Individual Differences in the Encoding Processes of Egocentric and Allocentric Survey Knowledge

This study examined how different components of working memory are involved in the acquisition of egocentric and allocentric survey knowledge by people with a good and poor sense of direction (SOD). We employed a dual‐task method and asked participants to learn routes from videos with verbal, visual, and spatial interference tasks and without any interference. Results showed that people with a good SOD encoded and integrated knowledge about landmarks and routes into egocentric survey knowledge in verbal and spatial working memory, which is then transformed into allocentric survey knowledge with the support of all three components, distances being processed in verbal and spatial working memory and directions in visual and spatial working memory. In contrast, people with a poor SOD relied on verbal working memory and lacked spatial processing, thus failing to acquire accurate survey knowledge. Based on the results, a possible model for explaining individual differences in spatial knowledge acquisition is proposed.     

The 36th Sir Frederick Bartlett Lecture: An associative analysis of spatial learning

The ability of animals to find important goals in their environment has been said to require a form of learning that is qualitatively different from that normally studied in the conditioning laboratory. Such spatial learning has been said to depend upon the construction of a global representation of the environment, and the acquisition of knowledge about the position of goals with reference to this representation is said to be unaffected by the presence of other cues or landmarks. To evaluate the first of these claims, experiments are described that investigated the extent to which the effects of training in one environment transfer to another. To evaluate the second claim, experiments are described that investigated whether cue competition effects normally found in conditioning studies can be found in spatial tasks. Overall, the results indicate that most of the phenomena of spatial learning can be explained by the principles of associative learning. The implications of the reported results for an understanding of the neural mechanisms of spatial learning are considered.     

Grounding Bayesian accounts of numerosity and variability effects in a similarity-based framework: the case of self-organising maps

ABSTRACT

In this paper, we propose self-organising maps as possible candidates to explain the psychological mechanisms underlying category generalisation. Self-organising maps are psychologically and biologically plausible neural network models that can learn after limited exposure to positive category examples, without any need of contrastive information. They reproduce human behaviour in category generalisation, in particular, the Numerosity and Variability effects, which are usually explained with Bayesian tools. Where category generalisation is concerned, self-organising maps deserve attention to bridge the gap between the computational level of analysis in Marr's hierarchy (where Bayesian models are often situated) and the algorithmic level of analysis in which plausible mechanisms are described.     

Review

Book reviewed in this article:
David Ray Griffin, Religion and Scientific Naturalism: Overcoming the Conflicts     

An evolutionary function of the depressive reaction: the cognitive map hypothesis

Existing hypotheses for an evolutionary function of depression are insufficient, primarily because they fail to show convincingly the advantages that might compensate for the high evolutionary costs of its features, such as general passivity, decreased appetite and sex drive.In this article, it is shown that depression may have the function of motivating a period of reduced activity after a major loss. It thus allows for time out to update the cognitive structures for altered circumstances, and avoids dangerous actions based on the use of inadequate cognitive maps. This cognitive map hypothesis provides a viable evolutionary explanation for the high incidence of depression reaction, in spite of its apparently unfavorable characteristics. The article discusses how this hypothesis may also shed light on the occurrence of clinical depression, proposing that it is caused by a failure to update complex conceptual cognitive structures. Finally, recommendations for the treatment of depression that derive from this hypothesis are presented.     

Model-based recursive partitioning of extended redundancy analysis with an application to nicotine dependence among US adults

Extended redundancy analysis (ERA) is used to reduce multiple sets of predictors to a smaller number of components and examine the effects of these components on a response variable. In various social and behavioural studies, auxiliary covariates (e.g., gender, ethnicity) can often lead to heterogeneous subgroups of observations, each of which involves distinctive relationships between predictor and response variables. ERA is currently unable to consider such covariate-dependent heterogeneity to examine whether the model parameters vary across subgroups differentiated by covariates. To address this issue, we combine ERA with model-based recursive partitioning in a single framework. This combined method, MOB-ERA, aims to partition observations into heterogeneous subgroups recursively based on a set of covariates while fitting a specified ERA model to data. Upon the completion of the partitioning procedure, one can easily examine the difference in the estimated ERA parameters across covariate-dependent subgroups. Moreover, it produces a tree diagram that aids in visualizing a hierarchy of partitioning covariates, as well as interpreting their interactions. In the analysis of public data concerning nicotine dependence among US adults, the method uncovered heterogeneous subgroups characterized by several sociodemographic covariates, each of which yielded different directional relationships between three predictor sets and nicotine dependence.     

Linking property crime using offender crime scene behaviour: A comparison of methods

This study compared the ability of seven statistical models to distinguish between linked and unlinked crimes. The seven models utilised geographical, temporal, and modus operandi information relating to residential burglaries (n = 180), commercial robberies, (n = 118), and car thefts (n = 376). Model performance was assessed using receiver operating characteristic analysis and by examining the success with which the seven models could successfully prioritise linked over unlinked crimes. The regression‐based and probabilistic models achieved comparable accuracy and were generally more accurate than the tree‐based models tested in this study. The Logistic algorithm achieved the highest area under the curve (AUC) for residential burglary (AUC = 0.903) and commercial robbery (AUC = 0.830) and the SimpleLogistic algorithm achieving the highest for car theft (AUC = 0.820). The findings also indicated that discrimination accuracy is maximised (in some situations) if behavioural domains are utilised rather than individual crime scene behaviours and that the AUC should not be used as the sole measure of accuracy in behavioural crime linkage research.     

应用决策树探讨中国当代大学生情感素质下属各情感的相互关系

为深入了解大学生情感素质及其下属情感的相互关系,本文在已有全国大学生情感素质调查的基础上,利用决策树算法对大学生的情感素质及其下属情感(道德情感、生活情感、情绪智力)进行预测分类。结果表明:(1)决策树可以有效地对大学生情感素质下属各情感进行预测分类;(2)按属性重要性提取规则,道德情感对情感素质影响最大,生活情感次之;责任感对道德情感影响较大;自强感对生活情感有较强影响;理解他人情绪能力对情绪智力的影响较大。