真实线和想象线的朝向辨别学习及其相互迁移

以往的朝向辨别学习普遍采用真实刺激作为材料,其特异性与迁移性是研究争论的焦点之一。该研究以实线和想象线为刺激,采用朝向辨别任务训练被试,系统考察两者朝向辨别学习的特点和相互关系。结果发现,训练实线和想象线任务的两组被试行为都有显著提高,并且这两种学习效果能部分地彼此迁移,且都能迁移到不同位置。该研究结果提示,不论是想象线的学习还是实线的学习都涉及高级脑区的参与,并且两者的学习有部分共同的脑机制。     

视觉系统中类别信息加工区的特异性

近年来, 神经成像的研究结果显示, 在人类的腹侧视觉皮层内可能存在与特定类别刺激加工一一对应的类别信息加工区。但是, 类别信息加工区是否具有特异性仍然存在争议。文章总结了相关研究领域对这一颇具争议的问题的研究结果, 同时指出了末来研究可能深入的方向。这些方向包括：进一步探讨不同抽象水平的类别信息加工区域的特异性问题、检验类别信息加工区的拓扑分布观点、回答不同类别信息加工区之间的信息如何交流的问题、揭示类别信息加工区的学习机制。     

急性心理性应激诱发的神经内分泌反应及其影响因素

急性心理性应激源分别通过下丘脑-脑垂体-肾上腺轴(hypothalamus–pituitary–adrenal axis,HPAA)和交感神经-肾上腺髓质轴(sympathetic-adrenal medulla axis)诱发神经内分泌反应。唾液皮质醇被认为是检测急性心理性应激所诱发的HPA轴反应的稳定指标。以特里尔社会应激测试(Trier Social Stress Test,TSST)及其变式作为应激源, 以HPA轴的反应作为应激指标, 影响个体在急性心理性应激情境中发生特异性神经内分泌反应的因素主要包括人口统计学、环境和应激频率三大方面, 未来应加强急性心理性应激所诱发的神经内分泌反应的纵向研究。     

Creating cluster‐specific purchase profiles from point‐of‐sale scanner data and geodemographic clusters: improving category management at a major US grocery chain

In the retail grocery industry, category management is the process of managing categories of products for greater profitability and customer value. Category management is a data‐driven process and, as a result, can benefit from point‐of‐sale (POS) scanner data. This paper describes the results of a one‐year project that shows how to use POS scanner data and geodemographic clusters to improve the practice of category management at Price Chopper, a large US grocery chain. The paper demonstrates how to merge POS scanner data with geodemographic clusters to create detailed purchase profiles that provide valuable information to category managers. It also discusses the trials and tribulations of using scanner data and provides several findings as implications (eg store‐specific promotions should be more effective than chain‐wide promotions for stores servicing a small number of geodemographic clusters with distinct shopping profiles) that supermarket managers can immediately use to improve existing promotional strategies. The paper's contents should be relevant to academicians and practitioners interested in improving the practice of category management in the UK, USA, Western Europe and Australia. Copyright © 2004 Henry Stewart Publications.     

Mind and Miracles

Miracles are real or imagined events that contradict our intuitive expectations of how entities normally behave. Miracles in the weak sense are unexplained counterintuitive events. Miracles in the strong sense are counterintuitive events we explain by referring to the counterintuitive agents and forces of various religious traditions. Such explanations result from the fact that our minds treat half–understood information by carrying out searches in the memory, trying to connect new information with something already known. This is cognitively the most economical way of dealing with new information: we obtain the maximum of relevance at minimal processing cost.     

View-invariant object category learning, recognition, and search: how spatial and object attention are coordinated using surface-based attentional shrouds

How does the brain learn to recognize an object from multiple viewpoints while scanning a scene with eye movements? How does the brain avoid the problem of erroneously classifying parts of different objects together? How are attention and eye movements intelligently coordinated to facilitate object learning? A neural model provides a unified mechanistic explanation of how spatial and object attention work together to search a scene and learn what is in it. The ARTSCAN model predicts how an object's surface representation generates a form-fitting distribution of spatial attention, or "attentional shroud". All surface representations dynamically compete for spatial attention to form a shroud. The winning shroud persists during active scanning of the object. The shroud maintains sustained activity of an emerging view-invariant category representation while multiple view-specific category representations are learned and are linked through associative learning to the view-invariant object category. The shroud also helps to restrict scanning eye movements to salient features on the attended object. Object attention plays a role in controlling and stabilizing the learning of view-specific object categories. Spatial attention hereby coordinates the deployment of object attention during object category learning. Shroud collapse releases a reset signal that inhibits the active view-invariant category in the What cortical processing stream. Then a new shroud, corresponding to a different object, forms in the Where cortical processing stream, and search using attention shifts and eye movements continues to learn new objects throughout a scene. The model mechanistically clarifies basic properties of attention shifts (engage, move, disengage) and inhibition of return. It simulates human reaction time data about object-based spatial attention shifts, and learns with 98.1% accuracy and a compression of 430 on a letter database whose letters vary in size, position, and orientation. The model provides a powerful framework for unifying many data about spatial and object attention, and their interactions during perception, cognition, and action.     

Learning How to Generalize

Generalization is a fundamental problem solved by every cognitive system in essentially every domain. Although it is known that how people generalize varies in complex ways depending on the context or domain, it is an open question how people learn the appropriate way to generalize for a new context. To understand this capability, we cast the problem of learning how to generalize as a problem of learning the appropriate hypothesis space for generalization. We propose a normative mathematical framework for learning how to generalize by learning inductive biases for which properties are relevant for generalization in a domain from the statistical structure of features and concepts observed in that domain. More formally, the framework predicts that an ideal learner should learn to generalize by either taking the weighted average of the results of generalizing according to each hypothesis space, with weights given by how well each hypothesis space fits the previously observed concepts, or by using the most likely hypothesis space. We compare the predictions of this framework to human generalization behavior with three experiments in one perceptual (rectangles) and two conceptual (animals and numbers) domains. Across all three studies we find support for the framework's predictions, including individual‐level support for averaging in the third study.     

Do Additional Features Help or Hurt Category Learning? The Curse of Dimensionality in Human Learners

The curse of dimensionality, which has been widely studied in statistics and machine learning, occurs when additional features cause the size of the feature space to grow so quickly that learning classification rules becomes increasingly difficult. How do people overcome the curse of dimensionality when acquiring real‐world categories that have many different features? Here we investigate the possibility that the structure of categories can help. We show that when categories follow a family resemblance structure, people are unaffected by the presence of additional features in learning. However, when categories are based on a single feature, they fall prey to the curse, and having additional irrelevant features hurts performance. We compare and contrast these results to three different computational models to show that a model with limited computational capacity best captures human performance across almost all of the conditions in both experiments.     

Children's suggestibility for an instance of a repeated event versus a unique event: the effect of degree of association between variable details

Are children who experience an event repeatedly more suggestible about an instance of the event than children who experience it once? Researchers have answered this question both in the affirmative and in the negative. In this study, we hypothesized that the degree of association between details that changed across instantiations of the event would help to explain the discrepancy. Preschoolers (4- and 5-year-olds) and first graders (6- and 7-year-olds) participated in either a single play session or four repeated play sessions, each of which contained 16 critical details. Across play sessions in the repeat-event condition, half of the critical details were associated and half were not associated. During a biasing interview 2 weeks later, children were misinformed about half of the critical details. The next day, children answered free and cued recall questions about the target play session. Among older children, repeat-event participants were more suggestible than single-event participants, especially for high-association details. Among younger children, repeat-event participants were more suggestible than single-event participants for low-association details. Consistent with some current theories of children's memory, older children were more suggestible than younger children.     

What's in a name? Typicality and relatedness effects in children

We studied how category typicality and out-of-category relatedness affect speeded category verification (vote "yes" if pictured object is clothing) in typically developing 4- to 14-year-olds and adults. Stimuli were typical and atypical category objects (e.g., pants, glove) and related and unrelated out-of-category objects (e.g., necklace, soup). Typical and unrelated out-of-category objects exhibited preferential processing (faster reaction times and fewer errors). Variations in typicality and relatedness disproportionately influenced children's performance, with developmental improvement associated with both verbal and nonverbal factors. Underextension versus overextension errors seemed to be associated with independent factors, namely multifaceted maturational factors versus receptive vocabulary skill, respectively. Errors were infrequent, suggesting spontaneous taxonomic classification by all participants. An experiment with printed words in adults replicated results, indicating that typicality and relatedness effects reflected organizational principles of the semantic system, not picture-related processes. This research establishes the viability of an online approach to assessing automatic components of semantic organization in children.