Contrast effects in typicality judgements: A hierarchical Bayesian approach

We examine the influence of contrast categories on the internal graded membership structure of everyday concepts using computational models proposed in the artificial category learning tradition. In particular, the generalized context model (Nosofsky, 1986), which assumes that only members of a given category contribute to the typicality of a category member, is contrasted to the similarity–dissimilarity generalized context model (SD-GCM; Stewart & Brown, 2005), which assumes that members of other categories are also influential in determining typicality. The models are compared in a hierarchical Bayesian framework in their account of the typicality gradient of five animal categories and six artefact categories. For each target category, we consider all possible relevant contrast categories. Three separate issue are examined: (a) whether contrast effects can be found, (b) which categories are responsible for these effects, and (c) whether more than one category influences the typicality. Results indicate that the internal category structure is codetermined by dissimilarity towards potential contrast categories. In most cases, only a single contrast category contributed to the typicality. The present findings suggest that contrast effects might be more widespread than has previously been assumed. Further, they stress the importance of characteristics particular of everyday concepts, which require careful consideration when applying computational models of representation of the artificial category learning tradition to everyday concepts.     

Attention and memory protection: Interactions between retrospective attention cueing and interference

Visual working memory (VWM) and attention have a number of features in common, but despite extensive research it is still unclear how the two interact. Can focused attention improve VWM precision? Can it protect VWM from interference? Here we used a partial-report, continuous-response orientation memory task to examine how attention and interference affect different aspects of VWM and how they interact with one another. Both attention and interference were orthogonally manipulated during the retention interval. Attention was manipulated by presenting informative retro-cues, whereas interference was manipulated by introducing a secondary interfering task. Mixture-model analyses revealed that retro-cues, compared to uninformative cues, improved all aspects of performance: Attention increased recall precision and decreased guessing rate and swap-errors (reporting a wrong item in memory). Similarly, performing a secondary task impaired all aspects of the VWM task. In particular, an interaction between retro-cue and secondary task interference was found primarily for swap-errors. Together these results suggest that both the quantity and quality of VWM representations are sensitive to attention cueing and interference modulations, and they highlight the role of attention in protecting the feature–location associations needed to access the correct items in memory.     

Inconsistency effects in source memory and compensatory schema-consistent guessing

The attention–elaboration hypothesis of memory for schematically unexpected information predicts better source memory for unexpected than expected sources. In three source-monitoring experiments, the authors tested the occurrence of an inconsistency effect in source memory. Participants were presented with items that were schematically either very expected or very unexpected for their source. Multinomial processing tree models were used to separate source memory, item memory, and guessing bias. Results show an inconsistency effect in source memory accompanied by a compensatory schema-consistent guessing bias when expectancy strength is high, that is, when items are very expected or very unexpected for their source.     

Methodological and empirical developments for the Ratcliff diffusion model of response times and accuracy

Summerfield, Egner, Mangels, and Hirsch (2006) suggested that visual misperception may be triggered by strong yet wrong expectation when sensory data are insufficient. Bar (2003) posits that immediately after stimulus presentation, low frequency spatial information (LFSI) convey the global form of the image which is matched to stored representations in the orbitofrontal cortex to generate predictions of the input. We used signal detection to test whether a strong prediction induced by informative global form, hence reducing the number of possible input matches, would facilitate recognition, but at the price of increasing the rate of misperceptions. Twenty-five participants were presented with target and foil images that shared global form, but differed in details. Pictures with informative global form resulted in higher confidence in recognition and shorter reaction times, but increased false alarms. Predictions of sensory input based on low frequency spatial information allow quick, facilitated recognition. However, the price for speed is the increased rate of misperceptions.     

Incurable suffering from the “hiatus theoreticus”? Some epistemological problems in modern medicine and the clinical relevance of philosophy of medicine

Up to now neither the question, whether all theoretical medical knowledge can at least be described as scientific, nor the one how exactly access to the existing scientific and theoretical medical knowledge during clinical problem-solving is made, has been sufficiently answered. Scientific theories play an important role in controlling clinical practice and improving the quality of clinical care in modern medicine on the one hand, and making it vindicable on the other. Therefore, the vagueness of unexplicit interrelations between medicine's stock of knowledge and medical practice appears as a gap in the theoretical concept of modern medicine which can be described as Hiatus theoreticus in the anatomy of medicine. A central intention of the paper is to analyze the role of philosophy of medicine for the clarification of the theoretical basis of medical practice. Clinical relevance and normativity in the sense of modern theory of science are suggested as criteria to establish a differentiation between philosophy of medicine as a primary medical discipline and the application of general philosophy in medicine.     

Loss context enhances preferences for generosity but reduces preferences for honesty: Evidence from a combined behavioural-computational approach

The current literature has revealed mixed evidence on whether loss (vs. gain) context promotes or curtails human prosociality. The current study (N=96) aimed to address this issue by examining whether gain/loss context has distinct effects on different prosocial preferences combining computational modelling with Dictator Game and Message Game. These interactive games allow for dissociating preferences for generosity and honesty, which have been respectively associated with intuitive and deliberative systems. Our behavioural and computational modelling results indicate that loss context enhances concerns for generosity but reduces concerns for honesty. These findings support an account under the framework of dual process model asserting that loss facilitates intuitive responses during social decision-making, regardless of whether they are prosocial or proself. The current findings reconcile previous debates on the relationship between loss-gain context and human prosociality and shed light on the design of institutions to promote human prosocial behaviours.     

The mediational role of motivation in the model of motor development in childhood: A longitudinal study

The aim of this study was twofold: first, to examine the stability of the hypothesized conceptual model of motor development (without and with including various types of motivation) when children are followed up one-year later, and second to examine longitudinally whether changes in one model variable predict changes in other variables, according to the hypothesized pathways in the model. A sample of 361 Spanish students (50.7% girls, 8–11 years old) voluntarily participated in this study. In relation to the first aim, structural equation modeling revealed the expected positive relationship between the model variables in both measurement times. That is: actual motor competence (MC) predicted physical activity (PA) (p < .001), perceived MC mediated the relationship between actual MC and PA (p < .001), and autonomous motivation mediated the relationship between perceived MC and PA (p < .05). Moreover, the comparison of the invariance analysis showed non-practical differences between the unconstrained model and the constrained model, supporting the stability of the model over time. In relation to the second aim, the hypothesized model in Time 2 controlling for Time 1 values showed that changes in children’s actual MC positively predicted changes in their perceived MC (p < .001), which in turn, predicted changes in their autonomous motivation (p < .001), and PA (p < .001) at Time 2. Based on these findings Physical Education teachers are recommended to foster children’s actual and perceived MC as well as their autonomous motivation over time in order to promote PA strategies for lifelong health.     

One-year prediction of cognitive decline following cognitive-stimulation from real-world data

Clinical evidence based on real-world data (RWD) is accumulating exponentially providing larger sample sizes available, which demand novel methods to deal with the enhanced heterogeneity of the data. Here, we used RWD to assess the prediction of cognitive decline in a large heterogeneous sample of participants being enrolled with cognitive stimulation, a phenomenon that is of great interest to clinicians but that is riddled with difficulties and limitations. More precisely, from a multitude of neuropsychological Training Materials (TMs), we asked whether was possible to accurately predict an individual's cognitive decline one year after being tested. In particular, we performed longitudinal modelling of the scores obtained from 215 different tests, grouped into 29 cognitive domains, a total of 124,610 instances from 7902 participants (40% male, 46% female, 14% not indicated), each performing an average of 16 tests. Employing a machine learning approach based on ROC analysis and cross-validation techniques to overcome overfitting, we show that different TMs belonging to several cognitive domains can accurately predict cognitive decline, while other domains perform poorly, suggesting that the ability to predict decline one year later is not specific to any particular domain, but is rather widely distributed across domains. Moreover, when addressing the same problem between individuals with a common diagnosed label, we found that some domains had more accurate classification for conditions such as Parkinson's disease and Down syndrome, whereas they are less accurate for Alzheimer's disease or multiple sclerosis. Future research should combine similar approaches to ours with standard neuropsychological measurements to enhance interpretability and the possibility of generalizing across different cohorts.     

Mixture-modelling-based Bayesian MH-RM algorithm for the multidimensional 4PLM

Several recent works have tackled the estimation issue for the unidimensional four-parameter logistic model (4PLM). Despite these efforts, the issue remains a challenge for the multidimensional 4PLM (M4PLM). Fu et al. (2021) proposed a Gibbs sampler for the M4PLM, but it is time-consuming. In this paper, a mixture-modelling-based Bayesian MH-RM (MM-MH-RM) algorithm is proposed for the M4PLM to obtain the maximum a posteriori (MAP) estimates. In a comparison of the MM-MH-RM algorithm to the original MH-RM algorithm, two simulation studies and an empirical example demonstrated that the MM-MH-RM algorithm possessed the benefits of the mixture-modelling approach and could produce more robust estimates with guaranteed convergence rates and fast computation. The MATLAB codes for the MM-MH-RM algorithm are available in the online appendix.