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According to the neuroanatomy of sensory and motor systems, a distributed neural network supporting concrete conceptual knowledge is supported by a distributed neural network that reflects various semantic attributes. Different parts of the left anterior temporal lobe's left anterior temporal lobe responded selectively to abstract and concrete theories. The left middle temporal gyrus was adapted by emotions and beliefs, whereas concrete goods were modified from the left fusiform gyrus. Our findings reveal that some categories of abstract knowledge have specific brain correlates corresponding to the prevalent semantic dimensions used in their representation, in comparison to concrete concepts.
Source link: https://doi.org/10.1038/s41598-021-02013-8
Three grounding sets consisted of three grounding styles with neurons displaying specific perceptual or action-related characteristics; neurons were either unique to one pattern or shared between patterns of the same set. Concrete categories were developed as pattern triplets overlapping in their "shared neurons," ensuring semantic feature sharing of all instances of a category. Abstract concepts, on the other hand, had partially shared feature neurons common to only two instances of a category category, thus, displaying family resemblance but lacking complete coverage overlap. After learning, the shared neurons of concrete concepts' instances were more prominent in central areas in comparison to peripheral sensorimotor ones, whereas for abstract concepts, the converse pattern of results was observed, with central areas displaying fewer neurons shared between two group members than in peripheral ones. These findings were interpreted in light of recent reports regarding the relative difficulty students have when learning abstract words.
Source link: https://doi.org/10.1007/s00426-021-01591-6
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