Simple games as dynamic, coupled systems: randomness and other emergent properties

From a game theory perspective the ability to generate random behaviors is critical. However, psychological studies have consistently found that individuals are poor at behaving randomly. In this paper we investigated the possibility that the randomness mechanism lies not within the individual players but in the interaction between the players. Provided that players are influenced by their opponent’s past behavior, their relationship may constitute a state of reciprocal causation [Cognitive Science 21 (1998) 461], in which each player simultaneously affects and is affected by the other player. The result of this would be a dynamic, coupled system. Using neural networks to represent the individual players in a game of paper, rock, and scissors, a model of this process was developed and shown to be capable of generating chaos-like behaviors as an emergent property. In addition, it was found that by manipulating the control parameters of the model, corresponding to the amount of working memory and the perceived values of different outcomes, that the game could be biased in favor of one player over the other, an outcome not predicted by game theory. Human data was collected and the results show that the model accurately describes human behavior. The results and the model are discussed in light of recent theoretical advances in dynamic systems theory and cognition.     

Moving to higher ground: The dynamic field theory and the dynamics of visual cognition

In the present report, we describe a new dynamic field theory that captures the dynamics of visuo-spatial cognition. This theory grew out of the dynamic systems approach to motor control and development, and is grounded in neural principles. The initial application of dynamic field theory to issues in visuo-spatial cognition extended concepts of the motor approach to decision making in a sensori-motor context, and, more recently, to the dynamics of spatial cognition. Here we extend these concepts still further to address topics in visual cognition, including visual working memory for non-spatial object properties, the processes that underlie change detection, and the ‘binding problem’ in vision. In each case, we demonstrate that the general principles of the dynamic field approach can unify findings in the literature and generate novel predictions. We contend that the application of these concepts to visual cognition avoids the pitfalls of reductionist approaches in cognitive science, and points toward a formal integration of brains, bodies, and behavior.     

Explaining after by before: Basic aspects of a dynamic systems approach to the study of development

The basic properties of a dynamic systems approach of development are illustrated by contrasting two simple equations. One, y_t+1 = f (y_t), is characteristic of dynamic systems models. The other, y_i = f (x_i), refers to what, for the sake of simplicity, is referred to as the standard developmental approach. We give illustrations from cognitive, language and social development to show the characteristic differences of these two types of models and show their complementarity. The article further compares the “Bloomington” with the “Groningen” approach to dynamic systems theorizing in developmental psychology. It continues with a discussion of two important questions. One involves the issue of measurement and the nature of developmental variables from the viewpoint of dynamic systems. The second concerns the question of short- and long-term time scales in developmental models, which is discussed on the basis of an example, namely dyadic interaction of young children in the context of different social statuses.     

Motivated learning for the development of autonomous systems

A new machine learning approach known as motivated learning (ML) is presented in this work. Motivated learning drives a machine to develop abstract motivations and choose its own goals. ML also provides a self-organizing system that controls a machine’s behavior based on competition between dynamically-changing pain signals. This provides an interplay of externally driven and internally generated control signals. It is demonstrated that ML not only yields a more sophisticated learning mechanism and system of values than reinforcement learning (RL), but is also more efficient in learning complex relations and delivers better performance than RL in dynamically-changing environments. In addition, this paper shows the basic neural network structures used to create abstract motivations, higher level goals, and subgoals. Finally, simulation results show comparisons between ML and RL in environments of gradually increasing sophistication and levels of difficulty.     

Visual working memory for dynamic objects: Impaired binding between object feature and location

In daily life, people frequently need to observe dynamic objects and temporarily maintain their representations in visual working memory (VWM). The present study explored the mechanism underlying the binding between perceptual features and locations of dynamic objects in VWM. In three experiments, we measured and compared the memory performance for feature-location binding of multiple dynamic and static objects. The results showed that the feature-location binding was impaired for the dynamic objects compared with the static objects. The impairment persisted when the global spatial configuration of the objects remained intact during the motion, as well as when the binding task was relatively easy, such as binding between single-feature objects and coarse locations. The results indicate that object features and locations are not maintained in VWM as well-integrated object files; rather, the formation of feature-location binding may require additional processes, which are disrupted by the constant change of locations in dynamic circumstances. We propose a consolidation process as possible underlying mechanism, and discuss factors that may influence the strength of feature-location binding in dynamic circumstances.     

The relationship between the perception of axes of symmetry and spatial memory during early childhood

Early in development, there is a transition in spatial working memory (SWM). When remembering a location in a homogeneous space (e.g., in a sandbox), young children are biased toward the midline symmetry axis of the space. Over development, a transition occurs that leads to older children being biased away from midline. The dynamic field theory (DFT) explains this transition in biases as being caused by a change in the precision of neural interaction in SWM and improvements in the perception of midline. According to the DFT, young children perceive midline, but there is a quantitative improvement in the perception of midline over development. In the experiment reported here, children and adults needed to determine on which half of a large monitor a target was located. In support of the DFT, even the youngest children performed above chance at most locations, but performance also improved gradually with age.     

The thalamic dynamic core theory of conscious experience

I propose that primary conscious awareness arises from synchronized activity in dendrites of neurons in dorsal thalamic nuclei, mediated particularly by inhibitory interactions with thalamic reticular neurons. In support, I offer four evidential pillars: (1) consciousness is restricted to the results of cortical computations; (2) thalamus is the common locus of action of brain injury in vegetative state and of general anesthetics; (3) the anatomy and physiology of the thalamus imply a central role in consciousness; (4) neural synchronization is a neural correlate of consciousness.     

Life-long environmental enrichment differentially affects the mnemonic response to estrogen in young, middle-aged, and aged female mice

The present study was designed to examine whether life-long exposure to standard or enriched housing affects the ability of estrogen to improve spatial and object memory throughout the lifespan. Three-week-old female mice were maintained in standard or enriched housing up to and through ovariectomy and behavioral testing at 5, 17, or 22 months of age. Spatial memory was tested in the Morris water maze and object memory was tested using an object recognition task. Immediately after training each day, mice were injected intraperitoneally with vehicle or 0.2 mg/kg 17beta-estradiol. Among young females, object recognition was enhanced by estradiol alone, an effect that was reduced by enrichment. In contrast, spatial water maze performance was impaired by estradiol alone, but improved by the combination of both estradiol and enrichment. At middle-age, object recognition was enhanced by estradiol or enrichment alone, and the combination of both treatments. Spatial memory in the water maze was also improved by both treatments at middle-age, but the beneficial effects of estradiol were limited to standard-housed females. Finally, whereas enrichment in aged females significantly enhanced performance in both tasks, estradiol had no effect at this age in either task. In total, the data indicate that life-long enrichment can significantly alter the extent to which estradiol affects memory in mice throughout the lifespan. Importantly, the interaction between these treatments is highly dependent on age and type of memory tested.     

Applications of social cognitive theory to the career development of women of color

This article provides a review of the literature on the educational and career development of women of color within the context of social cognitive career theory (Lent, et al, 1994 and Lent, et al, 1996). Specifically, possible gender, ethnic, racial, and cultural influences on career self-efficacy and outcome expectations are explored to delinate the potential mechanisms whereby ethnicity, culture, and ethnic and racial identity development, in interaction with gender, affect career choice and adjustment. Suggestions for future research on social cognitive career theory and the career development of women of color are presented.     

Contributions of longitudinal research to a cognitive theory of adjustment to aging

In agreement with Costa and McCrae (1992), the principle of ‘multiple uses’ of longitudinal studies is stressed based on a comparative review of the history of the Berkeley longitudinal studies and their different uses, and of those of the Bonn Longitudinal Study on Aging (BOLSA). Of the many uses of BOLSA, its contribution to the testing of a cognitive theory of aging is discussed. A selection of the findings of BOLSA and other studies of the Bonn Department of Psychology and the Institute of Gerontology, University of Heidelberg, is reported. These findings support three postulates of this theory: ( 1 ) the perceived rather than the objective situation directs behaviour; (2) perceptions of situations are related to dominant concerns of the person; and (3) adjustment to aging is achieved when a balance between the cognitive and motivational systems of the person has been attained.     

Applying linear systems analysis to dynamic behavior

In this paper we present an abbreviated discussion of the linear systems analysis in the time domain. We then consider the qualitative character of the behavioral dynamics predicted using the linear form of the analysis. The analysis is then extended to a second-order form. We illustrate some relevant new features introduced by the second-order form with a special case example.     

A category theory approach to cognitive development

The category theory concept of a commutative diagram is used to construct a model of the way in which symbolic processes are applied to problem solving. The model provides for a relationship between symbolic processes and the problem which depends on structural isomorphism and consistency, but is independent of similarity between symbol elements and problem elements. It is then shown that several different levels of thought can be distinguished within the basic model. More information is needed to assign symbolic processes to a problem in a consistent way with higher-level thought processes than with lower-level processes. These information-processing requirements permit the approximate age of mastery of each level to be predicted, thereby offering an alternate theory of cognitive developmental stages. Two experiments designed to test the theory are reported.     

Doing cognitive neuroscience: a third way

The “top-down” and “bottom-up” approaches have been thought to exhaust the possibilities for doing cognitive neuroscience. We argue that neither approach is likely to succeed in providing a theory that enables us to understand how cognition is achieved in biological creatures like ourselves. We consider a promising third way of doing cognitive neuroscience, what might be called the “neural dynamic systems” approach, that construes cognitive neuroscience as an autonomous explanatory endeavor, aiming to characterize in its own terms the states and processes responsible for brain-based cognition. We sketch the basic motivation for the approach, describe a particular version of the approach, so-called ‘Dynamic Causal Modeling’ (DCM), and consider a concrete example of DCM. This third way, we argue, has the potential to avoid the problems that afflict the other two approaches.     

The biological foundations of cognitive science

Cognitive Science originated in reactions against behaviorism that were motivated in significant part by the example of the computer. The computer raised the exciting possibility that mind could be understood almost entirely independently of brain: if the operations of the mind are akin to the execution of a program, then almost all the relevant aspects of mind would be captured by that program, independently of whatever was running it, be it transistors or neurons. This presumed independence of cognitive science from biology has waned considerably in recent decades, but in this paper, I argue that there is at least one crucial aspect of biology that has yet to be appreciated for its relevance to mental and other normative processes—the thermodynamics of living systems. In particular, I argue that the emergence of normativity in general—and normative function and representation in particular—depends on special systems that are far from thermodynamic equilibrium; these form the interface between the factual world of atoms and molecules and the normative world of mind. The nature of that emergence, in turn, imposes strong constraints on how the central nervous system functions, and, therefore, on how cognition is realized.     

Combining dynamic systems and multivariate analyses to compare the mother-child interactions of externalizing subtypes

A dynamic systems analysis was conducted to distinguish the parent–child interactions of pure externalizing children from children comorbid for externalizing and internalizing problems. Thirty-three parents and clinically referred children (8–12 years old) discussed a problem for 4 min and then tried to wrap up in response to a signal (a perturbation). The perturbation was intended to increase the pressure on the dyad, triggering a reorganization of their behavioral system. We hypothesized that the comorbid group would be distinguished from the externalizing-only group as a result of this reorganization, but not before. The sequential data were analyzed using a combination of case-sensitive (state space grids and chi-square analyses) and group-based, multivariate techniques (log-linear modeling). Results revealed that externalizing dyads engaged in a permissive pattern throughout the problem-solving session, whereas comorbid dyads shifted from a permissive pattern to a mutually hostile pattern after the perturbation. These findings punctuate the need for a dynamic systems approach to the study of relationship processes associated with the development of childhood psychopathology. Theoretical and clinical implications are discussed.     

Extending Dynamical Systems Theory to Model Embodied Cognition

We define a mathematical formalism based on the concept of an ‘‘open dynamical system” and show how it can be used to model embodied cognition. This formalism extends classical dynamical systems theory by distinguishing a ‘‘total system’’ (which models an agent in an environment) and an ‘‘agent system’’ (which models an agent by itself), and it includes tools for analyzing the collections of overlapping paths that occur in an embedded agent's state space. To illustrate the way this formalism can be applied, several neural network models are embedded in a simple model environment. Such phenomena as masking, perceptual ambiguity, and priming are then observed. We also use this formalism to reinterpret examples from the embodiment literature, arguing that it provides for a more thorough analysis of the relevant phenomena.     

Using relations within conceptual systems to translate across conceptual systems

According to an "external grounding" theory of meaning, a concept's meaning depends on its connection to the external world. By a "conceptual web" account, a concept's meaning depends on its relations to other concepts within the same system. We explore one aspect of meaning, the identification of matching concepts across systems (e.g. people, theories, or cultures). We present a computational algorithm called ABSURDIST (Aligning Between Systems Using Relations Derived Inside Systems for Translation) that uses only within-system similarity relations to find between-system translations. While illustrating the sufficiency of a conceptual web account for translating between systems, simulations of ABSURDIST also indicate powerful synergistic interactions between intrinsic, within-system information and extrinsic information.     

Evidence of a role for multiple memory systems in behavioral extinction

The acquisition of learned behavior involves multiple memory systems, and hippocampal system damage impairs cognitive learning while leaving stimulus-response habit learning intact. In view of evidence that extinction also involves new learning, the present experiments examined whether multiple memory systems theory may be applicable to the neural bases of extinction. Adult Long-Evans rats were trained to run in a straight-alley maze for food reward. Twenty-four hours later, rats matched for runway latencies during acquisition received extinction training. In a response extinction condition conducive to habit learning, rats performed a runway approach response to an empty food cup. In a latent extinction condition conducive to cognitive learning, rats were placed at an empty food cup without performing a runway approach response. Prior to daily extinction training, neural activity of the dorsal hippocampus was reversibly inactivated via infusion of bupivacaine (0.75%, 0.5 microl/side). Control rats receiving saline infusions displayed extinction behavior in both the response and latent training conditions. In contrast, rats receiving bupivacaine extinguished normally in the response condition, but did not display latent extinction. The findings (1) confirm that learning underlying extinction of the same overt behavior can occur with or without explicit performance of the previously acquired response, (2) indicate that extinction learning produced by response and latent training procedures can be neuroanatomically dissociated, and (3) suggest that similarly to initial task acquisition, the hippocampus may critically mediate extinction in situations requiring the use of cognitive learning, such as when performance of a previously acquired response habit is prevented.     

Acetylcholine modulation of neural systems involved in learning and memory

Extensive evidence supports the view that cholinergic mechanisms modulate learning and memory formation. This paper reviews evidence for cholinergic regulation of multiple memory systems, noting that manipulations of cholinergic functions in many neural systems can enhance or impair memory for tasks generally associated with those neural systems. While parallel memory systems can be identified by combining lesions with carefully crafted tasks, most—if not all—tasks require the combinatorial participation of multiple neural systems. This paper offers the hypothesis that the magnitude of acetylcholine (ACh) release in different neural systems may regulate the relative contributions of these systems to learning. Recent studies of ACh release, obtained with in vivo microdialysis samples during training, together with direct injections of cholinergic drugs into different neural systems, provide evidence that release of ACh is important in engaging these systems during learning, and that the extent to which the systems are engaged is associated with individual differences in learning and memory.     

Contributions of domain-general cognitive resources and different forms of arithmetic development to pre-algebraic knowledge

The purpose of this study was to investigate the contributions of domain-general cognitive resources and different forms of arithmetic development to individual differences in pre-algebraic knowledge. Children (n = 279, mean age = 7.59 years) were assessed on 7 domain-general cognitive resources as well as arithmetic calculations and word problems at start of 2nd grade and on calculations, word problems, and pre-algebraic knowledge at end of 3rd grade. Multilevel path analysis, controlling for instructional effects associated with the sequence of classrooms in which students were nested across Grades 2-3, indicated arithmetic calculations and word problems are foundational to pre-algebraic knowledge. Also, results revealed direct contributions of nonverbal reasoning and oral language to pre-algebraic knowledge, beyond indirect effects that are mediated via arithmetic calculations and word problems. By contrast, attentive behavior, phonological processing, and processing speed contributed to pre-algebraic knowledge only indirectly via arithmetic calculations and word problems. (PsycINFO Database Record (c) 2012 APA, all rights reserved).