Associating brain topological networks to cognitive performance.

Fabrizio Parente, Colosimo Alfredo


Recent applications of graph theory to brain networks showed the possibility of a relation between network topological indexes and cognitive abilities. In this paper we want to study the relation between the topology of brain networks and a known parameter of executive functions, such as perseveration, using the WCST. To this end, nine healthy subjects were subjected to a fMRI acquisitions with a 3 Tesla Siemens scanner under condition of resting state and evaluated with the WCST. The images were analyzed using the following Matlab toolboxes: SPM8 and Functional Connectivity Toolbox. FromWCST data the indexes of perseverative, nonperseverative errors and perseverative response were calculated. A small-world feature appears in the cost
range (T) 0.45 - 0.50: In this interval, the index shows a positive correlation with perseverative responses ( T=0.50, r=0.864, p=0.006). Moreover, among the values of single cerebral regions (T=0.50), the middle part of orbital frontal gyrus left (r=0.920, p=0.001) show a significant trend for positive correlation with perseverative responses. These results suggest a relation between network’s segregation and perseveration; more specifically a greater segregation of subnetworks is related to a lower adaptability of behavior to the environment changes. Our findings can provide hints to understand the pathological alterations of mental disease related to impairment of executive functions.


Brain Networks, Graph Theory, Executive Functions.

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