Modeling developmental cognitive neuroscience

In the past few years connectionist models have greatly contributed to formulating theories of cognitive development. Some of these models follow the approach of developmental cognitive neuroscience in exploring interactions between brain development and cognitive development by integrating structural change into learning. We describe two classes of these models. The first focuses on experience-dependent structural elaboration within a brain region by adding or deleting units and connections during learning. The second models the gradual integration of different brain areas based on combinations of experience-dependent and maturational factors. These models provide new theories of the mechanisms of cognitive change in various domains and they offer an integrated framework to study normal and abnormal development, and normal and impaired adult processing.     

Behaviorism, latent learning, and cognitive maps: needed revisions in introductory psychology textbooks

This paper critically assesses the scholarship in introductory psychology textbooks in relation to the topic of latent learning. A review of the treatment of latent learning in 48 introductory psychology textbooks published between 1948 and 2004, with 21 of these texts published since 1999, reveals that the scholarship on the topic of latent learning demonstrated in introductory textbooks warrants improvement. Errors that persist in textbooks include the assertion that the latent learning experiments demonstrate unequivocally that reinforcement was not necessary for learning to occur, that behavioral theories could not account for the results of the latent learning experiments, that B. F. Skinner was an S-R association behaviorist who argued that reinforcement is necessary for learning to occur, and that because behavioral theories (including that of B. F. Skinner) were unable explain the results of the latent learning experiments the cognitive map invoked by Edward Tolman is the only explanation for latent learning. Finally, the validity of the cognitive map is typically accepted without question. Implications of the presence of these errors for students and the discipline are considered. Lastly, remedies are offered to improve the scholarship found in introductory psychology textbooks.     

Theory learning as stochastic search in the language of thought

We present an algorithmic model for the development of children's intuitive theories within a hierarchical Bayesian framework, where theories are described as sets of logical laws generated by a probabilistic context-free grammar. We contrast our approach with connectionist and other emergentist approaches to modeling cognitive development. While their subsymbolic representations provide a smooth error surface that supports efficient gradient-based learning, our symbolic representations are better suited to capturing children's intuitive theories but give rise to a harder learning problem, which can only be solved by exploratory search. Our algorithm attempts to discover the theory that best explains a set of observed data by performing stochastic search at two levels of abstraction: an outer loop in the space of theories and an inner loop in the space of explanations or models generated by each theory given a particular dataset. We show that this stochastic search is capable of learning appropriate theories in several everyday domains and discuss its dynamics in the context of empirical studies of children's learning.     

Enriched learning: behavior,brain, and computation

The presence of complementary information across multiple sensory or motor modalities during learning, referred to as multimodal enrichment, can markedly benefit learning outcomes. Why is this? Here, we integrate cognitive, neuroscientific, and computational approaches to understanding the effectiveness of enrichment and discuss recent neuroscience findings indicating that crossmodal responses in sensory and motor brain regions causally contribute to the behavioral benefits of enrichment. The findings provide novel evidence for multimodal theories of enriched learning, challenge assumptions of longstanding cognitive theories, and provide counterevidence to unimodal neurobiologically inspired theories. Enriched educational methods are likely effective not only because they may engage greater levels of attention or deeper levels of processing, but also because multimodal interactions in the brain can enhance learning and memory.     

Introduction to the special section on theory and data in categorization: Integrating computational, behavioral, and cognitive neuroscience approaches

This special section brings together behavioral, computational, mathematical, and neuroimaging approaches to understand the processes underlying category learning. Over the past decade, there has been growing convergence in research on categorization, with computational-mathematical models influencing the interpretation of brain imaging and neuropsychological data, and with cognitive neuroscience findings influencing the development and refinement of models. Classic debates between single-system and multiple-memory-system theories have become more nuanced and focused. Multiple brain areas and cognitive processes contribute to categorization, but theories differ markedly in whether and when those neurocognitive components are recruited for different aspects of categorization. The articles in this special section approach this issue from several diverse angles.     

A learning theory account of depression

Learning theory provides a foundation for understanding and deriving treatment principles for impacting a spectrum of functional processes relevant to the construct of depression. While behavioral interventions have been commonplace in the cognitive behavioral tradition, most often conceptualized within a cognitive theoretical framework, recent years have seen renewed interest in more purely behavioral models. These modern learning theory accounts of depression focus on the interchange between behavior and the environment, mainly in terms of lack of reinforcement, extinction of instrumental behavior, and excesses of aversive control, and include a conceptualization of relevant cognitive and emotional variables. These positions, drawn from extensive basic and applied research, cohere with biological theories on reduced reward learning and reward responsiveness and views of depression as a heterogeneous, complex set of disorders. Treatment techniques based on learning theory, often labeled Behavioral Activation (BA) focus on activating the individual in directions that increase contact with potential reinforcers, as defined ideographically with the client. BA is considered an empirically well‐established treatment that generalizes well across diverse contexts and populations. The learning theory account is discussed in terms of being a parsimonious model and ground for treatments highly suitable for large scale dissemination.     

Using experiential optimization to build lexical representations

To account for natural variability in cognitive processing, it is standard practice to optimize a model’s parameters by fitting it to behavioral data. Although most language-related theories acknowledge a large role for experience in language processing, variability reflecting that knowledge is usually ignored when evaluating a model’s fit to representative data. We fit language-based behavioral data using experiential optimization, a method that optimizes the materials that a model is given while retaining the learning and processing mechanisms of standard practice. Rather than using default materials, experiential optimization selects the optimal linguistic sources to create a memory representation that maximizes task performance. We demonstrate performance on multiple benchmark tasks by optimizing the experience on which a model’s representation is based.

     

Shared intentionality

We argue for the importance of processes of shared intentionality in children's early cognitive development. We look briefly at four important social-cognitive skills and how they are transformed by shared intentionality. In each case, we look first at a kind of individualistic version of the skill -- as exemplified most clearly in the behavior of chimpanzees -- and then at a version based on shared intentionality -- as exemplified most clearly in the behavior of human 1- and 2-year-olds. We thus see the following transformations: gaze following into joint attention, social manipulation into cooperative communication, group activity into collaboration, and social learning into instructed learning. We conclude by highlighting the role that shared intentionality may play in integrating more biologically based and more culturally based theories of human development.     

利用脑成像多体素模式分析解码认知的神经表征:原理和应用

多体素模式分析(multi-voxel pattern analysis,MVPA)是一种基于机器学习理论发展出来的新的功能磁共振数据分析技术。MVPA技术通过训练分类器,对由不同认知状态引起的多体素信号模式进行分类。与传统的基于单个体素的分析方法相比,该技术可更敏感地检测脑对认知状态的表征,并使得从神经信号解码认知状态成为可能。文章介绍MVPA技术的基本原理、分析步骤以及可以用MVPA来解决的科学问题,并对应用中可能面临的问题提供了参考建议。     

A Bayesian formulation of behavioral control

Helplessness, a belief that the world is not subject to behavioral control, has long been central to our understanding of depression, and has influenced cognitive theories, animal models and behavioral treatments. However, despite its importance, there is no fully accepted definition of helplessness or behavioral control in psychology or psychiatry, and the formal treatments in engineering appear to capture only limited aspects of the intuitive concepts. Here, we formalize controllability in terms of characteristics of prior distributions over affectively charged environments. We explore the relevance of this notion of control to reinforcement learning methods of optimising behavior in such environments and consider how apparently maladaptive beliefs can result from normative inference processes. These results are discussed with reference to depression and animal models thereof.     

A contextual approach to research on AIDS prevention

The acquired immune deficiency syndrome (AIDS) is a disease that is transmitted almost entirely through behavioral factors. In the absence of a cure or vaccine, the modification of AIDS-risk behavior presents a unique challenge to behavioral scientists and should be taken as a clear imperative by behavior analysts. This paper discusses the currently dominant social-cognitive theories (the health belief model, the theory of reasoned action, and self-efficacy theory) that have been widely used to predict and understand AIDS-risk behavior. Although these theories have generated a voluminous literature on the cognitive, attitudinal, and demographic correlates of AIDS-risk behavior, they have not resulted in specific intervention strategies to influence risky behavior, most likely because they fail to specify manipulable variables. As an alternative to social-cognitive theories, this paper evaluates the usefulness of a behavior-analytic approach to stem the spread of HIV infection. It examines some of the philosophical differences underlying cognitive and behavioral approaches that are embedded in mechanistic versus functional contextualistic principles. It explores the theoretical and practical implications of adopting either predicting and explaining behavior or predicting and influencing behavior as the goals of science. To illustrate the value of adopting the goal of prediction and influence, behavior-analytic research on the social context of risky sexual behavior in adolescents is described. The paper argues that in order to alter the future course of the AIDS epidemic, the behavioral sciences must move beyond describing cognitive and attitudinal correlates of risky behavior and focus on the social context of the behavior of individuals. In addition, population-wide changes in AIDS-risk behavior can be accomplished only if research focuses on how to influence larger social systems, including the media, school systems, and community organizations.     

马普人类发展研究所毕生发展心理研究中心：研究主题和研究活动展示

Paul B. Baltes于1981年在马普人类发展研究所成立的毕生发展心理研究中心已经使毕生发展心理学成为了发展心理学中的一个重要的概念分支。2004年以来,中心已经将研究项目扩展到了发展行为神经科学。中心主要在三个主题上开展研究工作: (1) 研究作为成熟、学习和衰老的交互作用的结果, 毕生的不同发展阶段中人类行为变化的规律: (2) 发展能够整合来自于自身机能、时间序列、以及行为和神经层面分析等领域实证证据的理论和方法体系。(3) 通过探索不同年龄可塑性上的差异寻找发展的机制。中心继续重点关注成人晚期和老年期, 这为理论和实践上的创新提供了独特的机遇。同时, 中心加强了对包括婴儿期和儿童早期在内的个体发展早期阶段的研究。本文报告了来自四项从行为和神经层面分析感觉和认知发展的研究的最新发现。     

Action mechanisms for social cognition: behavioral and neural correlates of developing Theory of Mind

Many psychological theories posit foundational links between two fundamental constructs: (1) our ability to produce, perceive, and represent action; and (2) our ability to understand the meaning and motivation behind the action (i.e. Theory of Mind; ToM). This position is contentious, however, and long‐standing competing theories of social‐cognitive development debate roles for basic action‐processing in ToM. Developmental research is key to investigating these hypotheses, but whether individual differences in neural and behavioral measures of motor action relate to social‐cognitive development is unknown. We examined 3‐ to 5‐year‐old children's (N = 26) EEG mu‐desynchronization during production of object‐directed action, and explored associations between mu‐desynchronization and children's behavioral motor skills, behavioral action‐representation abilities, and behavioral ToM. For children with high (but not low) mu‐desynchronization, motor skill related to action‐representation abilities, and action‐representation mediated relations between motor skill and ToM. Results demonstrate novel foundational links between action‐processing and ToM, suggesting that basic motor action may be a key mechanism for social‐cognitive development, thus shedding light on the origins and emergence of higher social cognition.     

Reciprocal relations between cognitive neuroscience and formal cognitive models: opposites attract?

Cognitive neuroscientists study how the brain implements particular cognitive processes such as perception, learning, and decision-making. Traditional approaches in which experiments are designed to target a specific cognitive process have been supplemented by two recent innovations. First, formal cognitive models can decompose observed behavioral data into multiple latent cognitive processes, allowing brain measurements to be associated with a particular cognitive process more precisely and more confidently. Second, cognitive neuroscience can provide additional data to inform the development of formal cognitive models, providing greater constraint than behavioral data alone. We argue that these fields are mutually dependent; not only can models guide neuroscientific endeavors, but understanding neural mechanisms can provide key insights into formal models of cognition.     

In search of the neurobiological underpinnings of the differential outcomes effect

Correlating unique rewards with to-be-remembered events (the Differential Outcomes Procedure [DOP]) enhances learning and memory performance in a range of species. Recently, we have demonstrated that the DOP can be used to reduce or eliminate the learning and memory impairments associated with animal models of amnesia and dementia. This powerful phenomenon, the Differential Outcomes Effect (DOE), has led to the question: How does such a simple manipulation exert such dramatic influence on learning and memory performance? A revised two-process account of the DOE states that using the DOP results in the activation of reward expectancies through Pavlovian mechanisms. The use of unique reward expectancies alters the nature of cognitive processing used to solve discrimination tasks. The change in cognitive processing is represented by utilization of a different memory system than that commonly used to acquire and remenber information when a Nondifferential Outcomes Procedure (NOP) is used. Using neurochemical manipulations, it has been demonstrated that different, potentially independent, brain systems modulate memory performance when subjects are trained with a NOP versus a DOP. This memory-based DOP/NOP distinction resembles other dissociative memory theories in which two psychological processes are purportedly served by distinct neurobiological mechanisms. In addition, such results have important ramifications for the treatment of memory disorders because they demonstrate that stimulus and behavioral manipulations, like drugs, can influence neurotransmitter functioning.     

儿童认知发展研究的前沿与动向

近一二十年,得益于认知发展理论的进步和研究方法的新发展,儿童认知发展研究取得了长足的进步。这体现在婴儿研究方兴未艾,一些新课题的出现使一些传统的研究领域重新恢复了活力。同时．发展认知神经科学和认知行为遗传学这两个边沿交叉学科研究蓬勃发展,应用认知发展心理学研究迅速发展,对认知发展心理学研究均产生了巨大的影响。     

In Search of the Neurobiological Underpinnings of the Differential Outcomes Effect

Correlating unique rewards with to-be-remembered events (the Differential Outcomes Procedure [DOP]) enhances learning and memory performance in a range of species. Recently, we have demonstrated that the DOP can be used to reduce or eliminate the learning and memory impairments associated with animal models of amnesia and dementia. This powerful phenomenon, the Differential Outcomes Effect (DOE), has led to the question: How does such a simple manipulation exert such dramatic influence on learning and memory performance? A revised two-process account of the DOE states that using the DOP results in the activation of reward expectancies through Pavlovian mechanisms. The use of unique reward expectancies alters the nature of cognitive processing used to solve discrimination tasks. The change in cognitive processing is represented by utilization of a different memory system than that commonly used to acquire and remember information when a Nondifferential Outcomes Procedure (NOP) is used. Using neurochemical manipulations, it has been demonstrated that different, potentially independent, brain systems modulate memory performance when subjects are trained with a NOP versus a DOP. This memory-based DOP/NOP distinction resembles other dissociative memory theories in which two psychological processes are purportedly served by distinct neurobiological mechanisms. In addition, such results have important ramifications for the treatment of memory disorders because they demonstrate that stimulus and behavioral manipulations, like drugs, can influence neurotransmitter functioning.     

Theoretical,and epistemological challenges in scientific investigations of complex emotional states in animals

This review brings to light critical epistemological and theoretical considerations when studying complex emotional states in animals. We discuss anthropomorphic and Umwelt perspectives of nonhuman animals and the ways in which distinct theories of consciousness and neural processing may restrict the potential for the development of knowledge on the topic. Within the same line of argumentation, we consider influences of the debate between monism and dualism and psychology’s behaviorism and cognitive theories. Finally, we contrast the affective consciousness, higher-order emotional consciousness, and constructed emotion theories to further our understanding of complex emotional states in animals.     

Domain-creating constraints

The contributions to this special issue on cognitive development collectively propose ways in which learning involves developing constraints that shape subsequent learning. A learning system must be constrained to learn efficiently, but some of these constraints are themselves learnable. To know how something will behave, a learner must know what kind of thing it is. Although this has led previous researchers to argue for domain-specific constraints that are tied to different kinds/domains, an exciting possibility is that kinds/domains themselves can be learned. General cognitive constraints, when combined with rich inputs, can establish domains, rather than these domains necessarily preexisting prior to learning. Knowledge is structured and richly differentiated, but its "skeleton" must not always be preestablished. Instead, the skeleton may be adapted to fit patterns of co-occurrence, task requirements, and goals. Finally, we argue that for models of development to demonstrate genuine cognitive novelty, it will be helpful for them to move beyond highly preprocessed and symbolic encodings that limit flexibility. We consider two physical models that learn to make tone discriminations. They are mechanistic models that preserve rich spatial, perceptual, dynamic, and concrete information, allowing them to form surprising new classes of hypotheses and encodings.     

LEARNING THEORY APPROACHES TO PERSUASION

This review synthesizes relevant research dealing with the processes of learning and suggests its applications to compliance gaining. The two major issues addressed are: (1) to what degree can learning theories explain the acquisition of new attitudes and behaviors, and (2) to what degree are attitudinal and behavioral changes governed by learning theory principles? The learning theories discussed are grouped into three categories: stimulus-response or connectionist approaches; cognitive approaches; and stochastic, mathematical, and cybernetic approaches. The stimulus-response models, which encompass most of the research examined in this paper, are further broken down into four types: (1) classical conditioning, (2) contiguity models, (3) instrumental (or operant) conditioning and (4) models including drive and drive reduction. Principles and major research evidence from numerous learning theories are reviewed and analyzed, and suggestions are made as to how this evidence may aid in the construction of more complete theories of persuasion and attitude change.