Adıyaman Üniversitesi Kurumsal Arşivi

Cracking the barcode of fullerene-like cortical microcolumns

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dc.contributor.author Tozzi, Arturo
dc.contributor.author ve diğerleri...
dc.date.accessioned 2025-07-07T11:54:29Z
dc.date.available 2025-07-07T11:54:29Z
dc.date.issued 2017
dc.identifier.issn 0304-3940
dc.identifier.uri http://dspace.adiyaman.edu.tr:8080/xmlui/handle/20.500.12414/6435
dc.description.abstract Artificial neural systems and nervous graph theoretical analysis rely upon the stance that the neural code is embodied in logic circuits, e.g., spatio-temporal sequences of ON/OFF spiking neurons. Nevertheless, this assumption does not fully explain complex brain functions. Here we show how nervous activity, other than logic circuits, could instead depend on topological transformations and symmetry constraints occurring at the micro-level of the cortical microcolumn, i.e., the embryological, anatomical and functional basic unit of the brain. Tubular microcolumns can be flattened in fullerene-like two-dimensional lattices, equipped with about 80 nodes standing for pyramidal neurons where neural computations take place. We show how the countless possible combinations of activated neurons embedded in the lattice resemble a barcode. Despite the fact that further experimental verification is required in order to validate our claim, different assemblies of firing neurons might have the appearance of diverse codes, each one responsible for a single mental activity. A two-dimensional fullerene-like lattice, grounded on simple topological changes standing for pyramidal neurons' activation, not just displays analogies with the real microcolumn's microcircuitry and the neural connectome, but also the potential for the manufacture of plastic, robust and fast artificial networks in robotic forms of full-fledged neural systems. tr
dc.language.iso en tr
dc.publisher Elsevier Ireland Ltd tr
dc.title Cracking the barcode of fullerene-like cortical microcolumns tr
dc.type Article tr
dc.contributor.department Univ North Texas, Ctr Nonlinear Sci, 1155 Union Circle 311427, Denton, TX 76203 USA tr
dc.identifier.endpage 106 tr
dc.identifier.startpage 100 tr
dc.identifier.volume 644 tr
dc.source.title NEUROSCIENCE LETTERS tr


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