Task complexity, the Cognition Hypothesis and second language learning and performance

In this paper we describe a taxonomy of task demands which distinguishes between Task Complexity, Task Condition and Task Difficulty. We then describe three theoretical claims and predictions of the Cognition Hypothesis (Robinson 2001, 2003b, 2005a) concerning the effects of task complexity on: (a) language production; (b) interaction and uptake of information available in the input to tasks; and (c) individual differences-task interactions. Finally we summarize the findings of the empirical studies in this special issue which all address one or more of these predictions and point to some directions for continuing, future research into the effects of task complexity on learning and performance.

Hippocampal Theta-Phase Modulation of Replay Correlates with Configural-Relational Short-Term Memory Performance

Thereis now growing evidencethatthe hippocampus generatestheta rhythmsthat can phase biasfast neural oscillationsinthe neocortex, allowing coordination of widespread fast oscillatory populations outside limbic areas. A recent magnetoencephalographic study showed that maintenance of configural-relational scene information in a delayed match-to-sample (DMS) task was associated with replay of that information during the delay period. The periodicity of the replay was coordinated by the phase of the ongoing theta rhythm, and the degree of theta coordination during the delay period was positively correlated with DMS performance. Here, we reanalyzed these data to investigate which brain regions were involved in generating the theta oscillations that coordinated the periodic replay of configural- relational information. We used a beamformer algorithm to produce estimates of regional theta rhythms and constructed volumetric images of the phase-locking between the local theta cycle and the instances of replay (in the 13- 80 Hz band). We found that individual differences in DMS performancefor configural-relational associations were relatedtothe degree of phase coupling of instances of cortical reactivations to theta oscillations generated in the right posterior hippocampus and the right inferior frontal gyrus. This demonstrates that the timing of memory reactivations in humans is biased toward hippocampal theta phase

The influence of genetic and environmental factors among MDMA users in cognitive performance

This study is aimed to clarify the association between MDMA cumulative use and cognitive dysfunction, and the potential role of candidate genetic polymorphisms in explaining individual differences in the cognitive effects of MDMA. Gene polymorphisms related to reduced serotonin function, poor competency of executive control and memory consolidation systems, and high enzymatic activity linked to bioactivation of MDMA to neurotoxic metabolites may contribute to explain variations in the cognitive impact of MDMA across regular users of this drug. Sixty ecstasy polydrug users, 110 cannabis users and 93 non-drug users were assessed using cognitive measures of Verbal Memory (California Verbal Learning Test, CVLT), Visual Memory (Rey-Osterrieth Complex Figure Test, ROCFT), Semantic Fluency, and Perceptual Attention (Symbol Digit Modalities Test, SDMT). Participants were also genotyped for polymorphisms within the 5HTT, 5HTR2A, COMT, CYP2D6, BDNF, and GRIN2B genes using polymerase chain reaction and TaqMan polymerase assays. Lifetime cumulative MDMA use was significantly associated with poorer performance on visuospatial memory and perceptual attention. Heavy MDMA users (>100 tablets lifetime use) interacted with candidate gene polymorphisms in explaining individual differences in cognitive performance between MDMA users and controls. MDMA users carrying COMT val/val and SERT s/s had poorer performance than paired controls on visuospatial attention and memory, and MDMA users with CYP2D6 ultra-rapid metabolizers performed worse than controls on semantic fluency. Both MDMA lifetime use and gene-related individual differences influence cognitive dysfunction in ecstasy users.

Towards a lightweight adaptative multicomponential affective recognition system

As part of the Affective Computing research field, the development of automatic affective recognition systems can enhance human-computer interactions by allowing the creation of interfaces that react to the user's emotional state. To that end, this Master Thesis brings affect recognition to nowadays most used human computer interface, mobile devices, by developing a facial expression recognition system able to perform detection under the difficult conditions of viewing angle and illumination that entails the interaction with a mobile device. Moreover, this Master Thesis proposes to combine emotional features detected from expression with contextual information of the current situation, to infer a complex and extensive emotional state of the user. Thus, a cognitive computational model of emotion is defined that provides a multicomponential affective state of the user through the integration of the detected emotional features into appraisal processes. In order to account for individual differences in the emotional experience, these processes can be adapted to the culture and personality of the user.

Work, risk and health: differences between immigrants and natives in Spain

We analyze the impact of working and contractual conditions, particularly exposure to job risks, on the probability of acquiring a disability. We postulate a model in which this impact is mediated by the choice of occupation, with a level of risk associated to it. We assume this choice is endogenous, and that it depends on preferences and opportunities in the labour market, both of which may differ between immigrants and natives. To test this hypothesis we use data from the Continuous Sample of Working Lives of the Spanish SS system. It contains individual, job and firm information of over a million workers, including a representative sample of immigrants. We find that risk exposure increases the probability of permanent disability by 5.3%; temporary employment also influences health. Migrant status -with differences among regions of origin- significantly affects both disability and the probability of being employed in a risky occupation. Most groups of immigrants work in riskier jobs, but have lower probability of becoming disabled. Nevertheless, our theoretical hypothesis that disability and risk are jointly determined is not valid for immigrants: i.e. for them working conditions is not a matter of choice in terms of health.

What made him change? an individual and national analysis of men's participation in housework in 26 countries

We offer new evidence on multi-level determinants of the gender division of housework. Using data from the 2004 European Social Survey (ESS) for 26 European, we study the micro and macro-level factors which increase the likelihood of men doing an equal or greater share of housework than their female partners. A sample of 11,915 young men and women is analysed with a multi-level logistic regression in order to test at individual level the classic relative-income, time-availability and gender-role values, and a new couple conflict hypothesis. At individual level we find significant relationships between relative resources, values, couple's disagreement, and the division of housework which support more economic dependency than "doing gender" perspectives. At the macro-level, we find important composition effects and also support for gender empowerment, family model and social stratification explanations of cross-country differences.

Generational effects on adult height in individual heterogeneity

As adult height is a well-established retrospective measure of health and standard of living, it is important to understand the factors that determine it. Among them, the influence of socio-environmental factors has been subjected to empirical scrutiny. This paper explores the influence of generational (or environmental) effects and individual and gender-specific heterogeneity on adult height. Our data set is from contemporary Spain, a country governed by an authoritarian regime between 1939 and 1977. First, we use normal position and quantile regression analysis to identify the determinants of self-reported adult height and to measure the influence of individual heterogeneity. Second, we use a Blinder-Oaxaca decomposition approach to explain the `gender height gap¿ and its distribution, so as to measure the influence on this gap of individual heterogeneity. Our findings suggest a significant increase in adult height in the generations that benefited from the country¿s economic liberalization in the 1950s, and especially those brought up after the transition to democracy in the 1970s. In contrast, distributional effects on height suggest that only in recent generations has ¿height increased more among the tallest¿. Although the mean gender height gap is 11 cm, generational effects and other controls such as individual capabilities explain on average roughly 5% of this difference, a figure that rises to 10% in the lowest 10% quantile.

Probe-specific mixed-model approach to detect copy number differences using multiplex ligation-dependent probe amplification (MLPA)

Background: MLPA method is a potentially useful semi-quantitative method to detect copy number alterations in targeted regions. In this paper, we propose a method for the normalization procedure based on a non-linear mixed-model, as well as a new approach for determining the statistical significance of altered probes based on linear mixed-model. This method establishes a threshold by using different tolerance intervals that accommodates the specific random error variability observed in each test sample.Results: Through simulation studies we have shown that our proposed method outperforms two existing methods that are based on simple threshold rules or iterative regression. We have illustrated the method using a controlled MLPA assay in which targeted regions are variable in copy number in individuals suffering from different disorders such as Prader-Willi, DiGeorge or Autism showing the best performace.Conclusion: Using the proposed mixed-model, we are able to determine thresholds to decide whether a region is altered. These threholds are specific for each individual, incorporating experimental variability, resulting in improved sensitivity and specificity as the examples with real data have revealed.

Generational effects on adult height in individual heterogeneity

As adult height is a well-established retrospective measure of health and standard of living, it is important to understand the factors that determine it. Among them, the influence of socio-environmental factors has been subjected to empirical scrutiny. This paper explores the influence of generational (or environmental) effects and individual and gender-specific heterogeneity on adult height. Our data set is from contemporary Spain, a country governed by an authoritarian regime between 1939 and 1977. First, we use normal position and quantile regression analysis to identify the determinants of self-reported adult height and to measure the influence of individual heterogeneity. Second, we use a Blinder-Oaxaca decomposition approach to explain the `gender height gap¿ and its distribution, so as to measure the influence on this gap of individual heterogeneity. Our findings suggest a significant increase in adult height in the generations that benefited from the country¿s economic liberalization in the 1950s, and especially those brought up after the transition to democracy in the 1970s. In contrast, distributional effects on height suggest that only in recent generations has ¿height increased more among the tallest¿. Although the mean gender height gap is 11 cm, generational effects and other controls such as individual capabilities explain on average roughly 5% of this difference, a figure that rises to 10% in the lowest 10% quantile.