The AHA! experience: creativity through emergent binding in neural networks

Many kinds of creativity result from combination of mental representations. This paper provides a computational account of how creative thinking can arise from combining neural patterns into ones that are potentially novel and useful. We defend the hypothesis that such combinations arise from mechanisms that bind together neural activity by a process of convolution, a mathematical operation that interweaves structures. We describe computer simulations that show the feasibility of using convolution to produce emergent patterns of neural activity that can support cognitive and emotional processes underlying human creativity.     

Perceiving the Present: Systematization of Illusions or Illusion of Systematization?

Mark Changizi et al. (2008) claim that it is possible systematically to organize more than 50 kinds of illusions in a 7 × 4 matrix of 28 classes. This systematization, they further maintain, can be explained by the operation of a single visual processing latency correction mechanism that they call “perceiving the present” (PTP). This brief report raises some concerns about the way a number of illusions are classified by the proposed systematization. It also poses two general problems—one empirical and one conceptual—for the PTP approach.     

Effects of Attention on the Strength of Lexical Influences on Speech Perception: Behavioral Experiments and Computational Mechanisms

The effects of lexical context on phonological processing are pervasive and there have been indications that such effects may be modulated by attention. However, attentional modulation in speech processing is neither well documented nor well understood. Experiment 1 demonstrated attentional modulation of lexical facilitation of speech sound recognition when task and critical stimuli were identical across attention conditions. We propose modulation of lexical activation as a neurophysiologically plausible computational mechanism that can account for this type of modulation. Contrary to the claims of critics, this mechanism can account for attentional modulation without violating the principle of interactive processing. Simulations of the interactive TRACE model extended to include two different ways of modulating lexical activation showed that each can account for attentional modulation of lexical feedback effects. Experiment 2 tested conflicting predictions from the two implementations and provided evidence that is consistent with bias input as the mechanism of attentional control of lexical activation.     

Perceiving the present and a systematization of illusions

Over the history of the study of visual perception there has been great success at discovering countless visual illusions. There has been less success in organizing the overwhelming variety of illusions into empirical generalizations (much less explaining them all via a unifying theory). Here, this article shows that it is possible to systematically organize more than 50 kinds of illusion into a 7 × 4 matrix of 28 classes. In particular, this article demonstrates that (1) smaller sizes, (2) slower speeds, (3) greater luminance contrast, (4) farther distance, (5) lower eccentricity, (6) greater proximity to the vanishing point, and (7) greater proximity to the focus of expansion all tend to have similar perceptual effects, namely, to (A) increase perceived size, (B) increase perceived speed, (C) decrease perceived luminance contrast, and (D) decrease perceived distance. The detection of these empirical regularities was motivated by a hypothesis, called "perceiving the present," that the visual system possesses mechanisms for compensating neural delay during forward motion. This article shows how this hypothesis predicts the empirical regularity.     

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.     

Why there are no good arguments for any interesting version of determinism

This paper considers the empirical evidence that we currently have for various kinds of determinism that might be relevant to the thesis that human beings possess libertarian free will. Libertarianism requires a very strong version of indeterminism, so it can be refuted not just by universal determinism, but by some much weaker theses as well. However, it is argued that at present, we have no good reason to believe even these weak deterministic views and, hence, no good reason—at least from this quarter—to doubt that we are libertarian free. In particular, the paper responds to various arguments for neural and psychological determinism, arguments based on the work of people like Honderich, Tegmark, Libet, Velmans, Wegner, and Festinger.     

Current status of the motor program: Revisited

The motor program is a concept that has had a major influence on theorizing in the field of motor control. However, there has been a lack of consensus as to what exactly is a motor program and its role in movement organization and execution. In 1994 Morris, Summers, Matyas, and Iansek concluded from a review of the application of the motor program concept in the field of physical therapy that continued use of the term may impede progress in the field. In this paper we examine what has happened to the motor program concept in the thirteen years since the previous evaluation. The review indicates that although the term is still being used in different ways, the theoretical existence of a motor program appears to be generally accepted by researchers in experimental psychology, movement science, and neurophysiology. The recent development of powerful brain imaging techniques may allow determination of whether the motor program should be regarded as a metaphorical or literal concept.     

RBF神经网络在股价预测中的应用

提出了一种基于RBF神经网络的股票价格预测模型。该模型通过对历史股价数据的分析,采用K-均值聚类算法动态确定RBF网络中心,根据梯度下降法进行自适应权值调整。并且根据股价的差异大,时变性强和高度非线性的特点,对RBF网络的学习算法进行了改进,进一步提高了RBF网络的非线性映射能力和自适应能力,最后运用该模型对股票走势进行了预测。     

情绪智力的基础：情绪觉察的研究现状与展望

情绪觉察作为情绪智力的重要基础,指的是识别与描述自己和他人情绪的能力,对个体的心理健康,人际交往具有重要意义。为系统考察情绪觉察的研究现状,采用定性和定量相结合的方式回顾以往研究,即先采用文献计量学的方法定量分析该领域研究的概况,然后在此基础上,对研究的具体内容从概念界定、测量工具、神经基础、相关因素和干预研究五个方面作进一步系统梳理。最后,对以往研究进行了总结和展望,以期为今后研究提供借鉴。