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.

Three‐ to 4‐month‐old infants show asymmetric exclusivity in the acquisition of cat and dog perceptual categories. The cat perceptual category excludes dog exemplars, but the dog perceptual category does not exclude cat exemplars. We describe a connectionist autoencoder model of perceptual categorization that shows the same asymmetries as infants. The model predicts the presence of asymmetric retroactive interference when infants acquire cat and dog categories sequentially. A subsequent experiment conducted with 3‐ to 4‐month‐olds verifies the predicted pattern of looking time (...) behaviors. We argue that bottom‐up, associative learning systems with distributed representations are appropriate for modeling the operation of short‐term visual memory in early perceptual category learning. (shrink)

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 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)

The development of analogical reasoning has traditionally been understood in terms of theories of adult competence. This approach emphasizes structured representations and structure mapping. In contrast, we argue that by taking a developmental perspective, analogical reasoning can be viewed as the product of a substantially different cognitive ability – relational priming. To illustrate this, we present a computational (here connectionist) account where analogy arises gradually as a by-product of pattern completion in a recurrent network. Initial exposure to a situation primes (...) a relation that can then be applied to a novel situation to make an analogy. Relations are represented as transformations between states. The network exhibits behaviors consistent with a broad range of key phenomena from the developmental literature, lending support to the appropriateness of this approach (using low-level cognitive mechanisms) for investigating a domain that has normally been the preserve of high-level models. Furthermore, we present an additional simulation that integrates the relational priming mechanism with deliberative controlled use of inhibition to demonstrate how the framework can be extended to complex analogical reasoning, such as the data from explicit mapping studies in the literature on adults. This account highlights how taking a developmental perspective constrains the theory construction and cognitive modeling processes in a way that differs substantially from that based purely on adult studies, and illustrates how a putative complex cognitive skill can emerge out of a simple mechanism. (shrink)

A mature science strives to provide causal explanations of observed phenomena rather than focusing on taxonomic descriptions of data. A field theory model is a step towards providing a truly scientific account of development. However, the model is under-constrained in that it ignores the boundary conditions defined by the physical constraints imposed by the infant's developing brain and body.

Missing from Quartz & Sejnowski's (Q&S's) unique and valuable effort to relate cognitive development to neural constructivism is an examination of the global emergent properties of adding new neural circuits. Such emergent properties can be studied with computational models. Modeling with generative connectionist networks shows that synaptogenic mechanisms can account for progressive increases in children's representational power.

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 normal cognitive systems, 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. Computer and robotic models provide concrete tools for investigating the processes and mechanisms involved in learning and development. Volume 2 illustrates the principles of 'Neuroconstructivist' development, with contributions from 9 different labs across the world. Each of the contributions illustrates how models play a central role in understanding development. The models presented include standard connectionist neural network models as well as multi-agent models. Also included are robotic models emphasizing the need to take embodiment and brain-system interactions seriously. A model of Autism and one of Specific Language Impairment also illustrate how atypical development can be understood in terms of the typical processes of development but operating under restricted conditions. This volume complements Volume 1 by providing concrete examples of how the 'Neuroconstructivist' principles can be grounded within a diverse range of domains, thereby shaping the research agenda in those domains. (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. Computer and robotic models provide concrete tools for investigating the processes and mechanisms involved in learning and development. Volume 2 illustrates the principles of 'Neuroconstructivist' development, with contributions from 9 different labs across the world. Each of the contributions illustrates how models play a central role in understanding development. The models presented include standard connectionist neural network models as well as multi-agent models. Also included are robotic models emphasizing the need to take embodiment and brain-system interactions seriously. A model of Autism and one of Specific Language Impairment also illustrate how atypical development can be understood in terms of the typical processes of development but operating under restricted conditions. This volume complements Volume 1 by providing concrete examples of how the 'Neuroconstructivist' principles can be grounded within a diverse range of domains, thereby shaping the research agenda in those domains. (shrink)

Norman presents intriguing arguments in support of a mapping between ecological and constructivist visual cognition, on the one hand, onto the dorsal ventral dual route processing hypothesis, on the other hand. Unfortunately, his account is incompatible with developmental data on the functional emergence of the dorsal and ventral routes. We argue that it is essential for theories of adult visual cognition to take constraints from development seriously.

Human adults appear different from other animals in their ability to form abstract mental representations that go beyond perceptual similarity. In short, they can conceptualize the world. This book brings together leading psychologists and neuroscientists to tackle the age-old puzzle of what might be unique about human concepts.

In this response, we reiterate the importance of development (both ontogenetic and phylogenetic) in the understanding of a complex cognitive skill – analogical reasoning. Four key questions structure the response: Does relational priming exist, and is it sufficient for analogy? What do we mean by relations as transformations? Could all or any relations be represented as transformations? And what about the challenge of more complex analogies? In addressing these questions we bring together a number of supportive commentaries, strengthening our emergentist (...) case for analogy (in particular with insights from comparative psychology), and review new supportive evidence. We also rebut those commentaries that ignore development at their peril. Along the way, we revisit the main assumptions underlying the analogy as relational priming (ARP) account of analogy, clarifying and elaborating as necessary. (shrink)

Connectionist models aiming to reveal the mechanisms of atypical development must in their undamaged form constitute plausible models of normal development and follow a developmental trajectory that matches empirical data. Constructivist models that adapt their structure to the learning task satisfy this demand. They are therefore more informative in the study of atypical development than the static models employed by Thomas & Karmiloff-Smith (T&K-S).

Human control of action in routine situations involves a flexible interplay between (a) task-dependent serial ordering constraints; (b) top-down, or intentional, control processes; and (c) bottom-up, or environmentally triggered, affordances. In addition, the interaction between these influences is modulated by learning mechanisms that, over time, appear to reduce the need for top-down control processes while still allowing those processes to intervene at any point if necessary or if desired. We present a model of the acquisition and control of goal-directed action (...) that goes beyond existing models by operationalizing an interface between two putative systems—a routine and a non-routine system—thereby demonstrating how explicitly represented goals can interact with the emergent task representations that develop through learning in the routine system. The gradual emergence of task representations offers an explanation for the transfer of control with experience from the non-routine goal-based system to the routine system. At the same time it allows action selection to be sensitive both to environmental triggers and to biasing from multiple levels within the goal system. (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)

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.

According to Aristotelian essentialism, the nature of an organism is constituted of a particular goal-directed disposition to produce an organism typical of its kind. This paper argues—against the prevailing orthodoxy—that essentialism of this sort is indispensable to evolutionary biology. The most powerful anti-essentialist arguments purport to show that the natures of organisms play no explanatory role in modern synthesis biology. I argue that recent evolutionary developmental biology provides compelling evidence to the contrary. Developmental biology shows that one must appeal to (...) the capacities of organisms to explain what makes adaptive evolution adaptive. Moreover, the specific capacities in question are precisely those that, according to Aristotle, constitute the nature of an organism. Essentialism 1.1 Aristotelian biological kinds Evolutionary anti-essentialism 2.1 Taxonomic anti-essentialism 2.2 Explanatory anti-essentialism Adaptation 3.1 Stability 3.2 Mutability 3.3 Phenotypic plasticity and adaptive evolution The natures of organisms Conclusion. (shrink)

There are two general approaches to characterising biological functions. One originates with Cummins. According to this approach, the function of a part of a system is just its causal contribution to some specified activity of the system. Call this the ‘C-function’ concept. The other approach ties the function of a trait to some aspect of its evolutionary significance. Call this the ‘E-function’ concept. According to the latter view, a trait's function is determined by the forces of natural selection. The C-function (...) and E-function concepts are clearly quite different, but there is an important relation between them which heretofore has gone unnoticed. The purpose of this paper is to outline that relation.This is not the first paper to discuss the relation of C-function and E-function. Previous attempts all follow either one of two strategies. The first proposes that the two concepts are ‘unified.’ The other proposes that they are radically distinct and apply to wholly different fields within biology. (shrink)

We distinguish dynamical and statistical interpretations of evolutionary theory. We argue that only the statistical interpretation preserves the presumed relation between natural selection and drift. On these grounds we claim that the dynamical conception of evolutionary theory as a theory of forces is mistaken. Selection and drift are not forces. Nor do selection and drift explanations appeal to the (sub-population-level) causes of population level change. Instead they explain by appeal to the statistical structure of populations. We briefly discuss the implications (...) of the statistical interpretation of selection for various debates within the philosophy of biologythe `explananda of selection' debate and the `units of selection' debate. (shrink)

Due to the transformation of digital media, the notion of “publicity” has become problematic. In most cases, the debate is focused on the question whether the internet causes a decline of so-called civic publicity or rather intensifies and pluralizes it. Rudolf Maresch outlines Jürgen Habermas's famous study of this category and challenges his claim concerning its “structural transformation,” referring to the governmental and medial processes which have always already controlled every form of communication. Publicity, he claims, is an epiphenomenon not (...) only of print media, but of a general addressability of subjects, that has been produced previously by postal services. Today, he concludes, publicity is a concept that competes with other offers of mass media, which are all based on criteria of novelty and excitement. Mercedes Bunz also notes the expansion and pluralization of the public sphere due to the change of digital media, but sees the crucial issues in the design and distribution of knowledge and power by evaluation. So-called human beings no longer decide on the dissemination and evaluation of information, but algorithms, which are for the most part concealed from the public sphere that they produce in the first place. Both authors agree that a pluralization of public sphere(s) has taken place, while Habermas's notion of publicity refers to a single public sphere. German Durch den digitalen Medienwandel ist der Begriff der Öffentlichkeit problematisch geworden. Die Debatte fokussiert sich zumeist auf die Frage, ob die sogenannte bürgerliche Öffentlichkeit durch das Internet im Niedergang begriffen ist oder eine Intensivierung und Pluralisierung erfährt. Rudolf Maresch zeichnet die berühmte Untersuchung der Kategorie durch Jürgen Habermas nach und zieht den von ihm konstatierten Strukturwandel der Öffentlichkeit in Zweifel. Dagegen verweist er auf die gouvernementalen und medialen Prozesse, die jede Form von Kommunikation immer schon gesteuert haben. Öffentlichkeit sei daher ein Epiphänomen nicht allein des Zeitungswesens, sondern der bereits vorgängig ergangenen postalischen Herstellung einer allgemeinen Adressierbarkeit von Subjekten. Heute sei Öffentlichkeit innerhalb der auf Novitäts- und Erregungskriterien abstellenden Massenmedien ein mit anderen Angeboten konkurrierendes Konzept. Mercedes Bunz konstatiert ebenfalls eine Ausweitung und Pluralisierung von Öffentlichkeit durch den digitalen Medienwandel, sieht aber die entscheidenden Fragen in der Konzeption und Verteilung von Evaluationswissen und Evaluationsmacht. Nicht mehr die sogenannten Menschen, sondern Algorithmen entscheiden über die Verbreitung und Bewertung von Nachrichten. Diese sind in der Öffentlichkeit – die sie allererst erzeugen – weitgehend verborgen. Einig sind sich die Autoren darin, dass es zu einer Pluralisierung von Öffentlichkeiten gekommen ist, während der Öffentlichkeitsbegriff von Habermas auf eine singuläre Öffentlichkeit abstellt. (shrink)

Durch den digitalen Medienwandel ist der Begriff der Öffentlichkeit problematisch geworden. Die Debatte fokussiert sich zumeist auf die Frage, ob die sogenannte bürgerliche Öffentlichkeit durch das Internet im Niedergang begriffen ist oder eine Intensivierung und Pluralisierung erfährt. Rudolf Maresch zeichnet die berühmte Untersuchung der Kategorie durch Jürgen Habermas nach und zieht den von ihm konstatierten Strukturwandel der Öffentlichkeit in Zweifel. Dagegen verweist er auf die gouvernementalen und medialen Prozesse, die jede Form von Kommunikation immer schon gesteuert haben. Öffentlichkeit sei daher (...) ein Epiphänomen nicht allein des Zeitungswesens, sondern der bereits vorgängig ergangenen postalischen Herstellung einer allgemeinen Adressierbarkeit von Subjekten. Heute sei Öffentlichkeit innerhalb der auf Novitäts- und Erregungskriterien abstellenden Massenmedien ein mit anderen Angeboten konkurrierendes Konzept. Mercedes Bunz konstatiert ebenfalls eine Ausweitung und Pluralisierung von Öffentlichkeit durch den digitalen Medienwandel, sieht aber die entscheidenden Fragen in der Konzeption und Verteilung von Evaluationswissen und Evaluationsmacht. Nicht mehr die sogenannten Menschen, sondern Algorithmen entscheiden über die Verbreitung und Bewertung von Nachrichten. Diese sind in der Öffentlichkeit – die sie allererst erzeugen – weitgehend verborgen. Einig sind sich die Autoren darin, dass es zu einer Pluralisierung von Öffentlichkeiten gekommen ist, während der Öffentlichkeitsbegriff von Habermas auf eine singuläre Öffentlichkeit abstellt. Due to the transformation of digital media, the notion of “publicity” has become problematic. In most cases, the debate is focused on the question whether the internet causes a decline of so-called civic publicity or rather intensifies and pluralizes it. Rudolf Maresch outlines Jürgen Habermas's famous study of this category and challenges his claim concerning its “structural transformation,” referring to the governmental and medial processes which have always already controlled every form of communication. Publicity, he claims, is an epiphenomenon not only of print media, but of a general addressability of subjects, that has been produced previously by postal services. Today, he concludes, publicity is a concept that competes with other offers of mass media, which are all based on criteria of novelty and excitement. Mercedes Bunz also notes the expansion and pluralization of the public sphere due to the change of digital media, but sees the crucial issues in the design and distribution of knowledge and power by evaluation. So-called human beings no longer decide on the dissemination and evaluation of information, but algorithms, which are for the most part concealed from the public sphere that they produce in the first place. Both authors agree that a pluralization of public sphere(s) has taken place, while Habermas's notion of publicity refers to a single public sphere. (shrink)

Over the past fifteen years there has been a considerable amount of debate concerning what theoretical population dynamic models tell us about the nature of natural selection and drift. On the causal interpretation, these models describe the causes of population change. On the statistical interpretation, the models of population dynamics models specify statistical parameters that explain, predict, and quantify changes in population structure, without identifying the causes of those changes. Selection and drift are part of a statistical description of population (...) change; they are not discrete, apportionable causes. Our objective here is to provide a definitive statement of the statistical position, so as to allay some confusions in the current literature. We outline four commitments that are central to statisticalism. They are: 1. Natural Selection is a higher order effect; 2. Trait fitness is primitive; 3. Modern Synthesis (MS)-models are substrate neutral; 4. MS-selection and drift are model-relative. (shrink)

There are two competing interpretations of the modern synthesis theory of evolution: the dynamical (also know as ‘traditional’) and the statistical. The dynamical interpretation maintains that explanations offered under the auspices of the modern synthesis theory articulate the causes of evolution. It interprets selection and drift as causes of population change. The statistical interpretation holds that modern synthesis explanations merely cite the statistical structure of populations. This paper offers a defense of statisticalism. It argues that a change in trait frequencies (...) in a population can be attributed only to selection or drift against the background of a particular statistical description of the population. The traditionalist supposition that selection and drift are description‐independent causes of population change leads the dynamical interpretation into a dilemma: it must face a contradiction or accept the loss of explanatory power. (shrink)

The concept of the environment appears to be indispensably involved in adaptive explanation. Quite what its role is, however, is a matter of some dispute. The environment is customarily viewed as the dual of the organism; a wholly external, discrete, autonomous cause of evolution. On this view, the external environment is the principal cause of the adaptedness of form, and the determinant of what it is to be an adaptation. I argue that this conception of the environment neither adequately explains (...) nor individuates evolutionary adaptations. Instead, adaptation, properly construed, is an evolutionary response to affordances. The environment, traditionally construed, underdetermines an organism’s affordances. Instead, I argue that the environment takes its place in evolutionary models not as a discrete causal entity, but as an abstraction. (shrink)

In evolutionary biology changes in population structure are explained by citing trait fitness distribution. I distinguish three interpretations of fitness explanations—the Two‐Factor Model, the Single‐Factor Model, and the Statistical Interpretation—and argue for the last of these. These interpretations differ in their degrees of causal commitment. The first two hold that trait fitness distribution causes population change. Trait fitness explanations, according to these interpretations, are causal explanations. The last maintains that trait fitness distribution correlates with population change but does not cause (...) it. My defense of the Statistical Interpretation relies on a distinctive feature of causation. Causes conform to the Sure Thing Principle. Trait fitness distributions, I argue, do not. *Received July 2009; revised October 2009. †To contact the author, please write to: Department of Philosophy/Institute for the History, Philosophy of Science and Technology, University of Toronto, Victoria College, 91 Charles Street West, Toronto, ON M5S 1K7, Canada; e‐mail: denis[email protected]. (shrink)

According to a prominent view of evolutionary theory, natural selection and the processes of development compete for explanatory relevance. Natural selection theory explains the evolution of biological form insofar as it is adaptive. Development is relevant to the explanation of form only insofar as it constrains the adaptation-promoting effects of selection. I argue that this view of evolutionary theory is erroneous. I outline an alternative, according to which natural selection explains adaptive evolution by appeal to the statistical structure of populations, (...) and development explains the causes of adaptive evolution at the level of individuals. Only together can a statistical theory of selection and a mechanical theory of development explain why populations of organisms comprise individuals that are adapted to their conditions of existence. (shrink)

Psychological individualism is motivated by two taxonomic principles: (i) that psychological states are individuated by their causal powers, and (ii) that causal powers supervene upon intrinsic physiological state. I distinguish two interpretations of individualism--the 'orthodox' and the 'alternative'--each of which is consistent with these motivating principles. I argue that the alternative interpretation is legitimately individualistic on the grounds that it accurately reflects the actual taxonomic practices of bona fide individualistic sciences. The classification of homeobox genes in developmental genetics provides an (...) illustration. When applied to the taxonomy of psychological kinds, alternative individualism has some surprising consequences. In particular, externalist taxonomies of thought are consistent with the alternative interpretation, and hence consistent with individualism. I conclude, on this basis, that the individualism/externalism dispute which has long preoccupied philosophy of psychology is an empty one. (shrink)