Brain Connectivity and Information-Flow Breakdown Revealed by a Minimum Spanning Tree-Based Analysis of MRI Data in Behavioral Variant Frontotemporal Dementia

• Published in: Frontiers in neuroscience Vol. 13; p. 211
• Main Authors: Saba, Valentina, Premi, Enrico, Cristillo, Viviana, Gazzina, Stefano, Palluzzi, Fernando, Zanetti, Orazio, Gasparotti, Roberto, Padovani, Alessandro, Borroni, Barbara, Grassi, Mario
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Research Foundation 14.03.2019; Frontiers Media S.A
• Subjects: behavioral variant frontotemporal dementia; Brain mapping; Cognitive ability; Dementia; Dementia disorders; Frontotemporal dementia; functional connectivity; Functional magnetic resonance imaging; graph theory; minimum spanning tree; Neural networks; Neurodegeneration; Neurodegenerative diseases; Neuroimaging; Neuroscience; NMR; Nuclear magnetic resonance; Phase transitions; resting state; Theory; Italy; behavioral variant frontotemporal dementia; resting state; functional connectivity; graph theory; minimum spanning tree; neurodegeneration; functional magnetic resonance imaging
• ISSN: 1662-453X; 1662-4548; 1662-453X
• DOI: 10.3389/fnins.2019.00211

Brain functional disruption and cognitive shortfalls as consequences of neurodegeneration are among the most investigated aspects in current clinical research. Traditionally, specific anatomical and behavioral traits have been associated with neurodegeneration, thus directly translatable in clinical terms. However, these qualitative traits, do not account for the extensive information flow breakdown within the functional brain network that deeply affect cognitive skills. Behavioural variant Frontotemporal Dementia (bvFTD) is a neurodegenerative disorder characterized by behavioral and executive functions disturbances. Deviations from the physiological cognitive functioning can be accurately inferred and modeled from functional connectivity alterations. Although the need for unbiased metrics is still an open issue in imaging studies, the graph-theory approach applied to neuroimaging techniques is becoming popular in the study of brain dysfunction. In this work, we assessed the global connectivity and topological alterations among brain regions in bvFTD patients using a minimum spanning tree (MST) based analysis of resting state functional MRI (rs-fMRI) data. Whilst several graph theoretical methods require arbitrary criteria (including the choice of network construction thresholds and weight normalization methods), MST is an unambiguous modeling solution, ensuring accuracy, robustness, and reproducibility. MST networks of 116 regions of interest (ROIs) were built on wavelet correlation matrices, extracted from 41 bvFTD patients and 39 healthy controls (HC). We observed a global fragmentation of the functional network backbone with severe disruption of information-flow highways. Frontotemporal areas were less compact, more isolated, and concentrated in less integrated structures, respect to healthy subjects. Our results reflected such complex breakdown of the frontal and temporal areas at both intra-regional and long-range connections. Our findings highlighted that MST, in conjunction with rs-fMRI data, was an effective method for quantifying and detecting functional brain network impairments, leading to characteristic bvFTD cognitive, social, and executive functions disorders.