Changes in information segregation and integration of aMCI based on low- and high-order functional connectivity

Abstract

Brain functional networks have studied amnestic mild cognitive impairment diagnosis. However, the abnormal patterns of amnestic mild cognitive impairment brain networks based on electroencephalography have not yet been resolved. In this study, a new method, the genuine low-order functional connectivity and high-order functional connection, integrates multilayer network information and dynamic network theory to analyze the characteristics of amnestic mild cognitive impairment function coupling. Meanwhile, the assessment framework combined dynamic brain functional networks and multidimensional metrics to diagnose amnestic mild cognitive impairment. Using the new method, this paper analyzed 28 amnestic mild cognitive impairment cases and 21 normal controls from clinical electroencephalography data. The results indicate that, except for the delta band, the connection strength of different amnestic mild cognitive impairment networks is lower than that of normal controls. The alpha and beta bands normal control’s network metric greater than amnestic mild cognitive impairment showed significant differences (P < 0.05). Meanwhile, the significant difference in state entropy between the amnestic mild cognitive impairment and normal controls disappeared in the delta band of the 10 s window and the beta band of the 2 s window in the dynamic high-order functional connection. The amnestic mild cognitive impairment brain functional network exhibits abnormal features. Meanwhile, the alpha and beta bands could be sensitive to diagnose amnestic mild cognitive impairment.

amnestic mild cognitive impairment, dynamic brain functional networks, electroencephalogram, low- and high-order functional connectivity, multidimensional metrics