What is universal and what differs in language development?

Goldin-Meadow (2015) presents an exceptional synthesis of work from studies of children acquiring language under variable circumstances of input or processing abilities. Deaf children who acquire homesign without any well- formed model from which to learn language represent a powerful example. Goldin-Meadow argues that the resilient properties of language that nevertheless emerge include simple syntactic structures, hierarchical organisation, markers modulating the meaning of sentences, and social- communicative functions. Among the fragile or input-dependent properties are the orders that the language follows, the parts into which words are decomposed, and the features that distinguish nominals from predicates. Separation of these two types of properties poses questions concerning the innate constraints on language acquisition (perhaps these equate to the resilient properties) and concerning the specificity of processes to language (e.g., whether properties such as hierarchical organisation are specific to language or originate in the structure of thought). The study of the resilient properties of human language in the face of adversity, and the relation of these properties to the information that is encoded in the human genome, represent a research strategy that draws inferences about species universals (properties that all humans share) from data about individual differences (factors that make humans different from one another). In the following, we suggest three reasons to be cautious about this approach

What can the study of genetics offer to educators? Mind, Brain, and Education

This article explores the potential contribution of modern genetic methods and findings to education. It is familiar to hear that the ‘gene’ for this or that behavior has been discovered, or that certain skills are ‘highly heritable’. Can this help educators? To explore this, we describe the methods used to relate genetic variation to individual differences in high-level behaviors such as academic skills and educational achievement. These methods include twin studies and genome-wide association studies. We address the key question of what genetic data imply about the ability of educators to optimize educational outcomes for children across the range of abilities

Educational neuroscience: progress and prospects

Educational neuroscience is an interdisciplinary research field that seeks to translate research findings on neural mechanisms of learning to educational practice and policy, and to understand the effects of education on the brain. Neuroscience and education can interact directly, by virtue of considering the brain as a biological organ that needs to be in the optimal condition to learn (‘brain health’); or indirectly, as neuroscience shapes psychological theory and psychology influences education. In this article, we trace the origins of educational neuroscience, its main areas of research activity, and the principal challenges it faces as a translational field. We consider how a pure psychology approach that ignores neuroscience is at risk of being misleading for educators. We address the major criticisms of the field, respectively comprising a priori arguments against the relevance of neuroscience to education, reservations with the current practical operation of the field, and doubts about the viability of neuroscience methods for diagnosing disorders or predicting individual differences. We consider future prospects of the field and ethical issues it raises. Finally, we discuss the challenge of responding to the (welcome) desire of education policymakers to include neuroscience evidence in their policymaking, while ensuring recommendations do not exceed the limitations of current basic science

Quantities of qualia.

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)

Consciousness: mapping the theoretical landscape

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

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