This paper elaborates a novel hypothesis regarding the observed predictive relation between finger gnosis and mathematical ability. In brief, we suggest that these two cognitive phenomena have overlapping neural substrates, as the result of the re-use (“redeployment”) of part of the finger gnosis circuit for the purpose of representing number. We offer some background on the relation and current explanations for it; an outline of our alternate hypothesis; some evidence supporting redeployment over current views; and a plan for further research.

This paper introduces a very simple analytic method for mining large numbers of brain imaging experiments to discover functional cooperation between regions. We then report some preliminary results of its application, illustrate some of the many future projects in which we expect the technique will be of considerable use (including a way to relate fMRI to EEG), and describe a research resource for investigating functional cooperation in the cortex that will be made publicly available through the lab website. One significant finding is that differences between cognitive domains appear to be attributable more to differences in patterns of cooperation between brain regions, rather than to differences in which brain regions are used in each domain. This is not a result that is predicted by prevailing localization‐based and modular accounts of the organization of the cortex. Introduction and Background Hardly an issue of Science or Nature goes by without creating a stir over the discovery of “the” gene for some disease, trait, or predisposition, or “the ” brain area responsible for some behavior or cognitive capacity. Of course, we know better; the isolable parts of complex systems like the

This paper details and applies a novel method for assigning function to local cortical structure. Imaging results from multiple cognitive domains were used to investigate what a shared neural substrate could be contributing to two apparently different domains: finger and number representation. We identified a region within the left precentral gyrus contributing to both tasks; identified, across several cognitive domains, other cognitive uses to which the ROI may have been put; and looked across these cognitive uses to ascertain the functional contribution of the ROI. The result of this process is a proposed local working—an array of pointers—that can be tested empirically and will allow for further elaboration of the redeployment view of the relation between finger and number representations. This work is significant for understanding the relationship between finger gnosis and math, and for introducing cross-domain modeling as a new empirical method.

Abstract: This paper lays out some of the empirical evidence for the importance of neural reuse—the reuse of existing (inherited and/or early-developing) neural circuitry for multiple behavioral purposes—in defining the overall functional structure of the brain. We then discuss in some detail one particular instance of such reuse: the involvement of a local neural circuit in finger awareness, number representation, and other diverse functions. Finally, we consider whether and how the notion of a developmental homology can help us understand the relationships between the cognitive functions that develop out of shared neural supports. How are neural resources deployed to support cognitive functioning in the adult organism, and how does that architecture come about? That is, what evolutionary and developmental pathways does the brain follow in acquiring its repertoire of capacities? Consider two possible options, one that has been largely identified with the embodied/embedded school of cognitive science, and another associated with evolutionary psychology. A long-standing guiding principle of both embodied cognitive science (ECS) and evolutionary psychology (EvoPsy) is that cognition was built within a system primarily fitted to situated action. The central nervous system—the neocortex most definitely included—is first and

There are many research programs in cognitive science that urge a re-orientation under the banner of "embodied cognition. " Most of these programs promote a rather radical alternative to "standard " or "classical " cognitivism (for a recent review, see Shapiro 2011). Despite the common label, the programs are very heterogeneous, and I shall make no attempt here to survey them or offer any taxonomy. The present paper also uses the label of "embodied cognition, " but it advances a rather moderate conception of embodiment-oriented cognitive science. While highlighting the pervasiveness in cognition of bodily factors, it does not invoke this as a ground for revolutionizing the methodology of cognitive science. There are two core elements in my approach. The first element appeals to the idea of bodily representational codes (or formats), i.e., hypothesized mental codes that are primarily, or fundamentally, utilized in forming interoceptive or directive representations of one's own bodily states and activities (Goldman and Vignemont 2009). The second element of the approach adduces wide-ranging evidence that the brain reuses or redeploys cognitive processes that have different original uses. If this redeployment idea is applied

The study of errors allows researchers insight into the production of speech. Speech errors have been shown to accommodate in form to their erroneous environment, demonstrating that errors occur before the processing of the phonological rule component. That this configuration is a complete picture of the processing involved, however, has been called into question by the prevalence of nonaccommodated errors that have been detected via instrumental analysis (Gormley 2008). This paper presents a model of speech production developed using Python ACT-R (Stewart & West, 2007a) that uses a noisy recall system and explicit encoding of phonological rules. This system produces both accommodated and mismatch speech errors at the same rates as observed in the empirical study.

The paper outlines some of the broad architectural implications of the modularity thesis, and reports on an attempt to test for them. The method involved analysing 472 functional magnetic resonance imaging experiments in eight cognitive domains to discover which brain regions co-operated with which others, under what conditions. The results indicate that the same brain regions contribute to functions across various cognitive domains, but in each domain co-operate with one another in different patterns. This does not appear to be compatible with the modularity thesis. The paper discusses the implications of the finding for the best approach to the design and implementation of intelligent systems in general, and of language-using robots in particular. Implications for the best approach to analysing and modelling cognitive functions will also be discussed.

Abstract not found

The neurobiology of imagination: possible role of

Artificial intelligence (AI) is the field of research that strives to understand, design and build cognitive systems. From computer programs that can beat top international grand masters at chess to robots that can help detect improvised explosive devices in war, AI has had many successes. As a science, it differs