Attentional cueing induces false memory

The fluency of stimulus processing significantly contributes to recognition memory judgments. We investigated the effect of processing fluency induced by attentional cueing on recognition judgments. Participants performed a Remember/Know recognition test, while their spatial attention was manipulated in the test session. Stimulus location was either predicted (congruent condition) or unpredicted (incongruent condition) using an arrow cue. The results revealed that familiarity-based false recognition increased in the incongruent condition wherein the participants may have attributed part of the perceived disfluency to the attentional cue, and they may have overestimated the fluency for the stimulus, leading to increased false recognition. However, in the congruent condition, the participants may have attributed some parts of the perceived fluency to the attentional cue and underestimated the fluency for the stimulus, leading to decreased false recognition. In sum, stimulus-irrelevant attentional cueing induces unintentional processing about the source of fluency and biases recognition memory.     

A method of optimal scaling for multivariate ordinal data and its extensions

This paper develops a method of optimal scaling for multivariate ordinal data, in the framework of a generalized principal component analysis. This method yields a multidimensional configuration of items, a unidimensional scale of category weights for each item and, optionally, a multidimensional configuration of subjects. The computation is performed by alternately solving an eigenvalue problem and executing a quasi-Newton projection method. The algorithm is extended for analysis of data with mixed measurement levels or for analysis with a combined weighting of items. Numerical examples and simulations are provided. The algorithm is discussed and compared with some related methods.Earlier results of this research appeared in Saito and Otsu (1983). The authors would like to acknowledge the helpful comments and encouragement of the editor.     

Parallel distributed processing and neuropsychology: A neural network model of Wisconsin card sorting and verbal fluency

Neural networks can be used as a tool in the explanation of neuropsychological data. Using the Hebbian Learning Rule and other such principles as competition and modifiable interlevel feedback, researchers have successfully modeled a widely used neuropsychological test, the Wisconsin Card Sorting Test. One of these models is reviewed here and extended to a qualitative analysis of how verbal fluency might be modeled, which demonstrates the importance of accounting for the attentional components of both tests. Difficulties remain in programming sequential cognitive processes within a parallel distributed processing (PDP) framework and integrating exceedingly complex neuropsychological tests such as Proverbs. PDP neural network methodology offers neuropsychologists co-validation procedures within narrowly defined areas of reliability and validity.     

Penalized optimal scaling for ordinal variables with an application to international classification of functioning core sets

Ordinal data occur frequently in the social sciences. When applying principal component analysis (PCA), however, those data are often treated as numeric, implying linear relationships between the variables at hand; alternatively, non-linear PCA is applied where the obtained quantifications are sometimes hard to interpret. Non-linear PCA for categorical data, also called optimal scoring/scaling, constructs new variables by assigning numerical values to categories such that the proportion of variance in those new variables that is explained by a predefined number of principal components (PCs) is maximized. We propose a penalized version of non-linear PCA for ordinal variables that is a smoothed intermediate between standard PCA on category labels and non-linear PCA as used so far. The new approach is by no means limited to monotonic effects and offers both better interpretability of the non-linear transformation of the category labels and better performance on validation data than unpenalized non-linear PCA and/or standard linear PCA. In particular, an application of penalized optimal scaling to ordinal data as given with the International Classification of Functioning, Disability and Health (ICF) is provided.     

A review of behavioral procedures to teach motor skills to individuals with severe disabilities

Behavioral procedures are one approach to teaching or improving the fluency of motor skills of individuals with severe disabilities. This article provides a review of behavioral procedures by highlighting antecedents, consequences, and multifaceted techniques. Investigations are reviewed in each area according to (a) replicability of the intervention, (b) experimental control, (c) maintenance, (d) generalization, and (e) social validation. Practitioner implications address selection of reinforcers, reinforcement schedules, and teaching within meaningful routines. Future research recommendations highlight the need for documenting that stimuli are actually reinforcers. Additional research needs emphasize targeting maintenance, generalization, and social validation.     

Social networks with two sets of actors

Traditional network research analyzes relational ties within a single group of actors: the models presented in this paper involve relational ties exist beteen two distinct sets of actors. Statistical models for traditional networks in which relations are measured within a group simplify when modeling unidirectional relations measured between groups. The traditional paradigm results in a one-mode socionatrix; the network paradigm considered in this paper results in a two-mode socionatrix; A statistical model is presented, illustrated on a sample data set, and compared to its traditional counterpart. Extensions are discussed, including those that model multivariate relations simultaneously, and those that allow for the inclustion of attributes of the individuals in the group.We thank the Editor and two anonymous reviewers for their helpful comments. We are also grateful to George Barnett for allowing us to analyze his data.     

Linguistic Distributional Knowledge and Sensorimotor Grounding both Contribute to Semantic Category Production

The human conceptual system comprises simulated information of sensorimotor experience and linguistic distributional information of how words are used in language. Moreover, the linguistic shortcut hypothesis predicts that people will use computationally cheaper linguistic distributional information where it is sufficient to inform a task response. In a pre-registered category production study, we asked participants to verbally name members of concrete and abstract categories and tested whether performance could be predicted by a novel measure of sensorimotor similarity (based on an 11-dimensional representation of sensorimotor strength) and linguistic proximity (based on word co-occurrence derived from a large corpus). As predicted, both measures predicted the order and frequency of category production but, critically, linguistic proximity had an effect above and beyond sensorimotor similarity. A follow-up study using typicality ratings as an additional predictor found that typicality was often the strongest predictor of category production variables, but it did not subsume sensorimotor and linguistic effects. Finally, we created a novel, fully grounded computational model of conceptual activation during category production, which best approximated typical human performance when conceptual activation was allowed to spread indirectly between concepts, and when candidate category members came from both sensorimotor and linguistic distributional representations. Critically, model performance was indistinguishable from typical human performance. Results support the linguistic shortcut hypothesis in semantic processing and provide strong evidence that both linguistic and grounded representations are inherent to the functioning of the conceptual system. All materials, data, and code are available at https://osf.io/vaq56/ .     

Shared lesion correlates of semantic and letter fluency in post-stroke aphasia

Lesion–symptom mapping studies have reported a temporal versus frontal dissociation between semantic and letter fluency, and mixed evidence regarding the role of white matter. Mass-univariate and multivariate lesion–symptom mapping was used to identify regions associated with semantic and letter fluency deficits in post-stroke aphasia. Multivariate LSM revealed broad networks including underlying white matter, and substantial overlap between both types of fluency, suggesting that semantic fluency and letter fluency largely rely on the same neural system. All data are available on OSF.     

语言范畴可否引起偏侧化颜色范畴知觉？

本研究考查了语言范畴是否会引起偏侧化颜色范畴知觉,并探讨了偏侧化颜色范畴知觉是语言范畴即时分类颜色还是长期与颜色联结的结果。实验中,以测量差别阈限的方法选定的渐变、相邻颜色知觉距离相当的A、B、C、D四种颜色（A、B为绿色,C、D为蓝色）为材料,以色词与颜色重组模式训练被试用4个人造词汇分别命名4种颜色,并让被试在训练前、第一次训练和第八次训练后均完成视觉搜索任务测试。经训练,原范畴内颜色（AB,CD）变成了范畴间颜色,原范畴间颜色（BC）仍为范畴间颜色。结果显示：被试在一次训练后能以新名字区分4种颜色,八次训练后掌握了4种颜色的新名字;在训练前测试中,出现了与蓝绿色相应的偏侧化颜色范畴知觉;在第八次训练后测试中,出现了与习得的语言范畴相应的偏侧化颜色范畴知觉,但在第一次训练后测试中并未出现这一效应。这些结果表明,语言范畴能引起偏侧化颜色范畴知觉,偏侧化颜色范畴知觉是语言范畴长期与颜色联结,而非即时分类颜色的结果。     

偏侧化颜色范畴知觉不依赖于语言?

本研究探讨了偏左脑颜色范畴知觉依赖于语言还是范畴。三组被试分别完成无干扰、语言加工干扰和范畴加工干扰视觉搜索任务。结果发现：无干扰组、语言加工干扰组和范畴加工干扰组的视觉搜索任务中分别出现了偏左脑颜色范畴知觉、左脑劣势颜色范畴知觉和无偏侧化颜色范畴知觉。此结果表明,偏左脑颜色范畴知觉可能主要是语言范畴作为一种范畴对颜色知觉的影响效应,但语言范畴的语言属性也会对颜色知觉产生影响。