Next Article in Journal
Fault Feature Extraction of Hydraulic Pumps Based on Symplectic Geometry Mode Decomposition and Power Spectral Entropy
Next Article in Special Issue
Multiscale Information Decomposition Dissects Control Mechanisms of Heart Rate Variability at Rest and During Physiological Stress
Previous Article in Journal
Processing and Characterization of Refractory Quaternary and Quinary High-Entropy Carbide Composite
Previous Article in Special Issue
Time-Frequency Analysis of Cardiovascular and Cardiorespiratory Interactions During Orthostatic Stress by Extended Partial Directed Coherence
Article Menu
Issue 5 (May) cover image

Export Article

Open AccessArticle

Communicability Characterization of Structural DWI Subcortical Networks in Alzheimer’s Disease

1
Dipartimento Interateneo di Fisica, Università degli Studi di Bari, 70125 Bari, Italy
2
Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70126 Bari, Italy
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Entropy 2019, 21(5), 475; https://doi.org/10.3390/e21050475
Received: 14 March 2019 / Revised: 28 April 2019 / Accepted: 28 April 2019 / Published: 6 May 2019
(This article belongs to the Special Issue Information Dynamics in Brain and Physiological Networks)
  |  
PDF [1169 KB, uploaded 16 May 2019]
  |  

Abstract

In this paper, we investigate the connectivity alterations of the subcortical brain network due to Alzheimer’s disease (AD). Mostly, the literature investigated AD connectivity abnormalities at the whole brain level or at the cortex level, while very few studies focused on the sub-network composed only by the subcortical regions, especially using diffusion-weighted imaging (DWI) data. In this work, we examine a mixed cohort including 46 healthy controls (HC) and 40 AD patients from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) data set. We reconstruct the brain connectome through the use of state of the art tractography algorithms and we propose a method based on graph communicability to enhance the information content of subcortical brain regions in discriminating AD. We develop a classification framework, achieving 77% of area under the receiver operating characteristic (ROC) curve in the binary discrimination AD vs. HC only using a 12 × 12 subcortical features matrix. We find some interesting AD-related connectivity patterns highlighting that subcortical regions tend to increase their communicability through cortical regions to compensate the physical connectivity reduction between them due to AD. This study also suggests that AD connectivity alterations mostly regard the inter-connectivity between subcortical and cortical regions rather than the intra-subcortical connectivity. View Full-Text
Keywords: brain connectivity; neuroscience; Alzheimer’s disease; diffusion tensor imaging; complex networks; communicability; subcortical brain network brain connectivity; neuroscience; Alzheimer’s disease; diffusion tensor imaging; complex networks; communicability; subcortical brain network
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Lella, E.; Amoroso, N.; Diacono, D.; Lombardi, A.; Maggipinto, T.; Monaco, A.; Bellotti, R.; Tangaro, S. Communicability Characterization of Structural DWI Subcortical Networks in Alzheimer’s Disease. Entropy 2019, 21, 475.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top