The underconnectivity theory of autism attributes the disorder to lower anatomical and functional systems connectivity between frontal and more posterior cortical processing. Here we review evidence for the theory and present a computational model of an executive functioning task (Tower of London) implementing the assumptions of underconnectivity. We make two modifications to a previous computational account of performance and brain activity in typical individuals in the Tower of London task (Newman et al., 2003): (1) the communication bandwidth between frontal and parietal areas was decreased and (2) the posterior centers were endowed with more executive capability (i.e., more autonomy, an adaptation is proposed to arise in response to the lowered frontal-posterior bandwidth). The autism model succeeds in matching the lower frontal-posterior functional connectivity (lower synchronization of activation) seen in fMRI data, as well as providing insight into behavioral response time results. The theory provides a unified account of how a neural dysfunction can produce a neural systems disorder and a psychological disorder with the widespread and diverse symptoms of autism.

Recent research in cognitive and developmental neuroscience is providing a new approach to the understanding of dyscalculia that emphasizes a core deficit in understanding sets and their numerosities, which is fundamental to all aspects of elementary school mathematics. The neural bases of numerosity processing have been investigated in structural and functional neuroimaging studies of adults and children, and neural markers of its impairment in dyscalculia have been identified. New interventions to strengthen numerosity processing, including adaptive software, promise effective evidence-based education for dyscalculic learners.

This study triangulates executive planning and visuo-spatial reasoning in the context of the Tower of London (TOL) task by using a variety of methodological approaches. These approaches include functional magnetic resonance imaging (fMRI), functional connectivity analysis, individual difference analysis, and computational modeling. A graded fMRI paradigm compared the brain activation during the solution of problems with varying path lengths: easy (1 and 2 moves), moderate (3 and 4 moves) and difficult (5 and 6 moves). There were three central findings regarding the prefrontal cortex: (1) while both the left and right prefrontal cortices were equally involved during the solution of moderate and difficult problems, the activation on the right was differentially attenuated during the solution of the easy problems; (2) the activation observed in the right prefrontal cortex was highly correlated with individual differences in working memory (measured independently by the reading span task); and (3) different patterns of functional connectivity were observed in the left and right prefrontal cortices. Results obtained from the superior parietal region also revealed left/right differences; only the left superior parietal region revealed an effect of difficulty. These fMRI results converged upon two hypotheses: (1) the right prefrontal area may be more involved in the generation of a plan, whereas the left prefrontal area may be more involved in plan execution; and (2) the right superior parietal region is more involved in attention processes while the left homologue is more of a visuo-spatial workspace. A 4CAPS computational model of the cognitive processes and brain activation in the TOL task integrated these hypothesized mechanisms, and provided a reasonably good fit to the observed behavioral and brain activation data. The multiple research approaches presented here converge on a deepening understanding of the combination of perceptual and conceptual processes in this type of visual problem solving.

Educational neuroscience is an emerging effort to integrate neuroscience methods, particularly functional neuroimaging, with behavioral methods to address issues of learning and instruction. This article consolidates common concerns about connecting education and neuroscience. One set of concerns is scientific: in-principle differences in methods, data, theory, and philosophy. The other set of concerns is pragmatic: considerations of costs, timing, locus of control, and likely payoffs. The authors first articulate the concerns and then revisit them, reinterpreting them as potential opportunities. They also provide instances of neuroscience findings and methods that are relevant to education. The goal is to offer education researchers a window into contemporary neuroscience to prepare them to think more specifically about the prospects of educational neuroscience.

The relationship of the mind to the brain has established itself at the forefront of scientific interest in large part because of the rapid development of functional magnetic resonance imaging (fMRI). Exciting new findings have often been expressed in the form of compelling images that indicate that brain areas become activated in various tasks or fail to activate in various special populations. These brain images appear to tell a simple and straightforward story. The invited inference is that a one-to-one mapping exists between the activation of brain areas and the execution of certain psychological processes, such as the process of perceiving a face. At first glance, this story imposes some order on the results; some consistencies emerge across brain imaging studies, and some imaging results seem to be related to studies of brain lesions in neuropsychological patients. But the consistencies are limited in scope, and the mapping between the infinity of possible tasks and the finite-indeed, rather small-number of activating brain areas identified by neuroimaging techniques is greatly underdetermined, if not logically troubling. We propose that the idea of a one-to-one mapping of cortical activation to high-level cognitive processes that is suggested by the brain activation images is incorrect-a gross oversimplification of a more complex (and more interesting) many-to-many mapping, governed by more subtle organizational principles. In brief, we argue that thinking is a network phenomenon and suggest the beginnings of a theory of the organization of cortical networks.This article explores how the various cortical areas that subserve cognition might function in conjunction with each other. The main objectives are to specify the operating principles that govern the complex, dynamic, and adaptive relationships among brain areas and to relate brain function to cognitive function. It is not our goal here to specify the cognitive specializations of each brain area, although to describe how areas work together, we necessarily have to hypothesize the cognitive endowments of some brain areas. We believe there is value in developing a theory of how various brain areas collaborate in order to realize cognitive information processing, despite the remaining uncertainty about the functional specializations of the individual areas.As functional imaging provides progressively finer detail about brain activation, computational modeling provides a theory-building workspace in which the new pieces of information can be put together and their cofunctioning can be examined. In this workspace, the component mechanisms can be specified in detail and their ability to account for the observed phenomena can be tested, as a few initial attempts have shown (Arbib, Billard, Iacoboni, & Oztop, 2000; Fincham, Carter, van Veen, Stenger, & Anderson, 2002;Horwitz & Tagamets, 1999;Just, Carpenter, & Varma, 1999). One of the goals of this study is to instantiate the operating principles in a cognitive neuroarchitecture, 4CAPS, that has been develop...

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In his recent critique of Educational Neuroscience, Bowers argues that neuroscience has no role to play in informing education, which he equates with classroom teaching. Neuroscience, he suggests, adds nothing to what we can learn from psychology. In this commentary, we argue that Bowers' assertions misrepresent the nature and aims of the work in this new field. We suggest that, by contrast, psychological and neural levels of explanation complement rather than compete with each other. Bowers' analysis also fails to include a role for educational expertise -a guiding principle of our new field. On this basis, we conclude that his critique is potentially misleading.We set out the well-documented goals of research in Educational Neuroscience, and show how, in collaboration with educators, significant progress has already been achieved, with the prospect of even greater progress in the future.

Bruer (1997) advocated connecting neuroscience and education indirectly through the intermediate discipline of psychology. We argue for a parallel route: the neurobiology of learning, and in particular the core concept of plasticity, have the potential to directly transform teacher preparation and professional development, and ultimately to affect how students think about their own learning. We present a case study of how the core concepts of neuroscience can be brought to in-service teachers – the BrainU workshops. We then discuss how neuroscience can be meaningfully integrated into pre-service teacher preparation, focusing on institutional and cultural barriers.