Are imaging and lesioning convergent methods for assessing functional specialisation?: investigations using an artificial neural network

This article presents an investigation of the relationship between lesioning and neuroimaging methods of assessing functional specialisation, using synthetic brain imaging (SBI) and lesioning of a connectionist network of past-tense formation. The model comprised two processing ‘routes’: one was a direct route between layers of input and output units, while the other, indirect, route featured an intermediate layer of processing units. Emergent specialisation within the network was assessed (1) by lesioning either the direct or indirect route and measuring past-tense performance for regular and irregular verbs, and (2) by measuring functional activation in each route when processing each verb type (SBI). SBI and lesioning approaches failed to converge when network activation was summed over each route in our SBI approach. Examination of individual network solutions suggested that the verb types might be using the indirect route differently in terms of the pattern of activation across the route, rather than in terms of gross activation. A subsequent SBI analysis compared patterns of activation in the indirect route and confirmed that these patterns were more similar between regular-type verbs than between regular and irregular verbs. As the spatial and temporal resolution of neuroimaging techniques improves, the results of this investigation suggest that the key to finding functional specialisation will be to distinguish local coding differences across behaviours that are the results of developmental processes. Other analyses suggest that lesioning data may be limited because, with increasing damage, they reveal the resting activations of a computational system rather than a computational specialisation per se.     

Measuring rail passenger crowding: Scale development and psychometric properties

Research on rail passenger crowding often tacitly subscribes to a measurement of crowding based on density (i.e. physical conditions involving space limitations) and rarely considers the possible role psychological factors may play in measuring this construct. This paper describes the development of an instrument that captures the dimensionality of rail passenger crowding and its relationship to the experience of stress and feelings of exhaustion. The proposed instrument is a 20-item self-rating questionnaire consisting of three sub-scales designed to assess subjective crowding experiences among rail users (n = 525). Findings from the factor analyses generally support the hypothesised three-factor structure of the measurement model (evaluation of the psychosocial aspects of the crowded situation, evaluation of the ambient environment of the crowded situation, and affective reactions to the crowded situation). All sub-scales demonstrate excellent internal consistency and construct validity as well as good convergent and discriminant validity values. The instrument was further tested using structural equation modelling to examine the impact of crowding on commuters’ stress and feelings of exhaustion. With the addition of the “passenger density” variable as an indicator of objective measurement of crowding operating in tandem with the crowding sub-scales, the results reveal that: (1) commuters’ evaluations of the psychosocial aspects of the crowded situation and of its ambient environment, alongside their rating of passenger density, significantly predict affective reactions to the crowded situation; (2) these affective reactions, in turn, significantly predict stress and feelings of exhaustion; and (3) evaluations of the psychosocial aspects of the crowded situation and of its ambient environment as well as passenger density do not directly predict stress and feelings of exhaustion. The link between rail passenger crowding and the negative outcomes therefore does not appear as a simple, direct relationship, but is mediated by affective feelings of crowdedness. Overall, these results provide satisfactory psychometric properties for the proposed instrument and support its use as an assessment tool for measuring crowding experience in the rail setting.     

Bayesian networks for unbiased assessment of referee bias in Association Football

ObjectivesTo assess referee bias with respect to fouls and penalty kicks awarded by taking explanatory factors into consideration.DesignWe present a novel Bayesian network model for assessing referee bias with respect to fouls and penalty kicks awarded. The model is applied to the 2011-12 English Premier League season.MethodUnlike previous studies, the model takes into consideration explanatory factors which, if ignored, can lead to biased assessments of referee bias. For example, a team may be awarded more penalties simply because it attacks more, not because referees are biased in its favour. Hence, we incorporate causal factors such as possession, time spent in the opposition penalty box, etc. prior to estimating the degree of penalty kicks bias.ResultsWe found fairly strong referee bias, based on penalty kicks awarded, in favour of certain teams when playing at home. Specifically, the two teams (Manchester City and Manchester United) who finished first and second appear to have benefited from bias that cannot be fully justified by the explanatory factors. Conversely Arsenal, a team of similar popularity and wealth and who finished third, benefited least of all 20 teams from referee bias at home with respect to penalty kicks awarded.ConclusionsAmong our conclusions are that, in contrast to many previous studies, being the home team does not in itself result in positive referee bias. More importantly, the model is able to explain significant discrepancies of penalty kicks bias into non-significant after accounting for the explanatory factors.     

Modelling unsupervised online-learning of artificial grammars: Linking implicit and statistical learning

Humans rapidly learn complex structures in various domains. Findings of above-chance performance of some untrained control groups in artificial grammar learning studies raise questions about the extent to which learning can occur in an untrained, unsupervised testing situation with both correct and incorrect structures. The plausibility of unsupervised online-learning effects was modelled with n-gram, chunking and simple recurrent network models. A novel evaluation framework was applied, which alternates forced binary grammaticality judgments and subsequent learning of the same stimulus. Our results indicate a strong online learning effect for n-gram and chunking models and a weaker effect for simple recurrent network models. Such findings suggest that online learning is a plausible effect of statistical chunk learning that is possible when ungrammatical sequences contain a large proportion of grammatical chunks. Such common effects of continuous statistical learning may underlie statistical and implicit learning paradigms and raise implications for study design and testing methodologies.     

A theoretical analysis of the perceptual span based on SWIFT simulations of the n + 2 boundary paradigm

Eye-movement experiments suggest that the perceptual span during reading is larger than the fixated word, asymmetric around the fixation position, and shrinks in size contingent on the foveal processing load. We used the SWIFT model of eye-movement control during reading to test these hypotheses and their implications under the assumption of graded parallel processing of all words inside the perceptual span. Specifically, we simulated reading in the boundary paradigm and analysed the effects of denying the model to have valid preview of a parafoveal word n + 2 two words to the right of fixation. Optimizing the model parameters for the valid preview condition only, we obtained span parameters with remarkably realistic estimates conforming to the empirical findings on the size of the perceptual span. More importantly, the SWIFT model generated parafoveal processing up to word n + 2 without fitting the model to such preview effects. Our results suggest that asymmetry and dynamic modulation are plausible properties of the perceptual span in a parallel word-processing model such as SWIFT. Moreover, they seem to guide the flexible distribution of processing resources during reading between foveal and parafoveal words.     

Is expressive suppression an effective coping strategy? A study of Chinese rescue medical staff following an earthquake

The current study examined the function of expressive suppression among Chinese rescue medical staff following a major earthquake. We administered self‐report questionnaires to (1) a sample of Chinese hospital medical staff (n = 305) who assisted victims of the Sichuan earthquake, and (2) a second sample of Chinese hospital medical staff (n = 149) who had not been exposed to a major stressor. To examine possible interaction effects among differing emotion regulation strategies, we also conducted structured interviews with a subset of rescue medical staff to obtain support for a positive function of expressive suppression and a mediating role of positive reappraisal. Structural equation modelling indicated that expressive suppression was associated with higher levels of job engagement and lower levels of job burnout among the rescue medical staff and that these effects were mediated by positive reappraisal. However, for regular medical staff (not exposed to traumatic stress), expressive suppression was associated with higher levels of both job engagement and job burnout; these effects were mediated by acceptance. These results provide preliminary evidence for the positive role of expressive suppression within Chinese culture.     

Interval timing predicts impulsivity in intertemporal choice: combined behavioral and drift-diffusion model evidence

ABSTRACT

This study investigated the relationship between interval timing and impulsivity in intertemporal choice in a healthy population. A duration production task was used to assess interval timing. Choice impulsivity was assessed using a hypothetical money choice task. Results from 134 participants indicated that faster internal clock significantly predicted lower choice impulsivity. A subsequent drift-diffusion model analysis of the behavioural data revealed that in the sub-group of relatively farsighted participants, faster internal clock predicted consideration of more information before making a choice, which in turn was associated with lower choice impulsivity. In the sub-group of relatively impatient participants too, faster internal clock predicted consideration of more information, but which in turn was associated with higher choice impulsivity. It is concluded that among relatively farsighted individuals in a normal population, faster internal clock favours a more deliberate processing of the options at hand, thus eliciting less impulsive choices.     

Social Dominance Orientation and Right‐Wing Authoritarianism: Additive and Interactive Effects on Political Conservatism

It is commonly accepted that social dominance orientation (SDO) and right‐wing authoritarianism (RWA) are potent unique predictors of a variety of prejudice and prejudice‐related constructs. However, contrary to some predictions, there has been little evidence that these constructs interact to produce this outcome—they appear to be additive but not interactive in their prediction of prejudice. We extend the interaction hypothesis to consideration of another broadly relevant construct—political ideology. Drawing from 14 independent New Zealand–based samples, we show, through meta‐analysis and multilevel random coefficient modelling, that SDO and RWA additively and interactively predict levels of political conservatism operationalised in a variety of ways. Specifically, both constructs are associated with increasing political conservatism, and the lowest levels of conservatism (or highest levels of political liberalism) are found in those lowest in both SDO and RWA.     

Modelling decisions to undergo genetic testing for susceptibility to common health conditions: An ancillary study of the Multiplex Initiative

New genetic tests reveal risks for multiple conditions simultaneously, although little is understood about the psychological factors that affect testing uptake. We assessed a conceptual model called the multiplex genetic testing model (MGTM) using structural equation modelling. The MGTM delineates worry, perceived severity, perceived risk, response efficacy and attitudes towards testing as predictors of intentions and behaviour. Participants were 270 healthy insured adults aged 25–40 from the Multiplex Initiative conducted within a health care system in Detroit, MI, USA. Participants were offered a genetic test that assessed risk for eight common health conditions. Confirmatory factor analysis revealed that worry, perceived risk and severity clustered into two disease domains: cancer or metabolic conditions. Only perceived severity of metabolic conditions was correlated with general response efficacy (β?=?0.13, p<0.05), which predicted general attitudes towards testing (β?=?0.24, p<0.01). Consistent with our hypothesised model, attitudes towards testing were the strongest predictors of intentions to undergo testing (β?=?0.49, p<0.01), which in turn predicted testing uptake (OR 17.7, β?=?0.97, p<0.01). The MGTM explained a striking 48% of the variance in intentions and 94% of the variation in uptake. These findings support use of the MGTM to explain psychological predictors of testing for multiple health conditions.     

Sociodemographic risk and early environmental factors that contribute to resilience in executive control: A factor mixture model of 3-year-olds

Young children at sociodemographic risk generally demonstrate lower executive control (EC), although with substantial heterogeneity across children. Given this marked variability, there may be some at-risk children who display higher EC and may be buffered from or resilient to the effects of sociodemographic risk who can be studied to identify the contributory factors. In this study, factor mixture modelling was used to determine whether subgroups of 3-year-old children existed based on their observed performance on a battery of EC tasks. Results indicated 2 latent groups: One characterized by lower EC and the other by higher EC. Both sociodemographically at-risk and low-risk children were represented in each group, yielding 4 risk-status-by-EC groups, where at-risk higher EC children were termed the resilient group. Proximal household enrichment (e.g., exposure to learning materials, varied enriching experiences, academic and language stimulation, parental responsivity) distinguished the resilient group from lower performing children of similar risk status, whereas distal financial resources and proximal social network resources did not distinguish these two groups. Results suggest potential intervention targets to promote optimal EC development, particularly among children at risk.