What are the processes, from conception to adulthood, that enable a single cell to grow into a sentient adult? Neuroconstructivism is a pioneering 2 volume work that sets out a whole new framework for considering the complex topic of development, integrating data from cognitive studies, computational work, and neuroimaging.

What makes us conscious? Many theories that attempt to answer this question have appeared recently in the context of widespread interest about consciousness in the cognitive neurosciences. Most of these proposals are formulated in terms of the information processing conducted by the brain. In this overview, we survey and contrast these models. We first delineate several notions of consciousness, addressing what it is that the various models are attempting to explain. Next, we describe a conceptual landscape that addresses how the (...) theories attempt to explain consciousness. We then situate each of several representative models in this landscape and indicate which aspect of consciousness they try to explain. We conclude that the search for the neural correlates of consciousness should be usefully complemented by a search for the computational correlates of consciousness. (shrink)

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. (shrink)

What are the processes, from conception to adulthood, that enable a single cell to grow into a sentient adult? The processes that occur along the way are so complex that any attempt to understand development necessitates a multi-disciplinary approach, integrating data from cognitive studies, computational work, and neuroimaging - an approach till now seldom taken in the study of child development. Neuroconstructivism is a major new 2 volume publication that seeks to redress this balance, presenting an integrative new framework for (...) considering development. In the first volume, the authors review up-to-to date findings from neurobiology, brain imaging, child development, computer and robotic modelling to consider why children's thinking develops the way it does. They propose a new synthesis of development that is based on 5 key principles found to operate at many levels of descriptions. They use these principles to explain what causes a number of key developmental phenomena, including infants' interacting with objects, early social cognitive interactions, and the causes of dyslexia. The "neuroconstructivist" framework also shows how developmental disorders do not arise from selective damage to the normal cognitive system, but instead arise from developmental processes that operate under atypical constraints. How these principles work is illustrated in several case studies ranging from perceptual to social and reading development. Finally, the authors use neuroimaging, behavioural analyses, computational simulations and robotic models to provide a way of understanding the mechanisms and processes that cause development to occur. (shrink)

In the multidisciplinary field of developmental cognitive neuroscience, statistical associations between levels of description play an increasingly important role. One example of such associations is the observation of correlations between relatively common gene variants and individual differences in behavior. It is perhaps surprising that such associations can be detected despite the remoteness of these levels of description, and the fact that behavior is the outcome of an extended developmental process involving interaction of the whole organism with a variable environment. Given (...) that they have been detected, how do such associations inform cognitive-level theories? To investigate this question, we employed a multiscale computational model of development, using a sample domain drawn from the field of language acquisition. The model comprised an artificial neural network model of past-tense acquisition trained using the backpropagation learning algorithm, extended to incorporate population modeling and genetic algorithms. It included five levels of description—four internal: genetic, network, neurocomputation, behavior; and one external: environment. Since the mechanistic assumptions of the model were known and its operation was relatively transparent, we could evaluate whether cross-level associations gave an accurate picture of causal processes. We established that associations could be detected between artificial genes and behavioral variation, even under polygenic assumptions of a many-to-one relationship between genes and neurocomputational parameters, and when an experience-dependent developmental process interceded between the action of genes and the emergence of behavior. We evaluated these associations with respect to their specificity, to their developmental stability, and to their replicability, as well as considering issues of missing heritability and gene–environment interactions. We argue that gene–behavior associations can inform cognitive theory with respect to effect size, specificity, and timing. The model demonstrates a means by which researchers can undertake multiscale modeling with respect to cognition and develop highly specific and complex hypotheses across multiple levels of description. (shrink)

Differences in socioeconomic status (SES) correlate both with differences in cognitive development and in brain structure. Associations between SES and brain measures such as cortical surface area and cortical thickness mediate differences in cognitive skills such as executive function and language. However, causal accounts that link SES, brain, and behavior are challenging because SES is a multidimensional construct: correlated environmental factors, such as family income and parental education, are only distal markers for proximal causal pathways. Moreover, the causal accounts themselves (...) must span multiple levels of description, employ a developmental perspective, and integrate genetic effects on individual differences. Nevertheless, causal accounts have the potential to inform policy and guide interventions to reduce gaps in developmental outcomes. In this article, we review the range of empirical data to be integrated in causal accounts of developmental effects on the brain and cognition associated with variation in SES. We take the specific example of language development and evaluate the potential of a multiscale computational model of development, based on an artificial neural network, to support the construction of causal accounts. We show how, with bridging assumptions that link properties of network structure to magnetic resonance imaging (MRI) measures of brain structure, different sets of empirical data on SES effects can be connected. We use the model to contrast two possible causal pathways for environmental influences that are associated with SES: differences in prenatal brain development and differences in postnatal cognitive stimulation. We then use the model to explore the implications of each pathway for the potential to intervene to reduce gaps in developmental outcomes. The model points to the cumulative effects of social disadvantage on multiple pathways as the source of the poorest response to interventions. Overall, we highlight the importance of implemented models to test competing accounts of environmental influences on individual differences. (shrink)

We address two points in this commentary. First, we question the extent to which O'Brien & Opie have established that the classical approach is unable to support a viable vehicle theory of consciousness. Second, assuming that connectionism does have the resources to support a vehicle theory, we explore how the activity of the units of a PDP network might sum together to form phenomenal experience (PE).

We argue that are no such things as literal categories in human cognition. Instead, we argue that there are merely temporary coalescences of dimensions of similarity, which are brought together by context in order to create the similarity structure in mental representations appropriate for the task at hand. Fodor contends that context‐sensitive cognition cannot be realised by current computational theories of mind. We address this challenge by describing a simple computational implementation that exhibits internal knowledge representations whose similarity structure alters (...) fluidly depending on context. We explicate the processing properties that support this function and illustrate with two more complex models, one applied to the development of semantic knowledge , the second to the processing of simple metaphorical comparisons . The models firstly demonstrate how phenomena that seem problematic for literal categorisation resolve to particular cases of the contextual modulation of mental representations; and secondly prompt a new perspective on the relation between language and thought: language affords the strategic control of context on semantic knowledge, allowing information to be brought to bear in a given situation that might otherwise not be available to influence processing. This may explain one way in which human thought is creative, and distinctive from animal cognition. (shrink)

In this response, we consider four main issues arising from the commentaries to the target article. These include further details of the theory of interactive specialization, the relationship between neuroconstructivism and selectionism, the implications of neuroconstructivism for the notion of representation, and the role of genetics in theories of development. We conclude by stressing the importance of multidisciplinary approaches in the future study of cognitive development and by identifying the directions in which neuroconstructivism can expand in the Twenty-first Century.