Neurocomputational Consequences of Evolutionary Connectivity Changes in Perisylvian Language Cortex
Schomers, M.R.; Garagnani, M. and Pulvermüller, F.. 2017. Neurocomputational Consequences of Evolutionary Connectivity Changes in Perisylvian Language Cortex. The Journal of Neuroscience, 37(11), pp. 3045-3055. ISSN 0270-6474 [Article]
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Abstract or Description
The human brain sets itself apart from that of its primate relatives by specific neuroanatomical features, especially the strong linkage of left perisylvian language areas (frontal and temporal cortex) by way of the arcuate fasciculus (AF). AF connectivity has been shown to correlate with verbal working memory—a specifically human trait providing the foundation for language abilities— but a mechanistic explanation of any related causal link between anatomical structure and cognitive function is still missing. Here, we provide a possible explanation and link, by using neurocomputational simulations in neuroanatomically structured models of the perisylvian language cortex. We compare networks mimicking key features of cortical connectivity in monkeys and humans, specifically the presence of relatively stronger higher-order “jumping links” between nonadjacent perisylvian cortical areas in the latter, and demonstrate that the emergence of working memory for syllables and word forms is a functional consequence of this structural evolutionary change. We also show that a mere increase of learning time is not sufficient, but that this specific structural feature, which entails higher connectivity degree of relevant areas and shorter sensorimotor path length, is crucial. These results offer a better understanding of specifically human anatomical features underlying the language faculty and their evolutionary selection advantage.
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Article |
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20208 |
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19 Apr 2017 08:48 |
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17 Nov 2020 10:51 |
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Yes, this version has been peer-reviewed. |
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