Who do students with mild disabilities nominate as cool in inclusive general education classrooms?

Examined the nominations that elementary students with mild disabilities made for peers they perceived as cool. The total sample was comprised of 948 students (496 girls, 452 boys) from the metropolitan Chicago area and North Carolina and included 107 (11.3%) students with mild disabilities. Overall, students with mild disabilities nominated prosocial and athletic peers who affiliate with students with mild disabilities. However, aggressive boys who are central in the social network were highly likely to view aggressive peers as cool. Results are discussed in relation to implications for social interventions for students with mild disabilities.     

Memory Maintenance

ABSTRACT— Change in the synaptic communication between neurons—known as synaptic plasticity—plays a key role in learning and memory. It is not yet clear, however, whether the properties of synaptic plasticity are sufficient to account for long-term-memory maintenance. Recent studies have revealed that synaptic plasticity can indeed persist for weeks or months, as might be expected of a long-term-memory mechanism. However, memories encoded by neural systems are not static; they continue to evolve as new learning occurs. Furthermore, neural-network modeling has shown that synapses must be able to reconfigure their connection strengths during new learning if old information is to be preserved. Recent tests confirm that synapses, once modified, retain their capacity for further modification, indicating that they can indeed operate in the manner predicted to be necessary for memory maintenance in a dynamic learning network.     

Are unsupervised neural networks ignorant? Sizing the effect of environmental distributions on unsupervised learning

Learning environmental biases is a rational behavior: by using prior odds, Bayesian networks rapidly became a benchmark in machine learning. Moreover, a growing body of evidence now suggests that humans are using base rate information. Unsupervised connectionist networks are used in computer science for machine learning and in psychology to model human cognition, but it is unclear whether they are sensitive to prior odds. In this paper, we show that hard competitive learners are unable to use environmental biases while recurrent associative memories use frequency of exemplars and categories independently. Hence, it is concluded that recurrent associative memories are more useful than hard competitive networks to model human cognition and have a higher potential in machine learning.     

成败情境下不同目标取向学生内在动机特点

以213名小学生为被试,设置成功和失败情境,考察三种成就目标取向学生内在动机的差异。结果发现:两种情境下,掌握目标的学生均有最高的内在动机;失败情境下,成绩接近目标学生的内在动机显著高于成绩回避目标的学生,但成功情境下,两种目标取向学生的内在动机没有显著差异;掌握目标学生在两种情境下的内在动机无显著差异;成绩接近和成绩回避目标学生在失败情境下的内在动机显著低于成功情境下的内在动机。     

Semantic boost on episodic associations: an empirically-based computational model

Words become associated following repeated co-occurrence episodes. This process might be further determined by the semantic characteristics of the words. The present study focused on how semantic and episodic factors interact in incidental formation of word associations. First, we found that human participants associate semantically related words more easily than unrelated words; this advantage increased linearly with repeated co-occurrence. Second, we developed a computational model, SEMANT, suggesting a possible mechanism for this semantic-episodic interaction. In SEMANT, episodic associations are implemented through lateral connections between nodes in a pre-existent self-organized map of word semantics. These connections are strengthened at each instance of concomitant activation, proportionally with the amount of the overlapping activity waves of activated nodes. In computer simulations SEMANT replicated the dynamics of associative learning in humans and led to testable predictions concerning normal associative learning as well as impaired learning in a diffuse semantic system like that characteristic of schizophrenia.     

Dynamic self-organization and early lexical development in children

In this study we present a self-organizing connectionist model of early lexical development. We call this model DevLex-II, based on the earlier DevLex model. DevLex-II can simulate a variety of empirical patterns in children's acquisition of words. These include a clear vocabulary spurt, effects of word frequency and length on age of acquisition, and individual differences as a function of phonological short-term memory and associative capacity. Further results from lesioned models indicate developmental plasticity in the network's recovery from damage, in a non-monotonic fashion. We attribute the network's abilities in accounting for lexical development to interactive dynamics in the learning process. In particular, variations displayed by the model in the rate and size of early vocabulary development are modulated by (a) input characteristics, such as word frequency and word length, (b) consolidation of lexical-semantic representation, meaning-form association, and phonological short-term memory, and (c) delayed processes due to interactions among timing, severity, and recoverability of lesion. Together, DevLex and DevLex-II provide an accurate computational account of early lexical development.     

Autoshaping and automaintenance: a neural-network approach

This article presents an interpretation of autoshaping, and positive and negative automaintenance, based on a neural-network model. The model makes no distinction between operant and respondent learning mechanisms, and takes into account knowledge of hippocampal and dopaminergic systems. Four simulations were run, each one using an A-B-A design and four instances of feedfoward architectures. In A, networks received a positive contingency between inputs that simulated a conditioned stimulus (CS) and an input that simulated an unconditioned stimulus (US). Responding was simulated as an output activation that was neither elicited by nor required for the US. B was an omission-training procedure. Response directedness was defined as sensory feedback from responding, simulated as a dependence of other inputs on responding. In Simulation 1, the phenomena were simulated with a fully connected architecture and maximally intense response feedback. The other simulations used a partially connected architecture without competition between CS and response feedback. In Simulation 2, a maximally intense feedback resulted in substantial autoshaping and automaintenance. In Simulation 3, eliminating response feedback interfered substantially with autoshaping and automaintenance. In Simulation 4, intermediate autoshaping and automaintenance resulted from an intermediate response feedback. Implications for the operant-respondent distinction and the behavior-neuroscience relation are discussed.     

A causal model theory of the meaning of cause, enable, and prevent

The verbs cause , enable , and prevent express beliefs about the way the world works. We offer a theory of their meaning in terms of the structure of those beliefs expressed using qualitative properties of causal models, a graphical framework for representing causal structure. We propose that these verbs refer to a causal model relevant to a discourse and that "A causes B" expresses the belief that the causal model includes a link from A to B. "A enables/allows B" entails that the model includes a link from A to B, that A represents a category of events necessary for B, and that an alternative cause of B exists. "A prevents B" entails that the model includes a link from A to B and that A reduces the likelihood of B. This theory is able to account for the results of four experiments as well as a variety of existing data on human reasoning.     

应当重视肿瘤微环境中外因的研究

长期以来,肿瘤学的几乎所有研究一直在关注肿瘤细胞本身,从哲学角度看这无疑是正确的。肿瘤细胞是肿瘤事件发生发展的内因。近年研究表明,肿瘤的外因,即肿瘤微环境中的非肿瘤细胞及其产物,对肿瘤的发生发展起着十分重要的作用。肿瘤微环境的外因,通过作用于内因选择了更具抵抗性的肿瘤细胞,促进了肿瘤的进展与转移。因此,重视肿瘤微环境的外因研究,对肿瘤治疗学将会开辟以外因为靶点干预的新思路。     

When linking is stronger than thinking: Associative transfer of valence disrupts the emergence of cognitive balance after attitude change

The present research investigated the role of cognitive balance vs. associative transfer of valence in attitude change. Participants first formed positive or negative attitudes toward several source individuals. Subsequently, participants were shown source–target pairs along with information about the source–target relationship (‘likes’/‘dislikes’). Afterwards, participants’ attitudes toward the sources were changed by means of information that was opposite to the initially induced attitude. In a control condition, initial source attitudes remained unqualified. Results in the control condition showed that initially formed attitudes and available relationship information produced target evaluations that were consistent with the notion of cognitive balance. However, when attitudes toward the sources changed, target evaluations directly matched attitudes toward individually associated sources, irrespective of the relation between source and target. These results suggest that associative transfer of valence can disrupt the emergence of cognitive balance after attitude change.