Multitask TSK fuzzy system modeling by mining intertask common hidden structure.

PubMed

Jiang, Yizhang; Chung, Fu-Lai; Ishibuchi, Hisao; Deng, Zhaohong; Wang, Shitong

2015-03-01

The classical fuzzy system modeling methods implicitly assume data generated from a single task, which is essentially not in accordance with many practical scenarios where data can be acquired from the perspective of multiple tasks. Although one can build an individual fuzzy system model for each task, the result indeed tells us that the individual modeling approach will get poor generalization ability due to ignoring the intertask hidden correlation. In order to circumvent this shortcoming, we consider a general framework for preserving the independent information among different tasks and mining hidden correlation information among all tasks in multitask fuzzy modeling. In this framework, a low-dimensional subspace (structure) is assumed to be shared among all tasks and hence be the hidden correlation information among all tasks. Under this framework, a multitask Takagi-Sugeno-Kang (TSK) fuzzy system model called MTCS-TSK-FS (TSK-FS for multiple tasks with common hidden structure), based on the classical L2-norm TSK fuzzy system, is proposed in this paper. The proposed model can not only take advantage of independent sample information from the original space for each task, but also effectively use the intertask common hidden structure among multiple tasks to enhance the generalization performance of the built fuzzy systems. Experiments on synthetic and real-world datasets demonstrate the applicability and distinctive performance of the proposed multitask fuzzy system model in multitask regression learning scenarios.

Application of Multi-task Lasso Regression in the Stellar Parametrization

NASA Astrophysics Data System (ADS)

Chang, L. N.; Zhang, P. A.

2015-01-01

The multi-task learning approaches have attracted the increasing attention in the fields of machine learning, computer vision, and artificial intelligence. By utilizing the correlations in tasks, learning multiple related tasks simultaneously is better than learning each task independently. An efficient multi-task Lasso (Least Absolute Shrinkage Selection and Operator) regression algorithm is proposed in this paper to estimate the physical parameters of stellar spectra. It not only makes different physical parameters share the common features, but also can effectively preserve their own peculiar features. Experiments were done based on the ELODIE data simulated with the stellar atmospheric simulation model, and on the SDSS data released by the American large survey Sloan. The precision of the model is better than those of the methods in the related literature, especially for the acceleration of gravity (lg g) and the chemical abundance ([Fe/H]). In the experiments, we changed the resolution of the spectrum, and applied the noises with different signal-to-noise ratio (SNR) to the spectrum, so as to illustrate the stability of the model. The results show that the model is influenced by both the resolution and the noise. But the influence of the noise is larger than that of the resolution. In general, the multi-task Lasso regression algorithm is easy to operate, has a strong stability, and also can improve the overall accuracy of the model.

Automated Pathogenesis-Based Diagnosis of Lumbar Neural Foraminal Stenosis via Deep Multiscale Multitask Learning.

PubMed

Han, Zhongyi; Wei, Benzheng; Leung, Stephanie; Nachum, Ilanit Ben; Laidley, David; Li, Shuo

2018-02-15

Pathogenesis-based diagnosis is a key step to prevent and control lumbar neural foraminal stenosis (LNFS). It conducts both early diagnosis and comprehensive assessment by drawing crucial pathological links between pathogenic factors and LNFS. Automated pathogenesis-based diagnosis would simultaneously localize and grade multiple spinal organs (neural foramina, vertebrae, intervertebral discs) to diagnose LNFS and discover pathogenic factors. The automated way facilitates planning optimal therapeutic schedules and relieving clinicians from laborious workloads. However, no successful work has been achieved yet due to its extreme challenges since 1) multiple targets: each lumbar spine has at least 17 target organs, 2) multiple scales: each type of target organ has structural complexity and various scales across subjects, and 3) multiple tasks, i.e., simultaneous localization and diagnosis of all lumbar organs, are extremely difficult than individual tasks. To address these huge challenges, we propose a deep multiscale multitask learning network (DMML-Net) integrating a multiscale multi-output learning and a multitask regression learning into a fully convolutional network. 1) DMML-Net merges semantic representations to reinforce the salience of numerous target organs. 2) DMML-Net extends multiscale convolutional layers as multiple output layers to boost the scale-invariance for various organs. 3) DMML-Net joins a multitask regression module and a multitask loss module to prompt the mutual benefit between tasks. Extensive experimental results demonstrate that DMML-Net achieves high performance (0.845 mean average precision) on T1/T2-weighted MRI scans from 200 subjects. This endows our method an efficient tool for clinical LNFS diagnosis.

Variation at work: alternations between physically and mentally demanding tasks in blue-collar occupations.

PubMed

Jahncke, Helena; Hygge, Staffan; Mathiassen, Svend Erik; Hallman, David; Mixter, Susanna; Lyskov, Eugene

2017-09-01

The aims of this questionnaire study were to describe the occurrence and desired number of alternations between mental and physical tasks in industrial and non-industrial blue-collar work, and determine to which extent selected personal and occupational factors influence these conditions. On average, the 122 participating workers (55 females) reported to have close to four alternations per day between mental and physical tasks, and to desire more alternations than they actually had. They also expressed a general preference for performing a physical task after a mental task and vice versa. In univariate regression models, the desired change in task alternations was significantly associated with gender, age, occupation, years with current work tasks and perceived job control, while occupation was the only significant determinant in a multiple regression model including all factors. Our results suggest that alternations between productive physical and mental tasks could be a viable option in future job rotation. Practitioner Summary: We addressed attitudes among blue-collar workers to alternations between physically and mentally demanding tasks. More alternations were desired than those occurring in the job, and workers preferred performing a physical task after a mental and vice versa. Alternating physical and mental tasks could, thus, be a viable option in job rotation.

Gait initiation time is associated with the risk of multiple falls-A population-based study.

PubMed

Callisaya, Michele L; Blizzard, Leigh; Martin, Kara; Srikanth, Velandai K

2016-09-01

In a population-based study of older people to examine whether 1) overall gait initiation (GI) time or its components are associated with falls and 2) GI under dual-task is a stronger predictor of falls risk than under single-task. Participants aged 60-85 years were randomly selected from the electoral roll. GI was obtained with a force platform under both single and dual-task conditions. Falls were ascertained prospectively over a 12-month period. Log multinomial regression was used to examine the association between GI time (total and its components) and risk of single and multiple falls. Age, sex and physiological and cognitive falls risk factors were considered as confounders. The mean age of the sample (n=124) was 71.0 (SD 6.8) years and 58.9% (n=73) were male. Over 12 months 21.8% (n=27) of participants reported a single fall and 16.1% (n=20) reported multiple falls. Slower overall GI time under both single (RR all per 100ms 1.28, 95%CI 1.03, 1.58) and dual-task (RR 1.14, 95%CI 1.02, 1.27) was associated with increased risk of multiple, but not single falls (p<0.05). Multiple falls were also associated with slower time to first lateral movement under single-task (RR 1.90 95%CI 0.59, 1.51) and swing time under dual-task condition (RR 1.44 95%CI 1.08, 1.94). Slower GI time is associated with the risk of multiple falls independent of other risk factors, suggesting it could be used as part of a comprehensive falls assessment. Time to the first lateral movement under single-task may be the best measures of this risk. Copyright © 2016 Elsevier B.V. All rights reserved.

NIMEFI: gene regulatory network inference using multiple ensemble feature importance algorithms.

PubMed

Ruyssinck, Joeri; Huynh-Thu, Vân Anh; Geurts, Pierre; Dhaene, Tom; Demeester, Piet; Saeys, Yvan

2014-01-01

One of the long-standing open challenges in computational systems biology is the topology inference of gene regulatory networks from high-throughput omics data. Recently, two community-wide efforts, DREAM4 and DREAM5, have been established to benchmark network inference techniques using gene expression measurements. In these challenges the overall top performer was the GENIE3 algorithm. This method decomposes the network inference task into separate regression problems for each gene in the network in which the expression values of a particular target gene are predicted using all other genes as possible predictors. Next, using tree-based ensemble methods, an importance measure for each predictor gene is calculated with respect to the target gene and a high feature importance is considered as putative evidence of a regulatory link existing between both genes. The contribution of this work is twofold. First, we generalize the regression decomposition strategy of GENIE3 to other feature importance methods. We compare the performance of support vector regression, the elastic net, random forest regression, symbolic regression and their ensemble variants in this setting to the original GENIE3 algorithm. To create the ensemble variants, we propose a subsampling approach which allows us to cast any feature selection algorithm that produces a feature ranking into an ensemble feature importance algorithm. We demonstrate that the ensemble setting is key to the network inference task, as only ensemble variants achieve top performance. As second contribution, we explore the effect of using rankwise averaged predictions of multiple ensemble algorithms as opposed to only one. We name this approach NIMEFI (Network Inference using Multiple Ensemble Feature Importance algorithms) and show that this approach outperforms all individual methods in general, although on a specific network a single method can perform better. An implementation of NIMEFI has been made publicly available.

Application of Multi-task Lasso Regression in the Parametrization of Stellar Spectra

NASA Astrophysics Data System (ADS)

Chang, Li-Na; Zhang, Pei-Ai

2015-07-01

The multi-task learning approaches have attracted the increasing attention in the fields of machine learning, computer vision, and artificial intelligence. By utilizing the correlations in tasks, learning multiple related tasks simultaneously is better than learning each task independently. An efficient multi-task Lasso (Least Absolute Shrinkage Selection and Operator) regression algorithm is proposed in this paper to estimate the physical parameters of stellar spectra. It not only can obtain the information about the common features of the different physical parameters, but also can preserve effectively their own peculiar features. Experiments were done based on the ELODIE synthetic spectral data simulated with the stellar atmospheric model, and on the SDSS data released by the American large-scale survey Sloan. The estimation precision of our model is better than those of the methods in the related literature, especially for the estimates of the gravitational acceleration (lg g) and the chemical abundance ([Fe/H]). In the experiments we changed the spectral resolution, and applied the noises with different signal-to-noise ratios (SNRs) to the spectral data, so as to illustrate the stability of the model. The results show that the model is influenced by both the resolution and the noise. But the influence of the noise is larger than that of the resolution. In general, the multi-task Lasso regression algorithm is easy to operate, it has a strong stability, and can also improve the overall prediction accuracy of the model.

Task deactivation reductions and atrophy within parietal default mode regions are overlapping but only weakly correlated in mild cognitive impairment

PubMed Central

Threlkeld, Zachary D.; Jicha, Greg A.; Smith, Charles D.; Gold, Brian T.

2012-01-01

Reduced task deactivation within regions of the default mode network (DMN) has been frequently reported in Alzheimer’s disease (AD) and amnestic mild cognitive impairment (aMCI). As task deactivations reductions become increasingly used in the study of early AD states, it is important to understand their relationship to atrophy. To address this issue, the present study compared task deactivation reductions during a lexical decision task and atrophy in aMCI, using a series of parallel voxel-wise and region-wise analyses of fMRI and structural data. Our results identified multiple regions within parietal cortex as convergence areas of task deactivation and atrophy in aMCI. Relationships between parietal regions showing overlapping task deactivation reductions and atrophy in aMCI were then explored. Regression analyses demonstrated minimal correlation between task deactivation reductions and either local or global atrophy in aMCI. In addition, a logistic regression model which combined task deactivation reductions and atrophy in parietal DMN regions showed higher classificatory accuracy of aMCI than separate task deactivation or atrophy models. Results suggest that task deactivation reductions and atrophy in parietal regions provide complementary rather than redundant information in aMCI. Future longitudinal studies will be required to assess the utility of combining task deactivation reductions and atrophy in the detection of early AD. PMID:21860094

Genotype-phenotype association study via new multi-task learning model

PubMed Central

Huo, Zhouyuan; Shen, Dinggang

2018-01-01

Research on the associations between genetic variations and imaging phenotypes is developing with the advance in high-throughput genotype and brain image techniques. Regression analysis of single nucleotide polymorphisms (SNPs) and imaging measures as quantitative traits (QTs) has been proposed to identify the quantitative trait loci (QTL) via multi-task learning models. Recent studies consider the interlinked structures within SNPs and imaging QTs through group lasso, e.g. ℓ2,1-norm, leading to better predictive results and insights of SNPs. However, group sparsity is not enough for representing the correlation between multiple tasks and ℓ2,1-norm regularization is not robust either. In this paper, we propose a new multi-task learning model to analyze the associations between SNPs and QTs. We suppose that low-rank structure is also beneficial to uncover the correlation between genetic variations and imaging phenotypes. Finally, we conduct regression analysis of SNPs and QTs. Experimental results show that our model is more accurate in prediction than compared methods and presents new insights of SNPs. PMID:29218896

Exploring General Versus Task-Specific Assessments of Metacognition in University Chemistry Students: A Multitrait-Multimethod Analysis

NASA Astrophysics Data System (ADS)

Wang, Chia-Yu

2015-08-01

The purpose of this study was to use multiple assessments to investigate the general versus task-specific characteristics of metacognition in dissimilar chemistry topics. This mixed-method approach investigated the nature of undergraduate general chemistry students' metacognition using four assessments: a self-report questionnaire, assessment of concurrent metacognitive skills, confidence judgment, and calibration accuracy. Data were analyzed using a multitrait-multimethod correlation matrix, supplemented with regression analyses, and qualitative interpretation. Significant correlations among task performance, calibration accuracy, and concurrent metacognition within a task suggest a converging relationship. Confidence judgment, however, was not associated with task performance or the other metacognitive measurements. The results partially support hypotheses of both general and task-specific metacognition. However, general and task-specific properties of metacognition were detected using different assessments. Case studies were constructed for two participants to illustrate how concurrent metacognition varied within different task demands. Considerations of how each assessment may appropriate different metacognitive constructs and the importance of the alignment of analytical constructs when using multiple assessments are discussed. These results may help lead to improvements in metacognition assessment and may provide insights into designs of effective metacognitive instruction.

Personality and attention: Levels of neuroticism and extraversion can predict attentional performance during a change detection task.

PubMed

Hahn, Sowon; Buttaccio, Daniel R; Hahn, Jungwon; Lee, Taehun

2015-01-01

The present study demonstrates that levels of extraversion and neuroticism can predict attentional performance during a change detection task. After completing a change detection task built on the flicker paradigm, participants were assessed for personality traits using the Revised Eysenck Personality Questionnaire (EPQ-R). Multiple regression analyses revealed that higher levels of extraversion predict increased change detection accuracies, while higher levels of neuroticism predict decreased change detection accuracies. In addition, neurotic individuals exhibited decreased sensitivity A' and increased fixation dwell times. Hierarchical regression analyses further revealed that eye movement measures mediate the relationship between neuroticism and change detection accuracies. Based on the current results, we propose that neuroticism is associated with decreased attentional control over the visual field, presumably due to decreased attentional disengagement. Extraversion can predict increased attentional performance, but the effect is smaller than the relationship between neuroticism and attention.

Brain networks of temporal preparation: A multiple regression analysis of neuropsychological data.

PubMed

Triviño, Mónica; Correa, Ángel; Lupiáñez, Juan; Funes, María Jesús; Catena, Andrés; He, Xun; Humphreys, Glyn W

2016-11-15

There are only a few studies on the brain networks involved in the ability to prepare in time, and most of them followed a correlational rather than a neuropsychological approach. The present neuropsychological study performed multiple regression analysis to address the relationship between both grey and white matter (measured by magnetic resonance imaging in patients with brain lesion) and different effects in temporal preparation (Temporal orienting, Foreperiod and Sequential effects). Two versions of a temporal preparation task were administered to a group of 23 patients with acquired brain injury. In one task, the cue presented (a red versus green square) to inform participants about the time of appearance (early versus late) of a target stimulus was blocked, while in the other task the cue was manipulated on a trial-by-trial basis. The duration of the cue-target time intervals (400 versus 1400ms) was always manipulated within blocks in both tasks. Regression analysis were conducted between either the grey matter lesion size or the white matter tracts disconnection and the three temporal preparation effects separately. The main finding was that each temporal preparation effect was predicted by a different network of structures, depending on cue expectancy. Specifically, the Temporal orienting effect was related to both prefrontal and temporal brain areas. The Foreperiod effect was related to right and left prefrontal structures. Sequential effects were predicted by both parietal cortex and left subcortical structures. These findings show a clear dissociation of brain circuits involved in the different ways to prepare in time, showing for the first time the involvement of temporal areas in the Temporal orienting effect, as well as the parietal cortex in the Sequential effects. Copyright © 2016 Elsevier Inc. All rights reserved.

Predicting MHC-II binding affinity using multiple instance regression

PubMed Central

EL-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2011-01-01

Reliably predicting the ability of antigen peptides to bind to major histocompatibility complex class II (MHC-II) molecules is an essential step in developing new vaccines. Uncovering the amino acid sequence correlates of the binding affinity of MHC-II binding peptides is important for understanding pathogenesis and immune response. The task of predicting MHC-II binding peptides is complicated by the significant variability in their length. Most existing computational methods for predicting MHC-II binding peptides focus on identifying a nine amino acids core region in each binding peptide. We formulate the problems of qualitatively and quantitatively predicting flexible length MHC-II peptides as multiple instance learning and multiple instance regression problems, respectively. Based on this formulation, we introduce MHCMIR, a novel method for predicting MHC-II binding affinity using multiple instance regression. We present results of experiments using several benchmark datasets that show that MHCMIR is competitive with the state-of-the-art methods for predicting MHC-II binding peptides. An online web server that implements the MHCMIR method for MHC-II binding affinity prediction is freely accessible at http://ailab.cs.iastate.edu/mhcmir. PMID:20855923

Executive function in middle childhood and the relationship with theory of mind.

PubMed

Wilson, Jennifer; Andrews, Glenda; Hogan, Christy; Wang, Si; Shum, David H K

2018-01-01

A group of 126 typically developing children (aged 5-12 years) completed three cool executive function tasks (spatial working memory, stop signal, intra-extra dimensional shift), two hot executive function tasks (gambling, delay of gratification), one advanced theory of mind task (strange stories with high versus low affective tone), and a vocabulary test. Older children performed better than younger children, consistent with the protracted development of hot and cool executive functions and theory of mind. Multiple regression analyses showed that hot and cool executive functions were correlated but they predicted theory of mind in different ways.

College Women's Value Orientations toward Family, Career, and Graduate School.

ERIC Educational Resources Information Center

Battle, Ann; Wigfield, Allan

2003-01-01

Scales assessing intention to attend graduate school and family/career values were completed by 216 college women. Multiple regression analyses demonstrated that components of task value (intrinsic-attainment, utility, cost) predicted graduate study intentions. Strong career orientation was positively related to the valuing of graduate education.…

Multiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular Malaysia.

PubMed

Ng, Kar Yong; Awang, Norhashidah

2018-01-06

Frequent haze occurrences in Malaysia have made the management of PM 10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM 10 variation and good forecast of PM 10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM 10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM 10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM 10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.

The Effect of Work Characteristics on Dermatologic Symptoms in Hairdressers

PubMed Central

2014-01-01

Objectives Hairdressers in Korea perform various tasks and are exposed to health risk factors such as chemical substances or prolonged duration of wet work. The objective of this study is to provide descriptive statistics on the demographics and work characteristics of hairdressers in Korea and to identify work-related risk factors for dermatologic symptoms in hairdressers. Methods 1,054 hairdressers were selected and analyzed for this study. Independent variables were exposure to chemical substances, the training status of the hairdressers, and the main tasks required of them, and the dependent variable was the incidence of dermatologic symptoms. The relationships between work characteristics and dermatologic symptoms were evaluated by estimating odds ratios using multiple logistic regression analysis. Results Among the 1,054 study subjects, 212 hairdressers (20.1%) complained of dermatologic symptoms, and the symptoms were more prevalent in younger, unmarried or highly educated hairdressers. The main tasks that comprise the majority of the wet work were strictly determined by training status, since 96.5% of staff hairdressers identified washing as their main task, while only 1.5% and 2.0% of master and designer hairdressers, respectively, identified this as their main task. Multiple logistic regressions was performed to estimate odds ratios. While exposure to hairdressing chemicals showed no significant effect on the odds ratio for the incidence of dermatologic symptoms, higher odds ratios of dermatologic symptoms were shown in staff hairdressers (2.70, 95% CI: 1.32 - 5.51) and in hairdressers who perform washing as their main task (2.03, 95% CI: 1.22 - 3.37), after adjusting for general and work characteristics. Conclusions This study showed that the training status and main tasks of hairdressers are closely related to each other and that the training status and main tasks of hairdressers are related to the incidence of dermatologic symptoms. This suggests that in the future, regulations on working conditions and health management guidelines for hairdressers should be established. PMID:25028609

Building a new predictor for multiple linear regression technique-based corrective maintenance turnaround time.

PubMed

Cruz, Antonio M; Barr, Cameron; Puñales-Pozo, Elsa

2008-01-01

This research's main goals were to build a predictor for a turnaround time (TAT) indicator for estimating its values and use a numerical clustering technique for finding possible causes of undesirable TAT values. The following stages were used: domain understanding, data characterisation and sample reduction and insight characterisation. Building the TAT indicator multiple linear regression predictor and clustering techniques were used for improving corrective maintenance task efficiency in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). Multiple linear regression was used for building a predictive TAT value model. The variables contributing to such model were clinical engineering department response time (CE(rt), 0.415 positive coefficient), stock service response time (Stock(rt), 0.734 positive coefficient), priority level (0.21 positive coefficient) and service time (0.06 positive coefficient). The regression process showed heavy reliance on Stock(rt), CE(rt) and priority, in that order. Clustering techniques revealed the main causes of high TAT values. This examination has provided a means for analysing current technical service quality and effectiveness. In doing so, it has demonstrated a process for identifying areas and methods of improvement and a model against which to analyse these methods' effectiveness.

The cognitive bases of the development of past and future episodic cognition in preschoolers.

PubMed

Ünal, Gülten; Hohenberger, Annette

2017-10-01

The aim of this study was to use a minimalist framework to examine the joint development of past and future episodic cognition and their underlying cognitive abilities in 3- to 5-year-old Turkish preschoolers. Participants engaged in two main tasks, a what-where-when (www) task to measure episodic memory and a future prediction task to measure episodic future thinking. Three additional tasks were used for predicting children's performance in the two main tasks: a temporal language task, an executive function task, and a spatial working memory task. Results indicated that past and future episodic tasks were significantly correlated with each other even after controlling for age. Hierarchical multiple regressions showed that, after controlling for age, the www task was predicted by executive functions, possibly supporting binding of episodic information and by linguistic abilities. The future prediction task was predicted by linguistic abilities alone, underlining the importance of language for episodic past and future thinking. Copyright © 2017 Elsevier Inc. All rights reserved.

Multiplicative Multitask Feature Learning

PubMed Central

Wang, Xin; Bi, Jinbo; Yu, Shipeng; Sun, Jiangwen; Song, Minghu

2016-01-01

We investigate a general framework of multiplicative multitask feature learning which decomposes individual task’s model parameters into a multiplication of two components. One of the components is used across all tasks and the other component is task-specific. Several previous methods can be proved to be special cases of our framework. We study the theoretical properties of this framework when different regularization conditions are applied to the two decomposed components. We prove that this framework is mathematically equivalent to the widely used multitask feature learning methods that are based on a joint regularization of all model parameters, but with a more general form of regularizers. Further, an analytical formula is derived for the across-task component as related to the task-specific component for all these regularizers, leading to a better understanding of the shrinkage effects of different regularizers. Study of this framework motivates new multitask learning algorithms. We propose two new learning formulations by varying the parameters in the proposed framework. An efficient blockwise coordinate descent algorithm is developed suitable for solving the entire family of formulations with rigorous convergence analysis. Simulation studies have identified the statistical properties of data that would be in favor of the new formulations. Extensive empirical studies on various classification and regression benchmark data sets have revealed the relative advantages of the two new formulations by comparing with the state of the art, which provides instructive insights into the feature learning problem with multiple tasks. PMID:28428735

NIMEFI: Gene Regulatory Network Inference using Multiple Ensemble Feature Importance Algorithms

PubMed Central

Ruyssinck, Joeri; Huynh-Thu, Vân Anh; Geurts, Pierre; Dhaene, Tom; Demeester, Piet; Saeys, Yvan

2014-01-01

One of the long-standing open challenges in computational systems biology is the topology inference of gene regulatory networks from high-throughput omics data. Recently, two community-wide efforts, DREAM4 and DREAM5, have been established to benchmark network inference techniques using gene expression measurements. In these challenges the overall top performer was the GENIE3 algorithm. This method decomposes the network inference task into separate regression problems for each gene in the network in which the expression values of a particular target gene are predicted using all other genes as possible predictors. Next, using tree-based ensemble methods, an importance measure for each predictor gene is calculated with respect to the target gene and a high feature importance is considered as putative evidence of a regulatory link existing between both genes. The contribution of this work is twofold. First, we generalize the regression decomposition strategy of GENIE3 to other feature importance methods. We compare the performance of support vector regression, the elastic net, random forest regression, symbolic regression and their ensemble variants in this setting to the original GENIE3 algorithm. To create the ensemble variants, we propose a subsampling approach which allows us to cast any feature selection algorithm that produces a feature ranking into an ensemble feature importance algorithm. We demonstrate that the ensemble setting is key to the network inference task, as only ensemble variants achieve top performance. As second contribution, we explore the effect of using rankwise averaged predictions of multiple ensemble algorithms as opposed to only one. We name this approach NIMEFI (Network Inference using Multiple Ensemble Feature Importance algorithms) and show that this approach outperforms all individual methods in general, although on a specific network a single method can perform better. An implementation of NIMEFI has been made publicly available. PMID:24667482

Pressures, Stresses, Anxieties, and On-Job Safety of the School Superintendent.

ERIC Educational Resources Information Center

Chand, Krishan

Identification of the causes of job stress for public school superintendents, with a focus on personal-experiential and task variables, is the purpose of this study. Methodology involved a mail survey of 1,531 randomly selected superintendents. Canonical correlation analysis (CCA) and multiple regression correlation (MCR) analysis were used to…

A CNN Regression Approach for Real-Time 2D/3D Registration.

PubMed

Shun Miao; Wang, Z Jane; Rui Liao

2016-05-01

In this paper, we present a Convolutional Neural Network (CNN) regression approach to address the two major limitations of existing intensity-based 2-D/3-D registration technology: 1) slow computation and 2) small capture range. Different from optimization-based methods, which iteratively optimize the transformation parameters over a scalar-valued metric function representing the quality of the registration, the proposed method exploits the information embedded in the appearances of the digitally reconstructed radiograph and X-ray images, and employs CNN regressors to directly estimate the transformation parameters. An automatic feature extraction step is introduced to calculate 3-D pose-indexed features that are sensitive to the variables to be regressed while robust to other factors. The CNN regressors are then trained for local zones and applied in a hierarchical manner to break down the complex regression task into multiple simpler sub-tasks that can be learned separately. Weight sharing is furthermore employed in the CNN regression model to reduce the memory footprint. The proposed approach has been quantitatively evaluated on 3 potential clinical applications, demonstrating its significant advantage in providing highly accurate real-time 2-D/3-D registration with a significantly enlarged capture range when compared to intensity-based methods.

Lifespan development of pro- and anti-saccades: multiple regression models for point estimates.

PubMed

Klein, Christoph; Foerster, Friedrich; Hartnegg, Klaus; Fischer, Burkhart

2005-12-07

The comparative study of anti- and pro-saccade task performance contributes to our functional understanding of the frontal lobes, their alterations in psychiatric or neurological populations, and their changes during the life span. In the present study, we apply regression analysis to model life span developmental effects on various pro- and anti-saccade task parameters, using data of a non-representative sample of 327 participants aged 9 to 88 years. Development up to the age of about 27 years was dominated by curvilinear rather than linear effects of age. Furthermore, the largest developmental differences were found for intra-subject variability measures and the anti-saccade task parameters. Ageing, by contrast, had the shape of a global linear decline of the investigated saccade functions, lacking the differential effects of age observed during development. While these results do support the assumption that frontal lobe functions can be distinguished from other functions by their strong and protracted development, they do not confirm the assumption of disproportionate deterioration of frontal lobe functions with ageing. We finally show that the regression models applied here to quantify life span developmental effects can also be used for individual predictions in applied research contexts or clinical practice.

Multiplicative Forests for Continuous-Time Processes

PubMed Central

Weiss, Jeremy C.; Natarajan, Sriraam; Page, David

2013-01-01

Learning temporal dependencies between variables over continuous time is an important and challenging task. Continuous-time Bayesian networks effectively model such processes but are limited by the number of conditional intensity matrices, which grows exponentially in the number of parents per variable. We develop a partition-based representation using regression trees and forests whose parameter spaces grow linearly in the number of node splits. Using a multiplicative assumption we show how to update the forest likelihood in closed form, producing efficient model updates. Our results show multiplicative forests can be learned from few temporal trajectories with large gains in performance and scalability. PMID:25284967

Multiplicative Forests for Continuous-Time Processes.

PubMed

Weiss, Jeremy C; Natarajan, Sriraam; Page, David

2012-01-01

Learning temporal dependencies between variables over continuous time is an important and challenging task. Continuous-time Bayesian networks effectively model such processes but are limited by the number of conditional intensity matrices, which grows exponentially in the number of parents per variable. We develop a partition-based representation using regression trees and forests whose parameter spaces grow linearly in the number of node splits. Using a multiplicative assumption we show how to update the forest likelihood in closed form, producing efficient model updates. Our results show multiplicative forests can be learned from few temporal trajectories with large gains in performance and scalability.

Glutamate and GABA contributions to medial prefrontal cortical activity to emotion: implications for mood disorders.

PubMed

Stan, Ana D; Schirda, Claudiu V; Bertocci, Michele A; Bebko, Genna M; Kronhaus, Dina M; Aslam, Haris A; LaBarbara, Eduard J; Tanase, Costin; Lockovich, Jeanette C; Pollock, Myrna H; Stiffler, Richelle S; Phillips, Mary L

2014-09-30

The dorsomedial prefrontal cortex (MdPFC) and anterior cingulate cortices (ACC) play a critical role in implicit emotion regulation; however the understanding of the specific neurotransmitters that mediate such role is lacking. In this study, we examined relationships between MdPFC concentrations of two neurotransmitters, glutamate and γ-amino butyric acid (GABA), and BOLD activity in ACC during performance of an implicit facial emotion-processing task. Twenty healthy volunteers, aged 20-35 years, were scanned while performing an implicit facial emotion-processing task, whereby presented facial expressions changed from neutral to one of the four emotions: happy, anger, fear, or sad. Glutamate concentrations were measured before and after the emotion-processing task in right MdPFC using magnetic resonance spectroscopy (MRS). GABA concentrations were measured in bilateral MdPFC after the emotion-processing task. Multiple regression models were run to determine the relative contribution of glutamate and GABA concentration, age, and gender to BOLD signal in ACC to each of the four emotions. Multiple regression analyses revealed a significant negative correlation between MdPFC GABA concentration and BOLD signal in subgenual ACC (p<0.05, corrected) to sad versus shape contrast. For the anger versus shape contrast, there was a significant negative correlation between age and BOLD signal in pregenual ACC (p<0.05, corrected) and a positive correlation between MdPFC glutamate concentration (pre-task) and BOLD signal in pregenual ACC (p<0.05, corrected). Our findings are the first to provide insight into relationships between MdPFC neurotransmitter concentrations and ACC BOLD signal, and could further understanding of molecular mechanisms underlying emotion processing in healthy and mood-disordered individuals. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Individual strategy ratings improve the control for task difficulty effects in arithmetic problem solving paradigms.

PubMed

Tschentscher, Nadja; Hauk, Olaf

2015-01-01

Mental arithmetic is a powerful paradigm to study problem solving using neuroimaging methods. However, the evaluation of task complexity varies significantly across neuroimaging studies. Most studies have parameterized task complexity by objective features such as the number size. Only a few studies used subjective rating procedures. In fMRI, we provided evidence that strategy self-reports control better for task complexity across arithmetic conditions than objective features (Tschentscher and Hauk, 2014). Here, we analyzed the relative predictive value of self-reported strategies and objective features for performance in addition and multiplication tasks, by using a paradigm designed for neuroimaging research. We found a superiority of strategy ratings as predictor of performance above objective features. In a Principal Component Analysis on reaction times, the first component explained over 90 percent of variance and factor loadings reflected percentages of self-reported strategies well. In multiple regression analyses on reaction times, self-reported strategies performed equally well or better than objective features, depending on the operation type. A Receiver Operating Characteristic (ROC) analysis confirmed this result. Reaction times classified task complexity better when defined by individual ratings. This suggests that participants' strategy ratings are reliable predictors of arithmetic complexity and should be taken into account in neuroimaging research.

Individual strategy ratings improve the control for task difficulty effects in arithmetic problem solving paradigms

PubMed Central

Tschentscher, Nadja; Hauk, Olaf

2015-01-01

Mental arithmetic is a powerful paradigm to study problem solving using neuroimaging methods. However, the evaluation of task complexity varies significantly across neuroimaging studies. Most studies have parameterized task complexity by objective features such as the number size. Only a few studies used subjective rating procedures. In fMRI, we provided evidence that strategy self-reports control better for task complexity across arithmetic conditions than objective features (Tschentscher and Hauk, 2014). Here, we analyzed the relative predictive value of self-reported strategies and objective features for performance in addition and multiplication tasks, by using a paradigm designed for neuroimaging research. We found a superiority of strategy ratings as predictor of performance above objective features. In a Principal Component Analysis on reaction times, the first component explained over 90 percent of variance and factor loadings reflected percentages of self-reported strategies well. In multiple regression analyses on reaction times, self-reported strategies performed equally well or better than objective features, depending on the operation type. A Receiver Operating Characteristic (ROC) analysis confirmed this result. Reaction times classified task complexity better when defined by individual ratings. This suggests that participants’ strategy ratings are reliable predictors of arithmetic complexity and should be taken into account in neuroimaging research. PMID:26321997

The effects of texting on driving performance in a driving simulator: the influence of driver age.

PubMed

Rumschlag, Gordon; Palumbo, Theresa; Martin, Amber; Head, Doreen; George, Rajiv; Commissaris, Randall L

2015-01-01

Distracted driving is a significant contributor to motor vehicle accidents and fatalities, and texting is a particularly significant form of driver distraction that continues to be on the rise. The present study examined the influence of driver age (18-59 years old) and other factors on the disruptive effects of texting on simulated driving behavior. While 'driving' the simulator, subjects were engaged in a series of brief text conversations with a member of the research team. The primary dependent variable was the occurrence of Lane Excursions (defined as any time the center of the vehicle moved outside the directed driving lane, e.g., into the lane for oncoming traffic or onto the shoulder of the road), measured as (1) the percent of subjects that exhibited Lane Excursions, (2) the number of Lane Excursions occurring and (3) the percent of the texting time in Lane Excursions. Multiple Regression analyses were used to assess the influence of several factors on driving performance while texting, including text task duration, texting skill level (subject-reported), texting history (#texts/week), driver gender and driver age. Lane Excursions were not observed in the absence of texting, but 66% of subjects overall exhibited Lane Excursions while texting. Multiple Regression analysis for all subjects (N=50) revealed that text task duration was significantly correlated with the number of Lane Excursions, and texting skill level and driver age were significantly correlated with the percent of subjects exhibiting Lane Excursions. Driver gender was not significantly correlated with Lane Excursions during texting. Multiple Regression analysis of only highly skilled texters (N=27) revealed that driver age was significantly correlated with the number of Lane Excursions, the percent of subjects exhibiting Lane Excursions and the percent of texting time in Lane Excursions. In contrast, Multiple Regression analysis of those drivers who self-identified as not highly skilled texters (N=23) revealed that text task duration was significantly correlated with the number of Lane Excursions. The present studies confirm past reports that texting impairs driving simulator performance. Moreover, the present study demonstrates that for highly skilled texters, the effects of texting on driving are actually worse for older drivers. Given the increasing frequency of texting while driving within virtually all age groups, these data suggest that 'no texting while driving' education and public service messages need to be continued, and they should be expanded to target older drivers as well. Copyright © 2014 Elsevier Ltd. All rights reserved.

Tibiofemoral contact forces during walking, running and sidestepping.

PubMed

Saxby, David J; Modenese, Luca; Bryant, Adam L; Gerus, Pauline; Killen, Bryce; Fortin, Karine; Wrigley, Tim V; Bennell, Kim L; Cicuttini, Flavia M; Lloyd, David G

2016-09-01

We explored the tibiofemoral contact forces and the relative contributions of muscles and external loads to those contact forces during various gait tasks. Second, we assessed the relationships between external gait measures and contact forces. A calibrated electromyography-driven neuromusculoskeletal model estimated the tibiofemoral contact forces during walking (1.44±0.22ms(-1)), running (4.38±0.42ms(-1)) and sidestepping (3.58±0.50ms(-1)) in healthy adults (n=60, 27.3±5.4years, 1.75±0.11m, and 69.8±14.0kg). Contact forces increased from walking (∼1-2.8 BW) to running (∼3-8 BW), sidestepping had largest maximum total (8.47±1.57 BW) and lateral contact forces (4.3±1.05 BW), while running had largest maximum medial contact forces (5.1±0.95 BW). Relative muscle contributions increased across gait tasks (up to 80-90% of medial contact forces), and peaked during running for lateral contact forces (∼90%). Knee adduction moment (KAM) had weak relationships with tibiofemoral contact forces (all R(2)<0.36) and the relationships were gait task-specific. Step-wise regression of multiple external gait measures strengthened relationships (0.20

Time and motion studies of National Health Service cataract theatre lists to determine strategies to improve efficiency.

PubMed

Roberts, Harry W; Myerscough, James; Borsci, Simone; Ni, Melody; O'Brart, David P S

2017-11-24

To provide a quantitative assessment of cataract theatre lists focusing on productivity and staffing levels/tasks using time and motion studies. National Health Service (NHS) cataract theatre lists were prospectively observed in five different institutions (four NHS hospitals and one private hospital). Individual tasks and their timings of every member of staff were recorded. Multiple linear regression analyses were performed to investigate possible associations between individual timings and tasks. 140 operations were studied over 18 theatre sessions. The median number of scheduled cataract operations was 7 (range: 5-14). The average duration of an operation was 10.3 min±(SD 4.11 min). The average time to complete one case including patient turnaround was 19.97 min (SD 8.77 min). The proportion of the surgeons' time occupied on total duties or operating ranged from 65.2% to 76.1% and from 42.4% to 56.7%, respectively. The correlations of the surgical time to patient time in theatre was R 2 =0.95. A multiple linear regression model found a significant association (F(3,111)=32.86, P<0.001) with R 2 =0.47 between the duration of one operation and the number of allied healthcare professionals (AHPs), the number of AHP key tasks and the time taken to perform these key tasks by the AHPs. Significant variability in the number of cases performed and the efficiency of patient flow were found between different institutions. Time and motion studies identified requirements for high-volume models and factors relating to performance. Supporting the surgeon with sufficient AHPs and tasks performed by AHPs could improve surgical efficiency up to approximately double productivity over conventional theatre models. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Predictive Factors of Household Task Participation in Brazilian Children and Adolescents.

PubMed

Drummond, Adriana de França; Gomes, Ana Maria Rabelo; Coster, Wendy J; Mancini, Marisa Cotta

2015-04-01

Home environment is an important setting for child participation. This study investigated the participation of Brazilian children and adolescents in household self-care (SC) and family-care (FC) tasks. Interviews were conducted with 109 caregivers of children and adolescents ages 6 to 14 years residing in Belo Horizonte (Brazil). Multiple regression models revealed that a greater number of FC tasks were performed by children and adolescents (R2 = .23) from families who did not have a housekeeper and those in which the mothers did not work outside of the home; children and adolescents from this subgroup also received less assistance from the caregivers (R2 = .21) and showed greater independence in task performance (R2 = .20). On average, Brazilian children and adolescents participate in about half of the SC and 25% the FC household tasks. Factors related to family structure and child's age were associated with task performance, caregiver assistance, and child and adolescent independence in household tasks.

Impairment in judgement of the moral emotion guilt following orbitofrontal cortex damage.

PubMed

Funayama, Michitaka; Koreki, Akihiro; Muramatsu, Taro; Mimura, Masaru; Kato, Motoichiro; Abe, Takayuki

2018-04-19

Although neuroimaging studies have provided evidence for an association between moral emotions and the orbitofrontal cortex, studies on patients with focal lesions using experimental probes of moral emotions are scarce. Here, we addressed this topic by presenting a moral emotion judgement task to patients with focal brain damage. Four judgement tasks in a simple pairwise choice paradigm were given to 72 patients with cerebrovascular disease. These tasks consisted of a perceptual line judgement task as a control task; the objects' preference task as a basic preference judgement task; and two types of moral emotion judgement task, an anger task and a guilt task. A multiple linear regression analysis was performed on each set of task performance scores to take into account potential confounders. Performance on the guilt emotion judgement task negatively correlated with the orbitofrontal cortex damage, but not with the other variables. Results for the other judgement tasks did not reach statistical significance. The close association between orbitofrontal cortex damage and a decrease in guilt emotion judgement consistency might suggest that the orbitofrontal cortex plays a key role in the sense of guilt, a hallmark of morality. © 2018 The British Psychological Society.

Minimization of annotation work: diagnosis of mammographic masses via active learning

NASA Astrophysics Data System (ADS)

Zhao, Yu; Zhang, Jingyang; Xie, Hongzhi; Zhang, Shuyang; Gu, Lixu

2018-06-01

The prerequisite for establishing an effective prediction system for mammographic diagnosis is the annotation of each mammographic image. The manual annotation work is time-consuming and laborious, which becomes a great hindrance for researchers. In this article, we propose a novel active learning algorithm that can adequately address this problem, leading to the minimization of the labeling costs on the premise of guaranteed performance. Our proposed method is different from the existing active learning methods designed for the general problem as it is specifically designed for mammographic images. Through its modified discriminant functions and improved sample query criteria, the proposed method can fully utilize the pairing of mammographic images and select the most valuable images from both the mediolateral and craniocaudal views. Moreover, in order to extend active learning to the ordinal regression problem, which has no precedent in existing studies, but is essential for mammographic diagnosis (mammographic diagnosis is not only a classification task, but also an ordinal regression task for predicting an ordinal variable, viz. the malignancy risk of lesions), multiple sample query criteria need to be taken into consideration simultaneously. We formulate it as a criteria integration problem and further present an algorithm based on self-adaptive weighted rank aggregation to achieve a good solution. The efficacy of the proposed method was demonstrated on thousands of mammographic images from the digital database for screening mammography. The labeling costs of obtaining optimal performance in the classification and ordinal regression task respectively fell to 33.8 and 19.8 percent of their original costs. The proposed method also generated 1228 wins, 369 ties and 47 losses for the classification task, and 1933 wins, 258 ties and 185 losses for the ordinal regression task compared to the other state-of-the-art active learning algorithms. By taking the particularities of mammographic images, the proposed AL method can indeed reduce the manual annotation work to a great extent without sacrificing the performance of the prediction system for mammographic diagnosis.

Minimization of annotation work: diagnosis of mammographic masses via active learning.

PubMed

Zhao, Yu; Zhang, Jingyang; Xie, Hongzhi; Zhang, Shuyang; Gu, Lixu

2018-05-22

The prerequisite for establishing an effective prediction system for mammographic diagnosis is the annotation of each mammographic image. The manual annotation work is time-consuming and laborious, which becomes a great hindrance for researchers. In this article, we propose a novel active learning algorithm that can adequately address this problem, leading to the minimization of the labeling costs on the premise of guaranteed performance. Our proposed method is different from the existing active learning methods designed for the general problem as it is specifically designed for mammographic images. Through its modified discriminant functions and improved sample query criteria, the proposed method can fully utilize the pairing of mammographic images and select the most valuable images from both the mediolateral and craniocaudal views. Moreover, in order to extend active learning to the ordinal regression problem, which has no precedent in existing studies, but is essential for mammographic diagnosis (mammographic diagnosis is not only a classification task, but also an ordinal regression task for predicting an ordinal variable, viz. the malignancy risk of lesions), multiple sample query criteria need to be taken into consideration simultaneously. We formulate it as a criteria integration problem and further present an algorithm based on self-adaptive weighted rank aggregation to achieve a good solution. The efficacy of the proposed method was demonstrated on thousands of mammographic images from the digital database for screening mammography. The labeling costs of obtaining optimal performance in the classification and ordinal regression task respectively fell to 33.8 and 19.8 percent of their original costs. The proposed method also generated 1228 wins, 369 ties and 47 losses for the classification task, and 1933 wins, 258 ties and 185 losses for the ordinal regression task compared to the other state-of-the-art active learning algorithms. By taking the particularities of mammographic images, the proposed AL method can indeed reduce the manual annotation work to a great extent without sacrificing the performance of the prediction system for mammographic diagnosis.

Use of probabilistic weights to enhance linear regression myoelectric control

NASA Astrophysics Data System (ADS)

Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.

2015-12-01

Objective. Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Approach. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts’ law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Main results. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p < 0.05) by preventing extraneous movement at additional DOFs. Similar results were seen in experiments with two transradial amputees. Though goodness-of-fit evaluations suggested that the EMG feature distributions showed some deviations from the Gaussian, equal-covariance assumptions used in this experiment, the assumptions were sufficiently met to provide improved performance compared to linear regression control. Significance. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

The Influence of Math Anxiety, Math Performance, Worry, and Test Anxiety on the Iowa Gambling Task and Balloon Analogue Risk Task.

PubMed

Buelow, Melissa T; Barnhart, Wesley R

2017-01-01

Multiple studies have shown that performance on behavioral decision-making tasks, such as the Iowa Gambling Task (IGT) and Balloon Analogue Risk Task (BART), is influenced by external factors, such as mood. However, the research regarding the influence of worry is mixed, and no research has examined the effect of math or test anxiety on these tasks. The present study investigated the effects of anxiety (including math anxiety) and math performance on the IGT and BART in a sample of 137 undergraduate students. Math performance and worry were not correlated with performance on the IGT, and no variables were correlated with BART performance. Linear regressions indicated math anxiety, physiological anxiety, social concerns/stress, and test anxiety significantly predicted disadvantageous selections on the IGT during the transition from decision making under ambiguity to decision making under risk. Implications for clinical evaluation of decision making are discussed. © The Author(s) 2015.

Executive functioning as a predictor of children's mathematics ability: inhibition, switching, and working memory.

PubMed

Bull, R; Scerif, G

2001-01-01

Children's mathematical skills were considered in relation to executive functions. Using multiple measures--including the Wisconsin Card Sorting Task (WCST), dual-task performance, Stroop task, and counting span-it was found that mathematical ability was significantly correlated with all measures of executive functioning, with the exception of dual-task performance. Furthermore, regression analyses revealed that each executive function measure predicted unique variance in mathematics ability. These results are discussed in terms of a central executive with diverse functions (Shallice & Burgess, 1996) and with recent evidence from Miyake, et al. (2000) showing the unity and diversity among executive functions. It is proposed that the particular difficulties for children of lower mathematical ability are lack of inhibition and poor working memory, which result in problems with switching and evaluation of new strategies for dealing with a particular task. The practical and theoretical implications of these results are discussed, along with suggestions for task changes and longitudinal studies that would clarify theoretical and developmental issues related to executive functioning.

Perception of difficulty and glucose control: Effects on academic performance in youth with type I diabetes.

PubMed

Potts, Tiffany M; Nguyen, Jacqueline L; Ghai, Kanika; Li, Kathy; Perlmuter, Lawrence

2015-04-15

To investigate whether perceptions of task difficulty on neuropsychological tests predicted academic achievement after controlling for glucose levels and depression. Participants were type 1 diabetic adolescents, with a mean age = 12.5 years (23 females and 16 males), seen at a northwest suburban Chicago hospital. The sample population was free of co-morbid clinical health conditions. Subjects completed a three-part neuropsychological battery including the Digit Symbol Task, Trail Making Test, and Controlled Oral Word Association test. Following each task, individuals rated task difficulty and then completed a depression inventory. Performance on these three tests is reflective of neuropsychological status in relation to glucose control. Blood glucose levels were measured immediately prior to and after completing the neuropsychological battery using a glucose meter. HbA1c levels were obtained from medical records. Academic performance was based on self-reported grades in Math, Science, and English. Data was analyzed using multiple regression models to evaluate the associations between academic performance, perception of task difficulty, and glucose control. Perceptions of difficulty on a neuropsychological battery significantly predicted academic performance after accounting for glucose control and depression. Perceptions of difficulty on the neuropsychological tests were inversely correlated with academic performance (r = -0.48), while acute (blood glucose) and long-term glucose levels increased along with perceptions of task difficulty (r = 0.47). Additionally, higher depression scores were associated with poorer academic performance (r = -0.43). With the first regression analysis, perception of difficulty on the neuropsychological tasks contributed to 8% of the variance in academic performance after controlling for peripheral blood glucose and depression. In the second regression analysis, perception of difficulty accounted for 11% of the variance after accounting for academic performance and depression. The final regression analysis indicated that perception of difficulty increased with peripheral blood glucose, contributing to 22% of the variance. Most importantly, after controlling for perceptions of task difficulty, academic performance no longer predicted glucose levels. Finally, subjects who found the cognitive battery difficult were likely to have poor academic grades. Perceptions of difficulty on neurological tests exhibited a significant association with academic achievement, indicating that deficits in this skill may lead to academic disadvantage in diabetic patients.

Who's Who? Memory updating and character reference in children's narratives.

PubMed

Whitely, Cristy; Colozzo, Paola

2013-10-01

The capacity to update and monitor the contents of working memory is an executive function presumed to play a critical role in language processing. The current study used an individual differences approach to consider the relationship between memory updating and accurate reference to story characters in the narratives of typically developing children. English-speaking children from kindergarten to grade 2 ( N = 63; M age = 7.0 years) completed updating tasks, short-term memory tasks, and narrative productions. The authors used multiple regression to test whether updating accounted for independent variability in referential adequacy. The capacity to update working memory was related to adequate character reference beyond the effects of age and of short-term memory capacity, with the strongest relationship emerging for maintaining reference over multiple utterances. This individual differences study is the first to show a link between updating and performance in a discourse production task for young school-age children. The findings contribute to the growing body of research investigating the role of working memory in shaping language production. This study invites extension to children of different ages and language abilities as well as to other language production tasks.

Subjective cognitive complaints and neuropsychological performance in former smokers with and without chronic obstructive pulmonary disease.

PubMed

Brunette, Amanda M; Holm, Kristen E; Wamboldt, Frederick S; Kozora, Elizabeth; Moser, David J; Make, Barry J; Crapo, James D; Meschede, Kimberly; Weinberger, Howard D; Moreau, Kerrie L; Bowler, Russell P; Hoth, Karin F

2018-05-01

This study examined the association of perceived cognitive difficulties with objective cognitive performance in former smokers. We hypothesized that greater perceived cognitive difficulties would be associated with poorer performance on objective executive and memory tasks. Participants were 95 former smokers recruited from the COPDGene study. They completed questionnaires (including the Cognitive Difficulties Scale [CDS] and the Hospital Anxiety and Depression Scale [HADS]), neuropsychological assessment, and pulmonary function testing. Pearson correlations and t-tests were conducted to examine the bivariate association of the CDS (total score and subscales for attention/concentration, praxis, delayed recall, orientation for persons, temporal orientation, and prospective memory) with each domain of objective cognitive functioning (memory recall, executive functioning/processing speed, visuospatial processing, and language). Simultaneous multiple linear regression was used to further examine all statistically significant bivariate associations. The following covariates were included in all regression models: age, sex, pack-years, premorbid functioning (WRAT-IV Reading), HADS total score, and chronic obstructive pulmonary disease (COPD) status (yes/no based on GOLD criteria). In regression models, greater perceived cognitive difficulties overall (using CDS total score) were associated with poorer performance on executive functioning/processing speed tasks (b = -0.07, SE = 0.03, p = .037). Greater perceived cognitive difficulties on the CDS praxis subscale were associated with poorer performance on executive functioning/processing speed tasks (b = -3.65, SE = 1.25, p = .005), memory recall tasks (b = -4.60, SE = 1.75, p = .010), and language tasks (b = -3.89, SE = 1.39, p = .006). Clinicians should be aware that cognitive complaints may be indicative of problems with the executive functioning/processing speed and memory of former smokers with and without COPD.

Computerized assessment of sustained attention: interactive effects of task demand, noise, and anxiety.

PubMed

Ballard, J C

1996-12-01

In a sample of 163 college undergraduates, the effects of task demand, noise, and anxiety on Continuous Performance Test (CPT) errors were evaluated with multiple regression and multivariate analysis of variance. Results indicated significantly more omission errors on the difficult task. Complex interaction effects of noise and self-reported anxiety yielded more omissions in quiet intermittent white noise, particularly for high-anxious subjects performing the difficult task. Anxiety levels tended to increase from pretest to posttest, particularly for low-anxious subjects in the quiet, difficult-task condition, while a decrease was seen for high-anxious subjects in the loud, easy-task condition. Commission errors were unrelated to any predictor variables, suggesting that "attention" cannot be considered a unitary phenomenon. The variety of direct and interactive effects on vigilance performance underscore the need for clinicians to use a variety of measures to assess attentional skills, to avoid diagnosis of attention deficits on the basis of a single computerized task performance, and to rule out anxiety and other contributors to poor vigilance task performance.

Self-regulated learning processes of medical students during an academic learning task.

PubMed

Gandomkar, Roghayeh; Mirzazadeh, Azim; Jalili, Mohammad; Yazdani, Kamran; Fata, Ladan; Sandars, John

2016-10-01

This study was designed to identify the self-regulated learning (SRL) processes of medical students during a biomedical science learning task and to examine the associations of the SRL processes with previous performance in biomedical science examinations and subsequent performance on a learning task. A sample of 76 Year 1 medical students were recruited based on their performance in biomedical science examinations and stratified into previous high and low performers. Participants were asked to complete a biomedical science learning task. Participants' SRL processes were assessed before (self-efficacy, goal setting and strategic planning), during (metacognitive monitoring) and after (causal attributions and adaptive inferences) their completion of the task using an SRL microanalytic interview. Descriptive statistics were used to analyse the means and frequencies of SRL processes. Univariate and multiple logistic regression analyses were conducted to examine the associations of SRL processes with previous examination performance and the learning task performance. Most participants (from 88.2% to 43.4%) reported task-specific processes for SRL measures. Students who exhibited higher self-efficacy (odds ratio [OR] 1.44, 95% confidence interval [CI] 1.09-1.90) and reported task-specific processes for metacognitive monitoring (OR 6.61, 95% CI 1.68-25.93) and causal attributions (OR 6.75, 95% CI 2.05-22.25) measures were more likely to be high previous performers. Multiple analysis revealed that similar SRL measures were associated with previous performance. The use of task-specific processes for causal attributions (OR 23.00, 95% CI 4.57-115.76) and adaptive inferences (OR 27.00, 95% CI 3.39-214.95) measures were associated with being a high learning task performer. In multiple analysis, only the causal attributions measure was associated with high learning task performance. Self-efficacy, metacognitive monitoring and causal attributions measures were associated positively with previous performance. Causal attributions and adaptive inferences measures were associated positively with learning task performance. These findings may inform remediation interventions in the early years of medical school training. © 2016 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

High-level language ability in healthy individuals and its relationship with verbal working memory.

PubMed

Antonsson, Malin; Longoni, Francesca; Einald, Christina; Hallberg, Lina; Kurt, Gabriella; Larsson, Kajsa; Nilsson, Tina; Hartelius, Lena

2016-01-01

The aims of the study were to investigate healthy subjects' performance on a clinical test of high-level language (HLL) and how it is related to demographic characteristics and verbal working memory (VWM). One hundred healthy subjects (20-79 years old) were assessed with the Swedish BeSS test (Laakso, Brunnegård, Hartelius, & Ahlsén, 2000) and two digit span tasks. Relationships between the demographic variables, VWM and BeSS were investigated both with bivariate correlations and multiple regression analysis. The results present the norms for BeSS. The correlations and multiple regression analysis show that demographic variables had limited influence on test performance. Measures of VWM were moderately related to total BeSS score and weakly to moderately correlated with five of the seven subtests. To conclude, education has an influence on the test as a whole but measures of VWM stood out as the most robust predictor of HLL.

The convergence of neomillennial learning styles and a multi-user virtual environment

NASA Astrophysics Data System (ADS)

Dieterle, Edward Robert, II

Learning styles influenced and cultivated by immersive technologies have spawned a new area of research, "neomillennial" learning styles (NLS). The present study utilizes a quantitative approach, including principal components analysis and multiple regression/correlation analysis, to investigate NLS. Evidence supporting the arguments laid out in this study derives from a sample of 574 middle grades students from urban, suburban, and rural school settings in North America that participated in the River City Project (RCP) in academic year 2006-07. Central to RCP is an immersive simulation for teaching inquiry-based science and 21st century skills, where success is measured across five dimensions: (a) collaboration, (b) science content understanding, (c) self-efficacy in science, (d) self-efficacy in scientific inquiry, and (e) thoughtfulness of inquiry. Besides taking part in RCP, participating students completed an instrument that generates a profile of their NLS. The resulting profile includes measures of students' fluency in multiple media; the extent to which they prefer learning based on collectively seeking, sieving, and synthesizing experiences; and their tendency toward expression through webs of representations. This study revealed that, on average, a student who prefers: (1) engaging tasks that require creative strategies and seeing and doing things in new ways, while avoiding tasks that involve details, is well suited for learning disease transmission and the scientific method in RCP; (2) distributing attention across multiple tasks that have been prioritized will further his or her belief in their ability to do science by participating via RCP whereas the same conditions may undercut a student who avoids distributing attention across multiple tasks that have been prioritized; (3) to read books, magazines, and newspapers by choice and who score high on measures of their general connectedness with the media is well suited for increasing his or her belief in their ability to complete activities common to practicing scientists in RCP; and (4) (a) engaging tasks that require creative strategies, (b) seeing and doing things in new ways, and (c) distributing attention across multiple tasks that have been prioritized is well suited for increasing his or her use of inquiry and reflection when performing science-related activities in RCP.

Cancer Patients Enrolled in a Smoking Cessation Clinical Trial: Characteristics and Correlates of Smoking Rate and Nicotine Dependence.

PubMed

Miele, Andrew; Thompson, Morgan; Jao, Nancy C; Kalhan, Ravi; Leone, Frank; Hogarth, Lee; Hitsman, Brian; Schnoll, Robert

2018-01-01

A substantial proportion of cancer patients continue to smoke after their diagnosis but few studies have evaluated correlates of nicotine dependence and smoking rate in this population, which could help guide smoking cessation interventions. This study evaluated correlates of smoking rate and nicotine dependence among 207 cancer patients. A cross-sectional analysis using multiple linear regression evaluated disease, demographic, affective, and tobacco-seeking correlates of smoking rate and nicotine dependence. Smoking rate was assessed using a timeline follow-back method. The Fagerström Test for Nicotine Dependence measured levels of nicotine dependence. A multiple linear regression predicting nicotine dependence showed an association with smoking to alleviate a sense of addiction from the Reasons for Smoking scale and tobacco-seeking behavior from the concurrent choice task ( p < .05), but not with affect measured by the HADS and PANAS ( p > .05). Multiple linear regression predicting prequit showed an association with smoking to alleviate addiction ( p < .05). ANOVA showed that Caucasian participants reported greater rates of smoking compared to other races. The results suggest that behavioral smoking cessation interventions that focus on helping patients to manage tobacco-seeking behavior, rather than mood management interventions, could help cancer patients quit smoking.

Deep ensemble learning of sparse regression models for brain disease diagnosis.

PubMed

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2017-04-01

Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effectiveness in handling high-dimensional data but with a small number of training samples, especially in medical problems. In the meantime, deep learning methods have been making great successes by outperforming the state-of-the-art performances in various applications. In this paper, we propose a novel framework that combines the two conceptually different methods of sparse regression and deep learning for Alzheimer's disease/mild cognitive impairment diagnosis and prognosis. Specifically, we first train multiple sparse regression models, each of which is trained with different values of a regularization control parameter. Thus, our multiple sparse regression models potentially select different feature subsets from the original feature set; thereby they have different powers to predict the response values, i.e., clinical label and clinical scores in our work. By regarding the response values from our sparse regression models as target-level representations, we then build a deep convolutional neural network for clinical decision making, which thus we call 'Deep Ensemble Sparse Regression Network.' To our best knowledge, this is the first work that combines sparse regression models with deep neural network. In our experiments with the ADNI cohort, we validated the effectiveness of the proposed method by achieving the highest diagnostic accuracies in three classification tasks. We also rigorously analyzed our results and compared with the previous studies on the ADNI cohort in the literature. Copyright © 2017 Elsevier B.V. All rights reserved.

Deep ensemble learning of sparse regression models for brain disease diagnosis

PubMed Central

Suk, Heung-Il; Lee, Seong-Whan; Shen, Dinggang

2018-01-01

Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effectiveness in handling high-dimensional data but with a small number of training samples, especially in medical problems. In the meantime, deep learning methods have been making great successes by outperforming the state-of-the-art performances in various applications. In this paper, we propose a novel framework that combines the two conceptually different methods of sparse regression and deep learning for Alzheimer’s disease/mild cognitive impairment diagnosis and prognosis. Specifically, we first train multiple sparse regression models, each of which is trained with different values of a regularization control parameter. Thus, our multiple sparse regression models potentially select different feature subsets from the original feature set; thereby they have different powers to predict the response values, i.e., clinical label and clinical scores in our work. By regarding the response values from our sparse regression models as target-level representations, we then build a deep convolutional neural network for clinical decision making, which thus we call ‘ Deep Ensemble Sparse Regression Network.’ To our best knowledge, this is the first work that combines sparse regression models with deep neural network. In our experiments with the ADNI cohort, we validated the effectiveness of the proposed method by achieving the highest diagnostic accuracies in three classification tasks. We also rigorously analyzed our results and compared with the previous studies on the ADNI cohort in the literature. PMID:28167394

Reduced dual-task gait speed is associated with visual Go/No-Go brain network activation in children and adolescents with concussion.

PubMed

Howell, David R; Meehan, William P; Barber Foss, Kim D; Reches, Amit; Weiss, Michal; Myer, Gregory D

2018-05-31

To investigate the association between dual-task gait performance and brain network activation (BNA) using an electroencephalography (EEG)-based Go/No-Go paradigm among children and adolescents with concussion. Participants with a concussion completed a visual Go/No-Go task with collection of electroencephalogram brain activity. Data were treated with BNA analysis, which involves an algorithmic approach to EEG-ERP activation quantification. Participants also completed a dual-task gait assessment. The relationship between dual-task gait speed and BNA was assessed using multiple linear regression models. Participants (n = 20, 13.9 ± 2.3 years of age, 50% female) were tested at a mean of 7.0 ± 2.5 days post-concussion and were symptomatic at the time of testing (post-concussion symptom scale = 40.4 ± 21.9). Slower dual-task average gait speed (mean = 82.2 ± 21.0 cm/s) was significantly associated with lower relative time BNA scores (mean = 39.6 ± 25.8) during the No-Go task (β = 0.599, 95% CI = 0.214, 0.985, p = 0.005, R 2  = 0.405), while controlling for the effect of age and gender. Among children and adolescents with a concussion, slower dual-task gait speed was independently associated with lower BNA relative time scores during a visual Go/No-Go task. The relationship between abnormal gait behaviour and brain activation deficits may be reflective of disruption to multiple functional abilities after concussion.

Perinatal Medical Variables Predict Executive Function within a Sample of Preschoolers Born Very Low Birth Weight

PubMed Central

Duvall, Susanne W.; Erickson, Sarah J.; MacLean, Peggy; Lowe, Jean R.

2014-01-01

The goal was to identify perinatal predictors of early executive dysfunction in preschoolers born very low birth weight. Fifty-seven preschoolers completed three executive function tasks (Dimensional Change Card Sort-Separated (inhibition, working memory and cognitive flexibility), Bear Dragon (inhibition and working memory) and Gift Delay Open (inhibition)). Relationships between executive function and perinatal medical severity factors (gestational age, days on ventilation, size for gestational age, maternal steroids and number of surgeries), and chronological age were investigated by multiple linear regression and logistic regression. Different perinatal medical severity factors were predictive of executive function tasks, with gestational age predicting Bear Dragon and Gift Open; and number of surgeries and maternal steroids predicting performance on Dimensional Change Card Sort-Separated. By understanding the relationship between perinatal medical severity factors and preschool executive outcomes, we may be able to identify children at highest risk for future executive dysfunction, thereby focusing targeted early intervention services. PMID:25117418

Using Explanatory Item Response Models to Evaluate Complex Scientific Tasks Designed for the Next Generation Science Standards

NASA Astrophysics Data System (ADS)

Chiu, Tina

This dissertation includes three studies that analyze a new set of assessment tasks developed by the Learning Progressions in Middle School Science (LPS) Project. These assessment tasks were designed to measure science content knowledge on the structure of matter domain and scientific argumentation, while following the goals from the Next Generation Science Standards (NGSS). The three studies focus on the evidence available for the success of this design and its implementation, generally labelled as "validity" evidence. I use explanatory item response models (EIRMs) as the overarching framework to investigate these assessment tasks. These models can be useful when gathering validity evidence for assessments as they can help explain student learning and group differences. In the first study, I explore the dimensionality of the LPS assessment by comparing the fit of unidimensional, between-item multidimensional, and Rasch testlet models to see which is most appropriate for this data. By applying multidimensional item response models, multiple relationships can be investigated, and in turn, allow for a more substantive look into the assessment tasks. The second study focuses on person predictors through latent regression and differential item functioning (DIF) models. Latent regression models show the influence of certain person characteristics on item responses, while DIF models test whether one group is differentially affected by specific assessment items, after conditioning on latent ability. Finally, the last study applies the linear logistic test model (LLTM) to investigate whether item features can help explain differences in item difficulties.

A Multiple Linear Regression Model for Predicting Zone A Retention by Military Occupational Specialty.

DTIC Science & Technology

1986-09-01

OF REPORT Approved for public release; distribution 2b DECLASSIFICATION /DOWNGRADING SCHEDULE is unlimited. 4 PERFORMING ORGANIZATION REPORT NUMBER(S...S MONITORING ORGANIZATION REPORT NUMBER(S) 6a NAME OF PERFORMING ORGANIZATION 6b OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION (If applicable...ORGAIZATION (If applicable) 8c ADDRESS(Ciry, State, ard ZIPCode) 10 SOURCE OF FUNDING NUMBERS PROGRAM PROJECT TASK WORK UNIT ELEMENT NO INO NO ACCESSION

Quantitative work demands, emotional demands, and cognitive stress symptoms in surgery nurses.

PubMed

Elfering, Achim; Grebner, Simone; Leitner, Monika; Hirschmüller, Anja; Kubosch, Eva Johanna; Baur, Heiner

2017-06-01

In surgery, cognitive stress symptoms, including problems in concentrating, deciding, memorising, and reflecting are risks to patient safety. Recent evidence points to social stressors as antecedents of cognitive stress symptoms in surgery personnel. The current study tests whether cognitive stress symptoms are positively associated with emotional abuse, emotional- and task-related demands and resources in surgery work. Forty-eight surgery nurses from two hospitals filled out the Copenhagen Psychosocial Questionnaire in its German version. Task-related and emotional demands were positively related to cognitive stress symptoms. In a stepwise, multiple, linear regression of cognitive stress symptoms on task-related and emotional demands, emotional abuse and emotional demands were unique predictors (p < .05). Efforts to increase patient safety should address emotional abuse, emotional demands, and, therefore, communication and cooperation team climate in surgery personnel.

Characterization of good teleoperators - What aptitudes, interests, and experience correlate with measures of teleoperator performance

NASA Technical Reports Server (NTRS)

Yorchak, J. P.; Hartley, C. S.; Hinman, E.

1985-01-01

The use of aptitude tests and questionnaries to evaluate an individuals aptitude for teleoperation is studied. The Raven Progressive Matrices Test and Differential Aptitude Tests, and a 16-item questionnaire for assessing the subject's interests, academic background, and previous experience are described. The Proto-Flight Manipulator Arm, cameras, console, hand controller, and task board utilized by the 17 engineers are examined. The correlation between aptitude scores and questionnaire responses, and operator performance is investigated. Multiple regression data reveal that the eight predictor variables are not individually significant for evaluating operator performance; however, the complete test battery is applicable for predicting 49 percent of subject variance on the criterion task.

Representation of limb kinematics in Purkinje cell simple spike discharge is conserved across multiple tasks

PubMed Central

Hewitt, Angela L.; Popa, Laurentiu S.; Pasalar, Siavash; Hendrix, Claudia M.

2011-01-01

Encoding of movement kinematics in Purkinje cell simple spike discharge has important implications for hypotheses of cerebellar cortical function. Several outstanding questions remain regarding representation of these kinematic signals. It is uncertain whether kinematic encoding occurs in unpredictable, feedback-dependent tasks or kinematic signals are conserved across tasks. Additionally, there is a need to understand the signals encoded in the instantaneous discharge of single cells without averaging across trials or time. To address these questions, this study recorded Purkinje cell firing in monkeys trained to perform a manual random tracking task in addition to circular tracking and center-out reach. Random tracking provides for extensive coverage of kinematic workspaces. Direction and speed errors are significantly greater during random than circular tracking. Cross-correlation analyses comparing hand and target velocity profiles show that hand velocity lags target velocity during random tracking. Correlations between simple spike firing from 120 Purkinje cells and hand position, velocity, and speed were evaluated with linear regression models including a time constant, τ, as a measure of the firing lead/lag relative to the kinematic parameters. Across the population, velocity accounts for the majority of simple spike firing variability (63 ± 30% of Radj2), followed by position (28 ± 24% of Radj2) and speed (11 ± 19% of Radj2). Simple spike firing often leads hand kinematics. Comparison of regression models based on averaged vs. nonaveraged firing and kinematics reveals lower Radj2 values for nonaveraged data; however, regression coefficients and τ values are highly similar. Finally, for most cells, model coefficients generated from random tracking accurately estimate simple spike firing in either circular tracking or center-out reach. These findings imply that the cerebellum controls movement kinematics, consistent with a forward internal model that predicts upcoming limb kinematics. PMID:21795616

Planning deficits in polysubstance dependent users: Differential associations with severity of drug use and intelligence.

PubMed

Valls-Serrano, C; Verdejo-García, A; Caracuel, A

2016-05-01

Polysubstance use is associated with alterations in different components of executive functioning such as working memory and response inhibition. Nevertheless, less attention has been given to executive planning skills, which are required to benefit of low structured interventions. This study examines the association between severity of use of cocaine, heroin, alcohol, fluid and crystallized intelligence and planning tasks varying on degree of structure. Data were collected from 60 polysubstance users and 30 healthy controls. Cognitive assessment consisted of three planning tasks with different structure levels: Stockings of Cambridge, Zoo Map test, and Multiple Errands Test. Polysubstance users had significant planning deficits across the three tasks compared to healthy controls. Hierarchical regression models showed that severity of drug use and fluid and crystallized intelligence significantly explained performance in all the planning tasks. However, these associations were higher for low-structured real world tasks. These low-structured tasks also showed a unique association with crystallized but not fluid intelligence. Drug abuse is negatively associated with planning abilities, and intelligence is positively associated with planning performance in real-world tasks. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Decision making of heavy cannabis users on the Iowa Gambling Task: stronger association with THC of hair analysis than with personality traits of the Tridimensional Personality Questionnaire.

PubMed

Hermann, Derik; Leménager, Tagrid; Gelbke, Jan; Welzel, Helga; Skopp, Gisela; Mann, Karl

2009-01-01

It is unclear whether impairment in decision making, measured by the Iowa Gambling Task (IGT), in addiction is substance-induced or the consequence of personality structure. Analysis of the IGT, the Tridimensional Personality Questionnaire (TPQ) and cannabinoids in hair and urine were performed in 13 cannabis users and matched controls. Hair Delta(9)-tetrahydrocannabinol (THC) correlated negatively with the last subtrial (cards 80-100) of the IGT (R = -0.67). In all participants (n = 26) the TPQ dimension, harm avoidance, correlated negatively with the total IGT score (R = -0.46). The last IGT-subtrial correlated with adventure seeking (R = 0.43), harm avoidance (R = -0.39) and reward dependence (R = -0.44). The last subtrial gives information on whether a participant has learned the IGT strategy. Multiple regression confirmed the impact of THC on the last subtrial, whereas TPQ personality traits did not additionally explain variance. Former indications of the IGT performance depending on the amount of cannabis consumed were replicated with an objective measurement of chronic cannabis consumption (hair THC). Multiple regression analysis argues for a stronger impact of chronic THC consumption than personality traits, but does not provide a causal relationship. Other factors (e.g. genetic) may also play a role. 2009 S. Karger AG, Basel.

Role of auditory non-verbal working memory in sentence repetition for bilingual children with primary language impairment.

PubMed

Ebert, Kerry Danahy

2014-01-01

Sentence repetition performance is attracting increasing interest as a valuable clinical marker for primary (or specific) language impairment (LI) in both monolingual and bilingual populations. Multiple aspects of memory appear to contribute to sentence repetition performance, but non-verbal memory has not yet been considered. To explore the relationship between a measure of non-verbal auditory working memory (NVWM) and sentence repetition performance in a sample of bilingual children with LI. Forty-seven school-aged Spanish-English bilingual children with LI completed sentence repetition and non-word repetition tasks in both Spanish and English as well as an NVWM task. Hierarchical multiple linear regression was used to predict sentence repetition in each language using age, non-word repetition and NVWM. NVWM predicted unique variance in sentence repetition performance in both languages after accounting for chronological age and language-specific phonological memory, as measured by non-word repetition. Domain-general memory resources play a unique role in sentence repetition performance in children with LI. Non-verbal working memory weaknesses may contribute to the poor performance of children with LI on sentence repetition tasks. © 2014 Royal College of Speech and Language Therapists.

The Role of Auditory Nonverbal Working Memory in Sentence Repetition for Bilingual Children with Primary Language Impairment

PubMed Central

Ebert, Kerry Danahy

2015-01-01

Background Sentence repetition performance is attracting increasing interest as a valuable clinical marker for Primary (or Specific) Language Impairment (LI) in both monolingual and bilingual populations. Multiple aspects of memory appear to contribute to sentence repetition performance, but nonverbal memory has not yet been considered. Aims The purpose of this study was to explore the relationship between a measure of nonverbal auditory working memory (NVWM) and sentence repetition performance in a sample of bilingual children with LI. Methods & Procedures Forty-seven school-aged Spanish-English bilingual children with LI completed sentence repetition and nonword repetition tasks in both Spanish and English as well as an NVWM task. Hierarchical multiple linear regression was used to predict sentence repetition in each language using age, nonword repetition, and NVWM. Outcomes & Results NVWM predicted unique variance in sentence repetition performance in both languages after accounting for chronological age and language-specific phonological memory, as measured by nonword repetition. Conclusions & Implications Domain-general memory resources play a unique role in sentence repetition performance in children with LI. Nonverbal working memory weaknesses may contribute to the poor performance of children with LI on sentence repetition tasks. PMID:24894308

Exercise-related goals and self-efficacy as correlates of aquatic exercise in individuals with arthritis.

PubMed

Gyurcsik, Nancy C; Estabrooks, Paul A; Frahm-Templar, Melissa J

2003-06-15

To examine whether aquatic exercise-related goals, task self-efficacy, and scheduling self-efficacy are predictive of aquatic exercise attendance in individuals with arthritis. A secondary objective was to determine whether high attendees differed from low attendees on goals and self-efficacy. The sample comprised 216 adults with arthritis (mean age 69.21 years). Measures included exercise-related goal difficulty and specificity, task and scheduling self-efficacy, and 8-week aquatic exercise attendance. Results of a multiple hierarchical regression analysis were significant (P < 0.01). Goal difficulty, specificity, and task self-efficacy were independent predictors of attendance (P < 0.05). A significant multivariate analysis of variance (P < 0.01) indicated that high attendees had higher task and scheduling self-efficacy and lower goal difficulty than did low attendees (P < 0.05). Support for the importance of exercise-related goal setting and self-efficacy was demonstrated. Implications pertain to the design of interventions to impact aquatic exercise.

To Stroop or Not to Stroop: Sex-Related Differences in Brain-Behavior Associations During Early Childhood

PubMed Central

Cuevas, Kimberly; Calkins, Susan D.; Bell, Martha Ann

2015-01-01

Executive functions (EFs) are linked with optimal cognitive and social-emotional development. Despite behavioral evidence of sex differences in early childhood EF, little is known about potential sex differences in corresponding brain-behavior associations. The present study examined changes in 4-year-olds’ 6–9 Hz EEG power in response to increased executive processing demands (i.e., “Stroop-like” vs. “non-Stroop” day-night tasks). Although there were no sex differences in task performance, an examination of multiple scalp electrode sites revealed that boys exhibited more widespread changes in EEG power as compared to girls. Further, multiple regression analyses controlling for maternal education and non-EF performance indicated that individual differences in boys’ and girls’ EF performance were associated with different frontal neural correlates (i.e., different frontal scalp sites and different measures of EEG power). These data reveal valuable information concerning sex differences in the neural systems underlying executive processing during early childhood. PMID:26681615

Logistic Stick-Breaking Process

PubMed Central

Ren, Lu; Du, Lan; Carin, Lawrence; Dunson, David B.

2013-01-01

A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general spatially- or temporally-dependent data, imposing the belief that proximate data are more likely to be clustered together. The sticks in the LSBP are realized via multiple logistic regression functions, with shrinkage priors employed to favor contiguous and spatially localized segments. The LSBP is also extended for the simultaneous processing of multiple data sets, yielding a hierarchical logistic stick-breaking process (H-LSBP). The model parameters (atoms) within the H-LSBP are shared across the multiple learning tasks. Efficient variational Bayesian inference is derived, and comparisons are made to related techniques in the literature. Experimental analysis is performed for audio waveforms and images, and it is demonstrated that for segmentation applications the LSBP yields generally homogeneous segments with sharp boundaries. PMID:25258593

Executive Function, Visual Attention and the Cocktail Party Problem in Musicians and Non-Musicians.

PubMed

Clayton, Kameron K; Swaminathan, Jayaganesh; Yazdanbakhsh, Arash; Zuk, Jennifer; Patel, Aniruddh D; Kidd, Gerald

2016-01-01

The goal of this study was to investigate how cognitive factors influence performance in a multi-talker, "cocktail-party" like environment in musicians and non-musicians. This was achieved by relating performance in a spatial hearing task to cognitive processing abilities assessed using measures of executive function (EF) and visual attention in musicians and non-musicians. For the spatial hearing task, a speech target was presented simultaneously with two intelligible speech maskers that were either colocated with the target (0° azimuth) or were symmetrically separated from the target in azimuth (at ±15°). EF assessment included measures of cognitive flexibility, inhibition control and auditory working memory. Selective attention was assessed in the visual domain using a multiple object tracking task (MOT). For the MOT task, the observers were required to track target dots (n = 1,2,3,4,5) in the presence of interfering distractor dots. Musicians performed significantly better than non-musicians in the spatial hearing task. For the EF measures, musicians showed better performance on measures of auditory working memory compared to non-musicians. Furthermore, across all individuals, a significant correlation was observed between performance on the spatial hearing task and measures of auditory working memory. This result suggests that individual differences in performance in a cocktail party-like environment may depend in part on cognitive factors such as auditory working memory. Performance in the MOT task did not differ between groups. However, across all individuals, a significant correlation was found between performance in the MOT and spatial hearing tasks. A stepwise multiple regression analysis revealed that musicianship and performance on the MOT task significantly predicted performance on the spatial hearing task. Overall, these findings confirm the relationship between musicianship and cognitive factors including domain-general selective attention and working memory in solving the "cocktail party problem".

Executive Function, Visual Attention and the Cocktail Party Problem in Musicians and Non-Musicians

PubMed Central

Clayton, Kameron K.; Swaminathan, Jayaganesh; Yazdanbakhsh, Arash; Zuk, Jennifer; Patel, Aniruddh D.; Kidd, Gerald

2016-01-01

The goal of this study was to investigate how cognitive factors influence performance in a multi-talker, “cocktail-party” like environment in musicians and non-musicians. This was achieved by relating performance in a spatial hearing task to cognitive processing abilities assessed using measures of executive function (EF) and visual attention in musicians and non-musicians. For the spatial hearing task, a speech target was presented simultaneously with two intelligible speech maskers that were either colocated with the target (0° azimuth) or were symmetrically separated from the target in azimuth (at ±15°). EF assessment included measures of cognitive flexibility, inhibition control and auditory working memory. Selective attention was assessed in the visual domain using a multiple object tracking task (MOT). For the MOT task, the observers were required to track target dots (n = 1,2,3,4,5) in the presence of interfering distractor dots. Musicians performed significantly better than non-musicians in the spatial hearing task. For the EF measures, musicians showed better performance on measures of auditory working memory compared to non-musicians. Furthermore, across all individuals, a significant correlation was observed between performance on the spatial hearing task and measures of auditory working memory. This result suggests that individual differences in performance in a cocktail party-like environment may depend in part on cognitive factors such as auditory working memory. Performance in the MOT task did not differ between groups. However, across all individuals, a significant correlation was found between performance in the MOT and spatial hearing tasks. A stepwise multiple regression analysis revealed that musicianship and performance on the MOT task significantly predicted performance on the spatial hearing task. Overall, these findings confirm the relationship between musicianship and cognitive factors including domain-general selective attention and working memory in solving the “cocktail party problem”. PMID:27384330

“The Relationship between Executive Functioning, Processing Speed and White Matter Integrity in Multiple Sclerosis”

PubMed Central

Genova, Helen M.; DeLuca, John; Chiaravalloti, Nancy; Wylie, Glenn

2014-01-01

The primary purpose of the current study was to examine the relationship between performance on executive tasks and white matter integrity, assessed by diffusion tensor imaging (DTI) in Multiple Sclerosis (MS). A second aim was to examine how processing speed affects the relationship between executive functioning and FA. This relationship was examined in two executive tasks that rely heavily on processing speed: the Color-Word Interference Test and Trail-Making Test (Delis-Kaplan Executive Function System). It was hypothesized that reduced fractional anisotropy (FA) is related to poor performance on executive tasks in MS, but that this relationship would be affected by the statistical correction of processing speed from the executive tasks. 15 healthy controls and 25 persons with MS participated. Regression analyses were used to examine the relationship between executive functioning and FA, both before and after processing speed was removed from the executive scores. Before processing speed was removed from the executive scores, reduced FA was associated with poor performance on Color-Word Interference Test and Trail-Making Test in a diffuse network including corpus callosum and superior longitudinal fasciculus. However, once processing speed was removed, the relationship between executive functions and FA was no longer significant on the Trail Making test, and significantly reduced and more localized on the Color-Word Interference Test. PMID:23777468

Machine Learning EEG to Predict Cognitive Functioning and Processing Speed Over a 2-Year Period in Multiple Sclerosis Patients and Controls.

PubMed

Kiiski, Hanni; Jollans, Lee; Donnchadha, Seán Ó; Nolan, Hugh; Lonergan, Róisín; Kelly, Siobhán; O'Brien, Marie Claire; Kinsella, Katie; Bramham, Jessica; Burke, Teresa; Hutchinson, Michael; Tubridy, Niall; Reilly, Richard B; Whelan, Robert

2018-05-01

Event-related potentials (ERPs) show promise to be objective indicators of cognitive functioning. The aim of the study was to examine if ERPs recorded during an oddball task would predict cognitive functioning and information processing speed in Multiple Sclerosis (MS) patients and controls at the individual level. Seventy-eight participants (35 MS patients, 43 healthy age-matched controls) completed visual and auditory 2- and 3-stimulus oddball tasks with 128-channel EEG, and a neuropsychological battery, at baseline (month 0) and at Months 13 and 26. ERPs from 0 to 700 ms and across the whole scalp were transformed into 1728 individual spatio-temporal datapoints per participant. A machine learning method that included penalized linear regression used the entire spatio-temporal ERP to predict composite scores of both cognitive functioning and processing speed at baseline (month 0), and months 13 and 26. The results showed ERPs during the visual oddball tasks could predict cognitive functioning and information processing speed at baseline and a year later in a sample of MS patients and healthy controls. In contrast, ERPs during auditory tasks were not predictive of cognitive performance. These objective neurophysiological indicators of cognitive functioning and processing speed, and machine learning methods that can interrogate high-dimensional data, show promise in outcome prediction.

Lesion symptom map of cognitive-postural interference in multiple sclerosis.

PubMed

Ruggieri, Serena; Fanelli, Fulvia; Castelli, Letizia; Petsas, Nikolaos; De Giglio, Laura; Prosperini, Luca

2018-04-01

To investigate the disease-altered structure-function relationship underlying the cognitive-postural interference (CPI) phenomenon in multiple sclerosis (MS). We measured postural sway of 96 patients and 48 sex-/age-matched healthy controls by force platform in quiet standing (single-task (ST)) while performing the Stroop test (dual-task (DT)) to estimate the dual-task cost (DTC) of balance. In patient group, binary T2 and T1 lesion masks and their corresponding lesion volumes were obtained from magnetic resonance imaging (MRI) of brain. Normalized brain volume (NBV) was also estimated by SIENAX. Correlations between DTC and lesion location were determined by voxel-based lesion symptom mapping (VLSM) analyses. Patients had greater DTC than controls ( p < 0.001). Among whole brain MRI metrics, only T1 lesion volume correlated with DTC ( r = -0.27; p < 0.01). However, VLSM analysis did not reveal any association with DTC using T1 lesion masks. By contrast, we found clusters of T2 lesions in distinct anatomical regions (anterior and superior corona radiata, bilaterally) to be correlated with DTC ( p < 0.01 false discovery rate (FDR)-corrected). A multivariable stepwise regression model confirmed findings from VLSM analysis. NBV did not contribute to fit the model. Our findings suggest that the CPI phenomenon in MS can be explained by disconnection along specific areas implicated in task-switching abilities and divided attention.

Harsh parenting and child externalizing behavior: skin conductance level reactivity as a moderator.

PubMed

Erath, Stephen A; El-Sheikh, Mona; Mark Cummings, E

2009-01-01

Skin conductance level reactivity (SCLR) was examined as a moderator of the association between harsh parenting and child externalizing behavior. Participants were 251 boys and girls (8-9 years). Mothers and fathers provided reports of harsh parenting and their children's externalizing behavior; children also provided reports of harsh parenting. SCLR was assessed in response to a socioemotional stress task and a problem-solving challenge task. Regression analyses revealed that the association between harsh parenting and externalizing behavior was stronger among children with lower SCLR, as compared to children with higher SCLR. SCLR may be a more robust moderator among boys compared to girls. Results are discussed with regard to theories on antisocial behavior and multiple-domain models of child development.

Should metacognition be measured by logistic regression?

PubMed

Rausch, Manuel; Zehetleitner, Michael

2017-03-01

Are logistic regression slopes suitable to quantify metacognitive sensitivity, i.e. the efficiency with which subjective reports differentiate between correct and incorrect task responses? We analytically show that logistic regression slopes are independent from rating criteria in one specific model of metacognition, which assumes (i) that rating decisions are based on sensory evidence generated independently of the sensory evidence used for primary task responses and (ii) that the distributions of evidence are logistic. Given a hierarchical model of metacognition, logistic regression slopes depend on rating criteria. According to all considered models, regression slopes depend on the primary task criterion. A reanalysis of previous data revealed that massive numbers of trials are required to distinguish between hierarchical and independent models with tolerable accuracy. It is argued that researchers who wish to use logistic regression as measure of metacognitive sensitivity need to control the primary task criterion and rating criteria. Copyright © 2017 Elsevier Inc. All rights reserved.

Relationships among goal orientations, motivational climate and flow in adolescent athletes: differences by gender.

PubMed

Moreno Murcia, Juan Antonio; Cervelló Gimeno, Eduardo; González-Cutre Coll, David

2008-05-01

The purpose of this investigation was to examine the relationships among perceived motivational climate, individuals' goal orientations, and dispositional flow, with attention to possible gender differences. A sample of 413 young athletes, ages 12 to 16 years, completed the Perceived Motivational Climate in Sport Questionnaire-2 (PMCSQ-2) and Perception of Success Questionnaire (POSQ), as well as the Dispositional Flow Scale. Task orientation was positively and significantly related to a perceived task-involving motivational climate and to the disposition to experience flow in the sport. Ego orientation was positively and significantly associated with a perceived ego-involving motivational climate and with dispositional flow. The perceptions of task-involving and ego-involving motivational climates were positively and significantly linked to general dispositional flow. Multiple regression analysis indicated that both task and ego goal orientations and perceived task- and ego-oriented climates predicted dispositional flow. Males displayed a stronger ego orientation, and were more likely to report that they participated in an ego-oriented climate, than did females. To the contrary, the females were more likely to perceive a task-oriented climate than did the males. No meaningful differences were found between males and females in general dispositional flow.

ERP correlates of word production predictors in picture naming: a trial by trial multiple regression analysis from stimulus onset to response.

PubMed

Valente, Andrea; Bürki, Audrey; Laganaro, Marina

2014-01-01

A major effort in cognitive neuroscience of language is to define the temporal and spatial characteristics of the core cognitive processes involved in word production. One approach consists in studying the effects of linguistic and pre-linguistic variables in picture naming tasks. So far, studies have analyzed event-related potentials (ERPs) during word production by examining one or two variables with factorial designs. Here we extended this approach by investigating simultaneously the effects of multiple theoretical relevant predictors in a picture naming task. High density EEG was recorded on 31 participants during overt naming of 100 pictures. ERPs were extracted on a trial by trial basis from picture onset to 100 ms before the onset of articulation. Mixed-effects regression models were conducted to examine which variables affected production latencies and the duration of periods of stable electrophysiological patterns (topographic maps). Results revealed an effect of a pre-linguistic variable, visual complexity, on an early period of stable electric field at scalp, from 140 to 180 ms after picture presentation, a result consistent with the proposal that this time period is associated with visual object recognition processes. Three other variables, word Age of Acquisition, Name Agreement, and Image Agreement influenced response latencies and modulated ERPs from ~380 ms to the end of the analyzed period. These results demonstrate that a topographic analysis fitted into the single trial ERPs and covering the entire processing period allows one to associate the cost generated by psycholinguistic variables to the duration of specific stable electrophysiological processes and to pinpoint the precise time-course of multiple word production predictors at once.

Are factors related to dual-task performance in people with Parkinson's disease dependent on the type of dual task?

PubMed

Strouwen, Carolien; Molenaar, Esther A L M; Keus, Samyra H J; Münks, Liesbeth; Heremans, Elke; Vandenberghe, Wim; Bloem, Bastiaan R; Nieuwboer, Alice

2016-02-01

Impaired dual-task performance significantly impacts upon functional mobility in people with Parkinson's disease (PD). The aim of this study was to identify determinants of dual-task performance in people with PD in three different dual tasks to assess their possible task-dependency. We recruited 121 home-dwelling patients with PD (mean age 65.93 years; mean disease duration 8.67 years) whom we subjected to regular walking (control condition) and to three dual-task conditions: walking combined with a backwards Digit Span task, an auditory Stroop task and a Mobile Phone task. We measured dual-task gait velocity using the GAITRite mat and dual-task reaction times and errors on the concurrent tasks as outcomes. Motor, cognitive and descriptive variables which correlated to dual-task performance (p < 0.20) were entered into a stepwise forward multiple linear regression model. Single-task gait velocity and executive function, tested by the alternating intake test, was significantly associated with gait velocity during the Digit Span (R(2) = 0.65; p < 0.001), the Stroop (R(2) = 0.73; p < 0.001) and the Mobile Phone task (R(2) = 0.62; p < 0.001). In addition, disease severity proved correlated to gait velocity during the Stroop task. Age was a surplus determinant of gait velocity while using a mobile phone. Single-task gait velocity and executive function as measured by a verbal fluency switching task were independent determinants of dual-task gait performance in people with PD. In contrast to expectation, these factors were the same across different tasks, supporting the robustness of the findings. Future study needs to determine whether these factors predict dual-task abnormalities prospectively. Copyright © 2015 Elsevier Ltd. All rights reserved.

Identification of the neural correlates of cyclothymic temperament using an esthetic judgment for paintings task in fMRI.

PubMed

Mizokami, Yoshinori; Terao, Takeshi; Hatano, Koji; Kodama, Kensuke; Kohno, Kentaro; Makino, Mayu; Hoaki, Nobuhiko; Araki, Yasuo; Izumi, Toshihiko; Shimomura, Tsuyoshi; Fujiki, Minoru; Kochiyama, Takanori

2014-12-01

There is a well-known association between artistic creativity and cyclothymic temperament but the neural correlates of cyclothymic temperament have not yet been fully identified. Recently, we showed that the left lingual gyrus and bilateral cuneus may be associated with esthetic judgment of representational paintings, we therefore sought to investigate brain activity during esthetic judgment of paintings in relation to measures of cyclothymic temperament. Regions of interest (ROI) were set at the left lingual gyrus and bilateral cuneus using automated anatomical labeling, and percent signal changes of the ROIs were measured by marsbar toolbox. The associations between percent signal changes of the ROIs during esthetic judgments of paintings and cyclothymic temperament scores were investigated by Pearson׳s coefficient. Moreover, the associations were further analyzed using multiple regression analysis whereby cyclothymic temperament scores were a dependent factor and percent signal changes of the 3 ROIs and the other 4 temperament scores were independent factors. There was a significantly negative association of cyclothymic temperament scores with the percent signal changes of the left lingual gyrus during esthetic judgments of paintings, but not with those of bilateral cuneus. Even after adjustment using multiple regression analysis, this finding remained unchanged. The number of subjects was relatively small and the task was limited to appreciation of paintings. The present findings suggest that cyclothymic temperament may be associated with the left lingual gyrus. Copyright © 2014 Elsevier B.V. All rights reserved.

Roles of Perceived Motivational Climates Created by Coach, Peer, and Parent on Dispositional Flow in Young Athletes.

PubMed

Çağlar, Emine; Aşçi, F Hülya; Uygurtaş, Murat

2017-04-01

We investigated the contribution of perceived motivational climates created by coach, peer, and parent on the dispositional flow experience of young athletes. Eighty-six female ( M age  = 14.24, SD = 1.38 years) and 134 male ( M age  = 16.28, SD = 1.17 years) athletes completed questionnaires of perceived motivational climates created by coach, peer, and parent and the Dispositional Flow Scale-2. Results of hierarchical multiple regression analyses indicated that perceived task-involving coach (β = .40, p < .001) and peer (β = .28, p < .002) motivational climates were the only significant predictors of dispositional flow. These findings suggest that task-involving motivational climates should be strengthened to increase experience of flow.

General functioning predicts reward and punishment learning in schizophrenia.

PubMed

Somlai, Zsuzsanna; Moustafa, Ahmed A; Kéri, Szabolcs; Myers, Catherine E; Gluck, Mark A

2011-04-01

Previous studies investigating feedback-driven reinforcement learning in patients with schizophrenia have provided mixed results. In this study, we explored the clinical predictors of reward and punishment learning using a probabilistic classification learning task. Patients with schizophrenia (n=40) performed similarly to healthy controls (n=30) on the classification learning task. However, more severe negative and general symptoms were associated with lower reward-learning performance, whereas poorer general psychosocial functioning was correlated with both lower reward- and punishment-learning performances. Multiple linear regression analyses indicated that general psychosocial functioning was the only significant predictor of reinforcement learning performance when education, antipsychotic dose, and positive, negative and general symptoms were included in the analysis. These results suggest a close relationship between reinforcement learning and general psychosocial functioning in schizophrenia. Published by Elsevier B.V.

Gaussian Process Regression for Predictive But Interpretable Machine Learning Models: An Example of Predicting Mental Workload across Tasks

PubMed Central

Caywood, Matthew S.; Roberts, Daniel M.; Colombe, Jeffrey B.; Greenwald, Hal S.; Weiland, Monica Z.

2017-01-01

There is increasing interest in real-time brain-computer interfaces (BCIs) for the passive monitoring of human cognitive state, including cognitive workload. Too often, however, effective BCIs based on machine learning techniques may function as “black boxes” that are difficult to analyze or interpret. In an effort toward more interpretable BCIs, we studied a family of N-back working memory tasks using a machine learning model, Gaussian Process Regression (GPR), which was both powerful and amenable to analysis. Participants performed the N-back task with three stimulus variants, auditory-verbal, visual-spatial, and visual-numeric, each at three working memory loads. GPR models were trained and tested on EEG data from all three task variants combined, in an effort to identify a model that could be predictive of mental workload demand regardless of stimulus modality. To provide a comparison for GPR performance, a model was additionally trained using multiple linear regression (MLR). The GPR model was effective when trained on individual participant EEG data, resulting in an average standardized mean squared error (sMSE) between true and predicted N-back levels of 0.44. In comparison, the MLR model using the same data resulted in an average sMSE of 0.55. We additionally demonstrate how GPR can be used to identify which EEG features are relevant for prediction of cognitive workload in an individual participant. A fraction of EEG features accounted for the majority of the model’s predictive power; using only the top 25% of features performed nearly as well as using 100% of features. Subsets of features identified by linear models (ANOVA) were not as efficient as subsets identified by GPR. This raises the possibility of BCIs that require fewer model features while capturing all of the information needed to achieve high predictive accuracy. PMID:28123359

Representation of limb kinematics in Purkinje cell simple spike discharge is conserved across multiple tasks.

PubMed

Hewitt, Angela L; Popa, Laurentiu S; Pasalar, Siavash; Hendrix, Claudia M; Ebner, Timothy J

2011-11-01

Encoding of movement kinematics in Purkinje cell simple spike discharge has important implications for hypotheses of cerebellar cortical function. Several outstanding questions remain regarding representation of these kinematic signals. It is uncertain whether kinematic encoding occurs in unpredictable, feedback-dependent tasks or kinematic signals are conserved across tasks. Additionally, there is a need to understand the signals encoded in the instantaneous discharge of single cells without averaging across trials or time. To address these questions, this study recorded Purkinje cell firing in monkeys trained to perform a manual random tracking task in addition to circular tracking and center-out reach. Random tracking provides for extensive coverage of kinematic workspaces. Direction and speed errors are significantly greater during random than circular tracking. Cross-correlation analyses comparing hand and target velocity profiles show that hand velocity lags target velocity during random tracking. Correlations between simple spike firing from 120 Purkinje cells and hand position, velocity, and speed were evaluated with linear regression models including a time constant, τ, as a measure of the firing lead/lag relative to the kinematic parameters. Across the population, velocity accounts for the majority of simple spike firing variability (63 ± 30% of R(adj)(2)), followed by position (28 ± 24% of R(adj)(2)) and speed (11 ± 19% of R(adj)(2)). Simple spike firing often leads hand kinematics. Comparison of regression models based on averaged vs. nonaveraged firing and kinematics reveals lower R(adj)(2) values for nonaveraged data; however, regression coefficients and τ values are highly similar. Finally, for most cells, model coefficients generated from random tracking accurately estimate simple spike firing in either circular tracking or center-out reach. These findings imply that the cerebellum controls movement kinematics, consistent with a forward internal model that predicts upcoming limb kinematics.

Pareto fronts for multiobjective optimization design on materials data

NASA Astrophysics Data System (ADS)

Gopakumar, Abhijith; Balachandran, Prasanna; Gubernatis, James E.; Lookman, Turab

Optimizing multiple properties simultaneously is vital in materials design. Here we apply infor- mation driven, statistical optimization strategies blended with machine learning methods, to address multi-objective optimization tasks on materials data. These strategies aim to find the Pareto front consisting of non-dominated data points from a set of candidate compounds with known character- istics. The objective is to find the pareto front in as few additional measurements or calculations as possible. We show how exploration of the data space to find the front is achieved by using uncer- tainties in predictions from regression models. We test our proposed design strategies on multiple, independent data sets including those from computations as well as experiments. These include data sets for Max phases, piezoelectrics and multicomponent alloys.

PRISM: Enmeshment of illness and self-schema.

PubMed

Denton, Fiona; Sharpe, Louise; Schrieber, Leslie

2004-01-01

The Pictorial Representation of Illness and Self Measure (PRISM) is a recently developed tool purported to assess burden of suffering due to illness. The nature of the PRISM task suggests a conceptual link to the illness self-schema construct hypothesised to be present in some individuals with chronic illness. This study investigates the relationship between PRISM and schema as measured by cognitive bias. 43 patients with systemic lupus erythematosus (SLE) completed an information-processing task involving endorsement of positive and negative illness words as descriptors of themselves, followed by free recall of the words. The outcome measures were endorsement and recall bias for negative illness words. Patients also completed the PRISM task and were assessed on other physical and psychological variables. PRISM did not correlate significantly with age, depression, functional impairment or disease activity. In a multiple regression analysis, only recall bias made an independent contribution to PRISM. Illness self-schema appears to play a significant role in determining the way in which SLE patients complete the PRISM task. This is discussed in light of a schema enmeshment model recently proposed in the cognitive bias literature. Copyright 2004 S. Karger AG, Basel

Normative data for distal line bisection and baking tray task.

PubMed

Facchin, Alessio; Beschin, Nicoletta; Pisano, Alessia; Reverberi, Cristina

2016-09-01

Line bisection is one of the tests used to diagnose unilateral spatial neglect (USN). Despite its wide application, no procedure or norms were available for the distal variant when the task was performed at distance with a laser pointer. Furthermore, the baking tray task was an ecological test aimed at diagnosing USN in a more natural context. The aim of this study was to collect normative values for these two tests in an Italian population. We recruited a sample of 191 healthy subjects with ages ranging from 20 to 89 years. They performed line bisection with a laser pointer on three different line lengths (1, 1.5, and 2 m) at a distance of 3 m. After this task, the subjects performed the baking tray task and a second repetition of line bisection to test the reliability of measurement. Multiple regression analysis revealed no significant effects of demographic variables on the performance of both tests. Normative cut-off values for the two tests were developed using non-parametric tolerance intervals. The results formed the basis for clinical use of these two tools for assessing lateralized performance of patients with brain injury and for diagnosing USN.

Statistical modelling of networked human-automation performance using working memory capacity.

PubMed

Ahmed, Nisar; de Visser, Ewart; Shaw, Tyler; Mohamed-Ameen, Amira; Campbell, Mark; Parasuraman, Raja

2014-01-01

This study examines the challenging problem of modelling the interaction between individual attentional limitations and decision-making performance in networked human-automation system tasks. Analysis of real experimental data from a task involving networked supervision of multiple unmanned aerial vehicles by human participants shows that both task load and network message quality affect performance, but that these effects are modulated by individual differences in working memory (WM) capacity. These insights were used to assess three statistical approaches for modelling and making predictions with real experimental networked supervisory performance data: classical linear regression, non-parametric Gaussian processes and probabilistic Bayesian networks. It is shown that each of these approaches can help designers of networked human-automated systems cope with various uncertainties in order to accommodate future users by linking expected operating conditions and performance from real experimental data to observable cognitive traits like WM capacity. Practitioner Summary: Working memory (WM) capacity helps account for inter-individual variability in operator performance in networked unmanned aerial vehicle supervisory tasks. This is useful for reliable performance prediction near experimental conditions via linear models; robust statistical prediction beyond experimental conditions via Gaussian process models and probabilistic inference about unknown task conditions/WM capacities via Bayesian network models.

Age differences in cognitive performance in later life: relationships to self-reported health and activity life style.

PubMed

Hultsch, D F; Hammer, M; Small, B J

1993-01-01

The predictive relationships among individual differences in self-reported physical health and activity life style and performance on an array of information processing and intellectual ability measures were examined. A sample of 484 men and women aged 55 to 86 years completed a battery of cognitive tasks measuring verbal processing time, working memory, vocabulary, verbal fluency, world knowledge, word recall, and text recall. Hierarchical regression was used to predict performance on these tasks from measures of self-reported physical health, alcohol and tobacco use, and level of participation in everyday activities. The results indicated: (a) individual differences in self-reported health and activity predicted performance on multiple cognitive measures; (b) self-reported health was more predictive of processing resource variables than knowledge-based abilities; (c) interaction effects indicated that participation in cognitively demanding activities was more highly related to performance on some measures for older adults than for middle-aged adults; and (d) age-related differences in performance on multiple measures were attenuated by partialing individual differences in self-reported health and activity.

Cold-Blooded Attention: Finger Temperature Predicts Attentional Performance.

PubMed

Vergara, Rodrigo C; Moënne-Loccoz, Cristóbal; Maldonado, Pedro E

2017-01-01

Thermal stress has been shown to increase the chances of unsafe behavior during industrial and driving performances due to reductions in mental and attentional resources. Nonetheless, establishing appropriate safety standards regarding environmental temperature has been a major problem, as modulations are also be affected by the task type, complexity, workload, duration, and previous experience with the task. To bypass this attentional and thermoregulatory problem, we focused on the body rather than environmental temperature. Specifically, we measured tympanic, forehead, finger and environmental temperatures accompanied by a battery of attentional tasks. We considered a 10 min baseline period wherein subjects were instructed to sit and relax, followed by three attentional tasks: a continuous performance task (CPT), a flanker task (FT) and a counting task (CT). Using multiple linear regression models, we evaluated which variable(s) were the best predictors of performance. The results showed a decrement in finger temperature due to instruction and task engagement that was absent when the subject was instructed to relax. No changes were observed in tympanic or forehead temperatures, while the environmental temperature remained almost constant for each subject. Specifically, the magnitude of the change in finger temperature was the best predictor of performance in all three attentional tasks. The results presented here suggest that finger temperature can be used as a predictor of alertness, as it predicted performance in attentional tasks better than environmental temperature. These findings strongly support that peripheral temperature can be used as a tool to prevent unsafe behaviors and accidents.

Taking Lessons Learned from a Proxy Application to a Full Application for SNAP and PARTISN

DOE PAGES

Womeldorff, Geoffrey Alan; Payne, Joshua Estes; Bergen, Benjamin Karl

2017-06-09

SNAP is a proxy application which simulates the computational motion of a neutral particle transport code, PARTISN. Here in this work, we have adapted parts of SNAP separately; we have re-implemented the iterative shell of SNAP in the task-model runtime Legion, showing an improvement to the original schedule, and we have created multiple Kokkos implementations of the computational kernel of SNAP, displaying similar performance to the native Fortran. We then translate our Kokkos experiments in SNAP to PARTISN, necessitating engineering development, regression testing, and further thought.

Taking Lessons Learned from a Proxy Application to a Full Application for SNAP and PARTISN

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

Womeldorff, Geoffrey Alan; Payne, Joshua Estes; Bergen, Benjamin Karl

SNAP is a proxy application which simulates the computational motion of a neutral particle transport code, PARTISN. Here in this work, we have adapted parts of SNAP separately; we have re-implemented the iterative shell of SNAP in the task-model runtime Legion, showing an improvement to the original schedule, and we have created multiple Kokkos implementations of the computational kernel of SNAP, displaying similar performance to the native Fortran. We then translate our Kokkos experiments in SNAP to PARTISN, necessitating engineering development, regression testing, and further thought.

Cognitive task demands, self-control demands and the mental well-being of office workers.

PubMed

Bridger, Robert S; Brasher, Kate

2011-09-01

The cognitive task demands of office workers and the self-control demands of their work roles were measured in a sample of 196 employees in two different office layouts using a self-report questionnaire, which was circulated electronically. Multiple linear regression analysis revealed that both factors were associated with mental well-being, but not with physical well-being, while controlling for exposure to psychosocial stressors. The interaction between cognitive task demands and self-control demands had the strongest association with mental well-being, suggesting that the deleterious effect of one was greater when the other was present. An exploratory analysis revealed that the association was stronger for employees working in a large open-plan office than for those working in smaller offices with more privacy. Frustration of work goals was the cognitive task demand having the strongest negative impact on mental well-being. Methodological limitations and scale psychometrics (particularly the use of the NASA Task Load Index) are discussed. STATEMENT OF RELEVANCE: Modern office work has high mental demands and low physical demands and there is a need to design offices to prevent adverse psychological reactions. It is shown that cognitive task demands interact with self-control demands to degrade mental well-being. The association was stronger in an open-plan office.

Creativity and inductive reasoning: the relationship between divergent thinking and performance on Wasons 246 task.

PubMed

Vartanian, Oshin; Martindale, Colin; Kwiatkowski, Jonna

2003-05-01

This study was an investigation of the relationship between potential creativityas measured by fluency scores on the Alternate Uses Testand performance on Wasons 246 task. As hypothesized, participants who were successful in discovering the rule had significantly higher fluency scores. Successful participants also generated higher frequencies of confirmatory and disconfirmatory hypotheses, but a multiple regression analysis using the stepwise method revealed that the frequency of generating disconfirmatory hypotheses and fluency scores were the only two significant factors in task outcome. The results also supported earlier studies where disconfirmation was shown to play a more important role in the later stages of hypothesis testing. This was especially true of successful participants, who employed a higher frequency of disconfirmatory hypotheses after receiving feedback on the first announcement. These results imply that successful participants benefited from the provision of feedback on the first announcement by switching to a more successful strategy in the hypothesis-testing sequence.

Impact of auditory selective attention on verbal short-term memory and vocabulary development.

PubMed

Majerus, Steve; Heiligenstein, Lucie; Gautherot, Nathalie; Poncelet, Martine; Van der Linden, Martial

2009-05-01

This study investigated the role of auditory selective attention capacities as a possible mediator of the well-established association between verbal short-term memory (STM) and vocabulary development. A total of 47 6- and 7-year-olds were administered verbal immediate serial recall and auditory attention tasks. Both task types probed processing of item and serial order information because recent studies have shown this distinction to be critical when exploring relations between STM and lexical development. Multiple regression and variance partitioning analyses highlighted two variables as determinants of vocabulary development: (a) a serial order processing variable shared by STM order recall and a selective attention task for sequence information and (b) an attentional variable shared by selective attention measures targeting item or sequence information. The current study highlights the need for integrative STM models, accounting for conjoined influences of attentional capacities and serial order processing capacities on STM performance and the establishment of the lexical language network.

Impact of Depression, Fatigue, and Global Measure of Cortical Volume on Cognitive Impairment in Multiple Sclerosis

PubMed Central

De Cola, Maria Cristina; D'Aleo, Giangaetano; Sessa, Edoardo; Marino, Silvia

2015-01-01

Objective. To investigate the influence of demographic and clinical variables, such as depression, fatigue, and quantitative MRI marker on cognitive performances in a sample of patients affected by multiple sclerosis (MS). Methods. 60 MS patients (52 relapsing remitting and 8 primary progressive) underwent neuropsychological assessments using Rao's Brief Repeatable Battery of Neuropsychological Tests (BRB-N), the Beck Depression Inventory-second edition (BDI-II), and the Fatigue Severity Scale (FSS). We performed magnetic resonance imaging to all subjects using a 3 T scanner and obtained tissue-specific volumes (normalized brain volume and cortical brain volume). We used Student's t-test to compare depressed and nondepressed MS patients. Finally, we performed a multivariate regression analysis in order to assess possible predictors of patients' cognitive outcome among demographic and clinical variables. Results. 27.12% of the sample (16/59) was cognitively impaired, especially in tasks requiring attention and information processing speed. From between group comparison, we find that depressed patients had worse performances on BRB-N score, greater disability and disease duration, and brain volume decrease. According to multiple regression analysis, the BDI-II score was a significant predictor for most of the neuropsychological tests. Conclusions. Our findings suggest that the presence of depressive symptoms is an important determinant of cognitive performance in MS patients. PMID:25861633

Parallel processing of cognitive and physical demands in left and right prefrontal cortices during smartphone use while walking.

PubMed

Takeuchi, Naoyuki; Mori, Takayuki; Suzukamo, Yoshimi; Tanaka, Naofumi; Izumi, Shin-Ichi

2016-02-01

Smartphone use while walking is becoming a public concern owing to an increased risk of falling that can result from cognitive-motor interference. We evaluated prefrontal cortex (PFC) activity in participants playing a smartphone game while walking, in order to elucidate the role of the PFC in the allocation of attention between physical and cognitive demands. Sixteen young and 15 older adults participated in this study. Participants were instructed to perform a touch number-selecting game on a smartphone while walking. The numbers of correct and mistake responses were analyzed as a measure of cognitive performance. Linear trunk accelerations were measured by another smartphone and analyzed for step time and acceleration magnitude as an assay of gait performance. PFC activity during the task was measured using a wearable 16-channel near-infrared spectroscopy system. Smartphone game playing while walking decreased the cognitive and gait performances compared with performances of single-task condition in older group more than in young group. There was no difference in PFC activation during smartphone use while walking between young and older groups, but age appeared to mediate correlation magnitude between PFC activation and changes in performance. In young adults, multiple regression analysis revealed an association of the right PFC with a reduction in acceleration magnitude (β = 0.581, p = 0.023), and an association of the left PFC with an increase in game-playing mistakes (β = -0.556, p = 0.032) during smartphone use while walking. In older adults, multiple regression analysis revealed an association of the middle PFC with a prolongation of step time (β = -0.550, p = 0.042) and of the left PFC with a reduction in acceleration magnitude (β = -0.648, p = 0.012). In young adults, the left PFC inhibited inappropriate action and the right PFC stabilized gait performance. In older adults, a less-lateralized PFC activity pattern suppressed the deterioration of gait performance, but this resulted in impairment on a simultaneous cognitive task. These results suggest that lateralization of motor and cognitive tasks aids in efficient task completion during a complex action such as using a smartphone while walking.

DeepSkeleton: Learning Multi-Task Scale-Associated Deep Side Outputs for Object Skeleton Extraction in Natural Images

NASA Astrophysics Data System (ADS)

Shen, Wei; Zhao, Kai; Jiang, Yuan; Wang, Yan; Bai, Xiang; Yuille, Alan

2017-11-01

Object skeletons are useful for object representation and object detection. They are complementary to the object contour, and provide extra information, such as how object scale (thickness) varies among object parts. But object skeleton extraction from natural images is very challenging, because it requires the extractor to be able to capture both local and non-local image context in order to determine the scale of each skeleton pixel. In this paper, we present a novel fully convolutional network with multiple scale-associated side outputs to address this problem. By observing the relationship between the receptive field sizes of the different layers in the network and the skeleton scales they can capture, we introduce two scale-associated side outputs to each stage of the network. The network is trained by multi-task learning, where one task is skeleton localization to classify whether a pixel is a skeleton pixel or not, and the other is skeleton scale prediction to regress the scale of each skeleton pixel. Supervision is imposed at different stages by guiding the scale-associated side outputs toward the groundtruth skeletons at the appropriate scales. The responses of the multiple scale-associated side outputs are then fused in a scale-specific way to detect skeleton pixels using multiple scales effectively. Our method achieves promising results on two skeleton extraction datasets, and significantly outperforms other competitors. Additionally, the usefulness of the obtained skeletons and scales (thickness) are verified on two object detection applications: Foreground object segmentation and object proposal detection.

Relationship between Leadership among Peers and Burnout in Sports Teams.

PubMed

Torrado, Julio; Arce, Constantino; Vales-Vázquez, Ángel; Areces, Alberto; Iglesias, Gabriel; Valle, Iván; Patiño, Gabriel

2017-04-03

This study has been conducted with the aim of ascertaining the relationship between peer leaders in sport teams and the levels of burnout experienced by their team-mates. A total of 219 Spanish athletes involved in football and basketball participated in the study. To measure leadership among peers, we employed the Sports Peer Leadership Scale, which comprises 24 items, grouped into 6 primary factors: empathy, influence on decision making, sports values, social support, training orientation and competition orientation. And to measure burnout, we employed the Athlete Burnout Questionnaire, which comprises 15 items which are indicators of physical and emotional exhaustion, devaluation and reduced sense of accomplishment among athletes. The results led to the conclusion that there is a statistically significant negative relationship between perceived leadership capacity and the levels of burnout experience by a team. The greater the level of leadership capacity perceived, the lower the levels of burnout will be. A multiple regression analysis with total burnout as dependent variable and social and task orientations of the leader as predictors showed standardized regression coefficients of -.241 (p = .010) and -.076 (p = .413), respectively for social and task orientation, being the effect size equal to .089.

Strategic predictors of performance in a divided attention task

PubMed Central

Faragó, Kinga Bettina; Lőrincz, András

2018-01-01

In this study we investigate the strategies of subjects in a complex divided attention task. We conducted a series of experiments with ten participants and evaluated their performance. After an extensive analysis, we identified four strategic measures that justify the achievement of the participants, by highlighting the individual differences and predicting performance in a regression analysis using generalized estimating equations. Selecting the more urgent task and user action between multiple simultaneous possibilities form two of the strategic decisions, respectively. The third one refers to choosing a response within the same task when the opportunity is present. The fourth and most important measure of strategy involves thinking ahead and executing an action before a situation would become critical. This latter one has the effect of reducing later cognitive load or timing constraints and it is shown to explain almost as much variance in performance as the other three, more straightforward predictors together. In addition to determining these strategic predictors, we also show how manipulating task difficulty induces a shift in strategy, thus impairing human performance in the rehearsed task. The results of this study indicate that considerable differences in the divided attention ability of normal subjects can be identified early and with simple measurements. The importance of describing and analyzing strategies is also emphasized, which can substantially influence performance in complex tasks and may serve training needs. PMID:29621292

Avoiding the conflict: Metacognitive awareness drives the selection of low-demand contexts.

PubMed

Desender, Kobe; Buc Calderon, Cristian; Van Opstal, Filip; Van den Bussche, Eva

2017-07-01

Previous research attempted to explain how humans strategically adapt behavior in order to achieve successful task performance. Recently, it has been suggested that 1 potential strategy is to avoid tasks that are too demanding. Here, we report 3 experiments that investigate the empirically neglected role of metacognitive awareness in this process. In these experiments, participants could freely choose between performing a task in either a high-demand or a low-demand context. Using subliminal priming, we ensured that participants were not aware of the visual stimuli creating these different demand contexts. Our results showed that participants who noticed a difference in task difficulty (i.e., metacognitive aware participants) developed a clear preference for the low-demand context. In contrast, participants who experienced no difference in task difficulty (i.e., metacognitive unaware participants) based their choices on variables unrelated to cognitive demand (e.g., the color or location associated with a context), and did not develop a preference for the low-demand context. Crucially, this pattern was found despite identical task performance in both metacognitive awareness groups. A multiple regression approach confirmed that metacognitive awareness was the main factor driving the preference for low-demand contexts. These results argue for an important role of metacognitive awareness in the strategic avoidance of demanding tasks. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Strategic predictors of performance in a divided attention task.

PubMed

Rill, Róbert Adrian; Faragó, Kinga Bettina; Lőrincz, András

2018-01-01

In this study we investigate the strategies of subjects in a complex divided attention task. We conducted a series of experiments with ten participants and evaluated their performance. After an extensive analysis, we identified four strategic measures that justify the achievement of the participants, by highlighting the individual differences and predicting performance in a regression analysis using generalized estimating equations. Selecting the more urgent task and user action between multiple simultaneous possibilities form two of the strategic decisions, respectively. The third one refers to choosing a response within the same task when the opportunity is present. The fourth and most important measure of strategy involves thinking ahead and executing an action before a situation would become critical. This latter one has the effect of reducing later cognitive load or timing constraints and it is shown to explain almost as much variance in performance as the other three, more straightforward predictors together. In addition to determining these strategic predictors, we also show how manipulating task difficulty induces a shift in strategy, thus impairing human performance in the rehearsed task. The results of this study indicate that considerable differences in the divided attention ability of normal subjects can be identified early and with simple measurements. The importance of describing and analyzing strategies is also emphasized, which can substantially influence performance in complex tasks and may serve training needs.

Language and false belief: evidence for general, not specific, effects in cantonese-speaking preschoolers.

PubMed

Tardif, Twila; So, Catherine Wing-Chee; Kaciroti, Niko

2007-03-01

Two studies were conducted with Cantonese-speaking preschoolers examining J. de Villiers's (1995) hypothesis that syntactic complements play a unique role in the acquisition of false belief (FB). In Study 1, the authors found a positive correlation between FB and syntactic complements in 72 four- to six-year-old Cantonese-speaking preschoolers. Study 2 followed 72 three- to five-year-old Cantonese-speaking children who initially failed an FB screening task and were then tested on general language abilities, short-term memory, inhibition, nonverbal IQ, and on FB and complement tasks. Once age and initial FB understanding were controlled for in both multiple regression and hierarchical linear modeling analyses, complements no longer uniquely predicted FB. Instead, individual differences in general language abilities and short-term memory contributed to the variation in both complements and FB.

Inhibitory saccadic dysfunction is associated with cerebellar injury in multiple sclerosis.

PubMed

Kolbe, Scott C; Kilpatrick, Trevor J; Mitchell, Peter J; White, Owen; Egan, Gary F; Fielding, Joanne

2014-05-01

Cognitive dysfunction is common in patients with multiple sclerosis (MS). Saccadic eye movement paradigms such as antisaccades (AS) can sensitively interrogate cognitive function, in particular, the executive and attentional processes of response selection and inhibition. Although we have previously demonstrated significant deficits in the generation of AS in MS patients, the neuropathological changes underlying these deficits were not elucidated. In this study, 24 patients with relapsing-remitting MS underwent testing using an AS paradigm. Rank correlation and multiple regression analyses were subsequently used to determine whether AS errors in these patients were associated with: (i) neurological and radiological abnormalities, as measured by standard clinical techniques, (ii) cognitive dysfunction, and (iii) regionally specific cerebral white and gray-matter damage. Although AS error rates in MS patients did not correlate with clinical disability (using the Expanded Disability Status Score), T2 lesion load or brain parenchymal fraction, AS error rate did correlate with performance on the Paced Auditory Serial Addition Task and the Symbol Digit Modalities Test, neuropsychological tests commonly used in MS. Further, voxel-wise regression analyses revealed associations between AS errors and reduced fractional anisotropy throughout most of the cerebellum, and increased mean diffusivity in the cerebellar vermis. Region-wise regression analyses confirmed that AS errors also correlated with gray-matter atrophy in the cerebellum right VI subregion. These results support the use of the AS paradigm as a marker for cognitive dysfunction in MS and implicate structural and microstructural changes to the cerebellum as a contributing mechanism for AS deficits in these patients. Copyright © 2013 Wiley Periodicals, Inc.

Working memory span in mild cognitive impairment. Influence of processing speed and cognitive reserve.

PubMed

Facal, David; Juncos-Rabadán, Onésimo; Pereiro, Arturo X; Lojo-Seoane, Cristina

2014-04-01

Mild cognitive impairment (MCI) often includes episodic memory impairment, but can also involve other types of cognitive decline. Although previous studies have shown poorer performance of MCI patients in working memory (WM) span tasks, different MCI subgroups were not studied. In the present exploratory study, 145 participants underwent extensive cognitive evaluation, which included three different WM span tasks, and were classified into the following groups: multiple-domain amnestic MCI (mda-MCI), single-domain amnestic MCI (sda-MCI), and controls. General linear model was conducted by considering the WM span tasks as the within-subject factor; the group (mda-MCI, sda-MCI, and controls) as the inter-subject factor; and processing speed, vocabulary and age as covariates. Multiple linear regression models were also used to test the influence of processing speed, vocabulary, and other cognitive reserve (CR) proxies. Results indicate different levels of impairment of WM, with more severe impairment in mda-MCI patients. The differences were still present when processing resources and CR were controlled. Between-group differences can be understood as a manifestation of the greater severity and widespread memory impairment in mda-MCI patients and may contribute to a better understanding of continuum from normal controls to mda-MCI patients. Processing speed and CR have a limited influence on WM scores, reducing but not removing differences between groups.

Probability Theory Plus Noise: Descriptive Estimation and Inferential Judgment.

PubMed

Costello, Fintan; Watts, Paul

2018-01-01

We describe a computational model of two central aspects of people's probabilistic reasoning: descriptive probability estimation and inferential probability judgment. This model assumes that people's reasoning follows standard frequentist probability theory, but it is subject to random noise. This random noise has a regressive effect in descriptive probability estimation, moving probability estimates away from normative probabilities and toward the center of the probability scale. This random noise has an anti-regressive effect in inferential judgement, however. These regressive and anti-regressive effects explain various reliable and systematic biases seen in people's descriptive probability estimation and inferential probability judgment. This model predicts that these contrary effects will tend to cancel out in tasks that involve both descriptive estimation and inferential judgement, leading to unbiased responses in those tasks. We test this model by applying it to one such task, described by Gallistel et al. ). Participants' median responses in this task were unbiased, agreeing with normative probability theory over the full range of responses. Our model captures the pattern of unbiased responses in this task, while simultaneously explaining systematic biases away from normatively correct probabilities seen in other tasks. Copyright © 2018 Cognitive Science Society, Inc.

Lexical factors and cerebral regions influencing verbal fluency performance in MCI.

PubMed

Clark, D G; Wadley, V G; Kapur, P; DeRamus, T P; Singletary, B; Nicholas, A P; Blanton, P D; Lokken, K; Deshpande, H; Marson, D; Deutsch, G

2014-02-01

To evaluate assumptions regarding semantic (noun), verb, and letter fluency in mild cognitive impairment (MCI) and Alzheimer disease (AD) using novel techniques for measuring word similarity in fluency lists and a region of interest (ROI) analysis of gray matter correlates. Fifty-eight individuals with normal cognition (NC, n=25), MCI (n=23), or AD (n=10) underwent neuropsychological tests, including 10 verbal fluency tasks (three letter tasks [F, A, S], six noun categories [animals, water creatures, fruits and vegetables, tools, vehicles, boats], and verbs). All pairs of words generated by each participant on each task were compared in terms of semantic (meaning), orthographic (spelling), and phonemic (pronunciation) similarity. We used mixed-effects logistic regression to determine which lexical factors were predictive of word adjacency within the lists. Associations between each fluency raw score and gray matter volumes in sixteen ROIs were identified by means of multiple linear regression. We evaluated causal models for both types of analyses to specify the contributions of diagnosis and various mediator variables to the outcomes of word adjacency and fluency raw score. Semantic similarity between words emerged as the strongest predictor of word adjacency for all fluency tasks, including the letter fluency tasks. Semantic similarity mediated the effect of cognitive impairment on word adjacency only for three fluency tasks employing a biological cue. Orthographic similarity was predictive of word adjacency for the A and S tasks, while phonemic similarity was predictive only for the S task and one semantic task (vehicles). The ROI analysis revealed different patterns of correlations among the various fluency tasks, with the most common associations in the right lower temporal and bilateral dorsal frontal regions. Following correction with gray matter volumes from the opposite hemisphere, significant associations persisted for animals, vehicles, and a composite nouns score in the left inferior frontal gyrus, but for letter A, letter S, and a composite FAS score in the right inferior frontal gyrus. These regressions also revealed a lateralized association of the left subcortical nuclei with all letter fluency scores and fruits and vegetables fluency, and an association of the right lower temporal ROI with letter A, FAS, and verb fluency. Gray matter volume in several bihemispheric ROIs (left dorsal frontal, right lower temporal, right occipital, and bilateral mesial temporal) mediated the relationship between cognitive impairment and fluency for fruits and vegetables. Gray matter volume in the right lower temporal ROI mediated the relationship between cognitive impairment and five fluency raw scores (animals, fruits and vegetables, tools, verbs, and the composite nouns score). Semantic memory exerts the strongest influence on word adjacency in letter fluency as well as semantic verbal fluency tasks. Orthography is a stronger influence than pronunciation. All types of fluency task raw scores (letter, noun, and verb) correlate with cerebral regions known to support verbal or nonverbal semantic memory. The findings emphasize the contribution of right hemisphere regions to fluency task performance, particularly for verb and letter fluency. The relationship between diagnosis and semantic fluency performance is mediated by semantic similarity of words and by gray matter volume in the right lower temporal region. Published by Elsevier Ltd.

Task demand influences relationships among sex, clustering strategy, and recall: 16-word versus 9-word list learning tests.

PubMed

Sunderaraman, Preeti; Blumen, Helena M; DeMatteo, David; Apa, Zoltan L; Cosentino, Stephanie

2013-06-01

We compared the relationships among sex, clustering strategy, and recall across different task demands using the 16-word California Verbal Learning Test-Second Edition (CVLT-II) and the 9-word Philadelphia (repeatable) Verbal Learning Test (PrVLT). Women generally score higher than men on verbal memory tasks, possibly because women tend to use semantic clustering. This sex difference has been established via word-list learning tests such as the CVLT-II. In a retrospective between-group study, we compared how 2 separate groups of cognitively healthy older adults performed on a longer and a shorter verbal learning test. The group completing the CVLT-II had 36 women and 26 men; the group completing the PrVLT had 27 women and 21 men. Overall, multiple regression analyses revealed that semantic clustering was significantly associated with total recall on both tests' lists (P<0.001). Sex differences in recall and semantic clustering diminished with the shorter PrVLT word list. Semantic clustering uniquely influenced recall on both the longer and shorter word lists. However, serial clustering and sex influenced recall depending on the length of the word list (ie, the task demand). These findings suggest a complex nonlinear relationship among verbal memory, clustering strategies, and task demand.

Task Demand Influences Relationships Among Sex, Clustering Strategy, and Recall: 16-Word Versus 9-Word List Learning Tests

PubMed Central

Sunderaraman, Preeti; Blumen, Helena M.; DeMatteo, David; Apa, Zoltan; Cosentino, Stephanie

2013-01-01

Objective We compared the relationships among sex, clustering strategy, and recall across different task demands using the 16-word California Verbal Learning Test–Second Edition (CVLT-II) and the 9-word Philadelphia (repeatable) Verbal Learning Test (PrVLT). Background Women generally score higher than men on verbal memory tasks, possibly because women tend to use semantic clustering. This sex difference has been established via word-list learning tests such as the CVLT-II. Methods In a retrospective between-group study, we compared how 2 separate groups of cognitively healthy older adults performed on a longer and a shorter verbal learning test. The group completing the CVLT-II had 36 women and 26 men; the group completing the PrVLT had 27 women and 21 men. Results Overall, multiple regression analyses revealed that semantic clustering was significantly associated with total recall on both tests’ lists (P < 0.001). Sex differences in recall and semantic clustering diminished with the shorter PrVLT word list. Conclusions Semantic clustering uniquely influenced recall on both the longer and shorter word lists. However, serial clustering and sex influenced recall depending on the length of the word list (ie, the task demand). These findings suggest a complex nonlinear relationship among verbal memory, clustering strategies, and task demand. PMID:23812171

Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation.

PubMed

Peternel, Luka; Noda, Tomoyuki; Petrič, Tadej; Ude, Aleš; Morimoto, Jun; Babič, Jan

2016-01-01

In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activity is minimised. The user can then relax while the exoskeleton takes over the task execution. If the task is altered and the existing assistive behaviour becomes inadequate, the exoskeleton gradually adapts to the new task execution so that the increased muscle activity caused by the new desired task can be reduced. The advantage of the proposed method is that it does not require biomechanical or dynamical models. Our proposed learning system uses Dynamical Movement Primitives (DMPs) as a trajectory generator and parameters of DMPs are modulated using Locally Weighted Regression. Then, the learning system is combined with adaptive oscillators that determine the phase and frequency of motion according to measured Electromyography (EMG) signals. We tested the method with real robot experiments where subjects wearing an elbow exoskeleton had to move an object of an unknown mass according to a predefined reference motion. We further evaluated the proposed approach on a whole-arm exoskeleton to show that it is able to adaptively derive assistive torques even for multiple-joint motion.

Both hands at work: the effect of aging on upper-limb kinematics in a multi-step activity of daily living.

PubMed

Gulde, Philipp; Hermsdörfer, Joachim

2017-05-01

The kinematic performance of basic motor tasks shows a clear decrease with advancing age. This study examined if the rules known from such tasks can be generalized to activities of daily living. We examined the end-effector kinematics of 13 young and 13 elderly participants in the multi-step activity of daily living of tea-making. Furthermore, we analyzed bimanual behavior and hand dominance in the task using different conditions of execution. The elderly sample took substantially longer to complete the activity (almost 50%) with longer trajectories compared with the young sample. Models of multiple linear regression revealed that the longer trajectories prolonged the trial duration in both groups, and while movement speed influenced the trial duration of young participants, phases of inactivity negatively affected how long the activity took the elderly subjects. No differences were found regarding bimanual performance or hand dominance. We assume that in self-paced activities of daily living, the age-dependent differences in the kinematics are more likely to be based on the higher cognitive demands of the task rather than on pure motor capability. Furthermore, it seems that not all of the rules known from basic motor tasks can be generalized to activities of daily living.

Adaptive Control of Exoskeleton Robots for Periodic Assistive Behaviours Based on EMG Feedback Minimisation

PubMed Central

Peternel, Luka; Noda, Tomoyuki; Petrič, Tadej; Ude, Aleš; Morimoto, Jun; Babič, Jan

2016-01-01

In this paper we propose an exoskeleton control method for adaptive learning of assistive joint torque profiles in periodic tasks. We use human muscle activity as feedback to adapt the assistive joint torque behaviour in a way that the muscle activity is minimised. The user can then relax while the exoskeleton takes over the task execution. If the task is altered and the existing assistive behaviour becomes inadequate, the exoskeleton gradually adapts to the new task execution so that the increased muscle activity caused by the new desired task can be reduced. The advantage of the proposed method is that it does not require biomechanical or dynamical models. Our proposed learning system uses Dynamical Movement Primitives (DMPs) as a trajectory generator and parameters of DMPs are modulated using Locally Weighted Regression. Then, the learning system is combined with adaptive oscillators that determine the phase and frequency of motion according to measured Electromyography (EMG) signals. We tested the method with real robot experiments where subjects wearing an elbow exoskeleton had to move an object of an unknown mass according to a predefined reference motion. We further evaluated the proposed approach on a whole-arm exoskeleton to show that it is able to adaptively derive assistive torques even for multiple-joint motion. PMID:26881743

Simultaneity, Sequentiality, and Speed: Organizational Messages about Multiple-Task Completion

ERIC Educational Resources Information Center

Stephens, Keri K.; Cho, Jaehee K.; Ballard, Dawna I.

2012-01-01

Workplace norms for task completion increasingly value speed and the ability to accomplish multiple tasks at once. This study situates this popularized issue of multitasking within the context of chronemics scholarship by addressing related issues of simultaneity, sequentiality, and speed. Ultimately, we consider 2 multiple-task completion…

Interleaved Practice in Multi-Dimensional Learning Tasks: Which Dimension Should We Interleave?

ERIC Educational Resources Information Center

Rau, Martina A.; Aleven, Vincent; Rummel, Nikol

2013-01-01

Research shows that multiple representations can enhance student learning. Many curricula use multiple representations across multiple task types. The temporal sequence of representations and task types is likely to impact student learning. Research on contextual interference shows that interleaving learning tasks leads to better learning results…

Judgments of Learning are Influenced by Multiple Cues In Addition to Memory for Past Test Accuracy.

PubMed

Hertzog, Christopher; Hines, Jarrod C; Touron, Dayna R

When people try to learn new information (e.g., in a school setting), they often have multiple opportunities to study the material. One of the most important things to know is whether people adjust their study behavior on the basis of past success so as to increase their overall level of learning (for example, by emphasizing information they have not yet learned). Monitoring their learning is a key part of being able to make those kinds of adjustments. We used a recognition memory task to replicate prior research showing that memory for past test outcomes influences later monitoring, as measured by judgments of learning (JOLs; confidence that the material has been learned), but also to show that subjective confidence in whether the test answer and the amount of time taken to restudy the items also have independent effects on JOLs. We also show that there are individual differences in the effects of test accuracy and test confidence on JOLs, showing that some but not all people use past test experiences to guide monitoring of their new learning. Monitoring learning is therefore a complex process of considering multiple cues, and some people attend to those cues more effectively than others. Improving the quality of monitoring performance and learning could lead to better study behaviors and better learning. An individual's memory of past test performance (MPT) is often cited as the primary cue for judgments of learning (JOLs) following test experience during multi-trial learning tasks (Finn & Metcalfe, 2007; 2008). We used an associative recognition task to evaluate MPT-related phenomena, because performance monitoring, as measured by recognition test confidence judgments (CJs), is fallible and varies in accuracy across persons. The current study used multilevel regression models to show the simultaneous and independent influences of multiple cues on Trial 2 JOLs, in addition to performance accuracy (the typical measure of MPT in cued-recall experiments). These cues include recognition CJs, perceived recognition fluency, and Trial 2 study time allocation (an index of reprocessing fluency). Our results expand the scope of MPT-related phenomena in recognition memory testing to show independent effects of recognition test accuracy and CJs on second-trial JOLs, while also demonstrating individual differences in the effects of these cues on JOLs (as manifested in significant random effects for those regression effects in the model). The effect of study time on second-trial JOLs controlling on other variables, including Trial 1 recognition memory accuracy, also demonstrates that second-trial encoding behavior influence JOLs in addition to MPT.

The Challenge of Multiple Perspectives: Multiple Solution Tasks for Students Incorporating Diverse Tools and Representation Systems

ERIC Educational Resources Information Center

Kordaki, Maria

2015-01-01

This study focuses on the role of multiple solution tasks (MST) incorporating multiple learning tools and representation systems (MTRS) in encouraging each student to develop multiple perspectives on the learning concepts under study and creativity of thought. Specifically, two types of MST were used, namely tasks that allowed and demanded…

Intersession consistency of single-trial classification of the prefrontal response to mental arithmetic and the no-control state by NIRS.

PubMed

Power, Sarah D; Kushki, Azadeh; Chau, Tom

2012-01-01

Near-infrared spectroscopy (NIRS) has been recently investigated for use in noninvasive brain-computer interface (BCI) technologies. Previous studies have demonstrated the ability to classify patterns of neural activation associated with different mental tasks (e.g., mental arithmetic) using NIRS signals. Though these studies represent an important step towards the realization of an NIRS-BCI, there is a paucity of literature regarding the consistency of these responses, and the ability to classify them on a single-trial basis, over multiple sessions. This is important when moving out of an experimental context toward a practical system, where performance must be maintained over longer periods. When considering response consistency across sessions, two questions arise: 1) can the hemodynamic response to the activation task be distinguished from a baseline (or other task) condition, consistently across sessions, and if so, 2) are the spatiotemporal characteristics of the response which best distinguish it from the baseline (or other task) condition consistent across sessions. The answers will have implications for the viability of an NIRS-BCI system, and the design strategies (especially in terms of classifier training protocols) adopted. In this study, we investigated the consistency of classification of a mental arithmetic task and a no-control condition over five experimental sessions. Mixed model linear regression on intrasession classification accuracies indicate that the task and baseline states remain differentiable across multiple sessions, with no significant decrease in accuracy (p = 0.67). Intersession analysis, however, revealed inconsistencies in spatiotemporal response characteristics. Based on these results, we investigated several different practical classifier training protocols, including scenarios in which the training and test data come from 1) different sessions, 2) the same session, and 3) a combination of both. Results indicate that when selecting optimal classifier training protocols for NIRS-BCI, a compromise between accuracy and convenience (e.g., in terms of duration/frequency of training data collection) must be considered.

Multi-Target Regression via Robust Low-Rank Learning.

PubMed

Zhen, Xiantong; Yu, Mengyang; He, Xiaofei; Li, Shuo

2018-02-01

Multi-target regression has recently regained great popularity due to its capability of simultaneously learning multiple relevant regression tasks and its wide applications in data mining, computer vision and medical image analysis, while great challenges arise from jointly handling inter-target correlations and input-output relationships. In this paper, we propose Multi-layer Multi-target Regression (MMR) which enables simultaneously modeling intrinsic inter-target correlations and nonlinear input-output relationships in a general framework via robust low-rank learning. Specifically, the MMR can explicitly encode inter-target correlations in a structure matrix by matrix elastic nets (MEN); the MMR can work in conjunction with the kernel trick to effectively disentangle highly complex nonlinear input-output relationships; the MMR can be efficiently solved by a new alternating optimization algorithm with guaranteed convergence. The MMR leverages the strength of kernel methods for nonlinear feature learning and the structural advantage of multi-layer learning architectures for inter-target correlation modeling. More importantly, it offers a new multi-layer learning paradigm for multi-target regression which is endowed with high generality, flexibility and expressive ability. Extensive experimental evaluation on 18 diverse real-world datasets demonstrates that our MMR can achieve consistently high performance and outperforms representative state-of-the-art algorithms, which shows its great effectiveness and generality for multivariate prediction.

Regression modeling and prediction of road sweeping brush load characteristics from finite element analysis and experimental results.

PubMed

Wang, Chong; Sun, Qun; Wahab, Magd Abdel; Zhang, Xingyu; Xu, Limin

2015-09-01

Rotary cup brushes mounted on each side of a road sweeper undertake heavy debris removal tasks but the characteristics have not been well known until recently. A Finite Element (FE) model that can analyze brush deformation and predict brush characteristics have been developed to investigate the sweeping efficiency and to assist the controller design. However, the FE model requires large amount of CPU time to simulate each brush design and operating scenario, which may affect its applications in a real-time system. This study develops a mathematical regression model to summarize the FE modeled results. The complex brush load characteristic curves were statistically analyzed to quantify the effects of cross-section, length, mounting angle, displacement and rotational speed etc. The data were then fitted by a multiple variable regression model using the maximum likelihood method. The fitted results showed good agreement with the FE analysis results and experimental results, suggesting that the mathematical regression model may be directly used in a real-time system to predict characteristics of different brushes under varying operating conditions. The methodology may also be used in the design and optimization of rotary brush tools. Copyright © 2015 Elsevier Ltd. All rights reserved.

Managing Multiple Tasks in Complex, Dynamic Environments

NASA Technical Reports Server (NTRS)

Freed, Michael; Null, Cynthia H. (Technical Monitor)

1998-01-01

Sketchy planners are designed to achieve goals in realistically complex, time-pressured, and uncertain task environments. However, the ability to manage multiple, potentially interacting tasks in such environments requires extensions to the functionality these systems typically provide. This paper identifies a number of factors affecting how interacting tasks should be prioritized, interrupted, and resumed, and then describes a sketchy planner called APEX that takes account of these factors when managing multiple tasks.

Common limbic and frontal-striatal disturbances in patients with obsessive compulsive disorder, panic disorder and hypochondriasis.

PubMed

van den Heuvel, O A; Mataix-Cols, D; Zwitser, G; Cath, D C; van der Werf, Y D; Groenewegen, H J; van Balkom, A J L M; Veltman, D J

2011-11-01

Direct comparisons of brain function between obsessive compulsive disorder (OCD) and other anxiety or OCD spectrum disorders are rare. This study aimed to investigate the specificity of altered frontal-striatal and limbic activations during planning in OCD, a prototypical anxiety disorder (panic disorder) and a putative OCD spectrum disorder (hypochondriasis). The Tower of London task, a 'frontal-striatal' task, was used during functional magnetic resonance imaging measurements in 50 unmedicated patients, diagnosed with OCD (n=22), panic disorder (n=14) or hypochondriasis (n=14), and in 22 healthy subjects. Blood oxygen level-dependent (BOLD) signal changes were calculated for contrasts of interest (planning versus baseline and task load effects). Moreover, correlations between BOLD responses and both task performance and state anxiety were analysed. Overall, patients showed a decreased recruitment of the precuneus, caudate nucleus, globus pallidus and thalamus, compared with healthy controls. There were no statistically significant differences in brain activation between the three patient groups. State anxiety was negatively correlated with dorsal frontal-striatal activation. Task performance was positively correlated with dorsal frontal-striatal recruitment and negatively correlated with limbic and ventral frontal-striatal recruitment. Multiple regression models showed that adequate task performance was best explained by independent contributions from dorsolateral prefrontal cortex (positive correlation) and amygdala (negative correlation), even after controlling for state anxiety. Patients with OCD, panic disorder and hypochondriasis share similar alterations in frontal-striatal brain regions during a planning task, presumably partly related to increased limbic activation.

Musculoskeletal disorders among workers in plastic manufacturing plants.

PubMed

Fernandes, Rita de Cássia Pereira; Assunção, Ada Avila; Silvany Neto, Annibal Muniz; Carvalho, Fernando Martins

2010-03-01

Epidemiological studies have indicated an association between musculoskeletal disorders (MSDs) and physical work demands. Psychosocial work demands have also been identified as possible risk factors, but findings have been inconsistent. To evaluate factors associated with upper back, neck and upper limb MSD among workers from 14 plastic manufacturing companies located in the city of Salvador, Brazil. A cross-sectional study design was used to survey a stratified proportional random sample of 577 workers. Data were collected by questionnaire interviews. Factor analysis was carried out on 11 physical demands variables. Psychosocial work demands were measured by demand, control and social support questions. The role of socio-demographic factors, lifestyle and household tasks was also examined. Multiple logistic regression was used to identify factors related to upper back, neck and upper limb MSDs. Results from multiple logistic regression showed that distal upper limb MSDs were related to manual handling, work repetitiveness, psychosocial demands, job dissatisfaction, and gender. Neck, shoulder or upper back MSDs were related to manual handling, work repetitiveness, psychosocial demands, job dissatisfaction, and physical unfitness. Reducing the prevalence of musculoskeletal disorders requires: improving the work environment, reducing biomechanical risk factors, and replanning work organization. Programs must also be aware of gender specificities related to MSDs.

Writing Forces Associated With Four Pencil Grasp Patterns in Grade 4 Children

PubMed Central

Schwellnus, Heidi; Carnahan, Heather; Kushki, Azadeh; Polatajko, Helene; Missiuna, Cheryl

2013-01-01

OBJECTIVE. We investigated differences in handwriting kinetics, speed, and legibility among four pencil grasps after a 10-min copy task. METHOD. Seventy-four Grade 4 students completed a handwriting assessment before and after a copy task. Grip and axial forces were measured with an instrumented stylus and force-sensitive tablet. We used multiple linear regression to analyze the relationship between grasp pattern and grip and axial forces. RESULTS. We found no kinetic differences among grasps, whether considered individually or grouped by the number of fingers on the barrel. However, when grasps were grouped according to the thumb position, the adducted grasps exhibited higher mean grip and axial forces. CONCLUSION. Grip forces were generally similar across the different grasps. Kinetic differences resulting from thumb position seemed to have no bearing on speed and legibility. Interventions for handwriting difficulties should focus more on speed and letter formation than on grasp pattern. PMID:23433277

Conveying the concept of movement in music: An event-related brain potential study.

PubMed

Zhou, Linshu; Jiang, Cunmei; Wu, Yingying; Yang, Yufang

2015-10-01

This study on event-related brain potential investigated whether music can convey the concept of movement. Using a semantic priming paradigm, natural musical excerpts were presented to non-musicians, followed by semantically congruent or incongruent pictures that depicted objects either in motion or at rest. The priming effects were tested in object decision and implicit recognition tasks to distinguish the effects of automatic conceptual activation from response competition. Results showed that in both tasks, pictures that were incongruent to preceding musical excerpts elicited larger N400 than congruent pictures, suggesting that music can prime the representations of movement concepts. Results of the multiple regression analysis showed that movement expression could be well predicted by specific acoustic and musical features, indicating the associations between music per se and the processing of iconic musical meaning. Copyright © 2015 Elsevier Ltd. All rights reserved.

Nurse practitioners: leadership behaviors and organizational climate.

PubMed

Jones, L C; Guberski, T D; Soeken, K L

1990-01-01

The purpose of this article is to examine the relationships of individual nurse practitioners' perceptions of the leadership climate in their organizations and self-reported formal and informal leadership behaviors. The nine climate dimensions (Structure, Responsibility, Reward, Perceived Support of Risk Taking, Warmth, Support, Standard Setting, Conflict, and Identity) identified by Litwin and Stringer in 1968 were used to predict five leadership dimensions (Meeting Organizational Needs, Managing Resources, Leadership Competence, Task Accomplishment, and Communications). Demographic variables of age, educational level, and percent of time spent performing administrative functions were forced as a first step in each multiple regression analysis and used to explain a significant amount of variance in all but one analysis. All leadership dimensions were predicted by at least one organizational climate dimension: (1) Meeting Organizational Needs by Risk and Reward; (2) Managing Resources by Risk and Structure; (3) Leadership Competence by Risk and Standards; (4) Task Accomplishment by Structure, Risk, and Standards; and (5) Communication by Rewards.

Effect of pencil grasp on the speed and legibility of handwriting in children.

PubMed

Schwellnus, Heidi; Carnahan, Heather; Kushki, Azadeh; Polatajko, Helene; Missiuna, Cheryl; Chau, Tom

2012-01-01

Pencil grasps other than the dynamic tripod may be functional for handwriting. This study examined the impact of grasp on handwriting speed and legibility. We videotaped 120 typically developing fourth-grade students while they performed a writing task. We categorized the grasps they used and evaluated their writing for speed and legibility using a handwriting assessment. Using linear regression analysis, we examined the relationship between grasp and handwriting. We documented six categories of pencil grasp: four mature grasp patterns, one immature grasp pattern, and one alternating grasp pattern. Multiple linear regression results revealed no significant effect for mature grasp on either legibility or speed. Pencil grasp patterns did not influence handwriting speed or legibility in this sample of typically developing children. This finding adds to the mounting body of evidence that alternative grasps may be acceptable for fast and legible handwriting. Copyright © 2012 by the American Occupational Therapy Association, Inc.

Factors Affecting Employment Among Informal Caregivers Assisting People with Multiple Sclerosis

PubMed Central

Huang, Chunfeng; Zheng, Zhida

2013-01-01

The objective of this study was to identify characteristics of informal caregivers, caregiving, and the people with multiple sclerosis (MS) receiving assistance that are associated with reduced caregiver employment. Data were collected during telephone interviews with 530 MS caregivers, including 215 employed caregivers, with these survey data analyzed using logistic regression. Poorer cognitive ability by the care recipient to make decisions about daily tasks and more caregiving hours per week predicted reduced caregiver employment. Better physical health domains of caregiver quality of life were associated with significantly lower odds of reduced employment. Health professionals treating informal caregivers, as well as those treating people with MS, need to be aware of respite, support, and intervention programs available to MS caregivers and refer them to these programs, which could reduce the negative impact of caregiving on employment. PMID:24453784

An Occupational Performance Test Validation Program for Fire Fighters at the Kennedy Space Center

NASA Technical Reports Server (NTRS)

Schonfeld, Brian R.; Doerr, Donald F.; Convertino, Victor A.

1990-01-01

We evaluated performance of a modified Combat Task Test (CTT) and of standard fitness tests in 20 male subjects to assess the prediction of occupational performance standards for Kennedy Space Center fire fighters. The CTT consisted of stair-climbing, a chopping simulation, and a victim rescue simulation. Average CTT performance time was 3.61 +/- 0.25 min (SEM) and all CTT tasks required 93% to 97% maximal heart rate. By using scores from the standard fitness tests, a multiple linear regression model was fitted to each parameter: the stairclimb (r(exp 2) = .905, P less than .05), the chopping performance time (r(exp 2) = .582, P less than .05), the victim rescue time (r(exp 2) = .218, P = not significant), and the total performance time (r(exp 2) = .769, P less than .05). Treadmill time was the predominant variable, being the major predictor in two of four models. These results indicated that standardized fitness tests can predict performance on some CTT tasks and that test predictors were amenable to exercise training.

Schizotypy and Performance on an Insight Problem-Solving Task: The Contribution of Persecutory Ideation.

PubMed

Cosgrave, Jan; Haines, Ross; Golodetz, Stuart; Claridge, Gordon; Wulff, Katharina; van Heugten-van der Kloet, Dalena

2018-01-01

Insight problem solving is thought to underpin creative thought as it incorporates both divergent (generating multiple ideas and solutions) and convergent (arriving at the optimal solution) thinking approaches. The current literature on schizotypy and creativity is mixed and requires clarification. An alternate approach was employed by designing an exploratory web-based study using only correlates of schizotypal traits (paranoia, dissociation, cognitive failures, fantasy proneness, and unusual sleep experiences) and examining which (if any) predicted optimal performance on an insight problem-solving task. One hundred and twenty-one participants were recruited online from the general population and completed the number reduction task. The discovery of the hidden rule (HR) was used as a measure of insight. Multivariate logistic regression analyses highlighted persecutory ideation to best predict the discovery of the HR (OR = 1.05; 95% CI 1.01-1.10, p = 0.017), with a one-point increase in persecutory ideas corresponding to the participant being 5% more likely to discover the HR. This result suggests that persecutory ideation, above other schizotypy correlates, may be involved in insight problem solving.

Neuropsychological correlates of sustained attention in schizophrenia.

PubMed

Chen, E Y; Lam, L C; Chen, R Y; Nguyen, D G; Chan, C K; Wilkins, A J

1997-04-11

We employed a simple and relatively undemanding task of monotone counting for the assessment of sustained attention in schizophrenic patients. The monotone counting task has been validated neuropsychologically and is particularly sensitive to right prefrontal lesions. We compared the performance of schizophrenic patients with age- and education-matched controls. We then explored the extent to which a range of commonly employed neuropsychological tasks in schizophrenia research are related to attentional impairment as measured in this way. Monotone counting performance was found to be correlated with digit span (WAIS-R-HK), information (WAIS-R-HK), comprehension (WAIS-R-HK), logical memory (immediate recall) (Weschler Memory Scale, WMS), and visual reproduction (WMS). Multiple regression analysis also identified visual reproduction, digit span and comprehension as significant predictors of attention performance. In contrast, logical memory (delay recall) (WMS), similarity (WAIS-R-HK), semantic fluency, and Wisconsin Card Sorting Test (perseverative errors) were not correlated with attention. In addition, no significant correlation between sustained attention and symptoms was found. These findings are discussed in the context of a weakly modular cognitive system where attentional impairment may contribute selectively to a range of other cognitive deficits.

Evaluation of Relationship between Trunk Muscle Endurance and Static Balance in Male Students

PubMed Central

Barati, Amirhossein; SafarCherati, Afsaneh; Aghayari, Azar; Azizi, Faeze; Abbasi, Hamed

2013-01-01

Purpose Fatigue of trunk muscle contributes to spinal instability over strenuous and prolonged physical tasks and therefore may lead to injury, however from a performance perspective, relation between endurance efficient core muscles and optimal balance control has not been well-known. The purpose of this study was to examine the relationship of trunk muscle endurance and static balance. Methods Fifty male students inhabitant of Tehran university dormitory (age 23.9±2.4, height 173.0±4.5 weight 70.7±6.3) took part in the study. Trunk muscle endurance was assessed using Sørensen test of trunk extensor endurance, trunk flexor endurance test, side bridge endurance test and static balance was measured using single-limb stance test. A multiple linear regression analysis was applied to test if the trunk muscle endurance measures significantly predicted the static balance. Results There were positive correlations between static balance level and trunk flexor, extensor and lateral endurance measures (Pearson correlation test, r=0.80 and P<0.001; r=0.71 and P<0.001; r=0.84 and P<0.001, respectively). According to multiple regression analysis for variables predicting static balance, the linear combination of trunk muscle endurance measures was significantly related to the static balance (F (3,46) = 66.60, P<0.001). Endurance of trunk flexor, extensor and lateral muscles were significantly associated with the static balance level. The regression model which included these factors had the sample multiple correlation coefficient of 0.902, indicating that approximately 81% of the variance of the static balance is explained by the model. Conclusion There is a significant relationship between trunk muscle endurance and static balance. PMID:24800004

Olfaction Is Related to Motor Function in Older Adults.

PubMed

Tian, Qu; Resnick, Susan M; Studenski, Stephanie A

2017-08-01

Among older adults, both olfaction and motor function predict future cognitive decline and dementia, suggesting potential shared causal pathways. However, it is not known whether olfactory and motor function are independently related in late life. We assessed cross-sectional associations of olfaction with motor and cognitive function, using concurrent data on olfactory function, mobility, balance, fine motor function, manual dexterity, and cognition in 163 Baltimore Longitudinal Study of Aging participants aged 60 and older without common neurological diseases (n = 114 with available cognitive data). Using multiple linear regression, we adjusted for age, sex, race, smoking history, height, and weight for mobility and balance, and education for cognition. We used multiple linear regression to test whether olfaction-motor associations were independent of cognition and depressive symptoms. Olfactory scores were significantly associated with mobility (usual gait speed, rapid gait speed, 400-m walk time, and Health ABC Physical Performance Battery score), balance, fine motor function, and manual dexterity (all p < .05). In those with available cognitive data, additional adjustment for depressive symptoms, verbal memory, or visuoperceptual speed demonstrated especially strong independent relationships with challenging motor tasks such as 400-m walk and nondominant hand manual dexterity (p < .005). This study demonstrates for the first time that, in older adults, olfactory function is associated with mobility, balance, fine motor function, and manual dexterity, and independent of cognitive function, with challenging upper and lower extremity motor function tasks. Longitudinal studies are needed to determine if olfactory performance predicts future mobility and functional decline. Published by Oxford University Press on behalf of The Gerontological Society of America 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

The effect of amblyopia on fine motor skills in children.

PubMed

Webber, Ann L; Wood, Joanne M; Gole, Glen A; Brown, Brian

2008-02-01

In an investigation of the functional impact of amblyopia in children, the fine motor skills of amblyopes and age-matched control subjects were compared. The influence of visual factors that might predict any decrement in fine motor skills was also explored. Vision and fine motor skills were tested in a group of children (n = 82; mean age, 8.2 +/- 1.7 [SD] years) with amblyopia of different causes (infantile esotropia, n = 17; acquired strabismus, n = 28; anisometropia, n = 15; mixed, n = 13; and deprivation n = 9), and age-matched control children (n = 37; age 8.3 +/- 1.3 years). Visual motor control (VMC) and upper limb speed and dexterity (ULSD) items of the Bruininks-Oseretsky Test of Motor Proficiency were assessed, and logMAR visual acuity (VA) and Randot stereopsis were measured. Multiple regression models were used to identify the visual determinants of fine motor skills performance. Amblyopes performed significantly poorer than control subjects on 9 of 16 fine motor skills subitems and for the overall age-standardized scores for both VMC and ULSD items (P < 0.05). The effects were most evident on timed tasks. The etiology of amblyopia and level of binocular function significantly affected fine motor skill performance on both items; however, when examined in a multiple regression model that took into account the intercorrelation between visual characteristics, poorer fine motor skills performance was associated with strabismus (F(1,75) = 5.428; P = 0.022), but not with the level of binocular function, refractive error, or visual acuity in either eye. Fine motor skills were reduced in children with amblyopia, particularly those with strabismus, compared with control subjects. The deficits in motor performance were greatest on manual dexterity tasks requiring speed and accuracy.

Comparing auditory filter bandwidths, spectral ripple modulation detection, spectral ripple discrimination, and speech recognition: Normal and impaired hearinga)

PubMed Central

Davies-Venn, Evelyn; Nelson, Peggy; Souza, Pamela

2015-01-01

Some listeners with hearing loss show poor speech recognition scores in spite of using amplification that optimizes audibility. Beyond audibility, studies have suggested that suprathreshold abilities such as spectral and temporal processing may explain differences in amplified speech recognition scores. A variety of different methods has been used to measure spectral processing. However, the relationship between spectral processing and speech recognition is still inconclusive. This study evaluated the relationship between spectral processing and speech recognition in listeners with normal hearing and with hearing loss. Narrowband spectral resolution was assessed using auditory filter bandwidths estimated from simultaneous notched-noise masking. Broadband spectral processing was measured using the spectral ripple discrimination (SRD) task and the spectral ripple depth detection (SMD) task. Three different measures were used to assess unamplified and amplified speech recognition in quiet and noise. Stepwise multiple linear regression revealed that SMD at 2.0 cycles per octave (cpo) significantly predicted speech scores for amplified and unamplified speech in quiet and noise. Commonality analyses revealed that SMD at 2.0 cpo combined with SRD and equivalent rectangular bandwidth measures to explain most of the variance captured by the regression model. Results suggest that SMD and SRD may be promising clinical tools for diagnostic evaluation and predicting amplification outcomes. PMID:26233047

Comparing auditory filter bandwidths, spectral ripple modulation detection, spectral ripple discrimination, and speech recognition: Normal and impaired hearing.

PubMed

Davies-Venn, Evelyn; Nelson, Peggy; Souza, Pamela

2015-07-01

Some listeners with hearing loss show poor speech recognition scores in spite of using amplification that optimizes audibility. Beyond audibility, studies have suggested that suprathreshold abilities such as spectral and temporal processing may explain differences in amplified speech recognition scores. A variety of different methods has been used to measure spectral processing. However, the relationship between spectral processing and speech recognition is still inconclusive. This study evaluated the relationship between spectral processing and speech recognition in listeners with normal hearing and with hearing loss. Narrowband spectral resolution was assessed using auditory filter bandwidths estimated from simultaneous notched-noise masking. Broadband spectral processing was measured using the spectral ripple discrimination (SRD) task and the spectral ripple depth detection (SMD) task. Three different measures were used to assess unamplified and amplified speech recognition in quiet and noise. Stepwise multiple linear regression revealed that SMD at 2.0 cycles per octave (cpo) significantly predicted speech scores for amplified and unamplified speech in quiet and noise. Commonality analyses revealed that SMD at 2.0 cpo combined with SRD and equivalent rectangular bandwidth measures to explain most of the variance captured by the regression model. Results suggest that SMD and SRD may be promising clinical tools for diagnostic evaluation and predicting amplification outcomes.

Leadership = Communication? The Relations of Leaders' Communication Styles with Leadership Styles, Knowledge Sharing and Leadership Outcomes.

PubMed

de Vries, Reinout E; Bakker-Pieper, Angelique; Oostenveld, Wyneke

2010-09-01

PURPOSE: The purpose of this study was to investigate the relations between leaders' communication styles and charismatic leadership, human-oriented leadership (leader's consideration), task-oriented leadership (leader's initiating structure), and leadership outcomes. METHODOLOGY: A survey was conducted among 279 employees of a governmental organization. The following six main communication styles were operationalized: verbal aggressiveness, expressiveness, preciseness, assuredness, supportiveness, and argumentativeness. Regression analyses were employed to test three main hypotheses. FINDINGS: In line with expectations, the study showed that charismatic and human-oriented leadership are mainly communicative, while task-oriented leadership is significantly less communicative. The communication styles were strongly and differentially related to knowledge sharing behaviors, perceived leader performance, satisfaction with the leader, and subordinate's team commitment. Multiple regression analyses showed that the leadership styles mediated the relations between the communication styles and leadership outcomes. However, leader's preciseness explained variance in perceived leader performance and satisfaction with the leader above and beyond the leadership style variables. IMPLICATIONS: This study offers potentially invaluable input for leadership training programs by showing the importance of leader's supportiveness, assuredness, and preciseness when communicating with subordinates. ORIGINALITY/VALUE: Although one of the core elements of leadership is interpersonal communication, this study is one of the first to use a comprehensive communication styles instrument in the study of leadership.

Commentary on the statistical properties of noise and its implication on general linear models in functional near-infrared spectroscopy.

PubMed

Huppert, Theodore J

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low levels of light to measure changes in cerebral blood oxygenation levels. In the majority of NIRS functional brain studies, analysis of this data is based on a statistical comparison of hemodynamic levels between a baseline and task or between multiple task conditions by means of a linear regression model: the so-called general linear model. Although these methods are similar to their implementation in other fields, particularly for functional magnetic resonance imaging, the specific application of these methods in fNIRS research differs in several key ways related to the sources of noise and artifacts unique to fNIRS. In this brief communication, we discuss the application of linear regression models in fNIRS and the modifications needed to generalize these models in order to deal with structured (colored) noise due to systemic physiology and noise heteroscedasticity due to motion artifacts. The objective of this work is to present an overview of these noise properties in the context of the linear model as it applies to fNIRS data. This work is aimed at explaining these mathematical issues to the general fNIRS experimental researcher but is not intended to be a complete mathematical treatment of these concepts.

Nonparametric methods for drought severity estimation at ungauged sites

NASA Astrophysics Data System (ADS)

Sadri, S.; Burn, D. H.

2012-12-01

The objective in frequency analysis is, given extreme events such as drought severity or duration, to estimate the relationship between that event and the associated return periods at a catchment. Neural networks and other artificial intelligence approaches in function estimation and regression analysis are relatively new techniques in engineering, providing an attractive alternative to traditional statistical models. There are, however, few applications of neural networks and support vector machines in the area of severity quantile estimation for drought frequency analysis. In this paper, we compare three methods for this task: multiple linear regression, radial basis function neural networks, and least squares support vector regression (LS-SVR). The area selected for this study includes 32 catchments in the Canadian Prairies. From each catchment drought severities are extracted and fitted to a Pearson type III distribution, which act as observed values. For each method-duration pair, we use a jackknife algorithm to produce estimated values at each site. The results from these three approaches are compared and analyzed, and it is found that LS-SVR provides the best quantile estimates and extrapolating capacity.

Effects of method and format on subjects' responses to a control of variables reasoning problem

NASA Astrophysics Data System (ADS)

Staver, John R.

Excessive time and training demands have rendered Piaget's clinical method of reasoning assessment impractical for researchers and science teachers who work with large numbers of students. The published literature[Note ][See: Lawson, A. E. Journal of Research in Science Teaching, 1978, 15(1), 11-24; Shayer, M., Adey, P., & Wylam, H. Journal of Research in Science Teaching, 1981, 18(2), 157-168; Staver, J. R., & Gabel, D. L. Journal of Research in Science Teaching, 1979, 16(6), 534-544; Tobin, K. G., & Capie, W. Educational and Psychological Measurement, 1981, 41(2), 413-424.] indicates that reliable, valid alternatives to clinical assessment are feasible. However, the overestimate/underestimate of reasoning for different methods and formats remains unresolved through research. The objective of this study was to determine the effects of various methods and formats on subjects' responses to a Piagetian reasoning problem requiring control of variables. The task chosen for this investigation was the Mealworm problem.[Note ][See: Karplus, R., Lawson, A., Wollman, W., Appel, M., Bernoff, R., Howe, A., Rusch, J., & Sullivan, F. Science teaching and the development of reasoning. Berkeley, CA: University of California, 1977.] The task was presented by three methods: (1) individual clinical interview; (2) group presentation of task followed by paper-and-pencil problem with illustration; and (3) group administration of paper-and-pencil instrument with illustration. Each method included four formats: (1) completion answer with essay justification; (2) completion answer with multiplechoice justification; (3) multiple-choice answer with essay justification; and (4) multiple-choice answer with multiple-choice justification. Two hundred and fifty-three (253) students who were enrolled in a freshman level biological science class participated in the study. The research design was a 3 × 4 factorial design with method and format of assessment as the main effects. The participants were in 12 randomly selected laboratory or discussion sections, and each section was randomly assigned to a cell in the research design. Regression analysis with the individual as the unit of analysis showed that format but not method of assessment accounted for a significant amount of variance in student performance. The overall interaction was nonsignificant. Regression analysis with sections as the unit of analysis revealed nonsignificant findings for both method and format. The interrater agreement in the scoring of the Mealworm task was 82.1%. The principal conclusion is that format but not method of task administration influenced the performance of subjects, and the influence is similar for various combinations of method and format. Discussion is focused on the relative importance of the nonsignificant and significant findings for using alternative methods of Piagetian assessment. The results are also discussed with respect to earlier work, and suggestions for future research as well as implications for teachers are set forth.

Physiological Aging Influence on Brain Hemodynamic Activity during Task-Switching: A fNIRS Study.

PubMed

Vasta, Roberta; Cutini, Simone; Cerasa, Antonio; Gramigna, Vera; Olivadese, Giuseppe; Arabia, Gennarina; Quattrone, Aldo

2017-01-01

Task-switching (TS) paradigm is a well-known validated tool useful for exploring the neural substrates of cognitive control, in particular the activity of the lateral and medial prefrontal cortex. This work is aimed at investigating how physiological aging influences hemodynamic response during the execution of a color-shape TS paradigm. A multi-channel near infrared spectroscopy (fNIRS) was used to measure hemodynamic activity in 27 young (30.00 ± 7.90 years) and 11 elderly participants (57.18 ± 9.29 years) healthy volunteers (55% male, age range: (19-69) years) during the execution of a TS paradigm. Two holders were placed symmetrically over the left/right hemispheres to record cortical activity [oxy-(HbO) and deoxy-hemoglobin (HbR) concentration] of the dorso-lateral prefrontal cortex (DLPFC), the dorsal premotor cortex (PMC), and the dorso-medial part of the superior frontal gyrus (sFG). TS paradigm requires participants to repeat the same task over a variable number of trials, and then to switch to a different task during the trial sequence. A two-sample t -test was carried out to detect differences in cortical responses between groups. Multiple linear regression analysis was used to evaluate the impact of age on the prefrontal neural activity. Elderly participants were significantly slower than young participants in both color- ( p < 0.01, t = -3.67) and shape-single tasks ( p = 0.026, t = -2.54) as well as switching ( p = 0.026, t = -2.41) and repetition trials ( p = 0.012, t = -2.80). Differences in cortical activation between groups were revealed for HbO mean concentration of switching task in the PMC ( p = 0.048, t = 2.94). In the whole group, significant increases of behavioral performance were detected in switching trials, which positively correlated with aging. Multivariate regression analysis revealed that the HbO mean concentration of switching task in the PMC ( p = 0.01, β = -0.321) and of shape single-task in the sFG ( p = 0.003, β = 0.342) were the best predictors of age effects. Our findings demonstrated that TS might be a reliable instrument to gather a measure of cognitive resources in older people. Moreover, the fNIRS-related brain activity extracted from frontoparietal cortex might become a useful indicator of aging effects.

A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

NASA Astrophysics Data System (ADS)

Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan

2018-04-01

In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.

Visual processing of multiple elements in the dyslexic brain: evidence for a superior parietal dysfunction

PubMed Central

Lobier, Muriel A.; Peyrin, Carole; Pichat, Cédric; Le Bas, Jean-François; Valdois, Sylviane

2014-01-01

The visual attention (VA) span deficit hypothesis of developmental dyslexia posits that impaired multiple element processing can be responsible for poor reading outcomes. In VA span impaired dyslexic children, poor performance on letter report tasks is associated with reduced parietal activations for multiple letter processing. While this hints towards a non-specific, attention-based dysfunction, it is still unclear whether reduced parietal activity generalizes to other types of stimuli. Furthermore, putative links between reduced parietal activity and reduced ventral occipito-temporal (vOT) in dyslexia have yet to be explored. Using functional magnetic resonance imaging, we measured brain activity in 12 VA span impaired dyslexic adults and 12 adult skilled readers while they carried out a categorization task on single or multiple alphanumeric or non-alphanumeric characters. While healthy readers activated parietal areas more strongly for multiple than single element processing (right-sided for alphanumeric and bilateral for non-alphanumeric), similar stronger multiple element right parietal activations were absent for dyslexic participants. Contrasts between skilled and dyslexic readers revealed significantly reduced right superior parietal lobule (SPL) activity for dyslexic readers regardless of stimuli type. Using a priori anatomically defined regions of interest, we showed that neural activity was reduced for dyslexic participants in both SPL and vOT bilaterally. Finally, we used multiple regressions to test whether SPL activity was related to vOT activity in each group. In the left hemisphere, SPL activity covaried with vOT activity for both normal and dyslexic readers. In contrast, in the right hemisphere, SPL activity covaried with vOT activity only for dyslexic readers. These results bring critical support to the VA interpretation of the VA Span deficit. In addition, they offer a new insight on how deficits in automatic vOT based word recognition could arise in developmental dyslexia. PMID:25071509

Distinguishing Schemes and Tasks in Children's Development of Multiplicative Reasoning

ERIC Educational Resources Information Center

Tzur, Ron; Johnson, Heather L.; McClintock, Evan; Kenney, Rachael H.; Xin, Yan P.; Si, Luo; Woordward, Jerry; Hord, Casey; Jin, Xianyan

2013-01-01

We present a synthesis of findings from constructivist teaching experiments regarding six schemes children construct for reasoning multiplicatively and tasks to promote them. We provide a task-generating platform game, depictions of each scheme, and supporting tasks. Tasks must be distinguished from children's thinking, and learning situations…

Effect of pencil grasp on the speed and legibility of handwriting after a 10-minute copy task in Grade 4 children.

PubMed

Schwellnus, Heidi; Carnahan, Heather; Kushki, Azadeh; Polatajko, Helene; Missiuna, Cheryl; Chau, Tom

2012-06-01

To investigate the impact of common pencil grasp patterns on the speed and legibility of handwriting after a 10-minute copy task, intended to induce muscle fatigue, in typically developing children and in those non-proficient in handwriting. A total of 120 Grade 4 students completed a standardised handwriting assessment before and after a 10-minute copy task. The students indicated the perceived difficulty of the handwriting task at baseline and after 10 minutes. The students also completed a self-report questionnaire regarding their handwriting proficiency upon completion. The majority of the students rated higher effort after the 10-minute copy task than at baseline (rank sum: P = 0.00001). The effort ratings were similar for the different grasp patterns (multiple linear regression: F = 0.37, P = 0.895). For both typically developing children and those with handwriting issues, the legibility of the writing samples decreased after the 10-minute copy task but the speed of writing increased. CONCLUSIONS AND SIGNIFICANCE OF THE STUDY: The quality of the handwriting decreased after the 10-minute copy task; however, there was no difference in the quality or speed scores among the different pencil grasps before and after the copy task. The dynamic tripod pencil grasp did not offer any advantage over the lateral tripod or the dynamic or lateral quadrupod pencil grasps in terms of quality of handwriting after a 10-minute copy task. These four pencil grasp patterns performed equivalently. Our findings question the practice of having students adopt the dynamic tripod pencil grasp. © 2012 The Authors Australian Occupational Therapy Journal © 2012 Occupational Therapy Australia.

Application of Multi-task Sparse Lasso Feature Extraction and Support Vector Machine Regression in the Stellar Atmospheric Parameterization

NASA Astrophysics Data System (ADS)

Gao, Wei; Li, Xiang-ru

2017-07-01

The multi-task learning takes the multiple tasks together to make analysis and calculation, so as to dig out the correlations among them, and therefore to improve the accuracy of the analyzed results. This kind of methods have been widely applied to the machine learning, pattern recognition, computer vision, and other related fields. This paper investigates the application of multi-task learning in estimating the stellar atmospheric parameters, including the surface temperature (Teff), surface gravitational acceleration (lg g), and chemical abundance ([Fe/H]). Firstly, the spectral features of the three stellar atmospheric parameters are extracted by using the multi-task sparse group Lasso algorithm, then the support vector machine is used to estimate the atmospheric physical parameters. The proposed scheme is evaluated on both the Sloan stellar spectra and the theoretical spectra computed from the Kurucz's New Opacity Distribution Function (NEWODF) model. The mean absolute errors (MAEs) on the Sloan spectra are: 0.0064 for lg (Teff /K), 0.1622 for lg (g/(cm · s-2)), and 0.1221 dex for [Fe/H]; the MAEs on the synthetic spectra are 0.0006 for lg (Teff /K), 0.0098 for lg (g/(cm · s-2)), and 0.0082 dex for [Fe/H]. Experimental results show that the proposed scheme has a rather high accuracy for the estimation of stellar atmospheric parameters.

Self-determination and goal orientation in track and field.

PubMed

Chin, Ngien-Siong; Khoo, Selina; Low, Wah-Yun

2012-06-01

This study investigated gender, age group and locality differences in adolescent athletes' self-determination motivation and goal orientations in track and field. It also examined the relationship between the self-determination theory and achievement goal theory. A total of 632 (349 boys, 283 girls) adolescent athletes (aged 13-18 years) completed the Sports Motivation Scale and Task and Ego Orientation in Sport Questionnaire. Results indicated significant differences between gender on intrinsic motivation, extrinsic motivation, amotivation (t(630) = 4.10, p < 0.05) and ego orientation (t(630) = 2.48, p < 0.05). Male students reported higher intrinsic motivation, extrinsic motivation, amotivation and ego orientation. A significant difference was found between age groups on task orientation (t(630) = 1.94, p < 0.05) and locality on ego orientation (t(630) = 1.94, p < 0.05). Older athletes showed significantly higher task orientation. Rural athletes had higher ego orientation whereas urban athletes have higher intrinsic motivation. Task orientation was related to intrinsic motivation (r = 0.55, p < 0.01), extrinsic motivation (r = 0.55, p < 0.01), but weakly related to amotivation (r = 0.10, p < 0.01). Ego orientation was related to intrinsic motivation (r = 0.30, p < 0.01), extrinsic motivation (r = 0.36, p < 0.01) and amotivaion (r = 0.36, p < 0.01). Task orientation was related to ego orientation (r = 0.29, p < 0.01). Multiple regression analysis showed intrinsic motivation, extrinsic motivation and amotivation accounted for 30.5% of the variances in task orientation.

Self-Determination and Goal Orientation in Track and Field

PubMed Central

Chin, Ngien-Siong; Khoo, Selina; Low, Wah-Yun

2012-01-01

This study investigated gender, age group and locality differences in adolescent athletes’ self-determination motivation and goal orientations in track and field. It also examined the relationship between the self-determination theory and achievement goal theory. A total of 632 (349 boys, 283 girls) adolescent athletes (aged 13–18 years) completed the Sports Motivation Scale and Task and Ego Orientation in Sport Questionnaire. Results indicated significant differences between gender on intrinsic motivation, extrinsic motivation, amotivation (t(630) = 4.10, p < 0.05) and ego orientation (t(630) = 2.48, p < 0.05). Male students reported higher intrinsic motivation, extrinsic motivation, amotivation and ego orientation. A significant difference was found between age groups on task orientation (t(630) = 1.94, p < 0.05) and locality on ego orientation (t(630) = 1.94, p < 0.05). Older athletes showed significantly higher task orientation. Rural athletes had higher ego orientation whereas urban athletes have higher intrinsic motivation. Task orientation was related to intrinsic motivation (r = 0.55, p < 0.01), extrinsic motivation (r = 0.55, p < 0.01), but weakly related to amotivation (r = 0.10, p < 0.01). Ego orientation was related to intrinsic motivation (r = 0.30, p < 0.01), extrinsic motivation (r = 0.36, p < 0.01) and amotivaion (r = 0.36, p < 0.01). Task orientation was related to ego orientation (r = 0.29, p < 0.01). Multiple regression analysis showed intrinsic motivation, extrinsic motivation and amotivation accounted for 30.5% of the variances in task orientation. PMID:23486244

Solving Multiple Isolated, Interleaved, and Blended Tasks through Modular Neuroevolution.

PubMed

Schrum, Jacob; Miikkulainen, Risto

2016-01-01

Many challenging sequential decision-making problems require agents to master multiple tasks. For instance, game agents may need to gather resources, attack opponents, and defend against attacks. Learning algorithms can thus benefit from having separate policies for these tasks, and from knowing when each one is appropriate. How well this approach works depends on how tightly coupled the tasks are. Three cases are identified: Isolated tasks have distinct semantics and do not interact, interleaved tasks have distinct semantics but do interact, and blended tasks have regions where semantics from multiple tasks overlap. Learning across multiple tasks is studied in this article with Modular Multiobjective NEAT, a neuroevolution framework applied to three variants of the challenging Ms. Pac-Man video game. In the standard blended version of the game, a surprising, highly effective machine-discovered task division surpasses human-specified divisions, achieving the best scores to date in this game. In isolated and interleaved versions of the game, human-specified task divisions are also successful, though the best scores are surprisingly still achieved by machine discovery. Modular neuroevolution is thus shown to be capable of finding useful, unexpected task divisions better than those apparent to a human designer.

Acquisition of dental skills in preclinical technique courses: influence of spatial and manual abilities.

PubMed

Schwibbe, Anja; Kothe, Christian; Hampe, Wolfgang; Konradt, Udo

2016-10-01

Sixty years of research have not added up to a concordant evaluation of the influence of spatial and manual abilities on dental skill acquisition. We used Ackerman's theory of ability determinants of skill acquisition to explain the influence of spatial visualization and manual dexterity on the task performance of dental students in two consecutive preclinical technique courses. We measured spatial and manual abilities of applicants to Hamburg Dental School by means of a multiple choice test on Technical Aptitude and a wire-bending test, respectively. Preclinical dental technique tasks were categorized as consistent-simple and inconsistent-complex based on their contents. For analysis, we used robust regression to circumvent typical limitations in dental studies like small sample size and non-normal residual distributions. We found that manual, but not spatial ability exhibited a moderate influence on the performance in consistent-simple tasks during dental skill acquisition in preclinical dentistry. Both abilities revealed a moderate relation with the performance in inconsistent-complex tasks. These findings support the hypotheses which we had postulated on the basis of Ackerman's work. Therefore, spatial as well as manual ability are required for the acquisition of dental skills in preclinical technique courses. These results support the view that both abilities should be addressed in dental admission procedures in addition to cognitive measures.

A simple method for assessment of muscle force, velocity, and power producing capacities from functional movement tasks.

PubMed

Zivkovic, Milena Z; Djuric, Sasa; Cuk, Ivan; Suzovic, Dejan; Jaric, Slobodan

2017-07-01

A range of force (F) and velocity (V) data obtained from functional movement tasks (e.g., running, jumping, throwing, lifting, cycling) performed under variety of external loads have typically revealed strong and approximately linear F-V relationships. The regression model parameters reveal the maximum F (F-intercept), V (V-intercept), and power (P) producing capacities of the tested muscles. The aim of the present study was to evaluate the level of agreement between the routinely used "multiple-load model" and a simple "two-load model" based on direct assessment of the F-V relationship from only 2 external loads applied. Twelve participants were tested on the maximum performance vertical jumps, cycling, bench press throws, and bench pull performed against a variety of different loads. All 4 tested tasks revealed both exceptionally strong relationships between the parameters of the 2 models (median R = 0.98) and a lack of meaningful differences between their magnitudes (fixed bias below 3.4%). Therefore, addition of another load to the standard tests of various functional tasks typically conducted under a single set of mechanical conditions could allow for the assessment of the muscle mechanical properties such as the muscle F, V, and P producing capacities.

Aerobic Capacity and Cognitive Control in Elementary School-Age Children

PubMed Central

Scudder, Mark R.; Lambourne, Kate; Drollette, Eric S.; Herrmann, Stephen; Washburn, Richard; Donnelly, Joseph E.; Hillman, Charles H.

2014-01-01

Purpose The current study examined the relationship between children’s performance on the Progressive Aerobic Cardiovascular Endurance Run (PACER) subtest of the FitnessGram® and aspects of cognitive control that are believed to support academic success. Methods Hierarchical linear regression analyses were conducted on a sample of 2nd and 3rd grade children (n = 397) who completed modified versions of a flanker task and spatial n-back task to assess inhibitory control and working memory, respectively. Results Greater aerobic fitness was significantly related to shorter reaction time and superior accuracy during the flanker task, suggesting better inhibitory control and the facilitation of attention in higher fit children. A similar result was observed for the n-back task such that higher fit children exhibited more accurate target detection and discrimination performance when working memory demands were increased. Conclusion These findings support the positive association between aerobic fitness and multiple aspects of cognitive control in a large sample of children, using a widely implemented and reliable field estimate of aerobic capacity. Importantly, the current results suggest that this relationship is consistent across methods used to assess fitness, which may have important implications for extending this research to more representative samples of children in a variety of experimental contexts. PMID:24743109

Quadriceps force and anterior tibial force occur obviously later than vertical ground reaction force: a simulation study.

PubMed

Ueno, Ryo; Ishida, Tomoya; Yamanaka, Masanori; Taniguchi, Shohei; Ikuta, Ryohei; Samukawa, Mina; Saito, Hiroshi; Tohyama, Harukazu

2017-11-18

Although it is well known that quadriceps force generates anterior tibial force, it has been unclear whether quadriceps force causes great anterior tibial force during the early phase of a landing task. The purpose of the present study was to examine whether the quadriceps force induced great anterior tibial force during the early phase of a landing task. Fourteen young, healthy, female subjects performed a single-leg landing task. Muscle force and anterior tibial force were estimated from motion capture data and synchronized force data from the force plate. One-way repeated measures analysis of variance and the post hoc Bonferroni test were conducted to compare the peak time of the vertical ground reaction force, quadriceps force and anterior tibial force during the single-leg landing. In addition, we examined the contribution of vertical and posterior ground reaction force, knee flexion angle and moment to peak quadriceps force using multiple linear regression. The peak times of the estimated quadriceps force (96.0 ± 23.0 ms) and anterior tibial force (111.9 ± 18.9 ms) were significantly later than that of the vertical ground reaction force (63.5 ± 6.8 ms) during the single-leg landing. The peak quadriceps force was positively correlated with the peak anterior tibial force (R = 0.953, P < 0.001). Multiple linear regression analysis showed that the peak knee flexion moment contributed significantly to the peak quadriceps force (R 2  = 0.778, P < 0.001). The peak times of the quadriceps force and the anterior tibial force were obviously later than that of the vertical ground reaction force for the female athletes during successful single-leg landings. Studies have reported that the peak time of the vertical ground reaction force was close to the time of anterior cruciate ligament (ACL) disruption in ACL injury cases. It is possible that early contraction of the quadriceps during landing might induce ACL disruption as a result of excessive anterior tibial force in unanticipated situations in ACL injury cases.

Efficient multitasking: parallel versus serial processing of multiple tasks

PubMed Central

Fischer, Rico; Plessow, Franziska

2015-01-01

In the context of performance optimizations in multitasking, a central debate has unfolded in multitasking research around whether cognitive processes related to different tasks proceed only sequentially (one at a time), or can operate in parallel (simultaneously). This review features a discussion of theoretical considerations and empirical evidence regarding parallel versus serial task processing in multitasking. In addition, we highlight how methodological differences and theoretical conceptions determine the extent to which parallel processing in multitasking can be detected, to guide their employment in future research. Parallel and serial processing of multiple tasks are not mutually exclusive. Therefore, questions focusing exclusively on either task-processing mode are too simplified. We review empirical evidence and demonstrate that shifting between more parallel and more serial task processing critically depends on the conditions under which multiple tasks are performed. We conclude that efficient multitasking is reflected by the ability of individuals to adjust multitasking performance to environmental demands by flexibly shifting between different processing strategies of multiple task-component scheduling. PMID:26441742

Efficient multitasking: parallel versus serial processing of multiple tasks.

PubMed

Fischer, Rico; Plessow, Franziska

2015-01-01

In the context of performance optimizations in multitasking, a central debate has unfolded in multitasking research around whether cognitive processes related to different tasks proceed only sequentially (one at a time), or can operate in parallel (simultaneously). This review features a discussion of theoretical considerations and empirical evidence regarding parallel versus serial task processing in multitasking. In addition, we highlight how methodological differences and theoretical conceptions determine the extent to which parallel processing in multitasking can be detected, to guide their employment in future research. Parallel and serial processing of multiple tasks are not mutually exclusive. Therefore, questions focusing exclusively on either task-processing mode are too simplified. We review empirical evidence and demonstrate that shifting between more parallel and more serial task processing critically depends on the conditions under which multiple tasks are performed. We conclude that efficient multitasking is reflected by the ability of individuals to adjust multitasking performance to environmental demands by flexibly shifting between different processing strategies of multiple task-component scheduling.

Human performance in a multiple-task environment: effects of automation reliability on visual attention allocation.

PubMed

Cullen, Ralph H; Rogers, Wendy A; Fisk, Arthur D

2013-11-01

Diagnostic automation has been posited to alleviate the high demands of multiple-task environments; however, mixed effects have been found pertaining to performance aid success. To better understand these effects, attention allocation must be studied directly. We developed a multiple-task environment to study the effects of automation on visual attention. Participants interacted with a system providing varying levels of automation and automation reliability and then were transferred to a system with no support. Attention allocation was measured by tracking the number of times each task was viewed. We found that participants receiving automation allocated their time according to the task frequency and that tasks that benefited most from automation were most harmed when it was removed. The results suggest that the degree to which automation affects multiple-task performance is dependent on the relative attributes of the tasks involved. Moreover, there is an inverse relationship between support and cost when automation fails. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Using Functional Electrical Stimulation Mediated by Iterative Learning Control and Robotics to Improve Arm Movement for People With Multiple Sclerosis.

PubMed

Sampson, Patrica; Freeman, Chris; Coote, Susan; Demain, Sara; Feys, Peter; Meadmore, Katie; Hughes, Ann-Marie

2016-02-01

Few interventions address multiple sclerosis (MS) arm dysfunction but robotics and functional electrical stimulation (FES) appear promising. This paper investigates the feasibility of combining FES with passive robotic support during virtual reality (VR) training tasks to improve upper limb function in people with multiple sclerosis (pwMS). The system assists patients in following a specified trajectory path, employing an advanced model-based paradigm termed iterative learning control (ILC) to adjust the FES to improve accuracy and maximise voluntary effort. Reaching tasks were repeated six times with ILC learning the optimum control action from previous attempts. A convenience sample of five pwMS was recruited from local MS societies, and the intervention comprised 18 one-hour training sessions over 10 weeks. The accuracy of tracking performance without FES and the amount of FES delivered during training were analyzed using regression analysis. Clinical functioning of the arm was documented before and after treatment with standard tests. Statistically significant results following training included: improved accuracy of tracking performance both when assisted and unassisted by FES; reduction in maximum amount of FES needed to assist tracking; and less impairment in the proximal arm that was trained. The system was well tolerated by all participants with no increase in muscle fatigue reported. This study confirms the feasibility of FES combined with passive robot assistance as a potentially effective intervention to improve arm movement and control in pwMS and provides the basis for a follow-up study.

EPIC Computational Models of Psychological Refractory-Period Effects in Human Multiple-Task Performance.

ERIC Educational Resources Information Center

Meyer, David E.; Kieras, David E.

Perceptual-motor and cognitive processes whereby people perform multiple concurrent tasks have been studied through an overlapping-tasks procedure in which two successive choice-reaction tasks are performed with a variable interval (stimulus onset asynchrony, or SOA) between the beginning of the first and second tasks. The increase in subjects'…

Theoretical exploration of the neural bases of behavioural disinhibition, apathy and executive dysfunction in preclinical Alzheimer's disease in people with Down's syndrome: potential involvement of multiple frontal-subcortical neuronal circuits.

PubMed

Ball, S L; Holland, A J; Watson, P C; Huppert, F A

2010-04-01

Recent research has suggested a specific impairment in frontal-lobe functioning in the preclinical stages of Alzheimer's disease (AD) in people with Down's syndrome (DS), characterised by prominent changes in personality or behaviour. The aim of the current paper is to explore whether particular kinds of change (namely executive dysfunction (EDF), disinhibition and apathy), associated in the literature with disruption of different underlying frontal-subcortical circuits, are a) more or less frequently reported than others and b) related to poor performance on tasks involving different cognitive processes. Seventy-eight participants (mean age 47 years, range 36-72) with DS and mild to moderate intellectual disability (based on ICD-10 criteria), without a diagnosis of dementia of Alzheimer's type (DAT) or other psychiatric disorders, were selected from a larger sample of older adults with DS (n = 122). Dementia diagnosis was based on the CAMDEX informant interview, conducted with each participant's main carer. Informant-reported changes in personality/behaviour and memory were recorded. Participants were scored based on symptoms falling into three behavioural domains and completed five executive function (EF) tasks, six memory tasks (two of which also had a strong executive component) and the BPVS (as a measure of general intellectual ability). Multiple regression analyses were conducted to determine the degree to which the behavioural variables of 'EDF', 'disinhibition' and 'apathy', along with informant-reported memory decline and antidepressant medication use, predicted performance on the cognitive tasks (whilst controlling for the effects of age and general intellectual ability). Strikingly, disinhibited behaviour was reported for 95.7% of participants with one or more behavioural change (n = 47) compared to 57.4% with reported apathy and 36.2% with reported EDF. 'Disinhibition' score significantly predicted performance on three EF tasks (designed to measure planning, response inhibition and working memory) and an object memory task, (also thought to place high demands on working memory), while 'apathy' score significantly predicted performance on two different tasks, those measuring spatial reversal and prospective memory (p < 0.05). Informant reported memory decline was associated only with performance on a delayed recall task while antidepressant medication use was associated with better performance on a working memory task (p < 0.05). Observed dissociation between performance on cognitive tasks associated with reported apathy and disinhibition is in keeping with proposed differences underlying neural circuitry and supports the involvement of multiple frontal-subcortical circuits in the early stages of DAT in DS. However, the prominence of disinhibition in the behavioural profile (which more closely resembles that of disinhibited subtype of DFT than that of AD in the general population) leads us to postulate that the serotonergically mediated orbitofrontal circuit may be disproportionately affected. A speculative theory is developed regarding the biological basis for observed changes and discussion is focused on how this understanding may aid us in the development of treatments directly targeting underlying abnormalities.

Downscaling Land Surface Temperature in Complex Regions by Using Multiple Scale Factors with Adaptive Thresholds

PubMed Central

Yang, Yingbao; Li, Xiaolong; Pan, Xin; Zhang, Yong; Cao, Chen

2017-01-01

Many downscaling algorithms have been proposed to address the issue of coarse-resolution land surface temperature (LST) derived from available satellite-borne sensors. However, few studies have focused on improving LST downscaling in urban areas with several mixed surface types. In this study, LST was downscaled by a multiple linear regression model between LST and multiple scale factors in mixed areas with three or four surface types. The correlation coefficients (CCs) between LST and the scale factors were used to assess the importance of the scale factors within a moving window. CC thresholds determined which factors participated in the fitting of the regression equation. The proposed downscaling approach, which involves an adaptive selection of the scale factors, was evaluated using the LST derived from four Landsat 8 thermal imageries of Nanjing City in different seasons. Results of the visual and quantitative analyses show that the proposed approach achieves relatively satisfactory downscaling results on 11 August, with coefficient of determination and root-mean-square error of 0.87 and 1.13 °C, respectively. Relative to other approaches, our approach shows the similar accuracy and the availability in all seasons. The best (worst) availability occurred in the region of vegetation (water). Thus, the approach is an efficient and reliable LST downscaling method. Future tasks include reliable LST downscaling in challenging regions and the application of our model in middle and low spatial resolutions. PMID:28368301

Limits of Spatial Attention in Three-Dimensional Space and Dual-task Driving Performance

PubMed Central

Andersen, George J.; Ni, Rui; Bian, Zheng; Kang, Julie

2010-01-01

The present study examined the limits of spatial attention while performing two driving relevant tasks that varied in depth. The first task was to maintain a fixed headway distance behind a lead vehicle that varied speed. The second task was to detect a light-change target in an array of lights located above the roadway. In Experiment 1 the light detection task required drivers to encode color and location. The results indicated that reaction time to detect a light-change target increased and accuracy decreased as a function of the horizontal location of the light-change target and as a function of the distance from the driver. In a second experiment the light change task was changed to a singleton search (detect the onset of a yellow light) and the workload of the car following task was systematically varied. The results of Experiment 2 indicated that RT increased as a function of task workload, the 2D position of the light-change target and the distance of the light-change target. A multiple regression analysis indicated that the effect of distance on light detection performance was not due to changes in the projected size of the light target. In Experiment 3 we found that the distance effect in detecting a light change could not be explained by the location of eye fixations. The results demonstrate that when drivers attend to a roadway scene attention is limited in three-dimensional space. These results have important implications for developing tests for assessing crash risk among drivers as well as the design of in vehicle technologies such as head-up displays. PMID:21094336

The Association between Dual-Task Gait after Concussion and Prolonged Symptom Duration.

PubMed

Howell, David R; Brilliant, Anna; Berkstresser, Brant; Wang, Francis; Fraser, Joana; Meehan, William P

2017-12-01

Quantitative gait measurements can identify persistent postconcussion impairments. However, their prognostic utility after injury to identify the likelihood of prolonged concussion symptoms remains unknown. Our objective was to examine if dual-task gait performance measures are independently associated with persistent (> 28 days) concussion symptoms among a sample of athletes. Sixty individuals diagnosed with a sport-related concussion were assessed within 10 days of their injury. Each participant completed a postconcussion symptom scale, an injury history questionnaire, and a single/dual-task gait examination. They were followed until they no longer reported symptoms, and the duration of time required for symptom resolution was calculated. A binary multivariable logistic regression model determined the independent association between dual-task gait and symptom duration (≤ 28 days vs. >28 days) while controlling for the effect of gender, age, symptom severity, injury-to-examination time, and history of concussion. Seventeen (28%) participants reported a symptom duration >28 days. The dual-task cost for average gait speed (-25.9 ± 9.5% vs. -19.8 ± 8.9%; p = 0.027) and cadence (-18.0 ± 2.9% vs. -12.0 ± 7.7%; p = 0.029) was significantly greater among participants who experienced symptoms for >28 days. After adjusting for potential confounding variables, greater dual-task average gait speed costs were independently associated with prolonged symptom duration (aOR = 0.908; 95% CI = 0.835-0.987). Examinations of dual-task gait may provide useful information during multifaceted concussion examinations. Quantitative assessments that simultaneously test multiple domains, such as dual tasks, may be clinically valuable after a concussion to identify those more likely to experience symptoms for >28 days after injury.

Evidencing the association between swimming capacities and performance indicators in water polo: a multiple regression study.

PubMed

Kontic, Dean; Zenic, Natasa; Uljevic, Ognjen; Sekulic, Damir; Lesnik, Blaz

2017-06-01

Swimming capacities are hypothesized to be important determinants of water polo performance but there is an evident lack of studies examining different swimming capacities in relation to specific offensive and defensive performance variables in this sport. The aim of this study was to determine the relationship between five swimming capacities and six performance determinants in water polo. The sample comprised 79 high-level youth water polo players (all males, 17-18 years of age). The variables included six performance-related variables (agility in offence and defense, efficacy in offence and defense, polyvalence in offence and defense), and five swimming-capacity tests (water polo sprint test [15 m], swimming sprint test [25 m], short-distance [100 m], aerobic endurance [400 m] and an anaerobic lactate endurance test [4× 50 m]). First, multiple regressions were calculated for one-half of the sample of subjects which were then validated with the remaining half of the sample. The 25-m swim was not included in the regression analyses due to the multicollinearity with other predictors. The originally calculated regression models were validated for defensive agility (R=0.67 and R=0.55 for the original regression calculation and validation subsample, respectively) offensive agility (R=0.59 and R=0.61), and offensive efficacy (R=0.64 and R=0.58). Anaerobic lactate endurance is a significant predictor of offensive and defensive agility, while 15 m sprint significantly contributes to offensive efficacy. Swimming capacities are not found to be related to the polyvalence of the players. The most superior offensive performance can be expected from those players with a high level of anaerobic lactate endurance and advanced sprinting capacity, while anaerobic lactate endurance is recognized as most important quality in defensive duties. Future studies should observe players' polyvalence in relation to (theoretical) knowledge of technical and tactical tasks. Results reinforce the need for the cross-validation of the prediction-models in sport and exercise sciences.

Predicting social and communicative ability in school-age children with autism spectrum disorder: A pilot study of the Social Attribution Task, Multiple Choice.

PubMed

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

2016-11-01

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 19-question Social Attribution Task, Multiple Choice, which presents ambiguous stimuli meant to elicit social attribution, was administered to children with autism spectrum disorder (N = 23) and to age-matched and verbal IQ-matched typically developing children (N = 57). The Social Attribution Task, Multiple Choice performance differed between autism spectrum disorder and typically developing groups, with typically developing children performing significantly better than children with autism spectrum disorder. The Social Attribution Task, Multiple Choice scores were positively correlated with age (r = 0.474) while being independent from verbal IQ (r = 0.236). The Social Attribution Task, Multiple Choice was strongly correlated with Vineland Adaptive Behavior Scales Communication (r = 0.464) and Socialization (r = 0.482) scores, but not with Daily Living Skills scores (r = 0.116), suggesting that the implicit social cognitive ability underlying performance on the Social Attribution Task, Multiple Choice is associated with real-life social adaptive function. © The Author(s) 2016.

The Effects of Study Tasks in a Computer-Based Chemistry Learning Environment

NASA Astrophysics Data System (ADS)

Urhahne, Detlef; Nick, Sabine; Poepping, Anna Christin; Schulz, Sarah Jayne

2013-12-01

The present study examines the effects of different study tasks on the acquisition of knowledge about acids and bases in a computer-based learning environment. Three different task formats were selected to create three treatment conditions: learning with gap-fill and matching tasks, learning with multiple-choice tasks, and learning only from text and figures without any additional tasks. Participants were 196 ninth-grade students who learned with a self-developed multimedia program in a pretest-posttest control group design. Research results reveal that gap-fill and matching tasks were most effective in promoting knowledge acquisition, followed by multiple-choice tasks, and no tasks at all. The findings are in line with previous research on this topic. The effects can possibly be explained by the generation-recognition model, which predicts that gap-fill and matching tasks trigger more encompassing learning processes than multiple-choice tasks. It is concluded that instructional designers should incorporate more challenging study tasks for enhancing the effectiveness of computer-based learning environments.

Multiple Correlation versus Multiple Regression.

ERIC Educational Resources Information Center

Huberty, Carl J.

2003-01-01

Describes differences between multiple correlation analysis (MCA) and multiple regression analysis (MRA), showing how these approaches involve different research questions and study designs, different inferential approaches, different analysis strategies, and different reported information. (SLD)

The Detection and Interpretation of Interaction Effects between Continuous Variables in Multiple Regression.

ERIC Educational Resources Information Center

Jaccard, James; And Others

1990-01-01

Issues in the detection and interpretation of interaction effects between quantitative variables in multiple regression analysis are discussed. Recent discussions associated with problems of multicollinearity are reviewed in the context of the conditional nature of multiple regression with product terms. (TJH)

Studying Different Tasks of Implicit Learning across Multiple Test Sessions Conducted on the Web

PubMed Central

Sævland, Werner; Norman, Elisabeth

2016-01-01

Implicit learning is usually studied through individual performance on a single task, with the most common tasks being the Serial Reaction Time (SRT) task, the Dynamic System Control (DSC) task, and Artificial Grammar Learning (AGL). Few attempts have been made to compare performance across different implicit learning tasks within the same study. The current study was designed to explore the relationship between performance on the DSC Sugar factory task and the Alternating Serial Reaction Time (ASRT) task. We also addressed another limitation of traditional implicit learning experiments, namely that implicit learning is usually studied in laboratory settings over a restricted time span lasting for less than an hour. In everyday situations, implicit learning is assumed to involve a gradual accumulation of knowledge across several learning episodes over a longer time span. One way to increase the ecological validity of implicit learning experiments could be to present the learning material repeatedly across shorter test sessions. This can most easily be done by using a web-based setup in which participants can access the material from home. We therefore created an online web-based system for measuring implicit learning that could be administered in either single or multiple sessions. Participants (n = 66) were assigned to either a single session or a multiple session condition. Learning occurred on both tasks, and awareness measures suggested that acquired knowledge was not fully conscious on either of the tasks. Learning and the degree of conscious awareness of the learned regularities were compared across conditions and tasks. On the DSC task, performance was not affected by whether learning had taken place in one or over multiple sessions. On the ASRT task, RT improvement across blocks was larger in the multiple-session condition. Learning in the two tasks was not related. PMID:27375512

A Rich Assessment Task as a Window into Students' Multiplicative Reasoning

ERIC Educational Resources Information Center

Downton, Ann; Wright, Vince

2016-01-01

This study explored the potential of a rich assessment task to reveal students' multiplicative thinking in respect to a hypothetical learning trajectory. Thirty pairs of students in grades 5 and 6 attempted the task. Twenty-two pairs applied multiplicative structure to find the number of items in arrays. However counting and computational errors…

A rotor optimization using regression analysis

NASA Technical Reports Server (NTRS)

Giansante, N.

1984-01-01

The design and development of helicopter rotors is subject to the many design variables and their interactions that effect rotor operation. Until recently, selection of rotor design variables to achieve specified rotor operational qualities has been a costly, time consuming, repetitive task. For the past several years, Kaman Aerospace Corporation has successfully applied multiple linear regression analysis, coupled with optimization and sensitivity procedures, in the analytical design of rotor systems. It is concluded that approximating equations can be developed rapidly for a multiplicity of objective and constraint functions and optimizations can be performed in a rapid and cost effective manner; the number and/or range of design variables can be increased by expanding the data base and developing approximating functions to reflect the expanded design space; the order of the approximating equations can be expanded easily to improve correlation between analyzer results and the approximating equations; gradients of the approximating equations can be calculated easily and these gradients are smooth functions reducing the risk of numerical problems in the optimization; the use of approximating functions allows the problem to be started easily and rapidly from various initial designs to enhance the probability of finding a global optimum; and the approximating equations are independent of the analysis or optimization codes used.

Beyond Multiple Regression: Using Commonality Analysis to Better Understand R[superscript 2] Results

ERIC Educational Resources Information Center

Warne, Russell T.

2011-01-01

Multiple regression is one of the most common statistical methods used in quantitative educational research. Despite the versatility and easy interpretability of multiple regression, it has some shortcomings in the detection of suppressor variables and for somewhat arbitrarily assigning values to the structure coefficients of correlated…

Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions.

PubMed

Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

2012-05-01

Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Lung nodule malignancy prediction using multi-task convolutional neural network

NASA Astrophysics Data System (ADS)

Li, Xiuli; Kao, Yueying; Shen, Wei; Li, Xiang; Xie, Guotong

2017-03-01

In this paper, we investigated the problem of diagnostic lung nodule malignancy prediction using thoracic Computed Tomography (CT) screening. Unlike most existing studies classify the nodules into two types benign and malignancy, we interpreted the nodule malignancy prediction as a regression problem to predict continuous malignancy level. We proposed a joint multi-task learning algorithm using Convolutional Neural Network (CNN) to capture nodule heterogeneity by extracting discriminative features from alternatingly stacked layers. We trained a CNN regression model to predict the nodule malignancy, and designed a multi-task learning mechanism to simultaneously share knowledge among 9 different nodule characteristics (Subtlety, Calcification, Sphericity, Margin, Lobulation, Spiculation, Texture, Diameter and Malignancy), and improved the final prediction result. Each CNN would generate characteristic-specific feature representations, and then we applied multi-task learning on the features to predict the corresponding likelihood for that characteristic. We evaluated the proposed method on 2620 nodules CT scans from LIDC-IDRI dataset with the 5-fold cross validation strategy. The multitask CNN regression result for regression RMSE and mapped classification ACC were 0.830 and 83.03%, while the results for single task regression RMSE 0.894 and mapped classification ACC 74.9%. Experiments show that the proposed method could predict the lung nodule malignancy likelihood effectively and outperforms the state-of-the-art methods. The learning framework could easily be applied in other anomaly likelihood prediction problem, such as skin cancer and breast cancer. It demonstrated the possibility of our method facilitating the radiologists for nodule staging assessment and individual therapeutic planning.

[Prevalence and factors associated with dental pain that prevents the performance of routine tasks by civil servants in Rio de Janeiro, Brazil].

PubMed

Alexandre, Gisele Caldas; Nadanovsky, Paulo; Lopes, Claudia S; Faerstein, Eduardo

2006-05-01

The aims of this study were to estimate the prevalence of dental pain preventing the performance of routine tasks and to assess its association with socioeconomic factors, minor psychiatric disorders, number of missing teeth, and dental consultation patterns. A cross-sectional study was conducted using a self-completed questionnaire answered by 4,030 administrative employees at a university in Rio de Janeiro, Brazil (the Pró-Saúde Study). Data were analyzed using multiple logistic regression. Prevalence of toothache preventing the performance of routine tasks in the two weeks prior to the interview was 2.9% (95%CI: 2.5-3.6). Men (OR = 1.6; 95%CI: 1.1-2.4), individuals with minor psychiatric disorders (OR = 1.7; 95%CI: 1.2-2.6), individuals with extensive tooth loss (OR = 3.4; 95%CI: 1.5-7.8), and those failing to appear for regular dental checkups (OR = 2.5; 95%CI: 1.8-17.3) showed increased odds of experiencing dental pain. Dental pain was an important problem in this population. Unfavorable living conditions and lack of regular dental checkups increased the odds of dental pain.

Abnormalities of mental rotation of hands associated with speed of information processing and executive function in chronic schizophrenic patients.

PubMed

Mazhari, Shahrzad; Moghadas Tabrizi, Yousef

2014-06-01

Deficits in mental imagery ability have been reported in patients with schizophrenia. However, there is scarce evidence about the correlation between impairment in mental rotation and other cognitive deficits in the patients. The aim of this study was to assess mental rotation ability, along with other measures of cognitive function in patients with schizophrenia. The performance of 29 patients with schizophrenia was compared with 29 healthy controls. Mental rotation was measured with the Hand Rotation Task, and cognitive functions were measured with the Brief Assessment of Cognition in Schizophrenia (BACS). On Hand Rotation Task, the patients were significantly slower and less accurate compared to controls. Moreover, mental rotation accuracy was significantly correlated with all the BACS domains except verbal memory. In multiple regression analysis, the two BACS subscales, Tower of London and Symbol Coding tasks, were significant predictors and accounted for 41% of the variance in accuracy in the patients. These results support previous findings showing dysfunction of the posterior parietal cortex in schizophrenia, which is involved in general mental rotation, as well as other cognitive processes. © 2014 The Authors. Psychiatry and Clinical Neurosciences © 2014 Japanese Society of Psychiatry and Neurology.

Brain areas consistently linked to individual differences in perceptual decision-making in younger as well as older adults before and after training.

PubMed

Kühn, Simone; Schmiedek, Florian; Schott, Björn; Ratcliff, Roger; Heinze, Hans-Jochen; Düzel, Emrah; Lindenberger, Ulman; Lövden, Martin

2011-09-01

Perceptual decision-making performance depends on several cognitive and neural processes. Here, we fit Ratcliff's diffusion model to accuracy data and reaction-time distributions from one numerical and one verbal two-choice perceptual-decision task to deconstruct these performance measures into the rate of evidence accumulation (i.e., drift rate), response criterion setting (i.e., boundary separation), and peripheral aspects of performance (i.e., nondecision time). These theoretical processes are then related to individual differences in brain activation by means of multiple regression. The sample consisted of 24 younger and 15 older adults performing the task in fMRI before and after 100 daily 1-hr behavioral training sessions in a multitude of cognitive tasks. Results showed that individual differences in boundary separation were related to striatal activity, whereas differences in drift rate were related to activity in the inferior parietal lobe. These associations were not significantly modified by adult age or perceptual expertise. We conclude that the striatum is involved in regulating response thresholds, whereas the inferior parietal lobe might represent decision-making evidence related to letters and numbers.

Domain or not domain? That is the question: longitudinal semantic deterioration in Alzheimer's disease.

PubMed

Moreno-Martínez, F Javier; Goñi-Imízcoz, Miguel; Spitznagel, Mary Beth

2011-10-01

Category specific semantic impairment (e.g. living versus nonliving things) has been reported in association with various pathologies, including herpes simplex encephalitis and semantic dementia. However, evidence is inconsistent regarding whether this effect exists in diseases progressively impacting diverse cortical regions, such as Alzheimer's disease (AD). Ceiling effects producing non-Gaussian distributions and poor control for confounds such as nuisance variables (e.g. familiarity) may contribute to this discrepancy. Fourteen AD patients were longitudinally studied examining category effects on three semantic tasks (picture naming, naming to description and word to picture matching) matched across domain on all known nuisance variables (NV). To address non-Gaussian distributions, we run bootstrap analyses to determine whether NV, semantic domain or control performance best predicted AD patient performance. Multiple hierarchical regression analyses revealed that, whilst NV accounted for most of the explained variance in patients in the three tasks, the influence of semantic domain was substantially lower. Individual logistic regression demonstrated a significant category effect in only a few patients and healthy controls. No significant qualitative changes were observed in patients over time. Our results confirm the importance of NVs as predictors of AD patient performance, suggesting that the role of semantic domain is not a useful predictor of the progressive deterioration in AD. Copyright © 2011 Elsevier Inc. All rights reserved.

Re-assessing acalculia: Distinguishing spatial and purely arithmetical deficits in right-hemisphere damaged patients.

PubMed

Benavides-Varela, S; Piva, D; Burgio, F; Passarini, L; Rolma, G; Meneghello, F; Semenza, C

2017-03-01

Arithmetical deficits in right-hemisphere damaged patients have been traditionally considered secondary to visuo-spatial impairments, although the exact relationship between the two deficits has rarely been assessed. The present study implemented a voxelwise lesion analysis among 30 right-hemisphere damaged patients and a controlled, matched-sample, cross-sectional analysis with 35 cognitively normal controls regressing three composite cognitive measures on standardized numerical measures. The results showed that patients and controls significantly differ in Number comprehension, Transcoding, and Written operations, particularly subtractions and multiplications. The percentage of patients performing below the cutoffs ranged between 27% and 47% across these tasks. Spatial errors were associated with extensive lesions in fronto-temporo-parietal regions -which frequently lead to neglect- whereas pure arithmetical errors appeared related to more confined lesions in the right angular gyrus and its proximity. Stepwise regression models consistently revealed that spatial errors were primarily predicted by composite measures of visuo-spatial attention/neglect and representational abilities. Conversely, specific errors of arithmetic nature linked to representational abilities only. Crucially, the proportion of arithmetical errors (ranging from 65% to 100% across tasks) was higher than that of spatial ones. These findings thus suggest that unilateral right hemisphere lesions can directly affect core numerical/arithmetical processes, and that right-hemisphere acalculia is not only ascribable to visuo-spatial deficits as traditionally thought. Copyright © 2017 Elsevier Ltd. All rights reserved.

Leadership = Communication? The Relations of Leaders’ Communication Styles with Leadership Styles, Knowledge Sharing and Leadership Outcomes

PubMed Central

Bakker-Pieper, Angelique; Oostenveld, Wyneke

2009-01-01

Purpose The purpose of this study was to investigate the relations between leaders’ communication styles and charismatic leadership, human-oriented leadership (leader’s consideration), task-oriented leadership (leader’s initiating structure), and leadership outcomes. Methodology A survey was conducted among 279 employees of a governmental organization. The following six main communication styles were operationalized: verbal aggressiveness, expressiveness, preciseness, assuredness, supportiveness, and argumentativeness. Regression analyses were employed to test three main hypotheses. Findings In line with expectations, the study showed that charismatic and human-oriented leadership are mainly communicative, while task-oriented leadership is significantly less communicative. The communication styles were strongly and differentially related to knowledge sharing behaviors, perceived leader performance, satisfaction with the leader, and subordinate’s team commitment. Multiple regression analyses showed that the leadership styles mediated the relations between the communication styles and leadership outcomes. However, leader’s preciseness explained variance in perceived leader performance and satisfaction with the leader above and beyond the leadership style variables. Implications This study offers potentially invaluable input for leadership training programs by showing the importance of leader’s supportiveness, assuredness, and preciseness when communicating with subordinates. Originality/value Although one of the core elements of leadership is interpersonal communication, this study is one of the first to use a comprehensive communication styles instrument in the study of leadership. PMID:20700375

Age-Related Differences in Multiple Task Monitoring

PubMed Central

Todorov, Ivo; Del Missier, Fabio; Mäntylä, Timo

2014-01-01

Coordinating multiple tasks with narrow deadlines is particularly challenging for older adults because of age related decline in cognitive control functions. We tested the hypothesis that multiple task performance reflects age- and gender-related differences in executive functioning and spatial ability. Young and older adults completed a multitasking session with four monitoring tasks as well as separate tasks measuring executive functioning and spatial ability. For both age groups, men exceeded women in multitasking, measured as monitoring accuracy. Individual differences in executive functioning and spatial ability were independent predictors of young adults' monitoring accuracy, but only spatial ability was related to sex differences. For older adults, age and executive functioning, but not spatial ability, predicted multitasking performance. These results suggest that executive functions contribute to multiple task performance across the adult life span and that reliance on spatial skills for coordinating deadlines is modulated by age. PMID:25215609

Age-related differences in multiple task monitoring.

PubMed

Todorov, Ivo; Del Missier, Fabio; Mäntylä, Timo

2014-01-01

Coordinating multiple tasks with narrow deadlines is particularly challenging for older adults because of age related decline in cognitive control functions. We tested the hypothesis that multiple task performance reflects age- and gender-related differences in executive functioning and spatial ability. Young and older adults completed a multitasking session with four monitoring tasks as well as separate tasks measuring executive functioning and spatial ability. For both age groups, men exceeded women in multitasking, measured as monitoring accuracy. Individual differences in executive functioning and spatial ability were independent predictors of young adults' monitoring accuracy, but only spatial ability was related to sex differences. For older adults, age and executive functioning, but not spatial ability, predicted multitasking performance. These results suggest that executive functions contribute to multiple task performance across the adult life span and that reliance on spatial skills for coordinating deadlines is modulated by age.

Knee Proprioception and Strength and Landing Kinematics During a Single-Leg Stop-Jump Task

PubMed Central

Nagai, Takashi; Sell, Timothy C; House, Anthony J; Abt, John P; Lephart, Scott M

2013-01-01

Context The importance of the sensorimotor system in maintaining a stable knee joint has been recognized. As individual entities, knee-joint proprioception, landing kinematics, and knee muscles play important roles in functional joint stability. Preventing knee injuries during dynamic tasks requires accurate proprioceptive information and adequate muscular strength. Few investigators have evaluated the relationship between knee proprioception and strength and landing kinematics. Objective To examine the relationship between knee proprioception and strength and landing kinematics. Design Cross-sectional study. Setting University research laboratory. Patients or Other Participants Fifty physically active men (age = 26.4 ± 5.8 years, height = 176.5 ± 8.0 cm, mass = 79.8 ± 16.6 kg). Intervention(s) Three tests were performed. Knee conscious proprioception was evaluated via threshold to detect passive motion (TTDPM). Knee strength was evaluated with a dynamometer. A 3-dimensional biomechanical analysis of a single-legged stop-jump task was used to calculate initial contact (IC) knee-flexion angle and knee-flexion excursion. Main Outcome Measure(s) The TTDPM toward knee flexion and extension, peak knee flexion and extension torque, and IC knee-flexion angle and knee flexion excursion. Linear correlation and stepwise multiple linear regression analyses were used to evaluate the relationships of both proprioception and strength against landing kinematics. The α level was set a priori at .05. Results Enhanced TTDPM and greater knee strength were positively correlated with greater IC knee-flexion angle (r range = 0.281–0.479, P range = .001–.048). The regression analysis revealed that 27.4% of the variance in IC knee-flexion angle could be accounted for by knee-flexion peak torque and TTDPM toward flexion (P = .001). Conclusions The current research highlighted the relationship between knee proprioception and strength and landing kinematics. Individuals with enhanced proprioception and muscular strength had better control of IC knee-flexion angle during a dynamic task. PMID:23672323

Multiple Types of Memory and Everyday Functional Assessment in Older Adults

PubMed Central

Beaver, Jenna

2017-01-01

Abstract Objective Current proxy measures for assessing everyday functioning (e.g., questionnaires, performance-based measures, and direct observation) show discrepancies in their rating of functional status. The present study investigated the relationship between multiple proxy measures of functional status and content memory (i.e., memory for information), temporal order memory, and prospective memory in an older adult sample. Method A total of 197 community-dwelling older adults who did (n = 45) or did not meet (n = 152) criteria for mild cognitive impairment (MCI), completed six different assessments of functional status (two questionnaires, two performance-based tasks, and two direct observation tasks) as well as experimental measures of content memory, prospective memory, and temporal order memory. Results After controlling for demographics and content memory, the temporal order and prospective memory measures explained a significant amount of variance in all proxy functional status measures. When all variables were entered into the regression analyses, content memory and prospective memory were found to be significant predictors of all measures of functional status, whereas temporal order memory was a significant predictor for the questionnaire and direct observation measures, but not performance-based measures. Conclusion The results suggest that direct observation and questionnaire measures may be able to capture components of everyday functioning that require context and temporal sequencing abilities, such as multi-tasking, that are not as well captured in many current laboratory performance-based measures of functional status. Future research should aim to inform the development and use of maximally effective and valid proxy measures of functional ability. PMID:28334170

Load Balancing in Cloud Computing Environment Using Improved Weighted Round Robin Algorithm for Nonpreemptive Dependent Tasks.

PubMed

Devi, D Chitra; Uthariaraj, V Rhymend

2016-01-01

Cloud computing uses the concepts of scheduling and load balancing to migrate tasks to underutilized VMs for effectively sharing the resources. The scheduling of the nonpreemptive tasks in the cloud computing environment is an irrecoverable restraint and hence it has to be assigned to the most appropriate VMs at the initial placement itself. Practically, the arrived jobs consist of multiple interdependent tasks and they may execute the independent tasks in multiple VMs or in the same VM's multiple cores. Also, the jobs arrive during the run time of the server in varying random intervals under various load conditions. The participating heterogeneous resources are managed by allocating the tasks to appropriate resources by static or dynamic scheduling to make the cloud computing more efficient and thus it improves the user satisfaction. Objective of this work is to introduce and evaluate the proposed scheduling and load balancing algorithm by considering the capabilities of each virtual machine (VM), the task length of each requested job, and the interdependency of multiple tasks. Performance of the proposed algorithm is studied by comparing with the existing methods.

Load Balancing in Cloud Computing Environment Using Improved Weighted Round Robin Algorithm for Nonpreemptive Dependent Tasks

PubMed Central

Devi, D. Chitra; Uthariaraj, V. Rhymend

2016-01-01

Cloud computing uses the concepts of scheduling and load balancing to migrate tasks to underutilized VMs for effectively sharing the resources. The scheduling of the nonpreemptive tasks in the cloud computing environment is an irrecoverable restraint and hence it has to be assigned to the most appropriate VMs at the initial placement itself. Practically, the arrived jobs consist of multiple interdependent tasks and they may execute the independent tasks in multiple VMs or in the same VM's multiple cores. Also, the jobs arrive during the run time of the server in varying random intervals under various load conditions. The participating heterogeneous resources are managed by allocating the tasks to appropriate resources by static or dynamic scheduling to make the cloud computing more efficient and thus it improves the user satisfaction. Objective of this work is to introduce and evaluate the proposed scheduling and load balancing algorithm by considering the capabilities of each virtual machine (VM), the task length of each requested job, and the interdependency of multiple tasks. Performance of the proposed algorithm is studied by comparing with the existing methods. PMID:26955656

Biomechanical evaluation of nursing tasks in a hospital setting.

PubMed

Jang, R; Karwowski, W; Quesada, P M; Rodrick, D; Sherehiy, B; Cronin, S N; Layer, J K

2007-11-01

A field study was conducted to investigate spinal kinematics and loading in the nursing profession using objective and subjective measurements of selected nursing tasks observed in a hospital setting. Spinal loading was estimated using trunk motion dynamics measured by the lumbar motion monitor (LMM) and lower back compressive and shear forces were estimated using the three-dimensional (3D) Static Strength Prediction Program. Subjective measures included the rate of perceived physical effort and the perceived risk of low back pain. A multiple logistic regression model, reported in the literature for predicting low back injury based on defined risk groups, was tested. The study results concluded that the major risk factors for low back injury in nurses were the weight of patients handled, trunk moment, and trunk axial rotation. The activities that required long time exposure to awkward postures were perceived by nurses as a high physical effort. This study also concluded that self-reported perceived exertion could be used as a tool to identify nursing activities with a high risk of low-back injury.

Human performance under two different command and control paradigms.

PubMed

Walker, Guy H; Stanton, Neville A; Salmon, Paul M; Jenkins, Daniel P

2014-05-01

The paradoxical behaviour of a new command and control concept called Network Enabled Capability (NEC) provides the motivation for this paper. In it, a traditional hierarchical command and control organisation was pitted against a network centric alternative on a common task, played thirty times, by two teams. Multiple regression was used to undertake a simple form of time series analysis. It revealed that whilst the NEC condition ended up being slightly slower than its hierarchical counterpart, it was able to balance and optimise all three of the performance variables measured (task time, enemies neutralised and attrition). From this it is argued that a useful conceptual response is not to consider NEC as an end product comprised of networked computers and standard operating procedures, nor to regard the human system interaction as inherently stable, but rather to view it as a set of initial conditions from which the most adaptable component of all can be harnessed: the human. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

[Relationships between motivational regulation strategies, motivational factors, and learning behaviors outside the classroom].

PubMed

Umemoto, Takatoyo; Tanaka, Kenshiro

2017-04-01

This study examined the relationships among motivational regulation strategies, motivational factors, and learning behaviors outside the classroom. There are three subtypes of motivational regulation strategies: autonomous regulation strategies, cooperative strategies, and performance-focused strategies. Motivational factors included in the investigation were self-efficacy and task value, while behavioral and emotional engagement and study time were selected as learning behaviors outside the classroom. A self-report questionnaire was administered to 322 undergraduates from two universities. Multiple regression analysis revealed the use of autonomous regulation strategies, and that task value was positively correlated with engagement and study time. Moreover, self-efficacy positively predicted study time. In contrast, the use of performance strategies negatively predicted engagement. The use of cooperative strategies did not predict learning behaviors. These results indicate that motivation, as well as the regulation of motivation, were important for learning outside the classroom. The effects of regulation of motivation and motivation on learning outside the classroom are discussed in light of the current findings.

Writing forces associated with four pencil grasp patterns in grade 4 children.

PubMed

Schwellnus, Heidi; Carnahan, Heather; Kushki, Azadeh; Polatajko, Helene; Missiuna, Cheryl; Chau, Tom

2013-01-01

OBJECTIVE. We investigated differences in handwriting kinetics, speed, and legibility among four pencil grasps after a 10-min copy task. METHOD. Seventy-four Grade 4 students completed a handwriting assessment before and after a copy task. Grip and axial forces were measured with an instrumented stylus and force-sensitive tablet. We used multiple linear regression to analyze the relationship between grasp pattern and grip and axial forces. RESULTS. We found no kinetic differences among grasps, whether considered individually or grouped by the number of fingers on the barrel. However, when grasps were grouped according to the thumb position, the adducted grasps exhibited higher mean grip and axial forces. CONCLUSION. Grip forces were generally similar across the different grasps. Kinetic differences resulting from thumb position seemed to have no bearing on speed and legibility. Interventions for handwriting difficulties should focus more on speed and letter formation than on grasp pattern. Copyright © 2013 by the American Occupational Therapy Association, Inc.

Handling limited datasets with neural networks in medical applications: A small-data approach.

PubMed

Shaikhina, Torgyn; Khovanova, Natalia A

2017-01-01

Single-centre studies in medical domain are often characterised by limited samples due to the complexity and high costs of patient data collection. Machine learning methods for regression modelling of small datasets (less than 10 observations per predictor variable) remain scarce. Our work bridges this gap by developing a novel framework for application of artificial neural networks (NNs) for regression tasks involving small medical datasets. In order to address the sporadic fluctuations and validation issues that appear in regression NNs trained on small datasets, the method of multiple runs and surrogate data analysis were proposed in this work. The approach was compared to the state-of-the-art ensemble NNs; the effect of dataset size on NN performance was also investigated. The proposed framework was applied for the prediction of compressive strength (CS) of femoral trabecular bone in patients suffering from severe osteoarthritis. The NN model was able to estimate the CS of osteoarthritic trabecular bone from its structural and biological properties with a standard error of 0.85MPa. When evaluated on independent test samples, the NN achieved accuracy of 98.3%, outperforming an ensemble NN model by 11%. We reproduce this result on CS data of another porous solid (concrete) and demonstrate that the proposed framework allows for an NN modelled with as few as 56 samples to generalise on 300 independent test samples with 86.5% accuracy, which is comparable to the performance of an NN developed with 18 times larger dataset (1030 samples). The significance of this work is two-fold: the practical application allows for non-destructive prediction of bone fracture risk, while the novel methodology extends beyond the task considered in this study and provides a general framework for application of regression NNs to medical problems characterised by limited dataset sizes. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Functional interactions of HIV-infection and methamphetamine dependence during motor programming.

PubMed

Archibald, Sarah L; Jacobson, Mark W; Fennema-Notestine, Christine; Ogasawara, Miki; Woods, Steven P; Letendre, Scott; Grant, Igor; Jernigan, Terry L

2012-04-30

Methamphetamine (METH) dependence is frequently comorbid with HIV infection and both have been linked to alterations of brain structure and function. In a previous study, we showed that the brain volume loss characteristic of HIV infection contrasts with METH-related volume increases in striatum and parietal cortex, suggesting distinct neurobiological responses to HIV and METH (Jernigan et al., 2005). Functional magnetic resonance imaging (fMRI) has the potential to reveal functional interactions between the effects of HIV and METH. In the present study, 50 participants were studied in four groups: an HIV+ group, a recently METH-dependent group, a dually affected group, and a group of unaffected community comparison subjects. An fMRI paradigm consisting of motor sequencing tasks of varying levels of complexity was administered to examine blood oxygenation level dependent (BOLD) changes. Within all groups, activity increased significantly with increasing task complexity in large clusters within sensorimotor and parietal cortex, basal ganglia, cerebellum, and cingulate. The task complexity effect was regressed on HIV status, METH status, and the HIV×METH interaction term in a simultaneous multiple regression. HIV was associated with less complexity-related activation in striatum, whereas METH was associated with less complexity-related activation in parietal regions. Significant interaction effects were observed in both cortical and subcortical regions; and, contrary to expectations, the complexity-related activation was less aberrant in dually affected than in single risk participants, in spite of comparable levels of neurocognitive impairment among the clinical groups. Thus, HIV and METH dependence, perhaps through their effects on dopaminergic systems, may have opposing functional effects on neural circuits involved in motor programming. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

The effect of question format and task difficulty on reasoning strategies and diagnostic performance in Internal Medicine residents.

PubMed

Heemskerk, Laura; Norman, Geoff; Chou, Sophia; Mintz, Marcy; Mandin, Henry; McLaughlin, Kevin

2008-11-01

Previous studies have suggested an association between reasoning strategies and diagnostic success, but the influence on this relationship of variables such as question format and task difficulty, has not been studied. Our objective was to study the association between question format, task difficulty, reasoning strategies and diagnostic success. Study participants were 13 Internal Medicine residents at the University of Calgary. Each was given eight problem-solving questions in four clinical presentations and were randomized to groups that differed only in the question format, such that a question presented as short answer (SA) to the first group was presented as extended matching (EM) to the second group. There were equal numbers of SA/EM questions and straightforward/difficult tasks. Participants performed think-aloud during diagnostic reasoning. Data were analyzed using multiple logistic regression. Question format was associated with reasoning strategies; hypothetico-deductive reasoning being used more frequently on EM questions and scheme-inductive reasoning on SA questions. For SA question, non-analytic reasoning alone was used more frequently to answer straightforward cases than difficult cases, whereas for EM questions no such association was observed. EM format and straightforward task increased the odds of diagnostic success, whereas hypothetico-deductive reasoning was associated with reduced odds of success. Question format and task difficulty both influence diagnostic reasoning strategies and studies that examine the effect of reasoning strategies on diagnostic success should control for these effects. Further studies are needed to investigate the effect of reasoning strategies on performance of different groups of learners.

Spatially aggregated multiclass pattern classification in functional MRI using optimally selected functional brain areas.

PubMed

Zheng, Weili; Ackley, Elena S; Martínez-Ramón, Manel; Posse, Stefan

2013-02-01

In previous works, boosting aggregation of classifier outputs from discrete brain areas has been demonstrated to reduce dimensionality and improve the robustness and accuracy of functional magnetic resonance imaging (fMRI) classification. However, dimensionality reduction and classification of mixed activation patterns of multiple classes remain challenging. In the present study, the goals were (a) to reduce dimensionality by combining feature reduction at the voxel level and backward elimination of optimally aggregated classifiers at the region level, (b) to compare region selection for spatially aggregated classification using boosting and partial least squares regression methods and (c) to resolve mixed activation patterns using probabilistic prediction of individual tasks. Brain activation maps from interleaved visual, motor, auditory and cognitive tasks were segmented into 144 functional regions. Feature selection reduced the number of feature voxels by more than 50%, leaving 95 regions. The two aggregation approaches further reduced the number of regions to 30, resulting in more than 75% reduction of classification time and misclassification rates of less than 3%. Boosting and partial least squares (PLS) were compared to select the most discriminative and the most task correlated regions, respectively. Successful task prediction in mixed activation patterns was feasible within the first block of task activation in real-time fMRI experiments. This methodology is suitable for sparsifying activation patterns in real-time fMRI and for neurofeedback from distributed networks of brain activation. Copyright © 2013 Elsevier Inc. All rights reserved.

Automatic identification of variables in epidemiological datasets using logic regression.

PubMed

Lorenz, Matthias W; Abdi, Negin Ashtiani; Scheckenbach, Frank; Pflug, Anja; Bülbül, Alpaslan; Catapano, Alberico L; Agewall, Stefan; Ezhov, Marat; Bots, Michiel L; Kiechl, Stefan; Orth, Andreas

2017-04-13

For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable. For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated. In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables. We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies.

[A comparative study of maintenance services using the data-mining technique].

PubMed

Cruz, Antonio M; Aguilera-Huertas, Wilmer A; Días-Mora, Darío A

2009-08-01

The main goal in this research was comparing two hospitals' maintenance service quality. One of them had a contract service; the other one had an in-house maintenance service. The authors followed the next stages when conducting this research: domain understanding, data characterisation and sample reduction, insight characterisation and building the TAT predictor. Multiple linear regression and clustering techniques were used for improving the efficiency of corrective maintenance tasks in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). The institution having an in-house maintenance service had better quality indicators than the contract maintenance service. There was lineal dependence between availability and service productivity.

Are we on the same page? The performance effects of congruence between supervisor and group trust.

PubMed

Carter, Min Z; Mossholder, Kevin W

2015-09-01

Taking a multiple-stakeholder perspective, we examined the effects of supervisor-work group trust congruence on groups' task and contextual performance using a polynomial regression and response surface analytical framework. We expected motivation experienced by work groups to mediate the positive influence of trust congruence on performance. Although hypothesized congruence effects on performance were more strongly supported for affective rather than for cognitive trust, we found significant indirect effects on performance (via work group motivation) for both types of trust. We discuss the performance effects of trust congruence and incongruence between supervisors and work groups, as well as implications for practice and future research. (c) 2015 APA, all rights reserved).

Balanced bilingualism and early age of second language acquisition as the underlying mechanisms of a bilingual executive control advantage: why variations in bilingual experiences matter

PubMed Central

Yow, W. Quin; Li, Xiaoqian

2015-01-01

Recent studies revealed inconsistent evidences of a bilingual advantage in executive processing. One potential source of explanation is the multifaceted experience of the bilinguals in these studies. This study seeks to test whether bilinguals who engage in language selection more frequently would perform better in executive control tasks than those bilinguals who engage in language selection less frequently. We examined the influence of the degree of bilingualism (i.e., language proficiency, frequency of use of two languages, and age of second language acquisition) on executive functioning in bilingual young adults using a comprehensive battery of executive control tasks. Seventy-two 18- to 25-years-old English–Mandarin bilinguals performed four computerized executive function (EF) tasks (Stroop, Eriksen flanker, number–letter switching, and n-back task) that measure the EF components: inhibition, mental-set shifting, and information updating and monitoring. Results from multiple regression analyses, structural equation modeling, and bootstrapping supported the positive association between age of second language acquisition and the interference cost in the Stroop task. Most importantly, we found a significant effect of balanced bilingualism (balanced usage of and balanced proficiency in two languages) on the Stroop and number–letter task (mixing cost only), indicating that a more balanced use and a more balanced level of proficiency in two languages resulted in better executive control skills in the adult bilinguals. We did not find any significant effect of bilingualism on flanker or n-back task. These findings provided important insights to the underlying mechanisms of the bilingual cognitive advantage hypothesis, demonstrating that regular experience with extensive practice in controlling attention to their two language systems results in better performance in related EFs such as inhibiting prepotent responses and global set-shifting. PMID:25767451

Balanced bilingualism and early age of second language acquisition as the underlying mechanisms of a bilingual executive control advantage: why variations in bilingual experiences matter.

PubMed

Yow, W Quin; Li, Xiaoqian

2015-01-01

Recent studies revealed inconsistent evidences of a bilingual advantage in executive processing. One potential source of explanation is the multifaceted experience of the bilinguals in these studies. This study seeks to test whether bilinguals who engage in language selection more frequently would perform better in executive control tasks than those bilinguals who engage in language selection less frequently. We examined the influence of the degree of bilingualism (i.e., language proficiency, frequency of use of two languages, and age of second language acquisition) on executive functioning in bilingual young adults using a comprehensive battery of executive control tasks. Seventy-two 18- to 25-years-old English-Mandarin bilinguals performed four computerized executive function (EF) tasks (Stroop, Eriksen flanker, number-letter switching, and n-back task) that measure the EF components: inhibition, mental-set shifting, and information updating and monitoring. Results from multiple regression analyses, structural equation modeling, and bootstrapping supported the positive association between age of second language acquisition and the interference cost in the Stroop task. Most importantly, we found a significant effect of balanced bilingualism (balanced usage of and balanced proficiency in two languages) on the Stroop and number-letter task (mixing cost only), indicating that a more balanced use and a more balanced level of proficiency in two languages resulted in better executive control skills in the adult bilinguals. We did not find any significant effect of bilingualism on flanker or n-back task. These findings provided important insights to the underlying mechanisms of the bilingual cognitive advantage hypothesis, demonstrating that regular experience with extensive practice in controlling attention to their two language systems results in better performance in related EFs such as inhibiting prepotent responses and global set-shifting.

ICA-Derived EEG Correlates to Mental Fatigue, Effort, and Workload in a Realistically Simulated Air Traffic Control Task.

PubMed

Dasari, Deepika; Shou, Guofa; Ding, Lei

2017-01-01

Electroencephalograph (EEG) has been increasingly studied to identify distinct mental factors when persons perform cognitively demanding tasks. However, most of these studies examined EEG correlates at channel domain, which suffers the limitation that EEG signals are the mixture of multiple underlying neuronal sources due to the volume conduction effect. Moreover, few studies have been conducted in real-world tasks. To precisely probe EEG correlates with specific neural substrates to mental factors in real-world tasks, the present study examined EEG correlates to three mental factors, i.e., mental fatigue [also known as time-on-task (TOT) effect], workload and effort, in EEG component signals, which were obtained using an independent component analysis (ICA) on high-density EEG data. EEG data were recorded when subjects performed a realistically simulated air traffic control (ATC) task for 2 h. Five EEG independent component (IC) signals that were associated with specific neural substrates (i.e., the frontal, central medial, motor, parietal, occipital areas) were identified. Their spectral powers at their corresponding dominant bands, i.e., the theta power of the frontal IC and the alpha power of the other four ICs, were detected to be correlated to mental workload and effort levels, measured by behavioral metrics. Meanwhile, a linear regression analysis indicated that spectral powers at five ICs significantly increased with TOT. These findings indicated that different levels of mental factors can be sensitively reflected in EEG signals associated with various brain functions, including visual perception, cognitive processing, and motor outputs, in real-world tasks. These results can potentially aid in the development of efficient operational interfaces to ensure productivity and safety in ATC and beyond.

Holistic rubric vs. analytic rubric for measuring clinical performance levels in medical students.

PubMed

Yune, So Jung; Lee, Sang Yeoup; Im, Sun Ju; Kam, Bee Sung; Baek, Sun Yong

2018-06-05

Task-specific checklists, holistic rubrics, and analytic rubrics are often used for performance assessments. We examined what factors evaluators consider important in holistic scoring of clinical performance assessment, and compared the usefulness of applying holistic and analytic rubrics respectively, and analytic rubrics in addition to task-specific checklists based on traditional standards. We compared the usefulness of a holistic rubric versus an analytic rubric in effectively measuring the clinical skill performances of 126 third-year medical students who participated in a clinical performance assessment conducted by Pusan National University School of Medicine. We conducted a questionnaire survey of 37 evaluators who used all three evaluation methods-holistic rubric, analytic rubric, and task-specific checklist-for each student. The relationship between the scores on the three evaluation methods was analyzed using Pearson's correlation. Inter-rater agreement was analyzed by Kappa index. The effect of holistic and analytic rubric scores on the task-specific checklist score was analyzed using multiple regression analysis. Evaluators perceived accuracy and proficiency to be major factors in objective structured clinical examinations evaluation, and history taking and physical examination to be major factors in clinical performance examinations evaluation. Holistic rubric scores were highly related to the scores of the task-specific checklist and analytic rubric. Relatively low agreement was found in clinical performance examinations compared to objective structured clinical examinations. Meanwhile, the holistic and analytic rubric scores explained 59.1% of the task-specific checklist score in objective structured clinical examinations and 51.6% in clinical performance examinations. The results show the usefulness of holistic and analytic rubrics in clinical performance assessment, which can be used in conjunction with task-specific checklists for more efficient evaluation.

Prediction of hearing outcomes by multiple regression analysis in patients with idiopathic sudden sensorineural hearing loss.

PubMed

Suzuki, Hideaki; Tabata, Takahisa; Koizumi, Hiroki; Hohchi, Nobusuke; Takeuchi, Shoko; Kitamura, Takuro; Fujino, Yoshihisa; Ohbuchi, Toyoaki

2014-12-01

This study aimed to create a multiple regression model for predicting hearing outcomes of idiopathic sudden sensorineural hearing loss (ISSNHL). The participants were 205 consecutive patients (205 ears) with ISSNHL (hearing level ≥ 40 dB, interval between onset and treatment ≤ 30 days). They received systemic steroid administration combined with intratympanic steroid injection. Data were examined by simple and multiple regression analyses. Three hearing indices (percentage hearing improvement, hearing gain, and posttreatment hearing level [HLpost]) and 7 prognostic factors (age, days from onset to treatment, initial hearing level, initial hearing level at low frequencies, initial hearing level at high frequencies, presence of vertigo, and contralateral hearing level) were included in the multiple regression analysis as dependent and explanatory variables, respectively. In the simple regression analysis, the percentage hearing improvement, hearing gain, and HLpost showed significant correlation with 2, 5, and 6 of the 7 prognostic factors, respectively. The multiple correlation coefficients were 0.396, 0.503, and 0.714 for the percentage hearing improvement, hearing gain, and HLpost, respectively. Predicted values of HLpost calculated by the multiple regression equation were reliable with 70% probability with a 40-dB-width prediction interval. Prediction of HLpost by the multiple regression model may be useful to estimate the hearing prognosis of ISSNHL. © The Author(s) 2014.

False Positives in Multiple Regression: Unanticipated Consequences of Measurement Error in the Predictor Variables

ERIC Educational Resources Information Center

Shear, Benjamin R.; Zumbo, Bruno D.

2013-01-01

Type I error rates in multiple regression, and hence the chance for false positive research findings, can be drastically inflated when multiple regression models are used to analyze data that contain random measurement error. This article shows the potential for inflated Type I error rates in commonly encountered scenarios and provides new…

Use of Multiple Regression and Use-Availability Analyses in Determining Habitat Selection by Gray Squirrels (Sciurus Carolinensis)

Treesearch

John W. Edwards; Susan C. Loeb; David C. Guynn

1994-01-01

Multiple regression and use-availability analyses are two methods for examining habitat selection. Use-availability analysis is commonly used to evaluate macrohabitat selection whereas multiple regression analysis can be used to determine microhabitat selection. We compared these techniques using behavioral observations (n = 5534) and telemetry locations (n = 2089) of...

Comparison of continuously acquired resting state and extracted analogues from active tasks.

PubMed

Ganger, Sebastian; Hahn, Andreas; Küblböck, Martin; Kranz, Georg S; Spies, Marie; Vanicek, Thomas; Seiger, René; Sladky, Ronald; Windischberger, Christian; Kasper, Siegfried; Lanzenberger, Rupert

2015-10-01

Functional connectivity analysis of brain networks has become an important tool for investigation of human brain function. Although functional connectivity computations are usually based on resting-state data, the application to task-specific fMRI has received growing attention. Three major methods for extraction of resting-state data from task-related signal have been proposed (1) usage of unmanipulated task data for functional connectivity; (2) regression against task effects, subsequently using the residuals; and (3) concatenation of baseline blocks located in-between task blocks. Despite widespread application in current research, consensus on which method best resembles resting-state seems to be missing. We, therefore, evaluated these techniques in a sample of 26 healthy controls measured at 7 Tesla. In addition to continuous resting-state, two different task paradigms were assessed (emotion discrimination and right finger-tapping) and five well-described networks were analyzed (default mode, thalamus, cuneus, sensorimotor, and auditory). Investigating the similarity to continuous resting-state (Dice, Intraclass correlation coefficient (ICC), R(2) ) showed that regression against task effects yields functional connectivity networks most alike to resting-state. However, all methods exhibited significant differences when compared to continuous resting-state and similarity metrics were lower than test-retest of two resting-state scans. Omitting global signal regression did not change these findings. Visually, the networks are highly similar, but through further investigation marked differences can be found. Therefore, our data does not support referring to resting-state when extracting signals from task designs, although functional connectivity computed from task-specific data may indeed yield interesting information. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Building Regression Models: The Importance of Graphics.

ERIC Educational Resources Information Center

Dunn, Richard

1989-01-01

Points out reasons for using graphical methods to teach simple and multiple regression analysis. Argues that a graphically oriented approach has considerable pedagogic advantages in the exposition of simple and multiple regression. Shows that graphical methods may play a central role in the process of building regression models. (Author/LS)

Testing Different Model Building Procedures Using Multiple Regression.

ERIC Educational Resources Information Center

Thayer, Jerome D.

The stepwise regression method of selecting predictors for computer assisted multiple regression analysis was compared with forward, backward, and best subsets regression, using 16 data sets. The results indicated the stepwise method was preferred because of its practical nature, when the models chosen by different selection methods were similar…

Decreasing Multicollinearity: A Method for Models with Multiplicative Functions.

ERIC Educational Resources Information Center

Smith, Kent W.; Sasaki, M. S.

1979-01-01

A method is proposed for overcoming the problem of multicollinearity in multiple regression equations where multiplicative independent terms are entered. The method is not a ridge regression solution. (JKS)

Virtual reality laparoscopy: which potential trainee starts with a higher proficiency level?

PubMed

Paschold, M; Schröder, M; Kauff, D W; Gorbauch, T; Herzer, M; Lang, H; Kneist, W

2011-09-01

Minimally invasive surgery requires technical skills distinct from those used in conventional surgery. The aim of this prospective study was to identify personal characteristics that may predict the attainable proficiency level of first-time virtual reality laparoscopy (VRL) trainees. Two hundred and seventy-nine consecutive undergraduate medical students without experience attended a standardized VRL training. Performance data of an abstract and a procedural task were correlated with possible predictive factors providing potential competence in VRL. Median global score requirement status was 86.7% (interquartile range (IQR) 75-93) for the abstract task and 74.4% (IQR 67-88) for the procedural task. Unadjusted analysis showed significant increase in the global score in both tasks for trainees who had a gaming console at home and frequently used it as well as for trainees who felt self-confident to assist in a laparoscopic operation. Multiple logistic regression analysis identified frequency of video gaming (often/frequently vs. rarely/not at all, odds ratio: abstract model 2.1 (95% confidence interval 1.2; 3.6), P = 0.009; virtual reality operation procedure 2.4 (95% confidence interval 1.3; 4.2), P = 0.003) as a predictive factor for VRL performance. Frequency of video gaming is associated with quality of first-time VRL performance. Video game experience may be used as trainee selection criteria for tailored concepts of VRL training programs.

Factors Associated With Community Health Worker Performance Differ by Task in a Multi-Tasked Setting in Rural Zimbabwe.

PubMed

Kambarami, Rukundo A; Mbuya, Mduduzi Nn; Pelletier, David; Fundira, Dadirai; Tavengwa, Naume V; Stoltzfus, Rebecca J

2016-06-20

Zimbabwe, like most low-income countries, faces health worker shortages. Community health workers (CHWs) bridge this gap by delivering essential health services and nutrition interventions to communities. However, as workloads increase, CHWs' ability to provide quality services may be compromised. We studied influences upon CHWs' performance related to pregnancy surveillance and nutrition and hygiene education in rural Zimbabwe. In the context of a cluster-randomized trial conducted in 2 rural districts between November 2012 and March 2015, 342 government-employed CHWs identified and referred pregnant women for early antenatal care and delivered household-level behavior change lessons about infant feeding and hygiene to more than 5,000 women. In 2013, we conducted a survey among 322 of the CHWs to assess the association between demographic and work characteristics and task performance. Exploratory factor analyses of the Likert-type survey questions produced 8 distinct and reliable constructs of job satisfaction and motivation, supervision, peer support, and feedback (Cronbach α range, 0.68 to 0.92). Pregnancy surveillance performance was assessed from pregnancy referrals, and nutrition and hygiene education performance was assessed by taking the average summative score (range, 5 to 30) of lesson delivery observations completed by a nurse supervisor using a 6-item Likert-type checklist. Poisson and multiple linear regressions were used to test associations between CHW demographic and work characteristics and performance. CHWs who referred more pregnant women were female, unmarried, under 40 years old, from larger households, and of longer tenure. They also perceived work resources to be adequate and received positive feedback from supervisors and the community, but they were less satisfied with remuneration. CHWs with high scores on behavior change lesson delivery were from smaller households, and they received more supportive supervision but less operational supervision. Measures of job satisfaction and motivation were not associated with either task. Among CHWs responsible for multiple tasks in rural Zimbabwe, factors associated with performance of one task were not the same as those associated with performance of another task. Our methods and findings illustrate ways to examine heterogeneity in CHW performance and to identify organizational factors associated with quality of program delivery. © Kambarami et al.

Factors Associated With Community Health Worker Performance Differ by Task in a Multi-Tasked Setting in Rural Zimbabwe

PubMed Central

Kambarami, Rukundo A; Mbuya, Mduduzi NN; Pelletier, David; Fundira, Dadirai; Tavengwa, Naume V; Stoltzfus, Rebecca J

2016-01-01

ABSTRACT Background: Zimbabwe, like most low-income countries, faces health worker shortages. Community health workers (CHWs) bridge this gap by delivering essential health services and nutrition interventions to communities. However, as workloads increase, CHWs’ ability to provide quality services may be compromised. We studied influences upon CHWs’ performance related to pregnancy surveillance and nutrition and hygiene education in rural Zimbabwe. Methods: In the context of a cluster-randomized trial conducted in 2 rural districts between November 2012 and March 2015, 342 government-employed CHWs identified and referred pregnant women for early antenatal care and delivered household-level behavior change lessons about infant feeding and hygiene to more than 5,000 women. In 2013, we conducted a survey among 322 of the CHWs to assess the association between demographic and work characteristics and task performance. Exploratory factor analyses of the Likert-type survey questions produced 8 distinct and reliable constructs of job satisfaction and motivation, supervision, peer support, and feedback (Cronbach α range, 0.68 to 0.92). Pregnancy surveillance performance was assessed from pregnancy referrals, and nutrition and hygiene education performance was assessed by taking the average summative score (range, 5 to 30) of lesson delivery observations completed by a nurse supervisor using a 6-item Likert-type checklist. Poisson and multiple linear regressions were used to test associations between CHW demographic and work characteristics and performance. Results: CHWs who referred more pregnant women were female, unmarried, under 40 years old, from larger households, and of longer tenure. They also perceived work resources to be adequate and received positive feedback from supervisors and the community, but they were less satisfied with remuneration. CHWs with high scores on behavior change lesson delivery were from smaller households, and they received more supportive supervision but less operational supervision. Measures of job satisfaction and motivation were not associated with either task. Conclusion: Among CHWs responsible for multiple tasks in rural Zimbabwe, factors associated with performance of one task were not the same as those associated with performance of another task. Our methods and findings illustrate ways to examine heterogeneity in CHW performance and to identify organizational factors associated with quality of program delivery. PMID:27353617

The Use of Digital Technology in Finding Multiple Paths to Solve and Extend an Equilateral Triangle Task

ERIC Educational Resources Information Center

Santos-Trigo, Manuel; Reyes-Rodriguez, Aaron

2016-01-01

Mathematical tasks are crucial elements for teachers to orient, foster and assess students' processes to comprehend and develop mathematical knowledge. During the process of working and solving a task, searching for or discussing multiple solution paths becomes a powerful strategy for students to engage in mathematical thinking. A simple task that…

Interference between a fast-paced spatial puzzle task and verbal memory demands.

PubMed

Epling, Samantha L; Blakely, Megan J; Russell, Paul N; Helton, William S

2017-06-01

Research continues to provide evidence that people are poor multi-taskers. Cognitive resource theory is a common explanation for the inability to efficiently perform multiple tasks at the same time. This theory proposes that one's limited supply of cognitive resources can be utilized faster than it is replenished, which results in a performance decline, particularly when these limited resources must be allocated among multiple tasks. Researchers have proposed both domain-specific, for example, spatial versus verbal processing resources, and domain general cognitive resources. In the present research, we investigated whether a spatial puzzle task performed simultaneously with a verbal recall task would impair performance in either task or both tasks, compared to performance on the tasks individually. As hypothesized, a reduction in word recall was found when dual-tasking, though performance on the puzzle task did not significantly differ between the single- and dual-task conditions. This is consistent, in part, with both a general resource theory and a Multiple Resource Theory, but further work is required to better understand the cognitive processing system. The employment of the recall task in the dual-task paradigm with a variety of secondary tasks will help to continue mapping out the specificity (or lack thereof) of cognitive resources utilized in various mental and physical tasks.

Multiple-Instance Regression with Structured Data

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; Lane, Terran; Roper, Alex

2008-01-01

We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) operates on a set of bags with real-valued labels, each containing a set of unlabeled items, in which the relevance of each item to its bag label is unknown. The goal is to predict the labels of new bags from their contents. Unlike previous MIR methods, MI-ClusterRegress can operate on bags that are structured in that they contain items drawn from a number of distinct (but unknown) distributions. MI-ClusterRegress simultaneously learns a model of the bag's internal structure, the relevance of each item, and a regression model that accurately predicts labels for new bags. We evaluated this approach on the challenging MIR problem of crop yield prediction from remote sensing data. MI-ClusterRegress provided predictions that were more accurate than those obtained with non-multiple-instance approaches or MIR methods that do not model the bag structure.

Measuring more than we know? An examination of the motivational and situational influences in science achievement

NASA Astrophysics Data System (ADS)

Haydel, Angela Michelle

The purpose of this dissertation was to advance theoretical understanding about fit between the personal resources of individuals and the characteristics of science achievement tasks. Testing continues to be pervasive in schools, yet we know little about how students perceive tests and what they think and feel while they are actually working on test items. This study focused on both the personal (cognitive and motivational) and situational factors that may contribute to individual differences in achievement-related outcomes. 387 eighth grade students first completed a survey including measures of science achievement goals, capability beliefs, efficacy related to multiple-choice items and performance assessments, validity beliefs about multiple-choice items and performance assessments, and other perceptions of these item formats. Students then completed science achievement tests including multiple-choice items and two performance assessments. A sample of students was asked to verbalize both thoughts and feelings as they worked through the test items. These think-alouds were transcribed and coded for evidence of cognitive, metacognitive and motivational engagement. Following each test, all students completed measures of effort, mood, energy level and strategy use during testing. Students reported that performance assessments were more challenging, authentic, interesting and valid than multiple-choice tests. They also believed that comparisons between students were easier using multiple-choice items. Overall, students tried harder, felt better, had higher levels of energy and used more strategies while working on performance assessments. Findings suggested that performance assessments might be more congruent with a mastery achievement goal orientation, while multiple-choice tests might be more congruent with a performance achievement goal orientation. A variable-centered analytic approach including regression analyses provided information about how students, on average, who differed in terms of their teachers' ratings of their science ability, achievement goals, capability beliefs and experiences with science achievement tasks perceived, engaged in, and performed on multiple-choice items and performance assessments. Person-centered analyses provided information about the perceptions, engagement and performance of subgroups of individuals who had different motivational characteristics. Generally, students' personal goals and capability beliefs related more strongly to test perceptions, but not performance, while teacher ratings of ability and test-specific beliefs related to performance.

Reducing the number of reconstructions needed for estimating channelized observer performance

NASA Astrophysics Data System (ADS)

Pineda, Angel R.; Miedema, Hope; Brenner, Melissa; Altaf, Sana

2018-03-01

A challenge for task-based optimization is the time required for each reconstructed image in applications where reconstructions are time consuming. Our goal is to reduce the number of reconstructions needed to estimate the area under the receiver operating characteristic curve (AUC) of the infinitely-trained optimal channelized linear observer. We explore the use of classifiers which either do not invert the channel covariance matrix or do feature selection. We also study the assumption that multiple low contrast signals in the same image of a non-linear reconstruction do not significantly change the estimate of the AUC. We compared the AUC of several classifiers (Hotelling, logistic regression, logistic regression using Firth bias reduction and the least absolute shrinkage and selection operator (LASSO)) with a small number of observations both for normal simulated data and images from a total variation reconstruction in magnetic resonance imaging (MRI). We used 10 Laguerre-Gauss channels and the Mann-Whitney estimator for AUC. For this data, our results show that at small sample sizes feature selection using the LASSO technique can decrease bias of the AUC estimation with increased variance and that for large sample sizes the difference between these classifiers is small. We also compared the use of multiple signals in a single reconstructed image to reduce the number of reconstructions in a total variation reconstruction for accelerated imaging in MRI. We found that AUC estimation using multiple low contrast signals in the same image resulted in similar AUC estimates as doing a single reconstruction per signal leading to a 13x reduction in the number of reconstructions needed.

Convolutional neural network regression for short-axis left ventricle segmentation in cardiac cine MR sequences.

PubMed

Tan, Li Kuo; Liew, Yih Miin; Lim, Einly; McLaughlin, Robert A

2017-07-01

Automated left ventricular (LV) segmentation is crucial for efficient quantification of cardiac function and morphology to aid subsequent management of cardiac pathologies. In this paper, we parameterize the complete (all short axis slices and phases) LV segmentation task in terms of the radial distances between the LV centerpoint and the endo- and epicardial contours in polar space. We then utilize convolutional neural network regression to infer these parameters. Utilizing parameter regression, as opposed to conventional pixel classification, allows the network to inherently reflect domain-specific physical constraints. We have benchmarked our approach primarily against the publicly-available left ventricle segmentation challenge (LVSC) dataset, which consists of 100 training and 100 validation cardiac MRI cases representing a heterogeneous mix of cardiac pathologies and imaging parameters across multiple centers. Our approach attained a .77 Jaccard index, which is the highest published overall result in comparison to other automated algorithms. To test general applicability, we also evaluated against the Kaggle Second Annual Data Science Bowl, where the evaluation metric was the indirect clinical measures of LV volume rather than direct myocardial contours. Our approach attained a Continuous Ranked Probability Score (CRPS) of .0124, which would have ranked tenth in the original challenge. With this we demonstrate the effectiveness of convolutional neural network regression paired with domain-specific features in clinical segmentation. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting story goodness performance from cognitive measures following traumatic brain injury.

PubMed

Lê, Karen; Coelho, Carl; Mozeiko, Jennifer; Krueger, Frank; Grafman, Jordan

2012-05-01

This study examined the prediction of performance on measures of the Story Goodness Index (SGI; Lê, Coelho, Mozeiko, & Grafman, 2011) from executive function (EF) and memory measures following traumatic brain injury (TBI). It was hypothesized that EF and memory measures would significantly predict SGI outcomes. One hundred sixty-seven individuals with TBI participated in the study. Story retellings were analyzed using the SGI protocol. Three cognitive measures--Delis-Kaplan Executive Function System (D-KEFS; Delis, Kaplan, & Kramer, 2001) Sorting Test, Wechsler Memory Scale--Third Edition (WMS-III; Wechsler, 1997) Working Memory Primary Index (WMI), and WMS-III Immediate Memory Primary Index (IMI)--were entered into a multiple linear regression model for each discourse measure. Two sets of regression analyses were performed, the first with the Sorting Test as the first predictor and the second with it as the last. The first set of regression analyses identified the Sorting Test and IMI as the only significant predictors of performance on measures of the SGI. The second set identified all measures as significant predictors when evaluating each step of the regression function. The cognitive variables predicted performance on the SGI measures, although there were differences in the amount of explained variance. The results (a) suggest that storytelling ability draws on a number of underlying skills and (b) underscore the importance of using discrete cognitive tasks rather than broad cognitive indices to investigate the cognitive substrates of discourse.

Better dual-task processing in simultaneous interpreters

PubMed Central

Strobach, Tilo; Becker, Maxi; Schubert, Torsten; Kühn, Simone

2015-01-01

Simultaneous interpreting (SI) is a highly complex activity and requires the performance and coordination of multiple, simultaneous tasks: analysis and understanding of the discourse in a first language, reformulating linguistic material, storing of intermediate processing steps, and language production in a second language among others. It is, however, an open issue whether persons with experience in SI possess superior skills in coordination of multiple tasks and whether they are able to transfer these skills to lab-based dual-task situations. Within the present study, we set out to explore whether interpreting experience is associated with related higher-order executive functioning in the context of dual-task situations of the Psychological Refractory Period (PRP) type. In this PRP situation, we found faster reactions times in participants with experience in simultaneous interpretation in contrast to control participants without such experience. Thus, simultaneous interpreters possess superior skills in coordination of multiple tasks in lab-based dual-task situations. PMID:26528232

Efficient Symbolic Task Planning for Multiple Mobile Robots

DTIC Science & Technology

2016-12-13

Efficient Symbolic Task Planning for Multiple Mobile Robots Yuqian Jiang December 13, 2016 Abstract Symbolic task planning enables a robot to make...high-level deci- sions toward a complex goal by computing a sequence of actions with minimum expected costs. This thesis builds on a single- robot ...time complexity of optimal planning for multiple mobile robots . In this thesis we first investigate the performance of the state-of-the-art solvers of

Research on air and missile defense task allocation based on extended contract net protocol

NASA Astrophysics Data System (ADS)

Zhang, Yunzhi; Wang, Gang

2017-10-01

Based on the background of air and missile defense distributed element corporative engagement, the interception task allocation problem of multiple weapon units with multiple targets under network condition is analyzed. Firstly, a mathematical model of task allocation is established by combat task decomposition. Secondly, the initialization assignment based on auction contract and the adjustment allocation scheme based on swap contract were introduced to the task allocation. Finally, through the simulation calculation of typical situation, the model can be used to solve the task allocation problem in complex combat environment.

Impairment of visuospatial/visuoconstructional skills in multiple sclerosis patients: the correlation with regional lesion load and subcortical atrophy.

PubMed

Marasescu, R; Cerezo Garcia, M; Aladro Benito, Y

2016-04-01

About 20% to 26% of patients with multiple sclerosis (MS) show alterations in visuospatial/visuoconstructive (VS-VC) skills even though temporo-parieto-occipital impairment is a frequent finding in magnetic resonance imaging. No studies have specifically analysed the relationship between these functions and lesion volume (LV) in these specific brain areas. To evaluate the relationship between VS-VC impairment and magnetic resonance imaging temporo-parieto-occipital LV with subcortical atrophy in patients with MS. Of 100 MS patients undergoing a routine neuropsychological evaluation, 21 were selected because they displayed VS-VC impairments in the following tests: Incomplete picture, Block design (WAIS-III), and Rey-Osterrieth complex figure test. We also selected 13 MS patients without cognitive impairment (control group). Regional LV was measured in FLAIR and T1-weighted images using a semiautomated method; subcortical atrophy was measured by bicaudate ratio and third ventricle width. Partial correlations (controlling for age and years of school) and linear regression analysis were employed to analyse correlations between magnetic resonance imaging parameters and cognitive performance. All measures of LV and brain atrophy were significantly higher in patients with cognitive impairment. Regional LV, bicaudate ratio, and third ventricle width are significantly and inversely correlated with cognitive performance; the strongest correlation was between third ventricle width and VC performance (Block design: P=.001; Rey-Osterrieth complex figure: P<.000). In the multivariate analysis, third ventricle width only had a significant effect on performance of VC tasks (Block design: P=.000; Rey-Osterrieth complex figure: P=.000), and regional FLAIR VL was linked to the VS task (Incomplete picture; P=.002). Measures of subcortical atrophy explain the variations in performance on visuocostructive tasks, and regional FLAIR VL measures are linked to VS tasks. Copyright © 2015 Sociedad Española de Neurología. Published by Elsevier España, S.L.U. All rights reserved.

Context-Dependent Upper Limb Prosthesis Control for Natural and Robust Use.

PubMed

Amsuess, Sebastian; Vujaklija, Ivan; Goebel, Peter; Roche, Aidan D; Graimann, Bernhard; Aszmann, Oskar C; Farina, Dario

2016-07-01

Pattern recognition and regression methods applied to the surface EMG have been used for estimating the user intended motor tasks across multiple degrees of freedom (DOF), for prosthetic control. While these methods are effective in several conditions, they are still characterized by some shortcomings. In this study we propose a methodology that combines these two approaches for mutually alleviating their limitations. This resulted in a control method capable of context-dependent movement estimation that switched automatically between sequential (one DOF at a time) or simultaneous (multiple DOF) prosthesis control, based on an online estimation of signal dimensionality. The proposed method was evaluated in scenarios close to real-life situations, with the control of a physical prosthesis in applied tasks of varying difficulties. Test prostheses were individually manufactured for both able-bodied and transradial amputee subjects. With these prostheses, two amputees performed the Southampton Hand Assessment Procedure test with scores of 58 and 71 points. The five able-bodied individuals performed standardized tests, such as the box&block and clothes pin test, reducing the completion times by up to 30%, with respect to using a state-of-the-art pure sequential control algorithm. Apart from facilitating fast simultaneous movements, the proposed control scheme was also more intuitive to use, since human movements are predominated by simultaneous activations across joints. The proposed method thus represents a significant step towards intelligent, intuitive and natural control of upper limb prostheses.

From rational numbers to algebra: separable contributions of decimal magnitude and relational understanding of fractions.

PubMed

DeWolf, Melissa; Bassok, Miriam; Holyoak, Keith J

2015-05-01

To understand the development of mathematical cognition and to improve instructional practices, it is critical to identify early predictors of difficulty in learning complex mathematical topics such as algebra. Recent work has shown that performance with fractions on a number line estimation task predicts algebra performance, whereas performance with whole numbers on similar estimation tasks does not. We sought to distinguish more specific precursors to algebra by measuring multiple aspects of knowledge about rational numbers. Because fractions are the first numbers that are relational expressions to which students are exposed, we investigated how understanding the relational bipartite format (a/b) of fractions might connect to later algebra performance. We presented middle school students with a battery of tests designed to measure relational understanding of fractions, procedural knowledge of fractions, and placement of fractions, decimals, and whole numbers onto number lines as well as algebra performance. Multiple regression analyses revealed that the best predictors of algebra performance were measures of relational fraction knowledge and ability to place decimals (not fractions or whole numbers) onto number lines. These findings suggest that at least two specific components of knowledge about rational numbers--relational understanding (best captured by fractions) and grasp of unidimensional magnitude (best captured by decimals)--can be linked to early success with algebraic expressions. Copyright © 2015 Elsevier Inc. All rights reserved.

A Quantile Regression Approach to Understanding the Relations Between Morphological Awareness, Vocabulary, and Reading Comprehension in Adult Basic Education Students

PubMed Central

Tighe, Elizabeth L.; Schatschneider, Christopher

2015-01-01

The purpose of this study was to investigate the joint and unique contributions of morphological awareness and vocabulary knowledge at five reading comprehension levels in Adult Basic Education (ABE) students. We introduce the statistical technique of multiple quantile regression, which enabled us to assess the predictive utility of morphological awareness and vocabulary knowledge at multiple points (quantiles) along the continuous distribution of reading comprehension. To demonstrate the efficacy of our multiple quantile regression analysis, we compared and contrasted our results with a traditional multiple regression analytic approach. Our results indicated that morphological awareness and vocabulary knowledge accounted for a large portion of the variance (82-95%) in reading comprehension skills across all quantiles. Morphological awareness exhibited the greatest unique predictive ability at lower levels of reading comprehension whereas vocabulary knowledge exhibited the greatest unique predictive ability at higher levels of reading comprehension. These results indicate the utility of using multiple quantile regression to assess trajectories of component skills across multiple levels of reading comprehension. The implications of our findings for ABE programs are discussed. PMID:25351773

Job compensable factors and factor weights derived from job analysis data.

PubMed

Chi, Chia-Fen; Chang, Tin-Chang; Hsia, Ping-Ling; Song, Jen-Chieh

2007-06-01

Government data on 1,039 job titles in Taiwan were analyzed to assess possible relationships between job attributes and compensation. For each job title, 79 specific variables in six major classes (required education and experience, aptitude, interest, work temperament, physical demands, task environment) were coded to derive the statistical predictors of wage for managers, professionals, technical, clerical, service, farm, craft, operatives, and other workers. Of the 79 variables, only 23 significantly related to pay rate were subjected to a factor and multiple regression analysis for predicting monthly wages. Given the heterogeneous nature of collected job titles, a 4-factor solution (occupational knowledge and skills, human relations skills, work schedule hardships, physical hardships) explaining 43.8% of the total variance but predicting only 23.7% of the monthly pay rate was derived. On the other hand, multiple regression with 9 job analysis items (required education, professional training, professional certificate, professional experience, coordinating, leadership and directing, demand on hearing, proportion of shift working indoors, outdoors and others, rotating shift) better predicted pay and explained 32.5% of the variance. A direct comparison of factors and subfactors of job evaluation plans indicated mental effort and responsibility (accountability) had not been measured with the current job analysis data. Cross-validation of job evaluation factors and ratings with the wage rates is required to calibrate both.

ℓ(p)-Norm multikernel learning approach for stock market price forecasting.

PubMed

Shao, Xigao; Wu, Kun; Liao, Bifeng

2012-01-01

Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ(1)-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ(p)-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ(1)-norm multiple support vector regression model.

Multiple Types of Memory and Everyday Functional Assessment in Older Adults.

PubMed

Beaver, Jenna; Schmitter-Edgecombe, Maureen

2017-06-01

Current proxy measures for assessing everyday functioning (e.g., questionnaires, performance-based measures, and direct observation) show discrepancies in their rating of functional status. The present study investigated the relationship between multiple proxy measures of functional status and content memory (i.e., memory for information), temporal order memory, and prospective memory in an older adult sample. A total of 197 community-dwelling older adults who did (n = 45) or did not meet (n = 152) criteria for mild cognitive impairment (MCI), completed six different assessments of functional status (two questionnaires, two performance-based tasks, and two direct observation tasks) as well as experimental measures of content memory, prospective memory, and temporal order memory. After controlling for demographics and content memory, the temporal order and prospective memory measures explained a significant amount of variance in all proxy functional status measures. When all variables were entered into the regression analyses, content memory and prospective memory were found to be significant predictors of all measures of functional status, whereas temporal order memory was a significant predictor for the questionnaire and direct observation measures, but not performance-based measures. The results suggest that direct observation and questionnaire measures may be able to capture components of everyday functioning that require context and temporal sequencing abilities, such as multi-tasking, that are not as well captured in many current laboratory performance-based measures of functional status. Future research should aim to inform the development and use of maximally effective and valid proxy measures of functional ability. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Effects of Classroom Practices on Reading Comprehension, Engagement, and Motivations for Adolescents

PubMed Central

Guthrie, John T.; Klauda, Susan Lutz

2014-01-01

We investigated the roles of classroom supports for multiple motivations and engagement in students’ informational text comprehension, motivation, and engagement. A composite of classroom contextual variables consisting of instructional support for choice, importance, collaboration, and competence, accompanied by cognitive scaffolding for informational text comprehension, was provided in four-week instructional units for 615 grade 7 students. These classroom motivational-engagement supports were implemented within integrated literacy/history instruction in the Concept-Oriented Reading Instruction (CORI) framework. CORI increased informational text comprehension compared with traditional instruction (TI) in a switching replications experimental design. Students’ perceptions of the motivational-engagement supports were associated with increases in students’ intrinsic motivation, value, perceived competence, and increased positive engagement (dedication) more markedly in CORI than in TI, according to multiple regression analyses. Results extended the evidence for the effectiveness of CORI to literacy/history subject matter and informational text comprehension among middle school students. The experimental effects in classroom contexts confirmed effects from task-specific, situated experimental studies in the literature. PMID:25506087

Classification of arrhythmia using hybrid networks.

PubMed

Haseena, Hassan H; Joseph, Paul K; Mathew, Abraham T

2011-12-01

Reliable detection of arrhythmias based on digital processing of Electrocardiogram (ECG) signals is vital in providing suitable and timely treatment to a cardiac patient. Due to corruption of ECG signals with multiple frequency noise and presence of multiple arrhythmic events in a cardiac rhythm, computerized interpretation of abnormal ECG rhythms is a challenging task. This paper focuses a Fuzzy C- Mean (FCM) clustered Probabilistic Neural Network (PNN) and Multi Layered Feed Forward Network (MLFFN) for the discrimination of eight types of ECG beats. Parameters such as fourth order Auto Regressive (AR) coefficients along with Spectral Entropy (SE) are extracted from each ECG beat and feature reduction has been carried out using FCM clustering. The cluster centers form the input of neural network classifiers. The extensive analysis of Massachusetts Institute of Technology- Beth Israel Hospital (MIT-BIH) arrhythmia database shows that FCM clustered PNNs is superior in cardiac arrhythmia classification than FCM clustered MLFFN with an overall accuracy of 99.05%, 97.14%, respectively.

Effects of Classroom Practices on Reading Comprehension, Engagement, and Motivations for Adolescents.

PubMed

Guthrie, John T; Klauda, Susan Lutz

2014-10-01

We investigated the roles of classroom supports for multiple motivations and engagement in students' informational text comprehension, motivation, and engagement. A composite of classroom contextual variables consisting of instructional support for choice, importance, collaboration, and competence, accompanied by cognitive scaffolding for informational text comprehension, was provided in four-week instructional units for 615 grade 7 students. These classroom motivational-engagement supports were implemented within integrated literacy/history instruction in the Concept-Oriented Reading Instruction (CORI) framework. CORI increased informational text comprehension compared with traditional instruction (TI) in a switching replications experimental design. Students' perceptions of the motivational-engagement supports were associated with increases in students' intrinsic motivation, value, perceived competence, and increased positive engagement (dedication) more markedly in CORI than in TI, according to multiple regression analyses. Results extended the evidence for the effectiveness of CORI to literacy/history subject matter and informational text comprehension among middle school students. The experimental effects in classroom contexts confirmed effects from task-specific, situated experimental studies in the literature.

Predictive performance models and multiple task performance

NASA Technical Reports Server (NTRS)

Wickens, Christopher D.; Larish, Inge; Contorer, Aaron

1989-01-01

Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.

Using a Personal Digital Assistant to Increase Completion of Novel Tasks and Independent Transitioning by Students with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Mechling, Linda C.; Savidge, Erin J.

2011-01-01

The purpose of this study was to evaluate the use of a Personal Digital Assistant with multiple prompt levels to increase completion of novel task boxes and transitioning within and between tasks. The study used a multiple probe design across three sets of task boxes replicated with three students with a diagnosis of autism spectrum disorder.…

Bias in discriminating very mild dementia for older adults with different levels of education in Hong Kong.

PubMed

Chang, Jianfang; Tse, Chi-Shing; Leung, Grace Tak Yu; Fung, Ada Wai Tung; Hau, Kit-Tai; Chiu, Helen Fung Kum; Lam, Linda Chiu Wa

2014-06-01

Education has a profound effect on older adults' cognitive performance. In Hong Kong, some dementia screening tasks were originally designed for developed population with, on average, higher education. We compared the screening power of these tasks for Chinese older adults with different levels of education. Community-dwelling older adults who were healthy (N = 383) and with very mild dementia (N = 405) performed the following tasks: Mini-Mental State Examination, Alzheimer's Disease Assessment Scale-Cognitive subscales, Verbal Fluency, Abstract Thinking, and Visual/Digit Span. Logistic regression was used to examine the power of these tasks to predict Clinical Dementia Rating (CDR 0.5 vs. 0). Logistic regression analysis showed that while the screening power of the total scores in all tasks was similar for high and low education groups, there were education biases in some items of these tasks. The differential screening power in high and low education groups was not identical across items in some tasks. Thus, in cognitive assessments, we should exercise great caution when using these potentially biased items for older adults with limited education.

Novel Analog For Muscle Deconditioning

NASA Technical Reports Server (NTRS)

Ploutz-Snyder, Lori; Ryder, Jeff; Buxton, Roxanne; Redd, Elizabeth; Scott-Pandorf, Melissa; Hackney, Kyle; Fiedler, James; Bloomberg, Jacob

2010-01-01

Existing models of muscle deconditioning are cumbersome and expensive (ex: bedrest). We propose a new model utilizing a weighted suit to manipulate strength, power or endurance (function) relative to body weight (BW). Methods: 20 subjects performed 7 occupational astronaut tasks while wearing a suit weighted with 0-120% of BW. Models of the full relationship between muscle function/BW and task completion time were developed using fractional polynomial regression and verified by the addition of pre- and post-flight astronaut performance data using the same tasks. Spline regression was used to identify muscle function thresholds below which task performance was impaired. Results: Thresholds of performance decline were identified for each task. Seated egress & walk (most difficult task) showed thresholds of: leg press (LP) isometric peak force/BW of 18 N/kg, LP power/BW of 18 W/kg, LP work/ BW of 79 J/kg, knee extension (KE) isokinetic/BW of 6 Nm/Kg and KE torque/BW of 1.9 Nm/kg. Conclusions: Laboratory manipulation of strength / BW has promise as an appropriate analog for spaceflight-induced loss of muscle function for predicting occupational task performance and establishing operationally relevant exercise targets.

Multiple-object tracking while driving: the multiple-vehicle tracking task.

PubMed

Lochner, Martin J; Trick, Lana M

2014-11-01

Many contend that driving an automobile involves multiple-object tracking. At this point, no one has tested this idea, and it is unclear how multiple-object tracking would coordinate with the other activities involved in driving. To address some of the initial and most basic questions about multiple-object tracking while driving, we modified the tracking task for use in a driving simulator, creating the multiple-vehicle tracking task. In Experiment 1, we employed a dual-task methodology to determine whether there was interference between tracking and driving. Findings suggest that although it is possible to track multiple vehicles while driving, driving reduces tracking performance, and tracking compromises headway and lane position maintenance while driving. Modified change-detection paradigms were used to assess whether there were change localization advantages for tracked targets in multiple-vehicle tracking. When changes occurred during a blanking interval, drivers were more accurate (Experiment 2a) and ~250 ms faster (Experiment 2b) at locating the vehicle that changed when it was a target rather than a distractor in tracking. In a more realistic driving task where drivers had to brake in response to the sudden onset of brake lights in one of the lead vehicles, drivers were more accurate at localizing the vehicle that braked if it was a tracking target, although there was no advantage in terms of braking response time. Overall, results suggest that multiple-object tracking is possible while driving and perhaps even advantageous in some situations, but further research is required to determine whether multiple-object tracking is actually used in day-to-day driving.

Mental chronometry with simple linear regression.

PubMed

Chen, J Y

1997-10-01

Typically, mental chronometry is performed by means of introducing an independent variable postulated to affect selectively some stage of a presumed multistage process. However, the effect could be a global one that spreads proportionally over all stages of the process. Currently, there is no method to test this possibility although simple linear regression might serve the purpose. In the present study, the regression approach was tested with tasks (memory scanning and mental rotation) that involved a selective effect and with a task (word superiority effect) that involved a global effect, by the dominant theories. The results indicate (1) the manipulation of the size of a memory set or of angular disparity affects the intercept of the regression function that relates the times for memory scanning with different set sizes or for mental rotation with different angular disparities and (2) the manipulation of context affects the slope of the regression function that relates the times for detecting a target character under word and nonword conditions. These ratify the regression approach as a useful method for doing mental chronometry.

Advanced statistics: linear regression, part II: multiple linear regression.

PubMed

Marill, Keith A

2004-01-01

The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

Relations of Instructional Tasks to Teacher-Student Discourse in Mathematics Classrooms of Chinese Primary Schools

ERIC Educational Resources Information Center

Ni, Yujing; Zhou, Dehui; Li, Xiaoqing; Li, Qiong

2014-01-01

This study, based on observation of 90 fifth-grade mathematics classes in Chinese elementary schools, examined how the task features, high cognitive demand, multiple representations, and multiple solution methods may relate to classroom discourse. Results indicate that high cognitive demand tasks were associated with teachers' use higher order…

Modeling Polytomous Item Responses Using Simultaneously Estimated Multinomial Logistic Regression Models

ERIC Educational Resources Information Center

Anderson, Carolyn J.; Verkuilen, Jay; Peyton, Buddy L.

2010-01-01

Survey items with multiple response categories and multiple-choice test questions are ubiquitous in psychological and educational research. We illustrate the use of log-multiplicative association (LMA) models that are extensions of the well-known multinomial logistic regression model for multiple dependent outcome variables to reanalyze a set of…

Arterial spin labeling reveals relationships between resting cerebral perfusion and motor learning in Parkinson's disease.

PubMed

Barzgari, Amy; Sojkova, Jitka; Maritza Dowling, N; Pozorski, Vincent; Okonkwo, Ozioma C; Starks, Erika J; Oh, Jennifer; Thiesen, Frances; Wey, Alexandra; Nicholas, Christopher R; Johnson, Sterling; Gallagher, Catherine L

2018-05-09

Parkinson's disease (PD) is an age-related neurodegenerative disease that produces changes in movement, cognition, sleep, and autonomic function. Motor learning involves acquisition of new motor skills through practice, and is affected by PD. The purpose of the present study was to evaluate regional differences in resting cerebral blood flow (rCBF), measured using arterial spin labeling (ASL) MRI, during a finger-typing task of motor skill acquisition in PD patients compared to age- and gender-matched controls. Voxel-wise multiple linear regression models were used to examine the relationship between rCBF and several task variables, including initial speed, proficiency gain, and accuracy. In these models, a task-by-disease group interaction term was included to investigate where the relationship between rCBF and task performance was influenced by PD. At baseline, perfusion was lower in PD subjects than controls in the right occipital cortex. The task-by-disease group interaction for initial speed was significantly related to rCBF (p < 0.05, corrected) in several brain regions involved in motor learning, including the occipital, parietal, and temporal cortices, cerebellum, anterior cingulate, and the superior and middle frontal gyri. In these regions, PD patients showed higher rCBF, and controls lower rCBF, with improved performance. Within the control group, proficiency gain over 12 typing trials was related to greater rCBF in cerebellar, occipital, and temporal cortices. These results suggest that higher rCBF within networks involved in motor learning enable PD patients to compensate for disease-related deficits.

Relationships of physical performance tests to military-relevant tasks in women.

PubMed

Szivak, Tunde K; Kraemer, William J; Nindl, Bradley C; Gotshalk, Lincoln A; Volek, Jeff S; Gomez, Ana L; Dunn-Lewis, Courtenay; Looney, David P; Comstock, Brett A; Hooper, David R; Flanagan, Shawn D; Maresh, Carl M

2014-01-01

This investigation sought to determine the most predictive measures of performance on a repetitive box lifting task (RBLT) and load bearing task (LBT) among 123 women (aged ±4 years, height 165±7 cm, body mass 64±10 kg). To determine the relationship of various predictors to performance on the RBLT and LBT, multiple regression analysis was conducted on body mass, height, leg cross-sectional area, upper and lower body muscular strength, lower body explosive power, upper and lower body local muscular endurance, and aerobic capacity. The mean±SD (range) number of repetitions for the RBLT was 86±23 (20-159). The mean±SD (range) time to complete the LBT was 2,054±340 seconds (1,307-3,447). The following equations were generated: RBLT (number of repetitions)=57.4+0.2(peak jump power)+0.4(number of pushups in 2 minutes)+0.15(number of repetitions during the squat endurance test)+1.39(one repetition maximal strength boxlift (kg))-0.04(2-mile run time (2MR) in seconds), R=0.81; standard error of the estimate (SEE)=14; LBT (in seconds)=1,831-4.28(number of repetitions during the squat endurance test)+0.95(2MR in seconds)-13.4(body mass), R=0.73; SEE=232. We found that the 2MR and squat endurance test were significant predictive factors for performance on both load carriage tasks. These data also imply that women's performance in combat-related tasks can be improved with training that targets muscular strength, power, and local muscular endurance in addition to aerobic capacity.

Exploring the motivation jungle: predicting performance on a novel task by investigating constructs from different motivation perspectives in tandem.

PubMed

Van Nuland, Hanneke J C; Dusseldorp, Elise; Martens, Rob L; Boekaerts, Monique

2010-08-01

Different theoretical viewpoints on motivation make it hard to decide which model has the best potential to provide valid predictions on classroom performance. This study was designed to explore motivation constructs derived from different motivation perspectives that predict performance on a novel task best. Motivation constructs from self-determination theory, self-regulation theory, and achievement goal theory were investigated in tandem. Performance was measured by systematicity (i.e. how systematically students worked on a problem-solving task) and test score (i.e. score on a multiple-choice test). Hierarchical regression analyses on data from 259 secondary school students showed a quadratic relation between a performance avoidance orientation and both performance outcomes, indicating that extreme high and low performance avoidance resulted in the lowest performance. Furthermore, two three-way interaction effects were found. Intrinsic motivation seemed to play a key role in test score and systematicity performance, provided that effort regulation and metacognitive skills were both high. Results indicate that intrinsic motivation in itself is not enough to attain a good performance. Instead, a moderate score on performance avoidance, together with the ability to remain motivated and effectively regulate and control task behavior, is needed to attain a good performance. High time management skills also contributed to higher test score and systematicity performance and a low performance approach orientation contributed to higher systematicity performance. We concluded that self-regulatory skills should be trained in order to have intrinsically motivated students perform well on novel tasks in the classroom.

To speak or not to speak - A multiple resource perspective

NASA Technical Reports Server (NTRS)

Tsang, P. S.; Hartzell, E. J.; Rothschild, R. A.

1985-01-01

The desirability of employing speech response in a dynamic dual task situation was discussed from a multiple resource perspective. A secondary task technique was employed to examine the time-sharing performance of five dual tasks with various degrees of resource overlap according to the structure-specific resource model of Wickens (1980). The primary task was a visual/manual tracking task which required spatial processing. The secondary task was either another tracking task or a spatial transformation task with one of four input (visual or auditory) and output (manual or speech) configurations. The results show that the dual task performance was best when the primary tracking task was paired with the visual/speech transformation task. This finding was explained by an interaction of the stimulus-central processing-response compatibility of the transformation task and the degree of resource competition between the time-shared tasks. Implications on the utility of speech response were discussed.

The relationship between executive function and fine motor control in young and older adults.

PubMed

Corti, Emily J; Johnson, Andrew R; Riddle, Hayley; Gasson, Natalie; Kane, Robert; Loftus, Andrea M

2017-01-01

The present study examined the relationship between executive function (EF) and fine motor control in young and older healthy adults. Participants completed 3 measures of executive function; a spatial working memory (SWM) task, the Stockings of Cambridge task (planning), and the Intra-Dimensional Extra-Dimensional Set-Shift task (set-shifting). Fine motor control was assessed using 3 subtests of the Purdue Pegboard (unimanual, bimanual, sequencing). For the younger adults, there were no significant correlations between measures of EF and fine motor control. For the older adults, all EFs significantly correlated with all measures of fine motor control. Three separate regressions examined whether planning, SWM and set-shifting independently predicted unimanual, bimanual, and sequencing scores for the older adults. Planning was the primary predictor of performance on all three Purdue subtests. A multiple-groups mediation model examined whether planning predicted fine motor control scores independent of participants' age, suggesting that preservation of planning ability may support fine motor control in older adults. Planning remained a significant predictor of unimanual performance in the older age group, but not bimanual or sequencing performance. The findings are discussed in terms of compensation theory, whereby planning is a key compensatory resource for fine motor control in older adults. Copyright © 2016 Elsevier B.V. All rights reserved.

Building intelligent communication systems for handicapped aphasiacs.

PubMed

Fu, Yu-Fen; Ho, Cheng-Seen

2010-01-01

This paper presents an intelligent system allowing handicapped aphasiacs to perform basic communication tasks. It has the following three key features: (1) A 6-sensor data glove measures the finger gestures of a patient in terms of the bending degrees of his fingers. (2) A finger language recognition subsystem recognizes language components from the finger gestures. It employs multiple regression analysis to automatically extract proper finger features so that the recognition model can be fast and correctly constructed by a radial basis function neural network. (3) A coordinate-indexed virtual keyboard allows the users to directly access the letters on the keyboard at a practical speed. The system serves as a viable tool for natural and affordable communication for handicapped aphasiacs through continuous finger language input.

Inhibition Plasticity in Older Adults: Practice and Transfer Effects Using a Multiple Task Approach.

PubMed

Wilkinson, Andrea J; Yang, Lixia

2016-01-01

OBJECTIVE. To examine plasticity of inhibition, as indexed by practice effects of inhibition tasks and the associated transfer effects, using a multiple task approach in healthy older adults. METHOD. Forty-eight healthy older adults were evenly assigned to either a practice group or a no-contact control group. All participants completed pretest (2.5 hours) and posttest (2 hours) sessions, with a 2-week interval in between. During the 2-week interval, only the practice group completed six 30-minute practice sessions (three sessions per week for two consecutive weeks) of three lab-based inhibition tasks. RESULTS. All three inhibition tasks demonstrated significant improvement across practice sessions, suggesting practice-induced plasticity. The benefit, however, only transferred to near-near tasks. The results are inconclusive with regard to the near-far and far-far transfer effects. DISCUSSION. This study further extends literature on practice effects of inhibition in older adults by using a multiple task approach. Together with previous work, the current study suggests that older adults are able to improve inhibition performance through practice and transfer the practice gains to tasks that overlap in both target cognitive ability and task structure (i.e., near-near tasks).

Inhibition Plasticity in Older Adults: Practice and Transfer Effects Using a Multiple Task Approach

PubMed Central

Wilkinson, Andrea J.; Yang, Lixia

2016-01-01

Objective. To examine plasticity of inhibition, as indexed by practice effects of inhibition tasks and the associated transfer effects, using a multiple task approach in healthy older adults. Method. Forty-eight healthy older adults were evenly assigned to either a practice group or a no-contact control group. All participants completed pretest (2.5 hours) and posttest (2 hours) sessions, with a 2-week interval in between. During the 2-week interval, only the practice group completed six 30-minute practice sessions (three sessions per week for two consecutive weeks) of three lab-based inhibition tasks. Results. All three inhibition tasks demonstrated significant improvement across practice sessions, suggesting practice-induced plasticity. The benefit, however, only transferred to near-near tasks. The results are inconclusive with regard to the near-far and far-far transfer effects. Discussion. This study further extends literature on practice effects of inhibition in older adults by using a multiple task approach. Together with previous work, the current study suggests that older adults are able to improve inhibition performance through practice and transfer the practice gains to tasks that overlap in both target cognitive ability and task structure (i.e., near-near tasks). PMID:26885407

Well-being of intensive care nurses (WEBIC): a job analytic approach.

PubMed

Le Blanc, P M; de Jonge, J; de Rijk, A E; Schaufeli, W B

2001-11-01

This paper presents the results of a validation study of the so-called well-being of intensive care nurses (WEBIC)-questionnaire that is designed to perform a detailed job analysis of intensive care unit (ICU) nurses' jobs. The WEBIC-questionnaire is based on modern sociotechnical systems theory, and distinguishes four integrated task categories: (1) operational, (2) organizing, (3) preparatory, and (4) supportive tasks. For each task, the WEBIC assesses (1) how demanding this task is, and (2) how satisfying the performance of this task is. Using the WEBIC, information is gathered about ICU nurses' qualitative workload, and typical job-related risks for ICU nurses' well-being at work can be mapped. A cross-sectional survey on work and well-being of almost 2000 ICU-nurses in 13 different European areas was conducted. Exploratory factor analyses were performed to study the validity of the factorial structure of the WEBIC-questionnaire. The construct validity of the WEBIC-questionnaire was studied by performing hierarchical multiple regression analyses of the WEBIC-factors on two types of job-related well-being, i.e. burnout and general job satisfaction. Results of the exploratory factor analyses showed that the hypothesized four-factor structure of the WEBIC is confirmed by our data. Internal consistencies of the different factors varied from 0.77 to 0.91. Intensive care unit nurses' most central (operational) tasks turned out to pose the greatest demands, but also seemed to drive their satisfaction. With respect to the relationships between the four WEBIC-factors, and burnout and general job satisfaction, it was found that, especially for the satisfying tasks, significant relationships with these outcomes were found. The reliability and construct validity of the WEBIC-questionnaire can be considered satisfactory. Furthermore, the questionnaire provides a systematical and detailed coverage of ICU nurses' tasks. In relation to this, the questionnaire is not only useful for scientific purposes but also for practical use.

Patients With Chondrolabral Pathology Have Bilateral Functional Impairments 12 to 24 Months After Unilateral Hip Arthroscopy: A Cross-sectional Study.

PubMed

Kemp, Joanne L; Risberg, May Arna; Schache, Anthony G; Makdissi, Michael; Pritchard, Michael G; Crossley, Kay M

2016-11-01

Study Design Cross-sectional study. Background Functional task performance in patients with chondrolabral pathology following hip arthroscopy is unknown. Objectives To investigate in people with chondrolabral pathology following hip arthroscopy (1) the bilateral differences in functional task performance compared to controls, (2) the association of hip muscle strength with functional task performance, and (3) the association of functional task performance scores with good outcome, as measured by International Hip Outcome Tool score. Methods Seventy-one patients who had unilateral hip arthroscopy for hip pain and 60 controls were recruited. Patient-reported outcomes included the 4 subscales of the International Hip Outcome Tool. Hip muscle strength measures included abduction, adduction, extension, flexion, external rotation, and internal rotation. Functional tasks assessed included the single hop test, the side bridge test, and the single-leg rise test. For aim 1, analyses of covariance tests were used. For aim 2, stepwise multiple linear regression analyses were used. For aim 3, receiver operating characteristic curve analyses were used. Results Compared to controls, the chondrolabral pathology group had significantly worse performance on both legs for each of the functional tasks (P<.001). Greater hip abduction strength was moderately associated with better performance on functional tasks in the chondrolabral pathology group (adjusted R 2 range, 0.197-0.407; P<.001). Cutoff values associated with good outcome were 0.37 (hop distance/height) for the single hop, 16 repetitions for the single-leg rise, and 34 seconds for the side bridge test. Conclusion Patients with hip chondrolabral pathology had reduced functional task performance bilaterally 12 to 24 months after unilateral hip arthroscopy when compared to controls. Level of Evidence Therapy/symptom prevalence, level 3b. J Orthop Sports Phys Ther 2016;46(11):947-956. doi:10.2519/jospt.2016.6577.

Isolating and Examining Sources of Suppression and Multicollinearity in Multiple Linear Regression

ERIC Educational Resources Information Center

Beckstead, Jason W.

2012-01-01

The presence of suppression (and multicollinearity) in multiple regression analysis complicates interpretation of predictor-criterion relationships. The mathematical conditions that produce suppression in regression analysis have received considerable attention in the methodological literature but until now nothing in the way of an analytic…

General Nature of Multicollinearity in Multiple Regression Analysis.

ERIC Educational Resources Information Center

Liu, Richard

1981-01-01

Discusses multiple regression, a very popular statistical technique in the field of education. One of the basic assumptions in regression analysis requires that independent variables in the equation should not be highly correlated. The problem of multicollinearity and some of the solutions to it are discussed. (Author)

ℓ p-Norm Multikernel Learning Approach for Stock Market Price Forecasting

PubMed Central

Shao, Xigao; Wu, Kun; Liao, Bifeng

2012-01-01

Linear multiple kernel learning model has been used for predicting financial time series. However, ℓ 1-norm multiple support vector regression is rarely observed to outperform trivial baselines in practical applications. To allow for robust kernel mixtures that generalize well, we adopt ℓ p-norm multiple kernel support vector regression (1 ≤ p < ∞) as a stock price prediction model. The optimization problem is decomposed into smaller subproblems, and the interleaved optimization strategy is employed to solve the regression model. The model is evaluated on forecasting the daily stock closing prices of Shanghai Stock Index in China. Experimental results show that our proposed model performs better than ℓ 1-norm multiple support vector regression model. PMID:23365561

Sample size determination for logistic regression on a logit-normal distribution.

PubMed

Kim, Seongho; Heath, Elisabeth; Heilbrun, Lance

2017-06-01

Although the sample size for simple logistic regression can be readily determined using currently available methods, the sample size calculation for multiple logistic regression requires some additional information, such as the coefficient of determination ([Formula: see text]) of a covariate of interest with other covariates, which is often unavailable in practice. The response variable of logistic regression follows a logit-normal distribution which can be generated from a logistic transformation of a normal distribution. Using this property of logistic regression, we propose new methods of determining the sample size for simple and multiple logistic regressions using a normal transformation of outcome measures. Simulation studies and a motivating example show several advantages of the proposed methods over the existing methods: (i) no need for [Formula: see text] for multiple logistic regression, (ii) available interim or group-sequential designs, and (iii) much smaller required sample size.

Logistic Regression Likelihood Ratio Test Analysis for Detecting Signals of Adverse Events in Post-market Safety Surveillance.

PubMed

Nam, Kijoeng; Henderson, Nicholas C; Rohan, Patricia; Woo, Emily Jane; Russek-Cohen, Estelle

2017-01-01

The Vaccine Adverse Event Reporting System (VAERS) and other product surveillance systems compile reports of product-associated adverse events (AEs), and these reports may include a wide range of information including age, gender, and concomitant vaccines. Controlling for possible confounding variables such as these is an important task when utilizing surveillance systems to monitor post-market product safety. A common method for handling possible confounders is to compare observed product-AE combinations with adjusted baseline frequencies where the adjustments are made by stratifying on observable characteristics. Though approaches such as these have proven to be useful, in this article we propose a more flexible logistic regression approach which allows for covariates of all types rather than relying solely on stratification. Indeed, a main advantage of our approach is that the general regression framework provides flexibility to incorporate additional information such as demographic factors and concomitant vaccines. As part of our covariate-adjusted method, we outline a procedure for signal detection that accounts for multiple comparisons and controls the overall Type 1 error rate. To demonstrate the effectiveness of our approach, we illustrate our method with an example involving febrile convulsion, and we further evaluate its performance in a series of simulation studies.

The Role of CLEAR Thinking in Learning Science from Multiple-Document Inquiry Tasks

ERIC Educational Resources Information Center

Griffin, Thomas D.; Wiley, Jennifer; Britt, M. Anne; Salas, Carlos R.

2012-01-01

The main goal for the current study was to investigate whether individual differences in domain-general thinking dispositions might affect learning from multiple-document inquiry tasks in science. Middle school students were given a set of documents and were tasked with understanding how and why recent patterns in global temperature might be…

Children's Understanding of the Inverse Relation between Multiplication and Division

ERIC Educational Resources Information Center

Robinson, Katherine M.; Dube, Adam K.

2009-01-01

Children's understanding of the inversion concept in multiplication and division problems (i.e., that on problems of the form "d multiplied by e/e" no calculations are required) was investigated. Children in Grades 6, 7, and 8 completed an inversion problem-solving task, an assessment of procedures task, and a factual knowledge task of simple…

Understanding and Integrating Multiple Science Texts: Summary Tasks Are Sometimes Better than Argument Tasks

ERIC Educational Resources Information Center

Gil, Laura; Braten, Ivar; Vidal-Abarca, Eduardo; Stromso, Helge I.

2010-01-01

One of the major challenges of a knowledge society is that students as well as other citizens must learn to understand and integrate information from multiple textual sources. Still, task and reader characteristics that may facilitate or constrain such intertextual processes are not well understood by researchers. In this study, we compare the…

Functional connectivity of task context representations in prefrontal nodes of the multiple demand network.

PubMed

Stiers, Peter; Goulas, Alexandros

2018-06-01

A subset of regions in the lateral and medial prefrontal cortex and the anterior insula increase their activity level whenever a cognitive task becomes more demanding, regardless of the specific nature of this demand. During execution of a task, these areas and the surrounding cortex temporally encode aspects of the task context in spatially distributed patterns of activity. It is not clear whether these patterns reflect underlying anatomical subnetworks that still exist when task execution has finished. We use fMRI in 12 participants performing alternating blocks of three cognitive tasks to address this question. A first data set is used to define multiple demand regions in each participant. A second dataset from the same participants is used to determine multiple demand voxel assemblies with a preference for one task over the others. We then show that these voxels remain functionally coupled during execution of non-preferred tasks and that they exhibit stronger functional connectivity during rest. This indicates that the assemblies of task preference sharing voxels reflect patterns of underlying anatomical connections. Moreover, we show that voxels preferring the same task have more similar whole brain functional connectivity profiles that are consistent across participants. This suggests that voxel assemblies differ in patterns of input-output connections, most likely reflecting task demand-specific information exchange.

Adults' strategies for simple addition and multiplication: verbal self-reports and the operand recognition paradigm.

PubMed

Metcalfe, Arron W S; Campbell, Jamie I D

2011-05-01

Accurate measurement of cognitive strategies is important in diverse areas of psychological research. Strategy self-reports are a common measure, but C. Thevenot, M. Fanget, and M. Fayol (2007) proposed a more objective method to distinguish different strategies in the context of mental arithmetic. In their operand recognition paradigm, speed of recognition memory for problem operands after solving a problem indexes strategy (e.g., direct memory retrieval vs. a procedural strategy). Here, in 2 experiments, operand recognition time was the same following simple addition or multiplication, but, consistent with a wide variety of previous research, strategy reports indicated much greater use of procedures (e.g., counting) for addition than multiplication. Operation, problem size (e.g., 2 + 3 vs. 8 + 9), and operand format (digits vs. words) had interactive effects on reported procedure use that were not reflected in recognition performance. Regression analyses suggested that recognition time was influenced at least as much by the relative difficulty of the preceding problem as by the strategy used. The findings indicate that the operand recognition paradigm is not a reliable substitute for strategy reports and highlight the potential impact of difficulty-related carryover effects in sequential cognitive tasks.

Contributions to "k"-Means Clustering and Regression via Classification Algorithms

ERIC Educational Resources Information Center

Salman, Raied

2012-01-01

The dissertation deals with clustering algorithms and transforming regression problems into classification problems. The main contributions of the dissertation are twofold; first, to improve (speed up) the clustering algorithms and second, to develop a strict learning environment for solving regression problems as classification tasks by using…

The Relationship Between Continuous Identity Disturbances, Negative Mood, and Suicidal Ideation.

PubMed

Sokol, Yosef; Eisenheim, Edouard

To examine the relationship between continuous identity and a measure of depression, anxiety, and stress as well as suicidal ideation using 2 validated measures of continuous identity. A total of 246 subjects recruited from the Amazon Mechanical Turk subject pool who completed a full survey in November 2014 were included in the analyses. Stress, anxiety, and depression severity were measured using the Depression, Anxiety, and Stress Scale. Continuous identity was measured with the Venn continuous identity task and the me/not me continuous identity task. Multiple regression analyses revealed continuous identity disturbances were significantly associated with depressed mood (R (2) = 0.37, P < .01). Continuous identity also predicted suicide severity, even after controlling for demographic factors, negative life events, and depressed mood. Additionally, predictive discriminant analysis revealed continuous identity, depression severity, and negative life events correctly classified 74.1% of participants into high and low suicide risk groups. Lack of continuous identity predicted both depression and suicidality severity. Integration of perceived identities may be a worthwhile goal for behavioral interventions aimed at reducing depressed mood and suicidality.

The Relationship Between Trait Procrastination, Internet Use, and Psychological Functioning: Results From a Community Sample of German Adolescents.

PubMed

Reinecke, Leonard; Meier, Adrian; Beutel, Manfred E; Schemer, Christian; Stark, Birgit; Wölfling, Klaus; Müller, Kai W

2018-01-01

Adolescents with a strong tendency for irrational task delay (i.e., high trait procrastination) may be particularly prone to use Internet applications simultaneously to other tasks (e.g., during homework) and in an insufficiently controlled fashion. Both Internet multitasking and insufficiently controlled Internet usage may thus amplify the negative mental health implications that have frequently been associated with trait procrastination. The present study explored this role of Internet multitasking and insufficiently controlled Internet use for the relationship between trait procrastination and impaired psychological functioning in a community sample of N = 818 early and middle adolescents. Results from multiple regression analyses indicate that trait procrastination was positively related to Internet multitasking and insufficiently controlled Internet use. Insufficiently controlled Internet use, but not Internet multitasking, was found to partially statistically mediate the association between trait procrastination and adolescents' psychological functioning (i.e., stress, sleep quality, and relationship satisfaction with parents). The study underlines that adolescents with high levels of trait procrastination may have an increased risk for negative outcomes of insufficiently controlled Internet use.

Academic procrastination in college students: the role of self-reported executive function.

PubMed

Rabin, Laura A; Fogel, Joshua; Nutter-Upham, Katherine E

2011-03-01

Procrastination, or the intentional delay of due tasks, is a widespread phenomenon in college settings. Because procrastination can negatively impact learning, achievement, academic self-efficacy, and quality of life, research has sought to understand the factors that produce and maintain this troublesome behavior. Procrastination is increasingly viewed as involving failures in self-regulation and volition, processes commonly regarded as executive functions. The present study was the first to investigate subcomponents of self-reported executive functioning associated with academic procrastination in a demographically diverse sample of college students aged 30 years and below (n = 212). We included each of nine aspects of executive functioning in multiple regression models that also included various demographic and medical/psychiatric characteristics, estimated IQ, depression, anxiety, neuroticism, and conscientiousness. The executive function domains of initiation, plan/organize, inhibit, self-monitor, working memory, task monitor, and organization of materials were significant predictors of academic procrastination in addition to increased age and lower conscientiousness. Results enhance understanding of the neuropsychological correlates of procrastination and may lead to practical suggestions or interventions to reduce its harmful effects on students' academic performance and well-being.

Evidence for aversive withdrawal response to own errors.

PubMed

Hochman, Eldad Yitzhak; Milman, Valery; Tal, Liron

2017-10-01

Recent model suggests that error detection gives rise to defensive motivation prompting protective behavior. Models of active avoidance behavior predict it should grow larger with threat imminence and avoidance. We hypothesized that in a task requiring left or right key strikes, error detection would drive an avoidance reflex manifested by rapid withdrawal of an erring finger growing larger with threat imminence and avoidance. In experiment 1, three groups differing by error-related threat imminence and avoidance performed a flanker task requiring left or right force sensitive-key strikes. As predicted, errors were followed by rapid force release growing faster with threat imminence and opportunity to evade threat. In experiment 2, we established a link between error key release time (KRT) and the subjective sense of inner-threat. In a simultaneous, multiple regression analysis of three error-related compensatory mechanisms (error KRT, flanker effect, error correction RT), only error KRT was significantly associated with increased compulsive checking tendencies. We propose that error response withdrawal reflects an error-withdrawal reflex. Copyright © 2017 Elsevier B.V. All rights reserved.

Healthy Aging Delays Scalp EEG Sensitivity to Noise in a Face Discrimination Task

PubMed Central

Rousselet, Guillaume A.; Gaspar, Carl M.; Pernet, Cyril R.; Husk, Jesse S.; Bennett, Patrick J.; Sekuler, Allison B.

2010-01-01

We used a single-trial ERP approach to quantify age-related changes in the time-course of noise sensitivity. A total of 62 healthy adults, aged between 19 and 98, performed a non-speeded discrimination task between two faces. Stimulus information was controlled by parametrically manipulating the phase spectrum of these faces. Behavioral 75% correct thresholds increased with age. This result may be explained by lower signal-to-noise ratios in older brains. ERP from each subject were entered into a single-trial general linear regression model to identify variations in neural activity statistically associated with changes in image structure. The fit of the model, indexed by R2, was computed at multiple post-stimulus time points. The time-course of the R2 function showed significantly delayed noise sensitivity in older observers. This age effect is reliable, as demonstrated by test–retest in 24 subjects, and started about 120 ms after stimulus onset. Our analyses suggest also a qualitative change from a young to an older pattern of brain activity at around 47 ± 4 years old. PMID:21833194

The Relationship Between Trait Procrastination, Internet Use, and Psychological Functioning: Results From a Community Sample of German Adolescents

PubMed Central

Reinecke, Leonard; Meier, Adrian; Beutel, Manfred E.; Schemer, Christian; Stark, Birgit; Wölfling, Klaus; Müller, Kai W.

2018-01-01

Adolescents with a strong tendency for irrational task delay (i.e., high trait procrastination) may be particularly prone to use Internet applications simultaneously to other tasks (e.g., during homework) and in an insufficiently controlled fashion. Both Internet multitasking and insufficiently controlled Internet usage may thus amplify the negative mental health implications that have frequently been associated with trait procrastination. The present study explored this role of Internet multitasking and insufficiently controlled Internet use for the relationship between trait procrastination and impaired psychological functioning in a community sample of N = 818 early and middle adolescents. Results from multiple regression analyses indicate that trait procrastination was positively related to Internet multitasking and insufficiently controlled Internet use. Insufficiently controlled Internet use, but not Internet multitasking, was found to partially statistically mediate the association between trait procrastination and adolescents’ psychological functioning (i.e., stress, sleep quality, and relationship satisfaction with parents). The study underlines that adolescents with high levels of trait procrastination may have an increased risk for negative outcomes of insufficiently controlled Internet use. PMID:29942268

A Quantile Regression Approach to Understanding the Relations Among Morphological Awareness, Vocabulary, and Reading Comprehension in Adult Basic Education Students.

PubMed

Tighe, Elizabeth L; Schatschneider, Christopher

2016-07-01

The purpose of this study was to investigate the joint and unique contributions of morphological awareness and vocabulary knowledge at five reading comprehension levels in adult basic education (ABE) students. We introduce the statistical technique of multiple quantile regression, which enabled us to assess the predictive utility of morphological awareness and vocabulary knowledge at multiple points (quantiles) along the continuous distribution of reading comprehension. To demonstrate the efficacy of our multiple quantile regression analysis, we compared and contrasted our results with a traditional multiple regression analytic approach. Our results indicated that morphological awareness and vocabulary knowledge accounted for a large portion of the variance (82%-95%) in reading comprehension skills across all quantiles. Morphological awareness exhibited the greatest unique predictive ability at lower levels of reading comprehension whereas vocabulary knowledge exhibited the greatest unique predictive ability at higher levels of reading comprehension. These results indicate the utility of using multiple quantile regression to assess trajectories of component skills across multiple levels of reading comprehension. The implications of our findings for ABE programs are discussed. © Hammill Institute on Disabilities 2014.

Stepwise versus Hierarchical Regression: Pros and Cons

ERIC Educational Resources Information Center

Lewis, Mitzi

2007-01-01

Multiple regression is commonly used in social and behavioral data analysis. In multiple regression contexts, researchers are very often interested in determining the "best" predictors in the analysis. This focus may stem from a need to identify those predictors that are supportive of theory. Alternatively, the researcher may simply be interested…

Endogenous Task Shift Processes in Relapsing-Remitting Multiple Sclerosis

ERIC Educational Resources Information Center

Stablum, F.; Meligrana, L.; Sgaramella, T.; Bortolon, F.; Toso, V.

2004-01-01

This paper reports a study that was aimed to evaluate executive functions in relapsing-remitting multiple sclerosis patients. The groups tested comprised 22 relapsing-remitting multiple sclerosis patients, and 22 non-brain damaged controls. When one is engaged in two speeded tasks, not simultaneously but with some form of alternation, it is slower…

Bilingual advantages in executive functioning: problems in convergent validity, discriminant validity, and the identification of the theoretical constructs

PubMed Central

Paap, Kenneth R.; Sawi, Oliver

2014-01-01

A sample of 58 bilingual and 62 monolingual university students completed four tasks commonly used to test for bilingual advantages in executive functioning (EF): antisaccade, attentional network test, Simon, and color-shape switching. Across the four tasks, 13 different indices were derived that are assumed to reflect individual differences in inhibitory control, monitoring, or switching. The effects of bilingualism on the 13 measures were explored by directly comparing the means of the two language groups and through regression analyses using a continuous measure of bilingualism and multiple demographic characteristics as predictors. Across the 13 different measures and two types of data analysis there were very few significant results and those that did occur supported a monolingual advantage. An equally important goal was to assess the convergent validity through cross-task correlations of indices assume to measure the same component of executive functioning. Most of the correlations using difference-score measures were non-significant and many near zero. Although modestly higher levels of convergent validity are sometimes reported, a review of the existing literature suggests that bilingual advantages (or disadvantages) may reflect task-specific differences that are unlikely to generalize to important general differences in EF. Finally, as cautioned by Salthouse, assumed measures of executive functioning may also be threatened by a lack of discriminant validity that separates individual or group differences in EF from those in general fluid intelligence or simple processing speed. PMID:25249988

The Complexity of Standing Postural Sway Associates with Future Falls in Community-Dwelling Older Adults: The MOBILIZE Boston Study.

PubMed

Zhou, Junhong; Habtemariam, Daniel; Iloputaife, Ikechukwu; Lipsitz, Lewis A; Manor, Brad

2017-06-07

Standing postural control is complex, meaning that it is dependent upon numerous inputs interacting across multiple temporal-spatial scales. Diminished physiologic complexity of postural sway has been linked to reduced ability to adapt to stressors. We hypothesized that older adults with lower postural sway complexity would experience more falls in the future. 738 adults aged ≥70 years completed the Short Physical Performance Battery test (SPPB) test and assessments of single and dual-task standing postural control. Postural sway complexity was quantified using multiscale entropy. Falls were subsequently tracked for 48 months. Negative binomial regression demonstrated that older adults with lower postural sway complexity in both single and dual-task conditions had higher future fall rate (incident rate ratio (IRR) = 0.98, p = 0.02, 95% Confidence Limits (CL) = 0.96-0.99). Notably, participants in the lowest quintile of complexity during dual-task standing suffered 48% more falls during the four-year follow-up as compared to those in the highest quintile (IRR = 1.48, p = 0.01, 95% CL = 1.09-1.99). Conversely, traditional postural sway metrics or SPPB performance did not associate with future falls. As compared to traditional metrics, the degree of multi-scale complexity contained within standing postural sway-particularly during dual task conditions- appears to be a better predictor of future falls in older adults.

Optimizing and Interpreting Insular Functional Connectivity Maps Obtained During Acute Experimental Pain: The Effects of Global Signal and Task Paradigm Regression.

PubMed

Ibinson, James W; Vogt, Keith M; Taylor, Kevin B; Dua, Shiv B; Becker, Christopher J; Loggia, Marco; Wasan, Ajay D

2015-12-01

The insula is uniquely located between the temporal and parietal cortices, making it anatomically well-positioned to act as an integrating center between the sensory and affective domains for the processing of painful stimulation. This can be studied through resting-state functional connectivity (fcMRI) imaging; however, the lack of a clear methodology for the analysis of fcMRI complicates the interpretation of these data during acute pain. Detected connectivity changes may reflect actual alterations in low-frequency synchronous neuronal activity related to pain, may be due to changes in global cerebral blood flow or the superimposed task-induced neuronal activity. The primary goal of this study was to investigate the effects of global signal regression (GSR) and task paradigm regression (TPR) on the changes in functional connectivity of the left (contralateral) insula in healthy subjects at rest and during acute painful electric nerve stimulation of the right hand. The use of GSR reduced the size and statistical significance of connectivity clusters and created negative correlation coefficients for some connectivity clusters. TPR with cyclic stimulation gave task versus rest connectivity differences similar to those with a constant task, suggesting that analysis which includes TPR is more accurately reflective of low-frequency neuronal activity. Both GSR and TPR have been inconsistently applied to fcMRI analysis. Based on these results, investigators need to consider the impact GSR and TPR have on connectivity during task performance when attempting to synthesize the literature.

Parallel processing considerations for image recognition tasks

NASA Astrophysics Data System (ADS)

Simske, Steven J.

2011-01-01

Many image recognition tasks are well-suited to parallel processing. The most obvious example is that many imaging tasks require the analysis of multiple images. From this standpoint, then, parallel processing need be no more complicated than assigning individual images to individual processors. However, there are three less trivial categories of parallel processing that will be considered in this paper: parallel processing (1) by task; (2) by image region; and (3) by meta-algorithm. Parallel processing by task allows the assignment of multiple workflows-as diverse as optical character recognition [OCR], document classification and barcode reading-to parallel pipelines. This can substantially decrease time to completion for the document tasks. For this approach, each parallel pipeline is generally performing a different task. Parallel processing by image region allows a larger imaging task to be sub-divided into a set of parallel pipelines, each performing the same task but on a different data set. This type of image analysis is readily addressed by a map-reduce approach. Examples include document skew detection and multiple face detection and tracking. Finally, parallel processing by meta-algorithm allows different algorithms to be deployed on the same image simultaneously. This approach may result in improved accuracy.

A Method of Calculating Functional Independence Measure at Discharge from Functional Independence Measure Effectiveness Predicted by Multiple Regression Analysis Has a High Degree of Predictive Accuracy.

PubMed

Tokunaga, Makoto; Watanabe, Susumu; Sonoda, Shigeru

2017-09-01

Multiple linear regression analysis is often used to predict the outcome of stroke rehabilitation. However, the predictive accuracy may not be satisfactory. The objective of this study was to elucidate the predictive accuracy of a method of calculating motor Functional Independence Measure (mFIM) at discharge from mFIM effectiveness predicted by multiple regression analysis. The subjects were 505 patients with stroke who were hospitalized in a convalescent rehabilitation hospital. The formula "mFIM at discharge = mFIM effectiveness × (91 points - mFIM at admission) + mFIM at admission" was used. By including the predicted mFIM effectiveness obtained through multiple regression analysis in this formula, we obtained the predicted mFIM at discharge (A). We also used multiple regression analysis to directly predict mFIM at discharge (B). The correlation between the predicted and the measured values of mFIM at discharge was compared between A and B. The correlation coefficients were .916 for A and .878 for B. Calculating mFIM at discharge from mFIM effectiveness predicted by multiple regression analysis had a higher degree of predictive accuracy of mFIM at discharge than that directly predicted. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Application-level regression testing framework using Jenkins

DOE PAGES

Budiardja, Reuben; Bouvet, Timothy; Arnold, Galen

2017-09-26

Monitoring and testing for regression of large-scale systems such as the NCSA's Blue Waters supercomputer are challenging tasks. In this paper, we describe the solution we came up with to perform those tasks. The goal was to find an automated solution for running user-level regression tests to evaluate system usability and performance. Jenkins, an automation server software, was chosen for its versatility, large user base, and multitude of plugins including collecting data and plotting test results over time. We also describe our Jenkins deployment to launch and monitor jobs on remote HPC system, perform authentication with one-time password, and integratemore » with our LDAP server for its authorization. We show some use cases and describe our best practices for successfully using Jenkins as a user-level system-wide regression testing and monitoring framework for large supercomputer systems.« less

Application-level regression testing framework using Jenkins

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

Budiardja, Reuben; Bouvet, Timothy; Arnold, Galen

Monitoring and testing for regression of large-scale systems such as the NCSA's Blue Waters supercomputer are challenging tasks. In this paper, we describe the solution we came up with to perform those tasks. The goal was to find an automated solution for running user-level regression tests to evaluate system usability and performance. Jenkins, an automation server software, was chosen for its versatility, large user base, and multitude of plugins including collecting data and plotting test results over time. We also describe our Jenkins deployment to launch and monitor jobs on remote HPC system, perform authentication with one-time password, and integratemore » with our LDAP server for its authorization. We show some use cases and describe our best practices for successfully using Jenkins as a user-level system-wide regression testing and monitoring framework for large supercomputer systems.« less

Use of Empirical Estimates of Shrinkage in Multiple Regression: A Caution.

ERIC Educational Resources Information Center

Kromrey, Jeffrey D.; Hines, Constance V.

1995-01-01

The accuracy of four empirical techniques to estimate shrinkage in multiple regression was studied through Monte Carlo simulation. None of the techniques provided unbiased estimates of the population squared multiple correlation coefficient, but the normalized jackknife and bootstrap techniques demonstrated marginally acceptable performance with…

Enhance-Synergism and Suppression Effects in Multiple Regression

ERIC Educational Resources Information Center

Lipovetsky, Stan; Conklin, W. Michael

2004-01-01

Relations between pairwise correlations and the coefficient of multiple determination in regression analysis are considered. The conditions for the occurrence of enhance-synergism and suppression effects when multiple determination becomes bigger than the total of squared correlations of the dependent variable with the regressors are discussed. It…

Sustained attention to response task (SART) shows impaired vigilance in a spectrum of disorders of excessive daytime sleepiness.

PubMed

Van Schie, Mojca K M; Thijs, Roland D; Fronczek, Rolf; Middelkoop, Huub A M; Lammers, Gert Jan; Van Dijk, J Gert

2012-08-01

The sustained attention to response task comprises withholding key presses to one in nine of 225 target stimuli; it proved to be a sensitive measure of vigilance in a small group of narcoleptics. We studied sustained attention to response task results in 96 patients from a tertiary narcolepsy referral centre. Diagnoses according to ICSD-2 criteria were narcolepsy with (n=42) and without cataplexy (n=5), idiopathic hypersomnia without long sleep time (n=37), and obstructive sleep apnoea syndrome (n=12). The sustained attention to response task was administered prior to each of five multiple sleep latency test sessions. Analysis concerned error rates, mean reaction time, reaction time variability and post-error slowing, as well as the correlation of sustained attention to response task results with mean latency of the multiple sleep latency test and possible time of day influences. Median sustained attention to response task error scores ranged from 8.4 to 11.1, and mean reaction times from 332 to 366ms. Sustained attention to response task error score and mean reaction time did not differ significantly between patient groups. Sustained attention to response task error score did not correlate with multiple sleep latency test sleep latency. Reaction time was more variable as the error score was higher. Sustained attention to response task error score was highest for the first session. We conclude that a high sustained attention to response task error rate reflects vigilance impairment in excessive daytime sleepiness irrespective of its cause. The sustained attention to response task and the multiple sleep latency test reflect different aspects of sleep/wakefulness and are complementary. © 2011 European Sleep Research Society.

Factors Contributing to Single- and Dual-Task Timed "Up & Go" Test Performance in Middle-Aged and Older Adults Who Are Active and Dwell in the Community.

PubMed

Chen, Hui-Ya; Tang, Pei-Fang

2016-03-01

Dual-task Timed "Up & Go" (TUG) tests are likely to have applications different from those of a single-task TUG test and may have different contributing factors. The purpose of this study was to compare factors contributing to performance on single- and dual-task TUG tests. This investigation was a cross-sectional study. Sixty-four adults who were more than 50 years of age and dwelled in the community were recruited. Interviews and physical examinations were performed to identify potential contributors to TUG test performance. The time to complete the single-task TUG test (TUGsingle) or the dual-task TUG test, which consisted of completing the TUG test while performing a serial subtraction task (TUGcognitive) or while carrying water (TUGmanual), was measured. Age, hip extensor strength, walking speed, general mental function, and Stroop scores for word and color were significantly associated with performance on all TUG tests. Hierarchical multiple regression models, without the input of walking speed, revealed different independent factors contributing to TUGsingle performance (Mini-Mental Status Examination score, β=-0.32), TUGmanual performance (age, β=0.35), and TUGcognitive performance (Stroop word score, β=-0.40; Mini-Mental Status Examination score, β=-0.31). At least 40% of the variance in the performance on the 3 TUG tests was not explained by common clinical measures, even when the factor of walking speed was considered. However, this study successfully identified some important factors contributing to performance on different TUG tests, and other studies have reported similar findings for single-task TUG test and dual-task gait performance. Although the TUGsingle and the TUGcognitive shared general mental function as a common factor, the TUGmanual was uniquely influenced by age and the TUGcognitive was uniquely influenced by focused attention. These results suggest that both common and unique factors contribute to performance on single- and dual-task TUG tests and suggest important applications of the combined use of the 3 TUG tests. © 2016 American Physical Therapy Association.

Classification Systems for Individual Differences in Multiple-task Performance and Subjective Estimates of Workload

NASA Technical Reports Server (NTRS)

Damos, D. L.

1984-01-01

Human factors practitioners often are concerned with mental workload in multiple-task situations. Investigations of these situations have demonstrated repeatedly that individuals differ in their subjective estimates of workload. These differences may be attributed in part to individual differences in definitions of workload. However, after allowing for differences in the definition of workload, there are still unexplained individual differences in workload ratings. The relation between individual differences in multiple-task performance, subjective estimates of workload, information processing abilities, and the Type A personality trait were examined.

Logistic Regression Modeling for Predicting Task-Related ICT Use in Teaching

ERIC Educational Resources Information Center

Askar, Petek; Usluel, Yasemin Kocak; Mumcu, Filiz Kuskaya

2006-01-01

The main goal of this study is to estimate the extent to which perceived innovation characteristics are associated with the probability of task related ICT use among secondary school teachers. The tasks were categorized as teaching preparation, teaching delivery, and management. Four hundred and sixteen teachers from secondary schools in Turkey,…

Design-Build-Write: Increasing the Impact of English for Specific Purposes Learning and Teaching in Aeronautical Engineering Education through Multiple Intelligences Task Design

ERIC Educational Resources Information Center

Tatzl, Dietmar

2011-01-01

This article presents an English for Specific Purposes (ESP) task developed for teaching aeronautical engineering students. The task Design-Build-Write rests on the assumption that engineering students are skilled at mathematical reasoning, problem solving, drawing and constructing. In Gardner's 1983 Multiple Intelligences (MI) theory, these…

Explorative Function in Williams Syndrome Analyzed through a Large-Scale Task with Multiple Rewards

ERIC Educational Resources Information Center

Foti, F.; Petrosini, L.; Cutuli, D.; Menghini, D.; Chiarotti, F.; Vicari, S.; Mandolesi, L.

2011-01-01

This study aimed to evaluate spatial function in subjects with Williams syndrome (WS) by using a large-scale task with multiple rewards and comparing the spatial abilities of WS subjects with those of mental age-matched control children. In the present spatial task, WS participants had to explore an open space to search nine rewards placed in…

A methodology for the design of experiments in computational intelligence with multiple regression models.

PubMed

Fernandez-Lozano, Carlos; Gestal, Marcos; Munteanu, Cristian R; Dorado, Julian; Pazos, Alejandro

2016-01-01

The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the field of Computational Intelligence and especially on a correct comparison between the different results provided for different methods, as those techniques are complex systems that require further study to be fully understood. A methodology commonly accepted in Computational intelligence is implemented in an R package called RRegrs. This package includes ten simple and complex regression models to carry out predictive modeling using Machine Learning and well-known regression algorithms. The framework for experimental design presented herein is evaluated and validated against RRegrs. Our results are different for three out of five state-of-the-art simple datasets and it can be stated that the selection of the best model according to our proposal is statistically significant and relevant. It is of relevance to use a statistical approach to indicate whether the differences are statistically significant using this kind of algorithms. Furthermore, our results with three real complex datasets report different best models than with the previously published methodology. Our final goal is to provide a complete methodology for the use of different steps in order to compare the results obtained in Computational Intelligence problems, as well as from other fields, such as for bioinformatics, cheminformatics, etc., given that our proposal is open and modifiable.

A methodology for the design of experiments in computational intelligence with multiple regression models

PubMed Central

Gestal, Marcos; Munteanu, Cristian R.; Dorado, Julian; Pazos, Alejandro

2016-01-01

The design of experiments and the validation of the results achieved with them are vital in any research study. This paper focuses on the use of different Machine Learning approaches for regression tasks in the field of Computational Intelligence and especially on a correct comparison between the different results provided for different methods, as those techniques are complex systems that require further study to be fully understood. A methodology commonly accepted in Computational intelligence is implemented in an R package called RRegrs. This package includes ten simple and complex regression models to carry out predictive modeling using Machine Learning and well-known regression algorithms. The framework for experimental design presented herein is evaluated and validated against RRegrs. Our results are different for three out of five state-of-the-art simple datasets and it can be stated that the selection of the best model according to our proposal is statistically significant and relevant. It is of relevance to use a statistical approach to indicate whether the differences are statistically significant using this kind of algorithms. Furthermore, our results with three real complex datasets report different best models than with the previously published methodology. Our final goal is to provide a complete methodology for the use of different steps in order to compare the results obtained in Computational Intelligence problems, as well as from other fields, such as for bioinformatics, cheminformatics, etc., given that our proposal is open and modifiable. PMID:27920952

An Effect Size for Regression Predictors in Meta-Analysis

ERIC Educational Resources Information Center

Aloe, Ariel M.; Becker, Betsy Jane

2012-01-01

A new effect size representing the predictive power of an independent variable from a multiple regression model is presented. The index, denoted as r[subscript sp], is the semipartial correlation of the predictor with the outcome of interest. This effect size can be computed when multiple predictor variables are included in the regression model…

Regression Analysis: Legal Applications in Institutional Research

ERIC Educational Resources Information Center

Frizell, Julie A.; Shippen, Benjamin S., Jr.; Luna, Andrew L.

2008-01-01

This article reviews multiple regression analysis, describes how its results should be interpreted, and instructs institutional researchers on how to conduct such analyses using an example focused on faculty pay equity between men and women. The use of multiple regression analysis will be presented as a method with which to compare salaries of…

RAWS II: A MULTIPLE REGRESSION ANALYSIS PROGRAM,

DTIC Science & Technology

This memorandum gives instructions for the use and operation of a revised version of RAWS, a multiple regression analysis program. The program...of preprocessed data, the directed retention of variable, listing of the matrix of the normal equations and its inverse, and the bypassing of the regression analysis to provide the input variable statistics only. (Author)

Incremental Net Effects in Multiple Regression

ERIC Educational Resources Information Center

Lipovetsky, Stan; Conklin, Michael

2005-01-01

A regular problem in regression analysis is estimating the comparative importance of the predictors in the model. This work considers the 'net effects', or shares of the predictors in the coefficient of the multiple determination, which is a widely used characteristic of the quality of a regression model. Estimation of the net effects can be a…

Floating Data and the Problem with Illustrating Multiple Regression.

ERIC Educational Resources Information Center

Sachau, Daniel A.

2000-01-01

Discusses how to introduce basic concepts of multiple regression by creating a large-scale, three-dimensional regression model using the classroom walls and floor. Addresses teaching points that should be covered and reveals student reaction to the model. Finds that the greatest benefit of the model is the low fear, walk-through, nonmathematical…

Using Multiple and Logistic Regression to Estimate the Median WillCost and Probability of Cost and Schedule Overrun for Program Managers

DTIC Science & Technology

2017-03-23

PUBLIC RELEASE; DISTRIBUTION UNLIMITED Using Multiple and Logistic Regression to Estimate the Median Will- Cost and Probability of Cost and... Cost and Probability of Cost and Schedule Overrun for Program Managers Ryan C. Trudelle Follow this and additional works at: https://scholar.afit.edu...afit.edu. Recommended Citation Trudelle, Ryan C., "Using Multiple and Logistic Regression to Estimate the Median Will- Cost and Probability of Cost and

Comparison between Linear and Nonlinear Regression in a Laboratory Heat Transfer Experiment

ERIC Educational Resources Information Center

Gonçalves, Carine Messias; Schwaab, Marcio; Pinto, José Carlos

2013-01-01

In order to interpret laboratory experimental data, undergraduate students are used to perform linear regression through linearized versions of nonlinear models. However, the use of linearized models can lead to statistically biased parameter estimates. Even so, it is not an easy task to introduce nonlinear regression and show for the students…

Posture-Motor and Posture-Ideomotor Dual-Tasking: A Putative Marker of Psychomotor Retardation and Depressive Rumination in Patients With Major Depressive Disorder.

PubMed

Aftanas, Lyubomir I; Bazanova, Olga M; Novozhilova, Nataliya V

2018-01-01

Background: Recent studies have demonstrated that the assessment of postural performance may be a potentially reliable and objective marker of the psychomotor retardation (PMR) in the major depressive disorder (MDD). One of the important facets of MDD-related PMR is reflected in disrupted central mechanisms of psychomotor control, heavily influenced by compelling maladaptive depressive rumination. In view of this we designed a research paradigm that included sequential execution of simple single-posture task followed by more challenging divided attention posture tasks, involving concurring motor and ideomotor workloads. Another difficulty dimension assumed executing of all the tasks with eyes open (EO) (easy) and closed (EC) (difficult) conditions. We aimed at investigating the interplay between the severity of MDD, depressive rumination, and efficiency of postural performance. Methods: Compared with 24 age- and body mass index-matched healthy controls (HCs), 26 patients with MDD sequentially executed three experimental tasks: (1) single-posture task of maintaining a quiet stance (ST), (2) actual posture-motor dual task (AMT); and (3) mental/imaginary posture-motor dual task (MMT). All the tasks were performed in the EO and the EC conditions. The primary dependent variable was the amount of kinetic energy ( E ) expended for the center of pressure deviations (CoPDs), whereas the absolute divided attention cost index showed energy cost to the dual-tasking vs. the single-posture task according to the formula: Δ E = ( E Dual-task - E Single-task ). Results: The signs of PMR in the MDD group were objectively indexed by deficient posture control in the EC condition along with overall slowness of fine motor and ideomotor activity. Another important and probably more challenging feature of the findings was that the posture deficit manifested in the ST condition was substantially and significantly attenuated in the MMT and AMT performance dual-tasking activity. A multiple linear regression analysis evidenced further that the dual-tasking energy cost (i.e., Δ E ) significantly predicted clinical scores of severity of MDD and depressive rumination. Conclusion: The findings allow to suggest that execution of concurrent actual or imaginary fine motor task with closed visual input deallocates attentional resources from compelling maladaptive depressive rumination thereby attenuating severity of absolute dual-tasking energy costs for balance maintenance in patients with MDD. Significance: Quantitative assessment of PMR through measures of the postural performance in dual-tasking may be useful to capture the negative impact of past depressive episodes, optimize the personalized treatment selection, and improve the understanding of the pathophysiological mechanisms underlying MDD.

Comparison of continuously acquired resting state and extracted analogues from active tasks

PubMed Central

Ganger, Sebastian; Hahn, Andreas; Küblböck, Martin; Kranz, Georg S.; Spies, Marie; Vanicek, Thomas; Seiger, René; Sladky, Ronald; Windischberger, Christian; Kasper, Siegfried

2015-01-01

Abstract Functional connectivity analysis of brain networks has become an important tool for investigation of human brain function. Although functional connectivity computations are usually based on resting‐state data, the application to task‐specific fMRI has received growing attention. Three major methods for extraction of resting‐state data from task‐related signal have been proposed (1) usage of unmanipulated task data for functional connectivity; (2) regression against task effects, subsequently using the residuals; and (3) concatenation of baseline blocks located in‐between task blocks. Despite widespread application in current research, consensus on which method best resembles resting‐state seems to be missing. We, therefore, evaluated these techniques in a sample of 26 healthy controls measured at 7 Tesla. In addition to continuous resting‐state, two different task paradigms were assessed (emotion discrimination and right finger‐tapping) and five well‐described networks were analyzed (default mode, thalamus, cuneus, sensorimotor, and auditory). Investigating the similarity to continuous resting‐state (Dice, Intraclass correlation coefficient (ICC), R 2) showed that regression against task effects yields functional connectivity networks most alike to resting‐state. However, all methods exhibited significant differences when compared to continuous resting‐state and similarity metrics were lower than test‐retest of two resting‐state scans. Omitting global signal regression did not change these findings. Visually, the networks are highly similar, but through further investigation marked differences can be found. Therefore, our data does not support referring to resting‐state when extracting signals from task designs, although functional connectivity computed from task‐specific data may indeed yield interesting information. Hum Brain Mapp 36:4053–4063, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:26178250

Imitating actions on objects in early-onset and regressive autism: Effects and implications of task characteristics on performance

PubMed Central

Rogers, Sally J.; Young, Gregory S.; Cook, Ian; Giolzetti, Angelo; Ozonoff, Sally

2010-01-01

This study was designed to examine the nature of object imitation performance in early autism. We hypothesized that imitation would be relatively preserved when behaviors on objects resulted in salient instrumental effects. We designed tasks in which, in one condition, the motor action resulted in a salient, meaningful effect on an object, whereas in the other condition, the same action resulted in a less salient effect because of differing object characteristics. The motor aspects of the tasks did not vary across conditions. Four participant groups of 2- to 5-year-olds were examined: 17 children with early-onset autism, 24 children with regressive onset autism, 22 children with developmental delays, and 22 children with typical development. Groups were matched on nonverbal skills, and differences in verbal development were examined as a moderator of imitative ability. Results revealed an interaction of group by condition, with the combined autism group failing more tasks than the combined comparison groups, and failing more tasks in the less salient condition than in the more salient condition, as hypothesized. Analyses of autism subgroups revealed these effects were primarily because of the regression onset group. Accuracy of motor performance was examined by analyzing errors. Among children passing imitative acts, there were no group differences and no condition effects in the number, type, or pattern of performance errors. Among children passing the tasks, the group with autism did not demonstrate more emulation errors (imitating the goal but not the means) than other groups. There was no evidence that either motor or attentional aspects of the tasks contributed to the poorer imitative performance of the children with autism. PMID:20102648

Tools to Support Interpreting Multiple Regression in the Face of Multicollinearity

PubMed Central

Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K.

2012-01-01

While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses. PMID:22457655

Tools to support interpreting multiple regression in the face of multicollinearity.

PubMed

Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K

2012-01-01

While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses.

Human interaction with an intelligent computer in multi-task situations

NASA Technical Reports Server (NTRS)

Rouse, W. B.

1975-01-01

A general formulation of human decision making in multiple task situations is presented. It includes a description of the state, event, and action space in which the multiple task supervisor operates. A specific application to a failure detection and correction situation is discussed and results of a simulation experiment presented. Issues considered include static vs. dynamic allocation of responsibility and competitive vs. cooperative intelligence.

The comparison between several robust ridge regression estimators in the presence of multicollinearity and multiple outliers

NASA Astrophysics Data System (ADS)

Zahari, Siti Meriam; Ramli, Norazan Mohamed; Moktar, Balkiah; Zainol, Mohammad Said

2014-09-01

In the presence of multicollinearity and multiple outliers, statistical inference of linear regression model using ordinary least squares (OLS) estimators would be severely affected and produces misleading results. To overcome this, many approaches have been investigated. These include robust methods which were reported to be less sensitive to the presence of outliers. In addition, ridge regression technique was employed to tackle multicollinearity problem. In order to mitigate both problems, a combination of ridge regression and robust methods was discussed in this study. The superiority of this approach was examined when simultaneous presence of multicollinearity and multiple outliers occurred in multiple linear regression. This study aimed to look at the performance of several well-known robust estimators; M, MM, RIDGE and robust ridge regression estimators, namely Weighted Ridge M-estimator (WRM), Weighted Ridge MM (WRMM), Ridge MM (RMM), in such a situation. Results of the study showed that in the presence of simultaneous multicollinearity and multiple outliers (in both x and y-direction), the RMM and RIDGE are more or less similar in terms of superiority over the other estimators, regardless of the number of observation, level of collinearity and percentage of outliers used. However, when outliers occurred in only single direction (y-direction), the WRMM estimator is the most superior among the robust ridge regression estimators, by producing the least variance. In conclusion, the robust ridge regression is the best alternative as compared to robust and conventional least squares estimators when dealing with simultaneous presence of multicollinearity and outliers.

The psychometrics of mental workload: multiple measures are sensitive but divergent.

PubMed

Matthews, Gerald; Reinerman-Jones, Lauren E; Barber, Daniel J; Abich, Julian

2015-02-01

A study was run to test the sensitivity of multiple workload indices to the differing cognitive demands of four military monitoring task scenarios and to investigate relationships between indices. Various psychophysiological indices of mental workload exhibit sensitivity to task factors. However, the psychometric properties of multiple indices, including the extent to which they intercorrelate, have not been adequately investigated. One hundred fifty participants performed in four task scenarios based on a simulation of unmanned ground vehicle operation. Scenarios required threat detection and/or change detection. Both single- and dual-task scenarios were used. Workload metrics for each scenario were derived from the electroencephalogram (EEG), electrocardiogram, transcranial Doppler sonography, functional near infrared, and eye tracking. Subjective workload was also assessed. Several metrics showed sensitivity to the differing demands of the four scenarios. Eye fixation duration and the Task Load Index metric derived from EEG were diagnostic of single-versus dual-task performance. Several other metrics differentiated the two single tasks but were less effective in differentiating single- from dual-task performance. Psychometric analyses confirmed the reliability of individual metrics but failed to identify any general workload factor. An analysis of difference scores between low- and high-workload conditions suggested an effort factor defined by heart rate variability and frontal cortex oxygenation. General workload is not well defined psychometrically, although various individual metrics may satisfy conventional criteria for workload assessment. Practitioners should exercise caution in using multiple metrics that may not correspond well, especially at the level of the individual operator.

An improved multiple linear regression and data analysis computer program package

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1972-01-01

NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.

Locus of Control and Sex Differences in Performance on an Instructional Task.

ERIC Educational Resources Information Center

Holloway, Richard L.; Robinson, Beatrice

1979-01-01

Used locus of control, ability, sex, task selection, task structure, and recall in a regression model to predict affective response to type of instruction of 104 high school seniors. Results showed a main effect for recall, and interaction effects for recall x sex and recall x ability. References are listed. (Author/JEG)

Variables Associated with Communicative Participation in People with Multiple Sclerosis: A Regression Analysis

ERIC Educational Resources Information Center

Baylor, Carolyn; Yorkston, Kathryn; Bamer, Alyssa; Britton, Deanna; Amtmann, Dagmar

2010-01-01

Purpose: To explore variables associated with self-reported communicative participation in a sample (n = 498) of community-dwelling adults with multiple sclerosis (MS). Method: A battery of questionnaires was administered online or on paper per participant preference. Data were analyzed using multiple linear backward stepwise regression. The…

Relationships between Spontaneous Note-Taking, Self-Reported Strategies and Comprehension When Reading Multiple Texts in Different Task Conditions

ERIC Educational Resources Information Center

Hagen, Åste M.; Braasch, Jason L. G.; Bråten, Ivar

2014-01-01

This study investigated note-taking during multiple-text reading across two different task conditions in relation to comprehension performance and self-reports of strategy use. Forty-four undergraduates read multiple texts about climate change to write an argument or a summary. Analysis of students' spontaneous note-taking during reading…

Relationships between Reward Sensitivity, Risk-Taking and Family History of Alcoholism during an Interactive Competitive fMRI Task

PubMed Central

Yarosh, Haley L.; Hyatt, Christopher J.; Meda, Shashwath A.; Jiantonio-Kelly, Rachel; Potenza, Marc N.; Assaf, Michal; D.Pearlson, Godfrey

2014-01-01

Background Individuals with a positive family history for alcoholism (FHP) have shown differences from family-history-negative (FHN) individuals in the neural correlates of reward processing. FHP, compared to FHN individuals, demonstrate relatively diminished ventral striatal activation during anticipation of monetary rewards, and the degree of ventral striatal activation shows an inverse correlation with specific impulsivity measures in alcohol-dependent individuals. Rewards in socially interactive contexts relate importantly to addictive propensities, yet have not been examined with respect to how their neural underpinnings relate to impulsivity-related measures. Here we describe impulsivity measures in FHN and FHP individuals as they relate to a socially interactive functional magnetic resonance imaging (fMRI) task. Methods Forty FHP and 29 FHN subjects without histories of Axis-I disorders completed a socially interactive Domino task during functional magnetic resonance imaging and completed self-report and behavioral impulsivity-related assessments. Results FHP compared to FHN individuals showed higher scores (p = .004) on one impulsivity-related factor relating to both compulsivity (Padua Inventory) and reward/punishment sensitivity (Sensitivity to Punishment/Sensitivity to Reward Questionnaire). Multiple regression analysis within a reward-related network revealed a correlation between risk-taking (involving another impulsivity-related factor, the Balloon Analog Risk Task (BART)) and right ventral striatum activation under reward >punishment contrast (p<0.05 FWE corrected) in the social task. Conclusions Behavioral risk-taking scores may be more closely associated with neural correlates of reward responsiveness in socially interactive contexts than are FH status or impulsivity-related self-report measures. These findings suggest that risk-taking assessments be examined further in socially interactive settings relevant to addictive behaviors. PMID:24505424

Relationship between sports experience and executive function in 6-12-year-old children: independence from physical fitness and moderation by gender.

PubMed

Ishihara, Toru; Sugasawa, Shigemi; Matsuda, Yusuke; Mizuno, Masao

2018-05-01

The purpose of this study was to evaluate the relationship between sports experience (i.e., tennis experience) and executive function in children while controlling for physical activity and physical fitness. Sixty-eight participants (6-12 years old, 34 males and 34 females) were enrolled in regular tennis lessons (mean = 2.4 years, range = 0.1-7.3 years) prior to the study. Executive functions, including inhibitory control (the Stroop Color-Word Test), working memory (the 2-back Task), and cognitive flexibility (the Local-global Task) were evaluated. Participants' levels of daily physical activity, ranging from moderate to vigorous, were evaluated using triaxial accelerometers. The total score for physical fitness was assessed using the Tennis Field Test. Hierarchical multiple regression analyses revealed interaction effects between gender and tennis experience on participants' reaction time (RT) on the switch cost of the Local-global Task after controlling for age, BMI, gender, physical activity, physical fitness, and tennis experience. Longer tennis experience was associated with shorter switch cost in males but not in females. Higher scores on physical fitness were positively associated with lower interference scores on the Stroop Color-Word Test, RT on the 2-back Task, and RT in the switching condition of the Local-global Task, after controlling for age, BMI, gender, and physical activity. In conclusion, all three foundational components of executive function (i.e., inhibitory control, working memory, and cognitive flexibility) were more strongly related to physical fitness than to physical activity in males and females, whereas greater cognitive flexibility was related to tennis experience only in the males. © 2017 John Wiley & Sons Ltd.

Work related stress and blood glucose levels.

PubMed

Sancini, A; Ricci, S; Tomei, F; Sacco, C; Pacchiarotti, A; Nardone, N; Ricci, P; Suppi, A; De Cesare, D P; Anzelmo, V; Giubilati, R; Pimpinella, B; Rosati, M V; Tomei, G

2017-01-01

The aim of the study is to evaluate work-related subjective stress in a group of workers on a major Italian company in the field of healthcare through the administration of a valid "questionnaire-tool indicator" (HSE Indicator Tool), and to analyze any correlation between stress levels taken from questionnaire scores and blood glucose values. We studied a final sample consisting of 241 subjects with different tasks. The HSE questionnaire - made up of 35 items (divided into 7 organizational dimensions) with 5 possible answers - has been distributed to all the subjects in occasion of the health surveillance examinations provided by law. The questionnaire was then analyzed using its specific software to process the results related to the 7 dimensions. These results were compared using the Pearson correlation and multiple linear regression with the blood glucose values obtained from each subject. From the analysis of the data the following areas resulted critical, in other words linked to an intermediate (yellow area) or high (red area) condition of stress: sustain from managers, sustain from colleagues, quality of relationships and professional changes. A significant positive correlation (p <0.05) between the mean values of all critical areas and the concentrations of glucose values have been highlighted with the correlation index of Pearson. Multiple linear regression confirmed these findings, showing that the critical dimensions resulting from the questionnaire were the significant variables that can increase the levels of blood glucose. The preliminary results indicate that perceived work stress can be statistically associated with increased levels of blood glucose.

Impulsivity, attention, memory, and decision-making among adolescent marijuana users.

PubMed

Dougherty, Donald M; Mathias, Charles W; Dawes, Michael A; Furr, R Michael; Charles, Nora E; Liguori, Anthony; Shannon, Erin E; Acheson, Ashley

2013-03-01

Marijuana is a popular drug of abuse among adolescents, and they may be uniquely vulnerable to resulting cognitive and behavioral impairments. Previous studies have found impairments among adolescent marijuana users. However, the majority of this research has examined measures individually rather than multiple domains in a single cohesive analysis. This study used a logistic regression model that combines performance on a range of tasks to identify which measures were most altered among adolescent marijuana users. The purpose of this research was to determine unique associations between adolescent marijuana use and performances on multiple cognitive and behavioral domains (attention, memory, decision-making, and impulsivity) in 14- to 17-year-olds while simultaneously controlling for performances across the measures to determine which measures most strongly distinguish marijuana users from nonusers. Marijuana-using adolescents (n = 45) and controls (n = 48) were tested. Logistic regression analyses were conducted to test for: (1) differences between marijuana users and nonusers on each measure, (2) associations between marijuana use and each measure after controlling for the other measures, and (3) the degree to which (1) and (2) together elucidated differences among marijuana users and nonusers. Of all the cognitive and behavioral domains tested, impaired short-term recall memory and consequence sensitivity impulsivity were associated with marijuana use after controlling for performances across all measures. This study extends previous findings by identifying cognitive and behavioral impairments most strongly associated with adolescent marijuana users. These specific deficits are potential targets of intervention for this at-risk population.

Resting-state functional connectivity in multiple sclerosis: an examination of group differences and individual differences.

PubMed

Janssen, Alisha L; Boster, Aaron; Patterson, Beth A; Abduljalil, Amir; Prakash, Ruchika Shaurya

2013-11-01

Multiple sclerosis (MS) is a neurodegenerative, inflammatory disease of the central nervous system, resulting in physical and cognitive disturbances. The goal of the current study was to examine the association between network integrity and composite measures of cognition and disease severity in individuals with relapsing-remitting MS (RRMS), relative to healthy controls. All participants underwent a neuropsychological and neuroimaging session, where resting-state data was collected. Independent component analysis and dual regression were employed to examine network integrity in individuals with MS, relative to healthy controls. The MS sample exhibited less connectivity in the motor and visual networks, relative to healthy controls, after controlling for group differences in gray matter volume. However, no alterations were observed in the frontoparietal, executive control, or default-mode networks, despite previous evidence of altered neuronal patterns during tasks of exogenous processing. Whole-brain, voxel-wise regression analyses with disease severity and processing speed composites were also performed to elucidate the brain-behavior relationship with neuronal network integrity. Individuals with higher levels of disease severity demonstrated reduced intra-network connectivity of the motor network, and the executive control network, while higher disease burden was associated with greater inter-network connectivity between the medial visual network and areas involved in visuomotor learning. Our findings underscore the importance of examining resting-state oscillations in this population, both as a biomarker of disease progression and a potential target for therapeutic intervention. Copyright © 2013 Elsevier Ltd. All rights reserved.

Visual discrimination in the pigeon (Columba livia): effects of selective lesions of the nucleus rotundus

NASA Technical Reports Server (NTRS)

Laverghetta, A. V.; Shimizu, T.

1999-01-01

The nucleus rotundus is a large thalamic nucleus in birds and plays a critical role in many visual discrimination tasks. In order to test the hypothesis that there are functionally distinct subdivisions in the nucleus rotundus, effects of selective lesions of the nucleus were studied in pigeons. The birds were trained to discriminate between different types of stationary objects and between different directions of moving objects. Multiple regression analyses revealed that lesions in the anterior, but not posterior, division caused deficits in discrimination of small stationary stimuli. Lesions in neither the anterior nor posterior divisions predicted effects in discrimination of moving stimuli. These results are consistent with a prediction led from the hypothesis that the nucleus is composed of functional subdivisions.

Sportsmanship in young athletes: the role of competitiveness, motivational orientation, and perceived purposes of sport.

PubMed

Ryska, Todd A

2003-05-01

The purpose of the study was to evaluate measures of competitiveness, motivational orientation, and perceived purposes of participation as predictors of sportsmanship in a sample of 319 young participants in sports. Hierarchical regression analyses indicated that intrinsic reasons for sports participation, such as enhanced self-esteem and task mastery, predicted higher levels on multiple dimensions of sportsmanship, above and beyond the influence of competitiveness, motivational orientation, and various demographic variables. In contrast, extrinsic purposes for participation in sports, such as to obtain social status and a high-status career, contributed to lower levels on 3 of the 4 sportsmanship dimensions. These results are discussed with regard to developing a competitive sport setting that promotes ethical standards of interpersonal behavior for young participants in sports.

Algorithm-Dependent Generalization Bounds for Multi-Task Learning.

PubMed

Liu, Tongliang; Tao, Dacheng; Song, Mingli; Maybank, Stephen J

2017-02-01

Often, tasks are collected for multi-task learning (MTL) because they share similar feature structures. Based on this observation, in this paper, we present novel algorithm-dependent generalization bounds for MTL by exploiting the notion of algorithmic stability. We focus on the performance of one particular task and the average performance over multiple tasks by analyzing the generalization ability of a common parameter that is shared in MTL. When focusing on one particular task, with the help of a mild assumption on the feature structures, we interpret the function of the other tasks as a regularizer that produces a specific inductive bias. The algorithm for learning the common parameter, as well as the predictor, is thereby uniformly stable with respect to the domain of the particular task and has a generalization bound with a fast convergence rate of order O(1/n), where n is the sample size of the particular task. When focusing on the average performance over multiple tasks, we prove that a similar inductive bias exists under certain conditions on the feature structures. Thus, the corresponding algorithm for learning the common parameter is also uniformly stable with respect to the domains of the multiple tasks, and its generalization bound is of the order O(1/T), where T is the number of tasks. These theoretical analyses naturally show that the similarity of feature structures in MTL will lead to specific regularizations for predicting, which enables the learning algorithms to generalize fast and correctly from a few examples.

Multiple task performance as a predictor of the potential of air traffic controller trainees.

DOT National Transportation Integrated Search

1972-01-01

Two hundred and twenty-nine air traffic controller trainees were tested on the CAMI Multiple Task Performance Battery. The battery provides objective measures of monitoring, arithmetical skills, visual discrimination, and group problem solving. The c...

Contribution of calcaneal and leg segment rotations to ankle joint dorsiflexion in a weight-bearing task.

PubMed

Chizewski, Michael G; Chiu, Loren Z F

2012-05-01

Joint angle is the relative rotation between two segments where one is a reference and assumed to be non-moving. However, rotation of the reference segment will influence the system's spatial orientation and joint angle. The purpose of this investigation was to determine the contribution of leg and calcaneal rotations to ankle rotation in a weight-bearing task. Forty-eight individuals performed partial squats recorded using a 3D motion capture system. Markers on the calcaneus and leg were used to model leg and calcaneal segment, and ankle joint rotations. Multiple linear regression was used to determine the contribution of leg and calcaneal segment rotations to ankle joint dorsiflexion. Regression models for left (R(2)=0.97) and right (R(2)=0.97) ankle dorsiflexion were significant. Sagittal plane leg rotation had a positive influence (left: β=1.411; right: β=1.418) while sagittal plane calcaneal rotation had a negative influence (left: β=-0.573; right: β=-0.650) on ankle dorsiflexion. Sagittal plane rotations of the leg and calcaneus were positively correlated (left: r=0.84, P<0.001; right: r=0.80, P<0.001). During a partial squat, the calcaneus rotates forward. Simultaneous forward calcaneal rotation with ankle dorsiflexion reduces total ankle dorsiflexion angle. Rear foot posture is reoriented during a partial squat, allowing greater leg rotation in the sagittal plane. Segment rotations may provide greater insight into movement mechanics that cannot be explained via joint rotations alone. Copyright © 2012 Elsevier B.V. All rights reserved.

Predictors of postoperative outcomes of cubital tunnel syndrome treatments using multiple logistic regression analysis.

PubMed

Suzuki, Taku; Iwamoto, Takuji; Shizu, Kanae; Suzuki, Katsuji; Yamada, Harumoto; Sato, Kazuki

2017-05-01

This retrospective study was designed to investigate prognostic factors for postoperative outcomes for cubital tunnel syndrome (CubTS) using multiple logistic regression analysis with a large number of patients. Eighty-three patients with CubTS who underwent surgeries were enrolled. The following potential prognostic factors for disease severity were selected according to previous reports: sex, age, type of surgery, disease duration, body mass index, cervical lesion, presence of diabetes mellitus, Workers' Compensation status, preoperative severity, and preoperative electrodiagnostic testing. Postoperative severity of disease was assessed 2 years after surgery by Messina's criteria which is an outcome measure specifically for CubTS. Bivariate analysis was performed to select candidate prognostic factors for multiple linear regression analyses. Multiple logistic regression analysis was conducted to identify the association between postoperative severity and selected prognostic factors. Both bivariate and multiple linear regression analysis revealed only preoperative severity as an independent risk factor for poor prognosis, while other factors did not show any significant association. Although conflicting results exist regarding prognosis of CubTS, this study supports evidence from previous studies and concludes early surgical intervention portends the most favorable prognosis. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Functional Neuroanatomy Involved in Automatic order Mental Arithmetic and Recitation of the Multiplication Table

NASA Astrophysics Data System (ADS)

Wang, Li-Qun; Saito, Masao

We used 1.5T functional magnetic resonance imaging (fMRI) to explore that which brain areas contribute uniquely to numeric computation. The BOLD effect activation pattern of metal arithmetic task (successive subtraction: actual calculation task) was compared with multiplication tables repetition task (rote verbal arithmetic memory task) response. The activation found in right parietal lobule during metal arithmetic task suggested that quantitative cognition or numeric computation may need the assistance of sensuous convert, such as spatial imagination and spatial sensuous convert. In addition, this mechanism may be an ’analog algorithm’ in the simple mental arithmetic processing.

Age-Related Imbalance Is Associated With Slower Walking Speed: An Analysis From the National Health and Nutrition Examination Survey.

PubMed

Xie, Yanjun J; Liu, Elizabeth Y; Anson, Eric R; Agrawal, Yuri

Walking speed is an important dimension of gait function and is known to decline with age. Gait function is a process of dynamic balance and motor control that relies on multiple sensory inputs (eg, visual, proprioceptive, and vestibular) and motor outputs. These sensory and motor physiologic systems also play a role in static postural control, which has been shown to decline with age. In this study, we evaluated whether imbalance that occurs as part of healthy aging is associated with slower walking speed in a nationally representative sample of older adults. We performed a cross-sectional analysis of the previously collected 1999 to 2002 National Health and Nutrition Examination Survey (NHANES) data to evaluate whether age-related imbalance is associated with slower walking speed in older adults aged 50 to 85 years (n = 2116). Balance was assessed on a pass/fail basis during a challenging postural task-condition 4 of the modified Romberg Test-and walking speed was determined using a 20-ft (6.10 m) timed walk. Multivariable linear regression was used to evaluate the association between imbalance and walking speed, adjusting for demographic and health-related covariates. A structural equation model was developed to estimate the extent to which imbalance mediates the association between age and slower walking speed. In the unadjusted regression model, inability to perform the NHANES balance task was significantly associated with 0.10 m/s slower walking speed (95% confidence interval: -0.13 to -0.07; P < .01). In the multivariable regression analysis, inability to perform the balance task was significantly associated with 0.06 m/s slower walking speed (95% confidence interval: -0.09 to -0.03; P < .01), an effect size equivalent to 12 years of age. The structural equation model estimated that age-related imbalance mediates 12.2% of the association between age and slower walking speed in older adults. In a nationally representative sample, age-related balance limitation was associated with slower walking speed. Balance impairment may lead to walking speed declines. In addition, reduced static postural control and dynamic walking speed that occur with aging may share common etiologic origins, including the decline in visual, proprioceptive, and vestibular sensory and motor functions.

Cognitive declines in healthy aging: evidence from multiple aspects of interference resolution.

PubMed

Pettigrew, Corinne; Martin, Randi C

2014-06-01

The present study tested the hypothesis that older adults show age-related deficits in interference resolution, also referred to as inhibitory control. Although oftentimes considered as a unitary aspect of executive function, various lines of work support the notion that interference resolution may be better understood as multiple constructs, including resistance to proactive interference (PI) and response-distractor inhibition (e.g., Friedman & Miyake, 2004). Using this dichotomy, the present study assessed whether older adults (relative to younger adults) show impaired performance across both, 1, or neither of these interference resolution constructs. To do so, we used multiple tasks to tap each construct and examined age effects at both the single task and latent variable levels. Older adults consistently demonstrated exaggerated interference effects across resistance to PI tasks. Although the results for the response-distractor inhibition tasks were less consistent at the individual task level analyses, age effects were evident on multiple tasks, as well as at the latent variable level. However, results of the latent variable modeling suggested declines in interference resolution are best explained by variance that is common to the 2 interference resolution constructs measured herein. Furthermore, the effect of age on interference resolution was found to be both distinct from declines in working memory, and independent of processing speed. These findings suggest multiple cognitive domains are independently sensitive to age, but that declines in the interference resolution constructs measured herein may originate from a common cause. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Which Feedback Is More Effective for Pursuing Multiple Goals of Differing Importance? The Interaction Effects of Goal Importance and Performance Feedback Type on Self-Regulation and Task Achievement

ERIC Educational Resources Information Center

Lee, Hyunjoo

2016-01-01

This study examined how performance feedback type (progress vs. distance) affects Korean college students' self-regulation and task achievement according to relative goal importance in the pursuit of multiple goals. For this study, 146 students participated in a computerised task. The results showed the interaction effects of goal importance and…

Dual task cost of walking is related to fall risk in persons with multiple sclerosis.

PubMed

Wajda, Douglas A; Motl, Robert W; Sosnoff, Jacob J

2013-12-15

Persons with multiple sclerosis (MS) commonly have walking and cognitive impairments. While walking with a simultaneous cognitive task, persons with MS experience a greater decline in walking performance than healthy controls. This change in performance is termed dual task cost or dual task interference and has been associated with fall risk in older adults. We examined whether dual task cost during walking was related to fall risk in persons with MS. Thirty-three ambulatory persons with MS performed walking tasks with and without a concurrent cognitive task (dual task condition) as well as underwent a fall risk assessment. Dual task cost was operationalized as the percent change in velocity from normal walking conditions to dual task walking conditions. Fall risk was quantified using the Physiological Profile Assessment. A Spearman correlation analysis revealed a significant positive correlation between dual task cost of walking velocity and fall risk as well as dual task cost of stride length and fall risk. Overall, the findings indicate that dual task cost is associated with fall risk and may be an important target for falls prevention strategies. © 2013.

The Geometry of Enhancement in Multiple Regression

ERIC Educational Resources Information Center

Waller, Niels G.

2011-01-01

In linear multiple regression, "enhancement" is said to occur when R[superscript 2] = b[prime]r greater than r[prime]r, where b is a p x 1 vector of standardized regression coefficients and r is a p x 1 vector of correlations between a criterion y and a set of standardized regressors, x. When p = 1 then b [is congruent to] r and…

Arabic handwritten: pre-processing and segmentation

NASA Astrophysics Data System (ADS)

Maliki, Makki; Jassim, Sabah; Al-Jawad, Naseer; Sellahewa, Harin

2012-06-01

This paper is concerned with pre-processing and segmentation tasks that influence the performance of Optical Character Recognition (OCR) systems and handwritten/printed text recognition. In Arabic, these tasks are adversely effected by the fact that many words are made up of sub-words, with many sub-words there associated one or more diacritics that are not connected to the sub-word's body; there could be multiple instances of sub-words overlap. To overcome these problems we investigate and develop segmentation techniques that first segment a document into sub-words, link the diacritics with their sub-words, and removes possible overlapping between words and sub-words. We shall also investigate two approaches for pre-processing tasks to estimate sub-words baseline, and to determine parameters that yield appropriate slope correction, slant removal. We shall investigate the use of linear regression on sub-words pixels to determine their central x and y coordinates, as well as their high density part. We also develop a new incremental rotation procedure to be performed on sub-words that determines the best rotation angle needed to realign baselines. We shall demonstrate the benefits of these proposals by conducting extensive experiments on publicly available databases and in-house created databases. These algorithms help improve character segmentation accuracy by transforming handwritten Arabic text into a form that could benefit from analysis of printed text.

The Pitch Imagery Arrow Task: Effects of Musical Training, Vividness, and Mental Control

PubMed Central

Gelding, Rebecca W.; Thompson, William Forde; Johnson, Blake W.

2015-01-01

Musical imagery is a relatively unexplored area, partly because of deficiencies in existing experimental paradigms, which are often difficult, unreliable, or do not provide objective measures of performance. Here we describe a novel protocol, the Pitch Imagery Arrow Task (PIAT), which induces and trains pitch imagery in both musicians and non-musicians. Given a tonal context and an initial pitch sequence, arrows are displayed to elicit a scale-step sequence of imagined pitches, and participants indicate whether the final imagined tone matches an audible probe. It is a staircase design that accommodates individual differences in musical experience and imagery ability. This new protocol was used to investigate the roles that musical expertise, self-reported auditory vividness and mental control play in imagery performance. Performance on the task was significantly better for participants who employed a musical imagery strategy compared to participants who used an alternative cognitive strategy and positively correlated with scores on the Control subscale from the Bucknell Auditory Imagery Scale (BAIS). Multiple regression analysis revealed that Imagery performance accuracy was best predicted by a combination of strategy use and scores on the Vividness subscale of BAIS. These results confirm that competent performance on the PIAT requires active musical imagery and is very difficult to achieve using alternative cognitive strategies. Auditory vividness and mental control were more important than musical experience in the ability to perform manipulation of pitch imagery. PMID:25807078

THE EFFECT OF PLAUSIBILITY ON SENTENCE COMPREHENSION AMONG OLDER ADULTS AND ITS RELATION TO COGNITIVE FUNCTIONS

PubMed Central

Yoon, Jungmee; Campanelli, Luca; Goral, Mira; Marton, Klara; Eichorn, Naomi; Obler, Loraine K.

2016-01-01

Background/Study Context Older adults show age-related decline in complex-sentence comprehension. This has been attributed to a decrease in cognitive abilities that may support language processing, such as working memory (e.g., Caplan, DeDe, Waters, & Michaud, 2011,Psychology and Aging, 26, 439–450). The authors examined whether older adults have difficulty comprehending semantically implausible sentences and whether specific executive functions contribute to their comprehension performance. Methods Forty-two younger adults (aged 18–35) and 42 older adults (aged 55–75) were tested on two experimental tasks: a multiple negative comprehension task and an information processing battery. Results Both groups, older and younger adults, showed poorer performance for implausible sentences than for plausible sentences; however, no interaction was found between plausibility and age group. A regression analysis revealed that inhibition efficiency, as measured by a task that required resistance to proactive interference, predicted comprehension of implausible sentences in older adults only. Consistent with the compensation hypothesis, the older adults with better inhibition skills showed better comprehension than those with poor inhibition skills. Conclusion The findings suggest that semantic implausibility, along with syntactic complexity, increases linguistic and cognitive processing loads on auditory sentence comprehension. Moreover, the contribution of inhibitory control to the processing of semantic plausibility, particularly among older adults, suggests that the relationship between cognitive ability and language comprehension is strongly influenced by age. PMID:25978447

The effect of plausibility on sentence comprehension among older adults and its relation to cognitive functions.

PubMed

Yoon, Jungmee; Campanelli, Luca; Goral, Mira; Marton, Klara; Eichorn, Naomi; Obler, Loraine K

2015-01-01

BACKGROUND/STUDY CONTEXT: Older adults show age-related decline in complex-sentence comprehension. This has been attributed to a decrease in cognitive abilities that may support language processing, such as working memory (e.g., Caplan, DeDe, Waters, & Michaud, 2011,Psychology and Aging, 26, 439-450). The authors examined whether older adults have difficulty comprehending semantically implausible sentences and whether specific executive functions contribute to their comprehension performance. Forty-two younger adults (aged 18-35) and 42 older adults (aged 55-75) were tested on two experimental tasks: a multiple negative comprehension task and an information processing battery. Both groups, older and younger adults, showed poorer performance for implausible sentences than for plausible sentences; however, no interaction was found between plausibility and age group. A regression analysis revealed that inhibition efficiency, as measured by a task that required resistance to proactive interference, predicted comprehension of implausible sentences in older adults only. Consistent with the compensation hypothesis, the older adults with better inhibition skills showed better comprehension than those with poor inhibition skills. The findings suggest that semantic implausibility, along with syntactic complexity, increases linguistic and cognitive processing loads on auditory sentence comprehension. Moreover, the contribution of inhibitory control to the processing of semantic plausibility, particularly among older adults, suggests that the relationship between cognitive ability and language comprehension is strongly influenced by age.

Advanced statistics: linear regression, part I: simple linear regression.

PubMed

Marill, Keith A

2004-01-01

Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

The source of dual-task limitations: Serial or parallel processing of multiple response selections?

PubMed Central

Marois, René

2014-01-01

Although it is generally recognized that the concurrent performance of two tasks incurs costs, the sources of these dual-task costs remain controversial. The serial bottleneck model suggests that serial postponement of task performance in dual-task conditions results from a central stage of response selection that can only process one task at a time. Cognitive-control models, by contrast, propose that multiple response selections can proceed in parallel, but that serial processing of task performance is predominantly adopted because its processing efficiency is higher than that of parallel processing. In the present study, we empirically tested this proposition by examining whether parallel processing would occur when it was more efficient and financially rewarded. The results indicated that even when parallel processing was more efficient and was incentivized by financial reward, participants still failed to process tasks in parallel. We conclude that central information processing is limited by a serial bottleneck. PMID:23864266

Mission control of multiple unmanned aerial vehicles: a workload analysis.

PubMed

Dixon, Stephen R; Wickens, Christopher D; Chang, Dervon

2005-01-01

With unmanned aerial vehicles (UAVs), 36 licensed pilots flew both single-UAV and dual-UAV simulated military missions. Pilots were required to navigate each UAV through a series of mission legs in one of the following three conditions: a baseline condition, an auditory autoalert condition, and an autopilot condition. Pilots were responsible for (a) mission completion, (b) target search, and (c) systems monitoring. Results revealed that both the autoalert and the autopilot automation improved overall performance by reducing task interference and alleviating workload. The autoalert system benefited performance both in the automated task and mission completion task, whereas the autopilot system benefited performance in the automated task, the mission completion task, and the target search task. Practical implications for the study include the suggestion that reliable automation can help alleviate task interference and reduce workload, thereby allowing pilots to better handle concurrent tasks during single- and multiple-UAV flight control.

Multiple task performance as a predictor of the potential of air traffic controller trainees : a followup study.

DOT National Transportation Integrated Search

1974-11-01

Two hundred and twenty-nine air traffic controller trainees were tested on the CAMI Multiple Task Performance Battery. The battery provides objective measures of monitoring, arithmetical skills, visual discrimination, and group problem solving. The c...

Decreased cerebellar-cerebral connectivity contributes to complex task performance

PubMed Central

Knops, André

2016-01-01

The cerebellum's role in nonmotor processes is now well accepted, but cerebellar interaction with cerebral targets is not well understood. Complex cognitive tasks activate cerebellar, parietal, and frontal regions, but the effective connectivity between these regions has never been tested. To this end, we used psycho-physiological interactions (PPI) analysis to test connectivity changes of cerebellar and parietal seed regions in complex (2-digit by 1-digit multiplication, e.g., 12 × 3) vs. simple (1-digit by 1-digit multiplication, e.g., 4 × 3) task conditions (“complex − simple”). For cerebellar seed regions (lobule VI, hemisphere and vermis), we found significantly decreased cerebellar-parietal, cerebellar-cingulate, and cerebellar-frontal connectivity in complex multiplication. For parietal seed regions (PFcm, PFop, PFm) we found significantly increased parietal-parietal and parietal-frontal connectivity in complex multiplication. These results suggest that decreased cerebellar-cerebral connectivity contributes to complex task performance. Interestingly, BOLD activity contrasts revealed partially overlapping parietal areas of increased BOLD activity but decreased cerebellar-parietal PPI connectivity. PMID:27334957

Using Contact Forces and Robot Arm Accelerations to Automatically Rate Surgeon Skill at Peg Transfer.

PubMed

Brown, Jeremy D; O Brien, Conor E; Leung, Sarah C; Dumon, Kristoffel R; Lee, David I; Kuchenbecker, Katherine J

2017-09-01

Most trainees begin learning robotic minimally invasive surgery by performing inanimate practice tasks with clinical robots such as the Intuitive Surgical da Vinci. Expert surgeons are commonly asked to evaluate these performances using standardized five-point rating scales, but doing such ratings is time consuming, tedious, and somewhat subjective. This paper presents an automatic skill evaluation system that analyzes only the contact force with the task materials, the broad-bandwidth accelerations of the robotic instruments and camera, and the task completion time. We recruited N = 38 participants of varying skill in robotic surgery to perform three trials of peg transfer with a da Vinci Standard robot instrumented with our Smart Task Board. After calibration, three individuals rated these trials on five domains of the Global Evaluative Assessment of Robotic Skill (GEARS) structured assessment tool, providing ground-truth labels for regression and classification machine learning algorithms that predict GEARS scores based on the recorded force, acceleration, and time signals. Both machine learning approaches produced scores on the reserved testing sets that were in good to excellent agreement with the human raters, even when the force information was not considered. Furthermore, regression predicted GEARS scores more accurately and efficiently than classification. A surgeon's skill at robotic peg transfer can be reliably rated via regression using features gathered from force, acceleration, and time sensors external to the robot. We expect improved trainee learning as a result of providing these automatic skill ratings during inanimate task practice on a surgical robot.

Flexible modulation of network connectivity related to cognition in Alzheimer's disease.

PubMed

McLaren, Donald G; Sperling, Reisa A; Atri, Alireza

2014-10-15

Functional neuroimaging tools, such as fMRI methods, may elucidate the neural correlates of clinical, behavioral, and cognitive performance. Most functional imaging studies focus on regional task-related activity or resting state connectivity rather than how changes in functional connectivity across conditions and tasks are related to cognitive and behavioral performance. To investigate the promise of characterizing context-dependent connectivity-behavior relationships, this study applies the method of generalized psychophysiological interactions (gPPI) to assess the patterns of associative-memory-related fMRI hippocampal functional connectivity in Alzheimer's disease (AD) associated with performance on memory and other cognitively demanding neuropsychological tests and clinical measures. Twenty-four subjects with mild AD dementia (ages 54-82, nine females) participated in a face-name paired-associate encoding memory study. Generalized PPI analysis was used to estimate the connectivity between the hippocampus and the whole brain during encoding. The difference in hippocampal-whole brain connectivity between encoding novel and encoding repeated face-name pairs was used in multiple-regression analyses as an independent predictor for 10 behavioral, neuropsychological and clinical tests. The analysis revealed connectivity-behavior relationships that were distributed, dynamically overlapping, and task-specific within and across intrinsic networks; hippocampal-whole brain connectivity-behavior relationships were not isolated to single networks, but spanned multiple brain networks. Importantly, these spatially distributed performance patterns were unique for each measure. In general, out-of-network behavioral associations with encoding novel greater than repeated face-name pairs hippocampal-connectivity were observed in the default-mode network, while correlations with encoding repeated greater than novel face-name pairs hippocampal-connectivity were observed in the executive control network (p<0.05, cluster corrected). Psychophysiological interactions revealed significantly more extensive and robust associations between paired-associate encoding task-dependent hippocampal-whole brain connectivity and performance on memory and behavioral/clinical measures than previously revealed by standard activity-behavior analysis. Compared to resting state and task-activation methods, gPPI analyses may be more sensitive to reveal additional complementary information regarding subtle within- and between-network relations. The patterns of robust correlations between hippocampal-whole brain connectivity and behavioral measures identified here suggest that there are 'coordinated states' in the brain; that the dynamic range of these states is related to behavior and cognition; and that these states can be observed and quantified, even in individuals with mild AD. Copyright © 2014 Elsevier Inc. All rights reserved.

Effects of dual-task balance training on postural performance in patients with Multiple Sclerosis: a double-blind, randomized controlled pilot trial.

PubMed

Monjezi, Saeideh; Negahban, Hossein; Tajali, Shirin; Yadollahpour, Nava; Majdinasab, Nastaran

2017-02-01

To investigate the effects of dual-task balance training on postural performance in patients with multiple sclerosis as compared with single-task balance training. Double-blind, pretest-posttest, randomized controlled pilot trial. Local Multiple Sclerosis Society. A total of 47 patients were randomly assigned to two equal groups labeled as single-task training and dual-task training groups. All patients received supervised balance training sessions, 3 times per week for 4 weeks. The patients in the single-task group performed balance activities, alone. However, patients in dual-task group practiced balance activities while simultaneously performing cognitive tasks. The 10-Meter Walk Test and Timed Up-and-Go under single-task and dual-task conditions, in addition to Activities-specific Balance Confidence, Berg Balance Scale, and Functional Gait Assessment were assessed pre-, and post intervention and also 6-weeks after the end of intervention. Only 38 patients completed the treatment plan. There was no difference in the amount of improvement seen between the two study groups. In both groups there was a significant effect of time for dual-10 Meter Walk Test (F 1, 36 =11.33, p=0.002) and dual-Timed Up-and-Go (F 1, 36 =14.27, p=0.001) but not for their single-tasks. Moreover, there was a significant effect of time for Activities-specific Balance Confidence, Berg Balance Scale, and Functional Gait Assessment ( P<0.01). This pilot study did not show more benefits from undertaking dual-task training than single-task training. A power analysis showed 71 patients per group would be needed to determine whether there was a clinically relevant difference for dual-task gait speed between the groups.

Executive function processes predict mobility outcomes in older adults.

PubMed

Gothe, Neha P; Fanning, Jason; Awick, Elizabeth; Chung, David; Wójcicki, Thomas R; Olson, Erin A; Mullen, Sean P; Voss, Michelle; Erickson, Kirk I; Kramer, Arthur F; McAuley, Edward

2014-02-01

To examine the relationship between performance on executive function measures and subsequent mobility outcomes in community-dwelling older adults. Randomized controlled clinical trial. Champaign-Urbana, Illinois. Community-dwelling older adults (N = 179; mean age 66.4). A 12-month exercise trial with two arms: an aerobic exercise group and a stretching and strengthening group. Established cognitive tests of executive function (flanker task, task switching, and a dual-task paradigm) and the Wisconsin card sort test. Mobility was assessed using the timed 8-foot up and go test and times to climb up and down a flight of stairs. Participants completed the cognitive tests at baseline and the mobility measures at baseline and after 12 months of the intervention. Multiple regression analyses were conducted to determine whether baseline executive function predicted postintervention functional performance after controlling for age, sex, education, cardiorespiratory fitness, and baseline mobility levels. Selective baseline executive function measurements, particularly performance on the flanker task (β = 0.15-0.17) and the Wisconsin card sort test (β = 0.11-0.16) consistently predicted mobility outcomes at 12 months. The estimates were in the expected direction, such that better baseline performance on the executive function measures predicted better performance on the timed mobility tests independent of intervention. Executive functions of inhibitory control, mental set shifting, and attentional flexibility were predictive of functional mobility. Given the literature associating mobility limitations with disability, morbidity, and mortality, these results are important for understanding the antecedents to poor mobility function that well-designed interventions to improve cognitive performance can attenuate. © 2014, Copyright the Authors Journal compilation © 2014, The American Geriatrics Society.

A Behavioral Economic Approach to Assessing Demand for Marijuana

PubMed Central

Collins, R. Lorraine; Vincent, Paula C.; Yu, Jihnhee; Liu, Liu; Epstein, Leonard H.

2014-01-01

In the U.S., marijuana is the most commonly used illicit drug. Its prevalence is growing, particularly among young adults. Behavioral economic indices of the relative reinforcing efficacy (RRE) of substances have been used to examine the appeal of licit (e.g., alcohol) and illicit (e.g., heroin) drugs. The present study is the first to use an experimental, simulated purchasing task to examine the RRE of marijuana. Young-adult (M age = 21.64 years) recreational marijuana users (N = 59) completed a computerized marijuana purchasing task designed to generate demand curves and the related RRE indices (e.g., intensity of demand - purchases at lowest price; Omax - max. spent on marijuana; Pmax - price at which marijuana expenditure is max). Participants “purchased” high-grade marijuana across 16 escalating prices that ranged from $0/free to $160/joint. They also provided 2-weeks of real-time, ecological momentary assessment reports on their marijuana use. The purchasing task generated multiple RRE indices. Consistent with research on other substances, the demand for marijuana was inelastic at lower prices but became elastic at higher prices, suggesting that increases in the price of marijuana could lessen its use. In regression analyses, the intensity of demand, Omax and Pmax, and elasticity each accounted for significant variance in real-time marijuana use. These results provide support for the validity of a simulated marijuana purchasing task to examine its reinforcing efficacy. This study highlights the value of applying a behavioral economic framework to young-adult marijuana use and has implications for prevention, treatment, and policies to regulate marijuana use. PMID:24467370

Aging and inhibitory control of action: cortico-subthalamic connection strength predicts stopping performance.

PubMed

Coxon, James P; Van Impe, Annouchka; Wenderoth, Nicole; Swinnen, Stephan P

2012-06-13

Diffusion weighted imaging (DWI) studies in humans have shown that seniors exhibit reduced white matter integrity compared with young adults, with the most pronounced change occurring in frontal white matter. It is generally assumed that this structural deterioration underlies inhibitory control deficits in old age, but specific evidence from a structural neuroscience perspective is lacking. Cognitive action control is thought to rely on an interconnected network consisting of right inferior frontal cortex (r-IFC), pre-supplementary motor area (preSMA), and the subthalamic nucleus (STN). Here we performed probabilistic DWI tractography to delineate this cognitive control network and had the same individuals (20 young, 20 older adults) perform a task probing both response inhibition and action reprogramming. We hypothesized that structural integrity (fractional anisotropy) and connection strength within this network would be predictive of individual and age-related differences in task performance. We show that the integrity of r-IFC white matter is an age-independent predictor of stop-signal reaction time (SSRT). We further provide evidence that the integrity of white matter projecting to STN predicts both outright stopping (SSRT) and transient braking of response initiation to buy time for action reprogramming (stopping interference effects). These associations remain even after controlling for Go task performance, demonstrating specificity to the Stop component of this task. Finally, a multiple regression analysis reveals bilateral preSMA-STN tract strength as a significant predictor of SSRT in older adults. Our data link age-related decline in inhibitory control with structural decline of STN projections.

Singers' phonation threshold pressure and ratings of self-perceived effort on vocal tasks.

PubMed

McHenry, Monica; Evans, Joseph; Powitzky, Eric

2013-05-01

This study was designed to determine if singers' self-ratings of vocal effort could predict phonation threshold pressure (PTP). It was hypothesized that effort ratings on the more complex task of singing "Happy Birthday" would best predict PTP. A multiple regression analysis was performed with PTP as the predicted variable and self-ratings on four phonatory tasks as the predictor variables. Participants were 48 undergraduate and graduate students majoring in vocal performance. They produced /pi/ syllable trains as softly as possible for the measurement of PTP. They then rated their self-perceived vocal effort while softly producing the following: (1) sustained "ah" (comfortable, midrange pitch); (2) "ah" glide (chest to head voice); (3) Staccato "ah" in head voice (not falsetto); and (4) Happy Birthday in head voice (not falsetto). No ratings of vocal effort predicted PTP. The lack of correlation between PTP and ratings of Happy Birthday remained when separately evaluating graduate versus undergraduate students or males versus females. Informal evaluation of repeated ratings over time suggested the potential for effective self-monitoring. Students' ratings of self-perceived vocal effort were poor predictors of PTP. This may be because of the use of "effortless" imagery during singing instruction or consistent positive feedback regarding vocal performance. It is possible that self-rating could become an effective tool to predict vocal health if task elicitation instructions were more precise, and the student and voice teacher worked collaboratively to improve self-evaluation. Copyright © 2013 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

A behavioral economic approach to assessing demand for marijuana.

PubMed

Collins, R Lorraine; Vincent, Paula C; Yu, Jihnhee; Liu, Liu; Epstein, Leonard H

2014-06-01

In the United States, marijuana is the most commonly used illicit drug. Its prevalence is growing, particularly among young adults. Behavioral economic indices of the relative reinforcing efficacy (RRE) of substances have been used to examine the appeal of licit (e.g., alcohol) and illicit (e.g., heroin) drugs. The present study is the first to use an experimental, simulated purchasing task to examine the RRE of marijuana. Young-adult (M age = 21.64 years) recreational marijuana users (N = 59) completed a computerized marijuana purchasing task designed to generate demand curves and the related RRE indices (e.g., intensity of demand-purchases at lowest price; Omax-max. spent on marijuana; Pmax-price at which marijuana expenditure is max). Participants "purchased" high-grade marijuana across 16 escalating prices that ranged from $0/free to $160/joint. They also provided 2 weeks of real-time, ecological momentary assessment reports on their marijuana use. The purchasing task generated multiple RRE indices. Consistent with research on other substances, the demand for marijuana was inelastic at lower prices but became elastic at higher prices, suggesting that increases in the price of marijuana could lessen its use. In regression analyses, the intensity of demand, Omax, and Pmax, and elasticity each accounted for significant variance in real-time marijuana use. These results provide support for the validity of a simulated marijuana purchasing task to examine marijuana's reinforcing efficacy. This study highlights the value of applying a behavioral economic framework to young-adult marijuana use and has implications for prevention, treatment, and policies to regulate marijuana use. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Self-esteem levels and cardiovascular and inflammatory responses to acute stress.

PubMed

O'Donnell, Katie; Brydon, Lena; Wright, Caroline E; Steptoe, Andrew

2008-11-01

Acute mental stress tests have helped to clarify the pathways through which psychosocial factors are linked to disease risk. This methodology is now being used to investigate potentially protective psychosocial factors. We investigated whether global self-esteem might buffer cardiovascular and inflammatory responses to acute stress. One hundred and one students completed the Rosenberg Self-Esteem Scale. Heart rate and heart rate variability (HRV) were recorded for 5 min periods at baseline, during two mental stress tasks, (a speech and a color-word task) and 10, 25 and 40 min into a recovery period. Plasma levels of tumor-necrosis factor-alpha (TNF-alpha), interleukin-6 (IL-6) and interleukin-1 receptor antagonist (IL-1Ra) were assessed at baseline, immediately post-stress and after 45 min recovery. Repeated measures analysis of variance demonstrated that heart rate levels were lower across all time points in those with high self-esteem, although heart rate reactivity to stress was not related to self-esteem. There were no differences in baseline HRV, TNF-alpha, IL-6 or IL-1Ra. Multiple linear regressions revealed that greater self-esteem was associated with a smaller reduction in heart rate variability during the speech task, but not the color-word task. Greater self-esteem was associated with smaller TNF-alpha and IL-1Ra responses immediately following acute stress and smaller IL-1Ra responses at 45 min post-stress. In conclusion, global self-esteem is associated with lower heart rate and attenuated HRV and inflammatory responses to acute stress. These responses could be processes through which self-esteem protects against the development of disease.

Factors influencing self-reported vision-related activity limitation in the visually impaired.

PubMed

Tabrett, Daryl R; Latham, Keziah

2011-07-15

The use of patient-reported outcome (PRO) measures to assess self-reported difficulty in visual activities is common in patients with impaired vision. This study determines the visual and psychosocial factors influencing patients' responses to self-report measures, to aid in understanding what is being measured. One hundred visually impaired participants completed the Activity Inventory (AI), which assesses self-reported, vision-related activity limitation (VRAL) in the task domains of reading, mobility, visual information, and visual motor tasks. Participants also completed clinical tests of visual function (distance visual acuity and near reading performance both with and without low vision aids [LVAs], contrast sensitivity, visual fields, and depth discrimination), and questionnaires assessing depressive symptoms, social support, adjustment to visual loss, and personality. Multiple regression analyses identified that an acuity measure (distance or near), and, to a lesser extent, near reading performance without LVAs, visual fields, and contrast sensitivity best explained self-reported VRAL (28%-50% variance explained). Significant psychosocial correlates were depression and adjustment, explaining an additional 6% to 19% unique variance. Dependent on task domain, the parameters assessed explained 59% to 71% of the variance in self-reported VRAL. Visual function, most notably acuity without LVAs, is the best predictor of self-reported VRAL assessed by the AI. Depression and adjustment to visual loss also significantly influence self-reported VRAL, largely independent of the severity of visual loss and most notably in the less vision-specific tasks. The results suggest that rehabilitation strategies addressing depression and adjustment could improve perceived visual disability.

The contribution of general cognitive abilities and number abilities to different aspects of mathematics in children.

PubMed

Träff, Ulf

2013-10-01

This study examined the relative contributions of general cognitive abilities and number abilities to word problem solving, calculation, and arithmetic fact retrieval in a sample of 134 children aged 10 to 13 years. The following tasks were administered: listening span, visual matrix span, verbal fluency, color naming, Raven's Progressive Matrices, enumeration, number line estimation, and digit comparison. Hierarchical multiple regressions demonstrated that number abilities provided an independent contribution to fact retrieval and word problem solving. General cognitive abilities contributed to problem solving and calculation. All three number tasks accounted for a similar amount of variance in fact retrieval, whereas only the number line estimation task contributed unique variance in word problem solving. Verbal fluency and Raven's matrices accounted for an equal amount of variance in problem solving and calculation. The current findings demonstrate, in accordance with Fuchs and colleagues' developmental model of mathematical learning (Developmental Psychology, 2010, Vol. 46, pp. 1731-1746), that both number abilities and general cognitive abilities underlie 10- to 13-year-olds' proficiency in problem solving, whereas only number abilities underlie arithmetic fact retrieval. Thus, the amount and type of cognitive contribution to arithmetic proficiency varies between the different aspects of arithmetic. Furthermore, how closely linked a specific aspect of arithmetic is to the whole number representation systems is not the only factor determining the amount and type of cognitive contribution in 10- to 13-year-olds. In addition, the mathematical complexity of the task appears to influence the amount and type of cognitive support. Copyright © 2013 Elsevier Inc. All rights reserved.

Improving Visual Threat Detection: Research to Validate the Threat Detection Skills Trainer

DTIC Science & Technology

2013-08-01

potential threats present in this scene and explain the meaning and implications of these threats. You have two minutes to write a response...could be due to the nature of the tasks or to fatigue. Requiring Soldiers to write answers on multiple trials, and across similar tasks, might have...tasks will likely be significantly different from those experienced in the trainer. This would remove the writing requirement over multiple trials

The Time and Effort in Taking Care for Children with Profound Intellectual and Multiple Disabilities: A Study on Care Load and Support

ERIC Educational Resources Information Center

Tadema, Annemarie C.; Vlaskamp, Carla

2010-01-01

Raising children with profound intellectual and multiple disabilities is considered to be extremely difficult for parents, but figures on the content and amount of time needed for the caring task of parents is lacking. Data on what the caring task actually means (in terms of amount of time and type of task) is needed to be able to understand the…

Deficits in Visuo-Motor Temporal Integration Impacts Manual Dexterity in Probable Developmental Coordination Disorder.

PubMed

Nobusako, Satoshi; Sakai, Ayami; Tsujimoto, Taeko; Shuto, Takashi; Nishi, Yuki; Asano, Daiki; Furukawa, Emi; Zama, Takuro; Osumi, Michihiro; Shimada, Sotaro; Morioka, Shu; Nakai, Akio

2018-01-01

The neurological basis of developmental coordination disorder (DCD) is thought to be deficits in the internal model and mirror-neuron system (MNS) in the parietal lobe and cerebellum. However, it is not clear if the visuo-motor temporal integration in the internal model and automatic-imitation function in the MNS differs between children with DCD and those with typical development (TD). The current study aimed to investigate these differences. Using the manual dexterity test of the Movement Assessment Battery for Children (second edition), the participants were either assigned to the probable DCD (pDCD) group or TD group. The former was comprised of 29 children with clumsy manual dexterity, while the latter consisted of 42 children with normal manual dexterity. Visuo-motor temporal integration ability and automatic-imitation function were measured using the delayed visual feedback detection task and motor interference task, respectively. Further, the current study investigated whether autism-spectrum disorder (ASD) traits, attention-deficit hyperactivity disorder (ADHD) traits, and depressive symptoms differed among the two groups, since these symptoms are frequent comorbidities of DCD. In addition, correlation and multiple regression analyses were performed to extract factors affecting clumsy manual dexterity. In the results, the delay-detection threshold (DDT) and steepness of the delay-detection probability curve, which indicated visuo-motor temporal integration ability, were significantly prolonged and decreased, respectively, in children with pDCD. The interference effect, which indicated automatic-imitation function, was also significantly reduced in this group. These results highlighted that children with clumsy manual dexterity have deficits in visuo-motor temporal integration and automatic-imitation function. There was a significant correlation between manual dexterity, and measures of visuo-motor temporal integration, and ASD traits and ADHD traits and ASD. Multiple regression analysis revealed that the DDT, which indicated visuo-motor temporal integration, was the greatest predictor of poor manual dexterity. The current results supported and provided further evidence for the internal model deficit hypothesis. Further, they suggested a neurorehabilitation technique that improved visuo-motor temporal integration could be therapeutically effective for children with DCD.

Deficits in Visuo-Motor Temporal Integration Impacts Manual Dexterity in Probable Developmental Coordination Disorder

PubMed Central

Nobusako, Satoshi; Sakai, Ayami; Tsujimoto, Taeko; Shuto, Takashi; Nishi, Yuki; Asano, Daiki; Furukawa, Emi; Zama, Takuro; Osumi, Michihiro; Shimada, Sotaro; Morioka, Shu; Nakai, Akio

2018-01-01

The neurological basis of developmental coordination disorder (DCD) is thought to be deficits in the internal model and mirror-neuron system (MNS) in the parietal lobe and cerebellum. However, it is not clear if the visuo-motor temporal integration in the internal model and automatic-imitation function in the MNS differs between children with DCD and those with typical development (TD). The current study aimed to investigate these differences. Using the manual dexterity test of the Movement Assessment Battery for Children (second edition), the participants were either assigned to the probable DCD (pDCD) group or TD group. The former was comprised of 29 children with clumsy manual dexterity, while the latter consisted of 42 children with normal manual dexterity. Visuo-motor temporal integration ability and automatic-imitation function were measured using the delayed visual feedback detection task and motor interference task, respectively. Further, the current study investigated whether autism-spectrum disorder (ASD) traits, attention-deficit hyperactivity disorder (ADHD) traits, and depressive symptoms differed among the two groups, since these symptoms are frequent comorbidities of DCD. In addition, correlation and multiple regression analyses were performed to extract factors affecting clumsy manual dexterity. In the results, the delay-detection threshold (DDT) and steepness of the delay-detection probability curve, which indicated visuo-motor temporal integration ability, were significantly prolonged and decreased, respectively, in children with pDCD. The interference effect, which indicated automatic-imitation function, was also significantly reduced in this group. These results highlighted that children with clumsy manual dexterity have deficits in visuo-motor temporal integration and automatic-imitation function. There was a significant correlation between manual dexterity, and measures of visuo-motor temporal integration, and ASD traits and ADHD traits and ASD. Multiple regression analysis revealed that the DDT, which indicated visuo-motor temporal integration, was the greatest predictor of poor manual dexterity. The current results supported and provided further evidence for the internal model deficit hypothesis. Further, they suggested a neurorehabilitation technique that improved visuo-motor temporal integration could be therapeutically effective for children with DCD. PMID:29556211

Noninvasive spectral imaging of skin chromophores based on multiple regression analysis aided by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Nishidate, Izumi; Wiswadarma, Aditya; Hase, Yota; Tanaka, Noriyuki; Maeda, Takaaki; Niizeki, Kyuichi; Aizu, Yoshihisa

2011-08-01

In order to visualize melanin and blood concentrations and oxygen saturation in human skin tissue, a simple imaging technique based on multispectral diffuse reflectance images acquired at six wavelengths (500, 520, 540, 560, 580 and 600nm) was developed. The technique utilizes multiple regression analysis aided by Monte Carlo simulation for diffuse reflectance spectra. Using the absorbance spectrum as a response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as predictor variables, multiple regression analysis provides regression coefficients. Concentrations of melanin and total blood are then determined from the regression coefficients using conversion vectors that are deduced numerically in advance, while oxygen saturation is obtained directly from the regression coefficients. Experiments with a tissue-like agar gel phantom validated the method. In vivo experiments with human skin of the human hand during upper limb occlusion and of the inner forearm exposed to UV irradiation demonstrated the ability of the method to evaluate physiological reactions of human skin tissue.

Using the Coefficient of Determination "R"[superscript 2] to Test the Significance of Multiple Linear Regression

ERIC Educational Resources Information Center

Quinino, Roberto C.; Reis, Edna A.; Bessegato, Lupercio F.

2013-01-01

This article proposes the use of the coefficient of determination as a statistic for hypothesis testing in multiple linear regression based on distributions acquired by beta sampling. (Contains 3 figures.)

Effects of Goal Relations on Self-Regulated Learning in Multiple Goal Pursuits: Performance, the Self-Regulatory Process, and Task Enjoyment

ERIC Educational Resources Information Center

Lee, Hyunjoo

2012-01-01

The purpose of this study was to investigate the effects of goal relations on self-regulation in the pursuit of multiple goals, focusing on self-regulated performance, the self-regulatory process, and task enjoyment. The effect of multiple goal relations on self-regulation was explored in a set of three studies. Goal relations were divided into…

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis

PubMed Central

Rahman, Md. Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D. W.; Labrique, Alain B.; Rashid, Mahbubur; Christian, Parul; West, Keith P.

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 − -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset. PMID:29261760

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis.

PubMed

Kabir, Alamgir; Rahman, Md Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D W; Labrique, Alain B; Rashid, Mahbubur; Christian, Parul; West, Keith P

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 - -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset.

A General Cross-Layer Cloud Scheduling Framework for Multiple IoT Computer Tasks.

PubMed

Wu, Guanlin; Bao, Weidong; Zhu, Xiaomin; Zhang, Xiongtao

2018-05-23

The diversity of IoT services and applications brings enormous challenges to improving the performance of multiple computer tasks' scheduling in cross-layer cloud computing systems. Unfortunately, the commonly-employed frameworks fail to adapt to the new patterns on the cross-layer cloud. To solve this issue, we design a new computer task scheduling framework for multiple IoT services in cross-layer cloud computing systems. Specifically, we first analyze the features of the cross-layer cloud and computer tasks. Then, we design the scheduling framework based on the analysis and present detailed models to illustrate the procedures of using the framework. With the proposed framework, the IoT services deployed in cross-layer cloud computing systems can dynamically select suitable algorithms and use resources more effectively to finish computer tasks with different objectives. Finally, the algorithms are given based on the framework, and extensive experiments are also given to validate its effectiveness, as well as its superiority.

The M Word: Multicollinearity in Multiple Regression.

ERIC Educational Resources Information Center

Morrow-Howell, Nancy

1994-01-01

Notes that existence of substantial correlation between two or more independent variables creates problems of multicollinearity in multiple regression. Discusses multicollinearity problem in social work research in which independent variables are usually intercorrelated. Clarifies problems created by multicollinearity, explains detection of…

Effects of automation and task load on task switching during human supervision of multiple semi-autonomous robots in a dynamic environment.

PubMed

Squire, P N; Parasuraman, R

2010-08-01

The present study assessed the impact of task load and level of automation (LOA) on task switching in participants supervising a team of four or eight semi-autonomous robots in a simulated 'capture the flag' game. Participants were faster to perform the same task than when they chose to switch between different task actions. They also took longer to switch between different tasks when supervising the robots at a high compared to a low LOA. Task load, as manipulated by the number of robots to be supervised, did not influence switch costs. The results suggest that the design of future unmanned vehicle (UV) systems should take into account not simply how many UVs an operator can supervise, but also the impact of LOA and task operations on task switching during supervision of multiple UVs. The findings of this study are relevant for the ergonomics practice of UV systems. This research extends the cognitive theory of task switching to inform the design of UV systems and results show that switching between UVs is an important factor to consider.

Psychometric properties of neural responses to monetary and social rewards across development.

PubMed

Ethridge, Paige; Weinberg, Anna

2018-02-02

Reward-related event-related potentials (ERPs) are often used to index individual differences that signal the presence or predict the onset of psychopathology. However, relatively little research has explored the psychometric properties of reward-related ERPs. Without understanding their psychometric properties, the value of using ERPs as biomarkers for psychopathology is limited. The present study, therefore, sought to establish the internal consistency reliability and convergent validity of the reward positivity (RewP) and feedback negativity (FN) elicited by two types of incentives commonly used in individual differences research - monetary and social rewards. A large, developmentally-diverse sample completed a forced-choice guessing task in which they won or lost money, as well as a social interaction task in which they received acceptance and rejection feedback. Data were analyzed at both Cz and at a frontocentral region of interest (ROI) using techniques derived from classical test theory and generalizability theory. Results demonstrated good to excellent internal consistency of the RewP and FN within 20 trials in both tasks, in addition to convergent validity between the two tasks. Results from a regression-based approach to isolating activity specific to a single response demonstrated acceptable to good internal consistency within 20 trials in both tasks, while a subtraction-based approach (∆RewP) did not achieve acceptable internal consistency in either task. Internal consistency was not moderated by age and did not differ between Cz and the frontocentral ROI; however, the magnitudes of the RewP and FN were significantly associated with age at Cz but not at the ROI. This work replicates previous studies demonstrating good psychometric properties of the monetary RewP/FN and provides novel information about the psychometric properties of the social RewP/FN. These data support the use of reward-related ERPs elicited by multiple reward types in studies of biomarkers of psychopathology. Copyright © 2018 Elsevier B.V. All rights reserved.

Walking and cognition, but not symptoms, correlate with dual task cost of walking in multiple sclerosis.

PubMed

Motl, Robert W; Sosnoff, Jacob J; Dlugonski, Deirdre; Pilutti, Lara A; Klaren, Rachel; Sandroff, Brian M

2014-03-01

Performing a cognitive task while walking results in a reduction of walking performance among persons with MS. To date, very little is known about correlates of this dual task cost (DTC) of walking in MS. We examined walking performance, cognitive processing speed, and symptoms of fatigue, depression, anxiety, and pain as correlates of DTC of walking in MS. 82 persons with MS undertook a 6-min walk test (6MWT) and completed the Symbol Digit Modalities Test (SDMT), Fatigue Severity Scale (FSS), Short-form of the McGill Pain Questionnaire (SF-MPQ), Hospital Anxiety and Depression Scale (HADS), and self-reported Expanded Disability Status Scale (SR-EDSS). The participants completed 4 trials of walking at a self-selected pace on an electronic walkway that recorded spatiotemporal parameters of gait. The first 2 trials were performed without a cognitive task, whereas the second 2 trials were completed while performing a modified Word List Generation task. There were significant and large declines in gait performance with the addition of a cognitive task for velocity (p<.001, η2=.52), cadence (p<.001, η2=.49), and step length (p<.001, η2=.23). 6MWT and SDMT scores correlated with DTC for velocity (r=-.41, p<.001 and r=-.32, p<.001, respectively) and step length (r=-.45, p<.001 and r=-.37, p<.001, respectively); there were no significant associations between FSS, SF-MPQ, and HADS scores with the DTC of walking. Regression analyses indicated that 6MW, but not SDMT, explained variance in DTC for velocity (ΔR2=.11, p<.001) and step length (ΔR2=.13, p<.001), after controlling for SR-EDSS scores. Walking performance might be a target of interventions for reducing the DTC of walking in MS. Copyright © 2013 Elsevier B.V. All rights reserved.

[Prediction model of health workforce and beds in county hospitals of Hunan by multiple linear regression].

PubMed

Ling, Ru; Liu, Jiawang

2011-12-01

To construct prediction model for health workforce and hospital beds in county hospitals of Hunan by multiple linear regression. We surveyed 16 counties in Hunan with stratified random sampling according to uniform questionnaires,and multiple linear regression analysis with 20 quotas selected by literature view was done. Independent variables in the multiple linear regression model on medical personnels in county hospitals included the counties' urban residents' income, crude death rate, medical beds, business occupancy, professional equipment value, the number of devices valued above 10 000 yuan, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, and utilization rate of hospital beds. Independent variables in the multiple linear regression model on county hospital beds included the the population of aged 65 and above in the counties, disposable income of urban residents, medical personnel of medical institutions in county area, business occupancy, the total value of professional equipment, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, utilization rate of hospital beds, and length of hospitalization. The prediction model shows good explanatory and fitting, and may be used for short- and mid-term forecasting.

Hypothesis testing in functional linear regression models with Neyman's truncation and wavelet thresholding for longitudinal data.

PubMed

Yang, Xiaowei; Nie, Kun

2008-03-15

Longitudinal data sets in biomedical research often consist of large numbers of repeated measures. In many cases, the trajectories do not look globally linear or polynomial, making it difficult to summarize the data or test hypotheses using standard longitudinal data analysis based on various linear models. An alternative approach is to apply the approaches of functional data analysis, which directly target the continuous nonlinear curves underlying discretely sampled repeated measures. For the purposes of data exploration, many functional data analysis strategies have been developed based on various schemes of smoothing, but fewer options are available for making causal inferences regarding predictor-outcome relationships, a common task seen in hypothesis-driven medical studies. To compare groups of curves, two testing strategies with good power have been proposed for high-dimensional analysis of variance: the Fourier-based adaptive Neyman test and the wavelet-based thresholding test. Using a smoking cessation clinical trial data set, this paper demonstrates how to extend the strategies for hypothesis testing into the framework of functional linear regression models (FLRMs) with continuous functional responses and categorical or continuous scalar predictors. The analysis procedure consists of three steps: first, apply the Fourier or wavelet transform to the original repeated measures; then fit a multivariate linear model in the transformed domain; and finally, test the regression coefficients using either adaptive Neyman or thresholding statistics. Since a FLRM can be viewed as a natural extension of the traditional multiple linear regression model, the development of this model and computational tools should enhance the capacity of medical statistics for longitudinal data.

Examining Response Confidence in Multiple Text Tasks

ERIC Educational Resources Information Center

List, Alexandra; Alexander, Patricia A.

2015-01-01

Students' confidence in their responses to a multiple text-processing task and their justifications for those confidence ratings were investigated. Specifically, 215 undergraduates responded to two academic questions, differing by type (i.e., discrete and open-ended) and by domain (i.e., developmental psychology and astrophysics), using a digital…

Multiple-Object Tracking in Children: The "Catch the Spies" Task

ERIC Educational Resources Information Center

Trick, L.M.; Jaspers-Fayer, F.; Sethi, N.

2005-01-01

Multiple-object tracking involves simultaneously tracking positions of a number of target-items as they move among distractors. The standard version of the task poses special challenges for children, demanding extended concentration and the ability to distinguish targets from identical-looking distractors, and may thus underestimate children's…

Unravelling salutogenic mechanisms in the workplace: the role of learning.

PubMed

Pijpker, Roald; Vaandrager, Lenneke; Bakker, Evert Jan; Koelen, Maria

To explore the moderating and mediating role(s) of learning within the relationship between sense of coherence (SOC) and generalized resistance resources. Cross-sectional study (N=481), using a self-administered questionnaire, of employees working in the healthcare sector in the Netherlands in 2017. Four residential healthcare settings and one healthcare-related Facebook group were involved. Multiple linear regression models were used to test for moderating and mediating effects of learning. Social relations, task significance, and job control significantly explained variance in SOC. Conceptual, social, and instrumental learning, combined, moderated the relationship between SOC and task significance. Instrumental learning moderated the relationship between job control and SOC. Social learning also mediated this relationship. Conceptual learning did not show any moderating or mediating effect. The relationship between SOC and the three GRRs seems to be strengthened or explained-to a certain extent-by instrumental and social learning. Healthcare organizations are recommended to promote learning through formal activities as well as through cooperation, feedback, sharing experiences, and job challenges. This requires employee participation and a multilevel interdisciplinary approach. Copyright © 2018 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Person factors and work environments of workers who use mobility devices.

PubMed

Gray, David B; Morgan, Kerri A; Gottlieb, Meghan; Hollingsworth, Holly H

2014-01-01

Nearly 25% of people with mobility impairments and limitations who are of working age are employed, yet few studies have examined their perspectives on their jobs or work environments required to complete job tasks. The purpose of this study was to describe the factors that contribute to successful employment for those who use mobility devices. A convenience sample of 132 workers who use power wheelchairs, manual wheelchairs, canes, crutches or walkers. Participants completed an online version of the Mobility Device User Work Survey (MWS). A multivariate analysis and a two-step multiple linear regression analysis were used. Study participants had few secondary health conditions that influenced their work. Employee satisfactoriness to their employers was high. Accessibility of worksites was high. Assistive technologies were inexpensive, and personal assistance was used infrequently and usually was unpaid. Co-worker communications were very positive. Flexible work rules and supportive managers were highly valued. Job satisfaction positively correlated with accessibility, work tasks, co-worker communication and work support. The description of work environments of successfully employed mobility device users can provide some useful guidance to employers, vocational rehabilitation (VR) counselors and unemployed mobility device users to balance employee abilities and preferences with the needs of employers.

Interrelationships between trait anxiety, situational stress and mental effort predict phonological processing efficiency, but not effectiveness.

PubMed

Edwards, Elizabeth J; Edwards, Mark S; Lyvers, Michael

2016-08-01

Attentional control theory (ACT) describes the mechanisms associated with the relationship between anxiety and cognitive performance. We investigated the relationship between cognitive trait anxiety, situational stress and mental effort on phonological performance using a simple (forward-) and complex (backward-) word span task. Ninety undergraduate students participated in the study. Predictor variables were cognitive trait anxiety, indexed using questionnaire scores; situational stress, manipulated using ego threat instructions; and perceived level of mental effort, measured using a visual analogue scale. Criterion variables (a) performance effectiveness (accuracy) and (b) processing efficiency (accuracy divided by response time) were analyzed in separate multiple moderated-regression analyses. The results revealed (a) no relationship between the predictors and performance effectiveness, and (b) a significant 3-way interaction on processing efficiency for both the simple and complex tasks, such that at higher effort, trait anxiety and situational stress did not predict processing efficiency, whereas at lower effort, higher trait anxiety was associated with lower efficiency at high situational stress, but not at low situational stress. Our results were in full support of the assumptions of ACT and implications for future research are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Need for cognition and cognitive performance from a cross-cultural perspective: examples of academic success and solving anagrams.

PubMed

Gülgöz, S

2001-01-01

The cross-cultural validity of the Need for Cognition Scale and its relationship with cognitive performance were investigated in two studies. In the first study, the relationships between the scale and university entrance scores, course grades, study skills, and social desirability were examined. Using the short form of the Turkish version of the Need for Cognition Scale (S. Gülöz & C. J. Sadowski, 1995) no correlation with academic performance was found but there was significant correlation with a study skills scale and a social desirability scale created for this study. When regression analysis was used to predict grade point average, the Need for Cognition Scale was a significant predictor. In the second study, participants low or high in need for cognition solved multiple-solution anagrams. The instructions preceding the task set the participants' expectations regarding task difficulty. An interaction between expectation and need for cognition indicated that participants with low need for cognition performed worse when they expected difficult problems. Results of the two studies showed that need for cognition has cross-cultural validity and that its effect on cognitive performance was mediated by other variables.

Racial differences in knee osteoarthritis pain: potential contribution of occupational and household tasks.

PubMed

Allen, Kelli D; Chen, Jiu-Chiuan; Callahan, Leigh F; Golightly, Yvonne M; Helmick, Charles G; Renner, Jordan B; Schwartz, Todd A; Jordan, Joanne M

2012-02-01

We examined whether occupational and household tasks contributed to differences in pain between African Americans and whites with radiographic knee osteoarthritis (OA). Participants from the Johnston County Osteoarthritis Project self-reported the frequency (often/always vs never/seldom/sometimes) of performing 9 occupational tasks involving lower extremity joint loading at their longest job (N = 868) and current job (N = 273), as well as 8 household tasks ever performed (N = 811) and currently being performed (N = 767). The associations of the numbers of occupational or household tasks with the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain subscale were first examined in simple linear regression models. If significantly associated with greater pain, each of these was included in adjusted linear regression models to examine whether the association of race with pain remained statistically significant. African Americans reported significantly greater WOMAC pain scores than whites. Exposures to more occupational tasks at the longest job and the current job were associated with greater WOMAC pain scores (p < 0.01). The association of race with greater pain scores remained statistically significant when controlling for occupational tasks at the longest job, but was reduced by 26% and no longer significant when controlling for the number of current occupational tasks. Exposures to an increasing number of household tasks were associated with lower pain scores and were not further analyzed. Current performance of physically demanding occupational tasks contributed to racial differences in pain severity among individuals with knee OA. Better workplace policies to accommodate OA-related limitations may help to reduce racial differences in pain.

Logistic Mixed Models to Investigate Implicit and Explicit Belief Tracking.

PubMed

Lages, Martin; Scheel, Anne

2016-01-01

We investigated the proposition of a two-systems Theory of Mind in adults' belief tracking. A sample of N = 45 participants predicted the choice of one of two opponent players after observing several rounds in an animated card game. Three matches of this card game were played and initial gaze direction on target and subsequent choice predictions were recorded for each belief task and participant. We conducted logistic regressions with mixed effects on the binary data and developed Bayesian logistic mixed models to infer implicit and explicit mentalizing in true belief and false belief tasks. Although logistic regressions with mixed effects predicted the data well a Bayesian logistic mixed model with latent task- and subject-specific parameters gave a better account of the data. As expected explicit choice predictions suggested a clear understanding of true and false beliefs (TB/FB). Surprisingly, however, model parameters for initial gaze direction also indicated belief tracking. We discuss why task-specific parameters for initial gaze directions are different from choice predictions yet reflect second-order perspective taking.

[Analysis of intrusion errors in free recall].

PubMed

Diesfeldt, H F A

2017-06-01

Extra-list intrusion errors during five trials of the eight-word list-learning task of the Amsterdam Dementia Screening Test (ADST) were investigated in 823 consecutive psychogeriatric patients (87.1% suffering from major neurocognitive disorder). Almost half of the participants (45.9%) produced one or more intrusion errors on the verbal recall test. Correct responses were lower when subjects made intrusion errors, but learning slopes did not differ between subjects who committed intrusion errors and those who did not so. Bivariate regression analyses revealed that participants who committed intrusion errors were more deficient on measures of eight-word recognition memory, delayed visual recognition and tests of executive control (the Behavioral Dyscontrol Scale and the ADST-Graphical Sequences as measures of response inhibition). Using hierarchical multiple regression, only free recall and delayed visual recognition retained an independent effect in the association with intrusion errors, such that deficient scores on tests of episodic memory were sufficient to explain the occurrence of intrusion errors. Measures of inhibitory control did not add significantly to the explanation of intrusion errors in free recall, which makes insufficient strength of memory traces rather than a primary deficit in inhibition the preferred account for intrusion errors in free recall.

Adaptation can explain evidence for encoding of probabilistic information in macaque inferior temporal cortex.

PubMed

Vinken, Kasper; Vogels, Rufin

2017-11-20

In predictive coding theory, the brain is conceptualized as a prediction machine that constantly constructs and updates expectations of the sensory environment [1]. In the context of this theory, Bell et al.[2] recently studied the effect of the probability of task-relevant stimuli on the activity of macaque inferior temporal (IT) neurons and observed a reduced population response to expected faces in face-selective neurons. They concluded that "IT neurons encode long-term, latent probabilistic information about stimulus occurrence", supporting predictive coding. They manipulated expectation by the frequency of face versus fruit stimuli in blocks of trials. With such a design, stimulus repetition is confounded with expectation. As previous studies showed that IT neurons decrease their response with repetition [3], such adaptation (or repetition suppression), instead of expectation suppression as assumed by the authors, could explain their effects. The authors attempted to control for this alternative interpretation with a multiple regression approach. Here we show by using simulation that adaptation can still masquerade as expectation effects reported in [2]. Further, the results from the regression model used for most analyses cannot be trusted, because the model is not uniquely defined. Copyright © 2017 Elsevier Ltd. All rights reserved.

The use of regression analysis in determining reference intervals for low hematocrit and thrombocyte count in multiple electrode aggregometry and platelet function analyzer 100 testing of platelet function.

PubMed

Kuiper, Gerhardus J A J M; Houben, Rik; Wetzels, Rick J H; Verhezen, Paul W M; Oerle, Rene van; Ten Cate, Hugo; Henskens, Yvonne M C; Lancé, Marcus D

2017-11-01

Low platelet counts and hematocrit levels hinder whole blood point-of-care testing of platelet function. Thus far, no reference ranges for MEA (multiple electrode aggregometry) and PFA-100 (platelet function analyzer 100) devices exist for low ranges. Through dilution methods of volunteer whole blood, platelet function at low ranges of platelet count and hematocrit levels was assessed on MEA for four agonists and for PFA-100 in two cartridges. Using (multiple) regression analysis, 95% reference intervals were computed for these low ranges. Low platelet counts affected MEA in a positive correlation (all agonists showed r 2 ≥ 0.75) and PFA-100 in an inverse correlation (closure times were prolonged with lower platelet counts). Lowered hematocrit did not affect MEA testing, except for arachidonic acid activation (ASPI), which showed a weak positive correlation (r 2 = 0.14). Closure time on PFA-100 testing was inversely correlated with hematocrit for both cartridges. Regression analysis revealed different 95% reference intervals in comparison with originally established intervals for both MEA and PFA-100 in low platelet or hematocrit conditions. Multiple regression analysis of ASPI and both tests on the PFA-100 for combined low platelet and hematocrit conditions revealed that only PFA-100 testing should be adjusted for both thrombocytopenia and anemia. 95% reference intervals were calculated using multiple regression analysis. However, coefficients of determination of PFA-100 were poor, and some variance remained unexplained. Thus, in this pilot study using (multiple) regression analysis, we could establish reference intervals of platelet function in anemia and thrombocytopenia conditions on PFA-100 and in thrombocytopenia conditions on MEA.

Attentional networks and visuospatial working memory capacity in social anxiety.

PubMed

Moriya, Jun

2018-02-01

Social anxiety is associated with attentional bias and working memory for emotional stimuli; however, the ways in which social anxiety affects cognitive functions involving non-emotional stimuli remains unclear. The present study focused on the role of attentional networks (i.e. alerting, orienting, and executive control networks) and visuospatial working memory capacity (WMC) for non-emotional stimuli in the context of social anxiety. One hundred and seventeen undergraduates completed questionnaires on social anxiety. They then performed an attentional network test and a change detection task to measure visuospatial WMC. Orienting network and visuospatial WMC were positively correlated with social anxiety. A multiple regression analysis showed significant positive associations of alerting, orienting, and visuospatial WMC with social anxiety. Alerting, orienting networks, and high visuospatial WMC for non-emotional stimuli may predict degree of social anxiety.

An Automated Approach for Ranking Journals to Help in Clinician Decision Support

PubMed Central

Jonnalagadda, Siddhartha R.; Moosavinasab, Soheil; Nath, Chinmoy; Li, Dingcheng; Chute, Christopher G.; Liu, Hongfang

2014-01-01

Point of care access to knowledge from full text journal articles supports decision-making and decreases medical errors. However, it is an overwhelming task to search through full text journal articles and find quality information needed by clinicians. We developed a method to rate journals for a given clinical topic, Congestive Heart Failure (CHF). Our method enables filtering of journals and ranking of journal articles based on source journal in relation to CHF. We also obtained a journal priority score, which automatically rates any journal based on its importance to CHF. Comparing our ranking with data gathered by surveying 169 cardiologists, who publish on CHF, our best Multiple Linear Regression model showed a correlation of 0.880, based on five-fold cross validation. Our ranking system can be extended to other clinical topics. PMID:25954382

Executive function, approach sensitivity, and emotional decision making as influences on risk behaviors in young adults.

PubMed

Patrick, Megan E; Blair, Clancy; Maggs, Jennifer L

2008-05-01

Relations among executive function, behavioral approach sensitivity, emotional decision making, and risk behaviors (alcohol use, drug use, and delinquent behavior) were examined in single female college students (N = 72). Hierarchical multiple regressions indicated a significant Approach Sensitivity x Working Memory interaction in which higher levels of alcohol use were associated with the combination of greater approach tendency and better working memory. This Approach Sensitivity x Working Memory interaction was also marginally significant for drug use and delinquency. Poor emotional decision making, as measured by a gambling task, was also associated with higher levels of alcohol use, but only for individuals low in inhibitory control. Findings point to the complexity of relations among aspects of self-regulation and personality and provide much needed data on neuropsychological correlates of risk behaviors in a nonclinical population.

Emotion and attention interactions in social cognition: brain regions involved in processing anger prosody.

PubMed

Sander, David; Grandjean, Didier; Pourtois, Gilles; Schwartz, Sophie; Seghier, Mohamed L; Scherer, Klaus R; Vuilleumier, Patrik

2005-12-01

Multiple levels of processing are thought to be involved in the appraisal of emotionally relevant events, with some processes being engaged relatively independently of attention, whereas other processes may depend on attention and current task goals or context. We conducted an event-related fMRI experiment to examine how processing angry voice prosody, an affectively and socially salient signal, is modulated by voluntary attention. To manipulate attention orthogonally to emotional prosody, we used a dichotic listening paradigm in which meaningless utterances, pronounced with either angry or neutral prosody, were presented simultaneously to both ears on each trial. In two successive blocks, participants selectively attended to either the left or right ear and performed a gender-decision on the voice heard on the target side. Our results revealed a functional dissociation between different brain areas. Whereas the right amygdala and bilateral superior temporal sulcus responded to anger prosody irrespective of whether it was heard from a to-be-attended or to-be-ignored voice, the orbitofrontal cortex and the cuneus in medial occipital cortex showed greater activation to the same emotional stimuli when the angry voice was to-be-attended rather than to-be-ignored. Furthermore, regression analyses revealed a strong correlation between orbitofrontal regions and sensitivity on a behavioral inhibition scale measuring proneness to anxiety reactions. Our results underscore the importance of emotion and attention interactions in social cognition by demonstrating that multiple levels of processing are involved in the appraisal of emotionally relevant cues in voices, and by showing a modulation of some emotional responses by both the current task-demands and individual differences.

Neuropsychological Functioning in Preterm-Born Twins and Singletons at Preschool Age.

PubMed

Raz, Sarah; Piercy, Jamie C; Heitzer, Andrew M; Peters, Brittany N; Newman, Julie Bapp; DeBastos, Angela K; Ofen, Noa; Batton, Beau; Batton, Daniel G

2016-10-01

A limited body of research is available on the relationships between multiplicity of birth and neuropsychological functioning in preterm children who were conceived in the age of assisted reproductive technology and served by the modern neonatal intensive care unit. Our chief objective was to evaluate whether, after adjustment for sociodemographic factors and perinatal complications, twin birth accounted for a unique portion of developmental outcome variance in children born at-risk in the surfactant era. We compared the neuropsychological functioning of 77 twins and 144 singletons born preterm (<34 gestational weeks) and served by William Beaumont Hospital, Royal Oak, MI. Children were evaluated at preschool age, using standardized tests of memory, language, perceptual, and motor abilities. Multiple regression analyses, adjusting for sociodemographic and perinatal variables, revealed no differences on memory or motor indices between preterm twins and their singleton counterparts. In contrast, performance of language and visual processing tasks was significantly lower in twins despite reduced perinatal risk in comparison to singletons. Effect sizes ranged from .33 to .38 standard deviations for global language and visual processing ability indices, respectively. No significant group by sex interactions were observed, and comparison of first-, or second-born twins with singletons yielded medium effect sizes (Cohen's d=.56 and .40, respectively). The modest twin disadvantage on language and visual processing tasks at preschool-age could not be readily attributable to socioeconomic or perinatal variables. The possibility of biological or social twinning-related phenomena as mechanisms underlying the observed performance gaps are discussed. (JINS, 2016, 22, 865-877).

Prospective memory performance in individuals with Parkinson's disease who have mild cognitive impairment.

PubMed

Costa, Alberto; Peppe, Antonella; Zabberoni, Silvia; Serafini, Francesca; Barban, Francesco; Scalici, Francesco; Caltagirone, Carlo; Carlesimo, Giovanni Augusto

2015-09-01

Prospective memory (PM) is the ability to keep in memory and realize future intentions. We aimed at investigating whether in Parkinson's disease (PD) PM deficits are related to mild cognitive impairment (MCI). Other aims were to investigate the cognitive abilities underlying PM performance, and the association between PM performance and measures of daily living functioning. The study included 15 PD patients with single domain MCI, 15 with multiple domain MCI, 17 PD patients without cognitive disorders (PDNC) and 25 healthy controls (HCs). All subjects were administered a PM procedure that included focal (PM cue is processed in the ongoing task) and nonfocal (PM cue is not processed in the ongoing task) conditions. PD patients were administered an extensive neuropsychological battery and scales to assess daily living abilities. PD patients with MCI (both single and multiple domains) showed lower accuracy on all PM conditions than both HC and PDNC patients. This was predicted by their scores on shifting indices. Conversely, PM accuracy of PDNC patients was comparable to HCs. Regression analyses revealed that PD patients' PM performance significantly predicted scores on daily living scales Conclusions: Results suggest that PM efficiency is not tout-court reduced in PD patients, but it specifically depends on the presence of MCI. Moreover, decreased executive functioning, but not episodic memory failure, accounts for a significant proportion of variance in PM performance. Finally, PM accuracy indices were found to be associated with measures of global daily living functioning and management of medication. (c) 2015 APA, all rights reserved).

Interactive Multiple Object Tracking (iMOT)

PubMed Central

Thornton, Ian M.; Bülthoff, Heinrich H.; Horowitz, Todd S.; Rynning, Aksel; Lee, Seong-Whan

2014-01-01

We introduce a new task for exploring the relationship between action and attention. In this interactive multiple object tracking (iMOT) task, implemented as an iPad app, participants were presented with a display of multiple, visually identical disks which moved independently. The task was to prevent any collisions during a fixed duration. Participants could perturb object trajectories via the touchscreen. In Experiment 1, we used a staircase procedure to measure the ability to control moving objects. Object speed was set to 1°/s. On average participants could control 8.4 items without collision. Individual control strategies were quite variable, but did not predict overall performance. In Experiment 2, we compared iMOT with standard MOT performance using identical displays. Object speed was set to 2°/s. Participants could reliably control more objects (M = 6.6) than they could track (M = 4.0), but performance in the two tasks was positively correlated. In Experiment 3, we used a dual-task design. Compared to single-task baseline, iMOT performance decreased and MOT performance increased when the two tasks had to be completed together. Overall, these findings suggest: 1) There is a clear limit to the number of items that can be simultaneously controlled, for a given speed and display density; 2) participants can control more items than they can track; 3) task-relevant action appears not to disrupt MOT performance in the current experimental context. PMID:24498288

Impact of Learning Styles on Air Force Technical Training: Multiple and Linear Imagery in the Presentation of a Comparative Visual Location Task to Visual and Haptic Subjects. Interim Report for Period January 1977-January 1978.

ERIC Educational Resources Information Center

Ausburn, Floyd B.

A U.S. Air Force study was designed to develop instruction based on the supplantation theory, in which tasks are performed (supplanted) for individuals who are unable to perform them due to their cognitive style. The study examined the effects of linear and multiple imagery in presenting a task requiring visual comparison and location to…

SOME STATISTICAL ISSUES RELATED TO MULTIPLE LINEAR REGRESSION MODELING OF BEACH BACTERIA CONCENTRATIONS

EPA Science Inventory

As a fast and effective technique, the multiple linear regression (MLR) method has been widely used in modeling and prediction of beach bacteria concentrations. Among previous works on this subject, however, several issues were insufficiently or inconsistently addressed. Those is...

MULTIPLE REGRESSION MODELS FOR HINDCASTING AND FORECASTING MIDSUMMER HYPOXIA IN THE GULF OF MEXICO

EPA Science Inventory

A new suite of multiple regression models were developed that describe the relationship between the area of bottom water hypoxia along the northern Gulf of Mexico and Mississippi-Atchafalaya River nitrate concentration, total phosphorus (TP) concentration, and discharge. Variabil...

Upper extremity disorders in heavy industry workers in Greece.

PubMed

Tsouvaltzidou, Thomaella; Alexopoulos, Evangelos; Fragkakis, Ioannis; Jelastopulu, Eleni

2017-06-18

To investigate the disability due to musculoskeletal disorders of the upper extremities in heavy industry workers. The population under study consisted of 802 employees, both white- and blue-collar, working in a shipyard industry in Athens, Greece. Data were collected through the distribution of questionnaires and the recording of individual and job-related characteristics during the period 2006-2009. The questionnaires used were the Quick Disabilities of the Arm, Shoulder and Hand (QD) Outcome Measure, the Work Ability Index (WAI) and the Short-Form-36 (SF-36) Health Survey. The QD was divided into three parameters - movement restrictions in everyday activities, work and sports/music activities - and the SF-36 into two items, physical and emotional. Multiple linear regression analysis was performed by means of the SPSS v.22 for Windows Statistical Package. The answers given by the participants for the QD did not reveal great discomfort regarding the execution of manual tasks, with the majority of the participants scoring under 5%, meaning no disability. After conducting multiple linear regression, age revealed a positive association with the parameter of restrictions in everyday activities (b = 0.64, P = 0.000). Basic education showed a statistically significant association regarding restrictions during leisure activities, with b = 2.140 ( P = 0.029) for compulsory education graduates. WAI's final score displayed negative charging in the regression analysis of all three parameters, with b = -0.142 ( P = 0.0), b = -0.099 ( P = 0.055) and b = -0.376 ( P = 0.001) respectively, while the physical and emotional components of SF-36 associated with movement restrictions only in daily activities and work. The participants' specialty made no statistically significant associations with any of the three parameters of the QD. Increased musculoskeletal disorders of the upper extremity are associated with older age, lower basic education and physical and mental/emotional health and reduced working ability.

Contingent interaction during work and play tasks for mothers with multiple sclerosis and their daughters.

PubMed

Crist, P

1993-02-01

Occupational therapy has focused on activity as a catalyst for understanding human roles and interactions, regardless of whether disability or chronic illness is present. Parenting is an important interactional activity accompanied by specific role expectations. This investigation examined the interaction patterns of mothers with multiple sclerosis and their daughters. Thirty-one mothers with multiple sclerosis and their daughters aged 8 to 12 years were compared with 34 mothers without disabilities and their daughters aged 8 to 12 years. Videotaped mother-daughter interactions during a work task and a play task were scored by two raters for 11 different behaviors. These behaviors were collapsed into three behavioral composites--receptiveness, directiveness, and dissuasiveness--for statistical analysis. Statistical analysis revealed no significant differences between the two groups on the behavioral composites for either mothers or their daughters. The two tasks stimulated a different pattern of mother-daughter interactions. For both members of the dyad, interactions during the work task were more directive and less dissuasive than those in the play task. The clinical implication of this finding indicates the importance of understanding the influence of the task selected when observing interaction. Because of recent social and legal changes, understanding parenting and chronic illness is critical.

Estimate the contribution of incubation parameters influence egg hatchability using multiple linear regression analysis

PubMed Central

Khalil, Mohamed H.; Shebl, Mostafa K.; Kosba, Mohamed A.; El-Sabrout, Karim; Zaki, Nesma

2016-01-01

Aim: This research was conducted to determine the most affecting parameters on hatchability of indigenous and improved local chickens’ eggs. Materials and Methods: Five parameters were studied (fertility, early and late embryonic mortalities, shape index, egg weight, and egg weight loss) on four strains, namely Fayoumi, Alexandria, Matrouh, and Montazah. Multiple linear regression was performed on the studied parameters to determine the most influencing one on hatchability. Results: The results showed significant differences in commercial and scientific hatchability among strains. Alexandria strain has the highest significant commercial hatchability (80.70%). Regarding the studied strains, highly significant differences in hatching chick weight among strains were observed. Using multiple linear regression analysis, fertility made the greatest percent contribution (71.31%) to hatchability, and the lowest percent contributions were made by shape index and egg weight loss. Conclusion: A prediction of hatchability using multiple regression analysis could be a good tool to improve hatchability percentage in chickens. PMID:27651666

A Bayesian Approach for Summarizing and Modeling Time-Series Exposure Data with Left Censoring.

PubMed

Houseman, E Andres; Virji, M Abbas

2017-08-01

Direct reading instruments are valuable tools for measuring exposure as they provide real-time measurements for rapid decision making. However, their use is limited to general survey applications in part due to issues related to their performance. Moreover, statistical analysis of real-time data is complicated by autocorrelation among successive measurements, non-stationary time series, and the presence of left-censoring due to limit-of-detection (LOD). A Bayesian framework is proposed that accounts for non-stationary autocorrelation and LOD issues in exposure time-series data in order to model workplace factors that affect exposure and estimate summary statistics for tasks or other covariates of interest. A spline-based approach is used to model non-stationary autocorrelation with relatively few assumptions about autocorrelation structure. Left-censoring is addressed by integrating over the left tail of the distribution. The model is fit using Markov-Chain Monte Carlo within a Bayesian paradigm. The method can flexibly account for hierarchical relationships, random effects and fixed effects of covariates. The method is implemented using the rjags package in R, and is illustrated by applying it to real-time exposure data. Estimates for task means and covariates from the Bayesian model are compared to those from conventional frequentist models including linear regression, mixed-effects, and time-series models with different autocorrelation structures. Simulations studies are also conducted to evaluate method performance. Simulation studies with percent of measurements below the LOD ranging from 0 to 50% showed lowest root mean squared errors for task means and the least biased standard deviations from the Bayesian model compared to the frequentist models across all levels of LOD. In the application, task means from the Bayesian model were similar to means from the frequentist models, while the standard deviations were different. Parameter estimates for covariates were significant in some frequentist models, but in the Bayesian model their credible intervals contained zero; such discrepancies were observed in multiple datasets. Variance components from the Bayesian model reflected substantial autocorrelation, consistent with the frequentist models, except for the auto-regressive moving average model. Plots of means from the Bayesian model showed good fit to the observed data. The proposed Bayesian model provides an approach for modeling non-stationary autocorrelation in a hierarchical modeling framework to estimate task means, standard deviations, quantiles, and parameter estimates for covariates that are less biased and have better performance characteristics than some of the contemporary methods. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2017.

Crack Damage Detection Method via Multiple Visual Features and Efficient Multi-Task Learning Model.

PubMed

Wang, Baoxian; Zhao, Weigang; Gao, Po; Zhang, Yufeng; Wang, Zhe

2018-06-02

This paper proposes an effective and efficient model for concrete crack detection. The presented work consists of two modules: multi-view image feature extraction and multi-task crack region detection. Specifically, multiple visual features (such as texture, edge, etc.) of image regions are calculated, which can suppress various background noises (such as illumination, pockmark, stripe, blurring, etc.). With the computed multiple visual features, a novel crack region detector is advocated using a multi-task learning framework, which involves restraining the variability for different crack region features and emphasizing the separability between crack region features and complex background ones. Furthermore, the extreme learning machine is utilized to construct this multi-task learning model, thereby leading to high computing efficiency and good generalization. Experimental results of the practical concrete images demonstrate that the developed algorithm can achieve favorable crack detection performance compared with traditional crack detectors.

Mean centering, multicollinearity, and moderators in multiple regression: The reconciliation redux.

PubMed

Iacobucci, Dawn; Schneider, Matthew J; Popovich, Deidre L; Bakamitsos, Georgios A

2017-02-01

In this article, we attempt to clarify our statements regarding the effects of mean centering. In a multiple regression with predictors A, B, and A × B (where A × B serves as an interaction term), mean centering A and B prior to computing the product term can clarify the regression coefficients (which is good) and the overall model fit R 2 will remain undisturbed (which is also good).

A Common Mechanism for Resistance to Oxime Reactivation of Acetylcholinesterase Inhibited by Organophosphorus Compounds

DTIC Science & Technology

2013-01-01

application of the Hammett equation with the constants rph in the chemistry of organophosphorus compounds, Russ. Chem. Rev. 38 (1969) 795–811. [13...of oximes and OP compounds and the ability of oximes to reactivate OP- inhibited AChE. Multiple linear regression equations were analyzed using...phosphonate pairs, 21 oxime/ phosphoramidate pairs and 12 oxime/phosphate pairs. The best linear regression equation resulting from multiple regression anal

Guidelines on ergonomic aspects of control rooms

NASA Technical Reports Server (NTRS)

Mitchell, C. M.; Bocast, A. K.; Stewart, L. J.

1983-01-01

The anthropometry, workstation design, and environmental design of control rooms are outlined. The automated interface and VDTs and displays and various modes of communication between the system and the human operator using VDTs are discussed. The man in the loop is examined, the single controller single task framework and multiple controller multiple tasks issues are considered.

The Role of Multiple Solution Tasks in Developing Knowledge and Creativity in Geometry

ERIC Educational Resources Information Center

Levav-Waynberg, Anat; Leikin, Roza

2012-01-01

This paper describes changes in students' geometrical knowledge and their creativity associated with implementation of Multiple Solution Tasks (MSTs) in school geometry courses. Three hundred and three students from 14 geometry classes participated in the study, of whom 229 students from 11 classes learned in an experimental environment that…

Impulsivity, Attention, Memory, and Decision-Making among Adolescent Marijuana Users

PubMed Central

Dougherty, Donald M.; Mathias, Charles W.; Dawes, Michael A.; Furr, R. Michael; Charles, Nora E.; Liguori, Anthony; Shannon, Erin E.; Acheson, Ashley

2012-01-01

Rationale Marijuana is a popular drug of abuse among adolescents, and they may be uniquely vulnerable to resulting cognitive and behavioral impairments. Previous studies have found impairments among adolescent marijuana users. However, the majority of this research has examined measures individually rather than multiple domains in a single cohesive analysis. This study used a logistic regression model that combines performance on a range of tasks to identify which measures were most altered among adolescent marijuana users. Objectives The purpose of this research was to determine unique associations between adolescent marijuana user and performances on multiple cognitive and behavioral domains (attention, memory, decision-making, and impulsivity) in 14- to 17-year-olds while simultaneously controlling for performances across the measures to determine which measures most strongly distinguish marijuana users from non-users. Methods Marijuana-using adolescents (n=45) and controls (n=48) were tested. Logistic regression analyses were conducted to test for: (a) differences between marijuana users and non-users on each measure, (b) associations between marijuana use and each measure after controlling for the other measures, and (c) the degree to which (a) and (b) together elucidated differences among marijuana users and non-users. Results Of all the cognitive and behavioral domains tested, impaired short-term recall memory and consequence sensitivity impulsivity were associated with marijuana use after controlling for performances across all measures. Conclusions This study extends previous findings by identifying cognitive and behavioral impairments most strongly associated with adolescent marijuana users. These specific deficits are potential targets of intervention for this at-risk population. PMID:23138434

Single-Nucleotide Polymorphisms Associated with Skin Naphthyl–Keratin Adduct Levels in Workers Exposed to Naphthalene

PubMed Central

Jiang, Rong; French, John E.; Stober, Vandy P.; Kang-Sickel, Juei-Chuan C.; Zou, Fei

2012-01-01

Background: Individual genetic variation that results in differences in systemic response to xenobiotic exposure is not accounted for as a predictor of outcome in current exposure assessment models. Objective: We developed a strategy to investigate individual differences in single-nucleotide polymorphisms (SNPs) as genetic markers associated with naphthyl–keratin adduct (NKA) levels measured in the skin of workers exposed to naphthalene. Methods: The SNP-association analysis was conducted in PLINK using candidate-gene analysis and genome-wide analysis. We identified significant SNP–NKA associations and investigated the potential impact of these SNPs along with personal and workplace factors on NKA levels using a multiple linear regression model and the Pratt index. Results: In candidate-gene analysis, a SNP (rs4852279) located near the CYP26B1 gene contributed to the 2-naphthyl–keratin adduct (2NKA) level. In the multiple linear regression model, the SNP rs4852279, dermal exposure, exposure time, task replacing foam, age, and ethnicity all were significant predictors of 2NKA level. In genome-wide analysis, no single SNP reached genome-wide significance for NKA levels (all p ≥ 1.05 × 10–5). Pathway and network analyses of SNPs associated with NKA levels were predicted to be involved in the regulation of cellular processes and homeostasis. Conclusions: These results provide evidence that a quantitative biomarker can be used as an intermediate phenotype when investigating the association between genetic markers and exposure–dose relationship in a small, well-characterized exposed worker population. PMID:22391508

Computed tomography synthesis from magnetic resonance images in the pelvis using multiple random forests and auto-context features

NASA Astrophysics Data System (ADS)

Andreasen, Daniel; Edmund, Jens M.; Zografos, Vasileios; Menze, Bjoern H.; Van Leemput, Koen

2016-03-01

In radiotherapy treatment planning that is only based on magnetic resonance imaging (MRI), the electron density information usually obtained from computed tomography (CT) must be derived from the MRI by synthesizing a so-called pseudo CT (pCT). This is a non-trivial task since MRI intensities are neither uniquely nor quantitatively related to electron density. Typical approaches involve either a classification or regression model requiring specialized MRI sequences to solve intensity ambiguities, or an atlas-based model necessitating multiple registrations between atlases and subject scans. In this work, we explore a machine learning approach for creating a pCT of the pelvic region from conventional MRI sequences without using atlases. We use a random forest provided with information about local texture, edges and spatial features derived from the MRI. This helps to solve intensity ambiguities. Furthermore, we use the concept of auto-context by sequentially training a number of classification forests to create and improve context features, which are finally used to train a regression forest for pCT prediction. We evaluate the pCT quality in terms of the voxel-wise error and the radiologic accuracy as measured by water-equivalent path lengths. We compare the performance of our method against two baseline pCT strategies, which either set all MRI voxels in the subject equal to the CT value of water, or in addition transfer the bone volume from the real CT. We show an improved performance compared to both baseline pCTs suggesting that our method may be useful for MRI-only radiotherapy.

Novel applications of multitask learning and multiple output regression to multiple genetic trait prediction.

PubMed

He, Dan; Kuhn, David; Parida, Laxmi

2016-06-15

Given a set of biallelic molecular markers, such as SNPs, with genotype values encoded numerically on a collection of plant, animal or human samples, the goal of genetic trait prediction is to predict the quantitative trait values by simultaneously modeling all marker effects. Genetic trait prediction is usually represented as linear regression models. In many cases, for the same set of samples and markers, multiple traits are observed. Some of these traits might be correlated with each other. Therefore, modeling all the multiple traits together may improve the prediction accuracy. In this work, we view the multitrait prediction problem from a machine learning angle: as either a multitask learning problem or a multiple output regression problem, depending on whether different traits share the same genotype matrix or not. We then adapted multitask learning algorithms and multiple output regression algorithms to solve the multitrait prediction problem. We proposed a few strategies to improve the least square error of the prediction from these algorithms. Our experiments show that modeling multiple traits together could improve the prediction accuracy for correlated traits. The programs we used are either public or directly from the referred authors, such as MALSAR (http://www.public.asu.edu/~jye02/Software/MALSAR/) package. The Avocado data set has not been published yet and is available upon request. dhe@us.ibm.com. © The Author 2016. Published by Oxford University Press.

Simple and multiple linear regression: sample size considerations.

PubMed

Hanley, James A

2016-11-01

The suggested "two subjects per variable" (2SPV) rule of thumb in the Austin and Steyerberg article is a chance to bring out some long-established and quite intuitive sample size considerations for both simple and multiple linear regression. This article distinguishes two of the major uses of regression models that imply very different sample size considerations, neither served well by the 2SPV rule. The first is etiological research, which contrasts mean Y levels at differing "exposure" (X) values and thus tends to focus on a single regression coefficient, possibly adjusted for confounders. The second research genre guides clinical practice. It addresses Y levels for individuals with different covariate patterns or "profiles." It focuses on the profile-specific (mean) Y levels themselves, estimating them via linear compounds of regression coefficients and covariates. By drawing on long-established closed-form variance formulae that lie beneath the standard errors in multiple regression, and by rearranging them for heuristic purposes, one arrives at quite intuitive sample size considerations for both research genres. Copyright © 2016 Elsevier Inc. All rights reserved.

Multiple imputation for cure rate quantile regression with censored data.

PubMed

Wu, Yuanshan; Yin, Guosheng

2017-03-01

The main challenge in the context of cure rate analysis is that one never knows whether censored subjects are cured or uncured, or whether they are susceptible or insusceptible to the event of interest. Considering the susceptible indicator as missing data, we propose a multiple imputation approach to cure rate quantile regression for censored data with a survival fraction. We develop an iterative algorithm to estimate the conditionally uncured probability for each subject. By utilizing this estimated probability and Bernoulli sample imputation, we can classify each subject as cured or uncured, and then employ the locally weighted method to estimate the quantile regression coefficients with only the uncured subjects. Repeating the imputation procedure multiple times and taking an average over the resultant estimators, we obtain consistent estimators for the quantile regression coefficients. Our approach relaxes the usual global linearity assumption, so that we can apply quantile regression to any particular quantile of interest. We establish asymptotic properties for the proposed estimators, including both consistency and asymptotic normality. We conduct simulation studies to assess the finite-sample performance of the proposed multiple imputation method and apply it to a lung cancer study as an illustration. © 2016, The International Biometric Society.

Cognitive Reserve–Mediated Modulation of Positron Emission Tomographic Activations During Memory Tasks in Alzheimer Disease

PubMed Central

Scarmeas, Nikolaos; Zarahn, Eric; Anderson, Karen E.; Honig, Lawrence S.; Park, Aileen; Hilton, John; Flynn, Joseph; Sackeim, Harold A.; Stern, Yaakov

2011-01-01

Background Cognitive reserve (CR) is the ability of an individual to cope with advancing brain pathological abnormalities so that he or she remains free of symptoms. Epidemiological data and evidence from positron emission tomography suggest that it may be mediated through education or IQ. Objective To investigate CR-mediated differential brain activation in Alzheimer disease (AD) subjects compared with healthy elderly persons. Participants Using radioactive water positron emission tomography, we scanned 12 AD patients and 17 healthy elderly persons while performing a serial recognition memory task for nonverbalizable shapes under 2 conditions: low demand, in which one shape was presented in each study trial, and titrated demand, in which the study list length was adjusted so that each subject recognized shapes at approximately 75% accuracy. Positron emission tomographic scan acquisition included the encoding and recognition phases. A CR factor score that summarized years of education, National Adult Reading Test estimated IQ, and Wechsler Adult Intelligence Scale–Revised vocabulary subtest score (explaining 71% of the total variance) was used as an index of CR. Voxel-wise, multiple regression analyses were performed with the “activation” difference (titrated demand–low demand) as the dependent variables and the CR factor score as the independent one. Brain regions where regression slopes differed between the 2 groups were identified. Results The slopes were significantly more positive for the AD patients in the left precentral gyrus and in the left hippocampus and significantly more negative in the right fusiform, right middle occipital, left superior occipital, and left middle temporal gyri. Conclusion Brain regions where systematic relationships (slopes) between subjects’ education-IQ and brain activation differ as a function of disease status may mediate the differential ability to cope with (ie, delay or modify) clinical manifestations of AD. PMID:14732623

Different brain activations between own- and other-race face categorization: an fMRI study using group independent component analysis

NASA Astrophysics Data System (ADS)

Wei, Wenjuan; Liu, Jiangang; Dai, Ruwei; Feng, Lu; Li, Ling; Tian, Jie

2014-03-01

Previous behavioral research has proved that individuals process own- and other-race faces differently. One well-known effect is the other-race effect (ORE), which indicates that individuals categorize other-race faces more accurately and faster than own-race faces. The existed functional magnetic resonance imaging (fMRI) studies of the other-race effect mainly focused on the racial prejudice and the socio-affective differences towards own- and other-race face. In the present fMRI study, we adopted a race-categorization task to determine the activation level differences between categorizing own- and other-race faces. Thirty one Chinese participants who live in China with Chinese as the majority and who had no direct contact with Caucasian individual were recruited in the present study. We used the group independent component analysis (ICA), which is a method of blind source signal separation that has proven to be promising for analysis of fMRI data. We separated the entail data into 56 components which is estimated based on one subject using the Minimal Description Length (MDL) criteria. The components sorted based on the multiple linear regression temporal sorting criteria, and the fit regression parameters were used in performing statistical test to evaluate the task-relatedness of the components. The one way anova was performed to test the significance of the component time course in different conditions. Our result showed that the areas, which coordinates is similar to the right FFA coordinates that previous studies reported, were greater activated for own-race faces than other-race faces, while the precuneus showed greater activation for other-race faces than own-race faces.

Undergraduate Student Motivation in Modularized Developmental Mathematics Courses

ERIC Educational Resources Information Center

Pachlhofer, Keith A.

2017-01-01

This study used the Motivated Strategies for Learning Questionnaire in modularized courses at three institutions across the nation (N = 189), and multiple regression was completed to investigate five categories of student motivation that predicted academic success and course completion. The overall multiple regression analysis was significant and…

MULGRES: a computer program for stepwise multiple regression analysis

Treesearch

A. Jeff Martin

1971-01-01

MULGRES is a computer program source deck that is designed for multiple regression analysis employing the technique of stepwise deletion in the search for most significant variables. The features of the program, along with inputs and outputs, are briefly described, with a note on machine compatibility.

Categorical Variables in Multiple Regression: Some Cautions.

ERIC Educational Resources Information Center

O'Grady, Kevin E.; Medoff, Deborah R.

1988-01-01

Limitations of dummy coding and nonsense coding as methods of coding categorical variables for use as predictors in multiple regression analysis are discussed. The combination of these approaches often yields estimates and tests of significance that are not intended by researchers for inclusion in their models. (SLD)

Multiple Imputation of a Randomly Censored Covariate Improves Logistic Regression Analysis.

PubMed

Atem, Folefac D; Qian, Jing; Maye, Jacqueline E; Johnson, Keith A; Betensky, Rebecca A

2016-01-01

Randomly censored covariates arise frequently in epidemiologic studies. The most commonly used methods, including complete case and single imputation or substitution, suffer from inefficiency and bias. They make strong parametric assumptions or they consider limit of detection censoring only. We employ multiple imputation, in conjunction with semi-parametric modeling of the censored covariate, to overcome these shortcomings and to facilitate robust estimation. We develop a multiple imputation approach for randomly censored covariates within the framework of a logistic regression model. We use the non-parametric estimate of the covariate distribution or the semiparametric Cox model estimate in the presence of additional covariates in the model. We evaluate this procedure in simulations, and compare its operating characteristics to those from the complete case analysis and a survival regression approach. We apply the procedures to an Alzheimer's study of the association between amyloid positivity and maternal age of onset of dementia. Multiple imputation achieves lower standard errors and higher power than the complete case approach under heavy and moderate censoring and is comparable under light censoring. The survival regression approach achieves the highest power among all procedures, but does not produce interpretable estimates of association. Multiple imputation offers a favorable alternative to complete case analysis and ad hoc substitution methods in the presence of randomly censored covariates within the framework of logistic regression.

Rule-Based Category Learning in Down Syndrome

ERIC Educational Resources Information Center

Phillips, B. Allyson; Conners, Frances A.; Merrill, Edward; Klinger, Mark R.

2014-01-01

Rule-based category learning was examined in youths with Down syndrome (DS), youths with intellectual disability (ID), and typically developing (TD) youths. Two tasks measured category learning: the Modified Card Sort task (MCST) and the Concept Formation test of the Woodcock-Johnson-III (Woodcock, McGrew, & Mather, 2001). In regression-based…

Role of Social Performance in Predicting Learning Problems: Prediction of Risk Using Logistic Regression Analysis

ERIC Educational Resources Information Center

Del Prette, Zilda Aparecida Pereira; Prette, Almir Del; De Oliveira, Lael Almeida; Gresham, Frank M.; Vance, Michael J.

2012-01-01

Social skills are specific behaviors that individuals exhibit in order to successfully complete social tasks whereas social competence represents judgments by significant others that these social tasks have been successfully accomplished. The present investigation identified the best sociobehavioral predictors obtained from different raters…

The Effects of Study Tasks in a Computer-Based Chemistry Learning Environment

ERIC Educational Resources Information Center

Urhahne, Detlef; Nick, Sabine; Poepping, Anna Christin; Schulz , Sarah Jayne

2013-01-01

The present study examines the effects of different study tasks on the acquisition of knowledge about acids and bases in a computer-based learning environment. Three different task formats were selected to create three treatment conditions: learning with gap-fill and matching tasks, learning with multiple-choice tasks, and learning only from text…

Performance and strategy comparisons of human listeners and logistic regression in discriminating underwater targets.

PubMed

Yang, Lixue; Chen, Kean

2015-11-01

To improve the design of underwater target recognition systems based on auditory perception, this study compared human listeners with automatic classifiers. Performances measures and strategies in three discrimination experiments, including discriminations between man-made and natural targets, between ships and submarines, and among three types of ships, were used. In the experiments, the subjects were asked to assign a score to each sound based on how confident they were about the category to which it belonged, and logistic regression, which represents linear discriminative models, also completed three similar tasks by utilizing many auditory features. The results indicated that the performances of logistic regression improved as the ratio between inter- and intra-class differences became larger, whereas the performances of the human subjects were limited by their unfamiliarity with the targets. Logistic regression performed better than the human subjects in all tasks but the discrimination between man-made and natural targets, and the strategies employed by excellent human subjects were similar to that of logistic regression. Logistic regression and several human subjects demonstrated similar performances when discriminating man-made and natural targets, but in this case, their strategies were not similar. An appropriate fusion of their strategies led to further improvement in recognition accuracy.

A new semantic vigilance task: vigilance decrement, workload, and sensitivity to dual-task costs.

PubMed

Epling, Samantha L; Russell, Paul N; Helton, William S

2016-01-01

Cognitive resource theory is a common explanation for both the performance decline in vigilance tasks, known as the vigilance decrement, and the limited ability to perform multiple tasks simultaneously. The limited supply of cognitive resources may be utilized faster than they are replenished resulting in a performance decrement, or may need to be allocated among multiple tasks with some performance cost. Researchers have proposed both domain-specific, for example spatial versus verbal processing resources, and domain general cognitive resources. One challenge in testing the domain specificity of cognitive resources in vigilance is the current lack of difficult semantic vigilance tasks which reliably produce a decrement. In the present research, we investigated whether the vigilance decrement was found in a new abbreviated semantic discrimination vigilance task, and whether there was a performance decrement in said vigilance task when paired with a word recall task, as opposed to performed individually. As hypothesized, a vigilance decrement in the semantic vigilance task was found in both the single-task and dual-task conditions, along with reduced vigilance performance in the dual-task condition and reduced word recall in the dual-task condition. This is consistent with cognitive resource theory. The abbreviated semantic vigilance task will be a useful tool for researchers interested in determining the specificity of cognitive resources utilized in vigilance tasks.

Advanced Statistics for Exotic Animal Practitioners.

PubMed

Hodsoll, John; Hellier, Jennifer M; Ryan, Elizabeth G

2017-09-01

Correlation and regression assess the association between 2 or more variables. This article reviews the core knowledge needed to understand these analyses, moving from visual analysis in scatter plots through correlation, simple and multiple linear regression, and logistic regression. Correlation estimates the strength and direction of a relationship between 2 variables. Regression can be considered more general and quantifies the numerical relationships between an outcome and 1 or multiple variables in terms of a best-fit line, allowing predictions to be made. Each technique is discussed with examples and the statistical assumptions underlying their correct application. Copyright © 2017 Elsevier Inc. All rights reserved.

Use of Thematic Mapper for water quality assessment

NASA Technical Reports Server (NTRS)

Horn, E. M.; Morrissey, L. A.

1984-01-01

The evaluation of simulated TM data obtained on an ER-2 aircraft at twenty-five predesignated sample sites for mapping water quality factors such as conductivity, pH, suspended solids, turbidity, temperature, and depth, is discussed. Using a multiple regression for the seven TM bands, an equation is developed for the suspended solids. TM bands 1, 2, 3, 4, and 6 are used with logarithm conductivity in a multiple regression. The assessment of regression equations for a high coefficient of determination (R-squared) and statistical significance is considered. Confidence intervals about the mean regression point are calculated in order to assess the robustness of the regressions used for mapping conductivity, turbidity, and suspended solids, and by regressing random subsamples of sites and comparing the resultant range of R-squared, cross validation is conducted.

Distinct representations of subtraction and multiplication in the neural systems for numerosity and language

PubMed Central

Prado, Jérôme; Mutreja, Rachna; Zhang, Hongchuan; Mehta, Rucha; Desroches, Amy S.; Minas, Jennifer E.; Booth, James R.

2010-01-01

It has been proposed that recent cultural inventions such as symbolic arithmetic recycle evolutionary older neural mechanisms. A central assumption of this hypothesis is that the degree to which a pre-existing mechanism is recycled depends upon the degree of similarity between its initial function and the novel task. To test this assumption, we investigated whether the brain region involved in magnitude comparison in the intraparietal sulcus (IPS), localized by a numerosity comparison task, is recruited to a greater degree by arithmetic problems that involve number comparison (single-digit subtractions) than by problems that involve retrieving facts from memory (single-digit multiplications). Our results confirmed that subtractions are associated with greater activity in the IPS than multiplications, whereas multiplications elicit greater activity than subtractions in regions involved in verbal processing including the middle temporal gyrus and inferior frontal gyrus that were localized by a phonological processing task. Pattern analyses further indicated that the neural mechanisms more active for subtraction than multiplication in the IPS overlap with those involved in numerosity comparison, and that the strength of this overlap predicts inter-individual performance in the subtraction task. These findings provide novel evidence that elementary arithmetic relies on the co-option of evolutionary older neural circuits. PMID:21246667

Control-related systems in the human brain

PubMed Central

Power, Jonathan D; Petersen, Steven E

2013-01-01

A fundamental question in cognitive neuroscience is how the human brain self-organizes to perform tasks. Multiple accounts of this self-organization are currently influential and in this article we survey one of these accounts. We begin by introducing a psychological model of task control and several neuroimaging signals it predicts. We then discuss where such signals are found across tasks with emphasis on brain regions where multiple control signals are present. We then present results derived from spontaneous task-free functional connectivity between control-related regions that dovetail with distinctions made by control signals present in these regions, leading to a proposal that there are at least two task control systems in the brain. This prompts consideration of whether and how such control systems distinguish themselves from other brain regions in a whole-brain context. We present evidence from whole-brain networks that such distinctions do occur and that control systems comprise some of the basic system-level organizational elements of the human brain. We close with observations from the whole-brain networks that may suggest parsimony between multiple accounts of cognitive control. PMID:23347645

INTRODUCTION TO A COMBINED MULTIPLE LINEAR REGRESSION AND ARMA MODELING APPROACH FOR BEACH BACTERIA PREDICTION

EPA Science Inventory

Due to the complexity of the processes contributing to beach bacteria concentrations, many researchers rely on statistical modeling, among which multiple linear regression (MLR) modeling is most widely used. Despite its ease of use and interpretation, there may be time dependence...

Determining the Spatial and Seasonal Variability in OM/OC Ratios across the U.S. Using Multiple Regression

EPA Science Inventory

Data from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network are used to estimate organic mass to organic carbon (OM/OC) ratios across the United States by extending previously published multiple regression techniques. Our new methodology addresses com...

Analysis and Interpretation of Findings Using Multiple Regression Techniques

ERIC Educational Resources Information Center

Hoyt, William T.; Leierer, Stephen; Millington, Michael J.

2006-01-01

Multiple regression and correlation (MRC) methods form a flexible family of statistical techniques that can address a wide variety of different types of research questions of interest to rehabilitation professionals. In this article, we review basic concepts and terms, with an emphasis on interpretation of findings relevant to research questions…

Tracking the Gender Pay Gap: A Case Study

ERIC Educational Resources Information Center

Travis, Cheryl B.; Gross, Louis J.; Johnson, Bruce A.

2009-01-01

This article provides a short introduction to standard considerations in the formal study of wages and illustrates the use of multiple regression and resampling simulation approaches in a case study of faculty salaries at one university. Multiple regression is especially beneficial where it provides information on strength of association, specific…

Estimating air drying times of lumber with multiple regression

Treesearch

William T. Simpson

2004-01-01

In this study, the applicability of a multiple regression equation for estimating air drying times of red oak, sugar maple, and ponderosa pine lumber was evaluated. The equation allows prediction of estimated air drying times from historic weather records of temperature and relative humidity at any desired location.

Using Robust Variance Estimation to Combine Multiple Regression Estimates with Meta-Analysis

ERIC Educational Resources Information Center

Williams, Ryan

2013-01-01

The purpose of this study was to explore the use of robust variance estimation for combining commonly specified multiple regression models and for combining sample-dependent focal slope estimates from diversely specified models. The proposed estimator obviates traditionally required information about the covariance structure of the dependent…

Multiple Regression: A Leisurely Primer.

ERIC Educational Resources Information Center

Daniel, Larry G.; Onwuegbuzie, Anthony J.

Multiple regression is a useful statistical technique when the researcher is considering situations in which variables of interest are theorized to be multiply caused. It may also be useful in those situations in which the researchers is interested in studies of predictability of phenomena of interest. This paper provides an introduction to…

Using Monte Carlo Techniques to Demonstrate the Meaning and Implications of Multicollinearity

ERIC Educational Resources Information Center

Vaughan, Timothy S.; Berry, Kelly E.

2005-01-01

This article presents an in-class Monte Carlo demonstration, designed to demonstrate to students the implications of multicollinearity in a multiple regression study. In the demonstration, students already familiar with multiple regression concepts are presented with a scenario in which the "true" relationship between the response and…

Assessing the Impact of Influential Observations on Multiple Regression Analysis on Human Resource Research.

ERIC Educational Resources Information Center

Bates, Reid A.; Holton, Elwood F., III; Burnett, Michael F.

1999-01-01

A case study of learning transfer demonstrates the possible effect of influential observation on linear regression analysis. A diagnostic method that tests for violation of assumptions, multicollinearity, and individual and multiple influential observations helps determine which observation to delete to eliminate bias. (SK)

Multiple memory systems as substrates for multiple decision systems

PubMed Central

Doll, Bradley B.; Shohamy, Daphna; Daw, Nathaniel D.

2014-01-01

It has recently become widely appreciated that value-based decision making is supported by multiple computational strategies. In particular, animal and human behavior in learning tasks appears to include habitual responses described by prominent model-free reinforcement learning (RL) theories, but also more deliberative or goal-directed actions that can be characterized by a different class of theories, model-based RL. The latter theories evaluate actions by using a representation of the contingencies of the task (as with a learned map of a spatial maze), called an “internal model.” Given the evidence of behavioral and neural dissociations between these approaches, they are often characterized as dissociable learning systems, though they likely interact and share common mechanisms. In many respects, this division parallels a longstanding dissociation in cognitive neuroscience between multiple memory systems, describing, at the broadest level, separate systems for declarative and procedural learning. Procedural learning has notable parallels with model-free RL: both involve learning of habits and both are known to depend on parts of the striatum. Declarative memory, by contrast, supports memory for single events or episodes and depends on the hippocampus. The hippocampus is thought to support declarative memory by encoding temporal and spatial relations among stimuli and thus is often referred to as a relational memory system. Such relational encoding is likely to play an important role in learning an internal model, the representation that is central to model-based RL. Thus, insofar as the memory systems represent more general-purpose cognitive mechanisms that might subserve performance on many sorts of tasks including decision making, these parallels raise the question whether the multiple decision systems are served by multiple memory systems, such that one dissociation is grounded in the other. Here we investigated the relationship between model-based RL and relational memory by comparing individual differences across behavioral tasks designed to measure either capacity. Human subjects performed two tasks, a learning and generalization task (acquired equivalence) which involves relational encoding and depends on the hippocampus; and a sequential RL task that could be solved by either a model-based or model-free strategy. We assessed the correlation between subjects’ use of flexible, relational memory, as measured by generalization in the acquired equivalence task, and their differential reliance on either RL strategy in the decision task. We observed a significant positive relationship between generalization and model-based, but not model-free, choice strategies. These results are consistent with the hypothesis that model-based RL, like acquired equivalence, relies on a more general-purpose relational memory system. PMID:24846190

Decision-Making Under Risk, but Not Under Ambiguity, Predicts Pathological Gambling in Discrete Types of Abstinent Substance Users.

PubMed

Wilson, Michael J; Vassileva, Jasmin

2018-01-01

This study explored how different forms of reward-based decision-making are associated with pathological gambling (PG) among abstinent individuals with prior dependence on different classes of drugs. Participants had lifetime histories of either "pure" heroin dependence ( n = 64), "pure" amphetamine dependence ( n = 51), or polysubstance dependence ( n = 89), or had no history of substance dependence ( n = 133). Decision-making was assessed via two neurocognitive tasks: (1) the Iowa Gambling Task (IGT), a measure of decision-making under ambiguity (i.e., uncertain risk contingencies); and (2) the Cambridge Gambling task (CGT), a measure of decision-making under risk (i.e., explicit risk contingencies). The main effects of neurocognitive performance and drug class on PG (defined as ≥3 DSM-IV PG symptoms) as well as their interactional effects were assessed via multiple linear regression. Two CGT indices of decision-making under risk demonstrated positive main effects on PG. Interaction effects indicated that the effects of decision-making under risk on PG were largely consistent across participant groups. Notably, a linear relationship between greater CGT Risk-Taking and PG symptoms was not observed among amphetamine users, whereas IGT performance was selectively and positively associated with PG in polysubstance users. Overall, results indicate that reward-based decision-making under risk may represent a risk factor for PG across substance users, with some variations in these relationships influenced by specific class of substance of abuse.

Relationships between regional cerebellar volume and sensorimotor and cognitive function in young and older adults

PubMed Central

Bernard, Jessica A.; Seidler, Rachael D.

2013-01-01

The cerebellum has been implicated in both sensorimotor and cognitive function, but is known to undergo volumetric declines with advanced age. Individual differences in regional cerebellar volume may therefore provide insight into performance variability across the lifespan, as has been shown with other brain structures and behaviors. Here, we investigated whether there are regional age differences in cerebellar volume in young and older adults, and whether these volumes explain, in part, individual differences in sensorimotor and cognitive task performance. We found that older adults had smaller cerebellar volume than young adults; specifically, lobules in the anterior cerebellum were more impacted by age. Multiple regression analyses for both age groups revealed associations between sensorimotor task performance in several domains (balance, choice reaction time, and timing) and regional cerebellar volume. There were also relationships with working memory, but none with measures of general cognitive or executive function. Follow-up analyses revealed several differential relationships with age between regional volume and sensorimotor performance. These relationships were predominantly selective to cerebellar regions that have been implicated in cognitive functions. Therefore, it may be the cognitive aspects of sensorimotor task performance that are best explained by individual differences in regional cerebellar volumes. In sum, our results demonstrate the importance of regional cerebellar volume with respect to both sensorimotor and cognitive performance, and we provide additional insight into the role of the cerebellum in age-related performance declines. PMID:23625382

Subjective well-being in heart failure patients: influence of coping and depressive symptoms.

PubMed

Pérez-García, Ana M; Oliván, Silvia; Bover, Ramón

2014-04-01

Psychological factors play a crucial role in the well-being of chronically ill patients. This research examined coping, depressive symptoms and subjective well-being (SWB) in patients with heart failure (HF). The study also analysed whether depressive symptoms mediated the association between coping strategies and SWB. Participants (N = 60, 68.3 % men, aged between 40 and 89 years old) diagnosed with HF were recruited from the cardiology service of a general hospital. Coping strategies were assessed with 16 items of the Brief COPE Scale. The items were organised, according to theoretical and empirical data, into four types of coping: task-focused, seeking social support, maladaptive emotion-focused and acceptance coping. Depressive symptoms were assessed with the corresponding subscale of the Hospital Anxiety and Depression Scale. SWB was assessed considering the Satisfaction with Life Scale and the Positive and Negative Affect Schedule. The multiple regression analyses carried out indicated that SWB was positively associated with task-focused coping and inversely related to maladaptive strategies and depressive symptoms. Gender was also a significant predictor of SWB, with male patients reporting higher well-being than female patients. The mediational analysis showed that depressive symptoms partially mediated the relationships between task-focused coping and SWB. Results were discussed in the light of the importance of gender, depression and coping in patients with HF since these factors may affect subjective well-being and contribute to severe physical impairment.

Methods for cost estimation in software project management

NASA Astrophysics Data System (ADS)

Briciu, C. V.; Filip, I.; Indries, I. I.

2016-02-01

The speed in which the processes used in software development field have changed makes it very difficult the task of forecasting the overall costs for a software project. By many researchers, this task has been considered unachievable, but there is a group of scientist for which this task can be solved using the already known mathematical methods (e.g. multiple linear regressions) and the new techniques as genetic programming and neural networks. The paper presents a solution for building a model for the cost estimation models in the software project management using genetic algorithms starting from the PROMISE datasets related COCOMO 81 model. In the first part of the paper, a summary of the major achievements in the research area of finding a model for estimating the overall project costs is presented together with the description of the existing software development process models. In the last part, a basic proposal of a mathematical model of a genetic programming is proposed including here the description of the chosen fitness function and chromosome representation. The perspective of model described it linked with the current reality of the software development considering as basis the software product life cycle and the current challenges and innovations in the software development area. Based on the author's experiences and the analysis of the existing models and product lifecycle it was concluded that estimation models should be adapted with the new technologies and emerging systems and they depend largely by the chosen software development method.

Considerations of Numbers Used in Tasks for Promoting Multiplicative Reasoning in Students with Learning Difficulties in Mathematics

ERIC Educational Resources Information Center

Risley, Rachael Ann

2016-01-01

This study explored the impact of numbers used in instructional tasks on the construction and generalization of multiplicative reasoning by fourth grade students designated as having learning difficulties or disabilities in mathematics (SLDs). In particular, this study addressed the following research questions: (1) In what ways do SLDs'…

Effects of Text-Belief Consistency and Reading Task on the Strategic Validation of Multiple Texts

ERIC Educational Resources Information Center

Maier, Johanna; Richter, Tobias

2016-01-01

In the comprehension of multiple controversial scientific texts, readers with strong prior beliefs tend to construct a one-sided mental representation that is biased towards belief-consistent information. In the present study, we examined whether an argument in contrast to a summary task instruction can increase the resource allocation to and…

The Effects of Tasks on Integrating Information from Multiple Documents

ERIC Educational Resources Information Center

Cerdan, Raquel; Vidal-Abarca, Eduardo

2008-01-01

The authors examine 2 issues: (a) how students integrate information from multiple scientific documents to describe and explain a physical phenomenon that represents a subset of the information in the documents; and (b) the role of 2 sorts of tasks to achieve this type of integration, either writing an essay on a question requiring integration…

Multi-tasking arbitration and behaviour design for human-interactive robots

NASA Astrophysics Data System (ADS)

Kobayashi, Yuichi; Onishi, Masaki; Hosoe, Shigeyuki; Luo, Zhiwei

2013-05-01

Robots that interact with humans in household environments are required to handle multiple real-time tasks simultaneously, such as carrying objects, collision avoidance and conversation with human. This article presents a design framework for the control and recognition processes to meet these requirements taking into account stochastic human behaviour. The proposed design method first introduces a Petri net for synchronisation of multiple tasks. The Petri net formulation is converted to Markov decision processes and processed in an optimal control framework. Three tasks (safety confirmation, object conveyance and conversation) interact and are expressed by the Petri net. Using the proposed framework, tasks that normally tend to be designed by integrating many if-then rules can be designed in a systematic manner in a state estimation and optimisation framework from the viewpoint of the shortest time optimal control. The proposed arbitration method was verified by simulations and experiments using RI-MAN, which was developed for interactive tasks with humans.

Dynamic Integration of Task-Relevant Visual Features in Posterior Parietal Cortex

PubMed Central

Freedman, David J.

2014-01-01

Summary The primate visual system consists of multiple hierarchically organized cortical areas, each specialized for processing distinct aspects of the visual scene. For example, color and form are encoded in ventral pathway areas such as V4 and inferior temporal cortex, while motion is preferentially processed in dorsal pathway areas such as the middle temporal area. Such representations often need to be integrated perceptually to solve tasks which depend on multiple features. We tested the hypothesis that the lateral intraparietal area (LIP) integrates disparate task-relevant visual features by recording from LIP neurons in monkeys trained to identify target stimuli composed of conjunctions of color and motion features. We show that LIP neurons exhibit integrative representations of both color and motion features when they are task relevant, and task-dependent shifts of both direction and color tuning. This suggests that LIP plays a role in flexibly integrating task-relevant sensory signals. PMID:25199703

Functional capacity and dependency in transfer and dressing are associated with depressive symptoms in older people.

PubMed

Boström, Gustaf; Conradsson, Mia; Rosendahl, Erik; Nordström, Peter; Gustafson, Yngve; Littbrand, Håkan

2014-01-01

This study examined associations between depressive symptoms and functional capacity, overall dependency in personal activities of daily living (ADLs), and dependency in individual ADL tasks, respectively, in people with a high mean age, large range of functional capacity, and wide spectrum of dependency in ADLs. Cross-sectional data from three studies were used. A total of 392 individuals living in community and residential care facilities were included. Mean age was 86.2 years, 72% were women, 75% were dependent in ADLs, 42% had depression, and 39% had dementia. Depressive symptoms were assessed with the 15-item Geriatric Depression Scale (GDS-15), functional capacity with the Berg Balance Scale (BBS), and ADLs with the Barthel ADL Index. Multiple linear regression analyses with comprehensive adjustments were performed between GDS-15 and BBS, GDS-15 and Barthel ADL Index, and GDS-15 and each individual ADL task, separately. GDS-15 score was associated with BBS score (unstandardized b =-0.03, P=0.008), but not with Barthel ADL Index score (unstandardized b =-0.07, P=0.068). No significant interaction effects of sex, dementia, or living conditions were found in these associations. Among individual ADL tasks, dependency in transfer (unstandardized b =-1.03, P=0.007) and dressing (unstandardized b =-0.70, P=0.035) were associated with depressive symptoms. Functional capacity seems to be independently associated with depressive symptoms in older people living in community and residential care facilities, whereas overall ADL performance may not be associated. Dependency in the individual ADL tasks of transfer and dressing appear to be independently associated with depressive symptoms and may be an important focus of future interdisciplinary multifactorial intervention studies.

Functional capacity and dependency in transfer and dressing are associated with depressive symptoms in older people

PubMed Central

Boström, Gustaf; Conradsson, Mia; Rosendahl, Erik; Nordström, Peter; Gustafson, Yngve; Littbrand, Håkan

2014-01-01

Background This study examined associations between depressive symptoms and functional capacity, overall dependency in personal activities of daily living (ADLs), and dependency in individual ADL tasks, respectively, in people with a high mean age, large range of functional capacity, and wide spectrum of dependency in ADLs. Methods Cross-sectional data from three studies were used. A total of 392 individuals living in community and residential care facilities were included. Mean age was 86.2 years, 72% were women, 75% were dependent in ADLs, 42% had depression, and 39% had dementia. Depressive symptoms were assessed with the 15-item Geriatric Depression Scale (GDS-15), functional capacity with the Berg Balance Scale (BBS), and ADLs with the Barthel ADL Index. Multiple linear regression analyses with comprehensive adjustments were performed between GDS-15 and BBS, GDS-15 and Barthel ADL Index, and GDS-15 and each individual ADL task, separately. Results GDS-15 score was associated with BBS score (unstandardized b =−0.03, P=0.008), but not with Barthel ADL Index score (unstandardized b =−0.07, P=0.068). No significant interaction effects of sex, dementia, or living conditions were found in these associations. Among individual ADL tasks, dependency in transfer (unstandardized b =−1.03, P=0.007) and dressing (unstandardized b =−0.70, P=0.035) were associated with depressive symptoms. Conclusion Functional capacity seems to be independently associated with depressive symptoms in older people living in community and residential care facilities, whereas overall ADL performance may not be associated. Dependency in the individual ADL tasks of transfer and dressing appear to be independently associated with depressive symptoms and may be an important focus of future interdisciplinary multifactorial intervention studies. PMID:24523582

Infant care and wives' depressive symptoms.

PubMed

Lennon, M C; Wasserman, G A; Allen, R

1991-01-01

Although some investigators show that division of child care between spouses is related to the psychological well-being of wives, little attention has been given to the relevance of specific dimensions of child care or to nonemployed as well as employed wives. In this study we differentiate basic child care tasks, i.e., those that are essential for the family's physical well-being from other, more supplemental, or auxiliary tasks. We hypothesize that husbands' failure to perform auxiliary child care will be distressing for wives, regardless of employment status because it contributes to perceptions of marital inequity. On the other hand, husbands' lack of participation in the more time-consuming, basic, tasks will be most distressing for employed wives because it results in an increased overall work load. We also hypothesize that when employed mothers are responsible for arranging child care, and when such care entails financial strains, they are more likely to experience psychological distress. To evaluate these hypotheses we use data drawn from a mail survey of a sample of mothers of infants. Using multiple regression analysis, we find that husbands' involvement in child care and housework, especially in the time-consuming tasks, is relatively low and that the most consistent predictor of husbands' involvement is wives' relative income. In terms of the impact of husbands' involvement on wives' well-being, lower levels of husbands' participation in auxiliary, but not basic, child care are associated with increases in reported symptoms, regardless of wives' employment status. When child care is relatively more costly, employed wives report increased symptoms of depression. We discuss these results in terms of the role played by expectations of husbands and wives about parental responsibility for child care.

Automatic Scoring of Multiple Semantic Attributes With Multi-Task Feature Leverage: A Study on Pulmonary Nodules in CT Images.

PubMed

Sihong Chen; Jing Qin; Xing Ji; Baiying Lei; Tianfu Wang; Dong Ni; Jie-Zhi Cheng

2017-03-01

The gap between the computational and semantic features is the one of major factors that bottlenecks the computer-aided diagnosis (CAD) performance from clinical usage. To bridge this gap, we exploit three multi-task learning (MTL) schemes to leverage heterogeneous computational features derived from deep learning models of stacked denoising autoencoder (SDAE) and convolutional neural network (CNN), as well as hand-crafted Haar-like and HoG features, for the description of 9 semantic features for lung nodules in CT images. We regard that there may exist relations among the semantic features of "spiculation", "texture", "margin", etc., that can be explored with the MTL. The Lung Image Database Consortium (LIDC) data is adopted in this study for the rich annotation resources. The LIDC nodules were quantitatively scored w.r.t. 9 semantic features from 12 radiologists of several institutes in U.S.A. By treating each semantic feature as an individual task, the MTL schemes select and map the heterogeneous computational features toward the radiologists' ratings with cross validation evaluation schemes on the randomly selected 2400 nodules from the LIDC dataset. The experimental results suggest that the predicted semantic scores from the three MTL schemes are closer to the radiologists' ratings than the scores from single-task LASSO and elastic net regression methods. The proposed semantic attribute scoring scheme may provide richer quantitative assessments of nodules for better support of diagnostic decision and management. Meanwhile, the capability of the automatic association of medical image contents with the clinical semantic terms by our method may also assist the development of medical search engine.

Comparison of the goals and MISTELS scores for the evaluation of surgeons on training benches.

PubMed

Wolf, Rémi; Medici, Maud; Fiard, Gaëlle; Long, Jean-Alexandre; Moreau-Gaudry, Alexandre; Cinquin, Philippe; Voros, Sandrine

2018-01-01

Evaluation of surgical technical abilities is a major issue in minimally invasive surgery. Devices such as training benches offer specific scores to evaluate surgeons but cannot transfer in the operating room (OR). A contrario, several scores measure performance in the OR, but have not been evaluated on training benches. Our aim was to demonstrate that the GOALS score, which can effectively grade in the OR the abilities involved in laparoscopy, can be used for evaluation on a laparoscopic testbench (MISTELS). This could lead to training systems that can identify more precisely the skills that have been acquired or must still be worked on. 32 volunteers (surgeons, residents and medical students) performed the 5 tasks of the MISTELS training bench and were simultaneously video-recorded. Their performance was evaluated with the MISTELS score and with the GOALS score based on the review of the recording by two experienced, blinded laparoscopic surgeons. The concurrent validity of the GOALS score was assessed using Pearson and Spearman correlation coefficients with the MISTELS score. The construct validity of the GOALS score was assessed with k-means clustering and accuracy rates. Lastly, abilities explored by each MISTELS task were identified with multiple linear regression. GOALS and MISTELS scores are strongly correlated (Pearson correlation coefficient = 0.85 and Spearman correlation coefficient = 0.82 for the overall score). The GOALS score proves to be valid for construction for the tasks of the training bench, with a better accuracy rate between groups of level after k-means clustering, when compared to the original MISTELS score (accuracy rates, respectively, 0.75 and 0.56). GOALS score is well suited for the evaluation of the performance of surgeons of different levels during the completion of the tasks of the MISTELS training bench.

A neuroergonomic quasi-experiment: Predictors of situation awareness and display usability while performing complex tasks

NASA Astrophysics Data System (ADS)

Harbour, Steven D.; Christensen, James C.

2015-05-01

Situation awareness (SA) is the ability and capacity to perceive information and act on it acceptably. Head Up Display (HUD) versus Head Down Display (HDD) manipulation induced variation in task difficulty. HUD and HDD cockpit displays or display designs promoted or impaired SA. The quantitative research presented in this paper examines basic neurocognitive factors in order to identify their specific contributions to the formation of SA, while studying display usability and the effects on SA. Visual attentiveness (Va), perceptiveness (Vp), and spatial working memory (Vswm) were assessed as predictors of SA under varying task difficulty. The study participants were 19 tactical airlift pilots, selected from the Ohio Air National Guard. Neurocognitive tests were administered to the participants prior to flight. In-flight SA was objectively and subjectively assessed for 24 flights. At the completion of this field experiment, the data were analyzed and the tests were statistically significant for the three predictor visual abilities Vp, Va, and Vswm as task difficulty was varied, F(3,11) = 8.125, p = .008. In addition, multiple regression analyses revealed that the visual abilities together predicted a majority of the variance in SA, R2 = 0.753, p = .008. As validated and verified by ECG and EEG data, the HUD yielded a full ability and capacity to anticipate and accommodate trends were as the HDD yielded a saturated ability to anticipate and accommodate trends. Post-hoc tests revealed a Cohen's f2 = 3.05 yielding statistical power to be 0.98. This work results in a significant contribution to the field by providing an improved understanding of SA and path to safer travel for society worldwide. PA 88ABW-2015-1282.

The Role of Executive Functions in Social Cognition among Children with Down Syndrome: Relationship Patterns

PubMed Central

Amadó, Anna; Serrat, Elisabet; Vallès-Majoral, Eduard

2016-01-01

Many studies show a link between social cognition, a set of cognitive and emotional abilities applied to social situations, and executive functions in typical developing children. Children with Down syndrome (DS) show deficits both in social cognition and in some subcomponents of executive functions. However this link has barely been studied in this population. The aim of this study is to investigate the links between social cognition and executive functions among children with DS. We administered a battery of social cognition and executive function tasks (six theory of mind tasks, a test of emotion comprehension, and three executive function tasks) to a group of 30 participants with DS between 4 and 12 years of age. The same tasks were administered to a chronological-age control group and to a control group with the same linguistic development level. Results showed that apart from deficits in social cognition and executive function abilities, children with DS displayed a slight improvement with increasing chronological age and language development in those abilities. Correlational analysis suggested that working memory was the only component that remained constant in the relation patterns of the three groups of participants, being the relation patterns similar among participants with DS and the language development control group. A multiple linear regression showed that working memory explained above 50% of the variability of social cognition in DS participants and in language development control group, whereas in the chronological-age control group this component only explained 31% of the variability. These findings, and specifically the link between working memory and social cognition, are discussed on the basis of their theoretical and practical implications for children with DS. We discuss the possibility to use a working memory training to improve social cognition in this population. PMID:27679588

A framework for feature extraction from hospital medical data with applications in risk prediction.

PubMed

Tran, Truyen; Luo, Wei; Phung, Dinh; Gupta, Sunil; Rana, Santu; Kennedy, Richard Lee; Larkins, Ann; Venkatesh, Svetha

2014-12-30

Feature engineering is a time consuming component of predictive modeling. We propose a versatile platform to automatically extract features for risk prediction, based on a pre-defined and extensible entity schema. The extraction is independent of disease type or risk prediction task. We contrast auto-extracted features to baselines generated from the Elixhauser comorbidities. Hospital medical records was transformed to event sequences, to which filters were applied to extract feature sets capturing diversity in temporal scales and data types. The features were evaluated on a readmission prediction task, comparing with baseline feature sets generated from the Elixhauser comorbidities. The prediction model was through logistic regression with elastic net regularization. Predictions horizons of 1, 2, 3, 6, 12 months were considered for four diverse diseases: diabetes, COPD, mental disorders and pneumonia, with derivation and validation cohorts defined on non-overlapping data-collection periods. For unplanned readmissions, auto-extracted feature set using socio-demographic information and medical records, outperformed baselines derived from the socio-demographic information and Elixhauser comorbidities, over 20 settings (5 prediction horizons over 4 diseases). In particular over 30-day prediction, the AUCs are: COPD-baseline: 0.60 (95% CI: 0.57, 0.63), auto-extracted: 0.67 (0.64, 0.70); diabetes-baseline: 0.60 (0.58, 0.63), auto-extracted: 0.67 (0.64, 0.69); mental disorders-baseline: 0.57 (0.54, 0.60), auto-extracted: 0.69 (0.64,0.70); pneumonia-baseline: 0.61 (0.59, 0.63), auto-extracted: 0.70 (0.67, 0.72). The advantages of auto-extracted standard features from complex medical records, in a disease and task agnostic manner were demonstrated. Auto-extracted features have good predictive power over multiple time horizons. Such feature sets have potential to form the foundation of complex automated analytic tasks.

Cortical localization of cognitive function by regression of performance on event-related potentials

NASA Technical Reports Server (NTRS)

Montgomery, R. W.; Montgomery, L. D.; Guisado, R.

1992-01-01

This paper demonstrates a new method of mapping cortical localization of cognitive function, using electroencephalographic data. Cross-subject regression analyses are used to identify cortical sites and post-stimulus latencies where there is a high correlation between subjects' performance and their cognitive event-related potential amplitude. The procedure was tested using a mental arithmetic task and was found to identify essentially the same cortical regions that have been associated with such tasks on the basis of research with patients suffering localized cortical lesions. Thus, it appears to offer an inexpensive, noninvasive tool for exploring the dynamics of localization in neurologically normal subjects.

Processing speed and working memory span: their differential role in superficial and deep memory processes in schizophrenia.

PubMed

Brébion, Gildas; Bressan, Rodrigo A; Pilowsky, Lyn S; David, Anthony S

2011-05-01

Previous work has suggested that decrement in both processing speed and working memory span plays a role in the memory impairment observed in patients with schizophrenia. We undertook a study to examine simultaneously the effect of these two factors. A sample of 49 patients with schizophrenia and 43 healthy controls underwent a battery of verbal and visual memory tasks. Superficial and deep encoding memory measures were tallied. We conducted regression analyses on the various memory measures, using processing speed and working memory span as independent variables. In the patient group, processing speed was a significant predictor of superficial and deep memory measures in verbal and visual memory. Working memory span was an additional significant predictor of the deep memory measures only. Regression analyses involving all participants revealed that the effect of diagnosis on all the deep encoding memory measures was reduced to non-significance when processing speed was entered in the regression. Decreased processing speed is involved in verbal and visual memory deficit in patients, whether the task require superficial or deep encoding. Working memory is involved only insofar as the task requires a certain amount of effort.

Exploring inter-task transfer following a CO-OP approach with four children with DCD: A single subject multiple baseline design.

PubMed

Capistran, Julie; Martini, Rose

2016-10-01

Cognitive Orientation to daily Occupational Performance (CO-OP) approach has been shown to be effective for improving the performance of tasks worked on in therapy and the use of cognitive strategies. No study to date seems to have explored its effectiveness for improving performance of untrained tasks (inter-task transfer) in children with Developmental Coordination Disorder (DCD). This study aimed to determine whether CO-OP leads to improved performance in an untrained task. A single-subject design with multiple baselines across skills was adopted, with three replications. Four children with DCD (7-12years) received 10 sessions of CO-OP intervention where each child worked on three tasks during therapy sessions and a fourth task was identified, but not worked on, to verify inter-task transfer. Task performance was rated over four phases (baseline, intervention, post-intervention, follow-up) using the Performance Quality Rating Scale (PQRS-OD). Graphed data was statistically analyzed using a two or three standard deviation band method. Significant improvement was obtained for 11 of 12 tasks worked on during therapy and for two of the four untrained tasks. These results indicate that the effectiveness of CO-OP to improve untrained tasks in children merit further exploration. Copyright © 2016 Elsevier B.V. All rights reserved.

Identifying work preferences among individuals with severe multiple disabilities prior to beginning supported work.

PubMed

Reid, D H; Parsons, M B; Green, C W

1998-01-01

We evaluated a prework assessment for predicting work-task preferences among workers with severe multiple disabilities prior to beginning supported work. The assessment involved comparing worker selections from pairs of work tasks drawn from their future job duties. Results of workers' choices once they began their jobs in a publishing company indicated that the assessment predicted tasks that the workers preferred to work on during their job routines. Results are discussed regarding other possible means of determining preferred types of supported work.

Fluid Intelligence Predicts Novel Rule Implementation in a Distributed Frontoparietal Control Network.

PubMed

Tschentscher, Nadja; Mitchell, Daniel; Duncan, John

2017-05-03

Fluid intelligence has been associated with a distributed cognitive control or multiple-demand (MD) network, comprising regions of lateral frontal, insular, dorsomedial frontal, and parietal cortex. Human fluid intelligence is also intimately linked to task complexity, and the process of solving complex problems in a sequence of simpler, more focused parts. Here, a complex target detection task included multiple independent rules, applied one at a time in successive task epochs. Although only one rule was applied at a time, increasing task complexity (i.e., the number of rules) impaired performance in participants of lower fluid intelligence. Accompanying this loss of performance was reduced response to rule-critical events across the distributed MD network. The results link fluid intelligence and MD function to a process of attentional focus on the successive parts of complex behavior. SIGNIFICANCE STATEMENT Fluid intelligence is intimately linked to the ability to structure complex problems in a sequence of simpler, more focused parts. We examine the basis for this link in the functions of a distributed frontoparietal or multiple-demand (MD) network. With increased task complexity, participants of lower fluid intelligence showed reduced responses to task-critical events. Reduced responses in the MD system were accompanied by impaired behavioral performance. Low fluid intelligence is linked to poor foregrounding of task-critical information across a distributed MD system. Copyright © 2017 Tschentscher et al.

Exploring Cognitive Flexibility With a Noninvasive BCI Using Simultaneous Steady-State Visual Evoked Potentials and Sensorimotor Rhythms.

PubMed

Edelman, Bradley J; Meng, Jianjun; Gulachek, Nicholas; Cline, Christopher C; He, Bin

2018-05-01

EEG-based brain-computer interface (BCI) technology creates non-biological pathways for conveying a user's mental intent solely through noninvasively measured neural signals. While optimizing the performance of a single task has long been the focus of BCI research, in order to translate this technology into everyday life, realistic situations, in which multiple tasks are performed simultaneously, must be investigated. In this paper, we explore the concept of cognitive flexibility, or multitasking, within the BCI framework by utilizing a 2-D cursor control task, using sensorimotor rhythms (SMRs), and a four-target visual attention task, using steady-state visual evoked potentials (SSVEPs), both individually and simultaneously. We found no significant difference between the accuracy of the tasks when executing them alone (SMR-57.9% ± 15.4% and SSVEP-59.0% ± 14.2%) and simultaneously (SMR-54.9% ± 17.2% and SSVEP-57.5% ± 15.4%). These modest decreases in performance were supported by similar, non-significant changes in the electrophysiology of the SSVEP and SMR signals. In this sense, we report that multiple BCI tasks can be performed simultaneously without a significant deterioration in performance; this finding will help drive these systems toward realistic daily use in which a user's cognition will need to be involved in multiple tasks at once.

Time-sharing ability in complex performance : an expanded replication.

DOT National Transportation Integrated Search

1978-09-01

Factor analyses were performed on data from 51 subjects tested on the CAMI Multiple Task Performance Battery (MTPB). Five different complex performance task combinations were used as well as the six individual MTPB tasks performed by themselves. The ...

A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis.

PubMed

Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga

2006-08-01

A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.

Deriving percentage study weights in multi-parameter meta-analysis models: with application to meta-regression, network meta-analysis and one-stage individual participant data models.

PubMed

Riley, Richard D; Ensor, Joie; Jackson, Dan; Burke, Danielle L

2017-01-01

Many meta-analysis models contain multiple parameters, for example due to multiple outcomes, multiple treatments or multiple regression coefficients. In particular, meta-regression models may contain multiple study-level covariates, and one-stage individual participant data meta-analysis models may contain multiple patient-level covariates and interactions. Here, we propose how to derive percentage study weights for such situations, in order to reveal the (otherwise hidden) contribution of each study toward the parameter estimates of interest. We assume that studies are independent, and utilise a decomposition of Fisher's information matrix to decompose the total variance matrix of parameter estimates into study-specific contributions, from which percentage weights are derived. This approach generalises how percentage weights are calculated in a traditional, single parameter meta-analysis model. Application is made to one- and two-stage individual participant data meta-analyses, meta-regression and network (multivariate) meta-analysis of multiple treatments. These reveal percentage study weights toward clinically important estimates, such as summary treatment effects and treatment-covariate interactions, and are especially useful when some studies are potential outliers or at high risk of bias. We also derive percentage study weights toward methodologically interesting measures, such as the magnitude of ecological bias (difference between within-study and across-study associations) and the amount of inconsistency (difference between direct and indirect evidence in a network meta-analysis).

Logistic Mixed Models to Investigate Implicit and Explicit Belief Tracking

PubMed Central

Lages, Martin; Scheel, Anne

2016-01-01

We investigated the proposition of a two-systems Theory of Mind in adults’ belief tracking. A sample of N = 45 participants predicted the choice of one of two opponent players after observing several rounds in an animated card game. Three matches of this card game were played and initial gaze direction on target and subsequent choice predictions were recorded for each belief task and participant. We conducted logistic regressions with mixed effects on the binary data and developed Bayesian logistic mixed models to infer implicit and explicit mentalizing in true belief and false belief tasks. Although logistic regressions with mixed effects predicted the data well a Bayesian logistic mixed model with latent task- and subject-specific parameters gave a better account of the data. As expected explicit choice predictions suggested a clear understanding of true and false beliefs (TB/FB). Surprisingly, however, model parameters for initial gaze direction also indicated belief tracking. We discuss why task-specific parameters for initial gaze directions are different from choice predictions yet reflect second-order perspective taking. PMID:27853440

[Application of SAS macro to evaluated multiplicative and additive interaction in logistic and Cox regression in clinical practices].

PubMed

Nie, Z Q; Ou, Y Q; Zhuang, J; Qu, Y J; Mai, J Z; Chen, J M; Liu, X Q

2016-05-01

Conditional logistic regression analysis and unconditional logistic regression analysis are commonly used in case control study, but Cox proportional hazard model is often used in survival data analysis. Most literature only refer to main effect model, however, generalized linear model differs from general linear model, and the interaction was composed of multiplicative interaction and additive interaction. The former is only statistical significant, but the latter has biological significance. In this paper, macros was written by using SAS 9.4 and the contrast ratio, attributable proportion due to interaction and synergy index were calculated while calculating the items of logistic and Cox regression interactions, and the confidence intervals of Wald, delta and profile likelihood were used to evaluate additive interaction for the reference in big data analysis in clinical epidemiology and in analysis of genetic multiplicative and additive interactions.

Wavelet regression model in forecasting crude oil price

NASA Astrophysics Data System (ADS)

Hamid, Mohd Helmie; Shabri, Ani

2017-05-01

This study presents the performance of wavelet multiple linear regression (WMLR) technique in daily crude oil forecasting. WMLR model was developed by integrating the discrete wavelet transform (DWT) and multiple linear regression (MLR) model. The original time series was decomposed to sub-time series with different scales by wavelet theory. Correlation analysis was conducted to assist in the selection of optimal decomposed components as inputs for the WMLR model. The daily WTI crude oil price series has been used in this study to test the prediction capability of the proposed model. The forecasting performance of WMLR model were also compared with regular multiple linear regression (MLR), Autoregressive Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) using root mean square errors (RMSE) and mean absolute errors (MAE). Based on the experimental results, it appears that the WMLR model performs better than the other forecasting technique tested in this study.

Multiple regression for physiological data analysis: the problem of multicollinearity.

PubMed

Slinker, B K; Glantz, S A

1985-07-01

Multiple linear regression, in which several predictor variables are related to a response variable, is a powerful statistical tool for gaining quantitative insight into complex in vivo physiological systems. For these insights to be correct, all predictor variables must be uncorrelated. However, in many physiological experiments the predictor variables cannot be precisely controlled and thus change in parallel (i.e., they are highly correlated). There is a redundancy of information about the response, a situation called multicollinearity, that leads to numerical problems in estimating the parameters in regression equations; the parameters are often of incorrect magnitude or sign or have large standard errors. Although multicollinearity can be avoided with good experimental design, not all interesting physiological questions can be studied without encountering multicollinearity. In these cases various ad hoc procedures have been proposed to mitigate multicollinearity. Although many of these procedures are controversial, they can be helpful in applying multiple linear regression to some physiological problems.

Testing Mediation Using Multiple Regression and Structural Equation Modeling Analyses in Secondary Data

ERIC Educational Resources Information Center

Li, Spencer D.

2011-01-01

Mediation analysis in child and adolescent development research is possible using large secondary data sets. This article provides an overview of two statistical methods commonly used to test mediated effects in secondary analysis: multiple regression and structural equation modeling (SEM). Two empirical studies are presented to illustrate the…

A Simple and Convenient Method of Multiple Linear Regression to Calculate Iodine Molecular Constants

ERIC Educational Resources Information Center

Cooper, Paul D.

2010-01-01

A new procedure using a student-friendly least-squares multiple linear-regression technique utilizing a function within Microsoft Excel is described that enables students to calculate molecular constants from the vibronic spectrum of iodine. This method is advantageous pedagogically as it calculates molecular constants for ground and excited…

Conjoint Analysis: A Study of the Effects of Using Person Variables.

ERIC Educational Resources Information Center

Fraas, John W.; Newman, Isadore

Three statistical techniques--conjoint analysis, a multiple linear regression model, and a multiple linear regression model with a surrogate person variable--were used to estimate the relative importance of five university attributes for students in the process of selecting a college. The five attributes include: availability and variety of…

An Exploratory Study of Face-to-Face and Cyberbullying in Sixth Grade Students

ERIC Educational Resources Information Center

Accordino, Denise B.; Accordino, Michael P.

2011-01-01

In a pilot study, sixth grade students (N = 124) completed a questionnaire assessing students' experience with bullying and cyberbullying, demographic information, quality of parent-child relationship, and ways they have dealt with bullying/cyberbullying in the past. Two multiple regression analyses were conducted. The multiple regression analysis…

The Use of Multiple Regression and Trend Analysis to Understand Enrollment Fluctuations. AIR Forum 1979 Paper.

ERIC Educational Resources Information Center

Campbell, S. Duke; Greenberg, Barry

The development of a predictive equation capable of explaining a significant percentage of enrollment variability at Florida International University is described. A model utilizing trend analysis and a multiple regression approach to enrollment forecasting was adapted to investigate enrollment dynamics at the university. Four independent…

The Use of Multiple Regression Models to Determine if Conjoint Analysis Should Be Conducted on Aggregate Data.

ERIC Educational Resources Information Center

Fraas, John W.; Newman, Isadore

1996-01-01

In a conjoint-analysis consumer-preference study, researchers must determine whether the product factor estimates, which measure consumer preferences, should be calculated and interpreted for each respondent or collectively. Multiple regression models can determine whether to aggregate data by examining factor-respondent interaction effects. This…

Double Cross-Validation in Multiple Regression: A Method of Estimating the Stability of Results.

ERIC Educational Resources Information Center

Rowell, R. Kevin

In multiple regression analysis, where resulting predictive equation effectiveness is subject to shrinkage, it is especially important to evaluate result replicability. Double cross-validation is an empirical method by which an estimate of invariance or stability can be obtained from research data. A procedure for double cross-validation is…

Perceptual and Conceptual Priming of Cue Encoding in Task Switching

ERIC Educational Resources Information Center

Schneider, Darryl W.

2016-01-01

Transition effects in task-cuing experiments can be partitioned into task switching and cue repetition effects by using multiple cues per task. In the present study, the author shows that cue repetition effects can be partitioned into perceptual and conceptual priming effects. In 2 experiments, letters or numbers in their uppercase/lowercase or…

Effects of Task and Category Membership on Representation Stability

ERIC Educational Resources Information Center

Gaillard, Audrey; Urdapilleta, Isabel; Houix, Olivier; Manetta, Celine

2011-01-01

This study examined the within-subject stability of 150 participants who performed both a sorting task and a property-generation task over multiple sessions, focusing on three concrete concept categories (food, animals and bathroom products). We hypothesized that (1) the within-subject stability would be higher in the sorting task than in the…

Cognitive pitfall! Videogame players are not immune to dual-task costs.

PubMed

Donohue, Sarah E; James, Brittany; Eslick, Andrea N; Mitroff, Stephen R

2012-07-01

With modern technological advances, we often find ourselves dividing our attention between multiple tasks. While this may seem a productive way to live, our attentional capacity is limited, and this yields costs in one or more of the many tasks that we try to do. Some people believe that they are immune to the costs of multitasking and commonly engage in potentially dangerous behavior, such as driving while talking on the phone. But are some groups of individuals indeed immune to dual-task costs? This study examines whether avid action videogame players, who have been shown to have heightened attentional capacities, are particularly adept multitaskers. Participants completed three visually demanding experimental paradigms (a driving videogame, a multiple-object-tracking task, and a visual search), with and without answering unrelated questions via a speakerphone (i.e., with and without a dual-task component). All of the participants, videogame players and nonvideogame players alike, performed worse while engaging in the additional dual task for all three paradigms. This suggests that extensive videogame experience may not offer immunity from dual-task costs.

Writing Evaluation: Rater and Task Effects on the Reliability of Writing Scores for Children in Grades 3 and 4

PubMed Central

Kim, Grace Young-Suk; Schatschneider, Christopher; Wanzek, Jeanne; Gatlin, Brandy; Al Otaiba, Stephanie

2017-01-01

We examined how raters and tasks influence measurement error in writing evaluation and how many raters and tasks are needed to reach a desirable level of .90 and .80 reliabilities for children in Grades 3 and 4. A total of 211 children (102 boys) were administered three tasks in narrative and expository genres, respectively, and their written compositions were evaluated in widely used evaluation methods for developing writers: holistic scoring, productivity, and curriculum-based writing scores. Results showed that 54% and 52% of variance in narrative and expository compositions were attributable to true individual differences in writing. Students’ scores varied largely by tasks (30.44% and 28.61% of variance), but not by raters. To reach the reliability of .90, multiple tasks and raters were needed, and for the reliability of .80, a single rater and multiple tasks were needed. These findings offer important implications about reliably evaluating children’s writing skills, given that writing is typically evaluated by a single task and a single rater in classrooms and even in state accountability systems. PMID:29075050

Heterogeneous Suppression of Sequential Effects in Random Sequence Generation, but Not in Operant Learning.

PubMed

Shteingart, Hanan; Loewenstein, Yonatan

2016-01-01

There is a long history of experiments in which participants are instructed to generate a long sequence of binary random numbers. The scope of this line of research has shifted over the years from identifying the basic psychological principles and/or the heuristics that lead to deviations from randomness, to one of predicting future choices. In this paper, we used generalized linear regression and the framework of Reinforcement Learning in order to address both points. In particular, we used logistic regression analysis in order to characterize the temporal sequence of participants' choices. Surprisingly, a population analysis indicated that the contribution of the most recent trial has only a weak effect on behavior, compared to more preceding trials, a result that seems irreconcilable with standard sequential effects that decay monotonously with the delay. However, when considering each participant separately, we found that the magnitudes of the sequential effect are a monotonous decreasing function of the delay, yet these individual sequential effects are largely averaged out in a population analysis because of heterogeneity. The substantial behavioral heterogeneity in this task is further demonstrated quantitatively by considering the predictive power of the model. We show that a heterogeneous model of sequential dependencies captures the structure available in random sequence generation. Finally, we show that the results of the logistic regression analysis can be interpreted in the framework of reinforcement learning, allowing us to compare the sequential effects in the random sequence generation task to those in an operant learning task. We show that in contrast to the random sequence generation task, sequential effects in operant learning are far more homogenous across the population. These results suggest that in the random sequence generation task, different participants adopt different cognitive strategies to suppress sequential dependencies when generating the "random" sequences.

Convex Formulations of Learning from Crowds

NASA Astrophysics Data System (ADS)

Kajino, Hiroshi; Kashima, Hisashi

It has attracted considerable attention to use crowdsourcing services to collect a large amount of labeled data for machine learning, since crowdsourcing services allow one to ask the general public to label data at very low cost through the Internet. The use of crowdsourcing has introduced a new challenge in machine learning, that is, coping with low quality of crowd-generated data. There have been many recent attempts to address the quality problem of multiple labelers, however, there are two serious drawbacks in the existing approaches, that are, (i) non-convexity and (ii) task homogeneity. Most of the existing methods consider true labels as latent variables, which results in non-convex optimization problems. Also, the existing models assume only single homogeneous tasks, while in realistic situations, clients can offer multiple tasks to crowds and crowd workers can work on different tasks in parallel. In this paper, we propose a convex optimization formulation of learning from crowds by introducing personal models of individual crowds without estimating true labels. We further extend the proposed model to multi-task learning based on the resemblance between the proposed formulation and that for an existing multi-task learning model. We also devise efficient iterative methods for solving the convex optimization problems by exploiting conditional independence structures in multiple classifiers.

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…

A Verbal-Instruction System to Help Persons with Multiple Disabilities Perform Complex Food- and Drink-Preparation Tasks Independently

ERIC Educational Resources Information Center

Lancioni, Giulio E.; Singh, Nirbhay N.; O'Reilly, Mark F.; Sigafoos, Jeff; Oliva, Doretta; Smaldone, Angela; La Martire, Maria L.; Alberti, Gloria; Scigliuzzo, Francesca

2011-01-01

In a recent single-case study, we showed that a new verbal-instruction system, ensuring the automatic presentation of step instructions, was beneficial for promoting the task performance of a woman with multiple disabilities (including blindness). The present study was aimed at replicating and extending the aforementioned investigation with three…

The Effects of Multiple Exemplar Training on a Working Memory Task Involving Sequential Responding in Children with Autism

ERIC Educational Resources Information Center

Baltruschat, Lisa; Hasselhorn, Marcus; Tarbox, Jonathan; Dixon, Dennis R.; Najdowski, Adel; Mullins, Ryan David; Gould, Evelyn

2012-01-01

This study is part of a programmatic line of research into the use of basic positive reinforcement procedures for improving working memory in children with autism spectrum disorders. The authors evaluated the effects of multiple exemplar training, utilizing positive reinforcement, on performance of a "digit span backwards" task--a test of working…

Multiple Criteria Decision Analysis for Health Care Decision Making--Emerging Good Practices: Report 2 of the ISPOR MCDA Emerging Good Practices Task Force.

PubMed

Marsh, Kevin; IJzerman, Maarten; Thokala, Praveen; Baltussen, Rob; Boysen, Meindert; Kaló, Zoltán; Lönngren, Thomas; Mussen, Filip; Peacock, Stuart; Watkins, John; Devlin, Nancy

2016-01-01

Health care decisions are complex and involve confronting trade-offs between multiple, often conflicting objectives. Using structured, explicit approaches to decisions involving multiple criteria can improve the quality of decision making. A set of techniques, known under the collective heading, multiple criteria decision analysis (MCDA), are useful for this purpose. In 2014, ISPOR established an Emerging Good Practices Task Force. The task force's first report defined MCDA, provided examples of its use in health care, described the key steps, and provided an overview of the principal methods of MCDA. This second task force report provides emerging good-practice guidance on the implementation of MCDA to support health care decisions. The report includes: a checklist to support the design, implementation and review of an MCDA; guidance to support the implementation of the checklist; the order in which the steps should be implemented; illustrates how to incorporate budget constraints into an MCDA; provides an overview of the skills and resources, including available software, required to implement MCDA; and future research directions. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Qualitative differences in the guidance of attention during single-color and multiple-color visual search: behavioral and electrophysiological evidence.

PubMed

Grubert, Anna; Eimer, Martin

2013-10-01

To find out whether attentional target selection can be effectively guided by top-down task sets for multiple colors, we measured behavioral and ERP markers of attentional target selection in an experiment where participants had to identify color-defined target digits that were accompanied by a single gray distractor object in the opposite visual field. In the One Color task, target color was constant. In the Two Color task, targets could have one of two equally likely colors. Color-guided target selection was less efficient during multiple-color relative to single-color search, and this was reflected by slower response times and delayed N2pc components. Nontarget-color items that were presented in half of all trials captured attention and gained access to working memory when participants searched for two colors, but were excluded from attentional processing in the One Color task. Results demonstrate qualitative differences in the guidance of attentional target selection between single-color and multiple-color visual search. They suggest that top-down attentional control can be applied much more effectively when it is based on a single feature-specific attentional template. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Using Network Science Measures to Predict the Lexical Decision Performance of Adults Who Stutter.

PubMed

Castro, Nichol; Pelczarski, Kristin M; Vitevitch, Michael S

2017-07-12

Methods from network science have examined various aspects of language processing. Clinical populations may also benefit from these novel analyses. Phonological and lexical factors have been examined in adults who stutter (AWS) as potential contributing factors to stuttering, although differences reported are often subtle. We reexamined the performance of AWS and adults who do not stutter (AWNS) from a previously conducted lexical decision task in an attempt to determine if network science measures would provide additional insight into the phonological network of AWS beyond traditional psycholinguistic measures. Multiple regression was used to examine the influence of several traditional psycholinguistic measures as well as several new measures from network science on response times. AWS responded to low-frequency words more slowly than AWNS; responses for both groups were equivalent for high-frequency words. AWS responded to shorter words more slowly than AWNS, producing a reverse word-length effect. For the network measures, degree/neighborhood density and closeness centrality, but not whether a word was inside or outside the giant component, influenced response times similarly between groups. Network analyses suggest that multiple levels of the phonological network might influence phonological processing, not just the micro-level traditionally considered by mainstream psycholinguistics.

Stimulating cognition in schizophrenia: A controlled pilot study of the effects of prefrontal transcranial direct current stimulation upon memory and learning.

PubMed

Orlov, Natasza D; Tracy, Derek K; Joyce, Daniel; Patel, Shinal; Rodzinka-Pasko, Joanna; Dolan, Hayley; Hodsoll, John; Collier, Tracy; Rothwell, John; Shergill, Sukhwinder S

Schizophrenia is characterized by prominent cognitive deficits, impacting on memory and learning; these are strongly associated with the prefrontal cortex. To combine two interventions, transcranial direct current stimulation (tDCS) over the prefrontal cortex and cognitive training, to examine change in cognitive performance in patients with schizophrenia. A double blind, sham-controlled pilot study of 49 patients with schizophrenia, randomized into real or sham tDCS stimulation groups. Subjects participated in 4 days of cognitive training (days 1, 2, 14, 56) with tDCS applied at day-1 and day-14. The primary outcome measure was change in accuracy on working memory and implicit learning tasks from baseline. The secondary outcome measure was the generalization of learning to non-trained task, indexed by the CogState neuropsychological battery. Data analysis was conducted using multilevel modelling and multiple regressions. 24 participants were randomized to real tDCS and 25 to sham. The working memory task demonstrated a significant mean difference in performance in the tDCS treatment group: at day-2 (b = 0.68, CI 0.14-1.21; p = 0.044) and at day-56 (b = 0.71, 0.16-1.26; p = 0.044). There were no significant effects of tDCS on implicit learning. Trend evidence of generalization onto untrained tasks of attention and vigilance task (b = 0.40, 0.43-0.77; p = 0.058) was found. This is the first study to show a significant longer-term effect of tDCS on working memory in schizophrenia. Given the current lack of effective therapies for cognitive deficits, tDCS may offer an important novel approach to modulating brain networks to ameliorate cognitive deficits in schizophrenia. Copyright © 2016 Elsevier Inc. All rights reserved.

Computational phenotype discovery using unsupervised feature learning over noisy, sparse, and irregular clinical data.

PubMed

Lasko, Thomas A; Denny, Joshua C; Levy, Mia A

2013-01-01

Inferring precise phenotypic patterns from population-scale clinical data is a core computational task in the development of precision, personalized medicine. The traditional approach uses supervised learning, in which an expert designates which patterns to look for (by specifying the learning task and the class labels), and where to look for them (by specifying the input variables). While appropriate for individual tasks, this approach scales poorly and misses the patterns that we don't think to look for. Unsupervised feature learning overcomes these limitations by identifying patterns (or features) that collectively form a compact and expressive representation of the source data, with no need for expert input or labeled examples. Its rising popularity is driven by new deep learning methods, which have produced high-profile successes on difficult standardized problems of object recognition in images. Here we introduce its use for phenotype discovery in clinical data. This use is challenging because the largest source of clinical data - Electronic Medical Records - typically contains noisy, sparse, and irregularly timed observations, rendering them poor substrates for deep learning methods. Our approach couples dirty clinical data to deep learning architecture via longitudinal probability densities inferred using Gaussian process regression. From episodic, longitudinal sequences of serum uric acid measurements in 4368 individuals we produced continuous phenotypic features that suggest multiple population subtypes, and that accurately distinguished (0.97 AUC) the uric-acid signatures of gout vs. acute leukemia despite not being optimized for the task. The unsupervised features were as accurate as gold-standard features engineered by an expert with complete knowledge of the domain, the classification task, and the class labels. Our findings demonstrate the potential for achieving computational phenotype discovery at population scale. We expect such data-driven phenotypes to expose unknown disease variants and subtypes and to provide rich targets for genetic association studies.

Computational Phenotype Discovery Using Unsupervised Feature Learning over Noisy, Sparse, and Irregular Clinical Data

PubMed Central

Lasko, Thomas A.; Denny, Joshua C.; Levy, Mia A.

2013-01-01

Inferring precise phenotypic patterns from population-scale clinical data is a core computational task in the development of precision, personalized medicine. The traditional approach uses supervised learning, in which an expert designates which patterns to look for (by specifying the learning task and the class labels), and where to look for them (by specifying the input variables). While appropriate for individual tasks, this approach scales poorly and misses the patterns that we don’t think to look for. Unsupervised feature learning overcomes these limitations by identifying patterns (or features) that collectively form a compact and expressive representation of the source data, with no need for expert input or labeled examples. Its rising popularity is driven by new deep learning methods, which have produced high-profile successes on difficult standardized problems of object recognition in images. Here we introduce its use for phenotype discovery in clinical data. This use is challenging because the largest source of clinical data – Electronic Medical Records – typically contains noisy, sparse, and irregularly timed observations, rendering them poor substrates for deep learning methods. Our approach couples dirty clinical data to deep learning architecture via longitudinal probability densities inferred using Gaussian process regression. From episodic, longitudinal sequences of serum uric acid measurements in 4368 individuals we produced continuous phenotypic features that suggest multiple population subtypes, and that accurately distinguished (0.97 AUC) the uric-acid signatures of gout vs. acute leukemia despite not being optimized for the task. The unsupervised features were as accurate as gold-standard features engineered by an expert with complete knowledge of the domain, the classification task, and the class labels. Our findings demonstrate the potential for achieving computational phenotype discovery at population scale. We expect such data-driven phenotypes to expose unknown disease variants and subtypes and to provide rich targets for genetic association studies. PMID:23826094

Dual-Task Performance: Influence of Frailty, Level of Physical Activity, and Cognition.

PubMed

Giusti Rossi, Paulo; Pires de Andrade, Larissa; Hotta Ansai, Juliana; Silva Farche, Ana Claudia; Carnaz, Leticia; Dalpubel, Daniela; Ferriolli, Eduardo; Assis Carvalho Vale, Francisco; de Medeiros Takahashi, Anielle Cristhine

2018-03-08

Cognition and level of physical activity have been associated with frailty syndrome. The development of tools that assess deficits related to physical and cognitive frailties simultaneously are of common interest. However, little is known about how much these aspects influence the performance of dual-task tests. Our aims were (a) to verify the influence of frailty syndrome and objectively measured physical activity and cognition on the Timed Up and Go (TUG) test and Timed Up and Go associated with dual-task (TUG-DT) performances; and (b) to compare TUG and TUG-DT performances between older adults who develop frailty syndrome. Sixty-four community-dwelling older adults were divided into frail, prefrail, and nonfrail groups, according to frailty phenotype. Assessments included anamnesis, screening of frailty syndrome, cognitive assessment (Addenbrooke's cognitive examination), placement of a triaxial accelerometer to assess level of physical activity, and TUG and TUG-DT (TUG associated with a motor-cognitive task of calling a phone number) performances. After 7 days, the accelerometer was removed. A multiple linear regression was applied to identify which independent variables could explain performances in the TUG and TUG-DT. Subsequently, the analysis of covariance test, adjusted for age, cognition, and level of physical activity covariates, was used to compare test performances. There were no differences in cognition between groups. Significant differences in the level of physical activity were found in the frail group. Compared with the frail group, the nonfrail group required less time and fewer steps to complete the TUG. Regarding the TUG-DT, cognition and age influenced the time spent and number of steps, respectively; however, no differences were found between groups. Frail older adults presented worse performance in the TUG when compared with nonfrail older adults. The dual-task test does not differentiate older adults with frailty syndrome, regardless of cognitive performance.

A structured analysis of uncertainty surrounding modeled impacts of groundwater-extraction rules

NASA Astrophysics Data System (ADS)

Guillaume, Joseph H. A.; Qureshi, M. Ejaz; Jakeman, Anthony J.

2012-08-01

Integrating economic and groundwater models for groundwater-management can help improve understanding of trade-offs involved between conflicting socioeconomic and biophysical objectives. However, there is significant uncertainty in most strategic decision-making situations, including in the models constructed to represent them. If not addressed, this uncertainty may be used to challenge the legitimacy of the models and decisions made using them. In this context, a preliminary uncertainty analysis was conducted of a dynamic coupled economic-groundwater model aimed at assessing groundwater extraction rules. The analysis demonstrates how a variety of uncertainties in such a model can be addressed. A number of methods are used including propagation of scenarios and bounds on parameters, multiple models, block bootstrap time-series sampling and robust linear regression for model calibration. These methods are described within the context of a theoretical uncertainty management framework, using a set of fundamental uncertainty management tasks and an uncertainty typology.

Bimodal bilingualism as multisensory training?: Evidence for improved audiovisual speech perception after sign language exposure.

PubMed

Williams, Joshua T; Darcy, Isabelle; Newman, Sharlene D

2016-02-15

The aim of the present study was to characterize effects of learning a sign language on the processing of a spoken language. Specifically, audiovisual phoneme comprehension was assessed before and after 13 weeks of sign language exposure. L2 ASL learners performed this task in the fMRI scanner. Results indicated that L2 American Sign Language (ASL) learners' behavioral classification of the speech sounds improved with time compared to hearing nonsigners. Results indicated increased activation in the supramarginal gyrus (SMG) after sign language exposure, which suggests concomitant increased phonological processing of speech. A multiple regression analysis indicated that learner's rating on co-sign speech use and lipreading ability was correlated with SMG activation. This pattern of results indicates that the increased use of mouthing and possibly lipreading during sign language acquisition may concurrently improve audiovisual speech processing in budding hearing bimodal bilinguals. Copyright © 2015 Elsevier B.V. All rights reserved.

Prognostic Physiology: Modeling Patient Severity in Intensive Care Units Using Radial Domain Folding

PubMed Central

Joshi, Rohit; Szolovits, Peter

2012-01-01

Real-time scalable predictive algorithms that can mine big health data as the care is happening can become the new “medical tests” in critical care. This work describes a new unsupervised learning approach, radial domain folding, to scale and summarize the enormous amount of data collected and to visualize the degradations or improvements in multiple organ systems in real time. Our proposed system is based on learning multi-layer lower dimensional abstractions from routinely generated patient data in modern Intensive Care Units (ICUs), and is dramatically different from most of the current work being done in ICU data mining that rely on building supervised predictive models using commonly measured clinical observations. We demonstrate that our system discovers abstract patient states that summarize a patient’s physiology. Further, we show that a logistic regression model trained exclusively on our learned layer outperforms a customized SAPS II score on the mortality prediction task. PMID:23304406

A Bayesian Measurment Error Model for Misaligned Radiographic Data

DOE PAGES

Lennox, Kristin P.; Glascoe, Lee G.

2013-09-06

An understanding of the inherent variability in micro-computed tomography (micro-CT) data is essential to tasks such as statistical process control and the validation of radiographic simulation tools. The data present unique challenges to variability analysis due to the relatively low resolution of radiographs, and also due to minor variations from run to run which can result in misalignment or magnification changes between repeated measurements of a sample. Positioning changes artificially inflate the variability of the data in ways that mask true physical phenomena. We present a novel Bayesian nonparametric regression model that incorporates both additive and multiplicative measurement error inmore » addition to heteroscedasticity to address this problem. We also use this model to assess the effects of sample thickness and sample position on measurement variability for an aluminum specimen. Supplementary materials for this article are available online.« less

Who Chokes Under Pressure? The Big Five Personality Traits and Decision-Making under Pressure.

PubMed

Byrne, Kaileigh A; Silasi-Mansat, Crina D; Worthy, Darrell A

2015-02-01

The purpose of the present study was to examine whether the Big Five personality factors could predict who thrives or chokes under pressure during decision-making. The effects of the Big Five personality factors on decision-making ability and performance under social (Experiment 1) and combined social and time pressure (Experiment 2) were examined using the Big Five Personality Inventory and a dynamic decision-making task that required participants to learn an optimal strategy. In Experiment 1, a hierarchical multiple regression analysis showed an interaction between neuroticism and pressure condition. Neuroticism negatively predicted performance under social pressure, but did not affect decision-making under low pressure. Additionally, the negative effect of neuroticism under pressure was replicated using a combined social and time pressure manipulation in Experiment 2. These results support distraction theory whereby pressure taxes highly neurotic individuals' cognitive resources, leading to sub-optimal performance. Agreeableness also negatively predicted performance in both experiments.

Maternal report of infant negative affect predicts attenuated brain response to own infant.

PubMed

Kuzava, Sierra; Bernard, Kristin

2018-06-24

Parent-infant interaction is known to be influenced bidirectionally by parent and infant characteristics. However, it is unclear whether infant temperament affects parents' neural responses to infant stimuli. 85 infants (6-12 months) were filmed in distress-eliciting tasks, which were coded for infants' negative affect. Mothers' reported infant affect was obtained from the Infant Behavior Questionnaire Very Short Form-Revised. Mothers' EEG activity was recorded while passively viewing photos of own, familiarized, and unfamiliar infants. Multiple regression indicated that mothers who reported greater infant negative affect showed a smaller difference in the late positive potential (LPP) response to own infant versus familiarized infant, controlling for researcher-coded infant negative affect. The findings suggest that parents' perceptions of their infant's temperament, but not independent measures of infant temperament, are related to electrocortical indices of emotional attention. © 2018 Wiley Periodicals, Inc.

Autism-specific covariation in perceptual performances: "g" or "p" factor?

PubMed

Meilleur, Andrée-Anne S; Berthiaume, Claude; Bertone, Armando; Mottron, Laurent

2014-01-01

Autistic perception is characterized by atypical and sometimes exceptional performance in several low- (e.g., discrimination) and mid-level (e.g., pattern matching) tasks in both visual and auditory domains. A factor that specifically affects perceptive abilities in autistic individuals should manifest as an autism-specific association between perceptual tasks. The first purpose of this study was to explore how perceptual performances are associated within or across processing levels and/or modalities. The second purpose was to determine if general intelligence, the major factor that accounts for covariation in task performances in non-autistic individuals, equally controls perceptual abilities in autistic individuals. We asked 46 autistic individuals and 46 typically developing controls to perform four tasks measuring low- or mid-level visual or auditory processing. Intelligence was measured with the Wechsler's Intelligence Scale (FSIQ) and Raven Progressive Matrices (RPM). We conducted linear regression models to compare task performances between groups and patterns of covariation between tasks. The addition of either Wechsler's FSIQ or RPM in the regression models controlled for the effects of intelligence. In typically developing individuals, most perceptual tasks were associated with intelligence measured either by RPM or Wechsler FSIQ. The residual covariation between unimodal tasks, i.e. covariation not explained by intelligence, could be explained by a modality-specific factor. In the autistic group, residual covariation revealed the presence of a plurimodal factor specific to autism. Autistic individuals show exceptional performance in some perceptual tasks. Here, we demonstrate the existence of specific, plurimodal covariation that does not dependent on general intelligence (or "g" factor). Instead, this residual covariation is accounted for by a common perceptual process (or "p" factor), which may drive perceptual abilities differently in autistic and non-autistic individuals.

Autism-Specific Covariation in Perceptual Performances: “g” or “p” Factor?

PubMed Central

Meilleur, Andrée-Anne S.; Berthiaume, Claude; Bertone, Armando; Mottron, Laurent

2014-01-01

Background Autistic perception is characterized by atypical and sometimes exceptional performance in several low- (e.g., discrimination) and mid-level (e.g., pattern matching) tasks in both visual and auditory domains. A factor that specifically affects perceptive abilities in autistic individuals should manifest as an autism-specific association between perceptual tasks. The first purpose of this study was to explore how perceptual performances are associated within or across processing levels and/or modalities. The second purpose was to determine if general intelligence, the major factor that accounts for covariation in task performances in non-autistic individuals, equally controls perceptual abilities in autistic individuals. Methods We asked 46 autistic individuals and 46 typically developing controls to perform four tasks measuring low- or mid-level visual or auditory processing. Intelligence was measured with the Wechsler's Intelligence Scale (FSIQ) and Raven Progressive Matrices (RPM). We conducted linear regression models to compare task performances between groups and patterns of covariation between tasks. The addition of either Wechsler's FSIQ or RPM in the regression models controlled for the effects of intelligence. Results In typically developing individuals, most perceptual tasks were associated with intelligence measured either by RPM or Wechsler FSIQ. The residual covariation between unimodal tasks, i.e. covariation not explained by intelligence, could be explained by a modality-specific factor. In the autistic group, residual covariation revealed the presence of a plurimodal factor specific to autism. Conclusions Autistic individuals show exceptional performance in some perceptual tasks. Here, we demonstrate the existence of specific, plurimodal covariation that does not dependent on general intelligence (or “g” factor). Instead, this residual covariation is accounted for by a common perceptual process (or “p” factor), which may drive perceptual abilities differently in autistic and non-autistic individuals. PMID:25117450

Cooperative mission execution and planning

NASA Astrophysics Data System (ADS)

Flann, Nicholas S.; Saunders, Kevin S.; Pells, Larry

1998-08-01

Utilizing multiple cooperating autonomous vehicles to perform tasks enhances robustness and efficiency over the use of a single vehicle. Furthermore, because autonomous vehicles can be controlled precisely and their status known accurately in real time, new types of cooperative behaviors are possible. This paper presents a working system called MEPS that plans and executes missions for multiple autonomous vehicles in large structured environments. Two generic spatial tasks are supported, to sweep an area and to visit a location while activating on-board equipment. Tasks can be entered both initially by the user and dynamically during mission execution by both users and vehicles. Sensor data and task achievement data is shared among the vehicles enabling them to cooperatively adapt to changing environmental, vehicle and tasks conditions. The system has been successfully applied to control ATV and micro-robotic vehicles in precision agriculture and waste-site characterization environments.

Multitasking in multiple sclerosis: can it inform vocational functioning?

PubMed

Morse, Chelsea L; Schultheis, Maria T; McKeever, Joshua D; Leist, Thomas

2013-12-01

To examine associations between multitasking ability defined by performance on a complex task integrating multiple cognitive domains and vocational functioning in multiple sclerosis (MS). Survey data collection. Laboratory with referrals from an outpatient clinic. Community-dwelling individuals with MS (N=30) referred between October 2011 and June 2012. Not applicable. The modified Six Elements Test (SET) to measure multitasking ability, Fatigue Severity Scale to measure fatigue, several neuropsychological measures of executive functioning, and vocational status. Among the sample, 60% of individuals have reduced their work hours because of MS symptoms (cutback employment group) and 40% had maintained their work hours. Among both groups, SET performance was significantly associated with performance on several measures of neuropsychological functioning. Individuals in the cutback employment group demonstrated significantly worse overall performance on the SET (P=.041). Logistic regression was used to evaluate associations between SET performance and vocational status, while accounting for neuropsychological performance and fatigue. The overall model was significant (χ(2)3=8.65, P=.032), with fatigue [Exp(B)=.83, P=.01] and multitasking ability [Exp(B)=.60, P=.043] retained as significant predictors. Multitasking ability may play an important role in performance at work for individuals with MS. Given that multitasking was associated with vocational functioning, future efforts should assess the usefulness of incorporating multitasking ability into rehabilitation planning. Copyright © 2013 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Ridge: a computer program for calculating ridge regression estimates

Treesearch

Donald E. Hilt; Donald W. Seegrist

1977-01-01

Least-squares coefficients for multiple-regression models may be unstable when the independent variables are highly correlated. Ridge regression is a biased estimation procedure that produces stable estimates of the coefficients. Ridge regression is discussed, and a computer program for calculating the ridge coefficients is presented.

Divided visual attention: A comparison of patients with multiple sclerosis and controls, assessed with an optokinetic nystagmus suppression task.

PubMed

Williams, Isla M; Schofield, Peter; Khade, Neha; Abel, Larry A

2016-12-01

Multiple sclerosis (MS) frequently causes impairment of cognitive function. We compared patients with MS with controls on divided visual attention tasks. The MS patients' and controls' stare optokinetic nystagmus (OKN) was recorded in response to a 24°/s full field stimulus. Suppression of the OKN response, judged by the gain, was measured during tasks dividing visual attention between the fixation target and a second stimulus, central or peripheral, static or dynamic. All participants completed the Audio Recorded Cognitive Screen. MS patients had lower gain on the baseline stare OKN. OKN suppression in divided attention tasks was the same in MS patients as in controls but in both groups was better maintained in static than in dynamic tasks. In only dynamic tasks, older age was associated with less effective OKN suppression. MS patients had lower scores on a timed attention task and on memory. There was no significant correlation between attention or memory and eye movement parameters. Attention, a complex multifaceted construct, has different neural combinations for each task. Despite impairments on some measures of attention, MS patients completed the divided visual attention tasks normally. Copyright © 2016 Elsevier Ltd. All rights reserved.

Clustered Multi-Task Learning for Automatic Radar Target Recognition

PubMed Central

Li, Cong; Bao, Weimin; Xu, Luping; Zhang, Hua

2017-01-01

Model training is a key technique for radar target recognition. Traditional model training algorithms in the framework of single task leaning ignore the relationships among multiple tasks, which degrades the recognition performance. In this paper, we propose a clustered multi-task learning, which can reveal and share the multi-task relationships for radar target recognition. To further make full use of these relationships, the latent multi-task relationships in the projection space are taken into consideration. Specifically, a constraint term in the projection space is proposed, the main idea of which is that multiple tasks within a close cluster should be close to each other in the projection space. In the proposed method, the cluster structures and multi-task relationships can be autonomously learned and utilized in both of the original and projected space. In view of the nonlinear characteristics of radar targets, the proposed method is extended to a non-linear kernel version and the corresponding non-linear multi-task solving method is proposed. Comprehensive experimental studies on simulated high-resolution range profile dataset and MSTAR SAR public database verify the superiority of the proposed method to some related algorithms. PMID:28953267

BAYESIAN LARGE-SCALE MULTIPLE REGRESSION WITH SUMMARY STATISTICS FROM GENOME-WIDE ASSOCIATION STUDIES1

PubMed Central

Zhu, Xiang; Stephens, Matthew

2017-01-01

Bayesian methods for large-scale multiple regression provide attractive approaches to the analysis of genome-wide association studies (GWAS). For example, they can estimate heritability of complex traits, allowing for both polygenic and sparse models; and by incorporating external genomic data into the priors, they can increase power and yield new biological insights. However, these methods require access to individual genotypes and phenotypes, which are often not easily available. Here we provide a framework for performing these analyses without individual-level data. Specifically, we introduce a “Regression with Summary Statistics” (RSS) likelihood, which relates the multiple regression coefficients to univariate regression results that are often easily available. The RSS likelihood requires estimates of correlations among covariates (SNPs), which also can be obtained from public databases. We perform Bayesian multiple regression analysis by combining the RSS likelihood with previously proposed prior distributions, sampling posteriors by Markov chain Monte Carlo. In a wide range of simulations RSS performs similarly to analyses using the individual data, both for estimating heritability and detecting associations. We apply RSS to a GWAS of human height that contains 253,288 individuals typed at 1.06 million SNPs, for which analyses of individual-level data are practically impossible. Estimates of heritability (52%) are consistent with, but more precise, than previous results using subsets of these data. We also identify many previously unreported loci that show evidence for association with height in our analyses. Software is available at https://github.com/stephenslab/rss. PMID:29399241

Dual Task of Fine Motor Skill and Problem Solving in Individuals With Multiple Sclerosis: A Pilot Study.

PubMed

Goverover, Y; Sandroff, B M; DeLuca, J

2018-04-01

To (1) examine and compare dual-task performance in patients with multiple sclerosis (MS) and healthy controls (HCs) using mathematical problem-solving questions that included an everyday competence component while performing an upper extremity fine motor task; and (2) examine whether difficulties in dual-task performance are associated with problems in performing an everyday internet task. Pilot study, mixed-design with both a within and between subjects' factor. A nonprofit rehabilitation research institution and the community. Participants (N=38) included persons with MS (n=19) and HCs (n=19) who were recruited from a nonprofit rehabilitation research institution and from the community. Not applicable. Participant were presented with 2 testing conditions: (1) solving mathematical everyday problems or placing bolts into divots (single-task condition); and (2) solving problems while putting bolts into divots (dual-task condition). Additionally, participants were required to perform a test of everyday internet competence. As expected, dual-task performance was significantly worse than either of the single-task tasks (ie, number of bolts into divots or correct answers, and time to answer the questions). Cognitive but not motor dual-task cost was associated with worse performance in activities of everyday internet tasks. Cognitive dual-task cost is significantly associated with worse performance of everyday technology. This was not observed in the motor dual-task cost. The implications of dual-task costs on everyday activity are discussed. Copyright © 2017 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.