Resting-state neural networks in cognitive decline in patients with vascular encephalopathy

Abstract

We evaluated the connectivity reorganization of resting-state neural networks in patients with cognitive decline secondary to vascular encephalopathy (VE). Quantitative cognitive functions were evaluated using the Montreal Cognitive Assessment (MoCA) scale and compared with the organization of resting-state neural networks recorded using functional magnetic resonance imaging (fMRI). The aim of this work was to assess the relationship between various resting-state neural networks and cognitive function. Materials and methods. The study involved 29 people with VE, divided into two groups: without cognitive decline ( 26 points on the MoCA) and with cognitive impairment (2418 points on the MoCA). Connectivity between different brain regions was evaluated in all patients using resting-state fMRI, with SPM-12 and CONN18b software applications in Matlab. Results and conclusion. Statistically significant differences in connectivity were found between groups in the dorsal attention network, visual network, and sensorimotor networks, as well as in the left parahippocampal cortex. New, negative connectivity was observed alongside cognitive decline, which, together with reduced connectivity in resting-state neural networks, can be considered an obligatory sign accompanying cognitive impairment in VE.

Keywords

• vascular encephalopathy
• neuroimaging
• functional resting-state mri
• montreal cognitive assessment scale
• connectivity
• cognitive function
• resting-state neural networks