter A; Dong, Yan

2018-01-01

The lateral habenula (LHb) regulates reward learning and controls the updating of reward-related information. Drugs of abuse have the capacity to hijack the cellular and neurocircuit mechanisms mediating reward learning, forming non-adaptable, compulsive behaviors geared toward obtaining illicit substances. Here, we discuss current findings demonstrating how drugs of abuse alter intrinsic and synaptic LHb neuronal function. Additionally, we discuss evidence for how drug-induced LHb alterations may affect the ability to predict reward, potentially facilitating an addiction-like state. Altogether, we combine ex vivo and in vivo results for an overview of how drugs of abuse alter LHb function and how these functional alterations affect the ability to learn and update behavioral responses to hedonic external stimuli.

An immune clock of human pregnancy

PubMed Central

Aghaeepour, Nima; Ganio, Edward A.; Mcilwain, David; Tsai, Amy S.; Tingle, Martha; Van Gassen, Sofie; Gaudilliere, Dyani K.; Baca, Quentin; McNeil, Leslie; Okada, Robin; Ghaemi, Mohammad S.; Furman, David; Wong, Ronald J.; Winn, Virginia D.; Druzin, Maurice L.; El-Sayed, Yaser Y.; Quaintance, Cecele; Gibbs, Ronald; Darmstadt, Gary L.; Shaw, Gary M.; Stevenson, David K.; Tibshirani, Robert; Nolan, Garry P.; Lewis, David B.; Angst, Martin S.; Gaudilliere, Brice

2017-01-01

The maintenance of pregnancy relies on finely tuned immune adaptations. We demonstrate that these adaptations are precisely timed, reflecting an immune clock of pregnancy in women delivering at term. Using mass cytometry, the abundance and functional responses of all major immune cell subsets were quantified in serial blood samples collected throughout pregnancy. Cell signaling–based Elastic Net, a regularized regression method adapted from the elastic net algorithm, was developed to infer and prospectively validate a predictive model of interrelated immune events that accurately captures the chronology of pregnancy. Model components highlighted existing knowledge and revealed previously unreported biology, including a critical role for the interleukin-2–dependent STAT5ab signaling pathway in modulating T cell function during pregnancy. These findings unravel the precise timing of immunological events occurring during a term pregnancy and provide the analytical framework to identify immunological deviations implicated in pregnancy-related pathologies. PMID:28864494

Personality Constellations of Adolescents with Histories of Traumatic Parental Separations

PubMed Central

Malone, Johanna C.; Westen, Drew; Levendosky, Alytia A.

2014-01-01

Consistent with attachment theory and a developmental psychopathology framework, a growing body of research suggests that traumatic parental separations may lead to unique pathways of personality adaptation and maladaptation. The present study both examined personality characteristics and identified personality subtypes of adolescents with histories of traumatic separations. Randomly selected psychologists and psychiatrists provided data on 236 adolescents with histories of traumatic separations using a personality pathology instrument designed for use by clinically experienced observers, the Shedler-Westen Assessment Procedure (SWAP-II-A). Using a Q factor analysis, five distinct personality subtypes were identified: internalizing/avoidant, psychopathic, resilient, impulsive dysregulated, and immature dysregulated. Initial support for the validity of the subtypes was established based on Axis I and Axis II pathology, adaptive functioning, developmental history, and family history variables. The personality subtypes demonstrated substantial incremental validity in predicting adaptive functioning, above and beyond demographic variables and histories of other traumatic experiences. PMID:24647212

Predicting the practice effects on the blood oxygenation level-dependent (BOLD) function of fMRI in a symbolic manipulation task

NASA Astrophysics Data System (ADS)

Qin, Yulin; Sohn, Myeong-Ho; Anderson, John R.; Stenger, V. Andrew; Fissell, Kate; Goode, Adam; Carter, Cameron S.

2003-04-01

Based on adaptive control of thought-rational (ACT-R), a cognitive architecture for cognitive modeling, researchers have developed an information-processing model to predict the blood oxygenation level-dependent (BOLD) response of functional MRI in symbol manipulation tasks. As an extension of this research, the current event-related functional MRI study investigates the effect of relatively extensive practice on the activation patterns of related brain regions. The task involved performing transformations on equations in an artificial algebra system. This paper shows that the base-level activation learning in the ACT-R theory can predict the change of the BOLD response in practice in a left prefrontal region reflecting retrieval of information. In contrast, practice has relatively little effect on the form of BOLD response in the parietal region reflecting imagined transformations to the equation or the motor region reflecting manual programming.

Optimality Principles for Model-Based Prediction of Human Gait

PubMed Central

Ackermann, Marko; van den Bogert, Antonie J.

2010-01-01

Although humans have a large repertoire of potential movements, gait patterns tend to be stereotypical and appear to be selected according to optimality principles such as minimal energy. When applied to dynamic musculoskeletal models such optimality principles might be used to predict how a patient’s gait adapts to mechanical interventions such as prosthetic devices or surgery. In this paper we study the effects of different performance criteria on predicted gait patterns using a 2D musculoskeletal model. The associated optimal control problem for a family of different cost functions was solved utilizing the direct collocation method. It was found that fatigue-like cost functions produced realistic gait, with stance phase knee flexion, as opposed to energy-related cost functions which avoided knee flexion during the stance phase. We conclude that fatigue minimization may be one of the primary optimality principles governing human gait. PMID:20074736

Planetary Transmission Diagnostics

NASA Technical Reports Server (NTRS)

Lewicki, David G. (Technical Monitor); Samuel, Paul D.; Conroy, Joseph K.; Pines, Darryll J.

2004-01-01

This report presents a methodology for detecting and diagnosing gear faults in the planetary stage of a helicopter transmission. This diagnostic technique is based on the constrained adaptive lifting algorithm. The lifting scheme, developed by Wim Sweldens of Bell Labs, is a time domain, prediction-error realization of the wavelet transform that allows for greater flexibility in the construction of wavelet bases. Classic lifting analyzes a given signal using wavelets derived from a single fundamental basis function. A number of researchers have proposed techniques for adding adaptivity to the lifting scheme, allowing the transform to choose from a set of fundamental bases the basis that best fits the signal. This characteristic is desirable for gear diagnostics as it allows the technique to tailor itself to a specific transmission by selecting a set of wavelets that best represent vibration signals obtained while the gearbox is operating under healthy-state conditions. However, constraints on certain basis characteristics are necessary to enhance the detection of local wave-form changes caused by certain types of gear damage. The proposed methodology analyzes individual tooth-mesh waveforms from a healthy-state gearbox vibration signal that was generated using the vibration separation (synchronous signal-averaging) algorithm. Each waveform is separated into analysis domains using zeros of its slope and curvature. The bases selected in each analysis domain are chosen to minimize the prediction error, and constrained to have the same-sign local slope and curvature as the original signal. The resulting set of bases is used to analyze future-state vibration signals and the lifting prediction error is inspected. The constraints allow the transform to effectively adapt to global amplitude changes, yielding small prediction errors. However, local wave-form changes associated with certain types of gear damage are poorly adapted, causing a significant change in the prediction error. The constrained adaptive lifting diagnostic algorithm is validated using data collected from the University of Maryland Transmission Test Rig and the results are discussed.

Structural adaptation of cold-active RTX lipase from Pseudomonas sp. strain AMS8 revealed via homology and molecular dynamics simulation approaches.

PubMed

Mohamad Ali, Mohd Shukuri; Mohd Fuzi, Siti Farhanie; Ganasen, Menega; Abdul Rahman, Raja Noor Zaliha Raja; Basri, Mahiran; Salleh, Abu Bakar

2013-01-01

The psychrophilic enzyme is an interesting subject to study due to its special ability to adapt to extreme temperatures, unlike typical enzymes. Utilizing computer-aided software, the predicted structure and function of the enzyme lipase AMS8 (LipAMS8) (isolated from the psychrophilic Pseudomonas sp., obtained from the Antarctic soil) are studied. The enzyme shows significant sequence similarities with lipases from Pseudomonas sp. MIS38 and Serratia marcescens. These similarities aid in the prediction of the 3D molecular structure of the enzyme. In this study, 12 ns MD simulation is performed at different temperatures for structural flexibility and stability analysis. The results show that the enzyme is most stable at 0°C and 5°C. In terms of stability and flexibility, the catalytic domain (N-terminus) maintained its stability more than the noncatalytic domain (C-terminus), but the non-catalytic domain showed higher flexibility than the catalytic domain. The analysis of the structure and function of LipAMS8 provides new insights into the structural adaptation of this protein at low temperatures. The information obtained could be a useful tool for low temperature industrial applications and molecular engineering purposes, in the near future.

Characterizing Decision-Analysis Performances of Risk Prediction Models Using ADAPT Curves.

PubMed

Lee, Wen-Chung; Wu, Yun-Chun

2016-01-01

The area under the receiver operating characteristic curve is a widely used index to characterize the performance of diagnostic tests and prediction models. However, the index does not explicitly acknowledge the utilities of risk predictions. Moreover, for most clinical settings, what counts is whether a prediction model can guide therapeutic decisions in a way that improves patient outcomes, rather than to simply update probabilities.Based on decision theory, the authors propose an alternative index, the "average deviation about the probability threshold" (ADAPT).An ADAPT curve (a plot of ADAPT value against the probability threshold) neatly characterizes the decision-analysis performances of a risk prediction model.Several prediction models can be compared for their ADAPT values at a chosen probability threshold, for a range of plausible threshold values, or for the whole ADAPT curves. This should greatly facilitate the selection of diagnostic tests and prediction models.

ATLAS trigger operations: Upgrades to ``Xmon'' rate prediction system

NASA Astrophysics Data System (ADS)

Myers, Ava; Aukerman, Andrew; Hong, Tae Min; Atlas Collaboration

2017-01-01

We present ``Xmon,'' a tool to monitor trigger rates in the Control Room of the ATLAS Experiment. We discuss Xmon's recent (1) updates, (2) upgrades, and (3) operations. (1) Xmon was updated to modify the tool written for the three-level trigger architecture in Run-1 (2009-2012) to adapt to the new two-level system for Run-2 (2015-current). The tool takes as input the beam luminosity to make a rate prediction, which is compared with incoming rates to detect anomalies that occur both globally throughout a run and locally within a run. Global offsets are more commonly caught by the predictions based upon past runs, where offline processing allows for function adjustments and fit quality through outlier rejection. (2) Xmon was upgraded to detect local offsets using on-the-fly predictions, which uses a sliding window of in-run rates to make predictions. (3) Xmon operations examples are given. Future work involves further automation of the steps to provide the predictive functions and for alerting shifters.

Early play may predict later dominance relationships in yellow-bellied marmots (Marmota flaviventris).

PubMed

Blumstein, Daniel T; Chung, Lawrance K; Smith, Jennifer E

2013-05-22

Play has been defined as apparently functionless behaviour, yet since play is costly, models of adaptive evolution predict that it should have some beneficial function (or functions) that outweigh its costs. We provide strong evidence for a long-standing, but poorly supported hypothesis: that early social play is practice for later dominance relationships. We calculated the relative dominance rank by observing the directional outcome of playful interactions in juvenile and yearling yellow-bellied marmots (Marmota flaviventris) and found that these rank relationships were correlated with later dominance ranks calculated from agonistic interactions, however, the strength of this relationship attenuated over time. While play may have multiple functions, one of them may be to establish later dominance relationships in a minimally costly way.

DFT-based method for more accurate adsorption energies: An adaptive sum of energies from RPBE and vdW density functionals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hensley, Alyssa J. R.; Ghale, Kushal; Rieg, Carolin

In recent years, the popularity of density functional theory with periodic boundary conditions (DFT) has surged for the design and optimization of functional materials. However, no single DFT exchange–correlation functional currently available gives accurate adsorption energies on transition metals both when bonding to the surface is dominated by strong covalent or ionic bonding and when it has strong contributions from van der Waals interactions (i.e., dispersion forces). Here we present a new, simple method for accurately predicting adsorption energies on transition-metal surfaces based on DFT calculations, using an adaptively weighted sum of energies from RPBE and optB86b-vdW (or optB88-vdW) densitymore » functionals. This method has been benchmarked against a set of 39 reliable experimental energies for adsorption reactions. Our results show that this method has a mean absolute error and root mean squared error relative to experiments of 13.4 and 19.3 kJ/mol, respectively, compared to 20.4 and 26.4 kJ/mol for the BEEF-vdW functional. For systems with large van der Waals contributions, this method decreases these errors to 11.6 and 17.5 kJ/mol. Furthermore, this method provides predictions of adsorption energies both for processes dominated by strong covalent or ionic bonding and for those dominated by dispersion forces that are more accurate than those of any current standard DFT functional alone.« less

DFT-based method for more accurate adsorption energies: An adaptive sum of energies from RPBE and vdW density functionals

DOE PAGES

Hensley, Alyssa J. R.; Ghale, Kushal; Rieg, Carolin; ...

2017-01-26

In recent years, the popularity of density functional theory with periodic boundary conditions (DFT) has surged for the design and optimization of functional materials. However, no single DFT exchange–correlation functional currently available gives accurate adsorption energies on transition metals both when bonding to the surface is dominated by strong covalent or ionic bonding and when it has strong contributions from van der Waals interactions (i.e., dispersion forces). Here we present a new, simple method for accurately predicting adsorption energies on transition-metal surfaces based on DFT calculations, using an adaptively weighted sum of energies from RPBE and optB86b-vdW (or optB88-vdW) densitymore » functionals. This method has been benchmarked against a set of 39 reliable experimental energies for adsorption reactions. Our results show that this method has a mean absolute error and root mean squared error relative to experiments of 13.4 and 19.3 kJ/mol, respectively, compared to 20.4 and 26.4 kJ/mol for the BEEF-vdW functional. For systems with large van der Waals contributions, this method decreases these errors to 11.6 and 17.5 kJ/mol. Furthermore, this method provides predictions of adsorption energies both for processes dominated by strong covalent or ionic bonding and for those dominated by dispersion forces that are more accurate than those of any current standard DFT functional alone.« less

An Automated, Adaptive Framework for Optimizing Preprocessing Pipelines in Task-Based Functional MRI

PubMed Central

Churchill, Nathan W.; Spring, Robyn; Afshin-Pour, Babak; Dong, Fan; Strother, Stephen C.

2015-01-01

BOLD fMRI is sensitive to blood-oxygenation changes correlated with brain function; however, it is limited by relatively weak signal and significant noise confounds. Many preprocessing algorithms have been developed to control noise and improve signal detection in fMRI. Although the chosen set of preprocessing and analysis steps (the “pipeline”) significantly affects signal detection, pipelines are rarely quantitatively validated in the neuroimaging literature, due to complex preprocessing interactions. This paper outlines and validates an adaptive resampling framework for evaluating and optimizing preprocessing choices by optimizing data-driven metrics of task prediction and spatial reproducibility. Compared to standard “fixed” preprocessing pipelines, this optimization approach significantly improves independent validation measures of within-subject test-retest, and between-subject activation overlap, and behavioural prediction accuracy. We demonstrate that preprocessing choices function as implicit model regularizers, and that improvements due to pipeline optimization generalize across a range of simple to complex experimental tasks and analysis models. Results are shown for brief scanning sessions (<3 minutes each), demonstrating that with pipeline optimization, it is possible to obtain reliable results and brain-behaviour correlations in relatively small datasets. PMID:26161667

An in silico pipeline to filter the Toxoplasma gondii proteome for proteins that could traffic to the host cell nucleus and influence host cell epigenetic regulation.

PubMed

Syn, Genevieve; Blackwell, Jenefer M; Jamieson, Sarra E; Francis, Richard W

2018-01-01

Toxoplasma gondii uses epigenetic mechanisms to regulate both endogenous and host cell gene expression. To identify genes with putative epigenetic functions, we developed an in silico pipeline to interrogate the T. gondii proteome of 8313 proteins. Step 1 employs PredictNLS and NucPred to identify genes predicted to target eukaryotic nuclei. Step 2 uses GOLink to identify proteins of epigenetic function based on Gene Ontology terms. This resulted in 611 putative nuclear localised proteins with predicted epigenetic functions. Step 3 filtered for secretory proteins using SignalP, SecretomeP, and experimental data. This identified 57 of the 611 putative epigenetic proteins as likely to be secreted. The pipeline is freely available online, uses open access tools and software with user-friendly Perl scripts to automate and manage the results, and is readily adaptable to undertake any such in silico search for genes contributing to particular functions.

Switching Adaptability in Human-Inspired Sidesteps: A Minimal Model.

PubMed

Fujii, Keisuke; Yoshihara, Yuki; Tanabe, Hiroko; Yamamoto, Yuji

2017-01-01

Humans can adapt to abruptly changing situations by coordinating redundant components, even in bipedality. Conventional adaptability has been reproduced by various computational approaches, such as optimal control, neural oscillator, and reinforcement learning; however, the adaptability in bipedal locomotion necessary for biological and social activities, such as unpredicted direction change in chase-and-escape, is unknown due to the dynamically unstable multi-link closed-loop system. Here we propose a switching adaptation model for performing bipedal locomotion by improving autonomous distributed control, where autonomous actuators interact without central control and switch the roles for propulsion, balancing, and leg swing. Our switching mobility model achieved direction change at any time using only three actuators, although it showed higher motor costs than comparable models without direction change. Our method of evaluating such adaptation at any time should be utilized as a prerequisite for understanding universal motor control. The proposed algorithm may simply explain and predict the adaptation mechanism in human bipedality to coordinate the actuator functions within and between limbs.

Everyday executive function predicts adaptive and internalizing behavior among children with and without autism spectrum disorder.

PubMed

Gardiner, Emily; Iarocci, Grace

2018-02-01

Individuals with autism spectrum disorder (ASD) demonstrate challenges with executive function (EF), adaptive behavior, and mental health, all of which place long-term wellbeing at risk. In the current study we examined the relation between parent-rated EF and adaptive functioning and internalizing symptoms (anxiety, depression), as we expected that identifying the specific EF domains most closely related to these indices of functioning would illuminate opportunities for targeted intervention. Participants included 59 children and adolescents with ASD (M = 10.1 years) and 67 who were typically developing (TD) (M = 9.4 years) matched on age, IQ, mental age, and maternal education. Caregivers completed the Behavior Rating Inventory of EF (BRIEF) and Behavior Assessment System for Children, Second Edition (BASC-2). Parents rated children with ASD as demonstrating significantly more challenges across most of the examined BRIEF and BASC-2 indices and scales, with the exception of organization of materials (BRIEF) and anxiety (BASC-2). For both groups, metacognitive EF processes emerged as strongly associated with practical, conceptual, and social skills, though different BRIEF scales emerged as significant across the component subdomains. In terms of the relation with mental health, BRIEF index scores were unrelated to anxiety for both groups. Behavior regulation, however, was significantly associated with depression symptoms for children with and without ASD. The findings highlight the possibility that targeting particular EF domains among individuals with and without ASD may not only have direct benefit for behavior regulation and metacognitive abilities, but may also extend to other areas of life, including adaptive behavior and concomitant internalizing symptomatology. Autism Res 2018, 11: 284-295. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. We examined whether parents' ratings of their children's flexibility and ability to monitor their behavior predicted adaptive skills (e.g., ability to complete day-to-day personal tasks, communicate, and socialize) and symptoms of anxiety and depression among children with and without autism spectrum disorder. For both groups, children's abilities to manage and monitor their behavior were strongly related to adaptive skills. Children's flexibility and ability to inhibit inappropriate behavior and control their emotions was associated with depression symptoms for both groups. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Functionally dissociable influences on learning rate in a dynamic environment

PubMed Central

McGuire, Joseph T.; Nassar, Matthew R.; Gold, Joshua I.; Kable, Joseph W.

2015-01-01

Summary Maintaining accurate beliefs in a changing environment requires dynamically adapting the rate at which one learns from new experiences. Beliefs should be stable in the face of noisy data, but malleable in periods of change or uncertainty. Here we used computational modeling, psychophysics and fMRI to show that adaptive learning is not a unitary phenomenon in the brain. Rather, it can be decomposed into three computationally and neuroanatomically distinct factors that were evident in human subjects performing a spatial-prediction task: (1) surprise-driven belief updating, related to BOLD activity in visual cortex; (2) uncertainty-driven belief updating, related to anterior prefrontal and parietal activity; and (3) reward-driven belief updating, a context-inappropriate behavioral tendency related to activity in ventral striatum. These distinct factors converged in a core system governing adaptive learning. This system, which included dorsomedial frontal cortex, responded to all three factors and predicted belief updating both across trials and across individuals. PMID:25459409

Coping Skills Help Explain How Future-Oriented Adolescents Accrue Greater Well-Being Over Time.

PubMed

Chua, Li Wen; Milfont, Taciano L; Jose, Paul E

2015-11-01

Adolescents who endorse greater levels of future orientation report greater well-being over time, but we do not know the mechanism by which this happens. The present longitudinal study examined whether both adaptive as well as maladaptive coping strategies might explain how future orientation leads to ill-being and well-being over time in young New Zealanders. A sample of 1,774 preadolescents and early adolescents (51.9 % female) aged 10-15 years at Time 1 completed a self-report survey three times with 1 year intervals in between. Longitudinal mediation path models were constructed to determine whether and how maladaptive and adaptive coping strategies at Time 2 functioned as mediators between future orientation at Time 1 and ill-being and well-being at Time 3. Results showed that future orientation predicted lower maladaptive coping, which in turn predicted lower substance use and self-harming behavior. All three well-being outcomes (i.e., happiness with weight, vitality, and sleep) were consistently predicted by future orientation, and all three pathways were mediated by both lower maladaptive and higher adaptive coping strategies (with the exception of happiness with weight, which was mediated only by lower maladaptive coping). The results suggest that several pathways by which future orientation leads to greater well-being occurs through an increased use of adaptive coping, a decreased use of maladaptive coping, or both.

What's So Bad about Being Wet All Over: Investigating Leaf Surface Wetness.

ERIC Educational Resources Information Center

Brewer, Carol A.

1996-01-01

Presents investigations of leaf surface wetness that provide ideal opportunities for students to explore the relationships between leaf form and function, to study surface conditions of leaves and plant physiology, and to make predictions about plant adaptation in different environments. Describes simple procedures for exploring questions related…

Practical extension of a Lake States tree height model

Treesearch

Don C. Bragg

2008-01-01

By adapting data from national and state champion lists and the predictions of an existing height model, an exponential function was developed to improvetree height estimation. As a case study, comparisons between the original and redesigned model were made with eastern white pine (Pinus strobus L.). Forexample, the heights...

Neural network applications in telecommunications

NASA Technical Reports Server (NTRS)

Alspector, Joshua

1994-01-01

Neural network capabilities include automatic and organized handling of complex information, quick adaptation to continuously changing environments, nonlinear modeling, and parallel implementation. This viewgraph presentation presents Bellcore work on applications, learning chip computational function, learning system block diagram, neural network equalization, broadband access control, calling-card fraud detection, software reliability prediction, and conclusions.

Amygdala Habituation and Prefrontal Functional Connectivity in Youth with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Swartz, Johnna R.; Wiggins, Jillian Lee; Carrasco, Melissa; Lord, Catherine; Monk, Christopher S.

2013-01-01

Objective: Amygdala habituation, the rapid decrease in amygdala responsiveness to the repeated presentation of stimuli, is fundamental to the nervous system. Habituation is important for maintaining adaptive levels of arousal to predictable social stimuli and decreased habituation is associated with heightened anxiety. Input from the ventromedial…

A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

PubMed

Ingram, James N; Howard, Ian S; Flanagan, J Randall; Wolpert, Daniel M

2011-09-01

Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics, however, the representations can be engaged based on visual context, and are updated by a single-rate process.

Can personality traits predict the future development of heart disease in hospitalized psychiatric veterans?

PubMed

Williams, Wright; Kunik, Mark E; Springer, Justin; Graham, David P

2013-11-01

To examine which personality traits are associated with the new onset of chronic coronary heart disease (CHD) in psychiatric inpatients within 16 years after their initial evaluation. We theorized that personality measures of depression, anxiety, hostility, social isolation, and substance abuse would predict CHD development in psychiatric inpatients. We used a longitudinal database of psychological test data from 349 Veterans first admitted to a psychiatric unit between October 1, 1983, and September 30, 1987. Veterans Affairs and national databases were assessed to determine the development of new-onset chronic CHD over the intervening 16-year period. New-onset CHD developed in 154 of the 349 (44.1%) subjects. Thirty-one psychometric variables from five personality tests significantly predicted the development of CHD. We performed a factor analysis of these variables because they overlapped and four factors emerged, with positive adaptive functioning the only significant factor (OR=0.798, p=0.038). These results support previous research linking personality traits to the development of CHD, extending this association to a population of psychiatric inpatients. Compilation of these personality measures showed that 31 overlapping psychometric variables predicted those Veterans who developed a diagnosis of heart disease within 16 years after their initial psychiatric hospitalization. Our results suggest that personality variables measuring positive adaptive functioning are associated with a reduced risk of developing chronic CHD.

Dynamic filtering improves attentional state prediction with fNIRS

PubMed Central

Harrivel, Angela R.; Weissman, Daniel H.; Noll, Douglas C.; Huppert, Theodore; Peltier, Scott J.

2016-01-01

Brain activity can predict a person’s level of engagement in an attentional task. However, estimates of brain activity are often confounded by measurement artifacts and systemic physiological noise. The optimal method for filtering this noise – thereby increasing such state prediction accuracy – remains unclear. To investigate this, we asked study participants to perform an attentional task while we monitored their brain activity with functional near infrared spectroscopy (fNIRS). We observed higher state prediction accuracy when noise in the fNIRS hemoglobin [Hb] signals was filtered with a non-stationary (adaptive) model as compared to static regression (84% ± 6% versus 72% ± 15%). PMID:27231602

Neurocognitive, Social-Behavioral, and Adaptive Functioning in Preschool Children with Mild to Moderate Kidney Disease

PubMed Central

Hooper, Stephen R.; Gerson, Arlene C.; Johnson, Rebecca J.; Mendley, Susan R.; Shinnar, Shlomo; Lande, Marc B.; Matheson, Matthew B.; Gipson, Debbie S.; Morgenstern, Bruce; Warady, Bradley A.; Furth, Susan L.

2016-01-01

Objective The negative impact of End Stage Kidney Disease on cognitive function in children is well established, but no studies have examined the neurocognitive, social-behavioral, and adaptive behavior skills of preschool children with mild to moderate chronic kidney disease (CKD). Methods Participants included 124 preschool children with mild to moderate CKD, ages 12-68 months (median=3.7 years), and an associated mean glomerular filtration rate (GFR) of 50.0 ml/min per 1.73m2. In addition to level of function and percent of participants scoring≥1SD below the test mean, regression models examined the associations between biomarkers of CKD (GFR, anemia, hypertension, seizures, abnormal birth history), and Developmental Level/IQ, attention regulation, and parent ratings of executive functions, social-behavior, and adaptive behaviors. Results Median scores for all measures were in the average range; however, 27% were deemed at-risk for a Developmental Level/IQ<85, 20% were at-risk for attention variability, and parent ratings indicated 30% and 37% to be at-risk for executive dysfunction and adaptive behavior problems, respectively. Approximately 43% were deemed at-risk on two or more measures. None of the disease-related variables were significantly associated with these outcomes, although the presence of hypertension approached significance for attention variability (p<.09). Abnormal birth history and lower maternal education were significantly related to lower Developmental Level/IQ; seizures were related to lower parental ratings of executive function and adaptive behavior; and abnormal birth history was significantly related to lower ratings of adaptive behavior. When predicting risk status, the logistic regression did evidence both higher GFR and the lack of anemia to be associated with more intact Developmental Level/IQ. Conclusions These findings suggest relatively intact functioning for preschool children with mild to moderate CKD, but the need for ongoing developmental surveillance in this population remains warranted, particularly for those with abnormal birth histories, seizures, and heightened disease severity. PMID:26890559

A Structured Grid Based Solution-Adaptive Technique for Complex Separated Flows

NASA Technical Reports Server (NTRS)

Thornburg, Hugh; Soni, Bharat K.; Kishore, Boyalakuntla; Yu, Robert

1996-01-01

The objective of this work was to enhance the predictive capability of widely used computational fluid dynamic (CFD) codes through the use of solution adaptive gridding. Most problems of engineering interest involve multi-block grids and widely disparate length scales. Hence, it is desirable that the adaptive grid feature detection algorithm be developed to recognize flow structures of different type as well as differing intensity, and adequately address scaling and normalization across blocks. In order to study the accuracy and efficiency improvements due to the grid adaptation, it is necessary to quantify grid size and distribution requirements as well as computational times of non-adapted solutions. Flow fields about launch vehicles of practical interest often involve supersonic freestream conditions at angle of attack exhibiting large scale separate vortical flow, vortex-vortex and vortex-surface interactions, separated shear layers and multiple shocks of different intensity. In this work, a weight function and an associated mesh redistribution procedure is presented which detects and resolves these features without user intervention. Particular emphasis has been placed upon accurate resolution of expansion regions and boundary layers. Flow past a wedge at Mach=2.0 is used to illustrate the enhanced detection capabilities of this newly developed weight function.

Opto-mechanical design of ShaneAO: the adaptive optics system for the 3-meter Shane Telescope

NASA Astrophysics Data System (ADS)

Ratliff, C.; Cabak, J.; Gavel, D.; Kupke, R.; Dillon, D.; Gates, E.; Deich, W.; Ward, J.; Cowley, D.; Pfister, T.; Saylor, M.

2014-07-01

A Cassegrain mounted adaptive optics instrument presents unique challenges for opto-mechanical design. The flexure and temperature tolerances for stability are tighter than those of seeing limited instruments. This criteria requires particular attention to material properties and mounting techniques. This paper addresses the mechanical designs developed to meet the optical functional requirements. One of the key considerations was to have gravitational deformations, which vary with telescope orientation, stay within the optical error budget, or ensure that we can compensate with a steering mirror by maintaining predictable elastic behavior. Here we look at several cases where deformation is predicted with finite element analysis and Hertzian deformation analysis and also tested. Techniques used to address thermal deformation compensation without the use of low CTE materials will also be discussed.

Establishing a Dynamic Self-Adaptation Learning Algorithm of the BP Neural Network and Its Applications

NASA Astrophysics Data System (ADS)

Li, Xiaofeng; Xiang, Suying; Zhu, Pengfei; Wu, Min

2015-12-01

In order to avoid the inherent deficiencies of the traditional BP neural network, such as slow convergence speed, that easily leading to local minima, poor generalization ability and difficulty in determining the network structure, the dynamic self-adaptive learning algorithm of the BP neural network is put forward to improve the function of the BP neural network. The new algorithm combines the merit of principal component analysis, particle swarm optimization, correlation analysis and self-adaptive model, hence can effectively solve the problems of selecting structural parameters, initial connection weights and thresholds and learning rates of the BP neural network. This new algorithm not only reduces the human intervention, optimizes the topological structures of BP neural networks and improves the network generalization ability, but also accelerates the convergence speed of a network, avoids trapping into local minima, and enhances network adaptation ability and prediction ability. The dynamic self-adaptive learning algorithm of the BP neural network is used to forecast the total retail sale of consumer goods of Sichuan Province, China. Empirical results indicate that the new algorithm is superior to the traditional BP network algorithm in predicting accuracy and time consumption, which shows the feasibility and effectiveness of the new algorithm.

An economic prediction of the finer resolution level wavelet coefficients in electronic structure calculations.

PubMed

Nagy, Szilvia; Pipek, János

2015-12-21

In wavelet based electronic structure calculations, introducing a new, finer resolution level is usually an expensive task, this is why often a two-level approximation is used with very fine starting resolution level. This process results in large matrices to calculate with and a large number of coefficients to be stored. In our previous work we have developed an adaptively refined solution scheme that determines the indices, where the refined basis functions are to be included, and later a method for predicting the next, finer resolution coefficients in a very economic way. In the present contribution, we would like to determine whether the method can be applied for predicting not only the first, but also the other, higher resolution level coefficients. Also the energy expectation values of the predicted wave functions are studied, as well as the scaling behaviour of the coefficients in the fine resolution limit.

Improved fuzzy PID controller design using predictive functional control structure.

PubMed

Wang, Yuzhong; Jin, Qibing; Zhang, Ridong

2017-11-01

In conventional PID scheme, the ensemble control performance may be unsatisfactory due to limited degrees of freedom under various kinds of uncertainty. To overcome this disadvantage, a novel PID control method that inherits the advantages of fuzzy PID control and the predictive functional control (PFC) is presented and further verified on the temperature model of a coke furnace. Based on the framework of PFC, the prediction of the future process behavior is first obtained using the current process input signal. Then, the fuzzy PID control based on the multi-step prediction is introduced to acquire the optimal control law. Finally, the case study on a temperature model of a coke furnace shows the effectiveness of the fuzzy PID control scheme when compared with conventional PID control and fuzzy self-adaptive PID control. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Adapting to stress - chaperome networks in cancer.

PubMed

Joshi, Suhasini; Wang, Tai; Araujo, Thaís L S; Sharma, Sahil; Brodsky, Jeffrey L; Chiosis, Gabriela

2018-05-23

In this Opinion article, we aim to address how cells adapt to stress and the repercussions chronic stress has on cellular function. We consider acute and chronic stress-induced changes at the cellular level, with a focus on a regulator of cellular stress, the chaperome, which is a protein assembly that encompasses molecular chaperones, co-chaperones and other co-factors. We discuss how the chaperome takes on distinct functions under conditions of stress that are executed in ways that differ from the one-on-one cyclic, dynamic functions exhibited by distinct molecular chaperones. We argue that through the formation of multimeric stable chaperome complexes, a state of chaperome hyperconnectivity, or networking, is gained. The role of these chaperome networks is to act as multimolecular scaffolds, a particularly important function in cancer, where they increase the efficacy and functional diversity of several cellular processes. We predict that these concepts will change how we develop and implement drugs targeting the chaperome to treat cancer.

Predicting taxonomic and functional structure of microbial communities in acid mine drainage

PubMed Central

Kuang, Jialiang; Huang, Linan; He, Zhili; Chen, Linxing; Hua, Zhengshuang; Jia, Pu; Li, Shengjin; Liu, Jun; Li, Jintian; Zhou, Jizhong; Shu, Wensheng

2016-01-01

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray–Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural acidophilic microbial communities. PMID:26943622

Predicting taxonomic and functional structure of microbial communities in acid mine drainage.

PubMed

Kuang, Jialiang; Huang, Linan; He, Zhili; Chen, Linxing; Hua, Zhengshuang; Jia, Pu; Li, Shengjin; Liu, Jun; Li, Jintian; Zhou, Jizhong; Shu, Wensheng

2016-06-01

Predicting the dynamics of community composition and functional attributes responding to environmental changes is an essential goal in community ecology but remains a major challenge, particularly in microbial ecology. Here, by targeting a model system with low species richness, we explore the spatial distribution of taxonomic and functional structure of 40 acid mine drainage (AMD) microbial communities across Southeast China profiled by 16S ribosomal RNA pyrosequencing and a comprehensive microarray (GeoChip). Similar environmentally dependent patterns of dominant microbial lineages and key functional genes were observed regardless of the large-scale geographical isolation. Functional and phylogenetic β-diversities were significantly correlated, whereas functional metabolic potentials were strongly influenced by environmental conditions and community taxonomic structure. Using advanced modeling approaches based on artificial neural networks, we successfully predicted the taxonomic and functional dynamics with significantly higher prediction accuracies of metabolic potentials (average Bray-Curtis similarity 87.8) as compared with relative microbial abundances (similarity 66.8), implying that natural AMD microbial assemblages may be better predicted at the functional genes level rather than at taxonomic level. Furthermore, relative metabolic potentials of genes involved in many key ecological functions (for example, nitrogen and phosphate utilization, metals resistance and stress response) were extrapolated to increase under more acidic and metal-rich conditions, indicating a critical strategy of stress adaptation in these extraordinary communities. Collectively, our findings indicate that natural selection rather than geographic distance has a more crucial role in shaping the taxonomic and functional patterns of AMD microbial community that readily predicted by modeling methods and suggest that the model-based approach is essential to better understand natural acidophilic microbial communities.

Importance of stability of early living arrangements on behavior outcomes of children with and without prenatal drug exposure.

PubMed

Bada, Henrietta S; Langer, John; Twomey, Jean; Bursi, Charlotte; Lagasse, Linda; Bauer, Charles R; Shankaran, Seetha; Lester, Barry M; Higgins, Rosemary; Maza, Penelope L

2008-06-01

We evaluated whether living arrangements of children with or without prenatal drug exposure would be associated with their behavior outcomes and adaptive functioning. A total of 1388 children with or without prenatal cocaine or opiate exposure were enrolled in a longitudinal cohort study at 1 month of age, were seen at intervals, tracked over time for their living situation, and evaluated for behavior problems and adaptive functioning at 3 years of age. The Child Behavior Checklist and Vineland Adaptive Behavior Scales were administered. Using multiple regression models, we determined the factors that would predict behavior problems and adaptive functioning. Of the children enrolled, 1092 children were evaluated. Total and externalizing behavior problems T scores of children in relative care were lower (better) than those in parental care; externalizing behavior scores were lower than those in nonrelative care (p < .05). Total behavior problem scores increased 2.3 and 1.3 points, respectively, with each move per year and each year of Child Protective Services involvement. Compared to children in nonrelative care, those in parental or relative care had higher (better) scores in the Vineland Adaptive Behavior Scales total composite (p < .023), communication (p < .045), and daily living (p < .001). Each caretaker change was associated with a decrease of 2.65 and 2.19 points, respectively, in communication and daily living scores. Children's living arrangements were significantly associated with childhood behavior problems and adaptive functioning. The instability of living situation was also a significant predictor of these outcomes. While family preservation continues to be the goal of the child welfare system, expediting decision toward permanency remains paramount once children are placed in foster care.

β-Cell adaptation in pregnancy.

PubMed

Baeyens, L; Hindi, S; Sorenson, R L; German, M S

2016-09-01

Pregnancy in placental mammals places unique demands on the insulin-producing β-cells in the pancreatic islets of Langerhans. The pancreas anticipates the increase in insulin resistance that occurs late in pregnancy by increasing β-cell numbers and function earlier in pregnancy. In rodents, this β-cell expansion depends on secreted placental lactogens that signal through the prolactin receptor. Then at the end of pregnancy, the β-cell population contracts back to its pre-pregnancy size. In the current review, we focus on how glucose metabolism changes during pregnancy, how β-cells anticipate these changes through their response to lactogens and what molecular mechanisms guide the adaptive compensation. In addition, we summarize current knowledge of β-cell adaptation during human pregnancy and what happens when adaptation fails and gestational diabetes ensues. A better understanding of human β-cell adaptation to pregnancy would benefit efforts to predict, prevent and treat gestational diabetes. © 2016 John Wiley & Sons Ltd.

Family functioning and the course of adolescent bipolar disorder.

PubMed

Sullivan, Aimee E; Judd, Charles M; Axelson, David A; Miklowitz, David J

2012-12-01

The symptoms of bipolar disorder affect and are affected by the functioning of family environments. Little is known, however, about the stability of family functioning among youth with bipolar disorder as they cycle in and out of mood episodes. This study examined family functioning and its relationship to symptoms of adolescent bipolar disorder, using longitudinal measures of family cohesion, adaptability, and conflict. Parent- and adolescent-reported symptom and family functioning data were collected from 58 families of adolescents with bipolar disorder (mean age =14.48±1.60; 33 female, 25 male) who participated in a 2-year randomized trial of family-focused treatment for adolescents (FFT-A). Cohesion and adaptability scores did not significantly change over the course of the study. Parent-reported conflict prior to psychosocial treatment moderated the treatment responses of families, such that high-conflict families participating in FFT-A demonstrated greater reductions in conflict over time than low-conflict families. Moreover, adolescent mania symptoms improved more rapidly in low-conflict than in high-conflict families. For all respondents, cohesion, adaptability, and conflict were longitudinally correlated with adolescents' depression scores. Finally, decreases in parent-reported conflict also predicted decreases in adolescents' manic symptoms over the 2-year study. Findings suggest that family cohesion, adaptability, and conflict may be useful predictors of the course of adolescent mood symptoms. Family conflict may be an important target for family intervention in early onset bipolar disorder. Copyright © 2012. Published by Elsevier Ltd.

Do We Need Better Climate Predictions to Adapt to a Changing Climate? (Invited)

NASA Astrophysics Data System (ADS)

Dessai, S.; Hulme, M.; Lempert, R.; Pielke, R., Jr.

2009-12-01

Based on a series of international scientific assessments, climate change has been presented to society as a major problem that needs urgently to be tackled. The science that underpins these assessments has been pre-dominantly from the realm of the natural sciences and central to this framing have been ‘projections’ of future climate change (and its impacts on environment and society) under various greenhouse gas emissions scenarios and using a variety of climate model predictions with embedded assumptions. Central to much of the discussion surrounding adaptation to climate change is the claim - explicit or implicit - that decision makers need accurate and increasingly precise assessments of future impacts of climate change in order to adapt successfully. If true, this claim places a high premium on accurate and precise climate predictions at a range of geographical and temporal scales; such predictions therefore become indispensable, and indeed a prerequisite for, effective adaptation decision-making. But is effective adaptation tied to the ability of the scientific enterprise to predict future climate with accuracy and precision? If so, this may impose a serious and intractable limit on adaptation. This paper proceeds in three sections. It first gathers evidence of claims that climate prediction is necessary for adaptation decision-making. This evidence is drawn from peer-reviewed literature and from published science funding strategies and government policy in a number of different countries. The second part discusses the challenges of climate prediction and why science will consistently be unable to provide accurate and precise predictions of future climate relevant for adaptation (usually at the local/regional level). Section three discusses whether these limits to future foresight represent a limit to adaptation, arguing that effective adaptation need not be limited by a general inability to predict future climate. Given the deep uncertainties involved in climate prediction (and even more so in the prediction of climate impacts) and given that climate is usually only one factor in decisions aimed at climate adaptation, we conclude that the ‘predict and provide’ approach to science in support of climate change adaptation is largely flawed. We consider other important areas of public policy fraught with uncertainty - e.g. earthquake risk, national security, public health - where such a ‘predict and provide’ approach is not attempted. Instead of relying on an approach which has climate prediction (and consequent risk assessment) at its heart - which because of the associated epistemological limits to prediction will consequently act as an apparent limit to adaptation - we need to view adaptation differently, in a manner that opens up options for decision making under uncertainty. We suggest an approach which examines the robustness of adaptation strategies/policies/activities to the myriad of uncertainties that face us in the future, only one of which is the state of climate.

Functional morphology of the tetra fish Astyanax lacustris differs between divergent habitats in the Pantanal wetlands.

PubMed

Costa-Pereira, R; Araújo, M S; Paiva, F; Tavares, L E R

2016-08-01

This study investigated whether the body morphology of the tetra fish Astyanax lacustris (previously Astyanax asuncionensis) varied between populations inhabiting one lagoon (a lentic, shallow environment, with great habitat complexity created by aquatic macrophytes) and an adjacent river (a deeper, lotic environment where aquatic macrophytes are scarce) in a seasonally flooded wetland, despite population mixing during the wet season. Morphological differences matched a priori predictions of the theory relating functional body morphology and swimming performance in fishes between lagoon and river habitats. Observed morphological variation could have resulted from adaptive habitat choice by tetras, predation by piscivores and adaptive phenotypic plasticity during development. © 2016 The Fisheries Society of the British Isles.

Maternal supportive and interfering control as predictors of adaptive and social development in children with and without developmental delays

PubMed Central

Green, S.; Caplan, B.; Baker, B.

2016-01-01

Background Parents of children with developmental delays (DD) have been found to use more controlling behaviour with their children than parents of children with typical development (TD). While controlling behaviour is related to poorer developmental outcomes in TD children, there is little research on how it predicts outcomes in DD children. Furthermore, existing research tends to use inconsistent or non-specific definitions of controlling behaviour, often combining parent control which follows the child’s goal (e.g. supportive direction) and that which interferes with the child’s goal (e.g. interference). Methods Participants were 200 mother–child dyads observed at child age 3, with follow-up assessments of adaptive behaviour and social skills administered at child ages 5 and 6, respectively. We coded the frequency of both types of controlling behaviour based on mothers’ interactions with their children with TD (n = 113) or DD (n = 87) at age 3. Results Mothers in the DD group used more interfering but not more supportive directive acts compared to mothers in the TD group. Adaptive behaviour was assessed at child age 5 and social skills were assessed at age 6. Higher frequency of supportive directive acts predicted better adaptive functioning for the TD group and better social skills for the DD group. Higher frequency of interfering acts predicted lower adaptive and social skills for children with DD but not with TD. Conclusions Results are discussed in terms of the differential developmental needs of children with and without DD as well as implications for early intervention. PMID:23865770

A comparison of functional academic and daily living skills in males with fragile X syndrome with and without autism.

PubMed

Raspa, Melissa; Franco, Vitor; Bishop, Ellen; Wheeler, Anne C; Wylie, Amanda; Bailey, Donald B

2018-05-03

Adaptive behaviors, such as functional academic and daily living skills, are critical for independence in adults with intellectual and developmental disabilities. However, little is known about these skills in fragile X syndrome (FXS), the most common form of inherited intellectual disability. The purposes of this study were to describe the functional academic and daily living skills of males diagnosed with FXS across different age groups and compare skill attainment by autism status and other common co-occurring conditions. We used survey methods to assess parent-reported functional academic and daily living skills in 534 males with FXS. Functional academic skills included time and schedules, money, math, reading, and writing skills. Daily living skills included hygiene, cooking, laundry and housekeeping, transportation, and safety skills. Analyses examined functional academic and daily living skills in a cross-sectional sample of males between ages 5 and 67. Differences in skill attainment were found by child age, co-morbid autism status, total number of co-occurring conditions, and respondent education. Functional academic and daily living skills were predictive of community employment and independent living. These data provide important information on the mastery of both foundational and more complex adaptive skills in males with FXS. Both functional academic and daily living skills were predictive of measures of independence above and beyond other child and family characteristics. These findings point to the need to focus interventions to support the attainment of independence in males with FXS. Copyright © 2018 Elsevier Ltd. All rights reserved.

Prediction of Radical Scavenging Activities of Anthocyanins Applying Adaptive Neuro-Fuzzy Inference System (ANFIS) with Quantum Chemical Descriptors

PubMed Central

Jhin, Changho; Hwang, Keum Taek

2014-01-01

Radical scavenging activity of anthocyanins is well known, but only a few studies have been conducted by quantum chemical approach. The adaptive neuro-fuzzy inference system (ANFIS) is an effective technique for solving problems with uncertainty. The purpose of this study was to construct and evaluate quantitative structure-activity relationship (QSAR) models for predicting radical scavenging activities of anthocyanins with good prediction efficiency. ANFIS-applied QSAR models were developed by using quantum chemical descriptors of anthocyanins calculated by semi-empirical PM6 and PM7 methods. Electron affinity (A) and electronegativity (χ) of flavylium cation, and ionization potential (I) of quinoidal base were significantly correlated with radical scavenging activities of anthocyanins. These descriptors were used as independent variables for QSAR models. ANFIS models with two triangular-shaped input fuzzy functions for each independent variable were constructed and optimized by 100 learning epochs. The constructed models using descriptors calculated by both PM6 and PM7 had good prediction efficiency with Q-square of 0.82 and 0.86, respectively. PMID:25153627

IFCPT S-Duct Grid-Adapted FUN3D Computations for the Third Propulsion Aerodynamics Works

NASA Technical Reports Server (NTRS)

Davis, Zach S.; Park, M. A.

2017-01-01

Contributions of the unstructured Reynolds-averaged Navier-Stokes code, FUN3D, to the 3rd AIAA Propulsion Aerodynamics Workshop are described for the diffusing IFCPT S-Duct. Using workshop-supplied grids, results for the baseline S-Duct, baseline S-Duct with Aerodynamic Interface Plane (AIP) rake hardware, and baseline S-Duct with flow control devices are compared with experimental data and results computed with output-based, off-body grid adaptation in FUN3D. Due to the absence of influential geometry components, total pressure recovery is overpredicted on the baseline S-Duct and S-Duct with flow control vanes when compared to experimental values. An estimate for the exact value of total pressure recovery is derived for these cases given an infinitely refined mesh. When results from output-based mesh adaptation are compared with those computed on workshop-supplied grids, a considerable improvement in predicting total pressure recovery is observed. By including more representative geometry, output-based mesh adaptation compares very favorably with experimental data in terms of predicting the total pressure recovery cost-function; whereas, results computed using the workshop-supplied grids are underpredicted.

Genetic Adaptation to Climate in White Spruce Involves Small to Moderate Allele Frequency Shifts in Functionally Diverse Genes.

PubMed

Hornoy, Benjamin; Pavy, Nathalie; Gérardi, Sébastien; Beaulieu, Jean; Bousquet, Jean

2015-11-11

Understanding the genetic basis of adaptation to climate is of paramount importance for preserving and managing genetic diversity in plants in a context of climate change. Yet, this objective has been addressed mainly in short-lived model species. Thus, expanding knowledge to nonmodel species with contrasting life histories, such as forest trees, appears necessary. To uncover the genetic basis of adaptation to climate in the widely distributed boreal conifer white spruce (Picea glauca), an environmental association study was conducted using 11,085 single nucleotide polymorphisms representing 7,819 genes, that is, approximately a quarter of the transcriptome.Linear and quadratic regressions controlling for isolation-by-distance, and the Random Forest algorithm, identified several dozen genes putatively under selection, among which 43 showed strongest signals along temperature and precipitation gradients. Most of them were related to temperature. Small to moderate shifts in allele frequencies were observed. Genes involved encompassed a wide variety of functions and processes, some of them being likely important for plant survival under biotic and abiotic environmental stresses according to expression data. Literature mining and sequence comparison also highlighted conserved sequences and functions with angiosperm homologs.Our results are consistent with theoretical predictions that local adaptation involves genes with small frequency shifts when selection is recent and gene flow among populations is high. Accordingly, genetic adaptation to climate in P. glauca appears to be complex, involving many independent and interacting gene functions, biochemical pathways, and processes. From an applied perspective, these results shall lead to specific functional/association studies in conifers and to the development of markers useful for the conservation of genetic resources. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Genetic Adaptation to Climate in White Spruce Involves Small to Moderate Allele Frequency Shifts in Functionally Diverse Genes

PubMed Central

Hornoy, Benjamin; Pavy, Nathalie; Gérardi, Sébastien; Beaulieu, Jean; Bousquet, Jean

2015-01-01

Understanding the genetic basis of adaptation to climate is of paramount importance for preserving and managing genetic diversity in plants in a context of climate change. Yet, this objective has been addressed mainly in short-lived model species. Thus, expanding knowledge to nonmodel species with contrasting life histories, such as forest trees, appears necessary. To uncover the genetic basis of adaptation to climate in the widely distributed boreal conifer white spruce (Picea glauca), an environmental association study was conducted using 11,085 single nucleotide polymorphisms representing 7,819 genes, that is, approximately a quarter of the transcriptome. Linear and quadratic regressions controlling for isolation-by-distance, and the Random Forest algorithm, identified several dozen genes putatively under selection, among which 43 showed strongest signals along temperature and precipitation gradients. Most of them were related to temperature. Small to moderate shifts in allele frequencies were observed. Genes involved encompassed a wide variety of functions and processes, some of them being likely important for plant survival under biotic and abiotic environmental stresses according to expression data. Literature mining and sequence comparison also highlighted conserved sequences and functions with angiosperm homologs. Our results are consistent with theoretical predictions that local adaptation involves genes with small frequency shifts when selection is recent and gene flow among populations is high. Accordingly, genetic adaptation to climate in P. glauca appears to be complex, involving many independent and interacting gene functions, biochemical pathways, and processes. From an applied perspective, these results shall lead to specific functional/association studies in conifers and to the development of markers useful for the conservation of genetic resources. PMID:26560341

Functional integration of skeletal traits: an intraskeletal assessment of bone size, mineralization, and volume covariance.

PubMed

Schlecht, Stephen H; Jepsen, Karl J

2013-09-01

Understanding the functional integration of skeletal traits and how they naturally vary within and across populations will benefit assessments of functional adaptation directed towards interpreting bone stiffness in contemporary and past humans. Moreover, investigating how these traits intraskeletally vary will guide us closer towards predicting fragility from a single skeletal site. Using an osteological collection of 115 young adult male and female African-Americans, we assessed the functional relationship between bone robustness (i.e. total area/length), cortical tissue mineral density (Ct.TMD), and cortical area (Ct.Ar) for the upper and lower limbs. All long bones demonstrated significant trait covariance (p < 0.005) independent of body size, with slender bones having 25-50% less Ct.Ar and 5-8% higher Ct.TMD compared to robust bones. Robustness statistically explained 10.2-28% of Ct.TMD and 26.6-64.6% of Ct.Ar within male and female skeletal elements. This covariance is systemic throughout the skeleton, with either the slender or robust phenotype consistently represented within all long bones for each individual. These findings suggest that each person attains a unique trait set by adulthood that is both predictable by robustness and partially independent of environmental influences. The variation in these functionally integrated traits allows for the maximization of tissue stiffness and minimization of mass so that regardless of which phenotype is present, a given bone is reasonably stiff and strong, and sufficiently adapted to perform routine, habitual loading activities. Covariation intrinsic to functional adaptation suggests that whole bone stiffness depends upon particular sets of traits acquired during growth, presumably through differing levels of cellular activity, resulting in differing tissue morphology and composition. The outcomes of this intraskeletal examination of robustness and its correlates may have significant value in our progression towards improved clinical assessments of bone strength and fragility. Copyright © 2013 Elsevier Inc. All rights reserved.

Birth weight predicted baseline muscular efficiency, but not response of energy expenditure to calorie restriction: An empirical test of the predictive adaptive response hypothesis.

PubMed

Workman, Megan; Baker, Jack; Lancaster, Jane B; Mermier, Christine; Alcock, Joe

2016-07-01

Aiming to test the evolutionary significance of relationships linking prenatal growth conditions to adult phenotypes, this study examined whether birth size predicts energetic savings during fasting. We specifically tested a Predictive Adaptive Response (PAR) model that predicts greater energetic saving among adults who were born small. Data were collected from a convenience sample of young adults living in Albuquerque, NM (n = 34). Indirect calorimetry quantified changes in resting energy expenditure (REE) and active muscular efficiency that occurred in response to a 29-h fast. Multiple regression analyses linked birth weight to baseline and postfast metabolic values while controlling for appropriate confounders (e.g., sex, body mass). Birth weight did not moderate the relationship between body size and energy expenditure, nor did it predict the magnitude change in REE or muscular efficiency observed from baseline to after fasting. Alternative indicators of birth size were also examined (e.g., low v. normal birth weight, comparison of tertiles), with no effects found. However, baseline muscular efficiency improved by 1.1% per 725 g (S.D.) increase in birth weight (P = 0.037). Birth size did not influence the sensitivity of metabolic demands to fasting-neither at rest nor during activity. Moreover, small birth size predicted a reduction in the efficiency with which muscles convert energy expended into work accomplished. These results do not support the ascription of adaptive function to phenotypes associated with small birth size. © 2015 Wiley Periodicals, Inc. Am. J. Hum. Biol. 28:484-492, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Social Daydreaming and Adjustment: An Experience-Sampling Study of Socio-Emotional Adaptation During a Life Transition

PubMed Central

Poerio, Giulia L.; Totterdell, Peter; Emerson, Lisa-Marie; Miles, Eleanor

2016-01-01

Estimates suggest that up to half of waking life is spent daydreaming; that is, engaged in thought that is independent of, and unrelated to, one’s current task. Emerging research indicates that daydreams are predominately social suggesting that daydreams may serve socio-emotional functions. Here we explore the functional role of social daydreaming for socio-emotional adjustment during an important and stressful life transition (the transition to university) using experience-sampling with 103 participants over 28 days. Over time, social daydreams increased in their positive characteristics and positive emotional outcomes; specifically, participants reported that their daydreams made them feel more socially connected and less lonely, and that the content of their daydreams became less fanciful and involved higher quality relationships. These characteristics then predicted less loneliness at the end of the study, which, in turn was associated with greater social adaptation to university. Feelings of connection resulting from social daydreams were also associated with less emotional inertia in participants who reported being less socially adapted to university. Findings indicate that social daydreaming is functional for promoting socio-emotional adjustment to an important life event. We highlight the need to consider the social content of stimulus-independent cognitions, their characteristics, and patterns of change, to specify how social thoughts enable socio-emotional adaptation. PMID:26834685

MO-AB-BRA-10: Cancer Therapy Outcome Prediction Based On Dempster-Shafer Theory and PET Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lian, C; University of Rouen, QuantIF - EA 4108 LITIS, 76000 Rouen; Li, H

2015-06-15

Purpose: In cancer therapy, utilizing FDG-18 PET image-based features for accurate outcome prediction is challenging because of 1) limited discriminative information within a small number of PET image sets, and 2) fluctuant feature characteristics caused by the inferior spatial resolution and system noise of PET imaging. In this study, we proposed a new Dempster-Shafer theory (DST) based approach, evidential low-dimensional transformation with feature selection (ELT-FS), to accurately predict cancer therapy outcome with both PET imaging features and clinical characteristics. Methods: First, a specific loss function with sparse penalty was developed to learn an adaptive low-rank distance metric for representing themore » dissimilarity between different patients’ feature vectors. By minimizing this loss function, a linear low-dimensional transformation of input features was achieved. Also, imprecise features were excluded simultaneously by applying a l2,1-norm regularization of the learnt dissimilarity metric in the loss function. Finally, the learnt dissimilarity metric was applied in an evidential K-nearest-neighbor (EK- NN) classifier to predict treatment outcome. Results: Twenty-five patients with stage II–III non-small-cell lung cancer and thirty-six patients with esophageal squamous cell carcinomas treated with chemo-radiotherapy were collected. For the two groups of patients, 52 and 29 features, respectively, were utilized. The leave-one-out cross-validation (LOOCV) protocol was used for evaluation. Compared to three existing linear transformation methods (PCA, LDA, NCA), the proposed ELT-FS leads to higher prediction accuracy for the training and testing sets both for lung-cancer patients (100+/−0.0, 88.0+/−33.17) and for esophageal-cancer patients (97.46+/−1.64, 83.33+/−37.8). The ELT-FS also provides superior class separation in both test data sets. Conclusion: A novel DST- based approach has been proposed to predict cancer treatment outcome using PET image features and clinical characteristics. A specific loss function has been designed for robust accommodation of feature set incertitude and imprecision, facilitating adaptive learning of the dissimilarity metric for the EK-NN classifier.« less

Machine remaining useful life prediction: An integrated adaptive neuro-fuzzy and high-order particle filtering approach

NASA Astrophysics Data System (ADS)

Chen, Chaochao; Vachtsevanos, George; Orchard, Marcos E.

2012-04-01

Machine prognosis can be considered as the generation of long-term predictions that describe the evolution in time of a fault indicator, with the purpose of estimating the remaining useful life (RUL) of a failing component/subsystem so that timely maintenance can be performed to avoid catastrophic failures. This paper proposes an integrated RUL prediction method using adaptive neuro-fuzzy inference systems (ANFIS) and high-order particle filtering, which forecasts the time evolution of the fault indicator and estimates the probability density function (pdf) of RUL. The ANFIS is trained and integrated in a high-order particle filter as a model describing the fault progression. The high-order particle filter is used to estimate the current state and carry out p-step-ahead predictions via a set of particles. These predictions are used to estimate the RUL pdf. The performance of the proposed method is evaluated via the real-world data from a seeded fault test for a UH-60 helicopter planetary gear plate. The results demonstrate that it outperforms both the conventional ANFIS predictor and the particle-filter-based predictor where the fault growth model is a first-order model that is trained via the ANFIS.

Similarities in error processing establish a link between saccade prediction at baseline and adaptation performance.

PubMed

Wong, Aaron L; Shelhamer, Mark

2014-05-01

Adaptive processes are crucial in maintaining the accuracy of body movements and rely on error storage and processing mechanisms. Although classically studied with adaptation paradigms, evidence of these ongoing error-correction mechanisms should also be detectable in other movements. Despite this connection, current adaptation models are challenged when forecasting adaptation ability with measures of baseline behavior. On the other hand, we have previously identified an error-correction process present in a particular form of baseline behavior, the generation of predictive saccades. This process exhibits long-term intertrial correlations that decay gradually (as a power law) and are best characterized with the tools of fractal time series analysis. Since this baseline task and adaptation both involve error storage and processing, we sought to find a link between the intertrial correlations of the error-correction process in predictive saccades and the ability of subjects to alter their saccade amplitudes during an adaptation task. Here we find just such a relationship: the stronger the intertrial correlations during prediction, the more rapid the acquisition of adaptation. This reinforces the links found previously between prediction and adaptation in motor control and suggests that current adaptation models are inadequate to capture the complete dynamics of these error-correction processes. A better understanding of the similarities in error processing between prediction and adaptation might provide the means to forecast adaptation ability with a baseline task. This would have many potential uses in physical therapy and the general design of paradigms of motor adaptation. Copyright © 2014 the American Physiological Society.

Early play may predict later dominance relationships in yellow-bellied marmots (Marmota flaviventris)

PubMed Central

Blumstein, Daniel T.; Chung, Lawrance K.; Smith, Jennifer E.

2013-01-01

Play has been defined as apparently functionless behaviour, yet since play is costly, models of adaptive evolution predict that it should have some beneficial function (or functions) that outweigh its costs. We provide strong evidence for a long-standing, but poorly supported hypothesis: that early social play is practice for later dominance relationships. We calculated the relative dominance rank by observing the directional outcome of playful interactions in juvenile and yearling yellow-bellied marmots (Marmota flaviventris) and found that these rank relationships were correlated with later dominance ranks calculated from agonistic interactions, however, the strength of this relationship attenuated over time. While play may have multiple functions, one of them may be to establish later dominance relationships in a minimally costly way. PMID:23536602

Children with autism spectrum disorder show reduced adaptation to number

PubMed Central

Turi, Marco; Burr, David C.; Igliozzi, Roberta; Aagten-Murphy, David; Muratori, Filippo; Pellicano, Elizabeth

2015-01-01

Autism is known to be associated with major perceptual atypicalities. We have recently proposed a general model to account for these atypicalities in Bayesian terms, suggesting that autistic individuals underuse predictive information or priors. We tested this idea by measuring adaptation to numerosity stimuli in children diagnosed with autism spectrum disorder (ASD). After exposure to large numbers of items, stimuli with fewer items appear to be less numerous (and vice versa). We found that children with ASD adapted much less to numerosity than typically developing children, although their precision for numerosity discrimination was similar to that of the typical group. This result reinforces recent findings showing reduced adaptation to facial identity in ASD and goes on to show that reduced adaptation is not unique to faces (social stimuli with special significance in autism), but occurs more generally, for both parietal and temporal functions, probably reflecting inefficiencies in the adaptive interpretation of sensory signals. These results provide strong support for the Bayesian theories of autism. PMID:26056294

Circulating microRNA are predictive of aging and acute adaptive response to resistance exercise in men

USDA-ARS?s Scientific Manuscript database

Circulating microRNA (c-miRNA) have the potential to function as novel noninvasive markers of the underlying physiological state of skeletal muscle. This investigation sought to determine the influence of aging on c-miRNA expression at rest and following resistance exercise in male volunteers (Young...

Comparative genome analysis reveals genetic adaptation to versatile environmental conditions and importance of biofilm lifestyle in Comamonas testosteroni.

PubMed

Wu, Yichao; Arumugam, Krithika; Tay, Martin Qi Xiang; Seshan, Hari; Mohanty, Anee; Cao, Bin

2015-04-01

Comamonas testosteroni is an important environmental bacterium capable of degrading a variety of toxic aromatic pollutants and has been demonstrated to be a promising biocatalyst for environmental decontamination. This organism is often found to be among the primary surface colonizers in various natural and engineered ecosystems, suggesting an extraordinary capability of this organism in environmental adaptation and biofilm formation. The goal of this study was to gain genetic insights into the adaption of C. testosteroni to versatile environments and the importance of a biofilm lifestyle. Specifically, a draft genome of C. testosteroni I2 was obtained. The draft genome is 5,778,710 bp in length and comprises 110 contigs. The average G+C content was 61.88 %. A total of 5365 genes with 5263 protein-coding genes were predicted, whereas 4324 (80.60 % of total genes) protein-encoding genes were associated with predicted functions. The catabolic genes responsible for biodegradation of steroid and other aromatic compounds on draft genome were identified. Plasmid pI2 was found to encode a complete pathway for aniline degradation and a partial catabolic pathway for chloroaniline. This organism was found to be equipped with a sophisticated signaling system which helps it find ideal niches and switch between planktonic and biofilm lifestyles. A large number of putative multi-drug-resistant genes coding for abundant outer membrane transporters, chaperones, and heat shock proteins for the protection of cellular function were identified in the genome of strain I2. In addition, the genome of strain I2 was predicted to encode several proteins involved in producing, secreting, and uptaking siderophores under iron-limiting conditions. The genome of strain I2 contains a number of genes responsible for the synthesis and secretion of exopolysaccharides, an extracellular component essential for biofilm formation. Overall, our results reveal the genomic features underlying the adaption of C. testosteroni to versatile environments and highlighting the importance of its biofilm lifestyle.

A correlate of HIV-1 control consisting of both innate and adaptive immune parameters best predicts viral load by multivariable analysis in HIV-1 infected viremic controllers and chronically-infected non-controllers.

PubMed

Tomescu, Costin; Liu, Qin; Ross, Brian N; Yin, Xiangfan; Lynn, Kenneth; Mounzer, Karam C; Kostman, Jay R; Montaner, Luis J

2014-01-01

HIV-1 infected viremic controllers maintain durable viral suppression below 2000 copies viral RNA/ml without anti-retroviral therapy (ART), and the immunological factor(s) associated with host control in presence of low but detectable viral replication are of considerable interest. Here, we utilized a multivariable analysis to identify which innate and adaptive immune parameters best correlated with viral control utilizing a cohort of viremic controllers (median 704 viral RNA/ml) and non-controllers (median 21,932 viral RNA/ml) that were matched for similar CD4+ T cell counts in the absence of ART. We observed that HIV-1 Gag-specific CD8+ T cell responses were preferentially targeted over Pol-specific responses in viremic controllers (p = 0.0137), while Pol-specific responses were positively associated with viral load (rho = 0.7753, p = 0.0001, n = 23). Viremic controllers exhibited significantly higher NK and plasmacytoid dendritic cells (pDC) frequency as well as retained expression of the NK CD16 receptor and strong target cell-induced NK cell IFN-gamma production compared to non-controllers (p<0.05). Despite differences in innate and adaptive immune function however, both viremic controllers (p<0.05) and non-controller subjects (p<0.001) exhibited significantly increased CD8+ T cell activation and spontaneous NK cell degranulation compared to uninfected donors. Overall, we identified that a combination of innate (pDC frequency) and adaptive (Pol-specific CD8+ T cell responses) immune parameters best predicted viral load (R2 = 0.5864, p = 0.0021, n = 17) by a multivariable analysis. Together, this data indicates that preferential Gag-specific over Pol-specific CD8+ T cell responses along with a retention of functional innate subsets best predict host control over viral replication in HIV-1 infected viremic controllers compared to chronically-infected non-controllers.

A Two-Hit Model of Autism: Adolescence as the Second Hit

PubMed Central

Picci, Giorgia; Scherf, K. Suzanne

2015-01-01

Adolescence brings dramatic changes in behavior and neural organization. Unfortunately, for some 30% of individuals with autism, there is marked decline in adaptive functioning during adolescence. We propose a two-hit model of autism. First, early perturbations in neural development function as a “first hit” that sets up a neural system that is “built to fail” in the face of a second hit. Second, the confluence of pubertal hormones, neural reorganization, and increasing social demands during adolescence provides the “second hit” that interferes with the ability to transition into adult social roles and levels of adaptive functioning. In support of this model, we review evidence about adolescent-specific neural and behavioral development in autism. We conclude with predictions and recommendations for empirical investigation about several domains in which developmental trajectories for individuals with autism may be uniquely deterred in adolescence. PMID:26609500

Adaptation, plant evolution, and the fossil record

NASA Technical Reports Server (NTRS)

Knoll, A. H.; Niklas, K. J.

1987-01-01

The importance of adaptation in determining patterns of evolution has become an important focus of debate in evolutionary biology. As it pertains to paleobotany, the issue is whether or not adaptive evolution mediated by natural selection is sufficient to explain the stratigraphic distributions of taxa and character states observed in the plant fossil record. One means of addressing this question is the functional evaluation of stratigraphic series of plant organs set in the context of paleoenvironmental change and temporal patterns of floral composition within environments. For certain organ systems, quantitative estimates of biophysical performance can be made on the basis of structures preserved in the fossil record. Performance estimates for plants separated in time or space can be compared directly. Implicit in different hypotheses of the forces that shape the evolutionary record (e.g. adaptation, mass extinction, rapid environmental change, chance) are predictions about stratigraphic and paleoenvironmental trends in the efficacy of functional performance. Existing data suggest that following the evolution of a significant structural innovation, adaptation for improved functional performance can be a major determinant of evolutionary changes in plants; however, there are structural and development limits to functional improvement, and once these are reached, the structure in question may no longer figure strongly in selection until and unless a new innovation evolves. The Silurian-Devonian paleobotanical record is consistent with the hypothesis that the succession of lowland floodplain dominants preserved in the fossil record of this interval was determined principally by the repeated evolution of new taxa that rose to ecological importance because of competitive advantages conferred by improved biophysical performance. This does not seem to be equally true for Carboniferous-Jurassic dominants of swamp and lowland floodplain environments. In these cases, environmental disruption appears to have been a major factor in shaping the fossil record. This does not mean that continuing adaptation was not important during this interval, but it may indicate that adaptive evolution was strongest in environments other than those best represented in the paleobotanical record.

Adaptation, plant evolution, and the fossil record.

PubMed

Knoll, A H; Niklas, K J

1987-01-01

The importance of adaptation in determining patterns of evolution has become an important focus of debate in evolutionary biology. As it pertains to paleobotany, the issue is whether or not adaptive evolution mediated by natural selection is sufficient to explain the stratigraphic distributions of taxa and character states observed in the plant fossil record. One means of addressing this question is the functional evaluation of stratigraphic series of plant organs set in the context of paleoenvironmental change and temporal patterns of floral composition within environments. For certain organ systems, quantitative estimates of biophysical performance can be made on the basis of structures preserved in the fossil record. Performance estimates for plants separated in time or space can be compared directly. Implicit in different hypotheses of the forces that shape the evolutionary record (e.g. adaptation, mass extinction, rapid environmental change, chance) are predictions about stratigraphic and paleoenvironmental trends in the efficacy of functional performance. Existing data suggest that following the evolution of a significant structural innovation, adaptation for improved functional performance can be a major determinant of evolutionary changes in plants; however, there are structural and development limits to functional improvement, and once these are reached, the structure in question may no longer figure strongly in selection until and unless a new innovation evolves. The Silurian-Devonian paleobotanical record is consistent with the hypothesis that the succession of lowland floodplain dominants preserved in the fossil record of this interval was determined principally by the repeated evolution of new taxa that rose to ecological importance because of competitive advantages conferred by improved biophysical performance. This does not seem to be equally true for Carboniferous-Jurassic dominants of swamp and lowland floodplain environments. In these cases, environmental disruption appears to have been a major factor in shaping the fossil record. This does not mean that continuing adaptation was not important during this interval, but it may indicate that adaptive evolution was strongest in environments other than those best represented in the paleobotanical record.

Error-based analysis of optimal tuning functions explains phenomena observed in sensory neurons.

PubMed

Yaeli, Steve; Meir, Ron

2010-01-01

Biological systems display impressive capabilities in effectively responding to environmental signals in real time. There is increasing evidence that organisms may indeed be employing near optimal Bayesian calculations in their decision-making. An intriguing question relates to the properties of optimal encoding methods, namely determining the properties of neural populations in sensory layers that optimize performance, subject to physiological constraints. Within an ecological theory of neural encoding/decoding, we show that optimal Bayesian performance requires neural adaptation which reflects environmental changes. Specifically, we predict that neuronal tuning functions possess an optimal width, which increases with prior uncertainty and environmental noise, and decreases with the decoding time window. Furthermore, even for static stimuli, we demonstrate that dynamic sensory tuning functions, acting at relatively short time scales, lead to improved performance. Interestingly, the narrowing of tuning functions as a function of time was recently observed in several biological systems. Such results set the stage for a functional theory which may explain the high reliability of sensory systems, and the utility of neuronal adaptation occurring at multiple time scales.

Abrasive slurry jet cutting model based on fuzzy relations

NASA Astrophysics Data System (ADS)

Qiang, C. H.; Guo, C. W.

2017-12-01

The cutting process of pre-mixed abrasive slurry or suspension jet (ASJ) is a complex process affected by many factors, and there is a highly nonlinear relationship between the cutting parameters and cutting quality. In this paper, guided by fuzzy theory, the fuzzy cutting model of ASJ was developed. In the modeling of surface roughness, the upper surface roughness prediction model and the lower surface roughness prediction model were established respectively. The adaptive fuzzy inference system combines the learning mechanism of neural networks and the linguistic reasoning ability of the fuzzy system, membership functions, and fuzzy rules are obtained by adaptive adjustment. Therefore, the modeling process is fast and effective. In this paper, the ANFIS module of MATLAB fuzzy logic toolbox was used to establish the fuzzy cutting model of ASJ, which is found to be quite instrumental to ASJ cutting applications.

Examining the Construct Validity of the MMPI-2-RF Interpersonal Functioning Scales Using the Computerized Adaptive Test of Personality Disorder as a Comparative Framework.

PubMed

Franz, Annabel O; Harrop, Tiffany M; McCord, David M

2017-01-01

This study aimed to examine the construct validity of the Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF) interpersonal functioning scales (Ben-Porath & Tellegen, 2008/2011 ) using as a criterion measure the Computerized Adaptive Test of Personality Disorder-Static Form (CAT-PD-SF; Simms et al., 2011 ). Participants were college students (n = 98) recruited through the university subject pool. A series of a priori hypotheses were developed for each of the 6 interpersonal functioning scales of the MMPI-2-RF, expressed as predicted correlations with construct-relevant CAT-PD-SF scales. Of the 27 specific predictions, 21 were supported by substantial (≥ |.30|) correlations. The MMPI-2-RF Family Problems scale (FML) demonstrated the strongest correlations with CAT-PD-SF scales Anhedonia and Mistrust; Cynicism (RC3) was most highly correlated with Mistrust and Norm Violation; Interpersonal Passivity (IPP) was most highly correlated with Domineering and Rudeness; Social Avoidance (SAV) was most highly correlated with Social Withdrawal and Anhedonia; Shyness (SHY) was most highly correlated with Social Withdrawal and Anxioiusness; and Disaffiliativeness (DSF) was most highly correlated with Emotional Detachment and Mistrust. Results are largely consistent with hypotheses suggesting support for both models of constructs relevant to interpersonal functioning. Future research designed to more precisely differentiate Social Avoidance (SAV) and Shyness (SHY) is suggested.

Do Proxies for the Neurotransmitter Cortisol Predict Adaptation to Life with Chronic Pain?

NASA Astrophysics Data System (ADS)

Deamond, Wade

Among the numerous difficulties encountered by chronic pain patients, impulsive and dysfunctional decision-making complicate their already difficult life situations yet remains relatively understudied. This study examined a recently published neurobiological decision making model that identifies eight specific neurotransmitters and hormones (Dopamine, Testosterone, Endogenous Opioids Glutamate, Serotonin, Norepinephrine, Cortisol, and GABA) linked to unsound decision making related to cognitive, motivational and emotional dysregulation (Nussbaum et al., 2011) (see Appendix 2). The Perceived Stress Scale (PSS), a proxy for the cortisol element in the pharmacological decision making model was analyzed for the neurotransmitter's relationship to functionality and quality of life in a group of 37 chronic pain patients. Participants were comprised of males and females ranging from 23 to 52 years of age and were classified with respect to levels of adjustment to living with chronic pain based on the Quality of Life Scale (QLS), the Dartmouth WONCA COOP Charts and the Global Assessment of Functioning (GAF). The Iowa Gambling Task (IGT) and Frontal System Behavioral Scale (FSBS) measured decision making related to immediate gratification and daily living respectively. Results suggest that emotional dysregulation, as measured by the PSS is a significant predictor for adaptation to life with chronic pain and the PSS is superior to predicting adaptation to life with chronic pain than reported levels of pain as measured by the McGill Pain Questionnaire.

The Yak genome database: an integrative database for studying yak biology and high-altitude adaption

PubMed Central

2012-01-01

Background The yak (Bos grunniens) is a long-haired bovine that lives at high altitudes and is an important source of milk, meat, fiber and fuel. The recent sequencing, assembly and annotation of its genome are expected to further our understanding of the means by which it has adapted to life at high altitudes and its ecologically important traits. Description The Yak Genome Database (YGD) is an internet-based resource that provides access to genomic sequence data and predicted functional information concerning the genes and proteins of Bos grunniens. The curated data stored in the YGD includes genome sequences, predicted genes and associated annotations, non-coding RNA sequences, transposable elements, single nucleotide variants, and three-way whole-genome alignments between human, cattle and yak. YGD offers useful searching and data mining tools, including the ability to search for genes by name or using function keywords as well as GBrowse genome browsers and/or BLAST servers, which can be used to visualize genome regions and identify similar sequences. Sequence data from the YGD can also be downloaded to perform local searches. Conclusions A new yak genome database (YGD) has been developed to facilitate studies on high-altitude adaption and bovine genomics. The database will be continuously updated to incorporate new information such as transcriptome data and population resequencing data. The YGD can be accessed at http://me.lzu.edu.cn/yak. PMID:23134687

Family Perception and 6-Month Symptomatic and Functioning Outcomes in Young Adolescents at Clinical High Risk for Psychosis in a General Population in China.

PubMed

Wang, Lu; Shi, JingYu; Chen, FaZhan; Yao, YuHong; Zhan, ChenYu; Yin, XiaoWen; Fang, XiaoYan; Wang, HaoJie; Yuan, JiaBei; Zhao, XuDong

2015-01-01

Given the difficulty of treating schizophrenia and other forms of psychosis, researchers have shifted focus to early detection and intervention of individuals at clinical high risk (CHR) for psychosis. Previous studies have shown that elements in family functioning could predict symptom outcome in CHR individuals. However, associations between self reported family functioning and symptom or functioning outcome of CHR individuals was rarely reported. Our study aimed to investigate the characteristics and the role of family functioning in the development of CHR individuals among young adolescents. A sample of 32 CHR individuals was recruited from 2800 university students. The characteristics of family perception were evaluated by both Family Assessment Device (FAD) and Family cohesion and adaptability evaluation Scale II (FACES II). 6 month follow up data was available with 25 of the recruited CHR individuals. Baseline socio-demographic characteristics and family functioning were compared between CHR and control group. We also measured the associations between different dimensions of perceived family functioning and both severity of prodromal symptoms and global functioning at baseline and 6-month follow up. CHR individuals showed more maladaptive family functioning compared to control in nearly all of the dimensions of FAD and FACES II except for Affective Involvement. Better Problem Solving and Affective Responsiveness predicted less severe positive and negative symptoms respectively. Family cohesion and adaptability were not only correlated with the baseline severity of general symptoms, but also positively associated with the general and disorganized symptom outcome. This study contributed preliminary evidence towards the associations between family perception and symptom outcome of CHR individuals. It also provided evidence for the importance of family interventions on CHR individuals.

Individual differences in intrinsic brain connectivity predict decision strategy.

PubMed

Barnes, Kelly Anne; Anderson, Kevin M; Plitt, Mark; Martin, Alex

2014-10-15

When humans are provided with ample time to make a decision, individual differences in strategy emerge. Using an adaptation of a well-studied decision making paradigm, motion direction discrimination, we probed the neural basis of individual differences in strategy. We tested whether strategies emerged from moment-to-moment reconfiguration of functional brain networks involved in decision making with task-evoked functional MRI (fMRI) and whether intrinsic properties of functional brain networks, measured at rest with functional connectivity MRI (fcMRI), were associated with strategy use. We found that human participants reliably selected one of two strategies across 2 days of task performance, either continuously accumulating evidence or waiting for task difficulty to decrease. Individual differences in decision strategy were predicted both by the degree of task-evoked activation of decision-related brain regions and by the strength of pretask correlated spontaneous brain activity. These results suggest that spontaneous brain activity constrains strategy selection on perceptual decisions.

Emotion suppression moderates the quadratic association between RSA and executive function

PubMed Central

Spangler, Derek P.; Bell, Martha Ann; Deater-Deckard, Kirby

2016-01-01

There is uncertainty about whether respiratory sinus arrhythmia (RSA), a cardiac marker of adaptive emotion regulation, is involved in relatively low or high executive function performance. In the present study, we investigated: (1) whether RSA during rest and tasks predict both relatively low and high executive function within a larger quadratic association among the two variables, and (2) the extent to which this quadratic trend was moderated by individual differences in emotion regulation. To achieve these aims, a sample of ethnically and socioeconomically diverse women self-reported reappraisal and emotion suppression. They next experienced a two-minute resting period during which ECG was continually assessed. In the next phase, the women completed an array of executive function and non-executive cognitive tasks while ECG was measured throughout. As anticipated, resting RSA showed a quadratic association with executive function that was strongest for high suppression. These results suggest that relatively high resting RSA may predict poor executive function ability when emotion regulation consumes executive control resources needed for ongoing cognitive performance. PMID:26018941

Adaptive estimation of the log fluctuating conductivity from tracer data at the Cape Cod Site

USGS Publications Warehouse

Deng, F.W.; Cushman, J.H.; Delleur, J.W.

1993-01-01

An adaptive estimation scheme is used to obtain the integral scale and variance of the log-fluctuating conductivity at the Cape Cod site based on the fast Fourier transform/stochastic model of Deng et al. (1993) and a Kalmanlike filter. The filter incorporates prior estimates of the unknown parameters with tracer moment data to adaptively obtain improved estimates as the tracer evolves. The results show that significant improvement in the prior estimates of the conductivity can lead to substantial improvement in the ability to predict plume movement. The structure of the covariance function of the log-fluctuating conductivity can be identified from the robustness of the estimation. Both the longitudinal and transverse spatial moment data are important to the estimation.

Adaptive gamma correction-based expert system for nonuniform illumination face enhancement

NASA Astrophysics Data System (ADS)

Abdelhamid, Iratni; Mustapha, Aouache; Adel, Oulefki

2018-03-01

The image quality of a face recognition system suffers under severe lighting conditions. Thus, this study aims to develop an approach for nonuniform illumination adjustment based on an adaptive gamma correction (AdaptGC) filter that can solve the aforementioned issue. An approach for adaptive gain factor prediction was developed via neural network model-based cross-validation (NN-CV). To achieve this objective, a gamma correction function and its effects on the face image quality with different gain values were examined first. Second, an orientation histogram (OH) algorithm was assessed as a face's feature descriptor. Subsequently, a density histogram module was developed for face label generation. During the NN-CV construction, the model was assessed to recognize the OH descriptor and predict the face label. The performance of the NN-CV model was evaluated by examining the statistical measures of root mean square error and coefficient of efficiency. Third, to evaluate the AdaptGC enhancement approach, an image quality metric was adopted using enhancement by entropy, contrast per pixel, second-derivative-like measure of enhancement, and sharpness, then supported by visual inspection. The experiment results were examined using five face's databases, namely, extended Yale-B, Carnegie Mellon University-Pose, Illumination, and Expression, Mobio, FERET, and Oulu-CASIA-NIR-VIS. The final results prove that AdaptGC filter implementation compared with state-of-the-art methods is the best choice in terms of contrast and nonuniform illumination adjustment. In summary, the benefits attained prove that AdaptGC is driven by a profitable enhancement rate, which provides satisfying features for high rate face recognition systems.

Variation in trait trade-offs allows differentiation among predefined plant functional types: implications for predictive ecology.

PubMed

Verheijen, Lieneke M; Aerts, Rien; Bönisch, Gerhard; Kattge, Jens; Van Bodegom, Peter M

2016-01-01

Plant functional types (PFTs) aggregate the variety of plant species into a small number of functionally different classes. We examined to what extent plant traits, which reflect species' functional adaptations, can capture functional differences between predefined PFTs and which traits optimally describe these differences. We applied Gaussian kernel density estimation to determine probability density functions for individual PFTs in an n-dimensional trait space and compared predicted PFTs with observed PFTs. All possible combinations of 1-6 traits from a database with 18 different traits (total of 18 287 species) were tested. A variety of trait sets had approximately similar performance, and 4-5 traits were sufficient to classify up to 85% of the species into PFTs correctly, whereas this was 80% for a bioclimatically defined tree PFT classification. Well-performing trait sets included combinations of correlated traits that are considered functionally redundant within a single plant strategy. This analysis quantitatively demonstrates how structural differences between PFTs are reflected in functional differences described by particular traits. Differentiation between PFTs is possible despite large overlap in plant strategies and traits, showing that PFTs are differently positioned in multidimensional trait space. This study therefore provides the foundation for important applications for predictive ecology. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Predicting ethnic variation in adaptation to later life: styles of socioemotional functioning and constrained heterotypy.

PubMed

Consedine, Nathan S; Magai, Carol; Conway, Francine

2004-06-01

It is an axiom of social gerontology that populations of older individuals become increasingly differentiated as they age. Adaptations to physical and social losses and the increased dependency that typically accompany greater age are likely to be similarly heterogeneous, with different individuals adjusting to the aging process in widely diverse ways. In this paper we consider how individuals with diverse emotional and regulatory profiles, different levels of religiosity, and varied patterns of social relatedness fare as they age. Specifically, we examine the relation between ethnicity and patterns of socioemotional adaptation in a large, ethnically diverse sample (N = 1118) of community-dwelling older adults. Cluster analysis was applied to 11 measures of socioemotional functioning. Ten qualitatively different profiles were extracted and then related to a measure of physical resiliency. Consistent with ethnographic and psychological theory, individuals from different ethnic backgrounds were unevenly distributed across the clusters. Resilient participants of African descent (African Americans, Jamaicans, Trinidadians, Barbadians) were more likely to manifest patterns of adaptation characterized by religious beliefs, while resilient US-born Whites and Immigrant Whites were more likely to be resilient as a result of non-religious social connectedness. Taken together, although these data underscore the diversity of adaptation to later life, we suggest that patterns of successful adaptation vary systematically across ethnic groups. Implications for the continued study of ethnicity in aging and directions for future research are given.

Progress with the lick adaptive optics system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gavel, D T; Olivier, S S; Bauman, B

2000-03-01

Progress and results of observations with the Lick Observatory Laser Guide Star Adaptive Optics System are presented. This system is optimized for diffraction-limited imaging in the near infrared, 1-2 micron wavelength bands. We describe our development efforts in a number of component areas including, a redesign of the optical bench layout, the commissioning of a new infrared science camera, and improvements to the software and user interface. There is also an ongoing effort to characterize the system performance with both natural and laser guide stars and to fold this data into a refined system model. Such a model can bemore » used to help plan future observations, for example, predicting the point-spread function as a function of seeing and guide star magnitude.« less

The vibrational properties of the bee-killer imidacloprid insecticide: A molecular description

NASA Astrophysics Data System (ADS)

Moreira, Antônio A. G.; De Lima-Neto, Pedro; Caetano, Ewerton W. S.; Barroso-Neto, Ito L.; Freire, Valder N.

2017-10-01

The chemical imidacloprid belongs to the neonicotinoids insecticide class, widely used for insect pest control mainly for crop protection. However, imidacloprid is a non-selective agrochemical to the insects and it is able to kill the most important pollinators, the bees. The high toxicity of imidacloprid requires controlled release and continuous monitoring. For this purpose, high performance liquid chromatography (HPLC) is usually employed; infrared and Raman spectroscopy, however, are simple and viable techniques that can be adapted to portable devices for field application. In this communication, state-of-the-art quantum level simulations were used to predict the infrared and Raman spectra of the most stable conformer of imidacloprid. Four molecular geometries were investigated in vacuum and solvated within the Density Functional Theory (DFT) approach employing the hybrid meta functional M06-2X and the hybrid functional B3LYP. The M062X/PCM model proved to be the best to predict structural features, while the values of harmonic vibrational frequencies were predicted more accurately using the B3LYP functional.

Sequential reconstruction of driving-forces from nonlinear nonstationary dynamics

NASA Astrophysics Data System (ADS)

Güntürkün, Ulaş

2010-07-01

This paper describes a functional analysis-based method for the estimation of driving-forces from nonlinear dynamic systems. The driving-forces account for the perturbation inputs induced by the external environment or the secular variations in the internal variables of the system. The proposed algorithm is applicable to the problems for which there is too little or no prior knowledge to build a rigorous mathematical model of the unknown dynamics. We derive the estimator conditioned on the differentiability of the unknown system’s mapping, and smoothness of the driving-force. The proposed algorithm is an adaptive sequential realization of the blind prediction error method, where the basic idea is to predict the observables, and retrieve the driving-force from the prediction error. Our realization of this idea is embodied by predicting the observables one-step into the future using a bank of echo state networks (ESN) in an online fashion, and then extracting the raw estimates from the prediction error and smoothing these estimates in two adaptive filtering stages. The adaptive nature of the algorithm enables to retrieve both slowly and rapidly varying driving-forces accurately, which are illustrated by simulations. Logistic and Moran-Ricker maps are studied in controlled experiments, exemplifying chaotic state and stochastic measurement models. The algorithm is also applied to the estimation of a driving-force from another nonlinear dynamic system that is stochastic in both state and measurement equations. The results are judged by the posterior Cramer-Rao lower bounds. The method is finally put into test on a real-world application; extracting sun’s magnetic flux from the sunspot time series.

Mathematical models of human paralyzed muscle after long-term training.

PubMed

Law, L A Frey; Shields, R K

2007-01-01

Spinal cord injury (SCI) results in major musculoskeletal adaptations, including muscle atrophy, faster contractile properties, increased fatigability, and bone loss. The use of functional electrical stimulation (FES) provides a method to prevent paralyzed muscle adaptations in order to sustain force-generating capacity. Mathematical muscle models may be able to predict optimal activation strategies during FES, however muscle properties further adapt with long-term training. The purpose of this study was to compare the accuracy of three muscle models, one linear and two nonlinear, for predicting paralyzed soleus muscle force after exposure to long-term FES training. Further, we contrasted the findings between the trained and untrained limbs. The three models' parameters were best fit to a single force train in the trained soleus muscle (N=4). Nine additional force trains (test trains) were predicted for each subject using the developed models. Model errors between predicted and experimental force trains were determined, including specific muscle force properties. The mean overall error was greatest for the linear model (15.8%) and least for the nonlinear Hill Huxley type model (7.8%). No significant error differences were observed between the trained versus untrained limbs, although model parameter values were significantly altered with training. This study confirmed that nonlinear models most accurately predict both trained and untrained paralyzed muscle force properties. Moreover, the optimized model parameter values were responsive to the relative physiological state of the paralyzed muscle (trained versus untrained). These findings are relevant for the design and control of neuro-prosthetic devices for those with SCI.

Polar bears exhibit genome-wide signatures of bioenergetic adaptation to life in the arctic environment.

PubMed

Welch, Andreanna J; Bedoya-Reina, Oscar C; Carretero-Paulet, Lorenzo; Miller, Webb; Rode, Karyn D; Lindqvist, Charlotte

2014-02-01

Polar bears (Ursus maritimus) face extremely cold temperatures and periods of fasting, which might result in more severe energetic challenges than those experienced by their sister species, the brown bear (U. arctos). We have examined the mitochondrial and nuclear genomes of polar and brown bears to investigate whether polar bears demonstrate lineage-specific signals of molecular adaptation in genes associated with cellular respiration/energy production. We observed increased evolutionary rates in the mitochondrial cytochrome c oxidase I gene in polar but not brown bears. An amino acid substitution occurred near the interaction site with a nuclear-encoded subunit of the cytochrome c oxidase complex and was predicted to lead to a functional change, although the significance of this remains unclear. The nuclear genomes of brown and polar bears demonstrate different adaptations related to cellular respiration. Analyses of the genomes of brown bears exhibited substitutions that may alter the function of proteins that regulate glucose uptake, which could be beneficial when feeding on carbohydrate-dominated diets during hyperphagia, followed by fasting during hibernation. In polar bears, genes demonstrating signatures of functional divergence and those potentially under positive selection were enriched in functions related to production of nitric oxide (NO), which can regulate energy production in several different ways. This suggests that polar bears may be able to fine-tune intracellular levels of NO as an adaptive response to control trade-offs between energy production in the form of adenosine triphosphate versus generation of heat (thermogenesis).

Polar Bears Exhibit Genome-Wide Signatures of Bioenergetic Adaptation to Life in the Arctic Environment

PubMed Central

Welch, Andreanna J.; Carretero-Paulet, Lorenzo; Miller, Webb; Rode, Karyn D.; Lindqvist, Charlotte

2014-01-01

Polar bears (Ursus maritimus) face extremely cold temperatures and periods of fasting, which might result in more severe energetic challenges than those experienced by their sister species, the brown bear (U. arctos). We have examined the mitochondrial and nuclear genomes of polar and brown bears to investigate whether polar bears demonstrate lineage-specific signals of molecular adaptation in genes associated with cellular respiration/energy production. We observed increased evolutionary rates in the mitochondrial cytochrome c oxidase I gene in polar but not brown bears. An amino acid substitution occurred near the interaction site with a nuclear-encoded subunit of the cytochrome c oxidase complex and was predicted to lead to a functional change, although the significance of this remains unclear. The nuclear genomes of brown and polar bears demonstrate different adaptations related to cellular respiration. Analyses of the genomes of brown bears exhibited substitutions that may alter the function of proteins that regulate glucose uptake, which could be beneficial when feeding on carbohydrate-dominated diets during hyperphagia, followed by fasting during hibernation. In polar bears, genes demonstrating signatures of functional divergence and those potentially under positive selection were enriched in functions related to production of nitric oxide (NO), which can regulate energy production in several different ways. This suggests that polar bears may be able to fine-tune intracellular levels of NO as an adaptive response to control trade-offs between energy production in the form of adenosine triphosphate versus generation of heat (thermogenesis). PMID:24504087

Polar bears exhibit genome-wide signatures of bioenergetic adaptation to life in the Arctic environment

USGS Publications Warehouse

Welch, Andreanna J.; Bedoya-Reina, Oscar C.; Carretero-Paulet, Lorenzo; Miller, Webb; Rode, Karyn D.; Lindqvist, Charlotte

2014-01-01

Polar bears (Ursus maritimus) face extremely cold temperatures and periods of fasting, which might result in more severe energetic challenges than those experienced by their sister species, the brown bear (U. arctos). We have examined the mitochondrial and nuclear genomes of polar and brown bears to investigate if polar bears demonstrate lineage-specific signals of molecular adaptation in genes associated with cellular respiration/energy production. We observed increased evolutionary rates in the mitochondrial cytochrome c oxidase I gene in polar but not brown bears. An amino acid substitution occurred near the interaction site with a nuclear-encoded subunit of the cytochrome c oxidase complex, and was predicted to lead to a functional change, although the significance of this remains unclear. The nuclear genomes of brown and polar bears demonstrate different adaptations related to cellular respiration. Analyses of the genomes of brown bears exhibited substitutions that may alter the function of proteins that regulate glucose uptake, which could be beneficial when feeding on carbohydrate-dominated diets during hyperphagia, followed by fasting during hibernation. In polar bears, genes demonstrating signatures of functional divergence and those potentially under positive selection were enriched in functions related to production of nitric oxide, which can regulate energy production in several different ways. This suggests that polar bears may be able to fine-tune intracellular levels of nitric oxide as an adaptive response to control trade-offs between energy production in the form of ATP versus generation of heat (thermogenesis).

tDCS-induced alterations in GABA concentration within primary motor cortex predict motor learning and motor memory: a 7 T magnetic resonance spectroscopy study.

PubMed

Kim, Soyoung; Stephenson, Mary C; Morris, Peter G; Jackson, Stephen R

2014-10-01

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique that alters cortical excitability in a polarity specific manner and has been shown to influence learning and memory. tDCS may have both on-line and after-effects on learning and memory, and the latter are thought to be based upon tDCS-induced alterations in neurochemistry and synaptic function. We used ultra-high-field (7 T) magnetic resonance spectroscopy (MRS), together with a robotic force adaptation and de-adaptation task, to investigate whether tDCS-induced alterations in GABA and Glutamate within motor cortex predict motor learning and memory. Note that adaptation to a robot-induced force field has long been considered to be a form of model-based learning that is closely associated with the computation and 'supervised' learning of internal 'forward' models within the cerebellum. Importantly, previous studies have shown that on-line tDCS to the cerebellum, but not to motor cortex, enhances model-based motor learning. Here we demonstrate that anodal tDCS delivered to the hand area of the left primary motor cortex induces a significant reduction in GABA concentration. This effect was specific to GABA, localised to the left motor cortex, and was polarity specific insofar as it was not observed following either cathodal or sham stimulation. Importantly, we show that the magnitude of tDCS-induced alterations in GABA concentration within motor cortex predicts individual differences in both motor learning and motor memory on the robotic force adaptation and de-adaptation task. Copyright © 2014. Published by Elsevier Inc.

Estimation and Selection via Absolute Penalized Convex Minimization And Its Multistage Adaptive Applications

PubMed Central

Huang, Jian; Zhang, Cun-Hui

2013-01-01

The ℓ1-penalized method, or the Lasso, has emerged as an important tool for the analysis of large data sets. Many important results have been obtained for the Lasso in linear regression which have led to a deeper understanding of high-dimensional statistical problems. In this article, we consider a class of weighted ℓ1-penalized estimators for convex loss functions of a general form, including the generalized linear models. We study the estimation, prediction, selection and sparsity properties of the weighted ℓ1-penalized estimator in sparse, high-dimensional settings where the number of predictors p can be much larger than the sample size n. Adaptive Lasso is considered as a special case. A multistage method is developed to approximate concave regularized estimation by applying an adaptive Lasso recursively. We provide prediction and estimation oracle inequalities for single- and multi-stage estimators, a general selection consistency theorem, and an upper bound for the dimension of the Lasso estimator. Important models including the linear regression, logistic regression and log-linear models are used throughout to illustrate the applications of the general results. PMID:24348100

A dynamic feedforward neural network based on gaussian particle swarm optimization and its application for predictive control.

PubMed

Han, Min; Fan, Jianchao; Wang, Jun

2011-09-01

A dynamic feedforward neural network (DFNN) is proposed for predictive control, whose adaptive parameters are adjusted by using Gaussian particle swarm optimization (GPSO) in the training process. Adaptive time-delay operators are added in the DFNN to improve its generalization for poorly known nonlinear dynamic systems with long time delays. Furthermore, GPSO adopts a chaotic map with Gaussian function to balance the exploration and exploitation capabilities of particles, which improves the computational efficiency without compromising the performance of the DFNN. The stability of the particle dynamics is analyzed, based on the robust stability theory, without any restrictive assumption. A stability condition for the GPSO+DFNN model is derived, which ensures a satisfactory global search and quick convergence, without the need for gradients. The particle velocity ranges could change adaptively during the optimization process. The results of a comparative study show that the performance of the proposed algorithm can compete with selected algorithms on benchmark problems. Additional simulation results demonstrate the effectiveness and accuracy of the proposed combination algorithm in identifying and controlling nonlinear systems with long time delays.

CRISPR-Cas: evolution of an RNA-based adaptive immunity system in prokaryotes.

PubMed

Koonin, Eugene V; Makarova, Kira S

2013-05-01

The CRISPR-Cas (clustered regularly interspaced short palindromic repeats, CRISPR-associated genes) is an adaptive immunity system in bacteria and archaea that functions via a distinct self-non-self recognition mechanism that is partially analogous to the mechanism of eukaryotic RNA interference (RNAi). The CRISPR-Cas system incorporates fragments of virus or plasmid DNA into the CRISPR repeat cassettes and employs the processed transcripts of these spacers as guide RNAs to cleave the cognate foreign DNA or RNA. The Cas proteins, however, are not homologous to the proteins involved in RNAi and comprise numerous, highly diverged families. The majority of the Cas proteins contain diverse variants of the RNA recognition motif (RRM), a widespread RNA-binding domain. Despite the fast evolution that is typical of the cas genes, the presence of diverse versions of the RRM in most Cas proteins provides for a simple scenario for the evolution of the three distinct types of CRISPR-cas systems. In addition to several proteins that are directly implicated in the immune response, the cas genes encode a variety of proteins that are homologous to prokaryotic toxins that typically possess nuclease activity. The predicted toxins associated with CRISPR-Cas systems include the essential Cas2 protein, proteins of COG1517 that, in addition to a ligand-binding domain and a helix-turn-helix domain, typically contain different nuclease domains and several other predicted nucleases. The tight association of the CRISPR-Cas immunity systems with predicted toxins that, upon activation, would induce dormancy or cell death suggests that adaptive immunity and dormancy/suicide response are functionally coupled. Such coupling could manifest in the persistence state being induced and potentially providing conditions for more effective action of the immune system or in cell death being triggered when immunity fails.

Predicting Differential Item Functioning in Cross-Lingual Testing: The Case of a High Stakes Test in the Kyrgyz Republic

ERIC Educational Resources Information Center

Drummond, Todd W.

2011-01-01

Cross-lingual tests are assessment instruments created in one language and adapted for use with another language group. Practitioners and researchers use cross-lingual tests for various descriptive, analytical and selection purposes both in comparative studies across nations and within countries marked by linguistic diversity (Hambleton, 2005).…

The Developmental Significance of Late Adolescent Substance Use for Early Adult Functioning

ERIC Educational Resources Information Center

Englund, Michelle M.; Siebenbruner, Jessica; Oliva, Elizabeth M.; Egeland, Byron; Chung, Chu-Ting; Long, Jeffrey D.

2013-01-01

This study examines the predictive significance of late adolescent substance use groups (i.e., abstainers, experimental users, at-risk users, and abusers) for early adult adaptation. Participants (N = 159) were drawn from a prospective longitudinal study of first-born children of low-income mothers. At 17.5 years of age, participants were assigned…

Wetland features and landscape context predict the risk of wetland habitat loss

Treesearch

Kevin J. Gutzwiller; Curtis H. Flather

2011-01-01

Wetlands generally provide significant ecosystem services and function as important harbors of biodiversity. To ensure that these habitats are conserved, an efficient means of identifying wetlands at risk of conversion is needed, especially in the southern United States where the rate of wetland loss has been highest in recent decades. We used multivariate adaptive...

Hedgehog signaling mediates adaptive variation in a dynamic functional system in the cichlid feeding apparatus.

PubMed

Hu, Yinan; Albertson, R Craig

2014-06-10

Adaptive variation in the craniofacial skeleton is a key component of resource specialization and habitat divergence in vertebrates, but the proximate genetic mechanisms that underlie complex patterns of craniofacial variation are largely unknown. Here we demonstrate that the Hedgehog (Hh) signaling pathway mediates widespread variation across a complex functional system that affects the kinematics of lower jaw depression--the opercular four-bar linkage apparatus--among Lake Malawi cichlids. By using a combined quantitative trait locus mapping and population genetics approach, we show that allelic variation in the Hh receptor, ptch1, affects the development of distinct bony elements in the head that represent two of three movable links in this functional system. The evolutionarily derived allele is found in species that feed from the water column, and is associated with shifts in anatomy that translate to a four-bar system capable of faster jaw rotation. Alternatively, the ancestral allele is found in species that feed on attached algae, and is associated with the development of a four-bar system that predicts slower jaw movement. Experimental manipulation of the Hh pathway during cichlid development recapitulates functionally salient natural variation in craniofacial geometry. In all, these results significantly extend our understanding of the mechanisms that fine-tune the craniofacial skeletal complex during adaptation to new foraging niches.

Testing the adaptive radiation hypothesis for the lemurs of Madagascar.

PubMed

Herrera, James P

2017-01-01

Lemurs, the diverse, endemic primates of Madagascar, are thought to represent a classic example of adaptive radiation. Based on the most complete phylogeny of living and extinct lemurs yet assembled, I tested predictions of adaptive radiation theory by estimating rates of speciation, extinction and adaptive phenotypic evolution. As predicted, lemur speciation rate exceeded that of their sister clade by nearly twofold, indicating the diversification dynamics of lemurs and mainland relatives may have been decoupled. Lemur diversification rates did not decline over time, however, as predicted by adaptive radiation theory. Optimal body masses diverged among dietary and activity pattern niches as lineages diversified into unique multidimensional ecospace. Based on these results, lemurs only partially fulfil the predictions of adaptive radiation theory, with phenotypic evolution corresponding to an 'early burst' of adaptive differentiation. The results must be interpreted with caution, however, because over the long evolutionary history of lemurs (approx. 50 million years), the 'early burst' signal of adaptive radiation may have been eroded by extinction.

Testing the adaptive radiation hypothesis for the lemurs of Madagascar

PubMed Central

2017-01-01

Lemurs, the diverse, endemic primates of Madagascar, are thought to represent a classic example of adaptive radiation. Based on the most complete phylogeny of living and extinct lemurs yet assembled, I tested predictions of adaptive radiation theory by estimating rates of speciation, extinction and adaptive phenotypic evolution. As predicted, lemur speciation rate exceeded that of their sister clade by nearly twofold, indicating the diversification dynamics of lemurs and mainland relatives may have been decoupled. Lemur diversification rates did not decline over time, however, as predicted by adaptive radiation theory. Optimal body masses diverged among dietary and activity pattern niches as lineages diversified into unique multidimensional ecospace. Based on these results, lemurs only partially fulfil the predictions of adaptive radiation theory, with phenotypic evolution corresponding to an ‘early burst’ of adaptive differentiation. The results must be interpreted with caution, however, because over the long evolutionary history of lemurs (approx. 50 million years), the ‘early burst’ signal of adaptive radiation may have been eroded by extinction. PMID:28280597

Understanding the role of mirror neurons in action understanding will require more than a domain-general account.

PubMed

Martin, Alia; Santos, Laurie R

2014-04-01

Cook et al. propose that mirror neurons emerge developmentally through a domain-general associative mechanism. We argue that experience-sensitivity does not rule out an adaptive or genetic argument for mirror neuron function, and that current evidence suggests that mirror neurons are more specialized than the authors' account would predict. We propose that future work integrate behavioral and neurophysiological techniques used with primates to examine the proposed functions of mirror neurons in action understanding.

Simulating observations with HARMONI: the integral field spectrograph for the European Extremely Large Telescope

NASA Astrophysics Data System (ADS)

Zieleniewski, Simon; Thatte, Niranjan; Kendrew, Sarah; Houghton, Ryan; Tecza, Matthias; Clarke, Fraser; Fusco, Thierry; Swinbank, Mark

2014-07-01

With the next generation of extremely large telescopes commencing construction, there is an urgent need for detailed quantitative predictions of the scientific observations that these new telescopes will enable. Most of these new telescopes will have adaptive optics fully integrated with the telescope itself, allowing unprecedented spatial resolution combined with enormous sensitivity. However, the adaptive optics point spread function will be strongly wavelength dependent, requiring detailed simulations that accurately model these variations. We have developed a simulation pipeline for the HARMONI integral field spectrograph, a first light instrument for the European Extremely Large Telescope. The simulator takes high-resolution input data-cubes of astrophysical objects and processes them with accurate atmospheric, telescope and instrumental effects, to produce mock observed cubes for chosen observing parameters. The output cubes represent the result of a perfect data reduc- tion process, enabling a detailed analysis and comparison between input and output, showcasing HARMONI's capabilities. The simulations utilise a detailed knowledge of the telescope's wavelength dependent adaptive op- tics point spread function. We discuss the simulation pipeline and present an early example of the pipeline functionality for simulating observations of high redshift galaxies.

Adaptive focus for deep tissue using diffuse backscatter

NASA Astrophysics Data System (ADS)

Kress, Jeremy; Pourrezaei, Kambiz

2014-02-01

A system integrating high density diffuse optical imaging with adaptive optics using MEMS for deep tissue interaction is presented. In this system, a laser source is scanned over a high density fiber bundle using Digital Micromirror Device (DMD) and channeled to a tissue phantom. Backscatter is then collected from the tissue phantom by a high density fiber array of different fiber type and channeled to CMOS sensor for image acquisition. Intensity focus is directly verified using a second CMOS sensor which measures intensity transmitted though the tissue phantom. A set of training patterns are displayed on the DMD and backscatter is numerically fit to the transmission intensity. After the training patterns are displayed, adaptive focus is performed using only the backscatter and fitting functions. Additionally, tissue reconstruction and prediction of interference focusing by photoacoustic and optical tomographic methods is discussed. Finally, potential NIR applications such as in-vivo adaptive neural photostimulation and cancer targeting are discussed.

Deep neural network-based domain adaptation for classification of remote sensing images

NASA Astrophysics Data System (ADS)

Ma, Li; Song, Jiazhen

2017-10-01

We investigate the effectiveness of deep neural network for cross-domain classification of remote sensing images in this paper. In the network, class centroid alignment is utilized as a domain adaptation strategy, making the network able to transfer knowledge from the source domain to target domain on a per-class basis. Since predicted labels of target data should be used to estimate the centroid of each class, we use overall centroid alignment as a coarse domain adaptation method to improve the estimation accuracy. In addition, rectified linear unit is used as the activation function to produce sparse features, which may improve the separation capability. The proposed network can provide both aligned features and an adaptive classifier, as well as obtain label-free classification of target domain data. The experimental results using Hyperion, NCALM, and WorldView-2 remote sensing images demonstrated the effectiveness of the proposed approach.

Space adaptation syndrome: multiple etiological factors and individual differences

NASA Technical Reports Server (NTRS)

Lackner, J. R.; DiZio, P.

1991-01-01

Space motion sickness is a significant operational concern in the American and Soviet space programs. Nearly 70% of all astronauts and cosmonauts are affected to some degree during their first several days of flight. It is now beginning to appear that space motion sickness like terrestrial motion sickness is the consequence of multiple etiological factors. As we come to understand basic mechanisms of spatial orientation and sensory-motor adaptation we can begin to predict etiological factors in different motion environments. Individuals vary greatly in the extent to which they are susceptible to these different factors. However, individuals seem to be relatively self-consistent in terms of their rates of adaptation to provocative stimulation and their retention of adaptation. Attempts to relate susceptibility to motion sickness during the microgravity phases of parabolic flight maneuvers to vestibular function under 1G and 0G test conditions are described.

Adaptive Sampling for Urban Air Quality through Participatory Sensing

PubMed Central

Zeng, Yuanyuan; Xiang, Kai

2017-01-01

Air pollution is one of the major problems of the modern world. The popularization and powerful functions of smartphone applications enable people to participate in urban sensing to better know about the air problems surrounding them. Data sampling is one of the most important problems that affect the sensing performance. In this paper, we propose an Adaptive Sampling Scheme for Urban Air Quality (AS-air) through participatory sensing. Firstly, we propose to find the pattern rules of air quality according to the historical data contributed by participants based on Apriori algorithm. Based on it, we predict the on-line air quality and use it to accelerate the learning process to choose and adapt the sampling parameter based on Q-learning. The evaluation results show that AS-air provides an energy-efficient sampling strategy, which is adaptive toward the varied outside air environment with good sampling efficiency. PMID:29099766

Adaptive vehicle motion estimation and prediction

NASA Astrophysics Data System (ADS)

Zhao, Liang; Thorpe, Chuck E.

1999-01-01

Accurate motion estimation and reliable maneuver prediction enable an automated car to react quickly and correctly to the rapid maneuvers of the other vehicles, and so allow safe and efficient navigation. In this paper, we present a car tracking system which provides motion estimation, maneuver prediction and detection of the tracked car. The three strategies employed - adaptive motion modeling, adaptive data sampling, and adaptive model switching probabilities - result in an adaptive interacting multiple model algorithm (AIMM). The experimental results on simulated and real data demonstrate that our tracking system is reliable, flexible, and robust. The adaptive tracking makes the system intelligent and useful in various autonomous driving tasks.

Separate neural mechanisms underlie choices and strategic preferences in risky decision making.

PubMed

Venkatraman, Vinod; Payne, John W; Bettman, James R; Luce, Mary Frances; Huettel, Scott A

2009-05-28

Adaptive decision making in real-world contexts often relies on strategic simplifications of decision problems. Yet, the neural mechanisms that shape these strategies and their implementation remain largely unknown. Using an economic decision-making task, we dissociate brain regions that predict specific choices from those predicting an individual's preferred strategy. Choices that maximized gains or minimized losses were predicted by functional magnetic resonance imaging activation in ventromedial prefrontal cortex or anterior insula, respectively. However, choices that followed a simplifying strategy (i.e., attending to overall probability of winning) were associated with activation in parietal and lateral prefrontal cortices. Dorsomedial prefrontal cortex, through differential functional connectivity with parietal and insular cortex, predicted individual variability in strategic preferences. Finally, we demonstrate that robust decision strategies follow from neural sensitivity to rewards. We conclude that decision making reflects more than compensatory interaction of choice-related regions; in addition, specific brain systems potentiate choices depending on strategies, traits, and context.

Extinction Dynamics and Control in Adaptive Networks

NASA Astrophysics Data System (ADS)

Schwartz, Ira; Shaw, Leah; Hindes, Jason

Disease control is of paramount importance in public health. Moreover, models of disease spread are an important component in implementing effective vaccination and treatment campaigns. However, human behavior in response to an outbreak has only recently been included in epidemic models on networks. Here we develop the mathematical machinery to describe the dynamics of extinction in finite populations that include human adaptive behavior. The formalism enables us to compute the optimal, fluctuation-induced path to extinction, and predict the average extinction time in adaptive networks as a function of the adaptation rate. We find that both observables have several unique scalings depending on the relative speed of infection and adaptivity. Finally, we discuss how the theory can be used to design optimal control programs in general networks, by coupling the effective force of noise with treatment and human behavior. Research supported by U.S. Naval Research Laboratory funding (Grant No. N0001414WX00023) and the Office of Naval Research (Grant No. N0001414WX20610).

Age-Related Changes of Adaptive and Neuropsychological Features in Persons with Down Syndrome

PubMed Central

Ghezzo, Alessandro; Salvioli, Stefano; Solimando, Maria Caterina; Palmieri, Alice; Chiostergi, Chiara; Scurti, Maria; Lomartire, Laura; Bedetti, Federica; Cocchi, Guido; Follo, Daniela; Pipitone, Emanuela; Rovatti, Paolo; Zamberletti, Jessica; Gomiero, Tiziano; Castellani, Gastone; Franceschi, Claudio

2014-01-01

Down Syndrome (DS) is characterised by premature aging and an accelerated decline of cognitive functions in the vast majority of cases. As the life expectancy of DS persons is rapidly increasing, this decline is becoming a dramatic health problem. The aim of this study was to thoroughly evaluate a group of 67 non-demented persons with DS of different ages (11 to 66 years), from a neuropsychological, neuropsychiatric and psychomotor point of view in order to evaluate in a cross-sectional study the age-related adaptive and neuropsychological features, and to possibly identify early signs predictive of cognitive decline. The main finding of this study is that both neuropsychological functions and adaptive skills are lower in adult DS persons over 40 years old, compared to younger ones. In particular, language and short memory skills, frontal lobe functions, visuo-spatial abilities and adaptive behaviour appear to be the more affected domains. A growing deficit in verbal comprehension, along with social isolation, loss of interest and greater fatigue in daily tasks, are the main features found in older, non demented DS persons evaluated in our study. It is proposed that these signs can be alarm bells for incipient dementia, and that neuro-cognitive rehabilitation and psycho-pharmacological interventions must start as soon as the fourth decade (or even earlier) in DS persons, i.e. at an age where interventions can have the greatest efficacy. PMID:25419980

Human spaceflight and space adaptations: Computational simulation of gravitational unloading on the spine

NASA Astrophysics Data System (ADS)

Townsend, Molly T.; Sarigul-Klijn, Nesrin

2018-04-01

Living in reduced gravitational environments for a prolonged duration such, as a fly by mission to Mars or an extended stay at the international space station, affects the human body - in particular, the spine. As the spine adapts to spaceflight, morphological and physiological changes cause the mechanical integrity of the spinal column to be compromised, potentially endangering internal organs, nervous health, and human body mechanical function. Therefore, a high fidelity computational model and simulation of the whole human spine was created and validated for the purpose of investigating the mechanical integrity of the spine in crew members during exploratory space missions. A spaceflight exposed spine has been developed through the adaptation of a three-dimensional nonlinear finite element model with the updated Lagrangian formulation of a healthy ground-based human spine in vivo. Simulation of the porohyperelastic response of the intervertebral disc to mechanical unloading resulted in a model capable of accurately predicting spinal swelling/lengthening, spinal motion, and internal stress distribution. The curvature of this space adaptation exposed spine model was compared to a control terrestrial-based finite element model, indicating how the shape changed. Finally, the potential of injury sites to crew members are predicted for a typical 9 day mission.

Is Linear Displacement Information Or Angular Displacement Information Used During The Adaptation of Pointing Responses To An Optically Shifted Image?

NASA Technical Reports Server (NTRS)

Bautista, Abigail B.

1994-01-01

Twenty-four observers looked through a pair of 20 diopter wedge prisms and pointed to an image of a target which was displaced vertically from eye level by 6 cm at a distance of 30 cm. Observers pointed 40 times, using only their right hand, and received error-corrective feedback upon termination of each pointing response (terminal visual feedback). At three testing distances, 20, 30, and 40 cm, ten pre-exposure and ten post-exposure pointing responses were recorded for each hand as observers reached to a mirror-viewed target located at eye level. The difference between pre- and post-exposure pointing response (adaptive shift) was compared for both Exposed and Unexposed hands across all three testing distances. The data were assessed according to the results predicted by two alternative models for processing spatial-information: one using angular displacement information and another using linear displacement information. The angular model of spatial mapping best predicted the observer's pointing response for the Exposed hand. Although the angular adaptive shift did not change significantly as a function of distance (F(2,44) = 1.12, n.s.), the linear adaptive shift increased significantly over the three testing distances 02 44) = 4.90 p less than 0.01).

Accurately predicting the structure, density, and hydrostatic compression of crystalline β-1,3,5,7-tetranitro-1,3,5,7-tetraazacyclooctane based on its wave-function-based potential

NASA Astrophysics Data System (ADS)

Song, H.-J.; Huang, F.

2011-09-01

A wave-function-based intermolecular potential of the β phase 1,3,5,7-tetranitro-1,3,5,7-tetraazacyclooctane (HMX) molecule has been constructed from first principles using the Williams-Stone-Misquitta method and the symmetry-adapted perturbation theory. Using the potential and its derivatives, we have accurately predicted not only the structure and lattice energy of the crystalline β-HMX at 0 K, but also its densities at temperatures of 0-403 K within an accuracy of 1% of density. The calculated densities at pressures within 0-6 GPa excellently agree with the results from the experiments on hydrostatic compression.

Ventral striatal prediction error signaling is associated with dopamine synthesis capacity and fluid intelligence

PubMed Central

Schlagenhauf, Florian; Rapp, Michael A.; Huys, Quentin J. M.; Beck, Anne; Wüstenberg, Torsten; Deserno, Lorenz; Buchholz, Hans-Georg; Kalbitzer, Jan; Buchert, Ralph; Kienast, Thorsten; Cumming, Paul; Plotkin, Michail; Kumakura, Yoshitaka; Grace, Anthony A.; Dolan, Raymond J.; Heinz, Andreas

2013-01-01

Fluid intelligence represents the capacity for flexible problem solving and rapid behavioral adaptation. Rewards drive flexible behavioral adaptation, in part via a teaching signal expressed as reward prediction errors in the ventral striatum, which has been associated with phasic dopamine release in animal studies. We examined a sample of 28 healthy male adults using multimodal imaging and biological parametric mapping with 1) functional magnetic resonance imaging during a reversal learning task and 2) in a subsample of 17 subjects also with positron emission tomography using 6-[18F]fluoro-L-DOPA to assess dopamine synthesis capacity. Fluid intelligence was measured using a battery of nine standard neuropsychological tests. Ventral striatal BOLD correlates of reward prediction errors were positively correlated with fluid intelligence and, in the right ventral striatum, also inversely correlated with dopamine synthesis capacity (FDOPA Kinapp). When exploring aspects of fluid intelligence, we observed that prediction error signaling correlates with complex attention and reasoning. These findings indicate that individual differences in the capacity for flexible problem solving may be driven by ventral striatal activation during reward-related learning, which in turn proved to be inversely associated with ventral striatal dopamine synthesis capacity. PMID:22344813

Predicting early adolescent gang involvement from middle school adaptation.

PubMed

Dishion, Thomas J; Nelson, Sarah E; Yasui, Miwa

2005-03-01

This study examined the role of adaptation in the first year of middle school (Grade 6, age 11) to affiliation with gangs by the last year of middle school (Grade 8, age 13). The sample consisted of 714 European American (EA) and African American (AA) boys and girls. Specifically, academic grades, reports of antisocial behavior, and peer relations in 6th grade were used to predict multiple measures of gang involvement by 8th grade. The multiple measures of gang involvement included self-, peer, teacher, and counselor reports. Unexpectedly, self-report measures of gang involvement did not correlate highly with peer and school staff reports. The results, however, were similar for other and self-report measures of gang involvement. Mean level analyses revealed statistically reliable differences in 8th-grade gang involvement as a function of the youth gender and ethnicity. Structural equation prediction models revealed that peer nominations of rejection, acceptance, academic failure, and antisocial behavior were predictive of gang involvement for most youth. These findings suggest that the youth level of problem behavior and the school ecology (e.g., peer rejection, school failure) require attention in the design of interventions to prevent the formation of gangs among high-risk young adolescents.

Metabotypes with properly functioning mitochondria and anti-inflammation predict extended productive life span in dairy cows

PubMed Central

Huber, K.; Dänicke, S.; Rehage, J.; Sauerwein, H.; Otto, W.; Rolle-Kampczyk, U.; von Bergen, M.

2016-01-01

The failure to adapt metabolism to the homeorhetic demands of lactation is considered as a main factor in reducing the productive life span of dairy cows. The so far defined markers of production performance and metabolic health in dairy cows do not predict the length of productive life span satisfyingly. This study aimed to identify novel pathways and biomarkers related to productive life in dairy cows by means of (targeted) metabolomics. In a longitudinal study from 42 days before up to 100 days after parturition, we identified metabolites such as long-chain acylcarnitines and biogenic amines associated with extended productive life spans. These metabolites are mainly secreted by the liver and depend on the functionality of hepatic mitochondria. The concentrations of biogenic amines and some acylcarnitines differed already before the onset of lactation thus indicating their predictive potential for continuation or early ending of productive life. PMID:27089826

Metabotypes with properly functioning mitochondria and anti-inflammation predict extended productive life span in dairy cows.

PubMed

Huber, K; Dänicke, S; Rehage, J; Sauerwein, H; Otto, W; Rolle-Kampczyk, U; von Bergen, M

2016-04-19

The failure to adapt metabolism to the homeorhetic demands of lactation is considered as a main factor in reducing the productive life span of dairy cows. The so far defined markers of production performance and metabolic health in dairy cows do not predict the length of productive life span satisfyingly. This study aimed to identify novel pathways and biomarkers related to productive life in dairy cows by means of (targeted) metabolomics. In a longitudinal study from 42 days before up to 100 days after parturition, we identified metabolites such as long-chain acylcarnitines and biogenic amines associated with extended productive life spans. These metabolites are mainly secreted by the liver and depend on the functionality of hepatic mitochondria. The concentrations of biogenic amines and some acylcarnitines differed already before the onset of lactation thus indicating their predictive potential for continuation or early ending of productive life.

Functional connectivity patterns reflect individual differences in conflict adaptation.

PubMed

Wang, Xiangpeng; Wang, Ting; Chen, Zhencai; Hitchman, Glenn; Liu, Yijun; Chen, Antao

2015-04-01

Individuals differ in the ability to utilize previous conflict information to optimize current conflict resolution, which is termed the conflict adaptation effect. Previous studies have linked individual differences in conflict adaptation to distinct brain regions. However, the network-based neural mechanisms subserving the individual differences of the conflict adaptation effect have not been studied. The present study employed a psychophysiological interaction (PPI) analysis with a color-naming Stroop task to examine this issue. The main results were as follows: (1) the anterior cingulate cortex (ACC)-seeded PPI revealed the involvement of the salience network (SN) in conflict adaptation, while the posterior parietal cortex (PPC)-seeded PPI revealed the engagement of the central executive network (CEN). (2) Participants with high conflict adaptation effect showed higher intra-CEN connectivity and lower intra-SN connectivity; while those with low conflict adaptation effect showed higher intra-SN connectivity and lower intra-CEN connectivity. (3) The PPC-centered intra-CEN connectivity positively predicted the conflict adaptation effect; while the ACC-centered intra-SN connectivity had a negative correlation with this effect. In conclusion, our data demonstrated that conflict adaptation is likely supported by the CEN and the SN, providing a new perspective on studying individual differences in conflict adaptation on the basis of large-scale networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

The influence of surround suppression on adaptation effects in primary visual cortex

PubMed Central

Wissig, Stephanie C.

2012-01-01

Adaptation, the prolonged presentation of stimuli, has been used to probe mechanisms of visual processing in physiological, imaging, and perceptual studies. Previous neurophysiological studies have measured adaptation effects by using stimuli tailored to evoke robust responses in individual neurons. This approach provides an incomplete view of how an adapter alters the representation of sensory stimuli by a population of neurons with diverse functional properties. We implanted microelectrode arrays in primary visual cortex (V1) of macaque monkeys and measured orientation tuning and contrast sensitivity in populations of neurons before and after prolonged adaptation. Whereas previous studies in V1 have reported that adaptation causes stimulus-specific suppression of responsivity and repulsive shifts in tuning preference, we have found that adaptation can also lead to response facilitation and shifts in tuning toward the adapter. To explain this range of effects, we have proposed and tested a simple model that employs stimulus-specific suppression in both the receptive field and the spatial surround. The predicted effects on tuning depend on the relative drive provided by the adapter to these two receptive field components. Our data reveal that adaptation can have a much richer repertoire of effects on neuronal responsivity and tuning than previously considered and suggest an intimate mechanistic relationship between spatial and temporal contextual effects. PMID:22423001

ENFIN--A European network for integrative systems biology.

PubMed

Kahlem, Pascal; Clegg, Andrew; Reisinger, Florian; Xenarios, Ioannis; Hermjakob, Henning; Orengo, Christine; Birney, Ewan

2009-11-01

Integration of biological data of various types and the development of adapted bioinformatics tools represent critical objectives to enable research at the systems level. The European Network of Excellence ENFIN is engaged in developing an adapted infrastructure to connect databases, and platforms to enable both the generation of new bioinformatics tools and the experimental validation of computational predictions. With the aim of bridging the gap existing between standard wet laboratories and bioinformatics, the ENFIN Network runs integrative research projects to bring the latest computational techniques to bear directly on questions dedicated to systems biology in the wet laboratory environment. The Network maintains internally close collaboration between experimental and computational research, enabling a permanent cycling of experimental validation and improvement of computational prediction methods. The computational work includes the development of a database infrastructure (EnCORE), bioinformatics analysis methods and a novel platform for protein function analysis FuncNet.

The adaptive safety analysis and monitoring system

NASA Astrophysics Data System (ADS)

Tu, Haiying; Allanach, Jeffrey; Singh, Satnam; Pattipati, Krishna R.; Willett, Peter

2004-09-01

The Adaptive Safety Analysis and Monitoring (ASAM) system is a hybrid model-based software tool for assisting intelligence analysts to identify terrorist threats, to predict possible evolution of the terrorist activities, and to suggest strategies for countering terrorism. The ASAM system provides a distributed processing structure for gathering, sharing, understanding, and using information to assess and predict terrorist network states. In combination with counter-terrorist network models, it can also suggest feasible actions to inhibit potential terrorist threats. In this paper, we will introduce the architecture of the ASAM system, and discuss the hybrid modeling approach embedded in it, viz., Hidden Markov Models (HMMs) to detect and provide soft evidence on the states of terrorist network nodes based on partial and imperfect observations, and Bayesian networks (BNs) to integrate soft evidence from multiple HMMs. The functionality of the ASAM system is illustrated by way of application to the Indian Airlines Hijacking, as modeled from open sources.

Prediction of Tensile Strength of Friction Stir Weld Joints with Adaptive Neuro-Fuzzy Inference System (ANFIS) and Neural Network

NASA Technical Reports Server (NTRS)

Dewan, Mohammad W.; Huggett, Daniel J.; Liao, T. Warren; Wahab, Muhammad A.; Okeil, Ayman M.

2015-01-01

Friction-stir-welding (FSW) is a solid-state joining process where joint properties are dependent on welding process parameters. In the current study three critical process parameters including spindle speed (??), plunge force (????), and welding speed (??) are considered key factors in the determination of ultimate tensile strength (UTS) of welded aluminum alloy joints. A total of 73 weld schedules were welded and tensile properties were subsequently obtained experimentally. It is observed that all three process parameters have direct influence on UTS of the welded joints. Utilizing experimental data, an optimized adaptive neuro-fuzzy inference system (ANFIS) model has been developed to predict UTS of FSW joints. A total of 1200 models were developed by varying the number of membership functions (MFs), type of MFs, and combination of four input variables (??,??,????,??????) utilizing a MATLAB platform. Note EFI denotes an empirical force index derived from the three process parameters. For comparison, optimized artificial neural network (ANN) models were also developed to predict UTS from FSW process parameters. By comparing ANFIS and ANN predicted results, it was found that optimized ANFIS models provide better results than ANN. This newly developed best ANFIS model could be utilized for prediction of UTS of FSW joints.

Male partners of women with provoked vestibulodynia: attributions for pain and their implications for dyadic adjustment, sexual satisfaction, and psychological distress.

PubMed

Jodoin, Mélanie; Bergeron, Sophie; Khalifé, Samir; Dupuis, Marie-José; Desrochers, Geneviève; Leclerc, Bianca

2008-12-01

Provoked vestibulodynia is a female genital pain condition that results in sexual dysfunction and impacts negatively on the couple. Although patients' causal attributions have been linked to worse psychosexual outcomes, no study has documented the male partners' perspective of this distressing problem and its potential influence on their psychosexual adaptation. To identify whether male partners' attributions for vestibulodynia are possible predictors of their dyadic adjustment, sexual functioning, sexual satisfaction, and psychological distress, as well as of women's pain and sexual functioning. Thirty-eight women with vestibulodynia first completed measures of pain intensity and sexual functioning. Male partners responded to mailed questionnaires assessing their own attributions for genital pain as well as their psychological distress, relationship adjustment, sexual functioning, and sexual satisfaction. Women completed the McGill-Melzack Pain Questionnaire (MPQ) and the Female Sexual Function Index (FSFI). Attributions of male partners were measured using an adapted version of the Attributional Style Questionnaire (ASQ)-Partner Version. Men also filled out the Brief Symptom Inventory (BSI), the Dyadic Adjustment Scale (DAS), the Sexual History Form (SHF), and the Global Measure of Sexual Satisfaction (GMSEX). All four negative attribution dimensions and higher levels of women's pain intensity successfully predicted increased psychological distress in male partners. Higher levels of both internal and global attributions were associated with men's poorer dyadic adjustment, whereas global and stable attributions were related to their lower sexual satisfaction. Attributions failed to significantly predict sexual functioning in male partners and women's pain and sexual functioning. Evaluation and treatment of sexual pain problems should involve both partners and should explore the role of negative attributions.

Propagation of high-energy laser beams through the earth's atmosphere II; Proceedings of the Meeting, Los Angeles, CA, Jan. 21-23, 1991

NASA Technical Reports Server (NTRS)

Ulrich, Peter B. (Editor); Wilson, Leroy E. (Editor)

1991-01-01

Consideration is given to turbulence at the inner scale, modeling turbulent transport in laser beam propagation, variable wind direction effects on thermal blooming correction, realistic wind effects on turbulence and thermal blooming compensation, wide bandwidth spectral measurements of atmospheric tilt turbulence, remote alignment of adaptive optical systems with far-field optimization, focusing infrared laser beams on targets in space without using adaptive optics, and a simplex optimization method for adaptive optics system alignment. Consideration is also given to ground-to-space multiline propagation at 1.3 micron, a path integral approach to thermal blooming, functional reconstruction predictions of uplink whole beam Strehl ratios in the presence of thermal blooming, and stability analysis of semidiscrete schemes for thermal blooming computation.

Clinical and genetic correlates of decision making in anorexia nervosa.

PubMed

Tenconi, Elena; Degortes, Daniela; Clementi, Maurizio; Collantoni, Enrico; Pinato, Claudia; Forzan, Monica; Cassina, Matteo; Santonastaso, Paolo; Favaro, Angela

2016-01-01

Decision-making (DM) abilities have been found to be impaired in anorexia nervosa (AN), but few data are available about the characteristics and correlates of this cognitive function. The aim of the present study was to provide data on DM functioning in AN using both veridical and adaptive paradigms. While in veridical DM tasks, the individual's ability to predict a true/false response is measured, adaptive DM is the ability to consider both internal and external demands in order to make a good choice, in the absence of a single true "correct" answer. The participants were 189 women, of whom 91 were eating-disordered patients with a lifetime diagnosis of anorexia nervosa, and 98 were healthy women. All the participants underwent clinical, neuropsychological, and genetic assessment. The cognitive evaluation included a set of neuropsychological tasks and two decision-making tests: The Iowa Gambling Task and the Cognitive Bias Task. Anorexia nervosa patients showed significantly poorer performances on both decision-making tasks than healthy women. The Cognitive Bias Task revealed that anorexia nervosa patients employed significantly more context-independent decision-making strategies, which were independent from diagnostic subtype, handedness, education, and psychopathology. In the whole sample (patients and controls), Cognitive Bias Task performance was independently predicted by lifetime anorexia nervosa diagnosis, body mass index at assessment, and 5-HTTLPR genotype. Patients displayed poor decision-making functioning in both veridical and adaptive situations. The difficulties detected in anorexia nervosa individuals may affect not only the ability to consider the future outcomes of their actions (leading to "myopia for the future"), but also the capacity to update and review one's own mindset according to new environmental stimuli.

Application of Avco data analysis and prediction techniques (ADAPT) to prediction of sunspot activity

NASA Technical Reports Server (NTRS)

Hunter, H. E.; Amato, R. A.

1972-01-01

The results are presented of the application of Avco Data Analysis and Prediction Techniques (ADAPT) to derivation of new algorithms for the prediction of future sunspot activity. The ADAPT derived algorithms show a factor of 2 to 3 reduction in the expected 2-sigma errors in the estimates of the 81-day running average of the Zurich sunspot numbers. The report presents: (1) the best estimates for sunspot cycles 20 and 21, (2) a comparison of the ADAPT performance with conventional techniques, and (3) specific approaches to further reduction in the errors of estimated sunspot activity and to recovery of earlier sunspot historical data. The ADAPT programs are used both to derive regression algorithm for prediction of the entire 11-year sunspot cycle from the preceding two cycles and to derive extrapolation algorithms for extrapolating a given sunspot cycle based on any available portion of the cycle.

Minimizing the effect of process mismatch in a neuromorphic system using spike-timing-dependent adaptation.

PubMed

Cameron, Katherine; Murray, Alan

2008-05-01

This paper investigates whether spike-timing-dependent plasticity (STDP) can minimize the effect of mismatch within the context of a depth-from-motion algorithm. To improve noise rejection, this algorithm contains a spike prediction element, whose performance is degraded by analog very large scale integration (VLSI) mismatch. The error between the actual spike arrival time and the prediction is used as the input to an STDP circuit, to improve future predictions. Before STDP adaptation, the error reflects the degree of mismatch within the prediction circuitry. After STDP adaptation, the error indicates to what extent the adaptive circuitry can minimize the effect of transistor mismatch. The circuitry is tested with static and varying prediction times and chip results are presented. The effect of noisy spikes is also investigated. Under all conditions the STDP adaptation is shown to improve performance.

Data-Based Predictive Control with Multirate Prediction Step

NASA Technical Reports Server (NTRS)

Barlow, Jonathan S.

2010-01-01

Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

Predicting Social and Communicative Ability in School-Age Children with Autism Spectrum Disorder: A Pilot Study of the Social Attribution Task, Multiple Choice

ERIC Educational Resources Information Center

Burger-Caplan, Rebecca; Saulnier, Celine; Jones, Warren; Klin, Ami

2016-01-01

The Social Attribution Task, Multiple Choice is introduced as a measure of implicit social cognitive ability in children, addressing a key challenge in quantification of social cognitive function in autism spectrum disorder, whereby individuals can often be successful in explicit social scenarios, despite marked social adaptive deficits. The…

Age of First Words Predicts Cognitive Ability and Adaptive Skills in Children with ASD

ERIC Educational Resources Information Center

Mayo, Jessica; Chlebowski, Colby; Fein, Deborah A.; Eigsti, Inge-Marie

2013-01-01

Acquiring useful language by age 5 has been identified as a strong predictor of positive outcomes in individuals with Autism Spectrum Disorders (ASD). This study examined the relationship between age of language acquisition and later functioning in children with ASD (n = 119). First word acquisition at a range of ages was probed for its…

You Get What You Get and You Don't Throw a Fit!: Emotion Socialization and Child Physiology Jointly Predict Early Prosocial Development

ERIC Educational Resources Information Center

Scrimgeour, Meghan B.; Davis, Elizabeth L.; Buss, Kristin A.

2016-01-01

Prosocial behavior in early childhood is a precursor to later adaptive social functioning. This investigation leveraged mother-reported, physiological, and observational data to examine children's prosocial development from age 2 to age 4 (N = 125). Maternal emotion socialization (ES) strategies and children's parasympathetic regulation have each…

Early Antecedents of Social Competence in Elementary School of Later Peer Reputation and Sociometric Status in Dutch Adolescents.

ERIC Educational Resources Information Center

Scholte, Ron H. J.; Haselager, Gerbert J. T.; van Aken, Marcel A. G.; van Lieshout, Cornelis F. M.

Noting that a child's peer competence and sociometric status not only are important indices of the child's current social functioning, but may also predict adolescent adaptation, this study examined the antecedents in peer competence and sociometric status in early and late elementary school years of five peer reputation dimensions. These five…

Dimensional Structure of the Autism Phenotype: Relations between Early Development and Current Presentation

ERIC Educational Resources Information Center

Kamp-Becker, Inge; Ghahreman, Mardjan; Smidt, Judith; Remschmidt, Helmut

2009-01-01

The dimensional structure of higher functioning autism phenotype was investigated by factor analysis. The goal of this study was to identify the degree to which early symptoms of autism (measured using the ADI-R) could be predictive of the current symptoms of autism as identified using the ADOS, the adaptive behavior scales, IQ scores and theory…

A tissue adaptation model based on strain-dependent collagen degradation and contact-guided cell traction.

PubMed

Heck, T A M; Wilson, W; Foolen, J; Cilingir, A C; Ito, K; van Donkelaar, C C

2015-03-18

Soft biological tissues adapt their collagen network to the mechanical environment. Collagen remodeling and cell traction are both involved in this process. The present study presents a collagen adaptation model which includes strain-dependent collagen degradation and contact-guided cell traction. Cell traction is determined by the prevailing collagen structure and is assumed to strive for tensional homeostasis. In addition, collagen is assumed to mechanically fail if it is over-strained. Care is taken to use principally measurable and physiologically meaningful relationships. This model is implemented in a fibril-reinforced biphasic finite element model for soft hydrated tissues. The versatility and limitations of the model are demonstrated by corroborating the predicted transient and equilibrium collagen adaptation under distinct mechanical constraints against experimental observations from the literature. These experiments include overloading of pericardium explants until failure, static uniaxial and biaxial loading of cell-seeded gels in vitro and shortening of periosteum explants. In addition, remodeling under hypothetical conditions is explored to demonstrate how collagen might adapt to small differences in constraints. Typical aspects of all essentially different experimental conditions are captured quantitatively or qualitatively. Differences between predictions and experiments as well as new insights that emerge from the present simulations are discussed. This model is anticipated to evolve into a mechanistic description of collagen adaptation, which may assist in developing load-regimes for functional tissue engineered constructs, or may be employed to improve our understanding of the mechanisms behind physiological and pathological collagen remodeling. Copyright © 2014 Elsevier Ltd. All rights reserved.

Diagnosis and subtypes of adolescent antisocial personality disorder.

PubMed

Jones, Meredith; Westen, Drew

2010-04-01

The present study examined the application of the Antisocial Personality Disorder (APD) diagnosis to adolescents and investigated the possibility of subtypes of APD adolescents. As part of a broader study of adolescent personality in clinically-referred patients, experienced clinicians provided personality data on a randomly selected patient in their care using the SWAP-II-A personality pathology instrument. Three hundred thirteen adolescents met adult DSM-IV diagnostic criteria for APD. To characterize adolescents with the disorder, we aggregated the data to identify the items most descriptive and distinctive of APD adolescents relative to other teenagers in the sample (N = 950). Q-factor analysis identified five personality subtypes: psychopathic-like, socially withdrawn, impulsive-histrionic, emotionally dysregulated, and attentionally dysregulated. The five subtypes differed in predictable ways on a set of external criteria related to global adaptive functioning, childhood family environment, and family history of psychiatric illness. Both the APD diagnosis and the empirically derived APD subtypes provided incremental validity over and above the DSM-IV disruptive behavior disorders in predicting global adaptive functioning, number of arrests, early-onset severe externalizing pathology, and quality of peer relationships. Although preliminary, these results provide support for the use of both APD and personality-based subtyping systems in adolescents.

Transfer of adaptation reveals shared mechanism in grasping and manual estimation.

PubMed

Cesanek, Evan; Domini, Fulvio

2018-06-19

An influential idea in cognitive neuroscience is that perception and action are highly separable brain functions, implemented in distinct neural systems. In particular, this theory predicts that the functional distinction between grasping, a skilled action, and manual estimation, a type of perceptual report, should be mirrored by a split between their respective control systems. This idea has received support from a variety of dissociations, yet many of these findings have been criticized for failing to pinpoint the source of the dissociation. In this study, we devised a novel approach to this question, first targeting specific grasp control mechanisms through visuomotor adaptation, then testing whether adapted mechanisms were also involved in manual estimation - a response widely characterized as perceptual in function. Participants grasped objects in virtual reality that could appear larger or smaller than the actual physical sizes felt at the end of each grasp. After brief exposure to a size perturbation, manual estimates were biased in the same direction as the maximum grip apertures of grasping movements, indicating that the adapted mechanism is active in both tasks, regardless of the perception-action distinction. Additional experiments showed that the transfer effect generalizes broadly over space (Exp. 1B) and does not appear to arise from a change in visual perception (Exp. 2). We discuss two adaptable mechanisms that could have mediated the observed effect: (a) an afferent proprioceptive mechanism for sensing grip shape; and (b) an efferent visuomotor transformation of size information into a grip-shaping motor command. Copyright © 2018. Published by Elsevier Ltd.

Eye-pupil displacement and prediction: effects on residual wavefront in adaptive optics retinal imaging

PubMed Central

Kulcsár, Caroline; Raynaud, Henri-François; Garcia-Rissmann, Aurea

2016-01-01

This paper studies the effect of pupil displacements on the best achievable performance of retinal imaging adaptive optics (AO) systems, using 52 trajectories of horizontal and vertical displacements sampled at 80 Hz by a pupil tracker (PT) device on 13 different subjects. This effect is quantified in the form of minimal root mean square (rms) of the residual phase affecting image formation, as a function of the delay between PT measurement and wavefront correction. It is shown that simple dynamic models identified from data can be used to predict horizontal and vertical pupil displacements with greater accuracy (in terms of average rms) over short-term time horizons. The potential impact of these improvements on residual wavefront rms is investigated. These results allow to quantify the part of disturbances corrected by retinal imaging systems that are caused by relative displacements of an otherwise fixed or slowy-varying subject-dependent aberration. They also suggest that prediction has a limited impact on wavefront rms and that taking into account PT measurements in real time improves the performance of AO retinal imaging systems. PMID:27231607

Applications of Displacement Transfer Functions to Deformed Shape Predictions of the G-III Swept-Wing Structure

NASA Technical Reports Server (NTRS)

Lung, Shun-Fat; Ko, William L.

2016-01-01

In support of the Adaptive Compliant Trailing Edge [ACTE] project at the NASA Armstrong Flight Research Center, displacement transfer functions were applied to the swept wing of a Gulfstream G-III airplane (Gulfstream Aerospace Corporation, Savannah, Georgia) to obtain deformed shape predictions. Four strainsensing lines (two on the lower surface, two on the upper surface) were used to calculate the deformed shape of the G III wing under bending and torsion. There being an insufficient number of surface strain sensors, the existing G III wing box finite element model was used to generate simulated surface strains for input to the displacement transfer functions. The resulting predicted deflections have good correlation with the finite-element generated deflections as well as the measured deflections from the ground load calibration test. The convergence study showed that the displacement prediction error at the G III wing tip can be reduced by increasing the number of strain stations (for each strain-sensing line) down to a minimum error of l.6 percent at 17 strain stations; using more than 17 strain stations yielded no benefit because the error slightly increased to 1.9% when 32 strain stations were used.

Control, Filtering and Prediction for Phased Arrays in Directed Energy Systems

DTIC Science & Technology

2016-04-30

adaptive optics. 15. SUBJECT TERMS control, filtering, prediction, system identification, adaptive optics, laser beam pointing, target tracking, phase... laser beam control; furthermore, wavefront sensors are plagued by the difficulty of maintaining the required alignment and focusing in dynamic mission...developed new methods for filtering, prediction and system identification in adaptive optics for high energy laser systems including phased arrays. The

Questions regarding the predictive value of one evolved complex adaptive system for a second: exemplified by the SOD1 mouse.

PubMed

Greek, Ray; Hansen, Lawrence A

2013-11-01

We surveyed the scientific literature regarding amyotrophic lateral sclerosis, the SOD1 mouse model, complex adaptive systems, evolution, drug development, animal models, and philosophy of science in an attempt to analyze the SOD1 mouse model of amyotrophic lateral sclerosis in the context of evolved complex adaptive systems. Humans and animals are examples of evolved complex adaptive systems. It is difficult to predict the outcome from perturbations to such systems because of the characteristics of complex systems. Modeling even one complex adaptive system in order to predict outcomes from perturbations is difficult. Predicting outcomes to one evolved complex adaptive system based on outcomes from a second, especially when the perturbation occurs at higher levels of organization, is even more problematic. Using animal models to predict human outcomes to perturbations such as disease and drugs should have a very low predictive value. We present empirical evidence confirming this and suggest a theory to explain this phenomenon. We analyze the SOD1 mouse model of amyotrophic lateral sclerosis in order to illustrate this position. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Developing Tests of Visual Dependency

NASA Technical Reports Server (NTRS)

Kindrat, Alexandra N.

2011-01-01

Astronauts develop neural adaptive responses to microgravity during space flight. Consequently these adaptive responses cause maladaptive disturbances in balance and gait function when astronauts return to Earth and are re-exposed to gravity. Current research in the Neuroscience Laboratories at NASA-JSC is focused on understanding how exposure to space flight produces post-flight disturbances in balance and gait control and developing training programs designed to facilitate the rapid recovery of functional mobility after space flight. In concert with these disturbances, astronauts also often report an increase in their visual dependency during space flight. To better understand this phenomenon, studies were conducted with specially designed training programs focusing on visual dependency with the aim to understand and enhance subjects ability to rapidly adapt to novel sensory situations. The Rod and Frame test (RFT) was used first to assess an individual s visual dependency, using a variety of testing techniques. Once assessed, subjects were asked to perform two novel tasks under transformation (both the Pegboard and Cube Construction tasks). Results indicate that head position cues and initial visual test conditions had no effect on an individual s visual dependency scores. Subjects were also able to adapt to the manual tasks after several trials. Individual visual dependency correlated with ability to adapt manual to a novel visual distortion only for the cube task. Subjects with higher visual dependency showed decreased ability to adapt to this task. Ultimately, it was revealed that the RFT may serve as an effective prediction tool to produce individualized adaptability training prescriptions that target the specific sensory profile of each crewmember.

Rational metareasoning and the plasticity of cognitive control.

PubMed

Lieder, Falk; Shenhav, Amitai; Musslick, Sebastian; Griffiths, Thomas L

2018-04-01

The human brain has the impressive capacity to adapt how it processes information to high-level goals. While it is known that these cognitive control skills are malleable and can be improved through training, the underlying plasticity mechanisms are not well understood. Here, we develop and evaluate a model of how people learn when to exert cognitive control, which controlled process to use, and how much effort to exert. We derive this model from a general theory according to which the function of cognitive control is to select and configure neural pathways so as to make optimal use of finite time and limited computational resources. The central idea of our Learned Value of Control model is that people use reinforcement learning to predict the value of candidate control signals of different types and intensities based on stimulus features. This model correctly predicts the learning and transfer effects underlying the adaptive control-demanding behavior observed in an experiment on visual attention and four experiments on interference control in Stroop and Flanker paradigms. Moreover, our model explained these findings significantly better than an associative learning model and a Win-Stay Lose-Shift model. Our findings elucidate how learning and experience might shape people's ability and propensity to adaptively control their minds and behavior. We conclude by predicting under which circumstances these learning mechanisms might lead to self-control failure.

Rational metareasoning and the plasticity of cognitive control

PubMed Central

Shenhav, Amitai; Musslick, Sebastian; Griffiths, Thomas L.

2018-01-01

The human brain has the impressive capacity to adapt how it processes information to high-level goals. While it is known that these cognitive control skills are malleable and can be improved through training, the underlying plasticity mechanisms are not well understood. Here, we develop and evaluate a model of how people learn when to exert cognitive control, which controlled process to use, and how much effort to exert. We derive this model from a general theory according to which the function of cognitive control is to select and configure neural pathways so as to make optimal use of finite time and limited computational resources. The central idea of our Learned Value of Control model is that people use reinforcement learning to predict the value of candidate control signals of different types and intensities based on stimulus features. This model correctly predicts the learning and transfer effects underlying the adaptive control-demanding behavior observed in an experiment on visual attention and four experiments on interference control in Stroop and Flanker paradigms. Moreover, our model explained these findings significantly better than an associative learning model and a Win-Stay Lose-Shift model. Our findings elucidate how learning and experience might shape people’s ability and propensity to adaptively control their minds and behavior. We conclude by predicting under which circumstances these learning mechanisms might lead to self-control failure. PMID:29694347

Predictive Control of Speededness in Adaptive Testing

ERIC Educational Resources Information Center

van der Linden, Wim J.

2009-01-01

An adaptive testing method is presented that controls the speededness of a test using predictions of the test takers' response times on the candidate items in the pool. Two different types of predictions are investigated: posterior predictions given the actual response times on the items already administered and posterior predictions that use the…

When everything is not everywhere but species evolve: an alternative method to model adaptive properties of marine ecosystems

PubMed Central

Sauterey, Boris; Ward, Ben A.; Follows, Michael J.; Bowler, Chris; Claessen, David

2015-01-01

The functional and taxonomic biogeography of marine microbial systems reflects the current state of an evolving system. Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle. Here, we investigate the evolutionary adaptive potential of marine microbial systems under environmental change and introduce explicit Darwinian adaptation into an ocean modelling framework, simulating evolving phytoplankton communities in space and time. To this end, we adopt tools from adaptive dynamics theory, evaluating the fitness of invading mutants over annual timescales, replacing the resident if a fitter mutant arises. Using the evolutionary framework, we examine how community assembly, specifically the emergence of phytoplankton cell size diversity, reflects the combined effects of bottom-up and top-down controls. When compared with a species-selection approach, based on the paradigm that “Everything is everywhere, but the environment selects”, we show that (i) the selected optimal trait values are similar; (ii) the patterns emerging from the adaptive model are more robust, but (iii) the two methods lead to different predictions in terms of emergent diversity. We demonstrate that explicitly evolutionary approaches to modelling marine microbial populations and functionality are feasible and practical in time-varying, space-resolving settings and provide a new tool for exploring evolutionary interactions on a range of timescales in the ocean. PMID:25852217

When everything is not everywhere but species evolve: an alternative method to model adaptive properties of marine ecosystems.

PubMed

Sauterey, Boris; Ward, Ben A; Follows, Michael J; Bowler, Chris; Claessen, David

2015-01-01

The functional and taxonomic biogeography of marine microbial systems reflects the current state of an evolving system. Current models of marine microbial systems and biogeochemical cycles do not reflect this fundamental organizing principle. Here, we investigate the evolutionary adaptive potential of marine microbial systems under environmental change and introduce explicit Darwinian adaptation into an ocean modelling framework, simulating evolving phytoplankton communities in space and time. To this end, we adopt tools from adaptive dynamics theory, evaluating the fitness of invading mutants over annual timescales, replacing the resident if a fitter mutant arises. Using the evolutionary framework, we examine how community assembly, specifically the emergence of phytoplankton cell size diversity, reflects the combined effects of bottom-up and top-down controls. When compared with a species-selection approach, based on the paradigm that "Everything is everywhere, but the environment selects", we show that (i) the selected optimal trait values are similar; (ii) the patterns emerging from the adaptive model are more robust, but (iii) the two methods lead to different predictions in terms of emergent diversity. We demonstrate that explicitly evolutionary approaches to modelling marine microbial populations and functionality are feasible and practical in time-varying, space-resolving settings and provide a new tool for exploring evolutionary interactions on a range of timescales in the ocean.

Conservatism and Adaptability during Squirrel Radiation: What Is Mandible Shape Telling Us?

PubMed Central

Casanovas-Vilar, Isaac; van Dam, Jan

2013-01-01

Both functional adaptation and phylogeny shape the morphology of taxa within clades. Herein we explore these two factors in an integrated way by analyzing shape and size variation in the mandible of extant squirrels using landmark-based geometric morphometrics in combination with a comparative phylogenetic analysis. Dietary specialization and locomotion were found to be reliable predictors of mandible shape, with the prediction by locomotion probably reflecting the underlying diet. In addition a weak but significant allometric effect could be demonstrated. Our results found a strong phylogenetic signal in the family as a whole as well as in the main clades, which is in agreement with the general notion of squirrels being a conservative group. This fact does not preclude functional explanations for mandible shape, but rather indicates that ancient adaptations kept a prominent role, with most genera having diverged little from their ancestral clade morphologies. Nevertheless, certain groups have evolved conspicuous adaptations that allow them to specialize on unique dietary resources. Such adaptations mostly occurred in the Callosciurinae and probably reflect their radiation into the numerous ecological niches of the tropical and subtropical forests of Southeastern Asia. Our dietary reconstruction for the oldest known fossil squirrels (Eocene, 36 million years ago) show a specialization on nuts and seeds, implying that the development from protrogomorphous to sciuromorphous skulls was not necessarily related to a change in diet. PMID:23593456

The Norwegian Computerized Adaptive Test of Personality Disorder-Static Form (CAT-PD-SF): Reliability, Factor Structure, and Relationships With Personality Functioning.

PubMed

Thimm, Jens C

2017-12-01

The Computerized Adaptive Test of Personality Disorder-Static Form (CAT-PD-SF) is a self-report inventory developed to assess pathological personality traits. The current study explored the reliability and higher order factor structure of the Norwegian version of the CAT-PD-SF and the relationships between the CAT-PD traits and domains of personality functioning in an undergraduate student sample ( N = 375). In addition to the CAT-PD-SF, the short form of the Severity Indices of Personality Problems and the Brief Symptom Inventory were administered. The results showed that the Norwegian CAT-PD-SF has good score reliability. Factor analysis of the CAT-PD-SF scales indicated five superordinate factors that correspond to the trait domains of the alternative DSM-5 model for personality disorders. The CAT-PD traits were highly predictive of impaired personality functioning after controlling for psychological distress. It is concluded that the CAT-PD-SF is a promising tool for the assessment of personality disorder traits.

Assessing the predictive value of a neuropsychological model on concurrent function in acute stroke recovery and rehabilitation.

PubMed

Leitner, Damian; Miller, Harry; Libben, Maya

2018-06-25

Few studies have examined the relationship between cognition and function for acute stroke inpatients utilizing comprehensive methods. This study aimed to assess the relationship of a neuropsychological model, above and beyond a baseline model, with concurrent functional status across multiple domains in the early weeks of stroke recovery and rehabilitation. Seventy-four acute stroke patients were administered a comprehensive neuropsychological assessment. Functional domains of ability, adjustment, and participation were assessed using the Mayo-Portland Adaptability Inventory - 4 (MPAI-4). Hierarchical linear regression was used to assess a neuropsychological model comprised of cognitive tests scores on domains of executive function, memory, and visuospatial-constructional skills (VSC), after accounting for a baseline model comprised of common demographic and stroke variants used to predict outcome. The neuropsychological model was significantly associated, above and beyond the baseline model, with MPAI-4 Ability, Participation, and Total scores (all p-values < .05). The strength of association varied across functional domains. Analyzing tests of executive function, the Color Trails Test-Part 2 predicted MPAI-4 Participation (β = -.46, p = .001), and Total score (β = -.32, p = .02). Neuropsychological assessment contributes independently to the determination of multiple domains of functional function, above and beyond common medical variants of stroke, in the early weeks of recovery and rehabilitation. Multiple tests of executive function are recommended to develop a greater appreciation of a patient's concurrent functional abilities.

Adaptive plasticity in speech perception: Effects of external information and internal predictions.

PubMed

Guediche, Sara; Fiez, Julie A; Holt, Lori L

2016-07-01

When listeners encounter speech under adverse listening conditions, adaptive adjustments in perception can improve comprehension over time. In some cases, these adaptive changes require the presence of external information that disambiguates the distorted speech signals, whereas in other cases mere exposure is sufficient. Both external (e.g., written feedback) and internal (e.g., prior word knowledge) sources of information can be used to generate predictions about the correct mapping of a distorted speech signal. We hypothesize that these predictions provide a basis for determining the discrepancy between the expected and actual speech signal that can be used to guide adaptive changes in perception. This study provides the first empirical investigation that manipulates external and internal factors through (a) the availability of explicit external disambiguating information via the presence or absence of postresponse orthographic information paired with a repetition of the degraded stimulus, and (b) the accuracy of internally generated predictions; an acoustic distortion is introduced either abruptly or incrementally. The results demonstrate that the impact of external information on adaptive plasticity is contingent upon whether the intelligibility of the stimuli permits accurate internally generated predictions during exposure. External information sources enhance adaptive plasticity only when input signals are severely degraded and cannot reliably access internal predictions. This is consistent with a computational framework for adaptive plasticity in which error-driven supervised learning relies on the ability to compute sensory prediction error signals from both internal and external sources of information. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Adaptive plasticity in speech perception: effects of external information and internal predictions

PubMed Central

Guediche, Sara; Fiez, Julie A.; Holt, Lori L.

2016-01-01

When listeners encounter speech under adverse listening conditions, adaptive adjustments in perception can improve comprehension over time. In some cases, these adaptive changes require the presence of external information that disambiguates the distorted speech signals, whereas in other cases mere exposure is sufficient. Both external (e.g. written feedback) and internal (e.g., prior word knowledge) sources of information can be used to generate predictions about the correct mapping of a distorted speech signal. We hypothesize that these predictions provide a basis for determining the discrepancy between the expected and actual speech signal that can be used to guide adaptive changes in perception. This study provides the first empirical investigation that manipulates external and internal factors through 1) the availability of explicit external disambiguating information via the presence or absence of post-response orthographic information paired with a repetition of the degraded stimulus, and 2) the accuracy of internally-generated predictions; an acoustic distortion is introduced either abruptly or incrementally. The results demonstrate that the impact of external information on adaptive plasticity is contingent upon whether the intelligibility of the stimuli permits accurate internally-generated predictions during exposure. External information sources enhance adaptive plasticity only when input signals are severely degraded and cannot reliably access internal predictions. This is consistent with a computational framework for adaptive plasticity in which error-driven supervised learning relies on the ability to compute sensory prediction error signals from both internal and external sources of information. PMID:26854531

Emotion suppression moderates the quadratic association between RSA and executive function.

PubMed

Spangler, Derek P; Bell, Martha Ann; Deater-Deckard, Kirby

2015-09-01

There is uncertainty about whether respiratory sinus arrhythmia (RSA), a cardiac marker of adaptive emotion regulation, is involved in relatively low or high executive function performance. In the present study, we investigated (a) whether RSA during rest and tasks predict both relatively low and high executive function within a larger quadratic association among the two variables, and (b) the extent to which this quadratic trend was moderated by individual differences in emotion regulation. To achieve these aims, a sample of ethnically and socioeconomically diverse women self-reported reappraisal and emotion suppression. They next experienced a 2-min resting period during which electrocardiogram (ECG) was continually assessed. In the next phase, the women completed an array of executive function and nonexecutive cognitive tasks while ECG was measured throughout. As anticipated, resting RSA showed a quadratic association with executive function that was strongest for high suppression. These results suggest that relatively high resting RSA may predict poor executive function ability when emotion regulation consumes executive control resources needed for ongoing cognitive performance. © 2015 Society for Psychophysiological Research.

Research on adaptive optics image restoration algorithm based on improved joint maximum a posteriori method

NASA Astrophysics Data System (ADS)

Zhang, Lijuan; Li, Yang; Wang, Junnan; Liu, Ying

2018-03-01

In this paper, we propose a point spread function (PSF) reconstruction method and joint maximum a posteriori (JMAP) estimation method for the adaptive optics image restoration. Using the JMAP method as the basic principle, we establish the joint log likelihood function of multi-frame adaptive optics (AO) images based on the image Gaussian noise models. To begin with, combining the observed conditions and AO system characteristics, a predicted PSF model for the wavefront phase effect is developed; then, we build up iterative solution formulas of the AO image based on our proposed algorithm, addressing the implementation process of multi-frame AO images joint deconvolution method. We conduct a series of experiments on simulated and real degraded AO images to evaluate our proposed algorithm. Compared with the Wiener iterative blind deconvolution (Wiener-IBD) algorithm and Richardson-Lucy IBD algorithm, our algorithm has better restoration effects including higher peak signal-to-noise ratio ( PSNR) and Laplacian sum ( LS) value than the others. The research results have a certain application values for actual AO image restoration.

Spectral simplicity of apparent complexity. I. The nondiagonalizable metadynamics of prediction

NASA Astrophysics Data System (ADS)

Riechers, Paul M.; Crutchfield, James P.

2018-03-01

Virtually all questions that one can ask about the behavioral and structural complexity of a stochastic process reduce to a linear algebraic framing of a time evolution governed by an appropriate hidden-Markov process generator. Each type of question—correlation, predictability, predictive cost, observer synchronization, and the like—induces a distinct generator class. Answers are then functions of the class-appropriate transition dynamic. Unfortunately, these dynamics are generically nonnormal, nondiagonalizable, singular, and so on. Tractably analyzing these dynamics relies on adapting the recently introduced meromorphic functional calculus, which specifies the spectral decomposition of functions of nondiagonalizable linear operators, even when the function poles and zeros coincide with the operator's spectrum. Along the way, we establish special properties of the spectral projection operators that demonstrate how they capture the organization of subprocesses within a complex system. Circumventing the spurious infinities of alternative calculi, this leads in the sequel, Part II [P. M. Riechers and J. P. Crutchfield, Chaos 28, 033116 (2018)], to the first closed-form expressions for complexity measures, couched either in terms of the Drazin inverse (negative-one power of a singular operator) or the eigenvalues and projection operators of the appropriate transition dynamic.

Machine learning methods enable predictive modeling of antibody feature:function relationships in RV144 vaccinees.

PubMed

Choi, Ickwon; Chung, Amy W; Suscovich, Todd J; Rerks-Ngarm, Supachai; Pitisuttithum, Punnee; Nitayaphan, Sorachai; Kaewkungwal, Jaranit; O'Connell, Robert J; Francis, Donald; Robb, Merlin L; Michael, Nelson L; Kim, Jerome H; Alter, Galit; Ackerman, Margaret E; Bailey-Kellogg, Chris

2015-04-01

The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector cell responses may have been a key mechanism of the protection observed in the RV144 HIV vaccine trial. In an extensive investigation of a rich set of data collected from RV144 vaccine recipients, we here employ machine learning methods to identify and model associations between antibody features (IgG subclass and antigen specificity) and effector function activities (antibody dependent cellular phagocytosis, cellular cytotoxicity, and cytokine release). We demonstrate via cross-validation that classification and regression approaches can effectively use the antibody features to robustly predict qualitative and quantitative functional outcomes. This integration of antibody feature and function data within a machine learning framework provides a new, objective approach to discovering and assessing multivariate immune correlates.

The limits of a limited future time perspective in explaining age differences in emotional functioning.

PubMed

Grühn, Daniel; Sharifian, Neika; Chu, Qiao

2016-09-01

Although a limited future time perspective (FTP) has been theorized to be the underlying mechanism of positive emotional functioning later in life, there is scant empirical evidence for this position. Using an integrative data-analytic approach, we investigated the predictive value of FTP, age, and subjective health in explaining emotional functioning in a sample of 2,504 adults (17 to 87 years, M = 35.5, SD = 14.2). Although older adults reported a more limited FTP than younger adults, age and a limited FTP had opposite effects in predicting subjective well-being, affect, positive emotions, empathy, and attitudes toward emotions. That is, old age was linked to a more adaptive emotional profile, whereas a limited FTP was linked to a more maladaptive emotional profile. This was the case even after controlling for health-related aspects. The findings question the usage of FTP as an explanatory variable for observed age differences in emotional functioning. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Machine Learning Methods Enable Predictive Modeling of Antibody Feature:Function Relationships in RV144 Vaccinees

PubMed Central

Choi, Ickwon; Chung, Amy W.; Suscovich, Todd J.; Rerks-Ngarm, Supachai; Pitisuttithum, Punnee; Nitayaphan, Sorachai; Kaewkungwal, Jaranit; O'Connell, Robert J.; Francis, Donald; Robb, Merlin L.; Michael, Nelson L.; Kim, Jerome H.; Alter, Galit; Ackerman, Margaret E.; Bailey-Kellogg, Chris

2015-01-01

The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector cell responses may have been a key mechanism of the protection observed in the RV144 HIV vaccine trial. In an extensive investigation of a rich set of data collected from RV144 vaccine recipients, we here employ machine learning methods to identify and model associations between antibody features (IgG subclass and antigen specificity) and effector function activities (antibody dependent cellular phagocytosis, cellular cytotoxicity, and cytokine release). We demonstrate via cross-validation that classification and regression approaches can effectively use the antibody features to robustly predict qualitative and quantitative functional outcomes. This integration of antibody feature and function data within a machine learning framework provides a new, objective approach to discovering and assessing multivariate immune correlates. PMID:25874406

Towards Engineering Biological Systems in a Broader Context.

PubMed

Venturelli, Ophelia S; Egbert, Robert G; Arkin, Adam P

2016-02-27

Significant advances have been made in synthetic biology to program information processing capabilities in cells. While these designs can function predictably in controlled laboratory environments, the reliability of these devices in complex, temporally changing environments has not yet been characterized. As human society faces global challenges in agriculture, human health and energy, synthetic biology should develop predictive design principles for biological systems operating in complex environments. Natural biological systems have evolved mechanisms to overcome innumerable and diverse environmental challenges. Evolutionary design rules should be extracted and adapted to engineer stable and predictable ecological function. We highlight examples of natural biological responses spanning the cellular, population and microbial community levels that show promise in synthetic biology contexts. We argue that synthetic circuits embedded in host organisms or designed ecologies informed by suitable measurement of biotic and abiotic environmental parameters could be used as engineering substrates to achieve target functions in complex environments. Successful implementation of these methods will broaden the context in which synthetic biological systems can be applied to solve important problems. Copyright © 2015 Elsevier Ltd. All rights reserved.

Genes under positive selection in a model plant pathogenic fungus, Botrytis.

PubMed

Aguileta, Gabriela; Lengelle, Juliette; Chiapello, Hélène; Giraud, Tatiana; Viaud, Muriel; Fournier, Elisabeth; Rodolphe, François; Marthey, Sylvain; Ducasse, Aurélie; Gendrault, Annie; Poulain, Julie; Wincker, Patrick; Gout, Lilian

2012-07-01

The rapid evolution of particular genes is essential for the adaptation of pathogens to new hosts and new environments. Powerful methods have been developed for detecting targets of selection in the genome. Here we used divergence data to compare genes among four closely related fungal pathogens adapted to different hosts to elucidate the functions putatively involved in adaptive processes. For this goal, ESTs were sequenced in the specialist fungal pathogens Botrytis tulipae and Botrytis ficariarum, and compared with genome sequences of Botrytis cinerea and Sclerotinia sclerotiorum, responsible for diseases on over 200 plant species. A maximum likelihood-based analysis of 642 predicted orthologs detected 21 genes showing footprints of positive selection. These results were validated by resequencing nine of these genes in additional Botrytis species, showing they have also been rapidly evolving in other related species. Twenty of the 21 genes had not previously been identified as pathogenicity factors in B. cinerea, but some had functions related to plant-fungus interactions. The putative functions were involved in respiratory and energy metabolism, protein and RNA metabolism, signal transduction or virulence, similarly to what was detected in previous studies using the same approach in other pathogens. Mutants of B. cinerea were generated for four of these genes as a first attempt to elucidate their functions. Copyright © 2012 Elsevier B.V. All rights reserved.

Some practical universal noiseless coding techniques, part 3, module PSl14,K+

NASA Technical Reports Server (NTRS)

Rice, Robert F.

1991-01-01

The algorithmic definitions, performance characterizations, and application notes for a high-performance adaptive noiseless coding module are provided. Subsets of these algorithms are currently under development in custom very large scale integration (VLSI) at three NASA centers. The generality of coding algorithms recently reported is extended. The module incorporates a powerful adaptive noiseless coder for Standard Data Sources (i.e., sources whose symbols can be represented by uncorrelated non-negative integers, where smaller integers are more likely than the larger ones). Coders can be specified to provide performance close to the data entropy over any desired dynamic range (of entropy) above 0.75 bit/sample. This is accomplished by adaptively choosing the best of many efficient variable-length coding options to use on each short block of data (e.g., 16 samples) All code options used for entropies above 1.5 bits/sample are 'Huffman Equivalent', but they require no table lookups to implement. The coding can be performed directly on data that have been preprocessed to exhibit the characteristics of a standard source. Alternatively, a built-in predictive preprocessor can be used where applicable. This built-in preprocessor includes the familiar 1-D predictor followed by a function that maps the prediction error sequences into the desired standard form. Additionally, an external prediction can be substituted if desired. A broad range of issues dealing with the interface between the coding module and the data systems it might serve are further addressed. These issues include: multidimensional prediction, archival access, sensor noise, rate control, code rate improvements outside the module, and the optimality of certain internal code options.

Incorporating Midbrain Adaptation to Mean Sound Level Improves Models of Auditory Cortical Processing

PubMed Central

Schoppe, Oliver; King, Andrew J.; Schnupp, Jan W.H.; Harper, Nicol S.

2016-01-01

Adaptation to stimulus statistics, such as the mean level and contrast of recently heard sounds, has been demonstrated at various levels of the auditory pathway. It allows the nervous system to operate over the wide range of intensities and contrasts found in the natural world. Yet current standard models of the response properties of auditory neurons do not incorporate such adaptation. Here we present a model of neural responses in the ferret auditory cortex (the IC Adaptation model), which takes into account adaptation to mean sound level at a lower level of processing: the inferior colliculus (IC). The model performs high-pass filtering with frequency-dependent time constants on the sound spectrogram, followed by half-wave rectification, and passes the output to a standard linear–nonlinear (LN) model. We find that the IC Adaptation model consistently predicts cortical responses better than the standard LN model for a range of synthetic and natural stimuli. The IC Adaptation model introduces no extra free parameters, so it improves predictions without sacrificing parsimony. Furthermore, the time constants of adaptation in the IC appear to be matched to the statistics of natural sounds, suggesting that neurons in the auditory midbrain predict the mean level of future sounds and adapt their responses appropriately. SIGNIFICANCE STATEMENT An ability to accurately predict how sensory neurons respond to novel stimuli is critical if we are to fully characterize their response properties. Attempts to model these responses have had a distinguished history, but it has proven difficult to improve their predictive power significantly beyond that of simple, mostly linear receptive field models. Here we show that auditory cortex receptive field models benefit from a nonlinear preprocessing stage that replicates known adaptation properties of the auditory midbrain. This improves their predictive power across a wide range of stimuli but keeps model complexity low as it introduces no new free parameters. Incorporating the adaptive coding properties of neurons will likely improve receptive field models in other sensory modalities too. PMID:26758822

Plane-Wave Implementation and Performance of à-la-Carte Coulomb-Attenuated Exchange-Correlation Functionals for Predicting Optical Excitation Energies in Some Notorious Cases.

PubMed

Bircher, Martin P; Rothlisberger, Ursula

2018-06-12

Linear-response time-dependent density functional theory (LR-TD-DFT) has become a valuable tool in the calculation of excited states of molecules of various sizes. However, standard generalized-gradient approximation and hybrid exchange-correlation (xc) functionals often fail to correctly predict charge-transfer (CT) excitations with low orbital overlap, thus limiting the scope of the method. The Coulomb-attenuation method (CAM) in the form of the CAM-B3LYP functional has been shown to reliably remedy this problem in many CT systems, making accurate predictions possible. However, in spite of a rather consistent performance across different orbital overlap regimes, some pitfalls remain. Here, we present a fully flexible and adaptable implementation of the CAM for Γ-point calculations within the plane-wave pseudopotential molecular dynamics package CPMD and explore how customized xc functionals can improve the optical spectra of some notorious cases. We find that results obtained using plane waves agree well with those from all-electron calculations employing atom-centered bases, and that it is possible to construct a new Coulomb-attenuated xc functional based on simple considerations. We show that such a functional is able to outperform CAM-B3LYP in some cases, while retaining similar accuracy in systems where CAM-B3LYP performs well.

Barriers to adaptive reasoning in community ecology.

PubMed

McLachlan, Athol J; Ladle, Richard J

2011-08-01

Recent high-profile calls for a more trait-focused approach to community ecology have the potential to open up novel research areas, generate new insights and to transform community ecology into a more predictive science. However, a renewed emphasis on function and phenotype also requires a fundamental shift in approach and research philosophy within community ecology to more fully embrace evolutionary reasoning. Such a subject-wise transformation will be difficult due to at least four factors: (1) the historical development of the academic discipline of ecology and its roots as a descriptive science; (2) the dominating role of the ecosystem concept in the driving of contemporary ecological thought; (3) the practical difficulties associated with defining and identifying (phenotypic) adaptations, and; (4) scaling effects in ecology; the difficulty of teasing apart the overlapping and shifting hierarchical processes that generate the observed environment-trait correlations in nature. We argue that the ability to predict future ecological conditions through a sufficient understanding of ecological processes will not be achieved without the placement of the concept of adaptation at the centre of ecology, with influence radiating outwards through all the related (and rapidly specializing) sub-disciplines. © 2010 The Authors. Biological Reviews © 2010 Cambridge Philosophical Society.

Prediction of cardiovascular risk in rheumatoid arthritis: performance of original and adapted SCORE algorithms.

PubMed

Arts, E E A; Popa, C D; Den Broeder, A A; Donders, R; Sandoo, A; Toms, T; Rollefstad, S; Ikdahl, E; Semb, A G; Kitas, G D; Van Riel, P L C M; Fransen, J

2016-04-01

Predictive performance of cardiovascular disease (CVD) risk calculators appears suboptimal in rheumatoid arthritis (RA). A disease-specific CVD risk algorithm may improve CVD risk prediction in RA. The objectives of this study are to adapt the Systematic COronary Risk Evaluation (SCORE) algorithm with determinants of CVD risk in RA and to assess the accuracy of CVD risk prediction calculated with the adapted SCORE algorithm. Data from the Nijmegen early RA inception cohort were used. The primary outcome was first CVD events. The SCORE algorithm was recalibrated by reweighing included traditional CVD risk factors and adapted by adding other potential predictors of CVD. Predictive performance of the recalibrated and adapted SCORE algorithms was assessed and the adapted SCORE was externally validated. Of the 1016 included patients with RA, 103 patients experienced a CVD event. Discriminatory ability was comparable across the original, recalibrated and adapted SCORE algorithms. The Hosmer-Lemeshow test results indicated that all three algorithms provided poor model fit (p<0.05) for the Nijmegen and external validation cohort. The adapted SCORE algorithm mainly improves CVD risk estimation in non-event cases and does not show a clear advantage in reclassifying patients with RA who develop CVD (event cases) into more appropriate risk groups. This study demonstrates for the first time that adaptations of the SCORE algorithm do not provide sufficient improvement in risk prediction of future CVD in RA to serve as an appropriate alternative to the original SCORE. Risk assessment using the original SCORE algorithm may underestimate CVD risk in patients with RA. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Development of the NASA Digital Astronaut Project Muscle Model

NASA Technical Reports Server (NTRS)

Lewandowski, Beth E.; Pennline, James A.; Thompson, W. K.; Humphreys, B. T.; Ryder, J. W.; Ploutz-Snyder, L. L.; Mulugeta, L.

2015-01-01

This abstract describes development work performed on the NASA Digital Astronaut Project Muscle Model. Muscle atrophy is a known physiological response to exposure to a low gravity environment. The DAP muscle model computationally predicts the change in muscle structure and function vs. time in a reduced gravity environment. The spaceflight muscle model can then be used in biomechanical models of exercise countermeasures and spaceflight tasks to: 1) develop site specific bone loading input to the DAP bone adaptation model over the course of a mission; 2) predict astronaut performance of spaceflight tasks; 3) inform effectiveness of new exercise countermeasures concepts.

Adaptation of feedforward movement control is abnormal in patients with cervical dystonia and tremor.

PubMed

Avanzino, Laura; Ravaschio, Andrea; Lagravinese, Giovanna; Bonassi, Gaia; Abbruzzese, Giovanni; Pelosin, Elisa

2018-01-01

It is under debate whether the cerebellum plays a role in dystonia pathophysiology and in the expression of clinical phenotypes. We investigated a typical cerebellar function (anticipatory movement control) in patients with cervical dystonia (CD) with and without tremor. Twenty patients with CD, with and without tremor, and 17 healthy controls were required to catch balls of different load: 15 trials with a light ball, 25 trials with a heavy ball (adaptation) and 15 trials with a light ball (post-adaptation). Arm movements were recorded using a motion capture system. We evaluated: (i) the anticipatory adjustment (just before the impact); (ii) the extent and rate of the adaptation (at the impact) and (iii) the aftereffect in the post-adaptation phase. The anticipatory adjustment was reduced during adaptation in CD patients with tremor respect to CD patients without tremor and controls. The extent and rate of adaptation and the aftereffect in the post-adaptation phase were smaller in CD with tremor than in controls and CD without tremor. Patients with cervical dystonia and tremor display an abnormal predictive movement control. Our findings point to a possible role of cerebellum in the expression of a clinical phenotype in dystonia. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Examining the broader psychosocial effects of mass conflict on PTSD symptoms and functional impairment amongst West Papuan refugees resettled in Papua New Guinea (PNG).

PubMed

Tay, Alvin Kuowei; Rees, Susan; Chan, Jack; Kareth, Moses; Silove, Derrick

2015-05-01

Mass conflict and displacement erode the core psychosocial foundations of society, but there is a dearth of quantitative data examining the long-term mental health effects of these macrocosmic changes, particularly in relation to posttraumatic stress disorder (PTSD) symptoms. In 2013, we conducted a cross-sectional community study (n = 230) of West Papuan refugees residing in Port Moresby, Papua New Guinea, testing a moderated-mediation structural equation model of PTSD symptoms in which we examined relationships involving the psychosocial effects of mass conflict and displacement based on the Adaptation and Development after Persecution and Trauma (ADAPT) model, a trauma count (TC) of traumatic events (TEs) related to mass conflict, and a count index of current adversity (AC). A direct and an indirect path via AC led to PTSD symptoms. The ADAPT index exerted two effects on PTSD symptoms, an indirect effect via AC, and a moderating effect on TC. PTSD symptoms were directly associated with functional impairment. Although based on cross-sectional data, our findings provide support for a core prediction of the ADAPT model, that is, that undermining of the core psychosocial foundations of society brought about by mass conflict and displacement exerts an indirect and moderating influence on PTSD symptoms. The path model supports the importance of repairing the psychosocial pillars of society as a foundation for addressing trauma-related symptoms and promoting the functioning of refugees. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling the time--varying subjective quality of HTTP video streams with rate adaptations.

PubMed

Chen, Chao; Choi, Lark Kwon; de Veciana, Gustavo; Caramanis, Constantine; Heath, Robert W; Bovik, Alan C

2014-05-01

Newly developed hypertext transfer protocol (HTTP)-based video streaming technologies enable flexible rate-adaptation under varying channel conditions. Accurately predicting the users' quality of experience (QoE) for rate-adaptive HTTP video streams is thus critical to achieve efficiency. An important aspect of understanding and modeling QoE is predicting the up-to-the-moment subjective quality of a video as it is played, which is difficult due to hysteresis effects and nonlinearities in human behavioral responses. This paper presents a Hammerstein-Wiener model for predicting the time-varying subjective quality (TVSQ) of rate-adaptive videos. To collect data for model parameterization and validation, a database of longer duration videos with time-varying distortions was built and the TVSQs of the videos were measured in a large-scale subjective study. The proposed method is able to reliably predict the TVSQ of rate adaptive videos. Since the Hammerstein-Wiener model has a very simple structure, the proposed method is suitable for online TVSQ prediction in HTTP-based streaming.

Ready or Not: Microbial Adaptive Responses in Dynamic Symbiosis Environments.

PubMed

Cao, Mengyi; Goodrich-Blair, Heidi

2017-08-01

In mutually beneficial and pathogenic symbiotic associations, microbes must adapt to the host environment for optimal fitness. Both within an individual host and during transmission between hosts, microbes are exposed to temporal and spatial variation in environmental conditions. The phenomenon of phenotypic variation, in which different subpopulations of cells express distinctive and potentially adaptive characteristics, can contribute to microbial adaptation to a lifestyle that includes rapidly changing environments. The environments experienced by a symbiotic microbe during its life history can be erratic or predictable, and each can impact the evolution of adaptive responses. In particular, the predictability of a rhythmic or cyclical series of environments may promote the evolution of signal transduction cascades that allow preadaptive responses to environments that are likely to be encountered in the future, a phenomenon known as adaptive prediction. In this review, we summarize environmental variations known to occur in some well-studied models of symbiosis and how these may contribute to the evolution of microbial population heterogeneity and anticipatory behavior. We provide details about the symbiosis between Xenorhabdus bacteria and Steinernema nematodes as a model to investigate the concept of environmental adaptation and adaptive prediction in a microbial symbiosis. Copyright © 2017 American Society for Microbiology.

Horizontal gene transfer is more frequent with increased heterotrophy and contributes to parasite adaptation.

PubMed

Yang, Zhenzhen; Zhang, Yeting; Wafula, Eric K; Honaas, Loren A; Ralph, Paula E; Jones, Sam; Clarke, Christopher R; Liu, Siming; Su, Chun; Zhang, Huiting; Altman, Naomi S; Schuster, Stephan C; Timko, Michael P; Yoder, John I; Westwood, James H; dePamphilis, Claude W

2016-10-24

Horizontal gene transfer (HGT) is the transfer of genetic material across species boundaries and has been a driving force in prokaryotic evolution. HGT involving eukaryotes appears to be much less frequent, and the functional implications of HGT in eukaryotes are poorly understood. We test the hypothesis that parasitic plants, because of their intimate feeding contacts with host plant tissues, are especially prone to horizontal gene acquisition. We sought evidence of HGTs in transcriptomes of three parasitic members of Orobanchaceae, a plant family containing species spanning the full spectrum of parasitic capabilities, plus the free-living Lindenbergia Following initial phylogenetic detection and an extensive validation procedure, 52 high-confidence horizontal transfer events were detected, often from lineages of known host plants and with an increasing number of HGT events in species with the greatest parasitic dependence. Analyses of intron sequences in putative donor and recipient lineages provide evidence for integration of genomic fragments far more often than retro-processed RNA sequences. Purifying selection predominates in functionally transferred sequences, with a small fraction of adaptively evolving sites. HGT-acquired genes are preferentially expressed in the haustorium-the organ of parasitic plants-and are strongly biased in predicted gene functions, suggesting that expression products of horizontally acquired genes are contributing to the unique adaptive feeding structure of parasitic plants.

Genotypic variation in traits linked to climate and aboveground productivity in a widespread C₄ grass: evidence for a functional trait syndrome.

PubMed

Aspinwall, Michael J; Lowry, David B; Taylor, Samuel H; Juenger, Thomas E; Hawkes, Christine V; Johnson, Mari-Vaughn V; Kiniry, James R; Fay, Philip A

2013-09-01

Examining intraspecific variation in growth and function in relation to climate may provide insight into physiological evolution and adaptation, and is important for predicting species responses to climate change. Under common garden conditions, we grew nine genotypes of the C₄ species Panicum virgatum originating from different temperature and precipitation environments. We hypothesized that genotype productivity, morphology and physiological traits would be correlated with climate of origin, and a suite of adaptive traits would show high broad-sense heritability (H(2)). Genotype productivity and flowering time increased and decreased, respectively, with home-climate temperature, and home-climate temperature was correlated with genotypic differences in a syndrome of morphological and physiological traits. Genotype leaf and tiller size, leaf lamina thickness, leaf mass per area (LMA) and C : N ratios increased with home-climate temperature, whereas leaf nitrogen per unit mass (Nm ) and chlorophyll (Chl) decreased with home-climate temperature. Trait variation was largely explained by genotypic differences (H(2) = 0.33-0.85). Our results provide new insight into the role of climate in driving functional trait coordination, local adaptation and genetic divergence within species. These results emphasize the importance of considering intraspecific variation in future climate change scenarios. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Automatic identification and removal of ocular artifacts in EEG--improved adaptive predictor filtering for portable applications.

PubMed

Zhao, Qinglin; Hu, Bin; Shi, Yujun; Li, Yang; Moore, Philip; Sun, Minghou; Peng, Hong

2014-06-01

Electroencephalogram (EEG) signals have a long history of use as a noninvasive approach to measure brain function. An essential component in EEG-based applications is the removal of Ocular Artifacts (OA) from the EEG signals. In this paper we propose a hybrid de-noising method combining Discrete Wavelet Transformation (DWT) and an Adaptive Predictor Filter (APF). A particularly novel feature of the proposed method is the use of the APF based on an adaptive autoregressive model for prediction of the waveform of signals in the ocular artifact zones. In our test, based on simulated data, the accuracy of noise removal in the proposed model was significantly increased when compared to existing methods including: Wavelet Packet Transform (WPT) and Independent Component Analysis (ICA), Discrete Wavelet Transform (DWT) and Adaptive Noise Cancellation (ANC). The results demonstrate that the proposed method achieved a lower mean square error and higher correlation between the original and corrected EEG. The proposed method has also been evaluated using data from calibration trials for the Online Predictive Tools for Intervention in Mental Illness (OPTIMI) project. The results of this evaluation indicate an improvement in performance in terms of the recovery of true EEG signals with EEG tracking and computational speed in the analysis. The proposed method is well suited to applications in portable environments where the constraints with respect to acceptable wearable sensor attachments usually dictate single channel devices.

Negative Example Selection for Protein Function Prediction: The NoGO Database

PubMed Central

Youngs, Noah; Penfold-Brown, Duncan; Bonneau, Richard; Shasha, Dennis

2014-01-01

Negative examples – genes that are known not to carry out a given protein function – are rarely recorded in genome and proteome annotation databases, such as the Gene Ontology database. Negative examples are required, however, for several of the most powerful machine learning methods for integrative protein function prediction. Most protein function prediction efforts have relied on a variety of heuristics for the choice of negative examples. Determining the accuracy of methods for negative example prediction is itself a non-trivial task, given that the Open World Assumption as applied to gene annotations rules out many traditional validation metrics. We present a rigorous comparison of these heuristics, utilizing a temporal holdout, and a novel evaluation strategy for negative examples. We add to this comparison several algorithms adapted from Positive-Unlabeled learning scenarios in text-classification, which are the current state of the art methods for generating negative examples in low-density annotation contexts. Lastly, we present two novel algorithms of our own construction, one based on empirical conditional probability, and the other using topic modeling applied to genes and annotations. We demonstrate that our algorithms achieve significantly fewer incorrect negative example predictions than the current state of the art, using multiple benchmarks covering multiple organisms. Our methods may be applied to generate negative examples for any type of method that deals with protein function, and to this end we provide a database of negative examples in several well-studied organisms, for general use (The NoGO database, available at: bonneaulab.bio.nyu.edu/nogo.html). PMID:24922051

The use of regression tree analysis for predicting the functional outcome following traumatic spinal cord injury.

PubMed

Facchinello, Yann; Beauséjour, Marie; Richard-Denis, Andreane; Thompson, Cynthia; Mac-Thiong, Jean-Marc

2017-10-25

Predicting the long-term functional outcome following traumatic spinal cord injury is needed to adapt medical strategies and to plan an optimized rehabilitation. This study investigates the use of regression tree for the development of predictive models based on acute clinical and demographic predictors. This prospective study was performed on 172 patients hospitalized following traumatic spinal cord injury. Functional outcome was quantified using the Spinal Cord Independence Measure collected within the first-year post injury. Age, delay prior to surgery and Injury Severity Score were considered as continuous predictors while energy of injury, trauma mechanisms, neurological level of injury, injury severity, occurrence of early spasticity, urinary tract infection, pressure ulcer and pneumonia were coded as categorical inputs. A simplified model was built using only injury severity, neurological level, energy and age as predictor and was compared to a more complex model considering all 11 predictors mentioned above The models built using 4 and 11 predictors were found to explain 51.4% and 62.3% of the variance of the Spinal Cord Independence Measure total score after validation, respectively. The severity of the neurological deficit at admission was found to be the most important predictor. Other important predictors were the Injury Severity Score, age, neurological level and delay prior to surgery. Regression trees offer promising performances for predicting the functional outcome after a traumatic spinal cord injury. It could help to determine the number and type of predictors leading to a prediction model of the functional outcome that can be used clinically in the future.

Leuconostoc mesenteroides growth in food products: prediction and sensitivity analysis by adaptive-network-based fuzzy inference systems.

PubMed

Wang, Hue-Yu; Wen, Ching-Feng; Chiu, Yu-Hsien; Lee, I-Nong; Kao, Hao-Yun; Lee, I-Chen; Ho, Wen-Hsien

2013-01-01

An adaptive-network-based fuzzy inference system (ANFIS) was compared with an artificial neural network (ANN) in terms of accuracy in predicting the combined effects of temperature (10.5 to 24.5°C), pH level (5.5 to 7.5), sodium chloride level (0.25% to 6.25%) and sodium nitrite level (0 to 200 ppm) on the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. THE ANFIS AND ANN MODELS WERE COMPARED IN TERMS OF SIX STATISTICAL INDICES CALCULATED BY COMPARING THEIR PREDICTION RESULTS WITH ACTUAL DATA: mean absolute percentage error (MAPE), root mean square error (RMSE), standard error of prediction percentage (SEP), bias factor (Bf), accuracy factor (Af), and absolute fraction of variance (R (2)). Graphical plots were also used for model comparison. The learning-based systems obtained encouraging prediction results. Sensitivity analyses of the four environmental factors showed that temperature and, to a lesser extent, NaCl had the most influence on accuracy in predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. The observed effectiveness of ANFIS for modeling microbial kinetic parameters confirms its potential use as a supplemental tool in predictive mycology. Comparisons between growth rates predicted by ANFIS and actual experimental data also confirmed the high accuracy of the Gaussian membership function in ANFIS. Comparisons of the six statistical indices under both aerobic and anaerobic conditions also showed that the ANFIS model was better than all ANN models in predicting the four kinetic parameters. Therefore, the ANFIS model is a valuable tool for quickly predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions.

Leuconostoc Mesenteroides Growth in Food Products: Prediction and Sensitivity Analysis by Adaptive-Network-Based Fuzzy Inference Systems

PubMed Central

Wang, Hue-Yu; Wen, Ching-Feng; Chiu, Yu-Hsien; Lee, I-Nong; Kao, Hao-Yun; Lee, I-Chen; Ho, Wen-Hsien

2013-01-01

Background An adaptive-network-based fuzzy inference system (ANFIS) was compared with an artificial neural network (ANN) in terms of accuracy in predicting the combined effects of temperature (10.5 to 24.5°C), pH level (5.5 to 7.5), sodium chloride level (0.25% to 6.25%) and sodium nitrite level (0 to 200 ppm) on the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. Methods The ANFIS and ANN models were compared in terms of six statistical indices calculated by comparing their prediction results with actual data: mean absolute percentage error (MAPE), root mean square error (RMSE), standard error of prediction percentage (SEP), bias factor (Bf), accuracy factor (Af), and absolute fraction of variance (R 2). Graphical plots were also used for model comparison. Conclusions The learning-based systems obtained encouraging prediction results. Sensitivity analyses of the four environmental factors showed that temperature and, to a lesser extent, NaCl had the most influence on accuracy in predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. The observed effectiveness of ANFIS for modeling microbial kinetic parameters confirms its potential use as a supplemental tool in predictive mycology. Comparisons between growth rates predicted by ANFIS and actual experimental data also confirmed the high accuracy of the Gaussian membership function in ANFIS. Comparisons of the six statistical indices under both aerobic and anaerobic conditions also showed that the ANFIS model was better than all ANN models in predicting the four kinetic parameters. Therefore, the ANFIS model is a valuable tool for quickly predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. PMID:23705023

Homeostatic Regulation of Memory Systems and Adaptive Decisions

PubMed Central

Mizumori, Sheri JY; Jo, Yong Sang

2013-01-01

While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The “multiple memory systems of the brain” have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result in rigid and suboptimal decision making and memory as seen in addiction and neurological disease. © 2013 The Authors. Hippocampus Published by Wiley Periodicals, Inc. PMID:23929788

Homeostatic regulation of memory systems and adaptive decisions.

PubMed

Mizumori, Sheri J Y; Jo, Yong Sang

2013-11-01

While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The "multiple memory systems of the brain" have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result in rigid and suboptimal decision making and memory as seen in addiction and neurological disease. Copyright © 2013 Wiley Periodicals, Inc.

Schema-based learning of adaptable and flexible prey- catching in anurans II. Learning after lesioning.

PubMed

Corbacho, Fernando; Nishikawa, Kiisa C; Weerasuriya, Ananda; Liaw, Jim-Shih; Arbib, Michael A

2005-12-01

The previous companion paper describes the initial (seed) schema architecture that gives rise to the observed prey-catching behavior. In this second paper in the series we describe the fundamental adaptive processes required during learning after lesioning. Following bilateral transections of the hypoglossal nerve, anurans lunge toward mealworms with no accompanying tongue or jaw movement. Nevertheless anurans with permanent hypoglossal transections eventually learn to catch their prey by first learning to open their mouth again and then lunging their body further and increasing their head angle. In this paper we present a new learning framework, called schema-based learning (SBL). SBL emphasizes the importance of the current existent structure (schemas), that defines a functioning system, for the incremental and autonomous construction of ever more complex structure to achieve ever more complex levels of functioning. We may rephrase this statement into the language of Schema Theory (Arbib 1992, for a comprehensive review) as the learning of new schemas based on the stock of current schemas. SBL emphasizes a fundamental principle of organization called coherence maximization, that deals with the maximization of congruence between the results of an interaction (external or internal) and the expectations generated for that interaction. A central hypothesis consists of the existence of a hierarchy of predictive internal models (predictive schemas) all over the control center-brain-of the agent. Hence, we will include predictive models in the perceptual, sensorimotor, and motor components of the autonomous agent architecture. We will then show that predictive models are fundamental for structural learning. In particular we will show how a system can learn a new structural component (augment the overall network topology) after being lesioned in order to recover (or even improve) its original functionality. Learning after lesioning is a special case of structural learning but clearly shows that solutions cannot be known/hardwired a priori since it cannot be known, in advance, which substructure is going to break down.

The Utility of the Mayo-Portland Adaptability Inventory Participation Index (M2PI) in US Military Veterans With a History of Mild Traumatic Brain Injury.

PubMed

OʼRourke, Justin; Critchfield, Edan; Soble, Jason; Bain, Kathleen; Fullen, Chrystal; Eapen, Blessen

2018-05-31

To examine the utility of the Mayo-Portland Adaptability Inventory-4th Edition Participation Index (M2PI) as a self-report measure of functional outcome following mild traumatic brain injury (mTBI) in US Military veterans. Department of Veterans Affairs Polytrauma Rehabilitation Center specialty hospital. On hundred thirty-nine veterans with a history of self-reported mTBI. Retrospective cross-sectional examination of data collected from regular clinical visits. M2PI, Neurobehavioral Symptoms Inventory with embedded validity measures, Posttraumatic Stress Disorder Checklist-Military Version. Forty-one percent of the sample provided symptom reports that exceeded established cut scores on embedded symptom validity tests. Invalid responders had higher levels of unemployment and endorsed significantly greater functional impairment, posttraumatic stress symptoms, and postconcussive complaints. For valid responders, regression analyses revealed that self-reported functioning was primarily related to posttraumatic stress complaints, followed by postconcussive cognitive complaints. For invalid responders, posttraumatic stress complaints also predicted self-reported functioning. Caution is recommended when utilizing the M2PI to measure functional outcome following mTBI in military veterans, particularly in the absence of symptom validity tests.

Virtual Reality to Maximize Function for Hand and Arm Rehabilitation: Exploration of Neural Mechanisms

PubMed Central

MERIANS, Alma S.; TUNIK, Eugene; ADAMOVICH, Sergei V.

2015-01-01

Stroke patients report hand function as the most disabling motor deficit. Current evidence shows that learning new motor skills is essential for inducing functional neuroplasticity and functional recovery. Adaptive training paradigms that continually and interactively move a motor outcome closer to the targeted skill are important to motor recovery. Computerized virtual reality simulations when interfaced with robots, movement tracking and sensing glove systems are particularly adaptable, allowing for online and offline modifications of task based activities using the participant’s current performance and success rate. We have developed a second generation system that can exercise the hand and the arm together or in isolation and provides for both unilateral and bilateral hand and arm activities in three-dimensional space. We demonstrate that by providing haptic assistance for the hand and arm and adaptive anti-gravity support, the system can accommodate patients with lower level impairments. We hypothesize that combining training in VE with observation of motor actions can bring additional benefits. We present a proof of concept of a novel system that integrates interactive VE with functional neuroimaging to address this issue. Three components of this system are synchronized, the presentation of the visual display of the virtual hands, the collection of fMRI images and the collection of hand joint angles from the instrumented gloves. We show that interactive VEs can facilitate activation of brain areas during training by providing appropriately modified visual feedback. We predict that visual augmentation can become a tool to facilitate functional neuroplasticity. PMID:19592790

Real-time, adaptive machine learning for non-stationary, near chaotic gasoline engine combustion time series.

PubMed

Vaughan, Adam; Bohac, Stanislav V

2015-10-01

Fuel efficient Homogeneous Charge Compression Ignition (HCCI) engine combustion timing predictions must contend with non-linear chemistry, non-linear physics, period doubling bifurcation(s), turbulent mixing, model parameters that can drift day-to-day, and air-fuel mixture state information that cannot typically be resolved on a cycle-to-cycle basis, especially during transients. In previous work, an abstract cycle-to-cycle mapping function coupled with ϵ-Support Vector Regression was shown to predict experimentally observed cycle-to-cycle combustion timing over a wide range of engine conditions, despite some of the aforementioned difficulties. The main limitation of the previous approach was that a partially acasual randomly sampled training dataset was used to train proof of concept offline predictions. The objective of this paper is to address this limitation by proposing a new online adaptive Extreme Learning Machine (ELM) extension named Weighted Ring-ELM. This extension enables fully causal combustion timing predictions at randomly chosen engine set points, and is shown to achieve results that are as good as or better than the previous offline method. The broader objective of this approach is to enable a new class of real-time model predictive control strategies for high variability HCCI and, ultimately, to bring HCCI's low engine-out NOx and reduced CO2 emissions to production engines. Copyright © 2015 Elsevier Ltd. All rights reserved.

Genome-environment associations in sorghum landraces predict adaptive traits

PubMed Central

Lasky, Jesse R.; Upadhyaya, Hari D.; Ramu, Punna; Deshpande, Santosh; Hash, C. Tom; Bonnette, Jason; Juenger, Thomas E.; Hyma, Katie; Acharya, Charlotte; Mitchell, Sharon E.; Buckler, Edward S.; Brenton, Zachary; Kresovich, Stephen; Morris, Geoffrey P.

2015-01-01

Improving environmental adaptation in crops is essential for food security under global change, but phenotyping adaptive traits remains a major bottleneck. If associations between single-nucleotide polymorphism (SNP) alleles and environment of origin in crop landraces reflect adaptation, then these could be used to predict phenotypic variation for adaptive traits. We tested this proposition in the global food crop Sorghum bicolor, characterizing 1943 georeferenced landraces at 404,627 SNPs and quantifying allelic associations with bioclimatic and soil gradients. Environment explained a substantial portion of SNP variation, independent of geographical distance, and genic SNPs were enriched for environmental associations. Further, environment-associated SNPs predicted genotype-by-environment interactions under experimental drought stress and aluminum toxicity. Our results suggest that genomic signatures of environmental adaptation may be useful for crop improvement, enhancing germplasm identification and marker-assisted selection. Together, genome-environment associations and phenotypic analyses may reveal the basis of environmental adaptation. PMID:26601206

Experimental whole-stream warming alters community size structure.

PubMed

Nelson, Daniel; Benstead, Jonathan P; Huryn, Alexander D; Cross, Wyatt F; Hood, James M; Johnson, Philip W; Junker, James R; Gíslason, Gísli M; Ólafsson, Jón S

2017-07-01

How ecological communities respond to predicted increases in temperature will determine the extent to which Earth's biodiversity and ecosystem functioning can be maintained into a warmer future. Warming is predicted to alter the structure of natural communities, but robust tests of such predictions require appropriate large-scale manipulations of intact, natural habitat that is open to dispersal processes via exchange with regional species pools. Here, we report results of a two-year whole-stream warming experiment that shifted invertebrate assemblage structure via unanticipated mechanisms, while still conforming to community-level metabolic theory. While warming by 3.8 °C decreased invertebrate abundance in the experimental stream by 60% relative to a reference stream, total invertebrate biomass was unchanged. Associated shifts in invertebrate assemblage structure were driven by the arrival of new taxa and a higher proportion of large, warm-adapted species (i.e., snails and predatory dipterans) relative to small-bodied, cold-adapted taxa (e.g., chironomids and oligochaetes). Experimental warming consequently shifted assemblage size spectra in ways that were unexpected, but consistent with thermal optima of taxa in the regional species pool. Higher temperatures increased community-level energy demand, which was presumably satisfied by higher primary production after warming. Our experiment demonstrates how warming reassembles communities within the constraints of energy supply via regional exchange of species that differ in thermal physiological traits. Similar responses will likely mediate impacts of anthropogenic warming on biodiversity and ecosystem function across all ecological communities. © 2016 John Wiley & Sons Ltd.

On-line self-learning time forward voltage prognosis for lithium-ion batteries using adaptive neuro-fuzzy inference system

NASA Astrophysics Data System (ADS)

Fleischer, Christian; Waag, Wladislaw; Bai, Ziou; Sauer, Dirk Uwe

2013-12-01

The battery management system (BMS) of a battery-electric road vehicle must ensure an optimal operation of the electrochemical storage system to guarantee for durability and reliability. In particular, the BMS must provide precise information about the battery's state-of-functionality, i.e. how much dis-/charging power can the battery accept at current state and condition while at the same time preventing it from operating outside its safe operating area. These critical limits have to be calculated in a predictive manner, which serve as a significant input factor for the supervising vehicle energy management (VEM). The VEM must provide enough power to the vehicle's drivetrain for certain tasks and especially in critical driving situations. Therefore, this paper describes a new approach which can be used for state-of-available-power estimation with respect to lowest/highest cell voltage prediction using an adaptive neuro-fuzzy inference system (ANFIS). The estimated voltage for a given time frame in the future is directly compared with the actual voltage, verifying the effectiveness and accuracy of a relative voltage prediction error of less than 1%. Moreover, the real-time operating capability of the proposed algorithm was verified on a battery test bench while running on a real-time system performing voltage prediction.

The Predictive Utility of Narcissism among Children and Adolescents: Evidence for a Distinction between Adaptive and Maladaptive Narcissism

ERIC Educational Resources Information Center

Barry, Christopher T.; Frick, Paul J.; Adler, Kristy K.; Grafeman, Sarah J.

2007-01-01

We examined the predictive utility of narcissism among a community sample of children and adolescents (N=98) longitudinally. Analyses focused on the differential utility between maladaptive and adaptive narcissism for predicting later delinquency. Maladaptive narcissism significantly predicted self-reported delinquency at one-, two-, and…

Saccharomyces cerevisiae: a nomadic yeast with no niche?

PubMed

Goddard, Matthew R; Greig, Duncan

2015-05-01

Different species are usually thought to have specific adaptations, which allow them to occupy different ecological niches. But recent neutral ecology theory suggests that species diversity can simply be the result of random sampling, due to finite population sizes and limited dispersal. Neutral models predict that species are not necessarily adapted to specific niches, but are functionally equivalent across a range of habitats. Here, we evaluate the ecology of Saccharomyces cerevisiae, one of the most important microbial species in human history. The artificial collection, concentration and fermentation of large volumes of fruit for alcohol production produce an environment in which S. cerevisiae thrives, and therefore it is assumed that fruit is the ecological niche that S. cerevisiae inhabits and has adapted to. We find very little direct evidence that S. cerevisiae is adapted to fruit, or indeed to any other specific niche. We propose instead a neutral nomad model for S. cerevisiae, which we believe should be used as the starting hypothesis in attempting to unravel the ecology of this important microbe. © FEMS 2015.

Eco-evo-devo in the Study of Adaptive Divergence: Examples from Threespine Stickleback (Gasterosteus aculeatus).

PubMed

Jamniczky, Heather A; Barry, Tegan N; Rogers, Sean M

2015-07-01

The tight fit between form and function in organisms suggests the influence of adaptive evolution in biomechanics; however, the prevalence of adaptive traits, the mechanisms by which they arise and the corresponding responses to selection are subjects of extensive debate. We used three-dimensional microcomputed tomography and geometric morphometrics to characterize the structure of phenotypic covariance within the G. aculeatus trophic apparatus and its supporting structures in wild and controlled crosses of fish from two different localities. Our results reveal that while the structure of phenotypic covariance is conserved in marine and freshwater forms, it may be disrupted in the progeny of artificial crosses or during rapid adaptive divergence events. We discuss these results within the context of integrating covariance structure with quantitative genetics, toward establishing predictive links between genes, development, biomechanics, and the environment. © The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

A study on multiresolution lossless video coding using inter/intra frame adaptive prediction

NASA Astrophysics Data System (ADS)

Nakachi, Takayuki; Sawabe, Tomoko; Fujii, Tetsuro

2003-06-01

Lossless video coding is required in the fields of archiving and editing digital cinema or digital broadcasting contents. This paper combines a discrete wavelet transform and adaptive inter/intra-frame prediction in the wavelet transform domain to create multiresolution lossless video coding. The multiresolution structure offered by the wavelet transform facilitates interchange among several video source formats such as Super High Definition (SHD) images, HDTV, SDTV, and mobile applications. Adaptive inter/intra-frame prediction is an extension of JPEG-LS, a state-of-the-art lossless still image compression standard. Based on the image statistics of the wavelet transform domains in successive frames, inter/intra frame adaptive prediction is applied to the appropriate wavelet transform domain. This adaptation offers superior compression performance. This is achieved with low computational cost and no increase in additional information. Experiments on digital cinema test sequences confirm the effectiveness of the proposed algorithm.

Brain evolution and development: adaptation, allometry and constraint

PubMed Central

Barton, Robert A.

2016-01-01

Phenotypic traits are products of two processes: evolution and development. But how do these processes combine to produce integrated phenotypes? Comparative studies identify consistent patterns of covariation, or allometries, between brain and body size, and between brain components, indicating the presence of significant constraints limiting independent evolution of separate parts. These constraints are poorly understood, but in principle could be either developmental or functional. The developmental constraints hypothesis suggests that individual components (brain and body size, or individual brain components) tend to evolve together because natural selection operates on relatively simple developmental mechanisms that affect the growth of all parts in a concerted manner. The functional constraints hypothesis suggests that correlated change reflects the action of selection on distributed functional systems connecting the different sub-components, predicting more complex patterns of mosaic change at the level of the functional systems and more complex genetic and developmental mechanisms. These hypotheses are not mutually exclusive but make different predictions. We review recent genetic and neurodevelopmental evidence, concluding that functional rather than developmental constraints are the main cause of the observed patterns. PMID:27629025

Short-term prediction of chaotic time series by using RBF network with regression weights.

PubMed

Rojas, I; Gonzalez, J; Cañas, A; Diaz, A F; Rojas, F J; Rodriguez, M

2000-10-01

We propose a framework for constructing and training a radial basis function (RBF) neural network. The structure of the gaussian functions is modified using a pseudo-gaussian function (PG) in which two scaling parameters sigma are introduced, which eliminates the symmetry restriction and provides the neurons in the hidden layer with greater flexibility with respect to function approximation. We propose a modified PG-BF (pseudo-gaussian basis function) network in which the regression weights are used to replace the constant weights in the output layer. For this purpose, a sequential learning algorithm is presented to adapt the structure of the network, in which it is possible to create a new hidden unit and also to detect and remove inactive units. A salient feature of the network systems is that the method used for calculating the overall output is the weighted average of the output associated with each receptive field. The superior performance of the proposed PG-BF system over the standard RBF are illustrated using the problem of short-term prediction of chaotic time series.

An adaptive two-stage analog/regression model for probabilistic prediction of small-scale precipitation in France

NASA Astrophysics Data System (ADS)

Chardon, Jérémy; Hingray, Benoit; Favre, Anne-Catherine

2018-01-01

Statistical downscaling models (SDMs) are often used to produce local weather scenarios from large-scale atmospheric information. SDMs include transfer functions which are based on a statistical link identified from observations between local weather and a set of large-scale predictors. As physical processes driving surface weather vary in time, the most relevant predictors and the regression link are likely to vary in time too. This is well known for precipitation for instance and the link is thus often estimated after some seasonal stratification of the data. In this study, we present a two-stage analog/regression model where the regression link is estimated from atmospheric analogs of the current prediction day. Atmospheric analogs are identified from fields of geopotential heights at 1000 and 500 hPa. For the regression stage, two generalized linear models are further used to model the probability of precipitation occurrence and the distribution of non-zero precipitation amounts, respectively. The two-stage model is evaluated for the probabilistic prediction of small-scale precipitation over France. It noticeably improves the skill of the prediction for both precipitation occurrence and amount. As the analog days vary from one prediction day to another, the atmospheric predictors selected in the regression stage and the value of the corresponding regression coefficients can vary from one prediction day to another. The model allows thus for a day-to-day adaptive and tailored downscaling. It can also reveal specific predictors for peculiar and non-frequent weather configurations.

A resilience perspective to water risk management: case-study application of the adaptation tipping point method

NASA Astrophysics Data System (ADS)

Gersonius, Berry; Ashley, Richard; Jeuken, Ad; Nasruddin, Fauzy; Pathirana, Assela; Zevenbergen, Chris

2010-05-01

In a context of high uncertainty about hydrological variables due to climate change and other factors, the development of updated risk management approaches is as important as—if not more important than—the provision of improved data and forecasts of the future. Traditional approaches to adaptation attempt to manage future water risks to cities with the use of the predict-then-adapt method. This method uses hydrological change projections as the starting point to identify adaptive strategies, which is followed by analysing the cause-effect chain based on some sort of Pressures-State-Impact-Response (PSIR) scheme. The predict-then-adapt method presumes that it is possible to define a singular (optimal) adaptive strategy according to a most likely or average projection of future change. A key shortcoming of the method is, however, that the planning of water management structures is typically decoupled from forecast uncertainties and is, as such, inherently inflexible. This means that there is an increased risk of under- or over-adaptation, resulting in either mal-functioning or unnecessary costs. Rather than taking a traditional approach, responsible water risk management requires an alternative approach to adaptation that recognises and cultivates resiliency for change. The concept of resiliency relates to the capability of complex socio-technical systems to make aspirational levels of functioning attainable despite the occurrence of possible changes. Focusing on resiliency does not attempt to reduce uncertainty associated with future change, but rather to develop better ways of managing it. This makes it a particularly relevant perspective for adaptation to long-term hydrological change. Although resiliency is becoming more refined as a theory, the application of the concept to water risk management is still in an initial phase. Different methods are used in practice to support the implementation of a resilience-focused approach. Typically these approaches start the identification and analysis of adaptive strategies at the end of PSIR scheme: impact and examine whether, and for how long, current risk management strategies will continue to be effective under different future conditions. The most noteworthy application of this approach is the adaptation tipping point method. Adaptation tipping points (ATP) are defined as the points where the magnitude of change is such that the current risk management strategy can no longer meet its objectives. In the ATP method, policy objectives, determining aspirational functioning, are taken as the starting point. Also, the current measures to achieve these objectives are described. This is followed by a sensitivity analysis to determine the optimal and critical boundary conditions (state). Lastly, the state is related to pressures in terms of future change. It should be noted that in the ATP method the driver for adopting a new risk management strategy is not future change as such, but rather failing to meet the policy objectives. In the current paper, the ATP method is applied to the case study of an existing stormwater system in Dordrecht (the Netherlands). This application shows the potential of the ATP method to reduce the complexity of implementing a resilience-focused approach to water risk management. It is expected that this will help foster greater practical relevance of resilience as a perspective for the planning of water management structures.

Time course of dynamic range adaptation in the auditory nerve

PubMed Central

Wang, Grace I.; Dean, Isabel; Delgutte, Bertrand

2012-01-01

Auditory adaptation to sound-level statistics occurs as early as in the auditory nerve (AN), the first stage of neural auditory processing. In addition to firing rate adaptation characterized by a rate decrement dependent on previous spike activity, AN fibers show dynamic range adaptation, which is characterized by a shift of the rate-level function or dynamic range toward the most frequently occurring levels in a dynamic stimulus, thereby improving the precision of coding of the most common sound levels (Wen B, Wang GI, Dean I, Delgutte B. J Neurosci 29: 13797–13808, 2009). We investigated the time course of dynamic range adaptation by recording from AN fibers with a stimulus in which the sound levels periodically switch from one nonuniform level distribution to another (Dean I, Robinson BL, Harper NS, McAlpine D. J Neurosci 28: 6430–6438, 2008). Dynamic range adaptation occurred rapidly, but its exact time course was difficult to determine directly from the data because of the concomitant firing rate adaptation. To characterize the time course of dynamic range adaptation without the confound of firing rate adaptation, we developed a phenomenological “dual adaptation” model that accounts for both forms of AN adaptation. When fitted to the data, the model predicts that dynamic range adaptation occurs as rapidly as firing rate adaptation, over 100–400 ms, and the time constants of the two forms of adaptation are correlated. These findings suggest that adaptive processing in the auditory periphery in response to changes in mean sound level occurs rapidly enough to have significant impact on the coding of natural sounds. PMID:22457465

Disentangling cognition and emotion in older adults: the role of cognitive control and mental health in emotional conflict adaptation.

PubMed

Hantke, Nathan C; Gyurak, Anett; Van Moorleghem, Katie; Waring, Jill D; Adamson, Maheen M; O'Hara, Ruth; Beaudreau, Sherry A

2017-08-01

Recent research suggests cognition has a bidirectional relationship with emotional processing in older adults, yet the relationship is still poorly understood. We aimed to examine a potential relationship between late-life cognitive function, mental health symptoms, and emotional conflict adaptation. We hypothesized that worse cognitive control abilities would be associated with poorer emotional conflict adaptation. We further hypothesized that a higher severity of mental health symptoms would be associated with poorer emotional conflict adaptation. Participants included 83 cognitively normal community-dwelling older adults who completed a targeted mental health and cognitive battery, and emotion and gender conflict-adaptation tasks. Consistent with our hypothesis, poorer performance on components of cognitive control, specifically attention and working memory, was associated with poorer emotional conflict adaptation. This association with attention and working memory was not observed in the non-affective-based gender conflict adaptation task. Mental health symptoms did not predict emotional conflict adaptation, nor did performance on other cognitive measures. Our findings suggest that emotion conflict adaptation is disrupted in older individuals who have poorer attention and working memory. Components of cognitive control may therefore be an important potential source of inter-individual differences in late-life emotion regulation and cognitive affective deficits. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Adaptive non-linear control for cancer therapy through a Fokker-Planck observer.

PubMed

Shakeri, Ehsan; Latif-Shabgahi, Gholamreza; Esmaeili Abharian, Amir

2018-04-01

In recent years, many efforts have been made to present optimal strategies for cancer therapy through the mathematical modelling of tumour-cell population dynamics and optimal control theory. In many cases, therapy effect is included in the drift term of the stochastic Gompertz model. By fitting the model with empirical data, the parameters of therapy function are estimated. The reported research works have not presented any algorithm to determine the optimal parameters of therapy function. In this study, a logarithmic therapy function is entered in the drift term of the Gompertz model. Using the proposed control algorithm, the therapy function parameters are predicted and adaptively adjusted. To control the growth of tumour-cell population, its moments must be manipulated. This study employs the probability density function (PDF) control approach because of its ability to control all the process moments. A Fokker-Planck-based non-linear stochastic observer will be used to determine the PDF of the process. A cost function based on the difference between a predefined desired PDF and PDF of tumour-cell population is defined. Using the proposed algorithm, the therapy function parameters are adjusted in such a manner that the cost function is minimised. The existence of an optimal therapy function is also proved. The numerical results are finally given to demonstrate the effectiveness of the proposed method.

Prediction of brain maturity in infants using machine-learning algorithms.

PubMed

Smyser, Christopher D; Dosenbach, Nico U F; Smyser, Tara A; Snyder, Abraham Z; Rogers, Cynthia E; Inder, Terrie E; Schlaggar, Bradley L; Neil, Jeffrey J

2016-08-01

Recent resting-state functional MRI investigations have demonstrated that much of the large-scale functional network architecture supporting motor, sensory and cognitive functions in older pediatric and adult populations is present in term- and prematurely-born infants. Application of new analytical approaches can help translate the improved understanding of early functional connectivity provided through these studies into predictive models of neurodevelopmental outcome. One approach to achieving this goal is multivariate pattern analysis, a machine-learning, pattern classification approach well-suited for high-dimensional neuroimaging data. It has previously been adapted to predict brain maturity in children and adolescents using structural and resting state-functional MRI data. In this study, we evaluated resting state-functional MRI data from 50 preterm-born infants (born at 23-29weeks of gestation and without moderate-severe brain injury) scanned at term equivalent postmenstrual age compared with data from 50 term-born control infants studied within the first week of life. Using 214 regions of interest, binary support vector machines distinguished term from preterm infants with 84% accuracy (p<0.0001). Inter- and intra-hemispheric connections throughout the brain were important for group categorization, indicating that widespread changes in the brain's functional network architecture associated with preterm birth are detectable by term equivalent age. Support vector regression enabled quantitative estimation of birth gestational age in single subjects using only term equivalent resting state-functional MRI data, indicating that the present approach is sensitive to the degree of disruption of brain development associated with preterm birth (using gestational age as a surrogate for the extent of disruption). This suggests that support vector regression may provide a means for predicting neurodevelopmental outcome in individual infants. Copyright © 2016 Elsevier Inc. All rights reserved.

Prediction of brain maturity in infants using machine-learning algorithms

PubMed Central

Smyser, Christopher D.; Dosenbach, Nico U.F.; Smyser, Tara A.; Snyder, Abraham Z.; Rogers, Cynthia E.; Inder, Terrie E.; Schlaggar, Bradley L.; Neil, Jeffrey J.

2016-01-01

Recent resting-state functional MRI investigations have demonstrated that much of the large-scale functional network architecture supporting motor, sensory and cognitive functions in older pediatric and adult populations is present in term- and prematurely-born infants. Application of new analytical approaches can help translate the improved understanding of early functional connectivity provided through these studies into predictive models of neurodevelopmental outcome. One approach to achieving this goal is multivariate pattern analysis, a machine-learning, pattern classification approach well-suited for high-dimensional neuroimaging data. It has previously been adapted to predict brain maturity in children and adolescents using structural and resting state-functional MRI data. In this study, we evaluated resting state-functional MRI data from 50 preterm-born infants (born at 23–29 weeks of gestation and without moderate–severe brain injury) scanned at term equivalent postmenstrual age compared with data from 50 term-born control infants studied within the first week of life. Using 214 regions of interest, binary support vector machines distinguished term from preterm infants with 84% accuracy (p < 0.0001). Inter- and intra-hemispheric connections throughout the brain were important for group categorization, indicating that widespread changes in the brain's functional network architecture associated with preterm birth are detectable by term equivalent age. Support vector regression enabled quantitative estimation of birth gestational age in single subjects using only term equivalent resting state-functional MRI data, indicating that the present approach is sensitive to the degree of disruption of brain development associated with preterm birth (using gestational age as a surrogate for the extent of disruption). This suggests that support vector regression may provide a means for predicting neurodevelopmental outcome in individual infants. PMID:27179605

Fourier transform wavefront control with adaptive prediction of the atmosphere.

PubMed

Poyneer, Lisa A; Macintosh, Bruce A; Véran, Jean-Pierre

2007-09-01

Predictive Fourier control is a temporal power spectral density-based adaptive method for adaptive optics that predicts the atmosphere under the assumption of frozen flow. The predictive controller is based on Kalman filtering and a Fourier decomposition of atmospheric turbulence using the Fourier transform reconstructor. It provides a stable way to compensate for arbitrary numbers of atmospheric layers. For each Fourier mode, efficient and accurate algorithms estimate the necessary atmospheric parameters from closed-loop telemetry and determine the predictive filter, adjusting as conditions change. This prediction improves atmospheric rejection, leading to significant improvements in system performance. For a 48x48 actuator system operating at 2 kHz, five-layer prediction for all modes is achievable in under 2x10(9) floating-point operations/s.

On the mechanics of growing thin biological membranes

NASA Astrophysics Data System (ADS)

Rausch, Manuel K.; Kuhl, Ellen

2014-02-01

Despite their seemingly delicate appearance, thin biological membranes fulfill various crucial roles in the human body and can sustain substantial mechanical loads. Unlike engineering structures, biological membranes are able to grow and adapt to changes in their mechanical environment. Finite element modeling of biological growth holds the potential to better understand the interplay of membrane form and function and to reliably predict the effects of disease or medical intervention. However, standard continuum elements typically fail to represent thin biological membranes efficiently, accurately, and robustly. Moreover, continuum models are typically cumbersome to generate from surface-based medical imaging data. Here we propose a computational model for finite membrane growth using a classical midsurface representation compatible with standard shell elements. By assuming elastic incompressibility and membrane-only growth, the model a priori satisfies the zero-normal stress condition. To demonstrate its modular nature, we implement the membrane growth model into the general-purpose non-linear finite element package Abaqus/Standard using the concept of user subroutines. To probe efficiently and robustness, we simulate selected benchmark examples of growing biological membranes under different loading conditions. To demonstrate the clinical potential, we simulate the functional adaptation of a heart valve leaflet in ischemic cardiomyopathy. We believe that our novel approach will be widely applicable to simulate the adaptive chronic growth of thin biological structures including skin membranes, mucous membranes, fetal membranes, tympanic membranes, corneoscleral membranes, and heart valve membranes. Ultimately, our model can be used to identify diseased states, predict disease evolution, and guide the design of interventional or pharmaceutic therapies to arrest or revert disease progression.

Evolutionary Dynamics on Protein Bi-stability Landscapes can Potentially Resolve Adaptive Conflicts

PubMed Central

Sikosek, Tobias; Bornberg-Bauer, Erich; Chan, Hue Sun

2012-01-01

Experimental studies have shown that some proteins exist in two alternative native-state conformations. It has been proposed that such bi-stable proteins can potentially function as evolutionary bridges at the interface between two neutral networks of protein sequences that fold uniquely into the two different native conformations. Under adaptive conflict scenarios, bi-stable proteins may be of particular advantage if they simultaneously provide two beneficial biological functions. However, computational models that simulate protein structure evolution do not yet recognize the importance of bi-stability. Here we use a biophysical model to analyze sequence space to identify bi-stable or multi-stable proteins with two or more equally stable native-state structures. The inclusion of such proteins enhances phenotype connectivity between neutral networks in sequence space. Consideration of the sequence space neighborhood of bridge proteins revealed that bi-stability decreases gradually with each mutation that takes the sequence further away from an exactly bi-stable protein. With relaxed selection pressures, we found that bi-stable proteins in our model are highly successful under simulated adaptive conflict. Inspired by these model predictions, we developed a method to identify real proteins in the PDB with bridge-like properties, and have verified a clear bi-stability gradient for a series of mutants studied by Alexander et al. (Proc Nat Acad Sci USA 2009, 106:21149–21154) that connect two sequences that fold uniquely into two different native structures via a bridge-like intermediate mutant sequence. Based on these findings, new testable predictions for future studies on protein bi-stability and evolution are discussed. PMID:23028272

Socio-sexuality and episodic memory function in women: further evidence of an adaptive "mating mode".

PubMed

Smith, David S; Jones, Benedict C; Allan, Kevin

2013-08-01

The functionalist memory perspective predicts that information of adaptive value may trigger specific processing modes. It was recently demonstrated that women's memory is sensitive to cues of male sexual dimorphism (i.e., masculinity) that convey information of adaptive value for mate choice because they signal health and genetic quality, as well as personality traits important in relationship contexts. Here, we show that individual differences in women's mating strategies predict the effect of facial masculinity cues upon memory, strengthening the case for functional design within memory. Using the revised socio-sexual orientation inventory, Experiment 1 demonstrates that women pursuing a short-term, uncommitted mating strategy have enhanced source memory for men with exaggerated versus reduced masculine facial features, an effect that reverses in women who favor long-term committed relationships. The reversal in the direction of the effect indicates that it does not reflect the sex typicality of male faces per se. The same pattern occurred within women's source memory for women's faces, implying that the memory bias does not reflect the perceived attractiveness of faces per se. In Experiment 2, we reran the experiment using men's faces to establish the reliability of the core finding and replicated Experiment 1's results. Masculinity cues may therefore trigger a specific mode within women's episodic memory. We discuss why this mode may be triggered by female faces and its possible role in mate choice. In so doing, we draw upon the encoding specificity principle and the idea that episodic memory limits the scope of stereotypical inferences about male behavior.

On the mechanics of growing thin biological membranes

PubMed Central

Rausch, Manuel K.; Kuhl, Ellen

2013-01-01

Despite their seemingly delicate appearance, thin biological membranes fulfill various crucial roles in the human body and can sustain substantial mechanical loads. Unlike engineering structures, biological membranes are able to grow and adapt to changes in their mechanical environment. Finite element modeling of biological growth holds the potential to better understand the interplay of membrane form and function and to reliably predict the effects of disease or medical intervention. However, standard continuum elements typically fail to represent thin biological membranes efficiently, accurately, and robustly. Moreover, continuum models are typically cumbersome to generate from surface-based medical imaging data. Here we propose a computational model for finite membrane growth using a classical midsurface representation compatible with standard shell elements. By assuming elastic incompressibility and membrane-only growth, the model a priori satisfies the zero-normal stress condition. To demonstrate its modular nature, we implement the membrane growth model into the general-purpose non-linear finite element package Abaqus/Standard using the concept of user subroutines. To probe efficiently and robustness, we simulate selected benchmark examples of growing biological membranes under different loading conditions. To demonstrate the clinical potential, we simulate the functional adaptation of a heart valve leaflet in ischemic cardiomyopathy. We believe that our novel approach will be widely applicable to simulate the adaptive chronic growth of thin biological structures including skin membranes, mucous membranes, fetal membranes, tympanic membranes, corneoscleral membranes, and heart valve membranes. Ultimately, our model can be used to identify diseased states, predict disease evolution, and guide the design of interventional or pharmaceutic therapies to arrest or revert disease progression. PMID:24563551

Depression as sickness behavior? A test of the host defense hypothesis in a high pathogen population.

PubMed

Stieglitz, Jonathan; Trumble, Benjamin C; Thompson, Melissa Emery; Blackwell, Aaron D; Kaplan, Hillard; Gurven, Michael

2015-10-01

Sadness is an emotion universally recognized across cultures, suggesting it plays an important functional role in regulating human behavior. Numerous adaptive explanations of persistent sadness interfering with daily functioning (hereafter "depression") have been proposed, but most do not explain frequent bidirectional associations between depression and greater immune activation. Here we test several predictions of the host defense hypothesis, which posits that depression is part of a broader coordinated evolved response to infection or tissue injury (i.e. "sickness behavior") that promotes energy conservation and reallocation to facilitate immune activation. In a high pathogen population of lean and relatively egalitarian Bolivian forager-horticulturalists, we test whether depression and its symptoms are associated with greater baseline concentration of immune biomarkers reliably associated with depression in Western populations (i.e. tumor necrosis factor alpha [TNF-α], interleukin-1 beta [IL-1β], interleukin-6 [IL-6], and C-reactive protein [CRP]). We also test whether greater pro-inflammatory cytokine responses to ex vivo antigen stimulation are associated with depression and its symptoms, which is expected if depression facilitates immune activation. These predictions are largely supported in a sample of older adult Tsimane (mean±SD age=53.2±11.0, range=34-85, n=649) after adjusting for potential confounders. Emotional, cognitive and somatic symptoms of depression are each associated with greater immune activation, both at baseline and in response to ex vivo stimulation. The association between depression and greater immune activation is therefore not unique to Western populations. While our findings are not predicted by other adaptive hypotheses of depression, they are not incompatible with those hypotheses and future research is necessary to isolate and test competing predictions. Copyright © 2015 Elsevier Inc. All rights reserved.

Bridging the gap between theoretical ecology and real ecosystems: modeling invertebrate community composition in streams.

PubMed

Schuwirth, Nele; Reichert, Peter

2013-02-01

For the first time, we combine concepts of theoretical food web modeling, the metabolic theory of ecology, and ecological stoichiometry with the use of functional trait databases to predict the coexistence of invertebrate taxa in streams. We developed a mechanistic model that describes growth, death, and respiration of different taxa dependent on various environmental influence factors to estimate survival or extinction. Parameter and input uncertainty is propagated to model results. Such a model is needed to test our current quantitative understanding of ecosystem structure and function and to predict effects of anthropogenic impacts and restoration efforts. The model was tested using macroinvertebrate monitoring data from a catchment of the Swiss Plateau. Even without fitting model parameters, the model is able to represent key patterns of the coexistence structure of invertebrates at sites varying in external conditions (litter input, shading, water quality). This confirms the suitability of the model concept. More comprehensive testing and resulting model adaptations will further increase the predictive accuracy of the model.

A Personalized Predictive Framework for Multivariate Clinical Time Series via Adaptive Model Selection.

PubMed

Liu, Zitao; Hauskrecht, Milos

2017-11-01

Building of an accurate predictive model of clinical time series for a patient is critical for understanding of the patient condition, its dynamics, and optimal patient management. Unfortunately, this process is not straightforward. First, patient-specific variations are typically large and population-based models derived or learned from many different patients are often unable to support accurate predictions for each individual patient. Moreover, time series observed for one patient at any point in time may be too short and insufficient to learn a high-quality patient-specific model just from the patient's own data. To address these problems we propose, develop and experiment with a new adaptive forecasting framework for building multivariate clinical time series models for a patient and for supporting patient-specific predictions. The framework relies on the adaptive model switching approach that at any point in time selects the most promising time series model out of the pool of many possible models, and consequently, combines advantages of the population, patient-specific and short-term individualized predictive models. We demonstrate that the adaptive model switching framework is very promising approach to support personalized time series prediction, and that it is able to outperform predictions based on pure population and patient-specific models, as well as, other patient-specific model adaptation strategies.

Predictors of adaptation in Icelandic and American families of young children with chronic asthma.

PubMed

Svavarsdottir, Erla Kolbrun; Rayens, Mary Kay; McCubbin, Marilyn

2005-01-01

The purposes of this international study were to determine the predictors of adaptation and to assess potential moderating effects of parents' sense of coherence and family hardiness on the relationship of severity of illness of a child with asthma and family and caregiving demands as predictors of family adaptation. For both parents, sense of coherence and family hardiness predicted family adaptation. Icelandic mothers perceived their family's adaptation more favorably than did their American counterparts. For the fathers, family demands predicted adaptation. Sense of coherence moderated the effect of family demands on adaptation for both parents. These findings underscore the importance of strengthening individual and family resiliency as a mechanism for improving family adaptation.

Phenotypic plasticity and specialization in clonal versus non-clonal plants: A data synthesis

NASA Astrophysics Data System (ADS)

Fazlioglu, Fatih; Bonser, Stephen P.

2016-11-01

Reproductive strategies can be associated with ecological specialization and generalization. Clonal plants produce lineages adapted to the maternal habitat that can lead to specialization. However, clonal plants frequently display high phenotypic plasticity (e.g. clonal foraging for resources), factors linked to ecological generalization. Alternately, sexual reproduction can be associated with generalization via increasing genetic variation or specialization through rapid adaptive evolution. Moreover, specializing to high or low quality habitats can determine how phenotypic plasticity is expressed in plants. The specialization hypothesis predicts that specialization to good environments results in high performance trait plasticity and specialization to bad environments results in low performance trait plasticity. The interplay between reproductive strategies, phenotypic plasticity, and ecological specialization is important for understanding how plants adapt to variable environments. However, we currently have a poor understanding of these relationships. In this study, we addressed following questions: 1) Is there a relationship between phenotypic plasticity, specialization, and reproductive strategies in plants? 2) Do good habitat specialists express greater performance trait plasticity than bad habitat specialists? We searched the literature for studies examining plasticity for performance traits and functional traits in clonal and non-clonal plant species from different habitat types. We found that non-clonal (obligate sexual) plants expressed greater performance trait plasticity and functional trait plasticity than clonal plants. That is, non-clonal plants exhibited a specialist strategy where they perform well only in a limited range of habitats. Clonal plants expressed less performance loss across habitats and a more generalist strategy. In addition, specialization to good habitats did not result in greater performance trait plasticity. This result was contrary to the predictions of the specialization hypothesis. Overall, reproductive strategies are associated with ecological specialization or generalization through phenotypic plasticity. While specialization is common in plant populations, the evolution of specialization does not control the nature of phenotypic plasticity as predicted under the specialization hypothesis.

Do individual differences in Iowa Gambling Task performance predict adaptive decision making for risky gains and losses?

PubMed

Weller, Joshua A; Levin, Irwin P; Bechara, Antoine

2010-02-01

We relate performance on the Iowa Gambling Task (IGT), a widely used, but complex, neuropsychological task of executive function in which mixed outcomes (gains and losses) are experienced together, to performance on a relatively simpler descriptive task, the Cups task, which isolates adaptive decision making for achieving gains and avoiding losses. We found that poor IGT performance was associated with suboptimal decision making on Cups, especially for risky losses, suggesting that losses are weighted more than gains in the IGT. These findings were significant beyond several notable gender differences in which men outperformed women. Implications for the neuropsychological study of risk are discussed.

Study of the convergence behavior of the complex kernel least mean square algorithm.

PubMed

Paul, Thomas K; Ogunfunmi, Tokunbo

2013-09-01

The complex kernel least mean square (CKLMS) algorithm is recently derived and allows for online kernel adaptive learning for complex data. Kernel adaptive methods can be used in finding solutions for neural network and machine learning applications. The derivation of CKLMS involved the development of a modified Wirtinger calculus for Hilbert spaces to obtain the cost function gradient. We analyze the convergence of the CKLMS with different kernel forms for complex data. The expressions obtained enable us to generate theory-predicted mean-square error curves considering the circularity of the complex input signals and their effect on nonlinear learning. Simulations are used for verifying the analysis results.

Towards psychologically adaptive brain-computer interfaces

NASA Astrophysics Data System (ADS)

Myrden, A.; Chau, T.

2016-12-01

Objective. Brain-computer interface (BCI) performance is sensitive to short-term changes in psychological states such as fatigue, frustration, and attention. This paper explores the design of a BCI that can adapt to these short-term changes. Approach. Eleven able-bodied individuals participated in a study during which they used a mental task-based EEG-BCI to play a simple maze navigation game while self-reporting their perceived levels of fatigue, frustration, and attention. In an offline analysis, a regression algorithm was trained to predict changes in these states, yielding Pearson correlation coefficients in excess of 0.45 between the self-reported and predicted states. Two means of fusing the resultant mental state predictions with mental task classification were investigated. First, single-trial mental state predictions were used to predict correct classification by the BCI during each trial. Second, an adaptive BCI was designed that retrained a new classifier for each testing sample using only those training samples for which predicted mental state was similar to that predicted for the current testing sample. Main results. Mental state-based prediction of BCI reliability exceeded chance levels. The adaptive BCI exhibited significant, but practically modest, increases in classification accuracy for five of 11 participants and no significant difference for the remaining six despite a smaller average training set size. Significance. Collectively, these findings indicate that adaptation to psychological state may allow the design of more accurate BCIs.

Predictive and Reactive Locomotor Adaptability in Healthy Elderly: A Systematic Review and Meta-Analysis.

PubMed

Bohm, Sebastian; Mademli, Lida; Mersmann, Falk; Arampatzis, Adamantios

2015-12-01

Locomotor adaptability is based on the implementation of error-feedback information from previous perturbations to predictively adapt to expected perturbations (feedforward) and to facilitate reactive responses in recurring unexpected perturbations ('savings'). The effect of aging on predictive and reactive adaptability is yet unclear. However, such understanding is fundamental for the design and application of effective interventions targeting fall prevention. We systematically searched the Web of Science, MEDLINE, Embase and Science Direct databases as well as the reference lists of the eligible articles. A study was included if it addressed an investigation of the locomotor adaptability in response to repeated mechanical movement perturbations of healthy older adults (≥60 years). The weighted average effect size (WAES) of the general adaptability (adaptive motor responses to repeated perturbations) as well as predictive (after-effects) and reactive adaptation (feedback responses to a recurring unexpected perturbation) was calculated and tested for an overall effect. A subgroup analysis was performed regarding the factor age group [i.e., young (≤35 years) vs. older adults]. Furthermore, the methodological study quality was assessed. The review process yielded 18 studies [1009 participants, 613 older adults (70 ± 4 years)], which used various kinds of locomotor tasks and perturbations. The WAES for the general locomotor adaptability was 1.21 [95% confidence interval (CI) 0.68-1.74, n = 11] for the older and 1.39 (95% CI 0.90-1.89, n = 10) for the young adults with a significant (p < 0.05) overall effect for both age groups and no significant subgroup differences. Similar results were found for the predictive (older: WAES 1.10, 95% CI 0.37-1.83, n = 8; young: WAES 1.54, 95% CI 0.11-2.97, n = 7) and reactive (older: WAES 1.09, 95% CI 0.22-1.96, n = 5; young: WAES 1.35, 95% CI 0.60-2.09, n = 5) adaptation featuring significant (p < 0.05) overall effects without subgroup differences. The average score of the methodological quality was 67 ± 8 %. The present meta-analysis provides elaborate statistical evidence that locomotor adaptability in general and predictive and reactive adaptation in particular remain highly effective in the elderly, showing only minor, not statistically significant age-related deficits. Consequently, interventions which use adaptation and learning paradigms including the application of the mechanisms responsible for an effective predictive and reactive dynamic stability control may progressively improve older adults' recovery performance and, thus, reduce their risk of falling.

Children’s dynamic RSA change during anger and its relations with parenting, temperament, and control of aggression☆

PubMed Central

Miller, Jonas G.; Chocol, Caroline; Nuselovici, Jacob N.; Utendale, William T.; Simard, Melissa; Hastings, Paul D.

2014-01-01

This study examined the moderating effects of child temperament on the association between maternal socialization and 4–6-year-old children’s dynamic respiratory sinus arrhythmia (RSA) change in response to anger-themed emotional materials (N = 180). We used latent growth curve modeling to explore adaptive patterns of dynamic RSA change in response to anger. Greater change in RSA during anger-induction, characterized by more initial RSA suppression and a subsequent return to baseline, was related to children’s better regulation of aggression. For anger-themed materials, low levels of authoritarian parenting predicted more RSA suppression and recovery for more anger-prone children, whereas more authoritative parenting predicted more RSA suppression and recovery for less anger-prone children. These findings suggest that children’s adaptive patterns of dynamic RSA change can be characterized by latent growth curve modeling, and that these patterns may be differentially shaped by parent socialization experiences as a function of child temperament. PMID:23274169

Children's dynamic RSA change during anger and its relations with parenting, temperament, and control of aggression.

PubMed

Miller, Jonas G; Chocol, Caroline; Nuselovici, Jacob N; Utendale, William T; Simard, Melissa; Hastings, Paul D

2013-02-01

This study examined the moderating effects of child temperament on the association between maternal socialization and 4-6-year-old children's dynamic respiratory sinus arrhythmia (RSA) change in response to anger-themed emotional materials (N=180). We used latent growth curve modeling to explore adaptive patterns of dynamic RSA change in response to anger. Greater change in RSA during anger-induction, characterized by more initial RSA suppression and a subsequent return to baseline, was related to children's better regulation of aggression. For anger-themed materials, low levels of authoritarian parenting predicted more RSA suppression and recovery for more anger-prone children, whereas more authoritative parenting predicted more RSA suppression and recovery for less anger-prone children. These findings suggest that children's adaptive patterns of dynamic RSA change can be characterized by latent growth curve modeling, and that these patterns may be differentially shaped by parent socialization experiences as a function of child temperament. Copyright © 2013 Elsevier B.V. All rights reserved.

Fetal programming by maternal stress: Insights from a conflict perspective.

PubMed

Del Giudice, Marco

2012-10-01

Maternal stress during pregnancy has pervasive effects on the offspring's physiology and behavior, including the development of anxious, reactive temperament and increased stress responsivity. These outcomes can be seen as the result of adaptive developmental plasticity: maternal stress hormones carry useful information about the state of the external world, which can be used by the developing fetus to match its phenotype to the predicted environment. This account, however, neglects the inherent conflict of interest between mother and fetus about the outcomes of fetal programming. The aim of this paper is to extend the adaptive model of prenatal stress by framing mother-fetus interactions in an evolutionary conflict perspective. In the paper, I show how a conflict perspective provides many new insights in the functions and mechanisms of fetal programming, with particular emphasis on human pregnancy. I then take advantage of those insights to make sense of some puzzling features of maternal and fetal physiology and generate novel empirical predictions. Copyright © 2012 Elsevier Ltd. All rights reserved.

High-confidence prediction of global interactomes based on genome-wide coevolutionary networks

PubMed Central

Juan, David; Pazos, Florencio; Valencia, Alfonso

2008-01-01

Interacting or functionally related protein families tend to have similar phylogenetic trees. Based on this observation, techniques have been developed to predict interaction partners. The observed degree of similarity between the phylogenetic trees of two proteins is the result of many different factors besides the actual interaction or functional relationship between them. Such factors influence the performance of interaction predictions. One aspect that can influence this similarity is related to the fact that a given protein interacts with many others, and hence it must adapt to all of them. Accordingly, the interaction or coadaptation signal within its tree is a composite of the influence of all of the interactors. Here, we introduce a new estimator of coevolution to overcome this and other problems. Instead of relying on the individual value of tree similarity between two proteins, we use the whole network of similarities between all of the pairs of proteins within a genome to reassess the similarity of that pair, thereby taking into account its coevolutionary context. We show that this approach offers a substantial improvement in interaction prediction performance, providing a degree of accuracy/coverage comparable with, or in some cases better than, that of experimental techniques. Moreover, important information on the structure, function, and evolution of macromolecular complexes can be inferred with this methodology. PMID:18199838

High-confidence prediction of global interactomes based on genome-wide coevolutionary networks.

PubMed

Juan, David; Pazos, Florencio; Valencia, Alfonso

2008-01-22

Interacting or functionally related protein families tend to have similar phylogenetic trees. Based on this observation, techniques have been developed to predict interaction partners. The observed degree of similarity between the phylogenetic trees of two proteins is the result of many different factors besides the actual interaction or functional relationship between them. Such factors influence the performance of interaction predictions. One aspect that can influence this similarity is related to the fact that a given protein interacts with many others, and hence it must adapt to all of them. Accordingly, the interaction or coadaptation signal within its tree is a composite of the influence of all of the interactors. Here, we introduce a new estimator of coevolution to overcome this and other problems. Instead of relying on the individual value of tree similarity between two proteins, we use the whole network of similarities between all of the pairs of proteins within a genome to reassess the similarity of that pair, thereby taking into account its coevolutionary context. We show that this approach offers a substantial improvement in interaction prediction performance, providing a degree of accuracy/coverage comparable with, or in some cases better than, that of experimental techniques. Moreover, important information on the structure, function, and evolution of macromolecular complexes can be inferred with this methodology.

Global brain dynamics during social exclusion predict subsequent behavioral conformity

PubMed Central

Wasylyshyn, Nick; Hemenway Falk, Brett; Garcia, Javier O; Cascio, Christopher N; O’Donnell, Matthew Brook; Bingham, C Raymond; Simons-Morton, Bruce; Vettel, Jean M; Falk, Emily B

2018-01-01

Abstract Individuals react differently to social experiences; for example, people who are more sensitive to negative social experiences, such as being excluded, may be more likely to adapt their behavior to fit in with others. We examined whether functional brain connectivity during social exclusion in the fMRI scanner can be used to predict subsequent conformity to peer norms. Adolescent males (n = 57) completed a two-part study on teen driving risk: a social exclusion task (Cyberball) during an fMRI session and a subsequent driving simulator session in which they drove alone and in the presence of a peer who expressed risk-averse or risk-accepting driving norms. We computed the difference in functional connectivity between social exclusion and social inclusion from each node in the brain to nodes in two brain networks, one previously associated with mentalizing (medial prefrontal cortex, temporoparietal junction, precuneus, temporal poles) and another with social pain (dorsal anterior cingulate cortex, anterior insula). Using predictive modeling, this measure of global connectivity during exclusion predicted the extent of conformity to peer pressure during driving in the subsequent experimental session. These findings extend our understanding of how global neural dynamics guide social behavior, revealing functional network activity that captures individual differences. PMID:29529310

Novel Near-Lossless Compression Algorithm for Medical Sequence Images with Adaptive Block-Based Spatial Prediction.

PubMed

Song, Xiaoying; Huang, Qijun; Chang, Sheng; He, Jin; Wang, Hao

2016-12-01

To address the low compression efficiency of lossless compression and the low image quality of general near-lossless compression, a novel near-lossless compression algorithm based on adaptive spatial prediction is proposed for medical sequence images for possible diagnostic use in this paper. The proposed method employs adaptive block size-based spatial prediction to predict blocks directly in the spatial domain and Lossless Hadamard Transform before quantization to improve the quality of reconstructed images. The block-based prediction breaks the pixel neighborhood constraint and takes full advantage of the local spatial correlations found in medical images. The adaptive block size guarantees a more rational division of images and the improved use of the local structure. The results indicate that the proposed algorithm can efficiently compress medical images and produces a better peak signal-to-noise ratio (PSNR) under the same pre-defined distortion than other near-lossless methods.

A Novel Approach to Adaptive Flow Separation Control

DTIC Science & Technology

2016-09-03

particular, it considers control of flow separation over a NACA-0025 airfoil using microjet actuators and develops Adaptive Sampling Based Model...Predictive Control ( Adaptive SBMPC), a novel approach to Nonlinear Model Predictive Control that applies the Minimal Resource Allocation Network...Distribution Unlimited UU UU UU UU 03-09-2016 1-May-2013 30-Apr-2016 Final Report: A Novel Approach to Adaptive Flow Separation Control The views, opinions

A predictive model to inform adaptive management of double-crested cormorants and fisheries in Michigan

USGS Publications Warehouse

Tsehaye, Iyob; Jones, Michael L.; Irwin, Brian J.; Fielder, David G.; Breck, James E.; Luukkonen, David R.

2015-01-01

The proliferation of double-crested cormorants (DCCOs; Phalacrocorax auritus) in North America has raised concerns over their potential negative impacts on game, cultured and forage fishes, island and terrestrial resources, and other colonial water birds, leading to increased public demands to reduce their abundance. By combining fish surplus production and bird functional feeding response models, we developed a deterministic predictive model representing bird–fish interactions to inform an adaptive management process for the control of DCCOs in multiple colonies in Michigan. Comparisons of model predictions with observations of changes in DCCO numbers under management measures implemented from 2004 to 2012 suggested that our relatively simple model was able to accurately reconstruct past DCCO population dynamics. These comparisons helped discriminate among alternative parameterizations of demographic processes that were poorly known, especially site fidelity. Using sensitivity analysis, we also identified remaining critical uncertainties (mainly in the spatial distributions of fish vs. DCCO feeding areas) that can be used to prioritize future research and monitoring needs. Model forecasts suggested that continuation of existing control efforts would be sufficient to achieve long-term DCCO control targets in Michigan and that DCCO control may be necessary to achieve management goals for some DCCO-impacted fisheries in the state. Finally, our model can be extended by accounting for parametric or ecological uncertainty and including more complex assumptions on DCCO–fish interactions as part of the adaptive management process.

Predictable and Adaptable Complex Real-Time Systems

DTIC Science & Technology

1993-09-30

Predictable and Adaptable Complex Real - Time Systems Grant or Contract Number: N00014-92-J-1048 Reporting Period: 1 Oct 91 - 30 Sep 93 1... Real - Time Systems Grant or Contract Number: N00014-92-J-1048 Reporting Period: 1 Oct 91 - 30 Sep 93 2. Summary of Technical Progress Our...cs.umass.edu Grant or Contract Title: Predictable and Adaptable Complex Real - Time Systems Grant or Contract Number: N00014-92-J-1048 Reporting Period: 1 Oct 91

Clinical prediction models for mortality and functional outcome following ischemic stroke: A systematic review and meta-analysis

PubMed Central

Crayton, Elise; Wolfe, Charles; Douiri, Abdel

2018-01-01

Objective We aim to identify and critically appraise clinical prediction models of mortality and function following ischaemic stroke. Methods Electronic databases, reference lists, citations were searched from inception to September 2015. Studies were selected for inclusion, according to pre-specified criteria and critically appraised by independent, blinded reviewers. The discrimination of the prediction models was measured by the area under the curve receiver operating characteristic curve or c-statistic in random effects meta-analysis. Heterogeneity was measured using I2. Appropriate appraisal tools and reporting guidelines were used in this review. Results 31395 references were screened, of which 109 articles were included in the review. These articles described 66 different predictive risk models. Appraisal identified poor methodological quality and a high risk of bias for most models. However, all models precede the development of reporting guidelines for prediction modelling studies. Generalisability of models could be improved, less than half of the included models have been externally validated(n = 27/66). 152 predictors of mortality and 192 predictors and functional outcome were identified. No studies assessing ability to improve patient outcome (model impact studies) were identified. Conclusions Further external validation and model impact studies to confirm the utility of existing models in supporting decision-making is required. Existing models have much potential. Those wishing to predict stroke outcome are advised to build on previous work, to update and adapt validated models to their specific contexts opposed to designing new ones. PMID:29377923

Subjective Technology Adaptivity Predicts Technology Use in Old Age.

PubMed

Kamin, Stefan T; Lang, Frieder R; Beyer, Anja

2017-01-01

To date, not much is known about the psychological and motivational factors underlying technology use in late life. What are the interindividual determinants that lead older adults to invest in using technological innovations despite the age-related physiological changes that impose challenges on behavioral plasticity in everyday life? This research explores interindividual differences in subjective technology adaptivity - a general technology-related motivational resource that accounts for technology use in late life. More specifically, we investigate the influence of this factor relative to demographic characteristics, personality traits, and functional limitations in a longitudinal sample of community-dwelling older adults. We report results from a paper-and-pencil survey with 136 older adults between 59 and 92 years of age (mean = 71.4, SD = 7.4). Of those participants, 77 participated in a 2-year follow-up. We assessed self-reports of technology use, subjective technology adaptivity, functional limitations, and the personality traits openness to new experiences and neuroticism. Higher levels of subjective technology adaptivity were associated with technology use at the first measurement as well as increased use over the course of 2 years. Subjective technology adaptivity is a significant predictor of technology use in old age. Our findings contribute to improving the understanding of interindividual differences when using technological innovation in late life. Moreover, our findings have implications in the context of user involvement and may contribute to the successful development of innovative technology for older adults. © 2017 S. Karger AG, Basel.

Efficient simulations of large-scale structure in modified gravity cosmologies with comoving Lagrangian acceleration

NASA Astrophysics Data System (ADS)

Valogiannis, Georgios; Bean, Rachel

2017-05-01

We implement an adaptation of the cola approach, a hybrid scheme that combines Lagrangian perturbation theory with an N-body approach, to model nonlinear collapse in chameleon and symmetron modified gravity models. Gravitational screening is modeled effectively through the attachment of a suppression factor to the linearized Klein-Gordon equations. The adapted cola approach is benchmarked, with respect to an N-body code both for the Λ cold dark matter (Λ CDM ) scenario and for the modified gravity theories. It is found to perform well in the estimation of the dark matter power spectra, with consistency of 1% to k ˜2.5 h /Mpc . Redshift space distortions are shown to be effectively modeled through a Lorentzian parametrization with a velocity dispersion fit to the data. We find that cola performs less well in predicting the halo mass functions but has consistency, within 1 σ uncertainties of our simulations, in the relative changes to the mass function induced by the modified gravity models relative to Λ CDM . The results demonstrate that cola, proposed to enable accurate and efficient, nonlinear predictions for Λ CDM , can be effectively applied to a wider set of cosmological scenarios, with intriguing properties, for which clustering behavior needs to be understood for upcoming surveys such as LSST, DESI, Euclid, and WFIRST.

African American English-speaking students: a longitudinal examination of style shifting from kindergarten through second grade.

PubMed

Craig, Holly K; Kolenic, Giselle E; Hensel, Stephanie L

2014-02-01

The purpose of this longitudinal study was twofold: to examine shifting from African American English (AAE) to mainstream American English (MAE) across the early elementary grades, when students are first exposed to formal instruction in reading; and to examine how metalinguistic and cognitive variables influenced the students' dialectal adaptations from AAE to MAE in a literacy context with higher expectations for MAE. Participants were 102 typically developing AAE-speaking students enrolled in public schools in the northern Midwest. They were enrolled in the project at kindergarten and tested 3 times a year, for 3 years. Approximately half were male and half female, and two-thirds were from low socioeconomic status homes. A style shifting coefficient (SSC) was created to measure amounts of dialect change between contexts and over time by individuals. Some students shifted to MAE in literacy contexts, and shifting was not related to grade. Metalinguistic skills and SSC predicted reading, and metalinguistic skills predicted the SSC at 2nd grade. The findings indicated that cognitive executive functions may contribute to the SSC. The results provide strong support for the dialect shifting-reading achievement hypothesis and indicated that metalinguistic and perhaps executive functioning are important influences on this linguistic adaptation.

Proteomic analysis of the intestinal adaptation response reveals altered expression of fatty acid binding proteins following massive small bowel resection.

PubMed

Stephens, Andrew N; Pereira-Fantini, Prue M; Wilson, Guineva; Taylor, Russell G; Rainczuk, Adam; Meehan, Katie L; Sourial, Magdy; Fuller, Peter J; Stanton, Peter G; Robertson, David M; Bines, Julie E

2010-03-05

Intestinal adaptation in response to the loss of the small intestine is essential to restore enteral autonomy in patients who have undergone massive small bowel resection (MSBR). In a proportion of patients, intestinal function is not restored, resulting in chronic intestinal failure (IF). Early referral of such patients for transplant provides the best prognosis; however, the molecular mechanisms underlying intestinal adaptation remain elusive and there is currently no convenient marker to predict whether patients will develop IF. We have investigated the adaptation response in a well-characterized porcine model of intestinal adaptation. 2D DIGE analysis of ileal epithelium from piglets recovering from massive small bowel resection (MSBR) identified over 60 proteins that changed specifically in MSBR animals relative to nonoperational or sham-operated controls. Three fatty acid binding proteins (L-FABP, FABP-6, and I-FABP) showed changes in MSBR animals. The expression changes and localization of each FABP were validated by immunoblotting and immunohistochemical analysis. FABP expression changes in MSBR animals occurred concurrently with altered triglyceride and bile acid metabolism as well as weight gain. The observed FABP expression changes in the ileal epithelium occur as part of the intestinal adaptation response and could provide a clinically useful marker to evaluate adaptation following MSBR.

Predicting coral bleaching hotspots: the role of regional variability in thermal stress and potential adaptation rates

NASA Astrophysics Data System (ADS)

Teneva, Lida; Karnauskas, Mandy; Logan, Cheryl A.; Bianucci, Laura; Currie, Jock C.; Kleypas, Joan A.

2012-03-01

Sea surface temperature fields (1870-2100) forced by CO2-induced climate change under the IPCC SRES A1B CO2 scenario, from three World Climate Research Programme Coupled Model Intercomparison Project Phase 3 (WCRP CMIP3) models (CCSM3, CSIRO MK 3.5, and GFDL CM 2.1), were used to examine how coral sensitivity to thermal stress and rates of adaption affect global projections of coral-reef bleaching. The focus of this study was two-fold, to: (1) assess how the impact of Degree-Heating-Month (DHM) thermal stress threshold choice affects potential bleaching predictions and (2) examine the effect of hypothetical adaptation rates of corals to rising temperature. DHM values were estimated using a conventional threshold of 1°C and a variability-based threshold of 2σ above the climatological maximum Coral adaptation rates were simulated as a function of historical 100-year exposure to maximum annual SSTs with a dynamic rather than static climatological maximum based on the previous 100 years, for a given reef cell. Within CCSM3 simulations, the 1°C threshold predicted later onset of mild bleaching every 5 years for the fraction of reef grid cells where 1°C > 2σ of the climatology time series of annual SST maxima (1961-1990). Alternatively, DHM values using both thresholds, with CSIRO MK 3.5 and GFDL CM 2.1 SSTs, did not produce drastically different onset timing for bleaching every 5 years. Across models, DHMs based on 1°C thermal stress threshold show the most threatened reefs by 2100 could be in the Central and Western Equatorial Pacific, whereas use of the variability-based threshold for DHMs yields the Coral Triangle and parts of Micronesia and Melanesia as bleaching hotspots. Simulations that allow corals to adapt to increases in maximum SST drastically reduce the rates of bleaching. These findings highlight the importance of considering the thermal stress threshold in DHM estimates as well as potential adaptation models in future coral bleaching projections.

Modeling spatial tuning of adaptation of the angular vestibulo-ocular reflex

PubMed Central

Yakushin, Sergei B.

2012-01-01

Gain adaptation of the yaw angular vestibular ocular reflex (aVOR) induced in side-down positions has gravity-independent (global) and -dependent (localized) components. When the head oscillation angles are small during adaptation, localized gain changes are maximal in the approximate position of adaptation. Concurrently, polarization vectors of canal–otolith vestibular neurons adapt their orientations during these small-angle adaptation paradigms. Whether there is orientation adaptation with large amplitude head oscillations, when the head is not localized to a specific position, is unknown. Yaw aVOR gains were decreased by oscillating monkeys about a yaw axis in a side-down position in a subject–stationary visual surround for 2 h. Amplitudes of head oscillation ranged from 15° to 180°. The yaw aVOR gain was tested in darkness at 0.5 Hz, with small angles of oscillation (±15°) while upright and in tilted positions. The peak value of the gain change was highly tuned for small angular oscillations during adaptation and significantly broadened with larger oscillation angles during adaptation. When the orientation of the polarization vectors associated with the gravity-dependent component of the neural network model was adapted toward the direction of gravity, it predicted the localized learning for small angles and the broadening when the orientation adaptation was diminished. The model-based analysis suggests that the otolith orientation adaptation plays an important role in the localized behavior of aVOR as a function of gravity and in regulating the relationship between global and localized adaptation. PMID:22660376

The geography of sex-specific selection, local adaptation, and sexual dimorphism.

PubMed

Connallon, Tim

2015-09-01

Local adaptation and sexual dimorphism are iconic evolutionary scenarios of intraspecific adaptive differentiation in the face of gene flow. Although theory has traditionally considered local adaptation and sexual dimorphism as conceptually distinct processes, emerging data suggest that they often act concurrently during evolutionary diversification. Here, I merge theories of local adaptation in space and sex-specific adaptation over time, and show that their confluence yields several new predictions about the roles of context-specific selection, migration, and genetic correlations, in adaptive diversification. I specifically revisit two influential predictions from classical studies of clinal adaptation and sexual dimorphism: (1) that local adaptation should decrease with distance from the species' range center and (2) that opposing directional selection between the sexes (sexual antagonism) should inevitably accompany the evolution of sexual dimorphism. I show that both predictions can break down under clinally varying selection. First, the geography of local adaptation can be sexually dimorphic, with locations of relatively high local adaptation differing profoundly between the sexes. Second, the intensity of sexual antagonism varies across the species' range, with subpopulations near the range center representing hotspots for antagonistic selection. The results highlight the context-dependent roles of migration versus sexual conflict as primary constraints to adaptive diversification. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

Individual predictions of eye-movements with dynamic scenes

NASA Astrophysics Data System (ADS)

Barth, Erhardt; Drewes, Jan; Martinetz, Thomas

2003-06-01

We present a model that predicts saccadic eye-movements and can be tuned to a particular human observer who is viewing a dynamic sequence of images. Our work is motivated by applications that involve gaze-contingent interactive displays on which information is displayed as a function of gaze direction. The approach therefore differs from standard approaches in two ways: (1) we deal with dynamic scenes, and (2) we provide means of adapting the model to a particular observer. As an indicator for the degree of saliency we evaluate the intrinsic dimension of the image sequence within a geometric approach implemented by using the structure tensor. Out of these candidate saliency-based locations, the currently attended location is selected according to a strategy found by supervised learning. The data are obtained with an eye-tracker and subjects who view video sequences. The selection algorithm receives candidate locations of current and past frames and a limited history of locations attended in the past. We use a linear mapping that is obtained by minimizing the quadratic difference between the predicted and the actually attended location by gradient descent. Being linear, the learned mapping can be quickly adapted to the individual observer.

Predicting plant uptake of cadmium: validated with long-term contaminated soils.

PubMed

Lamb, Dane T; Kader, Mohammed; Ming, Hui; Wang, Liang; Abbasi, Sedigheh; Megharaj, Mallavarapu; Naidu, Ravi

2016-10-01

Cadmium accumulates in plant tissues at low soil loadings and is a concern for human health. Yet at higher levels it is also of concern for ecological receptors. We determined Cd partitioning constants for 41 soils to examine the role of soil properties controlling Cd partitioning and plant uptake. From a series of sorption and dose response studies, transfer functions were developed for predicting Cd uptake in Cucumis sativa L. (cucumber). The parameter log K f was predicted with soil pH ca , logCEC and log OC. Transfer of soil pore-water Cd 2+ to shoots was described with a power function (R 2  = 0.73). The dataset was validated with 13 long-term contaminated soils (plus 2 control soils) ranging in Cd concentration from 0.2 to 300 mg kg -1 . The series of equations predicting Cd shoot from pore-water Cd 2+ were able to predict the measured data in the independent dataset (root mean square error = 2.2). The good relationship indicated that Cd uptake to cucumber shoots could be predicted with Cd pore and Cd 2+ without other pore-water parameters such as pH or Ca 2+ . The approach may be adapted to a range of plant species.

Acute stress alters transcript expression pattern and reduces processing of proBDNF to mature BDNF in Dicentrarchus labrax

PubMed Central

2010-01-01

Background Stress involves alterations of brain functioning that may precipitate to mood disorders. The neurotrophin Brain Derived Neurotrophic Factor (BDNF) has recently been involved in stress-induced adaptation. BDNF is a key regulator of neuronal plasticity and adaptive processes. Regulation of BDNF is complex and may reflect not only stress-specific mechanisms but also hormonal and emotional responses. For this reason we used, as an animal model of stress, a fish whose brain organization is very similar to that of higher vertebrates, but is generally considered free of emotional reactions. Results We provide a comprehensive characterization of BDNF gene in the Dicentrarchus labrax and its transcriptional, translational and post-translational regulation following acute stress. While total BDNF mRNA levels are unchanged, BDNF transcripts 1c and 1d resulted down regulated after acute stress. Acute stress induces also a significant increase in proBDNF levels and reduction in mature BDNF suggesting altered regulation of proBDNF proteolytic processing. Notably, we provide here the first evidence that fishes possess a simplified proteolytic regulation of BDNF since the pro28Kda form, generated by the SKI-1 protease in mammals, is absent in fishes because the cleavage site has first emerged in reptilians. Finally, we show that the proBDNF/totBDNF ratio is a highly predictive novel quantitative biomarker to detect stress in fishes with sensitivity = 100%, specificity = 87%, and Negative Predictive Value = 100%. Conclusion The high predictivity of proBDNF/totBDNF ratio for stress in lower vertebrates indicates that processing of BDNF is a central mechanism in adaptation to stress and predicts that a similar regulation of pro/mature BDNF has likely been conserved throughout evolution of vertebrates from fish to man. PMID:20074340

Acute stress alters transcript expression pattern and reduces processing of proBDNF to mature BDNF in Dicentrarchus labrax.

PubMed

Tognoli, Chiara; Rossi, Federica; Di Cola, Francesco; Baj, Gabriele; Tongiorgi, Enrico; Terova, Genciana; Saroglia, Marco; Bernardini, Giovanni; Gornati, Rosalba

2010-01-14

Stress involves alterations of brain functioning that may precipitate to mood disorders. The neurotrophin Brain Derived Neurotrophic Factor (BDNF) has recently been involved in stress-induced adaptation. BDNF is a key regulator of neuronal plasticity and adaptive processes. Regulation of BDNF is complex and may reflect not only stress-specific mechanisms but also hormonal and emotional responses. For this reason we used, as an animal model of stress, a fish whose brain organization is very similar to that of higher vertebrates, but is generally considered free of emotional reactions. We provide a comprehensive characterization of BDNF gene in the Dicentrarchus labrax and its transcriptional, translational and post-translational regulation following acute stress. While total BDNF mRNA levels are unchanged, BDNF transcripts 1c and 1d resulted down regulated after acute stress. Acute stress induces also a significant increase in proBDNF levels and reduction in mature BDNF suggesting altered regulation of proBDNF proteolytic processing. Notably, we provide here the first evidence that fishes possess a simplified proteolytic regulation of BDNF since the pro28Kda form, generated by the SKI-1 protease in mammals, is absent in fishes because the cleavage site has first emerged in reptilians. Finally, we show that the proBDNF/totBDNF ratio is a highly predictive novel quantitative biomarker to detect stress in fishes with sensitivity = 100%, specificity = 87%, and Negative Predictive Value = 100%. The high predictivity of proBDNF/totBDNF ratio for stress in lower vertebrates indicates that processing of BDNF is a central mechanism in adaptation to stress and predicts that a similar regulation of pro/mature BDNF has likely been conserved throughout evolution of vertebrates from fish to man.

Evolution of the CRISPR-Cas adaptive immunity systems in prokaryotes: models and observations on virus-host coevolution.

PubMed

Koonin, Eugene V; Wolf, Yuri I

2015-01-01

CRISPR-Cas is an adaptive immunity system in prokaryotes that functions via a unique mechanism which involves incorporation of foreign DNA fragments into CRISPR arrays and subsequent utilization of transcripts of these inserts (known as spacers) as guide RNAs to cleave the cognate selfish element genome. Multiple attempts have been undertaken to explore the coevolution of viruses and microbial hosts carrying CRISPR-Cas using mathematical models that employ either systems of differential equations or an agent-based approach, or combinations thereof. Analysis of these models reveals highly complex co-evolutionary dynamics that ensues from the combination of the heritability of the CRISPR-mediated adaptive immunity with the existence of different degrees of immunity depending on the number of cognate spacers and the cost of carrying a CRISPR-Cas locus. Depending on the details of the models, a variety of testable, sometimes conflicting predictions have been made on the dependence of the degree of immunity and the benefit of maintaining CRISPR-Cas on the abundance and diversity of hosts and viruses. Some of these predictions have already been directly validated experimentally. In particular, both the reality of the virus-host arms race, with viruses escaping resistance and hosts reacquiring it through the capture of new spacers, and the fitness cost of CRISPR-Cas due to the curtailment of beneficial HGT have been reproduced in the laboratory. However, to test the predictions of the models more specifically, detailed studies of coevolving populations of microbes and viruses both in nature and in the laboratory are essential. Such analyses are expected to yield disagreements with the predictions of the current, oversimplified models and to trigger a new round of theoretical developments.

Ecological validity of the screening module and the Daily Living tests of the Neuropsychological Assessment Battery using the Mayo-Portland Adaptability Inventory-4 in postacute brain injury rehabilitation.

PubMed

Zgaljardic, Dennis J; Yancy, Sybil; Temple, Richard O; Watford, Monica F; Miller, Rebekah

2011-11-01

The assessment of ecological validity of neuropsychological measures is an area of growing interest, particularly in the postacute brain injury rehabilitation (PABIR) setting, as there is an increasing demand for clinicians to address functional and real-world outcomes. In the current study, we assessed the predictive value of the Screening module and the Daily Living tests of the Neuropsychological Assessment Battery (NAB) using clinician ratings from the Mayo-Portland Adaptability Inventory-4 (MPAI-4) in patients with moderate to severe traumatic brain injury. Forty-seven individuals were each administered the NAB Screening module (NAB-SM) and the NAB Daily Living (NAB-DL) tests following admission to a residential PABIR program. MPAI-4 ratings were also obtained at admission. Linear regression analysis was used to examine the association between these functional and neuropsychological assessment measures. We replicated prior work (Temple at al., 2009) and expanded evidence for the ecological validity of the NAB-SM. Furthermore, our findings support the ecological validity of the NAB-DL Bill Payment, Judgment, and Map Reading tests with regards to functional skills and real-world activities. The current study supports prior work from our lab assessing the predictive value of the NAB-SM, as well as provides evidence for the ecological validity for select NAB-DL tests in patients with moderate to severe traumatic brain injury admitted to a residential PABIR program.

Critical Analysis of Cluster Models and Exchange-Correlation Functionals for Calculating Magnetic Shielding in Molecular Solids.

PubMed

Holmes, Sean T; Iuliucci, Robbie J; Mueller, Karl T; Dybowski, Cecil

2015-11-10

Calculations of the principal components of magnetic-shielding tensors in crystalline solids require the inclusion of the effects of lattice structure on the local electronic environment to obtain significant agreement with experimental NMR measurements. We assess periodic (GIPAW) and GIAO/symmetry-adapted cluster (SAC) models for computing magnetic-shielding tensors by calculations on a test set containing 72 insulating molecular solids, with a total of 393 principal components of chemical-shift tensors from 13C, 15N, 19F, and 31P sites. When clusters are carefully designed to represent the local solid-state environment and when periodic calculations include sufficient variability, both methods predict magnetic-shielding tensors that agree well with experimental chemical-shift values, demonstrating the correspondence of the two computational techniques. At the basis-set limit, we find that the small differences in the computed values have no statistical significance for three of the four nuclides considered. Subsequently, we explore the effects of additional DFT methods available only with the GIAO/cluster approach, particularly the use of hybrid-GGA functionals, meta-GGA functionals, and hybrid meta-GGA functionals that demonstrate improved agreement in calculations on symmetry-adapted clusters. We demonstrate that meta-GGA functionals improve computed NMR parameters over those obtained by GGA functionals in all cases, and that hybrid functionals improve computed results over the respective pure DFT functional for all nuclides except 15N.

An Upside to Reward Sensitivity: The Hippocampus Supports Enhanced Reinforcement Learning in Adolescence.

PubMed

Davidow, Juliet Y; Foerde, Karin; Galván, Adriana; Shohamy, Daphna

2016-10-05

Adolescents are notorious for engaging in reward-seeking behaviors, a tendency attributed to heightened activity in the brain's reward systems during adolescence. It has been suggested that reward sensitivity in adolescence might be adaptive, but evidence of an adaptive role has been scarce. Using a probabilistic reinforcement learning task combined with reinforcement learning models and fMRI, we found that adolescents showed better reinforcement learning and a stronger link between reinforcement learning and episodic memory for rewarding outcomes. This behavioral benefit was related to heightened prediction error-related BOLD activity in the hippocampus and to stronger functional connectivity between the hippocampus and the striatum at the time of reinforcement. These findings reveal an important role for the hippocampus in reinforcement learning in adolescence and suggest that reward sensitivity in adolescence is related to adaptive differences in how adolescents learn from experience. Copyright © 2016 Elsevier Inc. All rights reserved.

A new interferential multispectral image compression algorithm based on adaptive classification and curve-fitting

NASA Astrophysics Data System (ADS)

Wang, Ke-Yan; Li, Yun-Song; Liu, Kai; Wu, Cheng-Ke

2008-08-01

A novel compression algorithm for interferential multispectral images based on adaptive classification and curve-fitting is proposed. The image is first partitioned adaptively into major-interference region and minor-interference region. Different approximating functions are then constructed for two kinds of regions respectively. For the major interference region, some typical interferential curves are selected to predict other curves. These typical curves are then processed by curve-fitting method. For the minor interference region, the data of each interferential curve are independently approximated. Finally the approximating errors of two regions are entropy coded. The experimental results show that, compared with JPEG2000, the proposed algorithm not only decreases the average output bit-rate by about 0.2 bit/pixel for lossless compression, but also improves the reconstructed images and reduces the spectral distortion greatly, especially at high bit-rate for lossy compression.

Plasticity of genetic interactions in metabolic networks of yeast.

PubMed

Harrison, Richard; Papp, Balázs; Pál, Csaba; Oliver, Stephen G; Delneri, Daniela

2007-02-13

Why are most genes dispensable? The impact of gene deletions may depend on the environment (plasticity), the presence of compensatory mechanisms (mutational robustness), or both. Here, we analyze the interaction between these two forces by exploring the condition-dependence of synthetic genetic interactions that define redundant functions and alternative pathways. We performed systems-level flux balance analysis of the yeast (Saccharomyces cerevisiae) metabolic network to identify genetic interactions and then tested the model's predictions with in vivo gene-deletion studies. We found that the majority of synthetic genetic interactions are restricted to certain environmental conditions, partly because of the lack of compensation under some (but not all) nutrient conditions. Moreover, the phylogenetic cooccurrence of synthetically interacting pairs is not significantly different from random expectation. These findings suggest that these gene pairs have at least partially independent functions, and, hence, compensation is only a byproduct of their evolutionary history. Experimental analyses that used multiple gene deletion strains not only confirmed predictions of the model but also showed that investigation of false predictions may both improve functional annotation within the model and also lead to the discovery of higher-order genetic interactions. Our work supports the view that functional redundancy may be more apparent than real, and it offers a unified framework for the evolution of environmental adaptation and mutational robustness.

Weak coordination between leaf structure and function among closely related tomato species.

PubMed

Muir, Christopher D; Conesa, Miquel À; Roldán, Emilio J; Molins, Arántzazu; Galmés, Jeroni

2017-03-01

Theory predicts that natural selection should favor coordination between leaf physiology, biochemistry and anatomical structure along a functional trait spectrum from fast, resource-acquisitive syndromes to slow, resource-conservative syndromes. However, the coordination hypothesis has rarely been tested at a phylogenetic scale most relevant for understanding rapid adaptation in the recent past or for the prediction of evolutionary trajectories in response to climate change. We used a common garden to examine genetically based coordination between leaf traits across 19 wild and cultivated tomato taxa. We found weak integration between leaf structure (e.g. leaf mass per area) and physiological function (photosynthetic rate, biochemical capacity and CO 2 diffusion), even though all were arrayed in the predicted direction along a 'fast-slow' spectrum. This suggests considerable scope for unique trait combinations to evolve in response to new environments or in crop breeding. In particular, we found that partially independent variation in stomatal and mesophyll conductance may allow a plant to improve water-use efficiency without necessarily sacrificing maximum photosynthetic rates. Our study does not imply that functional trait spectra, such as the leaf economics spectrum, are unimportant, but that many important axes of variation within a taxonomic group may be unique and not generalizable to other taxa. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Functional connectivity between somatosensory and motor brain areas predicts individual differences in motor learning by observing.

PubMed

McGregor, Heather R; Gribble, Paul L

2017-08-01

Action observation can facilitate the acquisition of novel motor skills; however, there is considerable individual variability in the extent to which observation promotes motor learning. Here we tested the hypothesis that individual differences in brain function or structure can predict subsequent observation-related gains in motor learning. Subjects underwent an anatomical MRI scan and resting-state fMRI scans to assess preobservation gray matter volume and preobservation resting-state functional connectivity (FC), respectively. On the following day, subjects observed a video of a tutor adapting her reaches to a novel force field. After observation, subjects performed reaches in a force field as a behavioral assessment of gains in motor learning resulting from observation. We found that individual differences in resting-state FC, but not gray matter volume, predicted postobservation gains in motor learning. Preobservation resting-state FC between left primary somatosensory cortex and bilateral dorsal premotor cortex, primary motor cortex, and primary somatosensory cortex and left superior parietal lobule was positively correlated with behavioral measures of postobservation motor learning. Sensory-motor resting-state FC can thus predict the extent to which observation will promote subsequent motor learning. NEW & NOTEWORTHY We show that individual differences in preobservation brain function can predict subsequent observation-related gains in motor learning. Preobservation resting-state functional connectivity within a sensory-motor network may be used as a biomarker for the extent to which observation promotes motor learning. This kind of information may be useful if observation is to be used as a way to boost neuroplasticity and sensory-motor recovery for patients undergoing rehabilitation for diseases that impair movement such as stroke. Copyright © 2017 the American Physiological Society.

Application of higher harmonic blade feathering for helicopter vibration reduction

NASA Technical Reports Server (NTRS)

Powers, R. W.

1978-01-01

Higher harmonic blade feathering for helicopter vibration reduction is considered. Recent wind tunnel tests confirmed the effectiveness of higher harmonic control in reducing articulated rotor vibratory hub loads. Several predictive analyses developed in support of the NASA program were shown to be capable of calculating single harmonic control inputs required to minimize a single 4P hub response. In addition, a multiple-input, multiple-output harmonic control predictive analysis was developed. All techniques developed thus far obtain a solution by extracting empirical transfer functions from sampled data. Algorithm data sampling and processing requirements are minimal to encourage adaptive control system application of such techniques in a flight environment.

A self-adaptive metamaterial beam with digitally controlled resonators for subwavelength broadband flexural wave attenuation

NASA Astrophysics Data System (ADS)

Li, Xiaopeng; Chen, Yangyang; Hu, Gengkai; Huang, Guoliang

2018-04-01

Designing lightweight materials and/or structures for broadband low-frequency noise/vibration mitigation is an issue of fundamental importance both practically and theoretically. In this paper, by leveraging the concept of frequency-dependent effective stiffness control, we numerically and experimentally demonstrate, for the first time, a self-adaptive metamaterial beam with digital circuit controlled mechanical resonators for strong and broadband flexural wave attenuation at subwavelength scales. The digital controllers that are capable of feedback control of piezoelectric shunts are integrated into mechanical resonators in the metamaterial, and the transfer function is semi-analytically determined to realize an effective bending stiffness in a quadratic function of the wave frequency for adaptive band gaps. The digital as well as analog control circuits as the backbone of the system are experimentally realized with the guarantee stability of the whole electromechanical system in whole frequency regions, which is the most challenging problem so far. Our experimental results are in good agreement with numerical predictions and demonstrate the strong wave attenuation in almost a three times larger frequency region over the bandwidth of a passive metamaterial. The proposed metamaterial could be applied in a range of applications in the design of elastic wave control devices.

Combining animal personalities with transcriptomics resolves individual variation within a wild-type zebrafish population and identifies underpinning molecular differences in brain function.

PubMed

Rey, S; Boltana, S; Vargas, R; Roher, N; Mackenzie, S

2013-12-01

Resolving phenotype variation within a population in response to environmental perturbation is central to understanding biological adaptation. Relating meaningful adaptive changes at the level of the transcriptome requires the identification of processes that have a functional significance for the individual. This remains a major objective towards understanding the complex interactions between environmental demand and an individual's capacity to respond to such demands. The interpretation of such interactions and the significance of biological variation between individuals from the same or different populations remain a difficult and under-addressed question. Here, we provide evidence that variation in gene expression between individuals in a zebrafish population can be partially resolved by a priori screening for animal personality and accounts for >9% of observed variation in the brain transcriptome. Proactive and reactive individuals within a wild-type population exhibit consistent behavioural responses over time and context that relates to underlying differences in regulated gene networks and predicted protein-protein interactions. These differences can be mapped to distinct regions of the brain and provide a foundation towards understanding the coordination of underpinning adaptive molecular events within populations. © 2013 John Wiley & Sons Ltd.

Use of the local lymph node assay in assessment of immune function.

PubMed

van den Berg, Femke A; Baken, Kirsten A; Vermeulen, Jolanda P; Gremmer, Eric R; van Steeg, Harry; van Loveren, Henk

2005-07-01

The murine local lymph node assay (LLNA) was originally developed as a predictive test method for the identification of chemicals with sensitizing potential. In this study we demonstrated that an adapted LLNA can also be used as an immune function assay by studying the effects of orally administered immunomodulating compounds on the T-cell-dependent immune response induced by the contact sensitizer 2,4-dinitrochlorobenzene (DNCB). C57Bl/6 mice were treated with the immunotoxic compounds cyclosporin A (CsA), bis(tri-n-butyltin)oxide (TBTO) or benzo[a]pyrene, (B[a]P). Subsequently, cell proliferation and interferon-gamma (IFN-gamma) and interleukin (IL)-4 release were determined in the auricular lymph nodes (LNs) after DNCB application on both ears. Immunosuppression induced by CsA, TBTO and B[a]P was clearly detectable in this application of the LLNA. Cytokine release measurements proved valuable to confirm the results of the cell proliferation assay and to obtain an indication of the effect on Th1/Th2 balance. We believe to have demonstrated the applicability of an adapted LLNA as an immune function assay in the mouse.

Adaptive responses reveal contemporary and future ecotypes in a desert shrub

USGS Publications Warehouse

Richardson, Bryce A.; Kitchen, Stanley G.; Pendleton, Rosemary L.; Pendleton, Burton K.; Germino, Matthew J.; Rehfeldt, Gerald E.; Meyer, Susan E.

2014-01-01

Interacting threats to ecosystem function, including climate change, wildfire, and invasive species necessitate native plant restoration in desert ecosystems. However, native plant restoration efforts often remain unguided by ecological genetic information. Given that many ecosystems are in flux from climate change, restoration plans need to account for both contemporary and future climates when choosing seed sources. In this study we analyze vegetative responses, including mortality, growth, and carbon isotope ratios in two blackbrush (Coleogyne ramosissima) common gardens that included 26 populations from a range-wide collection. This shrub occupies ecotones between the warm and cold deserts of Mojave and Colorado Plateau ecoregions in western North America. The variation observed in the vegetative responses of blackbrush populations was principally explained by grouping populations by ecoregions and by regression with site-specific climate variables. Aridity weighted by winter minimum temperatures best explained vegetative responses; Colorado Plateau sites were usually colder and drier than Mojave sites. The relationship between climate and vegetative response was mapped within the boundaries of the species–climate space projected for the contemporary climate and for the decade surrounding 2060. The mapped ecological genetic pattern showed that genetic variation could be classified into cool-adapted and warm-adapted ecotypes, with populations often separated by steep clines. These transitions are predicted to occur in both the Mojave Desert and Colorado Plateau ecoregions. While under contemporary conditions the warm-adapted ecotype occupies the majority of climate space, climate projections predict that the cool-adapted ecotype could prevail as the dominant ecotype as the climate space of blackbrush expands into higher elevations and latitudes. This study provides the framework for delineating climate change-responsive seed transfer guidelines, which are needed to inform restoration and management planning. We propose four transfer zones in blackbrush that correspond to areas currently dominated by cool-adapted and warm-adapted ecotypes in each of the two ecoregions.

Adaptive responses reveal contemporary and future ecotypes in a desert shrub.

PubMed

Richardson, Bryce A; Kitchen, Stanley G; Pendleton, Rosemary L; Pendleton, Burton K; Germino, Matthew J; Rehfeldt, Gerald E; Meyer, Susan E

2014-03-01

Interacting threats to ecosystem function, including climate change, wildfire, and invasive species necessitate native plant restoration in desert ecosystems. However, native plant restoration efforts often remain unguided by ecological genetic information. Given that many ecosystems are in flux from climate change, restoration plans need to account for both contemporary and future climates when choosing seed sources. In this study we analyze vegetative responses, including mortality, growth, and carbon isotope ratios in two blackbrush (Coleogyne ramosissima) common gardens that included 26 populations from a range-wide collection. This shrub occupies ecotones between the warm and cold deserts of Mojave and Colorado Plateau ecoregions in western North America. The variation observed in the vegetative responses of blackbrush populations was principally explained by grouping populations by ecoregions and by regression with site-specific climate variables. Aridity weighted by winter minimum temperatures best explained vegetative responses; Colorado Plateau sites were usually colder and drier than Mojave sites. The relationship between climate and vegetative response was mapped within the boundaries of the species-climate space projected for the contemporary climate and for the decade surrounding 2060. The mapped ecological genetic pattern showed that genetic variation could be classified into cool-adapted and warm-adapted ecotypes, with populations often separated by steep dines. These transitions are predicted to occur in both the Mojave Desert and Colorado Plateau ecoregions. While under contemporary conditions the warm-adapted ecotype occupies the majority of climate space, climate projections predict that the cool-adapted ecotype could prevail as the dominant ecotype as the climate space of blackbrush expands into higher elevations and latitudes. This study provides the framework for delineating climate change-responsive seed transfer guidelines, which are needed to inform restoration and management planning. We propose four transfer zones in blackbrush that correspond to areas currently dominated by cool-adapted and warm-adapted ecotypes in each of the two ecoregions.

Importance of whole-plant biomass allocation and reproductive timing to habitat differentiation across the North American sunflowers.

PubMed

Mason, Chase M; Goolsby, Eric W; Davis, Kaleigh E; Bullock, Devon V; Donovan, Lisa A

2017-05-01

Trait-based plant ecology attempts to use small numbers of functional traits to predict plant ecological strategies. However, a major gap exists between our understanding of organ-level ecophysiological traits and our understanding of whole-plant fitness and environmental adaptation. In this gap lie whole-plant organizational traits, including those that describe how plant biomass is allocated among organs and the timing of plant reproduction. This study explores the role of whole-plant organizational traits in adaptation to diverse environments in the context of life history, growth form and leaf economic strategy in a well-studied herbaceous system. A phylogenetic comparative approach was used in conjunction with common garden phenotyping to assess the evolution of biomass allocation and reproductive timing across 83 populations of 27 species of the diverse genus Helianthus (the sunflowers). Broad diversity exists among species in both relative biomass allocation and reproductive timing. Early reproduction is strongly associated with resource-acquisitive leaf economic strategy, while biomass allocation is less integrated with either reproductive timing or leaf economics. Both biomass allocation and reproductive timing are strongly related to source site environmental characteristics, including length of the growing season, temperature, precipitation and soil fertility. Herbaceous taxa can adapt to diverse environments in many ways, including modulation of phenology, plant architecture and organ-level ecophysiology. Although leaf economic strategy captures one key aspect of plant physiology, on their own leaf traits are not particularly predictive of ecological strategies in Helianthus outside of the context of growth form, life history and whole-plant organization. These results highlight the importance of including data on whole-plant organization alongside organ-level ecophysiological traits when attempting to bridge the gap between functional traits and plant fitness and environmental adaptation. © The Author 2017. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Importance of whole-plant biomass allocation and reproductive timing to habitat differentiation across the North American sunflowers

PubMed Central

Goolsby, Eric W.; Davis, Kaleigh E.; Bullock, Devon V.; Donovan, Lisa A.

2017-01-01

Abstract Background and Aims Trait-based plant ecology attempts to use small numbers of functional traits to predict plant ecological strategies. However, a major gap exists between our understanding of organ-level ecophysiological traits and our understanding of whole-plant fitness and environmental adaptation. In this gap lie whole-plant organizational traits, including those that describe how plant biomass is allocated among organs and the timing of plant reproduction. This study explores the role of whole-plant organizational traits in adaptation to diverse environments in the context of life history, growth form and leaf economic strategy in a well-studied herbaceous system. Methods A phylogenetic comparative approach was used in conjunction with common garden phenotyping to assess the evolution of biomass allocation and reproductive timing across 83 populations of 27 species of the diverse genus Helianthus (the sunflowers). Key Results Broad diversity exists among species in both relative biomass allocation and reproductive timing. Early reproduction is strongly associated with resource-acquisitive leaf economic strategy, while biomass allocation is less integrated with either reproductive timing or leaf economics. Both biomass allocation and reproductive timing are strongly related to source site environmental characteristics, including length of the growing season, temperature, precipitation and soil fertility. Conclusions Herbaceous taxa can adapt to diverse environments in many ways, including modulation of phenology, plant architecture and organ-level ecophysiology. Although leaf economic strategy captures one key aspect of plant physiology, on their own leaf traits are not particularly predictive of ecological strategies in Helianthus outside of the context of growth form, life history and whole-plant organization. These results highlight the importance of including data on whole-plant organization alongside organ-level ecophysiological traits when attempting to bridge the gap between functional traits and plant fitness and environmental adaptation. PMID:28203721

Psychosocial Outcomes in Long-Term Cochlear Implant Users.

PubMed

Castellanos, Irina; Kronenberger, William G; Pisoni, David B

The objectives of this study were to investigate psychosocial outcomes in a sample of prelingually deaf, early-implanted children, adolescents, and young adults who are long-term cochlear implant (CI) users and to examine the extent to which language and executive functioning predict psychosocial outcomes. Psychosocial outcomes were measured using two well-validated, parent-completed checklists: the Behavior Assessment System for Children and the Conduct Hyperactive Attention Problem Oppositional Symptom. Neurocognitive skills were measured using gold standard, performance-based assessments of language and executive functioning. CI users were at greater risk for clinically significant deficits in areas related to attention, oppositional behavior, hyperactivity-impulsivity, and social-adaptive skills compared with their normal-hearing peers, although the majority of CI users scored within average ranges relative to Behavior Assessment System for Children norms. Regression analyses revealed that language, visual-spatial working memory, and inhibition-concentration skills predicted psychosocial outcomes. Findings suggest that underlying delays and deficits in language and executive functioning may place some CI users at a risk for difficulties in psychosocial adjustment.

Predicting Mountainous Watershed Biogeochemical Dynamics, Including Response to Droughts and Early Snowmelt

NASA Astrophysics Data System (ADS)

Hubbard, S. S.; Williams, K. H.; Long, P.; Agarwal, D.; Banfield, J. F.; Beller, H. R.; Bouskill, N.; Brodie, E.; Maxwell, R. M.; Nico, P. S.; Steefel, C. I.; Steltzer, H.; Tokunaga, T. K.; Wainwright, H. M.

2016-12-01

Climate change, extreme weather, land-use change, and other perturbations are significantly reshaping interactions with in watersheds throughout the world. While mountainous watersheds are recognized as the water towers for the world, hydrological processes in watersheds also mediate biogeochemical processes that support all terrestrial life. Developing predictive understanding of watershed hydrological and biogeochemical functioning is challenging, as complex interactions occurring within a heterogeneous watershed can lead to a cascade of effects on downstream water availability and quality. Although these interactions can have significant implications for energy production, agriculture, water quality, and other benefits valued by society, uncertainty associated with predicting watershed function is high. The Watershed Function project aims to substantially reduce this uncertainty through developing a predictive understanding of how mountainous watersheds retain and release downgradient water, nutrients, carbon, and metals. In particular, the project is exploring how early snowmelt, drought, and other disturbances will influence mountainous watershed dynamics at seasonal to decadal timescales. The Watershed Function project is being carried out in a headwater mountainous catchment of the Upper Colorado River Basin, within a watershed characterized by significant gradients in elevation, vegetation and hydrogeology. A system-within system project perspective posits that the integrated watershed response to disturbances can be adequately predicted through consideration of interactions and feedbacks occurring within a limited number of subsystems, each having distinct vegetation-subsurface biogeochemical-hydrological characteristics. A key technological goal is the development of scale-adaptive simulation capabilities that can incorporate genomic information where and when it is useful for predicting the overall watershed response to disturbance. Through developing and integrating new microbial ecology, geochemical, hydrological, ecohydrological, computational and geophysical approaches, the project is developing new insights about biogeochemical dynamics from genome to watershed scales.

Objective Versus Subjective Measures of Executive Functions: Predictors of Participation and Quality of Life in Parkinson Disease?

PubMed

Vlagsma, Thialda T; Koerts, Janneke; Tucha, Oliver; Dijkstra, Hilde T; Duits, Annelien A; van Laar, Teus; Spikman, Jacoba M

2017-11-01

To determine whether objective (neuropsychological tests) and subjective measures (questionnaires) of executive functions (EFs) are associated in patients with Parkinson disease (PD), and to determine to what extent level of participation and quality of life (QoL) of patients with PD can be predicted by these measures of EFs. Correlational research design (case-control and prediction design). Departments of neuropsychology of 3 medical centers. A sample (N=136) of patients with PD (n=42) and their relatives, and controls without PD (n=94). Not applicable. A test battery measuring EFs. In addition, patients, their relatives, and controls completed the Dysexecutive Questionnaire, Brock Adaptive Functioning Questionnaire, and Barkley Deficits in Executive Functioning Scale - time management questionnaires measuring complaints about EFs. Participation and QoL were measured with the Impact on Participation and Autonomy scale and the Parkinson's Disease Questionnaire-39, respectively. Patients with PD showed impairments in EFs on objective tests and reported significantly more complaints about EFs than did controls without PD. No associations were found between patients' performances on objective and subjective measures of EFs. However, both objective and subjective measures predicted patients' level of participation. In addition, subjective measures of EFs predicted QoL in patients with PD. These findings show that objective and subjective measures of EFs are not interchangeable and that both approaches predict level of participation and QoL in patients with PD. However, within this context, sex needs to be taken into account. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Sensory processing and corollary discharge effects in posterior caudal lobe Purkinje cells in a weakly electric mormyrid fish.

PubMed

Alviña, Karina; Sawtell, Nathaniel B

2014-07-15

Although it has been suggested that the cerebellum functions to predict the sensory consequences of motor commands, how such predictions are implemented in cerebellar circuitry remains largely unknown. A detailed and relatively complete account of predictive mechanisms has emerged from studies of cerebellum-like sensory structures in fish, suggesting that comparisons of the cerebellum and cerebellum-like structures may be useful. Here we characterize electrophysiological response properties of Purkinje cells in a region of the cerebellum proper of weakly electric mormyrid fish, the posterior caudal lobe (LCp), which receives the same mossy fiber inputs and projects to the same target structures as the electrosensory lobe (ELL), a well-studied cerebellum-like structure. We describe patterns of simple spike and climbing fiber activation in LCp Purkinje cells in response to motor corollary discharge, electrosensory, and proprioceptive inputs and provide evidence for two functionally distinct Purkinje cell subtypes within LCp. Protocols that induce rapid associative plasticity in ELL fail to induce plasticity in LCp, suggesting differences in the adaptive functions of the two structures. Similarities and differences between LCp and ELL are discussed in light of these results. Copyright © 2014 the American Physiological Society.

Dynamic Connectivity between Brain Networks Supports Working Memory: Relationships to Dopamine Release and Schizophrenia.

PubMed

Cassidy, Clifford M; Van Snellenberg, Jared X; Benavides, Caridad; Slifstein, Mark; Wang, Zhishun; Moore, Holly; Abi-Dargham, Anissa; Horga, Guillermo

2016-04-13

Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during ann-back working-memory task) and positron emission tomography using the radiotracer [(11)C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. It is unclear how communication between brain networks responds to changing environmental demands during complex cognitive processes. Also, unknown in regard to these network dynamics is the role of neuromodulators, such as dopamine, and whether their dysregulation could underlie cognitive deficits in neuropsychiatric illness. We found that connectivity between brain networks changes with working-memory load and greater increases predict better working memory performance; however, it was not related to capacity for dopamine release in the cortex. Patients with schizophrenia did show dynamic internetwork connectivity; however, this was more weakly associated with successful performance in patients compared with healthy individuals. Our findings indicate that dynamic interactions between brain networks may support the type of flexible adaptations essential to goal-directed behavior. Copyright © 2016 the authors 0270-6474/16/364378-12$15.00/0.

Dynamic Connectivity between Brain Networks Supports Working Memory: Relationships to Dopamine Release and Schizophrenia

PubMed Central

Van Snellenberg, Jared X.; Benavides, Caridad; Slifstein, Mark; Wang, Zhishun; Moore, Holly; Abi-Dargham, Anissa

2016-01-01

Connectivity between brain networks may adapt flexibly to cognitive demand, a process that could underlie adaptive behaviors and cognitive deficits, such as those observed in neuropsychiatric conditions like schizophrenia. Dopamine signaling is critical for working memory but its influence on internetwork connectivity is relatively unknown. We addressed these questions in healthy humans using functional magnetic resonance imaging (during an n-back working-memory task) and positron emission tomography using the radiotracer [11C]FLB457 before and after amphetamine to measure the capacity for dopamine release in extrastriatal brain regions. Brain networks were defined by spatial independent component analysis (ICA) and working-memory-load-dependent connectivity between task-relevant pairs of networks was determined via a modified psychophysiological interaction analysis. For most pairs of task-relevant networks, connectivity significantly changed as a function of working-memory load. Moreover, load-dependent changes in connectivity between left and right frontoparietal networks (Δ connectivity lFPN-rFPN) predicted interindividual differences in task performance more accurately than other fMRI and PET imaging measures. Δ Connectivity lFPN-rFPN was not related to cortical dopamine release capacity. A second study in unmedicated patients with schizophrenia showed no abnormalities in load-dependent connectivity but showed a weaker relationship between Δ connectivity lFPN-rFPN and working memory performance in patients compared with matched healthy individuals. Poor working memory performance in patients was, in contrast, related to deficient cortical dopamine release. Our findings indicate that interactions between brain networks dynamically adapt to fluctuating environmental demands. These dynamic adaptations underlie successful working memory performance in healthy individuals and are not well predicted by amphetamine-induced dopamine release capacity. SIGNIFICANCE STATEMENT It is unclear how communication between brain networks responds to changing environmental demands during complex cognitive processes. Also, unknown in regard to these network dynamics is the role of neuromodulators, such as dopamine, and whether their dysregulation could underlie cognitive deficits in neuropsychiatric illness. We found that connectivity between brain networks changes with working-memory load and greater increases predict better working memory performance; however, it was not related to capacity for dopamine release in the cortex. Patients with schizophrenia did show dynamic internetwork connectivity; however, this was more weakly associated with successful performance in patients compared with healthy individuals. Our findings indicate that dynamic interactions between brain networks may support the type of flexible adaptations essential to goal-directed behavior. PMID:27076432

Frontal Theta Links Prediction Errors to Behavioral Adaptation in Reinforcement Learning

PubMed Central

Cavanagh, James F.; Frank, Michael J.; Klein, Theresa J.; Allen, John J.B.

2009-01-01

Investigations into action monitoring have consistently detailed a fronto-central voltage deflection in the Event-Related Potential (ERP) following the presentation of negatively valenced feedback, sometimes termed the Feedback Related Negativity (FRN). The FRN has been proposed to reflect a neural response to prediction errors during reinforcement learning, yet the single trial relationship between neural activity and the quanta of expectation violation remains untested. Although ERP methods are not well suited to single trial analyses, the FRN has been associated with theta band oscillatory perturbations in the medial prefrontal cortex. Medio-frontal theta oscillations have been previously associated with expectation violation and behavioral adaptation and are well suited to single trial analysis. Here, we recorded EEG activity during a probabilistic reinforcement learning task and fit the performance data to an abstract computational model (Q-learning) for calculation of single-trial reward prediction errors. Single-trial theta oscillatory activities following feedback were investigated within the context of expectation (prediction error) and adaptation (subsequent reaction time change). Results indicate that interactive medial and lateral frontal theta activities reflect the degree of negative and positive reward prediction error in the service of behavioral adaptation. These different brain areas use prediction error calculations for different behavioral adaptations: with medial frontal theta reflecting the utilization of prediction errors for reaction time slowing (specifically following errors), but lateral frontal theta reflecting prediction errors leading to working memory-related reaction time speeding for the correct choice. PMID:19969093

Searching for the bull's eye: agents and targets of selection vary among geographically disparate cyanogenesis clines in white clover (Trifolium repens L.)

PubMed Central

Kooyers, N J; Olsen, K M

2013-01-01

The recurrent evolution of adaptive clines within a species can be used to elucidate the selective factors and genetic responses that underlie adaptation. White clover is polymorphic for cyanogenesis (HCN release with tissue damage), and climate-associated cyanogenesis clines have evolved throughout the native and introduced species range. This polymorphism arises through two independently segregating Mendelian polymorphisms for the presence/absence of two required components: cyanogenic glucosides and their hydrolyzing enzyme linamarase. Cyanogenesis is commonly thought to function in herbivore defense; however, the individual cyanogenic components may also serve other physiological functions. To test whether cyanogenesis clines have evolved in response to the same selective pressures acting on the same genetic targets, we examined cyanogenesis cline shape and its environmental correlates in three world regions: southern New Zealand, the central United States and the US Pacific Northwest. For some regional comparisons, cline shapes are remarkably similar despite large differences in the spatial scales over which clines occur (40–1600 km). However, we also find evidence for major differences in both the agents and targets of selection among the sampled clines. Variation in cyanogenesis frequency is best predicted using a combination of minimum winter temperature and aridity variables. Together, our results provide evidence that recurrent adaptive clines do not necessarily reflect shared adaptive processes. PMID:23900395

Review: Towards the agroecological management of ruminants, pigs and poultry through the development of sustainable breeding programmes: I-selection goals and criteria.

PubMed

Phocas, F; Belloc, C; Bidanel, J; Delaby, L; Dourmad, J Y; Dumont, B; Ezanno, P; Fortun-Lamothe, L; Foucras, G; Frappat, B; González-García, E; Hazard, D; Larzul, C; Lubac, S; Mignon-Grasteau, S; Moreno, C R; Tixier-Boichard, M; Brochard, M

2016-11-01

Agroecology uses natural processes and local resources rather than chemical inputs to ensure production while limiting the environmental footprint of livestock and crop production systems. Selecting to achieve a maximization of target production criteria has long proved detrimental to fitness traits. However, since the 1990s, developments in animal breeding have also focussed on animal robustness by balancing production and functional traits within overall breeding goals. We discuss here how an agroecological perspective should further shift breeding goals towards functional traits rather than production traits. Breeding for robustness aims to promote individual adaptive capacities by considering diverse selection criteria which include reproduction, animal health and welfare, and adaptation to rough feed resources, a warm climate or fluctuating environmental conditions. It requires the consideration of genotype×environment interactions in the prediction of breeding values. Animal performance must be evaluated in low-input systems in order to select those animals that are adapted to limiting conditions, including feed and water availability, climate variations and diseases. Finally, we argue that there is no single agroecological animal type, but animals with a variety of profiles that can meet the expectations of agroecology. The standardization of both animals and breeding conditions indeed appears contradictory to the agroecological paradigm that calls for an adaptation of animals to local opportunities and constraints in weakly artificialized systems tied to their physical environment.

Generalization in Adaptation to Stable and Unstable Dynamics

PubMed Central

Kadiallah, Abdelhamid; Franklin, David W.; Burdet, Etienne

2012-01-01

Humans skillfully manipulate objects and tools despite the inherent instability. In order to succeed at these tasks, the sensorimotor control system must build an internal representation of both the force and mechanical impedance. As it is not practical to either learn or store motor commands for every possible future action, the sensorimotor control system generalizes a control strategy for a range of movements based on learning performed over a set of movements. Here, we introduce a computational model for this learning and generalization, which specifies how to learn feedforward muscle activity in a function of the state space. Specifically, by incorporating co-activation as a function of error into the feedback command, we are able to derive an algorithm from a gradient descent minimization of motion error and effort, subject to maintaining a stability margin. This algorithm can be used to learn to coordinate any of a variety of motor primitives such as force fields, muscle synergies, physical models or artificial neural networks. This model for human learning and generalization is able to adapt to both stable and unstable dynamics, and provides a controller for generating efficient adaptive motor behavior in robots. Simulation results exhibit predictions consistent with all experiments on learning of novel dynamics requiring adaptation of force and impedance, and enable us to re-examine some of the previous interpretations of experiments on generalization. PMID:23056191

Network-level architecture and the evolutionary potential of underground metabolism.

PubMed

Notebaart, Richard A; Szappanos, Balázs; Kintses, Bálint; Pál, Ferenc; Györkei, Ádám; Bogos, Balázs; Lázár, Viktória; Spohn, Réka; Csörgő, Bálint; Wagner, Allon; Ruppin, Eytan; Pál, Csaba; Papp, Balázs

2014-08-12

A central unresolved issue in evolutionary biology is how metabolic innovations emerge. Low-level enzymatic side activities are frequent and can potentially be recruited for new biochemical functions. However, the role of such underground reactions in adaptation toward novel environments has remained largely unknown and out of reach of computational predictions, not least because these issues demand analyses at the level of the entire metabolic network. Here, we provide a comprehensive computational model of the underground metabolism in Escherichia coli. Most underground reactions are not isolated and 45% of them can be fully wired into the existing network and form novel pathways that produce key precursors for cell growth. This observation allowed us to conduct an integrated genome-wide in silico and experimental survey to characterize the evolutionary potential of E. coli to adapt to hundreds of nutrient conditions. We revealed that underground reactions allow growth in new environments when their activity is increased. We estimate that at least ∼20% of the underground reactions that can be connected to the existing network confer a fitness advantage under specific environments. Moreover, our results demonstrate that the genetic basis of evolutionary adaptations via underground metabolism is computationally predictable. The approach used here has potential for various application areas from bioengineering to medical genetics.

Predicting mesh density for adaptive modelling of the global atmosphere.

PubMed

Weller, Hilary

2009-11-28

The shallow water equations are solved using a mesh of polygons on the sphere, which adapts infrequently to the predicted future solution. Infrequent mesh adaptation reduces the cost of adaptation and load-balancing and will thus allow for more accurate mapping on adaptation. We simulate the growth of a barotropically unstable jet adapting the mesh every 12 h. Using an adaptation criterion based largely on the gradient of the vorticity leads to a mesh with around 20 per cent of the cells of a uniform mesh that gives equivalent results. This is a similar proportion to previous studies of the same test case with mesh adaptation every 1-20 min. The prediction of the mesh density involves solving the shallow water equations on a coarse mesh in advance of the locally refined mesh in order to estimate where features requiring higher resolution will grow, decay or move to. The adaptation criterion consists of two parts: that resolved on the coarse mesh, and that which is not resolved and so is passively advected on the coarse mesh. This combination leads to a balance between resolving features controlled by the large-scale dynamics and maintaining fine-scale features.

De novo Assembly of the Indo-Pacific Humpback Dolphin Leucocyte Transcriptome to Identify Putative Genes Involved in the Aquatic Adaptation and Immune Response

PubMed Central

Xia, Jia; Yang, Lili; Chen, Jialin; Wu, Yuping; Yi, Meisheng

2013-01-01

Background The Indo-Pacific humpback dolphin (Sousa chinensis), a marine mammal species inhabited in the waters of Southeast Asia, South Africa and Australia, has attracted much attention because of the dramatic decline in population size in the past decades, which raises the concern of extinction. So far, this species is poorly characterized at molecular level due to little sequence information available in public databases. Recent advances in large-scale RNA sequencing provide an efficient approach to generate abundant sequences for functional genomic analyses in the species with un-sequenced genomes. Principal Findings We performed a de novo assembly of the Indo-Pacific humpback dolphin leucocyte transcriptome by Illumina sequencing. 108,751 high quality sequences from 47,840,388 paired-end reads were generated, and 48,868 and 46,587 unigenes were functionally annotated by BLAST search against the NCBI non-redundant and Swiss-Prot protein databases (E-value<10−5), respectively. In total, 16,467 unigenes were clustered into 25 functional categories by searching against the COG database, and BLAST2GO search assigned 37,976 unigenes to 61 GO terms. In addition, 36,345 unigenes were grouped into 258 KEGG pathways. We also identified 9,906 simple sequence repeats and 3,681 putative single nucleotide polymorphisms as potential molecular markers in our assembled sequences. A large number of unigenes were predicted to be involved in immune response, and many genes were predicted to be relevant to adaptive evolution and cetacean-specific traits. Conclusion This study represented the first transcriptome analysis of the Indo-Pacific humpback dolphin, an endangered species. The de novo transcriptome analysis of the unique transcripts will provide valuable sequence information for discovery of new genes, characterization of gene expression, investigation of various pathways and adaptive evolution, as well as identification of genetic markers. PMID:24015242

De novo assembly of the Indo-Pacific humpback dolphin leucocyte transcriptome to identify putative genes involved in the aquatic adaptation and immune response.

PubMed

Gui, Duan; Jia, Kuntong; Xia, Jia; Yang, Lili; Chen, Jialin; Wu, Yuping; Yi, Meisheng

2013-01-01

The Indo-Pacific humpback dolphin (Sousa chinensis), a marine mammal species inhabited in the waters of Southeast Asia, South Africa and Australia, has attracted much attention because of the dramatic decline in population size in the past decades, which raises the concern of extinction. So far, this species is poorly characterized at molecular level due to little sequence information available in public databases. Recent advances in large-scale RNA sequencing provide an efficient approach to generate abundant sequences for functional genomic analyses in the species with un-sequenced genomes. We performed a de novo assembly of the Indo-Pacific humpback dolphin leucocyte transcriptome by Illumina sequencing. 108,751 high quality sequences from 47,840,388 paired-end reads were generated, and 48,868 and 46,587 unigenes were functionally annotated by BLAST search against the NCBI non-redundant and Swiss-Prot protein databases (E-value<10(-5)), respectively. In total, 16,467 unigenes were clustered into 25 functional categories by searching against the COG database, and BLAST2GO search assigned 37,976 unigenes to 61 GO terms. In addition, 36,345 unigenes were grouped into 258 KEGG pathways. We also identified 9,906 simple sequence repeats and 3,681 putative single nucleotide polymorphisms as potential molecular markers in our assembled sequences. A large number of unigenes were predicted to be involved in immune response, and many genes were predicted to be relevant to adaptive evolution and cetacean-specific traits. This study represented the first transcriptome analysis of the Indo-Pacific humpback dolphin, an endangered species. The de novo transcriptome analysis of the unique transcripts will provide valuable sequence information for discovery of new genes, characterization of gene expression, investigation of various pathways and adaptive evolution, as well as identification of genetic markers.

Adaptive MPC based on MIMO ARX-Laguerre model.

PubMed

Ben Abdelwahed, Imen; Mbarek, Abdelkader; Bouzrara, Kais

2017-03-01

This paper proposes a method for synthesizing an adaptive predictive controller using a reduced complexity model. This latter is given by the projection of the ARX model on Laguerre bases. The resulting model is entitled MIMO ARX-Laguerre and it is characterized by an easy recursive representation. The adaptive predictive control law is computed based on multi-step-ahead finite-element predictors, identified directly from experimental input/output data. The model is tuned in each iteration by an online identification algorithms of both model parameters and Laguerre poles. The proposed approach avoids time consuming numerical optimization algorithms associated with most common linear predictive control strategies, which makes it suitable for real-time implementation. The method is used to synthesize and test in numerical simulations adaptive predictive controllers for the CSTR process benchmark. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Horizontal gene transfer is more frequent with increased heterotrophy and contributes to parasite adaptation

PubMed Central

Yang, Zhenzhen; Zhang, Yeting; Wafula, Eric K.; Honaas, Loren A.; Ralph, Paula E.; Jones, Sam; Clarke, Christopher R.; Liu, Siming; Su, Chun; Zhang, Huiting; Altman, Naomi S.; Schuster, Stephan C.; Timko, Michael P.; Yoder, John I.; dePamphilis, Claude W.

2016-01-01

Horizontal gene transfer (HGT) is the transfer of genetic material across species boundaries and has been a driving force in prokaryotic evolution. HGT involving eukaryotes appears to be much less frequent, and the functional implications of HGT in eukaryotes are poorly understood. We test the hypothesis that parasitic plants, because of their intimate feeding contacts with host plant tissues, are especially prone to horizontal gene acquisition. We sought evidence of HGTs in transcriptomes of three parasitic members of Orobanchaceae, a plant family containing species spanning the full spectrum of parasitic capabilities, plus the free-living Lindenbergia. Following initial phylogenetic detection and an extensive validation procedure, 52 high-confidence horizontal transfer events were detected, often from lineages of known host plants and with an increasing number of HGT events in species with the greatest parasitic dependence. Analyses of intron sequences in putative donor and recipient lineages provide evidence for integration of genomic fragments far more often than retro-processed RNA sequences. Purifying selection predominates in functionally transferred sequences, with a small fraction of adaptively evolving sites. HGT-acquired genes are preferentially expressed in the haustorium—the organ of parasitic plants—and are strongly biased in predicted gene functions, suggesting that expression products of horizontally acquired genes are contributing to the unique adaptive feeding structure of parasitic plants. PMID:27791104

Balancing Automatic-Controlled Behaviors and Emotional-Salience States: A Dynamic Executive Functioning Hypothesis.

PubMed

Kluwe-Schiavon, Bruno; Viola, Thiago W; Sanvicente-Vieira, Breno; Malloy-Diniz, Leandro F; Grassi-Oliveira, Rodrigo

2016-01-01

Recently, there has been growing interest in understanding how executive functions are conceptualized in psychopathology. Since several models have been proposed, the major issue lies within the definition of executive functioning itself. Theoretical discussions have emerged, narrowing the boundaries between "hot" and "cold" executive functions or between self-regulation and cognitive control. Nevertheless, the definition of executive functions is far from a consensual proposition and it has been suggested that these models might be outdated. Current efforts indicate that human behavior and cognition are by-products of many brain systems operating and interacting at different levels, and therefore, it is very simplistic to assume a dualistic perspective of information processing. Based upon an adaptive perspective, we discuss how executive functions could emerge from the ability to solve immediate problems and to generalize successful strategies, as well as from the ability to synthesize and to classify environmental information in order to predict context and future. We present an executive functioning perspective that emerges from the dynamic balance between automatic-controlled behaviors and an emotional-salience state. According to our perspective, the adaptive role of executive functioning is to automatize efficient solutions simultaneously with cognitive demand, enabling individuals to engage such processes with increasingly complex problems. Understanding executive functioning as a mediator of stress and cognitive engagement not only fosters discussions concerning individual differences, but also offers an important paradigm to understand executive functioning as a continuum process rather than a categorical and multicomponent structure.

Balancing Automatic-Controlled Behaviors and Emotional-Salience States: A Dynamic Executive Functioning Hypothesis

PubMed Central

Kluwe-Schiavon, Bruno; Viola, Thiago W.; Sanvicente-Vieira, Breno; Malloy-Diniz, Leandro F.; Grassi-Oliveira, Rodrigo

2017-01-01

Recently, there has been growing interest in understanding how executive functions are conceptualized in psychopathology. Since several models have been proposed, the major issue lies within the definition of executive functioning itself. Theoretical discussions have emerged, narrowing the boundaries between “hot” and “cold” executive functions or between self-regulation and cognitive control. Nevertheless, the definition of executive functions is far from a consensual proposition and it has been suggested that these models might be outdated. Current efforts indicate that human behavior and cognition are by-products of many brain systems operating and interacting at different levels, and therefore, it is very simplistic to assume a dualistic perspective of information processing. Based upon an adaptive perspective, we discuss how executive functions could emerge from the ability to solve immediate problems and to generalize successful strategies, as well as from the ability to synthesize and to classify environmental information in order to predict context and future. We present an executive functioning perspective that emerges from the dynamic balance between automatic-controlled behaviors and an emotional-salience state. According to our perspective, the adaptive role of executive functioning is to automatize efficient solutions simultaneously with cognitive demand, enabling individuals to engage such processes with increasingly complex problems. Understanding executive functioning as a mediator of stress and cognitive engagement not only fosters discussions concerning individual differences, but also offers an important paradigm to understand executive functioning as a continuum process rather than a categorical and multicomponent structure. PMID:28154541

Operator State Estimation for Adaptive Aiding in Uninhabited Combat Air Vehicles

DTIC Science & Technology

2005-09-01

1992). Van Boxtel, A., W. Waterink, and I.J.T. Veldhuizen . “Tonic Facial EMG Activity As An Index of Mental Effort: Effects of Work Rate, Time-On...the ‘normal’ functioning of brain activity (Beaumont, Burov, Carter, Cheuvront, Sawka, Wilson, Van Orden, Hockey, Balkin and Gundel, 2004). For...by the sympathetic nervous system. Electromyographic activity has been shown to predict arousal accurately ( Veldhuizen , Gaillard, and de Vries, 2003

Adaptive vibration control of structures under earthquakes

NASA Astrophysics Data System (ADS)

Lew, Jiann-Shiun; Juang, Jer-Nan; Loh, Chin-Hsiung

2017-04-01

techniques, for structural vibration suppression under earthquakes. Various control strategies have been developed to protect structures from natural hazards and improve the comfort of occupants in buildings. However, there has been little development of adaptive building control with the integration of real-time system identification and control design. Generalized predictive control, which combines the process of real-time system identification and the process of predictive control design, has received widespread acceptance and has been successfully applied to various test-beds. This paper presents a formulation of the predictive control scheme for adaptive vibration control of structures under earthquakes. Comprehensive simulations are performed to demonstrate and validate the proposed adaptive control technique for earthquake-induced vibration of a building.

Using soft computing techniques to predict corrected air permeability using Thomeer parameters, air porosity and grain density

NASA Astrophysics Data System (ADS)

Nooruddin, Hasan A.; Anifowose, Fatai; Abdulraheem, Abdulazeez

2014-03-01

Soft computing techniques are recently becoming very popular in the oil industry. A number of computational intelligence-based predictive methods have been widely applied in the industry with high prediction capabilities. Some of the popular methods include feed-forward neural networks, radial basis function network, generalized regression neural network, functional networks, support vector regression and adaptive network fuzzy inference system. A comparative study among most popular soft computing techniques is presented using a large dataset published in literature describing multimodal pore systems in the Arab D formation. The inputs to the models are air porosity, grain density, and Thomeer parameters obtained using mercury injection capillary pressure profiles. Corrected air permeability is the target variable. Applying developed permeability models in recent reservoir characterization workflow ensures consistency between micro and macro scale information represented mainly by Thomeer parameters and absolute permeability. The dataset was divided into two parts with 80% of data used for training and 20% for testing. The target permeability variable was transformed to the logarithmic scale as a pre-processing step and to show better correlations with the input variables. Statistical and graphical analysis of the results including permeability cross-plots and detailed error measures were created. In general, the comparative study showed very close results among the developed models. The feed-forward neural network permeability model showed the lowest average relative error, average absolute relative error, standard deviations of error and root means squares making it the best model for such problems. Adaptive network fuzzy inference system also showed very good results.

Age-related differences in neuropsychological assessment of fetal alcohol spectrum disorder: a cross-sectional study.

PubMed

Taylor, Nicole M; Enns, Leah N

2018-04-01

This cross-sectional study examined 6 key areas of neuropsychological functioning (cognitive, academic, attention, executive function, adaptive skills) comparing adolescents and school-age children with prenatal alcohol exposure (PAE). The aims were: (i) to examine which neuropsychological measures were predictive of an FASD diagnosis in adolescents and school-age children with PAE, and (ii) to compare the neuropsychological performance of adolescents and children diagnosed with FASD. Hierarchical logistic regressions determined that the Full-Scale IQ, Verbal Comprehension and Perceptual Reasoning indices, basic reading and math skills, adaptive functioning at school, and components of executive functioning (dependent on age) improved the probability of an accurate FASD diagnosis in both groups: 9.1% to 19.2% for adolescents and 10.9% to 19.4% for school-age children (61.5%-80.9% correct classifications overall). For the age comparison analyses (ANOVAs/MANOVAs), a significant difference was observed in the cognitive domain, as well as with basic math skills (trend) in the sample diagnosed with FASD, with lower scores observed for adolescents across these measures. These findings provide further evidence for age differences in neuropsychological assessment as well as increased neuropsychological difficulties in adolescence by comparison with childhood with FASD. Longitudinal studies will be needed to make further inferences about developmental changes in neuropsychological functioning in FASD.

Optimal trading from minimizing the period of bankruptcy risk

NASA Astrophysics Data System (ADS)

Liehr, S.; Pawelzik, K.

2001-04-01

Assuming that financial markets behave similar to random walk processes we derive a trading strategy with variable investment which is based on the equivalence of the period of bankruptcy risk and the risk to profit ratio. We define a state dependent predictability measure which can be attributed to the deterministic and stochastic components of the price dynamics. The influence of predictability variations and especially of short term inefficiency structures on the optimal amount of investment is analyzed in the given context and a method for adaptation of a trading system to the proposed objective function is presented. Finally we show the performance of our trading strategy on the DAX and S&P 500 as examples for real world data using different types of prediction models in comparison.

Sensorimotor synchronization with tempo-changing auditory sequences: Modeling temporal adaptation and anticipation.

PubMed

van der Steen, M C Marieke; Jacoby, Nori; Fairhurst, Merle T; Keller, Peter E

2015-11-11

The current study investigated the human ability to synchronize movements with event sequences containing continuous tempo changes. This capacity is evident, for example, in ensemble musicians who maintain precise interpersonal coordination while modulating the performance tempo for expressive purposes. Here we tested an ADaptation and Anticipation Model (ADAM) that was developed to account for such behavior by combining error correction processes (adaptation) with a predictive temporal extrapolation process (anticipation). While previous computational models of synchronization incorporate error correction, they do not account for prediction during tempo-changing behavior. The fit between behavioral data and computer simulations based on four versions of ADAM was assessed. These versions included a model with adaptation only, one in which adaptation and anticipation act in combination (error correction is applied on the basis of predicted tempo changes), and two models in which adaptation and anticipation were linked in a joint module that corrects for predicted discrepancies between the outcomes of adaptive and anticipatory processes. The behavioral experiment required participants to tap their finger in time with three auditory pacing sequences containing tempo changes that differed in the rate of change and the number of turning points. Behavioral results indicated that sensorimotor synchronization accuracy and precision, while generally high, decreased with increases in the rate of tempo change and number of turning points. Simulations and model-based parameter estimates showed that adaptation mechanisms alone could not fully explain the observed precision of sensorimotor synchronization. Including anticipation in the model increased the precision of simulated sensorimotor synchronization and improved the fit of model to behavioral data, especially when adaptation and anticipation mechanisms were linked via a joint module based on the notion of joint internal models. Overall results suggest that adaptation and anticipation mechanisms both play an important role during sensorimotor synchronization with tempo-changing sequences. This article is part of a Special Issue entitled SI: Prediction and Attention. Copyright © 2015 Elsevier B.V. All rights reserved.

Does a Measure of Support Needs Predict Funding Need Better Than a Measure of Adaptive and Maladaptive Behavior?

PubMed

Arnold, Samuel R C; Riches, Vivienne C; Stancliffe, Roger J

2015-09-01

Internationally, various approaches are used for the allocation of individualized funding. When using a databased approach, a key question is the predictive validity of adaptive behavior versus support needs assessment. This article reports on a subset of data from a larger project that allowed for a comparison of support needs and adaptive behavior assessments when predicting person-centered funding allocation. The first phase of the project involved a trial of the Inventory for Client and Agency Planning (ICAP) adaptive behavior and Instrument for the Classification and Assessment of Support Needs (I-CAN)-Brief Research version support needs assessments. Participants were in receipt of an individual support package allocated using a person-centered planning process, and were stable in their support arrangements. Regression analysis showed that the most useful items in predicting funding allocation came from the I-CAN-Brief Research. No additional variance could be explained by adding the ICAP, or using the ICAP alone. A further unique approach of including only items from the I-CAN-Brief Research marked as funded supports showed high predictive validity. It appears support need is more effective at determining resource need than adaptive behavior.

Transferability of species distribution models: a functional habitat approach for two regionally threatened butterflies.

PubMed

Vanreusel, Wouter; Maes, Dirk; Van Dyck, Hans

2007-02-01

Numerous models for predicting species distribution have been developed for conservation purposes. Most of them make use of environmental data (e.g., climate, topography, land use) at a coarse grid resolution (often kilometres). Such approaches are useful for conservation policy issues including reserve-network selection. The efficiency of predictive models for species distribution is usually tested on the area for which they were developed. Although highly interesting from the point of view of conservation efficiency, transferability of such models to independent areas is still under debate. We tested the transferability of habitat-based predictive distribution models for two regionally threatened butterflies, the green hairstreak (Callophrys rubi) and the grayling (Hipparchia semele), within and among three nature reserves in northeastern Belgium. We built predictive models based on spatially detailed maps of area-wide distribution and density of ecological resources. We used resources directly related to ecological functions (host plants, nectar sources, shelter, microclimate) rather than environmental surrogate variables. We obtained models that performed well with few resource variables. All models were transferable--although to different degrees--among the independent areas within the same broad geographical region. We argue that habitat models based on essential functional resources could transfer better in space than models that use indirect environmental variables. Because functional variables can easily be interpreted and even be directly affected by terrain managers, these models can be useful tools to guide species-adapted reserve management.

A unified theory for ice vapor growth suitable for cloud models: Testing and implications for cold cloud evolution

NASA Astrophysics Data System (ADS)

Zhang, Chengzhu

A new microphysical model for the vapor growth and aspect ratio evolution of atmospheric ice crystals is presented. The method is based on the adaptive habit model of Chen and Lamb (1994), but is modified to include surface kinetic processes for crystal growth. Inclusion of surface kinetic effects is accomplished with a new theory that accounts for axis dependent growth. Deposition coefficients (growth efficiencies) are predicted for two axis directions based on laboratory-determined parameters for growth initiation (critical supersaturations) on each face. In essence, the new theory extends the adaptive habit approach of Chen and Lamb (1994) to ice saturation states below that of liquid saturation, where Chen and Lamb (1994) is likely most valid. The new model is used to simulate changes in crystal primary habit as a function of temperature and ice supersaturation. Predictions are compared with a detailed hexagonal growth model both in a single particle framework and in a Lagrangian parcel model to indicate the accuracy of the new method. Moreover, predictions of the ratio of the axis deposition coefficients match laboratory-generated data. A parameterization for predicting deposition coefficients is developed for the bulk microphysics frame work in Regional Atmospheric Modeling System (RAMS). Initial eddy-resolving model simulation is conducted to study the effect of surface kinetics on microphysical and dynamical processes in cold cloud development.

NATO IST 124 Experimentation Instructions

DTIC Science & Technology

2016-11-10

more reliable and predictable network performance through adaptive and efficient control schemes . This report provides guidance and instructions for...tactical heterogeneous networks for more reliable and predictable network performance through adaptive and efficient control schemes . This report

Dynamic adjustments of cognitive control: oscillatory correlates of the conflict adaptation effect.

PubMed

Pastötter, Bernhard; Dreisbach, Gesine; Bäuml, Karl-Heinz T

2013-12-01

It is a prominent idea that cognitive control mediates conflict adaptation, in that response conflict in a previous trial triggers control adjustments that reduce conflict in a current trial. In the present EEG study, we investigated the dynamics of cognitive control in a response-priming task by examining the effects of previous trial conflict on intertrial and current trial oscillatory brain activities, both on the electrode and the source level. Behavioral results showed conflict adaptation effects for RTs and response accuracy. Physiological results showed sustained intertrial effects in left parietal theta power, originating in the left inferior parietal cortex, and midcentral beta power, originating in the left and right (pre)motor cortex. Moreover, physiological analysis revealed a current trial conflict adaptation effect in midfrontal theta power, originating in the ACC. Correlational analyses showed that intertrial effects predicted conflict-induced midfrontal theta power in currently incongruent trials. In addition, conflict adaptation effects in midfrontal theta power and RTs were positively related. Together, these findings point to a dynamic cognitive control system that, as a function of previous trial type, up- and down-regulates attention and preparatory motor activities in anticipation of the next trial.

The Role of Senior University Students' Career Adaptability in Predicting Their Subjective Well-Being

ERIC Educational Resources Information Center

Kirdök, Oguzhan; Bölükbasi, Ayten

2018-01-01

The aim of this study is to examine whether career adaptability and career adaptability subscales of senior undergraduates could predict subjective well-being. The research was a descriptive correlational study which was conducted on 310 senior students (173 women, 137 men) in a state-funded university on the Mediterranean coast of Turkey and…

Predicting Career Adaptability through Self-Esteem and Social Support: A Research on Young Adults

ERIC Educational Resources Information Center

Ataç, Lale Oral; Dirik, Deniz; Tetik, Hilmiye Türesin

2018-01-01

The purpose of this study is to investigate the relationship between career adaptability and self-esteem, and analyze the moderating role of social support in this relationship on a sample of 313 young adults. The results of the study confirm that career adaptability is significantly predicted by self-esteem. Moreover, findings suggest that (1)…

Prediction of human adaptation and performance in underwater environments.

PubMed

Colodro Plaza, Joaquín; Garcés de los Fayos Ruiz, Enrique J; López García, Juan J; Colodro Conde, Lucía

2014-01-01

Environmental stressors require the professional diver to undergo a complex process of psychophysiological adaptation in order to overcome the demands of an extreme environment and carry out effective and efficient work under water. The influence of cognitive and personality traits in predicting underwater performance and adaptation has been a common concern for diving psychology, and definitive conclusions have not been reached. In this ex post facto study, psychological and academic data were analyzed from a large sample of personnel participating in scuba diving courses carried out in the Spanish Navy Diving Center. In order to verify the relevance of individual differences in adaptation to a hostile environment, we evaluated the predictive validity of general mental ability and personality traits with regression techniques. The data indicated the existence of psychological variables that can predict the performance ( R² = .30, p <.001) and adaptation ( R²(N) = .51, p <.001) of divers in underwater environment. These findings support the hypothesis that individual differences are related to the probability of successful adaptation and effective performance in professional diving. These results also verify that dispositional traits play a decisive role in diving training and are significant factors in divers' psychological fitness.

Data-driven Analysis and Prediction of Arctic Sea Ice

NASA Astrophysics Data System (ADS)

Kondrashov, D. A.; Chekroun, M.; Ghil, M.; Yuan, X.; Ting, M.

2015-12-01

We present results of data-driven predictive analyses of sea ice over the main Arctic regions. Our approach relies on the Multilayer Stochastic Modeling (MSM) framework of Kondrashov, Chekroun and Ghil [Physica D, 2015] and it leads to prognostic models of sea ice concentration (SIC) anomalies on seasonal time scales.This approach is applied to monthly time series of leading principal components from the multivariate Empirical Orthogonal Function decomposition of SIC and selected climate variables over the Arctic. We evaluate the predictive skill of MSM models by performing retrospective forecasts with "no-look ahead" forup to 6-months ahead. It will be shown in particular that the memory effects included in our non-Markovian linear MSM models improve predictions of large-amplitude SIC anomalies in certain Arctic regions. Furtherimprovements allowed by the MSM framework will adopt a nonlinear formulation, as well as alternative data-adaptive decompositions.

Ontology-based prediction of surgical events in laparoscopic surgery

NASA Astrophysics Data System (ADS)

Katić, Darko; Wekerle, Anna-Laura; Gärtner, Fabian; Kenngott, Hannes; Müller-Stich, Beat Peter; Dillmann, Rüdiger; Speidel, Stefanie

2013-03-01

Context-aware technologies have great potential to help surgeons during laparoscopic interventions. Their underlying idea is to create systems which can adapt their assistance functions automatically to the situation in the OR, thus relieving surgeons from the burden of managing computer assisted surgery devices manually. To this purpose, a certain kind of understanding of the current situation in the OR is essential. Beyond that, anticipatory knowledge of incoming events is beneficial, e.g. for early warnings of imminent risk situations. To achieve the goal of predicting surgical events based on previously observed ones, we developed a language to describe surgeries and surgical events using Description Logics and integrated it with methods from computational linguistics. Using n-Grams to compute probabilities of followup events, we are able to make sensible predictions of upcoming events in real-time. The system was evaluated on professionally recorded and labeled surgeries and showed an average prediction rate of 80%.

Adaptive functioning following pediatric traumatic brain injury: Relationship to executive function and processing speed.

PubMed

Shultz, Emily L; Hoskinson, Kristen R; Keim, Madelaine C; Dennis, Maureen; Taylor, H Gerry; Bigler, Erin D; Rubin, Kenneth H; Vannatta, Kathryn; Gerhardt, Cynthia A; Stancin, Terry; Yeates, Keith Owen

2016-10-01

Pediatric traumatic brain injury (TBI) may affect children's ability to perform everyday tasks (i.e., adaptive functioning). Guided by the American Association for Intellectual and Developmental Disabilities (AAIDD) model, we explored the association between TBI and adaptive functioning at increasing levels of specificity (global, AAIDD domains, and subscales). We also examined the contributions of executive function and processing speed as mediators of TBI's effects on adaptive functioning. Children (ages 8-13) with severe TBI (STBI; n = 19), mild-moderate TBI (MTBI; n = 50), or orthopedic injury (OI; n = 60) completed measures of executive function (TEA-Ch) and processing speed (WISC-IV) an average of 2.7 years postinjury (SD = 1.2; range: 1-5.3). Parents rated children's adaptive functioning (ABAS-II, BASC-2, CASP). STBI had lower global adaptive functioning (η2 = .04-.08) than the MTBI and OI groups, which typically did not differ. Deficits in the STBI group were particularly evident in the social domain, with specific deficits in social participation, leisure, and social adjustment (η2 = .06-.09). Jointly, executive function and processing speed were mediators of STBI's effects on global adaptive functioning and in conceptual and social domains. In the STBI group, executive function mediated social functioning, and processing speed mediated social participation. Children with STBI experience deficits in adaptive functioning, particularly in social adjustment, with less pronounced deficits in conceptual and practical skills. Executive function and processing speed may mediate the effects of STBI on adaptive functioning. Targeting adaptive functioning and associated cognitive deficits for intervention may enhance quality of life for pediatric TBI survivors. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Adaptive functioning following pediatric traumatic brain injury: Relationship to executive function and processing speed

PubMed Central

Shultz, Emily; Robinson, Kristen E.; Keim, Madelaine; Dennis, Maureen; Taylor, H. Gerry; Bigler, Erin D.; Rubin, Kenneth H.; Vannatta, Kathryn; Gerhardt, Cynthia A.; Stancin, Terry; Yeates, Keith Owen

2016-01-01

Objective Pediatric traumatic brain injury (TBI) may affect children’s ability to perform everyday tasks (i.e., adaptive functioning). Guided by the American Association for Intellectual and Developmental Disabilities (AAIDD) model, we explored the association between TBI and adaptive functioning at increasing levels of specificity (global, AAIDD domains, and subscales). We also examined the contributions of executive function and processing speed as mediators of TBI’s effects on adaptive functioning. Method Children (ages 8–13) with severe TBI (STBI; n=19), mild-moderate TBI (MTBI; n=50), or orthopedic injury (OI; n=60) completed measures of executive function (TEA-Ch) and processing speed (WISC-IV) an average of 2.7 years post-injury (SD = 1.2; range: 1–5.3). Parents rated children’s adaptive functioning (ABAS-II, BASC-2, CASP). Results STBI had lower global adaptive functioning (η2 = .04–.08) than the MTBI and OI groups, which typically did not differ. Deficits in the STBI group were particularly evident in the social domain, with specific deficits in social participation, leisure, and social adjustment (η2 = .06–.09). Jointly, executive function and processing speed were mediators of STBI’s effects on global adaptive functioning and in conceptual and social domains. In the STBI group, executive function mediated social functioning, and processing speed mediated social participation. Conclusions Children with STBI experience deficits in adaptive functioning, particularly in social adjustment, with less pronounced deficits in conceptual and practical skills. Executive function and processing speed may mediate the effects of STBI on adaptive functioning. Targeting adaptive functioning and associated cognitive deficits for intervention may enhance quality of life for pediatric TBI survivors. PMID:27182708

Parents' Romantic Attachment Predicts Family Ritual Meaning and Family Cohesion Among Parents and Their Children With Cancer.

PubMed

Santos, Susana; Crespo, Carla; Canavarro, M Cristina; Kazak, Anne E

2017-01-01

Family functioning is associated with adaptation in pediatric illness. This study examines the role of parents’ relationships (specifically romantic attachment) as a predictor of family ritual meaning and family cohesion for parents and their children with cancer. The dyads, 58 partnered Portuguese parents and their children in treatment, reported on family ritual meaning and family cohesion at Time 1 (T1) and after 6 months (T2). Parents also completed the questionnaire assessing romantic attachment at T1. Parents’ avoidant attachment, but not anxious attachment, predicted lower family ritual meaning and family cohesion after 6 months. T2 family ritual meaning mediated the relationship between T1 avoidant attachment and T2 family cohesion. Parents’ avoidant attachment may have a negative effect on family functioning in parents and children. Clinical intervention to address avoidant attachment or/and to promote family ritual meaning may help strengthen family ties.

Dopamine prediction errors in reward learning and addiction: from theory to neural circuitry

PubMed Central

Keiflin, Ronald; Janak, Patricia H.

2015-01-01

Summary Midbrain dopamine (DA) neurons are proposed to signal reward prediction error (RPE), a fundamental parameter in associative learning models. This RPE hypothesis provides a compelling theoretical framework for understanding DA function in reward learning and addiction. New studies support a causal role for DA-mediated RPE activity in promoting learning about natural reward; however, this question has not been explicitly tested in the context of drug addiction. In this review, we integrate theoretical models with experimental findings on the activity of DA systems, and on the causal role of specific neuronal projections and cell types, to provide a circuit-based framework for probing DA-RPE function in addiction. By examining error-encoding DA neurons in the neural network in which they are embedded, hypotheses regarding circuit-level adaptations that possibly contribute to pathological error-signaling and addiction can be formulated and tested. PMID:26494275

Child and family characteristics associated with age of diagnosis of an autism spectrum disorder in a tertiary care setting.

PubMed

Bickel, Julie; Bridgemohan, Carolyn; Sideridis, Georgios; Huntington, Noelle

2015-01-01

To identify child and family characteristics associated with age of diagnosis of autism spectrum disorder (ASD) in a tertiary care setting using objective, standardized assessments ensuring diagnostic validity and timing. The authors conducted a chart review of children who received their initial ASD diagnosis from 2007 to 2011. Child variables included gender, birth order, cognitive functioning, and for children ≤36 months, language and adaptive assessments. Family variables included insurance, maternal age, maternal education, sibling or family member with ASD, and number of children in the house. Primary outcome was age of ASD diagnosis. The authors ran multiple regression models evaluating the impact of child and family variables on the total sample and on the subsample of children ≤36 months. Median age of diagnosis was 2.9 years (range, 15 mo-13.8 yr; n = 591). In the total sample, significant predictors of earlier age of diagnosis were later birth order, higher maternal education, fewer children in the house, and a sibling with ASD. In a separate analysis of children ≤36 months of age (n = 315) with additional data for language and adaptive assessments, significant predictors of younger age of diagnosis were higher cognitive and adaptive functioning, lower receptive and expressive language, and having a sibling with ASD. This study suggests that both family and child characteristics play an important role in the early identification of ASD and that predictive variables may vary based on a child's age. Future research should help to elucidate this finding so that screening measures and policies aimed at early identification can target the most predictive factors.

Predictive Understanding of Mountainous Watershed Hydro-Biogeochemical Function and Response to Perturbations

NASA Astrophysics Data System (ADS)

Hubbard, S. S.; Williams, K. H.; Agarwal, D.; Banfield, J. F.; Beller, H. R.; Bouskill, N.; Brodie, E.; Maxwell, R. M.; Nico, P. S.; Steefel, C. I.; Steltzer, H.; Tokunaga, T. K.; Wainwright, H. M.; Dwivedi, D.; Newcomer, M. E.

2017-12-01

Recognizing the societal importance, vulnerability and complexity of mountainous watersheds, the `Watershed Function' project is developing a predictive understanding of how mountainous watersheds retain and release downgradient water, nutrients, carbon, and metals. In particular, the project is exploring how early snowmelt, drought, floods and other disturbances will influence mountainous watershed dynamics at seasonal to decadal timescales. Located in the 300km2 East River headwater catchment of the Upper Colorado River Basin, the project is guided by several constructs. First, the project considers the integrated role of surface and subsurface flow and biogeochemical reactions - from bedrock to the top of the vegetative canopy, from terrestrial through aquatic compartments, and from summit to receiving waters. The project takes a system-of-systems perspective, focused on developing new methods to quantify the cumulative watershed hydrobiogeochemical response to perturbations based on information from select subsystems within the watershed, each having distinct vegetation-subsurface biogeochemical-hydrological characteristics. A `scale-adaptive' modeling capability, in development using adaptive mesh refinement methods, serves as the organizing framework for the SFA. The scale-adaptive approach is intended to permit simulation of system-within-systems behavior - and aggregation of that behavior - from genome through watershed scales. This presentation will describe several early project discoveries and advances made using experimental, observational and numerical approaches. Among others, examples may include:quantiying how seasonal hydrological perturbations drive biogeochemical responses across critical zone compartments, with a focus on N and C transformations; metagenomic documentation of the spatial variability in floodplain meander microbial ecology; 3D reactive transport simulations of couped hydrological-biogeochemical behavior in the hyporheic zone; and new characterization and inversion approaches to quantify co-variability between above and below ground dynamics and the susceptibility of vegetation to drought stress. More information is provided at: Watershed.lbl.gov

Genetics of Cerebellar and Neocortical Expansion in Anthropoid Primates: A Comparative Approach

PubMed Central

Harrison, Peter W.; Montgomery, Stephen H.

2017-01-01

What adaptive changes in brain structure and function underpin the evolution of increased cognitive performance in humans and our close relatives? Identifying the genetic basis of brain evolution has become a major tool in answering this question. Numerous cases of positive selection, altered gene expression or gene duplication have been identified that may contribute to the evolution of the neocortex, which is widely assumed to play a predominant role in cognitive evolution. However, the components of the neocortex co-evolve with other functionally interdependent regions of the brain, most notably in the cerebellum. The cerebellum is linked to a range of cognitive tasks and expanded rapidly during hominoid evolution. Here we present data that suggest that, across anthropoid primates, protein-coding genes with known roles in cerebellum development were just as likely to be targeted by selection as genes linked to cortical development. Indeed, based on currently available gene ontology data, protein-coding genes with known roles in cerebellum development are more likely to have evolved adaptively during hominoid evolution. This is consistent with phenotypic data suggesting an accelerated rate of cerebellar expansion in apes that is beyond that predicted from scaling with the neocortex in other primates. Finally, we present evidence that the strength of selection on specific genes is associated with variation in the volume of either the neocortex or the cerebellum, but not both. This result provides preliminary evidence that co-variation between these brain components during anthropoid evolution may be at least partly regulated by selection on independent loci, a conclusion that is consistent with recent intraspecific genetic analyses and a mosaic model of brain evolution that predicts adaptive evolution of brain structure. PMID:28683440

Visuomotor adaptation needs a validation of prediction error by feedback error

PubMed Central

Gaveau, Valérie; Prablanc, Claude; Laurent, Damien; Rossetti, Yves; Priot, Anne-Emmanuelle

2014-01-01

The processes underlying short-term plasticity induced by visuomotor adaptation to a shifted visual field are still debated. Two main sources of error can induce motor adaptation: reaching feedback errors, which correspond to visually perceived discrepancies between hand and target positions, and errors between predicted and actual visual reafferences of the moving hand. These two sources of error are closely intertwined and difficult to disentangle, as both the target and the reaching limb are simultaneously visible. Accordingly, the goal of the present study was to clarify the relative contributions of these two types of errors during a pointing task under prism-displaced vision. In “terminal feedback error” condition, viewing of their hand by subjects was allowed only at movement end, simultaneously with viewing of the target. In “movement prediction error” condition, viewing of the hand was limited to movement duration, in the absence of any visual target, and error signals arose solely from comparisons between predicted and actual reafferences of the hand. In order to prevent intentional corrections of errors, a subthreshold, progressive stepwise increase in prism deviation was used, so that subjects remained unaware of the visual deviation applied in both conditions. An adaptive aftereffect was observed in the “terminal feedback error” condition only. As far as subjects remained unaware of the optical deviation and self-assigned pointing errors, prediction error alone was insufficient to induce adaptation. These results indicate a critical role of hand-to-target feedback error signals in visuomotor adaptation; consistent with recent neurophysiological findings, they suggest that a combination of feedback and prediction error signals is necessary for eliciting aftereffects. They also suggest that feedback error updates the prediction of reafferences when a visual perturbation is introduced gradually and cognitive factors are eliminated or strongly attenuated. PMID:25408644

A Robust Adaptive Autonomous Approach to Optimal Experimental Design

NASA Astrophysics Data System (ADS)

Gu, Hairong

Experimentation is the fundamental tool of scientific inquiries to understand the laws governing the nature and human behaviors. Many complex real-world experimental scenarios, particularly in quest of prediction accuracy, often encounter difficulties to conduct experiments using an existing experimental procedure for the following two reasons. First, the existing experimental procedures require a parametric model to serve as the proxy of the latent data structure or data-generating mechanism at the beginning of an experiment. However, for those experimental scenarios of concern, a sound model is often unavailable before an experiment. Second, those experimental scenarios usually contain a large number of design variables, which potentially leads to a lengthy and costly data collection cycle. Incompetently, the existing experimental procedures are unable to optimize large-scale experiments so as to minimize the experimental length and cost. Facing the two challenges in those experimental scenarios, the aim of the present study is to develop a new experimental procedure that allows an experiment to be conducted without the assumption of a parametric model while still achieving satisfactory prediction, and performs optimization of experimental designs to improve the efficiency of an experiment. The new experimental procedure developed in the present study is named robust adaptive autonomous system (RAAS). RAAS is a procedure for sequential experiments composed of multiple experimental trials, which performs function estimation, variable selection, reverse prediction and design optimization on each trial. Directly addressing the challenges in those experimental scenarios of concern, function estimation and variable selection are performed by data-driven modeling methods to generate a predictive model from data collected during the course of an experiment, thus exempting the requirement of a parametric model at the beginning of an experiment; design optimization is performed to select experimental designs on the fly of an experiment based on their usefulness so that fewest designs are needed to reach useful inferential conclusions. Technically, function estimation is realized by Bayesian P-splines, variable selection is realized by Bayesian spike-and-slab prior, reverse prediction is realized by grid-search and design optimization is realized by the concepts of active learning. The present study demonstrated that RAAS achieves statistical robustness by making accurate predictions without the assumption of a parametric model serving as the proxy of latent data structure while the existing procedures can draw poor statistical inferences if a misspecified model is assumed; RAAS also achieves inferential efficiency by taking fewer designs to acquire useful statistical inferences than non-optimal procedures. Thus, RAAS is expected to be a principled solution to real-world experimental scenarios pursuing robust prediction and efficient experimentation.

Adaptive Trajectory Prediction Algorithm for Climbing Flights

NASA Technical Reports Server (NTRS)

Schultz, Charles Alexander; Thipphavong, David P.; Erzberger, Heinz

2012-01-01

Aircraft climb trajectories are difficult to predict, and large errors in these predictions reduce the potential operational benefits of some advanced features for NextGen. The algorithm described in this paper improves climb trajectory prediction accuracy by adjusting trajectory predictions based on observed track data. It utilizes rate-of-climb and airspeed measurements derived from position data to dynamically adjust the aircraft weight modeled for trajectory predictions. In simulations with weight uncertainty, the algorithm is able to adapt to within 3 percent of the actual gross weight within two minutes of the initial adaptation. The root-mean-square of altitude errors for five-minute predictions was reduced by 73 percent. Conflict detection performance also improved, with a 15 percent reduction in missed alerts and a 10 percent reduction in false alerts. In a simulation with climb speed capture intent and weight uncertainty, the algorithm improved climb trajectory prediction accuracy by up to 30 percent and conflict detection performance, reducing missed and false alerts by up to 10 percent.

Compensatory expressive behavior for facial paralysis: adaptation to congenital or acquired disability.

PubMed

Bogart, Kathleen R; Tickle-Degnen, Linda; Ambady, Nalini

2012-02-01

Although there has been little research on the adaptive behavior of people with congenital compared to acquired disability, there is reason to predict that people with congenital conditions may be better adapted because they have lived with their conditions for their entire lives (Smart, 2008). We examined whether people with congenital facial paralysis (FP), compared to people with acquired FP, compensate more for impoverished facial expression by using alternative channels of expression (i.e., voice and body). Participants with congenital (n = 13) and acquired (n = 14) FP were videotaped while recalling emotional events. Expressive verbal behavior was measured using the Linguistic Inquiry Word Count (Pennebaker, Booth, & Francis, 2007). Nonverbal behavior and FP severity were rated by trained coders. People with congenital FP, compared to acquired FP, used more compensatory expressive verbal and nonverbal behavior in their language, voices, and bodies. The extent of FP severity had little effect on compensatory expressivity. This study provides the first behavioral evidence that people with congenital FP use more adaptations to express themselves than people with acquired FP. These behaviors could inform social functioning interventions for people with FP.

Real-Time Adaptive Control Allocation Applied to a High Performance Aircraft

NASA Technical Reports Server (NTRS)

Davidson, John B.; Lallman, Frederick J.; Bundick, W. Thomas

2001-01-01

Abstract This paper presents the development and application of one approach to the control of aircraft with large numbers of control effectors. This approach, referred to as real-time adaptive control allocation, combines a nonlinear method for control allocation with actuator failure detection and isolation. The control allocator maps moment (or angular acceleration) commands into physical control effector commands as functions of individual control effectiveness and availability. The actuator failure detection and isolation algorithm is a model-based approach that uses models of the actuators to predict actuator behavior and an adaptive decision threshold to achieve acceptable false alarm/missed detection rates. This integrated approach provides control reconfiguration when an aircraft is subjected to actuator failure, thereby improving maneuverability and survivability of the degraded aircraft. This method is demonstrated on a next generation military aircraft Lockheed-Martin Innovative Control Effector) simulation that has been modified to include a novel nonlinear fluid flow control control effector based on passive porosity. Desktop and real-time piloted simulation results demonstrate the performance of this integrated adaptive control allocation approach.

Parenting and Coregulation: Adaptive Systems for Competence in Children Experiencing Homelessness

PubMed Central

Herbers, Janette E.; Cutuli, J. J.; Supkoff, Laura M.; Narayan, Angela J.; Masten, Ann S.

2018-01-01

The role of effective parenting in promoting child executive functioning and school success was examined among 138 children (age 4 to 6 years) staying in family emergency shelters the summer before kindergarten or first grade. Parent-child coregulation, which refers to relationship processes wherein parents guide and respond to the behavior of their children, was observed during structured interaction tasks and quantified as a dyadic construct using state space grid methodology. Positive coregulation was related to children’s executive functioning and IQ, which in turn were related to teacher-reported outcomes once school began. Separate models considering parenting behavior demonstrated that EF carried indirect effects of parents’ directive control to school outcomes. Meanwhile, responsive parenting behaviors directly predicted children’s peer acceptance at school beyond effects of EF and IQ. Findings support theory and past research in developmental science indicating the importance of effective parenting in shaping positive adaptive skills among children who overcome adversity, in part through processes of coregulation. PMID:24999527

Local kernel nonparametric discriminant analysis for adaptive extraction of complex structures

NASA Astrophysics Data System (ADS)

Li, Quanbao; Wei, Fajie; Zhou, Shenghan

2017-05-01

The linear discriminant analysis (LDA) is one of popular means for linear feature extraction. It usually performs well when the global data structure is consistent with the local data structure. Other frequently-used approaches of feature extraction usually require linear, independence, or large sample condition. However, in real world applications, these assumptions are not always satisfied or cannot be tested. In this paper, we introduce an adaptive method, local kernel nonparametric discriminant analysis (LKNDA), which integrates conventional discriminant analysis with nonparametric statistics. LKNDA is adept in identifying both complex nonlinear structures and the ad hoc rule. Six simulation cases demonstrate that LKNDA have both parametric and nonparametric algorithm advantages and higher classification accuracy. Quartic unilateral kernel function may provide better robustness of prediction than other functions. LKNDA gives an alternative solution for discriminant cases of complex nonlinear feature extraction or unknown feature extraction. At last, the application of LKNDA in the complex feature extraction of financial market activities is proposed.

Otolith and Vertical Canal Contributions to Dynamic Postural Control

NASA Technical Reports Server (NTRS)

Black, F. Owen

1999-01-01

The objective of this project is to determine: 1) how do normal subjects adjust postural movements in response to changing or altered otolith input, for example, due to aging? and 2) how do patients adapt postural control after altered unilateral or bilateral vestibular sensory inputs such as ablative inner ear surgery or ototoxicity, respectively? The following hypotheses are under investigation: 1) selective alteration of otolith input or abnormalities of otolith receptor function will result in distinctive spatial, frequency, and temporal patterns of head movements and body postural sway dynamics. 2) subjects with reduced, altered, or absent vertical semicircular canal receptor sensitivity but normal otolith receptor function or vice versa, should show predictable alterations of body and head movement strategies essential for the control of postural sway and movement. The effect of altered postural movement control upon compensation and/or adaptation will be determined. These experiments provide data for the development of computational models of postural control in normals, vestibular deficient subjects and normal humans exposed to unusual force environments, including orbital space flight.

Cardiac vagal control and children’s adaptive functioning: A meta-analysis

PubMed Central

Graziano, Paulo; Derefinko, Karen

2014-01-01

Polyvagal theory has influenced research on the role of cardiac vagal control, indexed by respiratory sinus arrhythmia withdrawal (RSA-W) during challenging states, in children’s self-regulation. However, it remains unclear how well RSA-W predicts adaptive functioning (AF) outcomes and whether certain caveats of measuring RSA (e.g., respiration) significantly impact these associations. A meta-analysis of 44 studies (n = 4,996 children) revealed small effect sizes such that greater levels of RSA-W were related to fewer externalizing, internalizing, and cognitive/academic problems. In contrast, RSA-W was differentially related to children’s social problems according to sample type (community vs. clinical/at-risk). The relations between RSA-W and children’s AF outcomes were stronger among studies that co-varied baseline RSA and in Caucasian children (no effect was found for respiration). Children from clinical/at-risk samples displayed lower levels of baseline RSA and RSA-W compared to children from community samples. Theoretical/practical implications for the study of cardiac vagal control are discussed. PMID:23648264

Interest Level in 2-Year-Olds with Autism Spectrum Disorder Predicts Rate of Verbal, Nonverbal, and Adaptive Skill Acquisition

ERIC Educational Resources Information Center

Klintwall, Lars; Macari, Suzanne; Eikeseth, Svein; Chawarska, Katarzyna

2015-01-01

Recent studies have suggested that skill acquisition rates for children with autism spectrum disorders receiving early interventions can be predicted by child motivation. We examined whether level of interest during an Autism Diagnostic Observation Schedule assessment at 2?years predicts subsequent rates of verbal, nonverbal, and adaptive skill…

Unified Sequence-Based Association Tests Allowing for Multiple Functional Annotations and Meta-analysis of Noncoding Variation in Metabochip Data.

PubMed

He, Zihuai; Xu, Bin; Lee, Seunggeun; Ionita-Laza, Iuliana

2017-09-07

Substantial progress has been made in the functional annotation of genetic variation in the human genome. Integrative analysis that incorporates such functional annotations into sequencing studies can aid the discovery of disease-associated genetic variants, especially those with unknown function and located outside protein-coding regions. Direct incorporation of one functional annotation as weight in existing dispersion and burden tests can suffer substantial loss of power when the functional annotation is not predictive of the risk status of a variant. Here, we have developed unified tests that can utilize multiple functional annotations simultaneously for integrative association analysis with efficient computational techniques. We show that the proposed tests significantly improve power when variant risk status can be predicted by functional annotations. Importantly, when functional annotations are not predictive of risk status, the proposed tests incur only minimal loss of power in relation to existing dispersion and burden tests, and under certain circumstances they can even have improved power by learning a weight that better approximates the underlying disease model in a data-adaptive manner. The tests can be constructed with summary statistics of existing dispersion and burden tests for sequencing data, therefore allowing meta-analysis of multiple studies without sharing individual-level data. We applied the proposed tests to a meta-analysis of noncoding rare variants in Metabochip data on 12,281 individuals from eight studies for lipid traits. By incorporating the Eigen functional score, we detected significant associations between noncoding rare variants in SLC22A3 and low-density lipoprotein and total cholesterol, associations that are missed by standard dispersion and burden tests. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Diversifying selection in the wheat stem rust fungus acts predominantly on pathogen-associated gene families and reveals candidate effectors

PubMed Central

Sperschneider, Jana; Ying, Hua; Dodds, Peter N.; Gardiner, Donald M.; Upadhyaya, Narayana M.; Singh, Karam B.; Manners, John M.; Taylor, Jennifer M.

2014-01-01

Plant pathogens cause severe losses to crop plants and threaten global food production. One striking example is the wheat stem rust fungus, Puccinia graminis f. sp. tritici, which can rapidly evolve new virulent pathotypes in response to resistant host lines. Like several other filamentous fungal and oomycete plant pathogens, its genome features expanded gene families that have been implicated in host-pathogen interactions, possibly encoding effector proteins that interact directly with target host defense proteins. Previous efforts to understand virulence largely relied on the prediction of secreted, small and cysteine-rich proteins as candidate effectors and thus delivered an overwhelming number of candidates. Here, we implement an alternative analysis strategy that uses the signal of adaptive evolution as a line of evidence for effector function, combined with comparative information and expression data. We demonstrate that in planta up-regulated genes that are rapidly evolving are found almost exclusively in pathogen-associated gene families, affirming the impact of host-pathogen co-evolution on genome structure and the adaptive diversification of specialized gene families. In particular, we predict 42 effector candidates that are conserved only across pathogens, induced during infection and rapidly evolving. One of our top candidates has recently been shown to induce genotype-specific hypersensitive cell death in wheat. This shows that comparative genomics incorporating the evolutionary signal of adaptation is powerful for predicting effector candidates for laboratory verification. Our system can be applied to a wide range of pathogens and will give insight into host-pathogen dynamics, ultimately leading to progress in strategies for disease control. PMID:25225496

An Expert System For Multispectral Threat Assessment And Response

NASA Astrophysics Data System (ADS)

Steinberg, Alan N.

1987-05-01

A concept has been defined for an automatic system to manage the self-defense of a combat aircraft. Distinctive new features of this concept include: a. the flexible prioritization of tasks and coordinated use of sensor, countermeasures, flight systems and weapons assets by means of an automated planning function; b. the integration of state-of-the-art data fusion algorithms with event prediction processing; c. the use of advanced Artificial Intelligence tools to emulate the decision processes of tactical EW experts. Threat Assessment functions (a) estimate threat identity, lethality and intent on the basis of multi-spectral sensor data, and (b) predict the time to critical events in threat engagements (e.g., target acquisition, tracking, weapon launch, impact). Response Management functions (a) select candidate responses to reported threat situations; (b) estimate the effects of candidate actions on survival; and (c) coordinate the assignment of sensors, weapons and countermeasures with the flight plan. The system employs Finite State Models to represent current engagements and to predict subsequent events. Each state in a model is associated with a set of observable features, allowing interpretation of sensor data and adaptive use of sensor assets. Defined conditions on state transitions allow prediction of times to critical future states and are used in planning self-defensive responses, which are designed either to impede a particular state transition or to force a transition to a lower threat state.

Predicting intentions to consume functional foods and supplements to offset memory loss using an adaptation of protection motivation theory.

PubMed

Cox, D N; Koster, A; Russell, C G

2004-08-01

The widespread use of dietary supplements and so-called 'functional foods' is thought to be partially motivated by self-control of health. However, whilst consumers want foods associated with well-being or disease prevention, they are unlikely to be willing to compromise on taste or technology. This presents a dilemma for promoters of functional foods. Middle-aged consumers' intentions to consume functional foods or supplements that may improve memory were tested within an adaptation of Protection Motivation theory (PMT). Participants evaluated text descriptions of four products described as: having an unpleasant bitter taste (Natural-FF); having 'additives' to reduce bitterness (Sweetened-FF); being genetically modified to enhance function (GM-FF) and Supplements. Participants were recruited as being of high and low perceived vulnerability to memory failure. In total, 290 middle-aged consumers (aged 40-60 years) participated in the study. Motivations to consume the GM-FF were the lowest. There were gender differences between intention to consume the supplements, Natural-FF and Sweetened-FF and product differences within genders. Women were less favourable than men in their attitudes towards genetic modification in general. Regression analyses indicated that PM predictors of intention to consume functional foods or supplements explained 59-63% of the variance (R2). Overall, perceived 'efficacy' (of the behaviour) and self-efficacy were the most important predictors of intentions to consume.

SpliceRover: Interpretable Convolutional Neural: Networks for Improved Splice Site Prediction.

PubMed

Zuallaert, Jasper; Godin, Fréderic; Kim, Mijung; Soete, Arne; Saeys, Yvan; De Neve, Wesley

2018-06-21

During the last decade, improvements in high-throughput sequencing have generated a wealth of genomic data. Functionally interpreting these sequences and finding the biological signals that are hallmarks of gene function and regulation is currently mostly done using automated genome annotation platforms, which mainly rely on integrated machine learning frameworks to identify different functional sites of interest, including splice sites. Splicing is an essential step in the gene regulation process, and the correct identification of splice sites is a major cornerstone in a genome annotation system. In this paper, we present SpliceRover, a predictive deep learning approach that outperforms the state-of-the-art in splice site prediction. SpliceRover uses convolutional neural networks (CNNs), which have been shown to obtain cutting edge performance on a wide variety of prediction tasks. We adapted this approach to deal with genomic sequence inputs, and show it consistently outperforms already existing approaches, with relative improvements in prediction effectiveness of up to 80.9% when measured in terms of false discovery rate. However, a major criticism of CNNs concerns their "black box" nature, as mechanisms to obtain insight into their reasoning processes are limited. To facilitate interpretability of the SpliceRover models, we introduce an approach to visualize the biologically relevant information learnt. We show that our visualization approach is able to recover features known to be important for splice site prediction (binding motifs around the splice site, presence of polypyrimidine tracts and branch points), as well as reveal new features (e.g., several types of exclusion patterns near splice sites). SpliceRover is available as a web service. The prediction tool and instructions can be found at http://bioit2.irc.ugent.be/splicerover/. Supplementary materials are available at Bioinformatics online.

Predicting life-history adaptations to pollutants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maltby, L.

1995-12-31

Animals may adapt to pollutant stress so that individuals from polluted environments are less susceptible than those from unpolluted environments. In addition to such direct adaptations, animals may respond to pollutant stress by life-history modifications; so-called indirect adaptations. This paper will demonstrate how, by combining life-history theory and toxicological data, it is possible to predict stress-induced alterations in reproductive output and offspring size. Pollutant-induced alterations in age-specific survival in favor of adults and reductions in juvenile growth, conditions are predicted to select for reduced investment in reproduction and the allocation of this investment into fewer, larger offspring. Field observations onmore » the freshwater crustaceans, Asellus aquaticus and Gammarus pulex, support these predictions. Females from metal-polluted sites had lower investment in reproduction and produced larger offspring than females of the same species from unpolluted sites. Moreover, interpopulation differences in reproductive biology persisted in laboratory cultures indicating that they had a genetic basis and were therefore due to adaptation rather than acclimation. The general applicability of this approach will be considered.« less

Implications of climate change for the fishes of the British Isles.

PubMed

Graham, C T; Harrod, C

2009-04-01

Recent climatic change has been recorded across the globe. Although environmental change is a characteristic feature of life on Earth and has played a major role in the evolution and global distribution of biodiversity, predicted future rates of climatic change, especially in temperature, are such that they will exceed any that has occurred over recent geological time. Climate change is considered as a key threat to biodiversity and to the structure and function of ecosystems that may already be subject to significant anthropogenic stress. The current understanding of climate change and its likely consequences for the fishes of Britain and Ireland and the surrounding seas are reviewed through a series of case studies detailing the likely response of several marine, diadromous and freshwater fishes to climate change. Changes in climate, and in particular, temperature have and will continue to affect fish at all levels of biological organization: cellular, individual, population, species, community and ecosystem, influencing physiological and ecological processes in a number of direct, indirect and complex ways. The response of fishes and of other aquatic taxa will vary according to their tolerances and life stage and are complex and difficult to predict. Fishes may respond directly to climate-change-related shifts in environmental processes or indirectly to other influences, such as community-level interactions with other taxa. However, the ability to adapt to the predicted changes in climate will vary between species and between habitats and there will be winners and losers. In marine habitats, recent changes in fish community structure will continue as fishes shift their distributions relative to their temperature preferences. This may lead to the loss of some economically important cold-adapted species such as Gadus morhua and Clupea harengus from some areas around Britain and Ireland, and the establishment of some new, warm-adapted species. Increased temperatures are likely to favour cool-adapted (e.g. Perca fluviatilis) and warm-adapted freshwater fishes (e.g. roach Rutilus rutilus and other cyprinids) whose distribution and reproductive success may currently be constrained by temperature rather than by cold-adapted species (e.g. salmonids). Species that occur in Britain and Ireland that are at the edge of their distribution will be most affected, both negatively and positively. Populations of conservation importance (e.g.Salvelinus alpinus and Coregonus spp.) may decline irreversibly. However, changes in food-web dynamics and physiological adaptation, for example because of climate change, may obscure or alter predicted responses. The residual inertia in climate systems is such that even a complete cessation in emissions would still leave fishes exposed to continued climate change for at least half a century. Hence, regardless of the success or failure of programmes aimed at curbing climate change, major changes in fish communities can be expected over the next 50 years with a concomitant need to adapt management strategies accordingly.

Diabetic db/db mice do not develop heart failure upon pressure overload: a longitudinal in vivo PET, MRI, and MRS study on cardiac metabolic, structural, and functional adaptations.

PubMed

Abdurrachim, Desiree; Nabben, Miranda; Hoerr, Verena; Kuhlmann, Michael T; Bovenkamp, Philipp; Ciapaite, Jolita; Geraets, Ilvy M E; Coumans, Will; Luiken, Joost J F P; Glatz, Jan F C; Schäfers, Michael; Nicolay, Klaas; Faber, Cornelius; Hermann, Sven; Prompers, Jeanine J

2017-08-01

Heart failure is associated with altered myocardial substrate metabolism and impaired cardiac energetics. Comorbidities like diabetes may influence the metabolic adaptations during heart failure development. We quantified to what extent changes in substrate preference, lipid accumulation, and energy status predict the longitudinal development of hypertrophy and failure in the non-diabetic and the diabetic heart. Transverse aortic constriction (TAC) was performed in non-diabetic (db/+) and diabetic (db/db) mice to induce pressure overload. Magnetic resonance imaging, 31P magnetic resonance spectroscopy (MRS), 1H MRS, and 18F-fluorodeoxyglucose-positron emission tomography (PET) were applied to measure cardiac function, energy status, lipid content, and glucose uptake, respectively. In vivo measurements were complemented with ex vivo techniques of high-resolution respirometry, proteomics, and western blotting to elucidate the underlying molecular pathways. In non-diabetic mice, TAC induced progressive cardiac hypertrophy and dysfunction, which correlated with increased protein kinase D-1 (PKD1) phosphorylation and increased glucose uptake. These changes in glucose utilization preceded a reduction in cardiac energy status. At baseline, compared with non-diabetic mice, diabetic mice showed normal cardiac function, higher lipid content and mitochondrial capacity for fatty acid oxidation, and lower PKD1 phosphorylation, glucose uptake, and energetics. Interestingly, TAC affected cardiac function only mildly in diabetic mice, which was accompanied by normalization of phosphorylated PKD1, glucose uptake, and cardiac energy status. The cardiac metabolic adaptations in diabetic mice seem to prevent the heart from failing upon pressure overload, suggesting that restoring the balance between glucose and fatty acid utilization is beneficial for cardiac function. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions please email: journals.permissions@oup.com.

Artificial intelligence models for predicting the performance of biological wastewater treatment plant in the removal of Kjeldahl Nitrogen from wastewater

NASA Astrophysics Data System (ADS)

Manu, D. S.; Thalla, Arun Kumar

2017-11-01

The current work demonstrates the support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) modeling to assess the removal efficiency of Kjeldahl Nitrogen of a full-scale aerobic biological wastewater treatment plant. The influent variables such as pH, chemical oxygen demand, total solids (TS), free ammonia, ammonia nitrogen and Kjeldahl Nitrogen are used as input variables during modeling. Model development focused on postulating an adaptive, functional, real-time and alternative approach for modeling the removal efficiency of Kjeldahl Nitrogen. The input variables used for modeling were daily time series data recorded at wastewater treatment plant (WWTP) located in Mangalore during the period June 2014-September 2014. The performance of ANFIS model developed using Gbell and trapezoidal membership functions (MFs) and SVM are assessed using different statistical indices like root mean square error, correlation coefficients (CC) and Nash Sutcliff error (NSE). The errors related to the prediction of effluent Kjeldahl Nitrogen concentration by the SVM modeling appeared to be reasonable when compared to that of ANFIS models with Gbell and trapezoidal MF. From the performance evaluation of the developed SVM model, it is observed that the approach is capable to define the inter-relationship between various wastewater quality variables and thus SVM can be potentially applied for evaluating the efficiency of aerobic biological processes in WWTP.

Community Landscapes: An Integrative Approach to Determine Overlapping Network Module Hierarchy, Identify Key Nodes and Predict Network Dynamics

PubMed Central

Kovács, István A.; Palotai, Robin; Szalay, Máté S.; Csermely, Peter

2010-01-01

Background Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. Methodology/Principal Findings Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1) determine pervasively overlapping modules with high resolution; (2) uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3) allow the determination of key network nodes and (4) help to predict network dynamics. Conclusions/Significance The concept opens a wide range of possibilities to develop new approaches and applications including network routing, classification, comparison and prediction. PMID:20824084

Striatum-medial prefrontal cortex connectivity predicts developmental changes in reinforcement learning.

PubMed

van den Bos, Wouter; Cohen, Michael X; Kahnt, Thorsten; Crone, Eveline A

2012-06-01

During development, children improve in learning from feedback to adapt their behavior. However, it is still unclear which neural mechanisms might underlie these developmental changes. In the current study, we used a reinforcement learning model to investigate neurodevelopmental changes in the representation and processing of learning signals. Sixty-seven healthy volunteers between ages 8 and 22 (children: 8-11 years, adolescents: 13-16 years, and adults: 18-22 years) performed a probabilistic learning task while in a magnetic resonance imaging scanner. The behavioral data demonstrated age differences in learning parameters with a stronger impact of negative feedback on expected value in children. Imaging data revealed that the neural representation of prediction errors was similar across age groups, but functional connectivity between the ventral striatum and the medial prefrontal cortex changed as a function of age. Furthermore, the connectivity strength predicted the tendency to alter expectations after receiving negative feedback. These findings suggest that the underlying mechanisms of developmental changes in learning are not related to differences in the neural representation of learning signals per se but rather in how learning signals are used to guide behavior and expectations.

Using natural selection and optimization for smarter vegetation models - challenges and opportunities

NASA Astrophysics Data System (ADS)

Franklin, Oskar; Han, Wang; Dieckmann, Ulf; Cramer, Wolfgang; Brännström, Åke; Pietsch, Stephan; Rovenskaya, Elena; Prentice, Iain Colin

2017-04-01

Dynamic global vegetation models (DGVMs) are now indispensable for understanding the biosphere and for estimating the capacity of ecosystems to provide services. The models are continuously developed to include an increasing number of processes and to utilize the growing amounts of observed data becoming available. However, while the versatility of the models is increasing as new processes and variables are added, their accuracy suffers from the accumulation of uncertainty, especially in the absence of overarching principles controlling their concerted behaviour. We have initiated a collaborative working group to address this problem based on a 'missing law' - adaptation and optimization principles rooted in natural selection. Even though this 'missing law' constrains relationships between traits, and therefore can vastly reduce the number of uncertain parameters in ecosystem models, it has rarely been applied to DGVMs. Our recent research have shown that optimization- and trait-based models of gross primary production can be both much simpler and more accurate than current models based on fixed functional types, and that observed plant carbon allocations and distributions of plant functional traits are predictable with eco-evolutionary models. While there are also many other examples of the usefulness of these and other theoretical principles, it is not always straight-forward to make them operational in predictive models. In particular on longer time scales, the representation of functional diversity and the dynamical interactions among individuals and species presents a formidable challenge. Here we will present recent ideas on the use of adaptation and optimization principles in vegetation models, including examples of promising developments, but also limitations of the principles and some key challenges.

Strategies for memory-based decision making: Modeling behavioral and neural signatures within a cognitive architecture.

PubMed

Fechner, Hanna B; Pachur, Thorsten; Schooler, Lael J; Mehlhorn, Katja; Battal, Ceren; Volz, Kirsten G; Borst, Jelmer P

2016-12-01

How do people use memories to make inferences about real-world objects? We tested three strategies based on predicted patterns of response times and blood-oxygen-level-dependent (BOLD) responses: one strategy that relies solely on recognition memory, a second that retrieves additional knowledge, and a third, lexicographic (i.e., sequential) strategy, that considers knowledge conditionally on the evidence obtained from recognition memory. We implemented the strategies as computational models within the Adaptive Control of Thought-Rational (ACT-R) cognitive architecture, which allowed us to derive behavioral and neural predictions that we then compared to the results of a functional magnetic resonance imaging (fMRI) study in which participants inferred which of two cities is larger. Overall, versions of the lexicographic strategy, according to which knowledge about many but not all alternatives is searched, provided the best account of the joint patterns of response times and BOLD responses. These results provide insights into the interplay between recognition and additional knowledge in memory, hinting at an adaptive use of these two sources of information in decision making. The results highlight the usefulness of implementing models of decision making within a cognitive architecture to derive predictions on the behavioral and neural level. Copyright © 2016 Elsevier B.V. All rights reserved.

A novel parallel pipeline structure of VP9 decoder

NASA Astrophysics Data System (ADS)

Qin, Huabiao; Chen, Wu; Yi, Sijun; Tan, Yunfei; Yi, Huan

2018-04-01

To improve the efficiency of VP9 decoder, a novel parallel pipeline structure of VP9 decoder is presented in this paper. According to the decoding workflow, VP9 decoder can be divided into sub-modules which include entropy decoding, inverse quantization, inverse transform, intra prediction, inter prediction, deblocking and pixel adaptive compensation. By analyzing the computing time of each module, hotspot modules are located and the causes of low efficiency of VP9 decoder can be found. Then, a novel pipeline decoder structure is designed by using mixed parallel decoding methods of data division and function division. The experimental results show that this structure can greatly improve the decoding efficiency of VP9.

The development of an acute care case manager orientation.

PubMed

Strzelecki, S; Brobst, R

1997-01-01

The authors describe the development of an inpatient acute care case manager orientation in a community hospital. Benner's application of the Dreyfus model of skill acquisition provides the basis for the orientation program. The candidates for the case manager position were expert clinicians. Because of the role change it was projected that they would function as advanced beginners. It was also predicted that, as the case managers progressed within the role, the educational process would need to be adapted to facilitate progression of skills to the proficient level. Feedback from participants reinforced that the model supported the case manager in the role transition. In addition, the model provided a predictive framework for ongoing educational activities.

Clinical factors and the decision to transfuse chronic dialysis patients.

PubMed

Whitman, Cynthia B; Shreay, Sanatan; Gitlin, Matthew; van Oijen, Martijn G H; Spiegel, Brennan M R

2013-11-01

Red blood cell transfusion was previously the principle therapy for anemia in CKD but became less prevalent after the introduction of erythropoiesis-stimulating agents. This study used adaptive choice-based conjoint analysis to identify preferences and predictors of transfusion decision-making in CKD. A computerized adaptive choice-based conjoint survey was administered between June and August of 2012 to nephrologists, internists, and hospitalists listed in the American Medical Association Masterfile. The survey quantified the relative importance of 10 patient attributes, including hemoglobin levels, age, occult blood in stool, severity of illness, eligibility for transplant, iron indices, erythropoiesis-stimulating agents, cardiovascular disease, and functional status. Triggers of transfusions in common dialysis scenarios were studied, and based on adaptive choice-based conjoint-derived preferences, relative importance by performing multivariable regression to identify predictors of transfusion preferences was assessed. A total of 350 providers completed the survey (n=305 nephrologists; mean age=46 years; 21% women). Of 10 attributes assessed, absolute hemoglobin level was the most important driver of transfusions, accounting for 29% of decision-making, followed by functional status (16%) and cardiovascular comorbidities (12%); 92% of providers transfused when hemoglobin was 7.5 g/dl, independent of other factors. In multivariable regression, Veterans Administration providers were more likely to transfuse at 8.0 g/dl (odds ratio, 5.9; 95% confidence interval, 1.9 to 18.4). Although transplant eligibility explained only 5% of decision-making, nephrologists were five times more likely to value it as important compared with non-nephrologists (odds ratio, 5.2; 95% confidence interval, 2.4 to 11.1). Adaptive choice-based conjoint analysis was useful in predicting influences on transfusion decisions. Hemoglobin level, functional status, and cardiovascular comorbidities most strongly influenced transfusion decision-making, but preference variations were observed among subgroups.

Assessment of parametric uncertainty for groundwater reactive transport modeling,

USGS Publications Warehouse

Shi, Xiaoqing; Ye, Ming; Curtis, Gary P.; Miller, Geoffery L.; Meyer, Philip D.; Kohler, Matthias; Yabusaki, Steve; Wu, Jichun

2014-01-01

The validity of using Gaussian assumptions for model residuals in uncertainty quantification of a groundwater reactive transport model was evaluated in this study. Least squares regression methods explicitly assume Gaussian residuals, and the assumption leads to Gaussian likelihood functions, model parameters, and model predictions. While the Bayesian methods do not explicitly require the Gaussian assumption, Gaussian residuals are widely used. This paper shows that the residuals of the reactive transport model are non-Gaussian, heteroscedastic, and correlated in time; characterizing them requires using a generalized likelihood function such as the formal generalized likelihood function developed by Schoups and Vrugt (2010). For the surface complexation model considered in this study for simulating uranium reactive transport in groundwater, parametric uncertainty is quantified using the least squares regression methods and Bayesian methods with both Gaussian and formal generalized likelihood functions. While the least squares methods and Bayesian methods with Gaussian likelihood function produce similar Gaussian parameter distributions, the parameter distributions of Bayesian uncertainty quantification using the formal generalized likelihood function are non-Gaussian. In addition, predictive performance of formal generalized likelihood function is superior to that of least squares regression and Bayesian methods with Gaussian likelihood function. The Bayesian uncertainty quantification is conducted using the differential evolution adaptive metropolis (DREAM(zs)) algorithm; as a Markov chain Monte Carlo (MCMC) method, it is a robust tool for quantifying uncertainty in groundwater reactive transport models. For the surface complexation model, the regression-based local sensitivity analysis and Morris- and DREAM(ZS)-based global sensitivity analysis yield almost identical ranking of parameter importance. The uncertainty analysis may help select appropriate likelihood functions, improve model calibration, and reduce predictive uncertainty in other groundwater reactive transport and environmental modeling.

Non-adaptive plasticity potentiates rapid adaptive evolution of gene expression in nature.

PubMed

Ghalambor, Cameron K; Hoke, Kim L; Ruell, Emily W; Fischer, Eva K; Reznick, David N; Hughes, Kimberly A

2015-09-17

Phenotypic plasticity is the capacity for an individual genotype to produce different phenotypes in response to environmental variation. Most traits are plastic, but the degree to which plasticity is adaptive or non-adaptive depends on whether environmentally induced phenotypes are closer or further away from the local optimum. Existing theories make conflicting predictions about whether plasticity constrains or facilitates adaptive evolution. Debate persists because few empirical studies have tested the relationship between initial plasticity and subsequent adaptive evolution in natural populations. Here we show that the direction of plasticity in gene expression is generally opposite to the direction of adaptive evolution. We experimentally transplanted Trinidadian guppies (Poecilia reticulata) adapted to living with cichlid predators to cichlid-free streams, and tested for evolutionary divergence in brain gene expression patterns after three to four generations. We find 135 transcripts that evolved parallel changes in expression within the replicated introduction populations. These changes are in the same direction exhibited in a native cichlid-free population, suggesting rapid adaptive evolution. We find 89% of these transcripts exhibited non-adaptive plastic changes in expression when the source population was reared in the absence of predators, as they are in the opposite direction to the evolved changes. By contrast, the remaining transcripts exhibiting adaptive plasticity show reduced population divergence. Furthermore, the most plastic transcripts in the source population evolved reduced plasticity in the introduction populations, suggesting strong selection against non-adaptive plasticity. These results support models predicting that adaptive plasticity constrains evolution, whereas non-adaptive plasticity potentiates evolution by increasing the strength of directional selection. The role of non-adaptive plasticity in evolution has received relatively little attention; however, our results suggest that it may be an important mechanism that predicts evolutionary responses to new environments.

Does the PFC model of analogy account for decision making, problem solving, reasoning, flexibility, adaptability, and even creativity?

PubMed

Barutta, Joaquin; Guex, Raphael; Ibáñez, Agustín

2010-06-01

Abstract From everyday cognition to scientific discovery, analogical processes play an important role: bringing connection, integration, and interrelation of information. Recently, a PFC model of analogy has been proposed to explain many cognitive processes and integrate general functional properties of PFC. We argue here that analogical processes do not suffice to explain the cognitive processes and functions of PFC. Moreover the model does not satisfactorily integrate specific explanatory mechanisms required for the different processes involved. Its relevance would be improved if fewer cognitive phenomena were considered and more specific predictions and explanations about those processes were stated.

Self-functioning and perceived parenting: relations of parental empathy and love inconsistency with narcissism, depression, and self-esteem.

PubMed

Trumpeter, Nevelyn N; Watson, P J; O'Leary, Brian J; Weathington, Bart L

2008-03-01

In Heinz Kohut's (1977, 1984) theory of the psychology of the self, good parenting provides a child with optimal frustration and just the right amount of loving empathic concern. In the present study, the authors examined the relations of perceived parental empathy and love inconsistency with measures of narcissism, self-esteem, and depression. In a sample of university undergraduates (N=232; 78 men, 153 women, and 1 nonresponder), perceived parental empathy predicted more adaptive self-functioning, whereas parental love inconsistency was related to psychological maladjustment. These results support the theoretical assumption that perceived parental empathy is associated with healthy self-development.

Grid-Adapted FUN3D Computations for the Second High Lift Prediction Workshop

NASA Technical Reports Server (NTRS)

Lee-Rausch, E. M.; Rumsey, C. L.; Park, M. A.

2014-01-01

Contributions of the unstructured Reynolds-averaged Navier-Stokes code FUN3D to the 2nd AIAA CFD High Lift Prediction Workshop are described, and detailed comparisons are made with experimental data. Using workshop-supplied grids, results for the clean wing configuration are compared with results from the structured code CFL3D Using the same turbulence model, both codes compare reasonably well in terms of total forces and moments, and the maximum lift is similarly over-predicted for both codes compared to experiment. By including more representative geometry features such as slat and flap brackets and slat pressure tube bundles, FUN3D captures the general effects of the Reynolds number variation, but under-predicts maximum lift on workshop-supplied grids in comparison with the experimental data, due to excessive separation. However, when output-based, off-body grid adaptation in FUN3D is employed, results improve considerably. In particular, when the geometry includes both brackets and the pressure tube bundles, grid adaptation results in a more accurate prediction of lift near stall in comparison with the wind-tunnel data. Furthermore, a rotation-corrected turbulence model shows improved pressure predictions on the outboard span when using adapted grids.

Pitch-Learning Algorithm For Speech Encoders

NASA Technical Reports Server (NTRS)

Bhaskar, B. R. Udaya

1988-01-01

Adaptive algorithm detects and corrects errors in sequence of estimates of pitch period of speech. Algorithm operates in conjunction with techniques used to estimate pitch period. Used in such parametric and hybrid speech coders as linear predictive coders and adaptive predictive coders.

Cardiorespiratory adaptation to breath-holding in air: Analysis via a cardiopulmonary simulation model.

PubMed

Albanese, Antonio; Limei Cheng; Ursino, Mauro; Chbat, Nicolas W

2015-01-01

Apnea via breath-holding (BH) in air induces cardiorespiratory adaptation that involves the activation of several reflex mechanisms and their complex interactions. Hence, the effects of BH in air on cardiorespiratory function can become hardly predictable and difficult to be interpreted. Particularly, the effect on heart rate is not yet completely understood because of the contradicting results of different physiological studies. In this paper we apply our previously developed cardiopulmonary model (CP Model) to a scenario of BH with a twofold intent: (1) further validating the CP Model via comparison against experimental data; (2) gaining insights into the physiological reasoning for such contradicting experimental results. Model predictions agreed with published experimental animal and human data and indicated that heart rate increases during BH in air. Changes in the balance between sympathetic and vagal effects on heart rate within the model proved to be effective in inverting directions of the heart rate changes during BH. Hence, the model suggests that intra-subject differences in such sympatho-vagal balance may be one of the reasons for the contradicting experimental results.

Functional decline in the elderly with MCI: Cultural adaptation of the ADCS-ADL scale.

PubMed

Cintra, Fabiana Carla Matos da Cunha; Cintra, Marco Túlio Gualberto; Nicolato, Rodrigo; Bertola, Laiss; Ávila, Rafaela Teixeira; Malloy-Diniz, Leandro Fernandes; Moraes, Edgar Nunes; Bicalho, Maria Aparecida Camargos

2017-07-01

Translate, transcultural adaptation and application to Brazilian Portuguese of the Alzheimer's Disease Cooperative Study - Activities of Daily Living (ADCS-ADL) scale as a cognitive screening instrument. We applied the back translation added with pretest and bilingual methods. The sample was composed by 95 elderly individuals and their caregivers. Thirty-two (32) participants were diagnosed as mild cognitive impairment (MCI) patients, 33 as Alzheimer's disease (AD) patients and 30 were considered as cognitively normal individuals. There were only little changes on the scale. The Cronbach alpha coefficient was 0.89. The scores were 72.9 for control group, followed by MCI (65.1) and by AD (55.9), with a p-value < 0.001. The ROC curve value was 0.89. We considered a cut point of 72 and we observed a sensibility of 86.2%, specificity of 70%, positive predictive value of 86.2%, negative predictive value of 70%, positive likelihood ratio of 2.9 and negative likelihood ratio of 0.2. ADCS-ADL scale presents satisfactory psychometric properties to discriminate between MCI, AD and normal cognition.

Adaptation for Planting and Irrigation Decisions to Changing Monsoon Regime in Northeast India: Risk-based Hydro-economic Optimization

NASA Astrophysics Data System (ADS)

Zhu, T.; Cai, X.

2013-12-01

Delay in onset of Indian summer monsoon becomes increasingly frequent. Delayed monsoon and occasional monsoon failures seriously affect agricultural production in the northeast as well as other parts of India. In the Vaishali district of the Bihar State, Monsoon rainfall is very skewed and erratic, often concentrating in shorter durations. Farmers in Vaishali reported that delayed Monsoon affected paddy planting and, consequently delayed cropping cycle, putting crops under the risks of 'terminal heat.' Canal system in the district does not function due to lack of maintenance; irrigation relies almost entirely on groundwater. Many small farmers choose not to irrigate when monsoon onset is delayed due to high diesel price, leading to reduced production or even crop failure. Some farmers adapt to delayed onset of Monsoon by planting short-duration rice, which gives the flexibility for planting the next season crops. Other sporadic autonomous adaptation activities were observed as well, with various levels of success. Adaptation recommendations and effective policy interventions are much needed. To explore robust options to adapt to the changing Monsoon regime, we build a stochastic programming model to optimize revenues of farmer groups categorized by landholding size, subject to stochastic Monsoon onset and rainfall amount. Imperfect probabilistic long-range forecast is used to inform the model onset and rainfall amount probabilities; the 'skill' of the forecasting is measured using probabilities of correctly predicting events in the past derived through hindcasting. Crop production functions are determined using self-calibrating Positive Mathematical Programming approach. The stochastic programming model aims to emulate decision-making behaviors of representative farmer agents through making choices in adaptation, including crop mix, planting dates, irrigation, and use of weather information. A set of technological and policy intervention scenarios are tested, including irrigation subsidies, drought and heat-tolerant crop varieties, and enhancing agricultural extension. A portfolio of prioritized adaption options are recommended for the study area.

Metagenomic Functional Potential Predicts Degradation Rates of a Model Organophosphorus Xenobiotic in Pesticide Contaminated Soils

PubMed Central

Jeffries, Thomas C.; Rayu, Smriti; Nielsen, Uffe N.; Lai, Kaitao; Ijaz, Ali; Nazaries, Loic; Singh, Brajesh K.

2018-01-01

Chemical contamination of natural and agricultural habitats is an increasing global problem and a major threat to sustainability and human health. Organophosphorus (OP) compounds are one major class of contaminant and can undergo microbial degradation, however, no studies have applied system-wide ecogenomic tools to investigate OP degradation or use metagenomics to understand the underlying mechanisms of biodegradation in situ and predict degradation potential. Thus, there is a lack of knowledge regarding the functional genes and genomic potential underpinning degradation and community responses to contamination. Here we address this knowledge gap by performing shotgun sequencing of community DNA from agricultural soils with a history of pesticide usage and profiling shifts in functional genes and microbial taxa abundance. Our results showed two distinct groups of soils defined by differing functional and taxonomic profiles. Degradation assays suggested that these groups corresponded to the organophosphorus degradation potential of soils, with the fastest degrading community being defined by increases in transport and nutrient cycling pathways and enzymes potentially involved in phosphorus metabolism. This was against a backdrop of taxonomic community shifts potentially related to contamination adaptation and reflecting the legacy of exposure. Overall our results highlight the value of using holistic system-wide metagenomic approaches as a tool to predict microbial degradation in the context of the ecology of contaminated habitats. PMID:29515526

Contributions to workload of rotational optical transformations

NASA Technical Reports Server (NTRS)

Atkinson, R. P.; Harrington, T. L.

1985-01-01

An investigation of visuomotor adaptation to optical rotation and optical inversion was conducted. Experiment 1 examined the visuomotor adaptability of subjects to an optically rotating visual world with a univariate repeated measures design. Experiment 1A tested one major prediction of a model of adaptation put forth by Welch who predicted that the aversive drive state that triggers adaptation would be habituated to fairly rapidly. Experiment 2 was conducted to investigate the role of motor activity in adaptation to optical rotation. Specifically, this experiment contrasted the reafference hypothesis and the proprioceptive change hypothesis. Experiment 3 examined the role of cognition, error-corrective feedback, and proprioceptive and/or reafferent feedback in visuomotor adaptation to optical inversion. Implications for research and implications for practice were suggested for all experiments.

Automatic Adaptation to Fast Input Changes in a Time-Invariant Neural Circuit

PubMed Central

Bharioke, Arjun; Chklovskii, Dmitri B.

2015-01-01

Neurons must faithfully encode signals that can vary over many orders of magnitude despite having only limited dynamic ranges. For a correlated signal, this dynamic range constraint can be relieved by subtracting away components of the signal that can be predicted from the past, a strategy known as predictive coding, that relies on learning the input statistics. However, the statistics of input natural signals can also vary over very short time scales e.g., following saccades across a visual scene. To maintain a reduced transmission cost to signals with rapidly varying statistics, neuronal circuits implementing predictive coding must also rapidly adapt their properties. Experimentally, in different sensory modalities, sensory neurons have shown such adaptations within 100 ms of an input change. Here, we show first that linear neurons connected in a feedback inhibitory circuit can implement predictive coding. We then show that adding a rectification nonlinearity to such a feedback inhibitory circuit allows it to automatically adapt and approximate the performance of an optimal linear predictive coding network, over a wide range of inputs, while keeping its underlying temporal and synaptic properties unchanged. We demonstrate that the resulting changes to the linearized temporal filters of this nonlinear network match the fast adaptations observed experimentally in different sensory modalities, in different vertebrate species. Therefore, the nonlinear feedback inhibitory network can provide automatic adaptation to fast varying signals, maintaining the dynamic range necessary for accurate neuronal transmission of natural inputs. PMID:26247884

Continuity and Change in, and Child Predictors of, Caregiver Reported Anxiety Symptoms in Young People with Autism Spectrum Disorder: A Follow-Up Study.

PubMed

Teh, Elizabeth J; Chan, Diana Mei-En; Tan, Germaine Ke Jia; Magiati, Iliana

2017-12-01

Little is known about continuity, change and predictors of anxiety in ASD. This follow-up study investigated changes in caregiver-reported anxiety in 54 non-referred youth with ASD after 10-19 months. Earlier child predictors of later anxiety were also examined. Anxiety scores were generally stable. Time 1 ASD repetitive behavior symptoms, but not social/communication symptoms, predicted Time 2 total anxiety scores, over and above child age, gender and adaptive functioning scores, but this predictive relationship was fully mitigated by Time 1 anxiety scores when these were included as a covariate in the regression model. Exploring bi-directionality between autism and anxiety symptomatology, Time 1 anxiety scores did not predict Time 2 ASD symptoms. Preliminary clinical implications and possible future directions are discussed.

Age and Adaptive Functioning in Children and Adolescents with ASD: The Effects of Intellectual Functioning and ASD Symptom Severity.

PubMed

Hill, Trenesha L; Gray, Sarah A O; Kamps, Jodi L; Enrique Varela, R

2015-12-01

The present study examined the moderating effects of intellectual functioning and ASD symptom severity on the relation between age and adaptive functioning in 220 youth with autism spectrum disorder (ASD). Regression analysis indicated that intellectual functioning and ASD symptom severity moderated the relation between age and adaptive functioning. For younger children with lower intellectual functioning, higher ASD symptom severity was associated with better adaptive functioning than that of those with lower ASD symptom severity. Similarly, for older children with higher intellectual functioning, higher ASD symptom severity was associated with better adaptive functioning than that of those with lower ASD symptom severity. Analyses by subscales suggest that this pattern is driven by the Conceptual subscale. Clinical and research implications are discussed.

Age and Adaptive Functioning in Children and Adolescents with ASD: The Effects of Intellectual Functioning and ASD Symptom Severity

PubMed Central

Hill, Trenesha L.; Gray, Sarah A. O.; Kamps, Jodi L.; Varela, R. Enrique

2016-01-01

The present study examined the moderating effects of intellectual functioning and ASD symptom severity on the relation between age and adaptive functioning in 220 youth with autism spectrum disorder (ASD). Regression analysis indicated that intellectual functioning and ASD symptom severity moderated the relation between age and adaptive functioning. For younger children with lower intellectual functioning, higher ASD symptom severity was associated with better adaptive functioning than that of those with lower ASD symptom severity. Similarly, for older children with higher intellectual functioning, higher ASD symptom severity was associated with better adaptive functioning than that of those with lower ASD symptom severity. Analyses by subscales suggest that this pattern is driven by the Conceptual subscale. Clinical and research implications are discussed. PMID:26174048

Attachment, Sexual Assertiveness, and Sexual Outcomes in Women with Provoked Vestibulodynia and Their Partners: A Mediation Model.

PubMed

Leclerc, Bianca; Bergeron, Sophie; Brassard, Audrey; Bélanger, Claude; Steben, Marc; Lambert, Bernard

2015-08-01

Provoked vestibulodynia (PVD) is a prevalent women's sexual pain disorder, which is associated with sexual function difficulties. Attachment theory has been used to understand adult sexual outcomes, providing a useful framework for examining sexual adaptation in couples confronted with PVD. Research to date indicates that anxious and avoidant attachment dimensions correlate with worse sexual outcomes in community and clinical samples. The present study examined the association between attachment, pain, sexual function, and sexual satisfaction in a sample of 101 couples in which the women presented with PVD. The actor-partner interdependence model was used in order to investigate both actor and partner effects. This study also examined the role of sexual assertiveness as a mediator of these associations via structural equation modeling. Women completed measures of pain intensity and both members of the couple completed measures of romantic attachment, sexual assertiveness, sexual function, and satisfaction. Results indicated that attachment dimensions did not predict pain intensity. Both anxious and avoidant attachment were associated with lower sexual satisfaction. Only attachment avoidance predicted lower sexual function in women. Partner effects indicated that higher sexual assertiveness in women predicted higher sexual satisfaction in men. Finally, women's sexual assertiveness was found to be a significant mediator of the relationship between their attachment dimensions, sexual function, and satisfaction. Findings highlight the importance of examining how anxious and avoidant attachment may lead to difficulties in sexual assertiveness and to less satisfying sexual interactions in couples where women suffer from PVD.

Functional Evidence for Memory Stabilization in Sensorimotor Adaptation: A 24-h Resting-State fMRI Study.

PubMed

Della-Maggiore, Valeria; Villalta, Jorge I; Kovacevic, Natasa; McIntosh, Anthony Randal

2017-03-01

Adaptation learning is crucial to maintain precise motor control in face of environmental perturbations. Although much progress has been made in understanding the psychophysics and neurophysiology of sensorimotor adaptation (SA), the time course of memory consolidation remains elusive. The lack of a reproducible gradient of memory resistance using protocols of retrograde interference has even led to the proposal that memories produced through SA do not consolidate. Here, we pursued an alternative approach using resting-state fMRI to track changes in functional connectivity (FC) induced by learning. Given that consolidation leads to long-term memory, we hypothesized that a change in FC that predicted long-term memory but not short-term memory would provide indirect evidence for memory stabilization. Six scans were acquired before, 15 min, 1, 3, 5.5, and 24 h after training on a center-out task under veridical or distorted visual feedback. The experimental group showed an increment in FC of a network including motor, premotor, posterior parietal cortex, cerebellum, and putamen that peaked at 5.5 h. Crucially, the strengthening of this network correlated positively with long-term retention but negatively with short-term retention. Our work provides evidence, suggesting that adaptation memories stabilize within a 6-h window, and points to different mechanisms subserving short- and long-term memory. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The cerebellum in action: a simulation and robotics study.

PubMed

Hofstötter, Constanze; Mintz, Matti; Verschure, Paul F M J

2002-10-01

The control or prediction of the precise timing of events are central aspects of the many tasks assigned to the cerebellum. Despite much detailed knowledge of its physiology and anatomy, it remains unclear how the cerebellar circuitry can achieve such an adaptive timing function. We present a computational model pursuing this question for one extensively studied type of cerebellar-mediated learning: the classical conditioning of discrete motor responses. This model combines multiple current assumptions on the function of the cerebellar circuitry and was used to investigate whether plasticity in the cerebellar cortex alone can mediate adaptive conditioned response timing. In particular, we studied the effect of changes in the strength of the synapses formed between parallel fibres and Purkinje cells under the control of a negative feedback loop formed between inferior olive, cerebellar cortex and cerebellar deep nuclei. The learning performance of the model was evaluated at the circuit level in simulated conditioning experiments as well as at the behavioural level using a mobile robot. We demonstrate that the model supports adaptively timed responses under real-world conditions. Thus, in contrast to many other models that have focused on cerebellar-mediated conditioning, we investigated whether and how the suggested underlying mechanisms could give rise to behavioural phenomena.

Spiders in motion: demonstrating adaptation, structure-function relationships, and trade-offs in invertebrates.

PubMed

Bowlin, Melissa S; McLeer, Dorothy F; Danielson-Francois, Anne M

2014-03-01

Evolutionary history and structural considerations constrain all aspects of animal physiology. Constraints on invertebrate locomotion are especially straightforward for students to observe and understand. In this exercise, students use spiders to investigate the concepts of adaptation, structure-function relationships, and trade-offs. Students measure burst and endurance performance in several taxonomic families of spiders whose ecological niches have led to different locomotory adaptations. Based on observations of spiders in their natural habitat and prior background information, students make predictions about spider performance. Students then construct their own knowledge by performing a hands-on, inquiry-based scientific experiment where the results are not necessarily known. Depending on the specific families chosen, students can observe that web-dwelling spiders have more difficulty navigating complex terrestrial terrain than ground-dwelling spiders and that there is a trade-off between burst performance and endurance performance in spiders. Our inexpensive runway design allows for countless variations on this basic experiment; for example, we have successfully used runways to show students how the performance of heterothermic ectotherms varies with temperature. High levels of intra- and interindividual variation in performance underscore the importance of using multiple trials and statistical tests. Finally, this laboratory activity can be completely student driven or standardized, depending on the instructor's preference.

Genetic variation in N- and C-terminal regions of bovine DNAJA1 heat shock protein gene in African, Asian and American cattle.

PubMed

Ajayi, Oyeyemi O; Peters, Sunday O; De Donato, Marcos; Mujibi, F Denis; Khan, Waqas A; Hussain, Tanveer; Babar, Masroor E; Imumorin, Ikhide G; Thomas, Bolaji N

2018-01-01

DNAJA1 or heat shock protein 40 (Hsp40) is associated with heat adaptation in various organisms. We amplified and sequenced a total of 1,142 bp of bovine Hsp40 gene representing the critical N-terminal (NTR) and C-terminal (CTR) regions in representative samples of African, Asian and American cattle breeds. Eleven and 9 different haplotypes were observed in the NTR in Asian and African breeds respectively while in American Brangus, only two mutations were observed resulting in two haplotypes. The CTR appears to be highly conserved between cattle and yak. In-silico functional analysis with PANTHER predicted putative deleterious functional impact of c.161 T>A; p. V54Q while alignment of bovine and human NTR-J domains revealed that p.Q19H, p.E20Q and p. E21X mutations occurred in helix 2 and p.V54Q missense mutation occurred in helix 3 respectively. The 124 bp insertion found in the yak DNAJA1 ortholog may have significant functional relevance warranting further investigation. Our results suggest that these genetic differences may be concomitant with population genetic history and possible functional consequences for climate adaptation in bovidae.

Functional neuroimaging of emotional learning and autonomic reactions.

PubMed

Peper, Martin; Herpers, Martin; Spreer, Joachim; Hennig, Jürgen; Zentner, Josef

2006-06-01

This article provides a selective overview of the functional neuroimaging literature with an emphasis on emotional activation processes. Emotions are fast and flexible response systems that provide basic tendencies for adaptive action. From the range of involved component functions, we first discuss selected automatic mechanisms that control basic adaptational changes. Second, we illustrate how neuroimaging work has contributed to the mapping of the network components associated with basic emotion families (fear, anger, disgust, happiness), and secondary dimensional concepts that organise the meaning space for subjective experience and verbal labels (emotional valence, activity/intensity, approach/withdrawal, etc.). Third, results and methodological difficulties are discussed in view of own neuroimaging experiments that investigated the component functions involved in emotional learning. The amygdala, prefrontal cortex, and striatum form a network of reciprocal connections that show topographically distinct patterns of activity as a correlate of up and down regulation processes during an emotional episode. Emotional modulations of other brain systems have attracted recent research interests. Emotional neuroimaging calls for more representative designs that highlight the modulatory influences of regulation strategies and socio-cultural factors responsible for inhibitory control and extinction. We conclude by emphasising the relevance of the temporal process dynamics of emotional activations that may provide improved prediction of individual differences in emotionality.

Prediction of natural disasters basing of chrono-and-information field characters

NASA Astrophysics Data System (ADS)

Sapunov, Valentin

2013-04-01

Living organisms are able to predict some future events particular catastrophic incidents. This is adaptive characters producing by evolution. The more energy produces incident the more possibility to predict one. Wild animals escaped natural hazards including tsunami (e.g. extremal tsunami in Asia December 2004). Living animals are able to predict strong phenomena of obscure nature. For example majority of animals escaped Tungus catastrophe taking place in Siberia at 1908. Wild animals are able to predict nuclear weapon experiences. The obscure characters are not typical for human, but they are fixed under probability 15%. Such were summarized by L.Vasiliev (1961). Effective theory describing such a characters is absent till now. N.Kozyrev (1991) suggested existence of unknown physical field (but gravitation and electro magnetic). The field was named "time" or "chrono". Some characters of the field appeared to be object of physical experiment. Kozyrev suggested specific role of the field for function of living organisms. Transition of biological information throw space (telepathy) and time (proscopy) may be based on characters of such a field. Hence physical chrono-and-information field is under consideration. Animals are more familiar with such a field than human. Evolutionary process experienced with possibility of extremal development of contact with such a field using highest primates. This mode of evolution appeared to stay obscure producing probable species "Wildman" (Bigfoot). Specific adaptive fitches suggest impossibility to study of such a species by usual ecological approaches. The perspective way for study of mysterious phenomena of physic is researches of this field characters.

Survey of adaptive image coding techniques

NASA Technical Reports Server (NTRS)

Habibi, A.

1977-01-01

The general problem of image data compression is discussed briefly with attention given to the use of Karhunen-Loeve transforms, suboptimal systems, and block quantization. A survey is then conducted encompassing the four categories of adaptive systems: (1) adaptive transform coding (adaptive sampling, adaptive quantization, etc.), (2) adaptive predictive coding (adaptive delta modulation, adaptive DPCM encoding, etc.), (3) adaptive cluster coding (blob algorithms and the multispectral cluster coding technique), and (4) adaptive entropy coding.