Précis of neuroconstructivism: how the brain constructs cognition

Neuroconstructivism: How the Brain Constructs Cognition proposes a unifying framework for the study of cognitive development that brings together (1) constructivism (which views development as the progressive elaboration of increasingly complex structures), (2) cognitive neuroscience (which aims to understand the neural mechanisms underlying behavior), and (3) computational modeling (which proposes formal and explicit specifications of information processing). The guiding principle of our approach is context dependence, within and (in contrast to Marr [1982]) between levels of organization. We propose that three mechanisms guide the emergence of representations: competition, cooperation, and chronotopy; which themselves allow for two central processes: proactivity and progressive specialization. We suggest that the main outcome of development is partial representations, distributed across distinct functional circuits. This framework is derived by examining development at the level of single neurons, brain systems, and whole organisms. We use the terms encellment, embrainment, and embodiment to describe the higher-level contextual influences that act at each of these levels of organization. To illustrate these mechanisms in operation we provide case studies in early visual perception, infant habituation, phonological development, and object representations in infancy. Three further case studies are concerned with interactions between levels of explanation: social development, atypical development and within that, developmental dyslexia. We conclude that cognitive development arises from a dynamic, contextual change in embodied neural structures leading to partial representations across multiple brain regions and timescales, in response to proactively specified physical and social environment.     

Multimodal interactions in typically and atypically developing children: natural versus artificial environments

This review addresses the central role played by multimodal interactions in neurocognitive development. We first analyzed our studies of multimodal verbal and nonverbal cognition and emotional interactions within neuronal, that is, natural environments in typically developing children. We then tried to relate them to the topic of creating artificial environments using mobile toy robots to neurorehabilitate severely autistic children. By doing so, both neural/natural and artificial environments are considered as the basis of neuronal organization and reorganization. The common thread underlying the thinking behind this approach revolves around the brain’s intrinsic properties: neuroplasticity and the fact that the brain is neurodynamic. In our approach, neural organization and reorganization using natural or artificial environments aspires to bring computational perspectives into cognitive developmental neuroscience.     

Development of the Brain’s Functional Network Architecture

A full understanding of the development of the brain’s functional network architecture requires not only an understanding of developmental changes in neural processing in individual brain regions but also an understanding of changes in inter-regional interactions. Resting state functional connectivity MRI (rs-fcMRI) is increasingly being used to study functional interactions between brain regions in both adults and children. We briefly review methods used to study functional interactions and networks with rs-fcMRI and how these methods have been used to define developmental changes in network functional connectivity. The developmental rs-fcMRI studies to date have found two general properties. First, regional interactions change from being predominately anatomically local in children to interactions spanning longer cortical distances in young adults. Second, this developmental change in functional connectivity occurs, in general, via mechanisms of segregation of local regions and integration of distant regions into disparate subnetworks.     

The constructivist brain

How do the representations underlying cognitive skills emerge? It is becoming increasingly apparent that answering this question requires integration of neural, cognitive and computational perspectives. Results from this integrative approach resonate with Piaget's central constructivist themes, thus converging on a 'neural constructivist' approach to development, which itself rests on two major research developments. First, accumulating neural evidence for developmental plasticity makes nativist proposals increasingly untenable. Instead, the evidence suggests that cortical development involves the progressive elaboration of neural circuits in which experience-dependent neural growth mechanisms act alongside intrinsic developmental processes to construct the representations underlying mature skills. Second, new research involving constructivist neural networks is elucidating the dynamic interaction between environmentally derived neural activity and developmental mechanisms. Recent neurodevelopmental studies further accord with Piaget's themes, supporting the view of human cortical development as a protracted period of hierarchical-representation construction. Combining constructive growth algorithms with the hierarchical construction of cortical regions suggests that cortical development involves a cascade of increasingly complex representations. Thus, protracted cortical development, while occurring at the expense of increased vulnerability and parental investment, appears to be a powerful and flexible strategy for constructing the representations underlying cognition.     

The Basics of Brain Development

Over the past several decades, significant advances have been made in our understanding of the basic stages and mechanisms of mammalian brain development. Studies elucidating the neurobiology of brain development span the levels of neural organization from the macroanatomic, to the cellular, to the molecular. Together this large body of work provides a picture of brain development as the product of a complex series of dynamic and adaptive processes operating within a highly constrained, genetically organized but constantly changing context. The view of brain development that has emerged from the developmental neurobiology literature presents both challenges and opportunities to psychologists seeking to understand the fundamental processes that underlie social and cognitive development, and the neural systems that mediate them. This chapter is intended to provide an overview of some very basic principles of brain development, drawn from contemporary developmental neurobiology, that may be of use to investigators from a wide range of disciplines.     

青少年风险决策的发展认知神经机制

随着认知神经科学技术的发展, 青少年风险决策的发展认知神经机制成为了新近的一个热点课题。从双系统理论模型(社会情感神经网络系统、认知控制神经网络系统)出发, 对与青少年风险决策相关的大脑结构、功能的变化进行了阐述, 重点分析了新近的大脑功能连接、脑网络的研究; 阐述了青少年风险决策认知神经机制的主要理论模型：双系统模型和三角模型。未来研究还应加强对认知神经机制理论模型的检验、整合和创新, 从社会认知神经科学的角度深入研究社会参照系统(同伴关系、亚文化等)在青少年风险决策中的作用及机制, 以及从认知神经层面如何预防和干预青少年高风险行为。     

Ontogenetic changes in the neural mechanisms of eyeblink conditioning

The rodent eyeblink conditioning paradigm is an ideal model system for examining the relationship between neural maturation and the ontogeny of associative learning. Elucidation of the neural mechanisms underlying the ontogeny of learning is tractable using eyeblink conditioning because the necessary neural circuitry (cerebellum and interconnected brainstem nuclei) underlying the acquisition and retention of the conditioned response (CR) has been identified in adult organisms. Moreover, the cerebellum exhibits substantial postnatal anatomical and physiological maturation in rats. The eyeblink CR emerges developmentally between postnatal day (PND) 17 and 24 in rats. A series of experiments found that the ontogenetic emergence of eyeblink conditioning is related to the development of associative learning and not related to changes in performance. More recent studies have examined the relationship between the development of eyeblink conditioning and the physiological maturation of the cerebellum, a brain structure that is necessary for eyeblink conditioning in adult organisms. Disrupting cerebellar development with lesions or antimitotic treatments impairs the ontogeny of eyeblink conditioning. Studies of the development of physiological processes within the cerebellum have revealed striking ontogenetic changes in stimulus-elicited and learning-related neuronal activity. Neurons in the interpositus nucleus and Purkinje cells in the cortex exhibit developmental increases in neuronal discharges following the unconditioned stimulus (US) and in neuronal discharges that model the amplitude and time-course of the eyeblink CR. The developmental changes in CR-related neuronal activity in the cerebellum suggest that the ontogeny of eyeblink conditioning depends on the development of mechanisms that estavlish cerebellar plasticity. Learning and the induction of neural plasticity depend on the magnitude of the US input to the cerebellum. The role of developmental changes in the efficacy of the US pathway has been investigated by monitoring neuronal activity in the inferior olive and with stimulation techniques. The results of these experiments indicate that the development of the conditioned eyeblink response may depend on dynamic interactions between multiple developmental processes within the eyeblink neural circuitry.     

Ontogenetic Changes in the Neural Mechanisms of Eyeblink Conditioning

The rodent eyeblink conditioning paradigm is an ideal model system for examining the relationship between neural maturation and the ontogeny of associative learning. Elucidation of the neural mechanisms underlying the ontogeny of learning is tractable using eyeblink conditioning because the necessary neural circuitry (cerebellum and interconnected brainstem nuclei) underlying the acquisition and retention of the conditioned response (CR) has been identified in adult organisms. Moreover, the cerebellum exhibits substantial postnatal anatomical and physiological maturation in rats. The eyeblink CR emerges developmentally between postnatal day (PND) 17 and 24 in rats. A series of experiments found that the ontogenetic emergence of eyeblink conditioning is related to the development of associative learning and not related to changes in performance. More recent studies have examined the relationship between the development of eyeblink conditioning and the physiological maturation of the cerebellum, a brain structure that is necessary for eyeblink conditioning in adult organisms. Disrupting cerebellar development with lesions or antimitotic treatments impairs the ontogeny of eyeblink conditioning. Studies of the development of physiological processes within the cerebellum have revealed striking ontogenetic changes in stimulus-elicited and learning-related neuronal activity. Neurons in the interpositus nucleus and Purkinje cells in the cortex exhibit developmental increases in neuronal discharges following the unconditioned stimulus (US) and in neuronal discharges that model the amplitude and time-course of the eyeblink CR. The developmental changes in CR-related neuronal activity in the cerebellum suggest that the ontogeny of eyeblink conditioning depends on the development of mechanisms that establish cerebellar plasticity. Learning and the induction of neural plasticity depend on the magnitude of the US input to the cerebellum. The role of developmental changes in the efficacy of the US pathway has been investigated by monitoring neuronal activity in the inferior olive and with stimulation techniques. The results of these experiments indicate that the development of the conditioned eyeblink response may depend on dynamic interactions between multiple developmental processes within the eyeblink neural circuitry.     

人际互动中社会学习的计算神经机制

人类在社会互动中通过他人的行为对他人特质、意图及特定情境下的社会规范进行学习, 是优化决策、维护积极社会互动的重要条件。近年来, 越来越多的研究通过结合计算模型与神经影像技术对社会学习的认知计算机制及其神经基础进行了深入考察。已有研究发现, 人类的社会学习过程能够较好地被强化学习模型与贝叶斯模型刻画, 主要涉及的认知计算过程包括主观期望、预期误差和不确定性的表征以及信息整合的过程。大脑对这些计算过程的执行主要涉及奖惩加工相关脑区(如腹侧纹状体与腹内侧前额叶)、社会认知加工相关脑区(如背内侧前额叶和颞顶联合区)及认知控制相关脑区(如背外侧前额叶)。需要指出的是, 计算过程与大脑区域之间并不是一一映射的关系, 提示未来研究可借助多变量分析与脑网络分析等技术从系统神经科学的角度来考察大尺度脑网络如何执行不同计算过程。此外, 将来研究应注重生态效度, 利用超扫描技术考察真实互动下的社会学习过程, 并更多地关注内隐社会学习的计算与神经机制。     

The development of gyrification in childhood and adolescence

Gyrification is the process by which the brain undergoes changes in surface morphology to create sulcal and gyral regions. The period of greatest development of brain gyrification is during the third trimester of pregnancy, a period of time in which the brain undergoes considerable growth. Little is known about changes in gyrification during childhood and adolescence, although considering the changes in gray matter volume and thickness during this time period, it is conceivable that alterations in the brain surface morphology could also occur during this period of development. The formation of gyri and sulci in the brain allows for compact wiring that promotes and enhances efficient neural processing. If cerebral function and form are linked through the organization of neural connectivity, then alterations in neural connectivity, i.e., synaptic pruning, may also alter the gyral and sulcal patterns of the brain. This paper reviews developmental theories of gyrification, computational techniques for measuring gyrification, and the potential interaction between gyrification and neuronal connectivity. We also present recent findings involving alterations in gyrification during childhood and adolescence.     

Theories of early language acquisition

What features of brain processing and neural development support linguistic development in young children? To what extent is the profile and timing of linguistic development in young children determined by a pre-ordained genetic programme? Does the environment play a crucial role in determining the patterns of change observed in children growing up? Recent experimental, neuroimaging and computational studies of developmental change in children promise to contribute to a deeper understanding of how the brain becomes wired up for language. In this review, the muttidisciplinary perspectives of cognitive neuroscience, experimental psycholinguistics and neural network modelling are brought to bear on four distinct areas in the study of language acquisition: early speech perception, word recognition, word learning and the acquisition of grammatical inflections. It is suggested that each area demonstrates how linguistic development can be driven by the interaction of general learning mechanisms, highly sensitive to particular statistical regularities in the input, with a richly structured environment which provides the necessary ingredients for the emergence of linguistic representations that support mature language processing. Similar epigenetic principles, guiding the emergence of linguistic structure, apply to all these domains, offering insights into phenomena ranging from the precocity of young infant's sensitivity to speech contrasts to the complexities of the problem facing the young child learning the arabic plural.     

Social outcomes in childhood brain disorder: a heuristic integration of social neuroscience and developmental psychology

The authors propose a heuristic model of the social outcomes of childhood brain disorder that draws on models and methods from both the emerging field of social cognitive neuroscience and the study of social competence in developmental psychology/psychopathology. The heuristic model characterizes the relationships between social adjustment, peer interactions and relationships, social problem solving and communication, social-affective and cognitive-executive processes, and their neural substrates. The model is illustrated by research on a specific form of childhood brain disorder, traumatic brain injury. The heuristic model may promote research regarding the neural and cognitive-affective substrates of children's social development. It also may engender more precise methods of measuring impairments and disabilities in children with brain disorder and suggest ways to promote their social adaptation.     

Models provide specificity: Testing a proposed mechanism of visual working memory capacity development

Numerous studies have established that visual working memory has a limited capacity that increases during childhood. However, debate continues over the source of capacity limits and its developmental increase. Simmering (2008) adapted a computational model of spatial cognitive development, the Dynamic Field Theory, to explain not only the source of capacity limitations but also the developmental mechanism. Capacity is limited by the balance between excitation and inhibition that maintains multiple neural representations simultaneously in the model. Development occurs according to the Spatial Precision Hypothesis, which proposes that excitatory and inhibitory connections strengthen throughout early childhood. These changes in connectivity result in increasing precision and stability of neural representations over development. Here we test this developmental mechanism by probing children's memory in a single-item change detection task. Results confirmed the model's predictions, providing further support for this account of visual working memory capacity development.     

Connectionist models of development

How have connectionist models informed the study of development? This paper considers three contributions from specific models. First, connectionist models have proven useful for exploring nonlinear dynamics and emergent properties, and their role in nonlinear developmental trajectories, critical periods and developmental disorders. Second, connectionist models have informed the study of the representations that lead to behavioral dissociations. Third, connectionist models have provided insight into neural mechanisms, and why different brain regions are specialized for different functions. Connectionist and dynamic systems approaches to development have differed, with connectionist approaches focused on learning processes and representations in cognitive tasks, and dynamic systems approaches focused on mathematical characterizations of physical elements of the system and their interactions with the environment. The two approaches also share much in common, such as their emphasis on continuous, nonlinear processes and their broad application to a range of behaviors.     

Is speech learning ‘gated’ by the social brain?

I advance the hypothesis that the earliest phases of language acquisition -- the developmental transition from an initial universal state of language processing to one that is language-specific -- requires social interaction. Relating human language learning to a broader set of neurobiological cases of communicative development, I argue that the social brain 'gates' the computational mechanisms involved in human language learning.     

Neonatal exposure to novel environment enhances hippocampal-dependent memory function during infancy and adulthood

Early life experience affects behavior and brain mechanisms. Handling rats during the first three weeks in life can slow age-related cognitive decline (as measured by a hippocampal-dependent spatial learning task) and reduce age-related hippocampal neuron loss. It is not clear, however, whether this early environmental influence on learning is selective for old age or is more general, affecting cognitive development during infancy and young adulthood as well. We briefly exposed neonatal rats to a novel non-home environment for 3 min daily during the first three weeks of life (as a component of the handling method). We found that this brief early environmental manipulation resulted in enhanced hippocampal-dependent learning immediately after weaning and that this learning enhancement persisted into adulthood. These results suggest that subtle early life events can affect cognitive development in all developmental stages and that changes in neural mechanisms other than neuron number are likely to mediate the learning enhancement at multiple developmental stages.     

Deviations in the emergence of representations: a neuroconstructivist framework for analysing developmental disorders

A common way of studying developmental disorders is to adopt a static neuropsychological deficit approach, in which the brain is characterized in terms of a normal brain with some parts or ‘modules’ impaired. In this paper we outline a neuroconstructivist approach in which developmental disorders are viewed as alternative developmental trajectories in the emergence of representations within neural networks. As a concrete instantiation of the assumptions underlying this general approach, we present a number of simulations in an artificial neural network model. The representations that emerge under different architectural, input and developmental timing conditions are then analysed within a multi‐dimensional state space. We explore alternative developmental trajectories in these simulations, demonstrating how initial differences in the same parameter can lead to very different outcomes, and conversely how different starting states can sometimes result in similar end states (phenotypes). We conclude that the assumptions of the neuroconstructivist approach are likely to be more appropriate for analysing developmental deviations in complex dynamic neural networks, such as the human brain.     

Are developmental disorders like cases of adult brain damage? Implications from connectionist modelling

It is often assumed that similar domain-specific behavioural impairments found in cases of adult brain damage and developmental disorders correspond to similar underlying causes, and can serve as convergent evidence for the modular structure of the normal adult cognitive system. We argue that this correspondence is contingent on an unsupported assumption that atypical development can produce selective deficits while the rest of the system develops normally (Residual Normality), and that this assumption tends to bias data collection in the field. Based on a review of connectionist models of acquired and developmental disorders in the domains of reading and past tense, as well as on new simulations, we explore the computational viability of Residual Normality and the potential role of development in producing behavioural deficits. Simulations demonstrate that damage to a developmental model can produce very different effects depending on whether it occurs prior to or following the training process. Because developmental disorders typically involve damage prior to learning, we conclude that the developmental process is a key component of the explanation of endstate impairments in such disorders. Further simulations demonstrate that in simple connectionist learning systems, the assumption of Residual Normality is undermined by processes of compensation or alteration elsewhere in the system. We outline the precise computational conditions required for Residual Normality to hold in development, and suggest that in many cases it is an unlikely hypothesis. We conclude that in developmental disorders, inferences from behavioural deficits to underlying structure crucially depend on developmental conditions, and that the process of ontogenetic development cannot be ignored in constructing models of developmental disorders.     

发展性计算障碍的最新研究进展

发展性计算障碍是一种影响算术技能获得的特定的学习障碍。截至目前,有关发展性计算障碍的认知与神经机制的理论尚存分歧,有关诊断与鉴别标准也未统一。近年来,对于发展性计算障碍的理论假设有从一般认知因素取向到数学特定因素取向发展的趋势。而随着脑成像技术的不断发展,对于发展性计算障碍神经机制的研究也从针对单个脑区的特异性功能发展到从功能连接网络角度进行研究。并且研究者们开始尝试开发基于数学认知基本理论的干预方法,并采用了利用生物技术手段的新方法。基因-脑-行为的整合研究将有助于全面揭示发展性计算障碍的发生机制,而建立在系统理论基础上经过科学评估的干预手段将可能有效促进障碍者的计算能力。