http://www.cnr.it/ontology/cnr/individuo/prodotto/ID199682
Reorganization of Functional Networks in Mild Cognitive Impairment (Articolo in rivista)
- Type
- Label
- Reorganization of Functional Networks in Mild Cognitive Impairment (Articolo in rivista) (literal)
- Anno
- 2011-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1371/journal.pone.001958 (literal)
- Alternative label
Javier M. Buldú (1,2); Ricardo Bajo (3); Fernando Maestú (3); Nazareth Castellanos (3); Inmaculada Leyva (1,2); Pablo Gil (4); Irene Sendiña-Nadal (1,2); Juan A. Almendral (1,2); Angel Nevado (3); Francisco del-Pozo (3); Stefano Boccaletti (5,6) (2011)
Reorganization of Functional Networks in Mild Cognitive Impairment
in PloS one
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Javier M. Buldú (1,2); Ricardo Bajo (3); Fernando Maestú (3); Nazareth Castellanos (3); Inmaculada Leyva (1,2); Pablo Gil (4); Irene Sendiña-Nadal (1,2); Juan A. Almendral (1,2); Angel Nevado (3); Francisco del-Pozo (3); Stefano Boccaletti (5,6) (literal)
- Pagina inizio
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0019584 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
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- Note
- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- 1 Complex Systems Group, Universidad Rey Juan Carlos, Fuenlabrada, Spain,
2 Laboratory of Biological Networks, Centre for Biomedical Technology, Madrid, Spain,
3 Cognitive and Computational Neuroscience Lab, Centre for Biomedical Technology, Polytechnic and Complutense University of Madrid (UPM-UCM), Madrid, Spain,
4 Memory Unit, Hospital Clínico San Carlos, Madrid, Spain,
5 Computational Systems Biology Group, Centre for Biomedical Technology, Madrid, Spain,
6 Istituto dei Sistemi Complessi, CNR, Florence, Italy (literal)
- Titolo
- Reorganization of Functional Networks in Mild Cognitive Impairment (literal)
- Abstract
- Whether the balance between integration and segregation of information in the brain is damaged in Mild Cognitive Impairment (MCI) subjects is still a matter of debate. Here we characterize the functional network architecture of MCI subjects by means of complex networks analysis. Magnetoencephalograms (MEG) time series obtained during a memory task were evaluated by synchronization likelihood (SL), to quantify the statistical dependence between MEG signals and to obtain the functional networks. Graphs from MCI subjects show an enhancement of the strength of connections, together with an increase in the outreach parameter, suggesting that memory processing in MCI subjects is associated with higher energy expenditure and a tendency toward random structure, which breaks the balance between integration and segregation. All features are reproduced by an evolutionary network model that simulates the degenerative process of a healthy functional network to that associated with MCI. Due to the high rate of conversion from MCI to Alzheimer Disease (AD), these results show that the analysis of functional networks could be an appropriate tool for the early detection of both MCI and AD. (literal)
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