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.     

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.     

A computational model of Parkinsonian handwriting that highlights the role of the indirect pathway in the basal ganglia

Parkinsonian handwriting is typically characterized by micrographia, jagged line contour, and unusual fluctuations in pen velocity. In this paper we present a computational model of handwriting generation that highlights the role of the basal ganglia, particularly the indirect pathway. Whereas reduced dopamine levels resulted in reduced letter size, transition of STN–GPe dynamics from desynchronized (normal) to synchronized (PD) condition resulted in increased fluctuations in velocity in the model. We also present handwriting data from PD patients (n = 34) who are at various stages of disease and had taken medication various lengths of time before the handwriting sessions. The patient data are compared with those of age-matched controls. PD handwriting statistically exhibited smaller size and larger velocity fluctuation compared to normal handwriting.     

发展性口吃的脑机制

口吃是一种常见的言语障碍,对此曾提出过大脑半球言语功能偏侧化异常假设。近期,发展性口吃的神经成像研究在支持这一经典假设的同时,还发现负责言语监控的颞叶系统和负责言语运动控制的额叶系统与皮层下脑结构存在功能失调,这可能损害言语产生时的精确时间控制。据此,研究者开始用神经网络的观点来解释发展性口吃产生的脑机制,认为患者可能存在由多个言语产生相关脑区构成的“双通路”网络的功能障碍     

Conceptualizing ‘social capital’ for health promotion in small local communities: a micro‐qualitative study

This paper reports on a micro‐qualitative case study of peoples' experiences of local community life in a south‐east English town. This material is used as the basis for a critical discussion of the suitability of Putnam's notion of social capital as a conceptual tool for the design and evaluation of ‘community strengthening’ policies and interventions. The study was motivated by a concern that too much debate about social capital has been conducted by academics and policy‐makers in a top‐down manner, with inadequate attention to the realities of life in the local communities that they refer to. Three‐hour semi‐structured interviews were conducted with 37 residents in two less affluent wards in our town of interest. Informants—half men and half women, and spread across the 15–75 age group—were encouraged to talk about their personal experiences of local community life. Interview findings are presented within the ‘norm’ categories of trust, neighbourliness and reciprocal help and support, and the ‘network’ categories of participation in informal networks, voluntary groupings and community activist groupings. Our case study points to a number of ways in which Putnam's concept needs to be refined if it is to inform ‘community strengthening’ policies and interventions in England. Far more notice needs to be taken of the role played by informal networks of friends and neighbours in the construction of local community life. Attention also needs to be given to the complex and shifting geographical spread of peoples' significant social networks. Putnam's conceptualization of cohesive local communities and his unitary notions of trust and local identity may also be unduly essentialist. In our particular communities of interest, they failed to capture the fluidity of local community norms and networks in a rapidly changing society. They also failed to do justice to the extent to which social distinctions—such as age, gender, ethnicity and housing tenure—shape and constrain the way in which people create, sustain and access social capital. Copyright © 2001 John Wiley & Sons, Ltd.     

The ghost of Christmas future: didn't Scrooge learn to be good? Commentary on Magnuson,McMurray, Tanenhaus,and Aslin (2003)

Magnuson, McMurray, Tanenhaus, and Aslin [Cogn. Sci. 27 (2003) 285] suggest that they have evidence of lexical feedback in speech perception, and that this evidence thus challenges the purely feedforward Merge model [Behav. Brain Sci. 23 (2000) 299]. This evidence is open to an alternative explanation, however, one which preserves the assumption in Merge that there is no lexical–prelexical feedback during on‐line speech processing. This explanation invokes the distinction between perceptual processing that occurs in the short term, as an utterance is heard, and processing that occurs over the longer term, for perceptual learning.     

A visual auditory model based on Growing Self-Organizing Maps to analyze the taxonomic response in early childhood

In this paper we present an extension of a visual auditory neural network model previously proposed by Mayor and Plunkett (2010) in order to explain the emergence of the taxonomic response in early childhood. The original model consists of two self-organizing maps (respectively, visual and acoustic) connected with Hebbian connections. With respect to the original model, our proposal adds two major features. First, our model follows a dynamic training regime, learning categories and word-object associations that evolve through time. Second, the visual and acoustic maps are Growing self-organizing maps that grow during training, when they are no longer able to consistently represent categories. With these two new characterizing features, our model replicates the performance of the original Mayor and Plunkett (2010)’s model, acquires psychological plausibility in the training regime, and avoids the risk of catastrophic interference.