The On-Line Processing of Verb-Phrase Ellipsis in Aphasia

We investigate the on-line processing of verb-phrase ellipsis (VPE) constructions in two brain injured populations: Broca’s and Anomic aphasics. VPE constructions are built from two simple clauses; the first is the antecedent clause and the second is the ellipsis clause. The ellipsis clause is missing its verb and object (i.e., its verb phrase (VP)), which receives its reference from the fully specified VP in the antecedent clause. VPE constructions are unlike other sentence types that require displacement of an argument NP; these latter constructions (e.g., object-relatives, wh-questions) yield either on-time or delayed antecedent reactivation. Our results demonstrate that Anomics, like unimpaired individuals, evince reactivation of the direct object NP (within the VP) at the elided position. Broca’s patients, on the other hand, do not show reactivation of the antecedent. We consider several interpretations for our data, including explanations focusing on the larger ‘grain size’ of the reconstructed material in the ellipsis clause, the properties of the auxiliary that carries tense and agreement features, and the possibility that the cost-free syntactic copy procedure claimed to underlie VPE may be modulated by the functional deficit in Broca’s aphasia.     

Composition of brain oscillations and their functions in the maintenance of auditory,visual and audio–visual speech percepts: an exploratory study

In the present exploratory study based on 7 subjects, we examined the composition of magnetoencephalographic (MEG) brain oscillations induced by the presentation of an auditory, visual, and audio-visual stimulus (a talking face) using an oddball paradigm. The composition of brain oscillations were assessed here by analyzing the probability-classification of short-term MEG spectral patterns. The probability index for particular brain oscillations being elicited was dependent on the type and the modality of the sensory percept. The maintenance of the integrated audio-visual percept was accompanied by the unique composition of distributed brain oscillations typical of auditory and visual modality, and the contribution of brain oscillations characteristic for visual modality was dominant. Oscillations around 20 Hz were characteristic for the maintenance of integrated audio-visual percept. Identifying the actual composition of brain oscillations allowed us (1) to distinguish two subjectively/consciously identical mental percepts, and (2) to characterize the types of brain functions involved in the maintenance of the multi-sensory percept.     

Meta‐CART: A tool to identify interactions between moderators in meta‐analysis

In the framework of meta‐analysis, moderator analysis is usually performed only univariately. When several study characteristics are available that may account for treatment effect, standard meta‐regression has difficulties in identifying interactions between them. To overcome this problem, meta‐CART has been proposed: an approach that applies classification and regression trees (CART) to identify interactions, and then subgroup meta‐analysis to test the significance of moderator effects. The previous version of meta‐CART has its shortcomings: when applying CART, the sample sizes of studies are not taken into account, and the effect sizes are dichotomized around the median value. Therefore, this article proposes new meta‐CART extensions, weighting study effect sizes by their accuracy, and using a regression tree to avoid dichotomization. In addition, new pruning rules are proposed. The performance of all versions of meta‐CART was evaluated via a Monte Carlo simulation study. The simulation results revealed that meta‐regression trees with random‐effects weights and a 0.5‐standard‐error pruning rule perform best. The required sample size for meta‐CART to achieve satisfactory performance depends on the number of study characteristics, the magnitude of the interactions, and the residual heterogeneity.     

The P600 in Implicit Artificial Grammar Learning

The suitability of the artificial grammar learning (AGL) paradigm to capture relevant aspects of the acquisition of linguistic structures has been empirically tested in a number of EEG studies. Some have shown a syntax‐related P600 component, but it has not been ruled out that the AGL P600 effect is a response to surface features (e.g., subsequence familiarity) rather than the underlying syntax structure. Therefore, in this study, we controlled for the surface characteristics of the test sequences (associative chunk strength) and recorded the EEG before (baseline preference classification) and after (preference and grammaticality classification) exposure to a grammar. After exposure, a typical, centroparietal P600 effect was elicited by grammatical violations and not by unfamiliar subsequences, suggesting that the AGL P600 effect signals a response to structural irregularities. Moreover, preference and grammaticality classification showed a qualitatively similar ERP profile, strengthening the idea that the implicit structural mere‐exposure paradigm in combination with preference classification is a suitable alternative to the traditional grammaticality classification test.     

Visualising mental representations: A primer on noise-based reverse correlation in social psychology

With the introduction of the psychophysical method of reverse correlation, a holy grail of social psychology appears to be within reach – visualising mental representations. Reverse correlation is a data-driven method that yields visual proxies of mental representations, based on judgements of randomly varying stimuli. This review is a primer to an influential reverse correlation approach in which stimuli vary by applying random noise to the pixels of images. Our review suggests that the technique is an invaluable tool in the investigation of social perception (e.g., in the perception of race, gender and personality traits), with ample potential applications. However, it is unclear how these visual proxies are best interpreted. Building on advances in cognitive neuroscience, we suggest that these proxies are visual reflections of the internal representations that determine how social stimuli are perceived. In addition, we provide a tutorial on how to perform reverse correlation experiments using R.     

The regression trunk approach to discover treatment covariate interaction

The regression trunk approach (RTA) is an integration of regression trees and multiple linear regression analysis. In this paper RTA is used to discover treatment covariate interactions, in the regression of one continuous variable on a treatment variable withmultiple covariates. The performance of RTA is compared to the classical method of forward stepwise regression. The results of two simulation studies, in which the true interactions are modeled as threshold interactions, show that RTA detects the interactions in a higher number of cases (82.3% in the first simulation study, and 52.3% in the second) than stepwise regression (56.5% and 20.5%). In a real data example the final RTA model has a higher cross-validated variance-accounted-for (29.8%) than the stepwise regression model (12.5%). All of these results indicate that RTA is a promising alternative method for demonstrating differential effectiveness of treatments. Supported by The Netherlands Organization for Scientific Research (NWO), grant 030-56403 to Jacqueline Meulman for the Pioneer project “Subject-Oriented Multivariate Analysis,” and grant 451-02-058 to Elise Dusseldorp for the Veni project “Modeling interaction effects as small trees in regression and classification.” We thank Bram Bakker for making the data of his doctoral dissertation available, and David Hand, Jerome Friedman, Bart Jan van Os, Philip Spinhoven, and the anonymous reviewers for their helpful suggestions. Special thanks are due to Lawrence Hubert.     

Three-Mode Component Analysis with Crisp or Fuzzy Partition of Units

A new methodology is proposed for the simultaneous reduction of units, variables, and occasions of a three-mode data set. Units are partitioned into a reduced number of classes, while, simultaneously, components for variables and occasions accounting for the largest common information for the classification are identified. The model is a constrained three-mode factor analysis and it can be seen as a generalization of the REDKM model proposed by De Soete and Carroll for two-mode data. The least squares fitting problem is mathematically formalized as a constrained problem in continuous and discrete variables. An iterative alternating least squares algorithm is proposed to give an efficient solution to this minimization problem in the crisp and fuzzy classification context. The performances of the proposed methodology are investigated by a simulation study comparing our model with other competing methodologies. Different procedures for starting the proposed algorithm have also been tested. A discussion of some interesting differences in the results follows. Finally, an application to real data illustrates the ability of the proposed model to provide substantive insights into the data complexities.     

Intense classification training to increase the detection of drowning swimmers

Lifeguards engage in a continuous process of deciding whether swimmers are in danger or not. The variety of behaviours that distressed swimmers show makes it difficult to impart declarative knowledge to this effect during lifeguard training. As an alternative, we propose a novel training tool that requires novice participants to rapidly categorise 3-s video clips of real-life swimmers as either ‘safe’ or ‘drowning’. A control group also completed a sham intervention, with surfers that may ‘fall’. Due to the complex nature of swimming pools, a scaffolded training approach was employed, which gradually increased the amount of background information over subsequent training rounds. Results demonstrated that the drowning classification training improved responses in a subsequent drowning detection test, compared with the active control-group. The scaffolded approach appeared to prepare participants for processing swimmers in the drowning-detection test. The results provide a foundation for a novel training protocol to improve lifeguard skills.     

Classification of Planning and Violent Behaviours in Serial Homicide: A Cross‐National Comparison Between South Africa and the US

Recent literature suggests that different ‘styles’ of homicide will most appropriately be reflected in the different types of behaviours committed by offenders during the crime. In the last few years, there has been a move to standardise classification systems of single homicides and establish their cross‐national generalisability. Literature on serial homicide to date has mostly centred on homicides occurring in the US. However, national differences due to factors such as culture, national identity, political, and socio‐economic circumstances may decrease the applicability of these models or certain aspects thereof in other countries and thus must be evaluated. The present study tested the applicability in the South African context of a recently developed US‐based serial homicide crime scene classification framework. Specifically, this study compared the thematic differentiation in planning and violent behaviours that the offenders engage in and how this differentiation compares with that in the US. The sample consisted of 25 homicides that were in total responsible for the murder of 267 victims. Results indicated that overall, the framework is useful and applicable in the South African sample, but important environmental and contextual constraints must be taken into account. Copyright © 2014 John Wiley & Sons, Ltd.