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Abstract
The present report examines the coinciding results of two study groups each presenting a power-of-two function to describe network structures underlying perceptual processes in one case and word production during verbal fluency tasks in the other. The former is theorized as neural cliques organized according to the function N = 2i − 1, whereas the latter assumes word conglomerations thinkable as tuples following the function N = 2i. Both theories assume the innate optimization of energy efficiency to cause the specific connectivity structure. The vast resemblance between both formulae motivated the development of a common formulation. This was obtained by using a vector space model, in which the configuration of neural cliques or connected words is represented by a N-dimensional state vector. A further analysis of the model showed that the entire time course of word production could be derived using basically one single minimal transformation-matrix. This again seems in line with the principle of maximum energy efficiency.
Highlights
Given the evolutionary need to quickly respond to complex situations, i.e., to behave in an adaptive fashion, nervous systems have developed highly efficient processing and reaction capacities
Motivated by the resemblance between the power-of-two functions derived for Functional Connectivity Motifs (FCM) structures (Tsien, 2015) and word production during verbal fluency (VF) tasks (Ehlen et al, 2016), suggesting similar connectivity patterns, the present study attempts to describe a common formulation for both models
With respect to the theoretical underpinnings, it should first be mentioned that the execution of VF tasks seems consistent with the specific-to-general organization principle proposed by Tsien (2015), in that hierarchization should enable the movement from a given category to various specific examples that are linked by their sub-characteristics as well as by their superordinate concept (Ehlen et al, 2016)
Summary
Reviewed by: Ioan Opris, University of Miami, United States Stephen Allan Selesnick, University of Missouri–St. The present report examines the coinciding results of two study groups each presenting a power-of-two function to describe network structures underlying perceptual processes in one case and word production during verbal fluency tasks in the other The former is theorized as neural cliques organized according to the function N = 2i − 1, whereas the latter assumes word conglomerations thinkable as tuples following the function N = 2i. The vast resemblance between both formulae motivated the development of a common formulation This was obtained by using a vector space model, in which the configuration of neural cliques or connected words is represented by a N-dimensional state vector. A further analysis of the model showed that the entire time course of word production could be derived using basically one single minimal transformation-matrix This again seems in line with the principle of maximum energy efficiency
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