Predatory aggression in the mink (Mustela vison): Roles of serotonin and food satiation

5-Hydroxytrypotophan at a dose of 50 mg/kg intraperitoneally (i.p.) sharply increased neural serotonin (5-HT) levels in mink and considerably inhibited that animal's predatory attack on rats. Intraperitoneal injection of 5-HT (10 and 20 mg/kg) did not influence such rat-killing. Neural levels of 5-HT or 5-hydroxyindoleacetic acid (5-HIAA) and subsequent aggression by the predator did not change to any great degree after ingestion of a single meal. Abundance of natural mink food for 3 days was associated with an increased level of 5-HIAA in the lateral hypothalamus and the amygdala as well as with an increased latency to attack and to kill rats. 5-HT seems to represent an endogenous factor that inhibits predatory attack by the mink; this effect appears to function through increased metabolism of 5-HT in some brain regions, which is evident after abundant intake of tryptophan with the natural diet.     

Learning and development in neural networks--the importance of prior experience

Infants can discriminate between familiar and unfamiliar grammatical patterns expressed in a vocabulary that is distinct from that used earlier during familiarization (Cognition 70(2) (1999) 109; Science 283 (1999) 77). Various models have captured the data, although each required that discrimination be distinct, in terms of the computational process, from familiarization. This article describes a simple recurrent network (SRN), equipped only with the assumption that it should predict what comes next, which models the data without distinguishing between familiarization and discrimination. To accomplish this, the SRN requires pre-training on a range of sequences instantiating different structures and different vocabulary items to those used subsequently during familiarization and test. Pre-training enables the network to avoid replacing structure acquired during familiarization with structure experienced at test. An equivalent enabling condition may underpin infants' resistance to catastrophic interference between the different structures and vocabulary items to which they are exposed.     

Behavior analysis and revaluation

Revaluation refers to phenomena in which the strength of an operant is altered by reinforcer-related manipulations that take place outside the conditioning situation in which the operant was selected. As an example, if lever pressing is acquired using food as a reinforcer and food is later paired with an aversive stimulus, the frequency of lever pressing decreases when subsequently tested. Associationist psychology infers from such findings that conditioning produces a response-outcome (i.e., reinforcer) association and that the operant decreased in strength because pairing the reinforcer with the aversive stimulus changed the value of the outcome. Here, we present an approach to the interpretation of these and related findings that employs neural network simulations grounded in the experimental analysis of behavior and neuroscience. In so doing, we address some general issues regarding the relations among behavior analysis, neuroscience, and associationism.     

Toward a Comprehensive Strategy for Effective Practitioner–Scientist Partnerships and Larger-Scale Community Health and Well-Being

This article articulates joint priorities for the fields of prevention science and community psychology. These priorities are intended to address issues raised by the frequent observation of natural tensions between community practitioners and scientists. The first priority is to expand the knowledge base on practitioner–scientist partnerships, particularly on factors associated with positive outcomes within communities. To further articulate this priority, the paper first discusses the rapid growth in community-based partnerships and the emergent research on them. Next described is an illustrative research project on a partnership model that links state university extension and public school delivery systems. The article then turns to the second, related priority of future capacity-building for diffusion of effective partnership-based interventions to achieve larger-scale health and well-being across communities. It outlines two salient tasks: clarification of a conceptual framework and the formulation of a comprehensive capacity-building strategy for diffusion. The comprehensive strategy would require careful attention to the expansion of networks of effective partnerships, partnership-based research agendas, and requisite policy-making.     

自我面孔识别的独特性

与识别他人的面孔相比,自我面孔识别在行为反应、种系发生、个体发展以及脑机制等方面都具有很大的独特性。行为指标方面,自我面孔识别在速度上快于识别他人的面孔;种系发生方面,只有人类和大猩猩等高级灵长类动物才具有识别自己面孔的能力;个体发展方面,儿童出生后不久即能识别他人面孔,但要在18个月左右才能表现出自我面孔识别能力;脑机制方面,神经心理学和脑成像研究结果表明自我面孔识别可能主要是右脑的功能。该领域的研究进展将为深入了解自我的形成机理提供一个新的探视“窗口”。     

A formal model for structuring local perceptions of environmental space

The problem of constructing computational models of space that mimic those found in human spatial reasoning is addressed. This paper extends a formal model that addressed point objects in a 2D world to include the presence of line objects and barriers. The problem consists of determining an appropriate global model for the spatial configuration given a sequence of local views or observations. A formal model is proposed based on constraint network theory. The model leads to the identification of stable regions within which perceptual information about the environment changes slowly, and zones of transition within which the perceptual information changes more quickly. A special case of transition zones is a gateway, which may be viewed as a kind of discontinuity or singularity in the model. It is expected that the model obtained will be used to mimic human mental representations of navigable outdoor environments.     

Transitive choices by a simple, fully connected, backpropagation neural network: implications for the comparative study of transitive inference.

In search of the minimal requirements for transitive reasoning, a simple neural network was trained and tested on the non-verbal version of the conventional "five-term-series task" – a paradigm used with human adults, children and a variety of non-human species. The transitive performance of the network was analogous in several aspects to that reported for children and animals. The three effects usually associated with transitive choices i.e. "symbolic distance", "lexical marking" and "end-anchor", were also clearly shown by the neural network. In a second experiment, where the training conditions were manipulated, the network failed to match the behavioural pattern reported for human adults in the test following an ordered presentation of the premises. However, it mimicked young children's performance when tested with a novel comparison term. Although we do not intend to suggest a new model of transitive inference, we conclude, in line with other authors, that a simple error-correcting rule can generate transitive behaviour similar to the choice pattern of children and animals in the binary form of the five-term-series task without requiring high-order logical or paralogical abilities. The analysis of the training history and of the final internal structure of the network reveals the associative strategy employed. However, our results indicate that the scope of the associative strategy used by the network might be limited. The extent to which the conventional five-term-series task, in absence of appropriate manipulations of training and testing conditions, is suitable to detect cognitive differences across species is also discussed on the basis of our results. Accepted after revision: 29 May 2001 Electronic Publication     

Anger Can Help: A Transactional Model and Three Pathways of the Experience and Expression of Anger

Anger is a significant human emotion with far‐reaching implications for individuals and relationships. We propose a transactional model of anger that highlights its relational relevance and potentially positive function, in addition to problematic malformations. By evolutionary design, physical, self‐concept, or attachment threats all similarly trigger diffuse physiological arousal, psychologically experienced as anger‐emotion. Anger is first a signaling and motivational system. Anger is then formed to affirming, productive use or malformed to destructive ends. A functional, prosocial approach to anger organizes it for protective and corrective personal and relational adaptation. In our model, threat perception interacts with a person's view of self in relation to other to produce helpful or harmful anger. Inflated or collapsed views of self in relation to other produce distinct manifestations of destructive anger that are harmful to self, other, and relationship. Conversely, a balanced view of self in relation to other promotes constructive anger and catalyzes self, other, and relationship healing. Clinical use of the model to shape healing personal and relational contact with anger is explored.     

Translating the ICAP Theory of Cognitive Engagement Into Practice

ICAP is a theory of active learning that differentiates students’ engagement based on their behaviors. ICAP postulates that I nteractive engagement, demonstrated by co‐generative collaborative behaviors, is superior for learning to C onstructive engagement, indicated by generative behaviors. Both kinds of engagement exceed the benefits of A ctive or P assive engagement, marked by manipulative and attentive behaviors, respectively. This paper discusses a 5‐year project that attempted to translate ICAP into a theory of instruction using five successive measures: (a) teachers’ understanding of ICAP after completing an online module, (b) their success at designing lesson plans using different ICAP modes, (c) fidelity of teachers’ classroom implementation, (d) modes of students’ enacted behaviors, and (e) students’ learning outcomes. Although teachers had minimal success in designing Constructive and Interactive activities, students nevertheless learned significantly more in the context of Constructive than Active activities. We discuss reasons for teachers’ overall difficulty in designing and eliciting Interactive engagement.     

Finding MAPs using strongly equivalent high order recurrent symmetric connectionist networks

Belief revision is the problem of finding the most plausible explanation for an observed set of evidences. It has many applications in various scientific domains like natural language understanding, medical diagnosis and computational biology. Bayesian Networks (BN) is an important probabilistic graphical formalism widely used for belief revision tasks. In BN, belief revision can be achieved by finding the maximum a posteriori (MAP) assignment. Finding MAP is an NP-Hard problem. In previous work, we showed how to find the MAP assignment in BN using High Order Recurrent Neural Networks (HORN) through an intermediate representation of Cost-Based Abduction. This method eliminates the need to explicitly construct the energy function in two steps, objective and constraints. This paper builds on that previous work by providing the theoretical foundation and proving that the resultant HORN used to find MAP is strongly equivalent to the original BN it tries to solve.