Associating brain topological networks to cognitive performance.

Abstract

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 costrange (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.