A Computational Model of the Simplest Motor Program

A computational procedure (program) is defined to generate control signals for the motoneuron pools of agonist and antagonist muscles that will move a limb segment from one stationary position to another. The program accounts for the ability to move different distances with different inertial loads and for the influence of instructions concerning movement speed and accuracy. These motor commands allow the program to produce EMG patterns as well as force and kinematic trajectories that are consistent with much of the data found in the literature of these movements. The program is premised on the notion that kinematically defined tasks are accomplished by programming commands to the motoneuron pools, based on only a few cognitively recognized kinematic and dynamic features of the task. Most of the features found in EMG and kinematic patterns can be considered consequences of the program's algorithmic procedures rather than specifically planned features of those movements.     

A Systemic Approach to Fetal Loss Following Genetic Testing

Advances in genetic technology challenge couples to make complex life and death decisions about their fetus that have far-reaching practical and emotional consequences. When genetic defects lead to fetal loss, whether by miscarriage, elective interruption, or still birth, it can be a devastating experience with ripple effects on couple and family development. This paper presents a systemic approach to coping and adaptation to fetal loss in the wake of genetic testing. Clinical vignettes illustrate common experiences and present interventions designed to help the individual grieving partners as well as the marriage. thereby strengthening the family fabric at a vulnerable transitional stage.     

A Computational Model of Linguistic Humor in Puns

Humor plays an essential role in human interactions. Precisely what makes something funny, however, remains elusive. While research on natural language understanding has made significant advancements in recent years, there has been little direct integration of humor research with computational models of language understanding. In this paper, we propose two information‐theoretic measures—ambiguity and distinctiveness—derived from a simple model of sentence processing. We test these measures on a set of puns and regular sentences and show that they correlate significantly with human judgments of funniness. Moreover, within a set of puns, the distinctiveness measure distinguishes exceptionally funny puns from mediocre ones. Our work is the first, to our knowledge, to integrate a computational model of general language understanding and humor theory to quantitatively predict humor at a fine‐grained level. We present it as an example of a framework for applying models of language processing to understand higher level linguistic and cognitive phenomena.     

CaMeRa: A Computational Model of Multiple Representations

This research aims to clarify, by constructing and testing a computer simulation, the use of multiple representations in problem solving, focusing on their role in visual reasoning. The model is motivated by extensive experimental evidence in the literature for the features it incorporates, but this article focuses on the system's structure. We illustrate the model's behavior by simulating the cognitive and perceptual processes of an economics expert as he teaches some well-learned economics principles while drawing a graph on a blackboard. Data in the experimental literature and concurrent verbal protocols were used to guide construction of a linked production system and parallel network, CaMeRa (Computation with Multiple Representations), that employs a "Mind's Eye" representation for pictorial information, consisting of a bitmap and associated node-link structures. Propositional list structures are used to represent verbal information and reasoning. Small individual pieces from the different representations are linked on a sequential and temporary basis to form a reasoning and inferencing chain, using visually encoded information recalled to the Mind's Eye from long-term memory and from cues recognized on an external display. CaMeRa, like the expert, uses the diagrammatic and verbal representations to complement one another, thus exploiting the unique advantages of each.     

A Computational Model for the Item‐Based Induction of Construction Networks

According to usage‐based approaches to language acquisition, linguistic knowledge is represented in the form of constructions—form‐meaning pairings—at multiple levels of abstraction and complexity. The emergence of syntactic knowledge is assumed to be a result of the gradual abstraction of lexically specific and item‐based linguistic knowledge. In this article, we explore how the gradual emergence of a network consisting of constructions at varying degrees of complexity can be modeled computationally. Linguistic knowledge is learned by observing natural language utterances in an ambiguous context. To determine meanings of constructions starting from ambiguous contexts, we rely on the principle of cross‐situational learning. While this mechanism has been implemented in several computational models, these models typically focus on learning mappings between words and referents. In contrast, in our model, we show how cross‐situational learning can be applied consistently to learn correspondences between form and meaning beyond such simple correspondences.     

Concepts as Semantic Pointers: A Framework and Computational Model

The reconciliation of theories of concepts based on prototypes, exemplars, and theory‐like structures is a longstanding problem in cognitive science. In response to this problem, researchers have recently tended to adopt either hybrid theories that combine various kinds of representational structure, or eliminative theories that replace concepts with a more finely grained taxonomy of mental representations. In this paper, we describe an alternative approach involving a single class of mental representations called “semantic pointers.” Semantic pointers are symbol‐like representations that result from the compression and recursive binding of perceptual, lexical, and motor representations, effectively integrating traditional connectionist and symbolic approaches. We present a computational model using semantic pointers that replicates experimental data from categorization studies involving each prior paradigm. We argue that a framework involving semantic pointers can provide a unified account of conceptual phenomena, and we compare our framework to existing alternatives in accounting for the scope, content, recursive combination, and neural implementation of concepts.     

基于多传感器数据的航空管制员情境意识的计算

航空管制人员保持良好的情境意识是确保空中交通以安全、高效方式运行的必要条件。如果在管制员工作过程中, 能准确监测其情境意识状态, 并在情境意识丧失前给予及时告警, 那么将会极大地提高管制绩效和减少空中两机相撞的概率。目前, 国外评价管制员情境意识的方法虽然不少, 但这些方法基本都是诊断性质和回溯性质的, 无法对管制员的情境意识进行监测或预警。管制员的情境意识受个体差异、任务等多种因素的影响, 同时, 其也可以由某些指标来表征, 如某些作业绩效指标和生理指标。为了能够实现对航空管制员情境意识的准确监控及告警, 拟通过雷达管制模拟实验、心理测量、专家评定等方法采集多传感器数据, 分别建立基于表征指标和基于影响变量的情境意识计算模型, 并比较其预测性能。该研究结果可为管制员情境意识的实时监测提供支持。     

Learning General Phonological Rules From Distributional Information: A Computational Model

Phonological rules create alternations in the phonetic realizations of related words. These rules must be learned by infants in order to identify the phonological inventory, the morphological structure, and the lexicon of a language. Recent work proposes a computational model for the learning of one kind of phonological alternation, allophony (Peperkamp, Le Calvez, Nadal, & Dupoux, 2006). This paper extends the model to account for learning of a broader set of phonological alternations and the formalization of these alternations as general rules. In Experiment 1, we apply the original model to new data in Dutch and demonstrate its limitations in learning nonallophonic rules. In Experiment 2, we extend the model to allow it to learn general rules for alternations that apply to a class of segments. In Experiment 3, the model is further extended to allow for generalization by context; we argue that this generalization must be constrained by linguistic principles.     

分形与心理的分形研究

介绍了分形和心理的分形研究,分析了心理分形研究的意义,并对传统的欧几里得研究范式和分形研究范式做了区分。     

A Computational Model of the Self‐Teaching Hypothesis Based on the Dual‐Route Cascaded Model of Reading

The self‐teaching hypothesis describes how children progress toward skilled sight‐word reading. It proposes that children do this via phonological recoding with assistance from contextual cues, to identify the target pronunciation for a novel letter string, and in so doing create an opportunity to self‐teach new orthographic knowledge. We present a new computational implementation of self‐teaching within the dual‐route cascaded (DRC) model of reading aloud, and we explore how decoding and contextual cues can work together to enable accurate self‐teaching under a variety of circumstances. The new model (ST‐DRC) uses DRC’s sublexical route and the interactivity between the lexical and sublexical routes to simulate phonological recoding. Known spoken words are activated in response to novel printed words, triggering an opportunity for orthographic learning, which is the basis for skilled sight‐word reading. ST‐DRC also includes new computational mechanisms for simulating how contextual information aids word identification, and it demonstrates how partial decoding and ambiguous context interact to achieve irregular‐word learning. Beyond modeling orthographic learning and self‐teaching, ST‐DRC’s performance suggests new avenues for empirical research on how difficult word classes such as homographs and potentiophones are learned.     

Word Senses as Clusters of Meaning Modulations: A Computational Model of Polysemy

Most words in natural languages are polysemous; that is, they have related but different meanings in different contexts. This one-to-many mapping of form to meaning presents a challenge to understanding how word meanings are learned, represented, and processed. Previous work has focused on solutions in which multiple static semantic representations are linked to a single word form, which fails to capture important generalizations about how polysemous words are used; in particular, the graded nature of polysemous senses, and the flexibility and regularity of polysemy use. We provide a novel view of how polysemous words are represented and processed, focusing on how meaning is modulated by context. Our theory is implemented within a recurrent neural network that learns distributional information through exposure to a large and representative corpus of English. Clusters of meaning emerge from how the model processes individual word forms. In keeping with distributional theories of semantics, we suggest word meanings are generalized from contexts of different word tokens, with polysemy emerging as multiple clusters of contextually modulated meanings. We validate our results against a human-annotated corpus of polysemy focusing on the gradedness, flexibility, and regularity of polysemous sense individuation, as well as behavioral findings of offline sense relatedness ratings and online sentence processing. The results provide novel insights into how polysemy emerges from contextual processing of word meaning from both a theoretical and computational point of view.     

A Network Analysis Approach on the Psychological Flexibility/Inflexibility Model

Acceptance and Commitment Therapy (ACT) is purported to work via targeting six interrelated processes summarized as the Psychological Inflexibility/Psychological Flexibility (PI/PF) model. However, the theoretical structure and interconnections of this model have not been sufficiently explored. Lacking are examinations of the interrelations among its components. Network Analysis (NA) can model PI/PF as a system of interconnected variables. We aimed at exploring the role and associations of the PI/PF model’s components using NA in two different samples and sets of scales, and compare its structure across sub-samples. Sample 1 consisted of 501 individuals, who completed an online battery of questionnaires including the Multidimensional Psychological Flexibility Inventory, and Sample 2 consisted of 428 people, who completed an online set of six ACT measures, each assessing a component of the PI/PF model. NA could not verify the six ACT dimensions as distinct components. Values and Committed Action components were found to be strongly associated and combined in a group in both sets of measures and samples. Interestingly, Acceptance and Defusion were not the most central components as purported in some ACT conceptualizations, whereas Self-as-Context had a key role on both sets of measures and its items were often merged with Present Moment Awareness items. No significant differences were found in the comparison of networks across different subsamples and sets of scales. After combining different sets of scales, the six ACT components could not be completely verified as distinct entities, which might reflect problems with the theoretical model, or with the scales used. All components had critical roles in the model, particularly Self-as-Context, which reflects the need to redirect research towards this understudied construct. Findings point towards considerations of a triflex instead of a hexaflex ACT model.     

一个基于综合印象评分法的作文分事后调整模型

对大学英语四、六级考试作文评分进行了详细的描述,重点介绍了作文分的事后调整的原理和方法,并且给出了一个基于线性等值原理的数学推导。认为其数学模型主要是一个运用了“极大似然估计法”和“正态分”概念的统计模型。“评分标准的制定”、“用参照样卷来校准阅卷员对作文评分标准的掌握尺度”以及“阅卷员的培训和考核”构成了大学英语四、六级考试作文信度的基石;而作文分调整中基于“随机分发作文卷”、“客观题分数与作文分相关”以及“评分前后一致性”的统计方法则对出现系统性误差的阅卷员的评分结果进行了事后的校正。还提出如果拥有往次考试总体作文分均值数据,使用“加权移动平均法”可以实现对作文分的跨考次平衡。     

Representations of Complexity: How Nature Appears in Our Theories

In science we study processes in the material world. The way these processes operate can be discovered by conducting experiments that activate them, and findings from such experiments can lead to functional complexity theories of how the material processes work. The results of a good functional theory will agree with experimental measurements, but the theory may not incorporate in its algorithmic workings a representation of the material processes themselves. Nevertheless, the algorithmic operation of a good functional theory may be said to make contact with material reality by incorporating the emergent computations the material processes carry out. These points are illustrated in the experimental analysis of behavior by considering an evolutionary theory of behavior dynamics, the algorithmic operation of which does not correspond to material features of the physical world, but the functional output of which agrees quantitatively and qualitatively with findings from a large body of research with live organisms.     

A Multi-informant Multi-Measure Approach to the Two Factor Model of Emotion with Youth

The two-factor model of emotion clarifies the complexities of the relationship between anxiety and depression through their varying associations with positive and negative affect. Although this model’s structure has been studied in children, the lack of parent report measures on model-specific constructs has thus far prevented a multi-informant perspective on the model. Capitalizing on recent advancements in parent report assessment instruments, the present investigation aimed to confirm the two-factor model of emotion per child self-report; expand the model’s applicability to include parent report; and create a combined-informant model with a large number of parent-child dyad pairs (N?=?610). Structural equation modeling demonstrated good fit within parent and child informant models, but diminished fit for the multi-informant model. These results suggest a high degree of robustness with respect to informant type. Implications for the integration of multi-informant assessment information are discussed.     

Filipino Personality Structure and the Big Five Model: A Lexical Approach

ABSTRACT In lexically based studies, we derived Filipino personality dimensions and related them to the Big Five model. In Study 1, Filipino high-school and college students (N= 629) rated themselves on a near-comprehensive list of 861 Filipino (Tagalog) trait adjectives. In Study 2, Filipino high-school and college students (N= 1,531) rated 280 markers of dimensions identified in Study 1. Some students (n= 473) also completed the NEO Five-Factor Inventory. Seven comparable Filipino dimensions were identified in factor analyses in the two studies. We concluded that the dimensions we labeled Concern for Others (vs. Egotism), Conscientiousness. Gregariousness, and Intellect were quite similar to Big Five Agreeableness, Conscientiousness, Extraversion, and Intellect, respectively. The Filipino Self-Assurance dimension was most similar to Big Five Neuroticism. The Filipino Temperamentalness dimension was more complex in Big Five terms, overlapping Agreeableness, Conscientiousness, and Neuroticism. A final Filipino factor resembled a Negative Valence or Infrequency dimension. More than five factors had to be extracted to obtain Philippine dimensions resembling all of the Big Five.     

The Abuse of Power: A View of Sexual Misconduct in a Systemic Approach to Pastoral Care

The article explores the dynamics of transference and countertransference in hierarchical relationships which exist between clergy and lay persons, both in the parish setting, as well as in the pastoral counseling relationship. It is of utmost importance that the power differential be consciously acknowledged by pastoral caregivers so that appropriate boundaries can be exercised. All too often it is the negligent, careless, or unconscious disregard for this power dynamic by individuals providing pastoral care that has led to the sexual violations recently surfaced within our religious institutions. Acknowledgement of the imbalance of power, and its consequences for both clergy and parishioner, is essential in a systemic model of pastoral care.     

An Ecological Process Model of Systems Change

In June 2007 the American Journal of Community Psychology published a special issue focused on theories, methods and interventions for systems change which included calls from the editors and authors for theoretical advancement in this field. We propose a conceptual model of systems change that integrates familiar and fundamental community psychology principles (succession, interdependence, cycling of resources, adaptation) and accentuates a process orientation. To situate our framework we offer a definition of systems change and a brief review of the ecological perspective and principles. The Ecological Process Model of Systems Change is depicted, described and applied to a case example of policy driven systems level change in publicly funded social programs. We conclude by identifying salient implications for thinking and action which flow from the Model.