Anomalous Consistency in Mild Cognitive Impairment: A Complex Networks Approach

Martínez Huartos, Johann Heinz and Ariza Bono, Pedro and Zanin, Massimiliano and Papo, David and Maestu Unturbe, Fernando and Pastor Ruiz, Juan Manuel and Bajo Breton, Ricardo and Boccaletti, Stefano and Martín Buldú, Javier (2015). Anomalous Consistency in Mild Cognitive Impairment: A Complex Networks Approach. "Chaos Solitons & Fractals", v. 70 ; pp. 144-155. ISSN 0960-0779. https://doi.org/10.1016/j.chaos.2014.10.013.

Description

Title: Anomalous Consistency in Mild Cognitive Impairment: A Complex Networks Approach
Author/s:
  • Martínez Huartos, Johann Heinz
  • Ariza Bono, Pedro
  • Zanin, Massimiliano
  • Papo, David
  • Maestu Unturbe, Fernando
  • Pastor Ruiz, Juan Manuel
  • Bajo Breton, Ricardo
  • Boccaletti, Stefano
  • Martín Buldú, Javier
Item Type: Article
Título de Revista/Publicación: Chaos Solitons & Fractals
Date: January 2015
Volume: 70
Subjects:
Faculty: E.T.S.I. Agrónomos (UPM) [antigua denominación]
Department: Física y Mecánica Fundamental, Aplicada a la Ingeniería Agroforestal [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

Increased variability in performance has been associated with the emergence of several neurological and psychiatric pathologies. However, whether and how consistency of neuronal activity may also be indicative of an underlying pathology is still poorly understood. Here we propose a novel method for evaluating consistency from non-invasive brain recordings. We evaluate the consistency of the cortical activity recorded with magnetoencephalography in a group of subjects diagnosed with Mild Cognitive Impairment (MCI), a condition sometimes prodromal of dementia, during the execution of a memory task. We use metrics coming from nonlinear dynamics to evaluate the consistency of cortical regions. A representation known as parenclitic networks is constructed, where atypical features are endowed with a network structure, the topological properties of which can be studied at various scales. Pathological conditions correspond to strongly heterogeneous networks, whereas typical or normative conditions are characterized by sparsely connected networks with homogeneous nodes. The analysis of this kind of networks allows identifying the extent to which consistency is affected in the MCI group and the focal points where MCI is especially severe. To the best of our knowledge, these results represent the first attempt at evaluating the consistency of brain functional activity using complex networks theory.

More information

Item ID: 38812
DC Identifier: http://oa.upm.es/38812/
OAI Identifier: oai:oa.upm.es:38812
DOI: 10.1016/j.chaos.2014.10.013
Official URL: http://www.sciencedirect.com/science/article/pii/S0960077914001842
Deposited by: Memoria Investigacion
Deposited on: 02 Feb 2016 16:10
Last Modified: 31 Jan 2017 23:30
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