Abstract
| Original language | English |
|---|---|
| Article number | 2050004 |
| Journal | Int. J. Neural Syst. |
| Volume | 30 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2020 |
Keywords
- Alzheimer's disease
- default mode network
- dementia
- EEG
- graph theory
- mild cognitve impairment
- neuropsychological test
- Electroencephalography
- Graph theory
- Default-mode networks
- Neuropsychological tests
- Neurodegenerative diseases
- aged
- Alzheimer disease
- amnesia
- brain
- cognitive defect
- disease exacerbation
- electroencephalography
- follow up
- human
- middle aged
- nerve tract
- pathophysiology
- prognosis
- rest
- signal processing
- very elderly
- Aged
- Aged, 80 and over
- Alzheimer Disease
- Amnesia
- Brain
- Cognitive Dysfunction
- Disease Progression
- Follow-Up Studies
- Humans
- Middle Aged
- Neural Pathways
- Neuropsychological Tests
- Prognosis
- Rest
- Signal Processing, Computer-Assisted
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Small World Index in Default Mode Network Predicts Progression from Mild Cognitive Impairment to Dementia : International Journal of Neural Systems. / Miraglia, F.; Vecchio, F.; Marra, C.; Quaranta, D.; Alù, F.; Peroni, B.; Granata, G.; Judica, E.; Cotelli, M.; Rossini, P.M.
In: Int. J. Neural Syst., Vol. 30, No. 2, 2050004, 2020.Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Small World Index in Default Mode Network Predicts Progression from Mild Cognitive Impairment to Dementia
T2 - International Journal of Neural Systems
AU - Miraglia, F.
AU - Vecchio, F.
AU - Marra, C.
AU - Quaranta, D.
AU - Alù, F.
AU - Peroni, B.
AU - Granata, G.
AU - Judica, E.
AU - Cotelli, M.
AU - Rossini, P.M.
N1 - Cited By :7 Export Date: 11 February 2021 Correspondence Address: Miraglia, F.; Brain Connectivity Laboratory, Italy; email: fra.miraglia@gmail.com Funding text 1: The paper is partially funded by the Italian Ministry of Health (“Ricerca corrente”). References: Deco, G., Jirsa, V.K., McIntosh, A.R., Emerging concepts for the dynamical organization of restingstate activity in the brain (2010) Nat. Rev. Neurosci., 12, p. 43; Raichle, M.E., MacLeod, A.M., Snyder, A.Z., Powers, W.J., Gusnard, D.A., Shulman, G.L., A default mode of brain function (2001) Proc. Natl. Acad. Sci. USA, 98 (2), pp. 676-682; Greicius, M.D., Krasnow, B., Reiss, A.L., Menon, V., Functional connectivity in the resting brain: A network analysis of the default mode hypothesis (2003) Proc. Natl. Acad. Sci. USA, 100 (1), pp. 253-258; Hsiao, F.J., Wang, Y.J., Yan, S.H., Chen, W.T., Lin, Y.Y., Altered oscillation and synchronization of default-mode network activity in mild Alzheimer's disease compared to mild cognitive impairment: An electrophysiological study (2013) PLoS One, 8 (7), p. e68792; Rubinov, M., Sporns, O., Complex network measures of brain connectivity: Uses and interpretations (2010) Neuroimage, 52 (3), pp. 1059-1069; Miraglia, F., Vecchio, F., Rossini, P.M., Searching for signs of aging and dementia in EEG through network analysis (2017) Behav. Brain Res., 317, pp. 292-300; Micheloyannis, S., Pachou, E., Stam, C.J., Small-world networks and disturbed functional connectivity in schizophrenia (2006) Schizophr. Res., 87 (1-3), pp. 60-66; Reijneveld, J.C., Ponten, S.C., Berendse, H.W., Stam, C.J., The application of graph theoretical analysis to complex networks in the brain (2007) Clin. Neurophysiol., 118 (11), pp. 2317-2331; Ponten, S.C., Daffertshofer, A., Hillebrand, A., Stam, C.J., The relationship between structural and functional connectivity: Graph theoretical analysis of an EEG neural mass model (2010) Neuroimage, 52 (3), pp. 985-994; Stam, C.J., Characterization of anatomical and functional connectivity in the brain: A complex networks perspective (2010) Int. J. Psychophysiol., 77 (3), pp. 186-194; Palva, S., Monto, S., Palva, J.M., Graph properties of synchronized cortical networks during visual working memory maintenance (2010) Neuroimage, 49 (4), pp. 3257-3268; Ahmadlou, M., Adeli, H., Functional community analysis of brain: A new approach for EEG-based investigation of the brain pathology (2011) Neuroimage, 58 (2), pp. 401-408; Ahmadlou, M., Adeli, H., Complexity of weighted graph: A new technique to investigate structural complexity of brain activities with applications to aging and autism (2017) Neurosci. Lett., 650, pp. 103-108; Ferri, R., Rundo, F., Bruni, O., Terzano, M.G., Stam, C.J., The functional connectivity of different EEG bands moves towards small-world network organization during sleep (2008) Clin. Neurophysiol., 119 (9), pp. 2026-2036; Park, C.H., Kim, S.Y., Ohn, S.H., Lee, B.H., Kim, S.T., Kim, Y.H., Hemispheric asymmetry of speed-dependent intercerebellar connectivity (2008) Neurosci. Lett., 443 (3), pp. 119-122; Tian, L., Wang, J., Yan, C., He, Y., Hemisphereand gender-related differences in small-world brain networks: A resting-state functional MRI study (2011) Neuroimage, 54 (1), pp. 191-202; Yuan, K., Qin, W., Liu, J., Altered small-world brain functional networks and duration of heroin use in Male abstinent heroin-dependent individuals (2010) Neurosci. Lett., 477 (1), pp. 37-42; Watts, D.J., Strogatz, S.H., Collective dynamics of "small-world" networks (1998) Nature, 393 (6684), pp. 440-442; Friston, K.J., Functional and effective connectivity in neuroimaging: A synthesis (2004) Human Brain Mapping, 2 (1-2), pp. 56-78; Tononi, G., Sporns, O., Edelman, G.M., A measure for brain complexity: Relating functional segregation and integration in the nervous system (1994) Proc. Natl. Acad. Sci. USA, 91 (11), pp. 5033-5037; Bullmore, E., Sporns, O., Complex brain networks: Graph theoretical analysis of structural and functional systems (2009) Nat. Rev. Neurosci., 10 (3), pp. 186-198; López-Sanz, D., Garcés, P., Álvarez, B., Delgado-Losada, M.L., López-Higes, R., Maestú, F., Network disruption in the preclinical stages of Alzheimer's disease: From subjective cognitive decline to mild cognitive impairment (2017) Int. J. Neural Syst., 27 (8), p. 1750041; Musaeus, C.S., Nielsen, M.S., Høgh, P., Altered low-frequency EEG connectivity in mild cognitive impairment as A sign of clinical progression (2019) J. Alzheimers Dis., 68 (3), pp. 947-960; Papageorgiou, C., Karanasiou, I.S., Tsianaka, E.I., Kyprianou, M., Papadimitriou, G.N., Uzunoglu, N.K., Motive related positivity: Decisionmaking during A prisoners' dilemma task (2013) J. Integr. Neurosci., 12 (2), pp. 183-199; Stam, C.J., Jones, B.F., Nolte, G., Breakspear, M., Scheltens, P., Small-world networks and functional connectivity in Alzheimer's disease (2007) Cereb. Cortex, 17 (1), pp. 92-99; Stam, C.J., De Haan, W., Daffertshofer, A., Graph theoretical analysis of magnetoencephalographic functional connectivity in Alzheimer's disease (2009) Brain, 132, pp. 213-224; De Haan, W., Pijnenburg, Y.A., Strijers, R.L., Functional neural network analysis in frontotemporal dementia and Alzheimer's disease using EEG and graph theory (2009) BMC Neurosci., 10, p. 101; Brown, C.A., Jiang, Y., Smith, C.D., Gold, B.T., Age and Alzheimer's pathology disrupt default mode network functioning via alterations in white matter microstructure but not hyperintensities (2018) Cortex, 104, pp. 58-74; Libon, D.J., Xie, S.X., Eppig, J., The heterogeneity of mild cognitive impairment: A neuropsychological analysis (2010) Int. J. Neuropsychol. Soc., 16 (1), pp. 84-93; Quaranta, D., Vita, M.G., Spinelli, P., Does semantic memory impairment in amnestic MCI with hippocampal atrophy conform to A distinctive pattern of progression? (2014) Curr. Alzheimer Res., 11 (4), pp. 399-407; Delano-Wood, L., Bondi, M.W., Sacco, J., Heterogeneity in mild cognitive impairment: Differences in neuropsychological profile and associated white matter lesion pathology (2009) Int. J. Neuropsychol. Soc., 15 (6), pp. 906-914; Petersen, R.C., Mild cognitive impairment as A diagnostic entity (2004) J. Intern. Med., 256 (3), pp. 183-194; Winblad, B., Palmer, K., Kivipelto, M., Mild cognitive impairment-beyond controversies towards A consensus: Report of the International Working Group on Mild Cognitive Impairment (2004) J. Intern. Med., 256 (3), pp. 240-246; Petersen, R.C., Caracciolo, B., Brayne, C., Gauthier, S., Jelic, V., Fratiglioni, L., Mild cognitive impairment: A concept in evolution (2014) J. Intern. Med., 275 (3), pp. 214-228; McKhann, G.M., Knopman, D.S., Chertkow, H., The diagnosis of dementia due to Alzheimer's disease: Recommendations from the National Institute on Aging-Alzheimer's association workgroups on diagnostic guidelines for Alzheimer's disease (2011) Alzheimers Dement., 7 (3), pp. 263-269; Caffarra, P., Vezzadini, G., Dieci, F., Zonato, F., Venneri, A., Rey-Osterrieth complex figure: Normative values in an Italian population sample (2002) Neurol. Sci., 22 (6), pp. 443-447; Marra, C., Gainotti, G., Fadda, L., Usefulness of an integrated analysis of different memory tasks to predict the progression from mild cognitive impairment to Alzheimer's disease: The episodic memory score (EMS) (2016) J. Alzheimers Dis., 50 (1), pp. 61-70; Novelli, G., Papagno, C., Capitani, E., Laiacona, M., Vallar, G., Cappa, S., Tre test clinici di ricerca e produzione lessicale. Taratura su sogetti normali (1986) Archivio di Psicologia, Neurologia e Psichiatria, 47 (4), pp. 477-506; Quaranta, D., Caprara, A., Piccininni, C., Vita, M.G., Gainotti, G., Marra, C., Standardization clinical validation, and typicality norms of A new test assessing semantic verbal fluency (2016) Arch. Clin. Neuropsychol., 31 (5), pp. 434-445; Marra, C., Gainotti, G., Scaricamazza, E., Piccininni, C., Ferraccioli, M., Quaranta, D., The multiple features target cancellation (MFTC): An attentional visual conjunction search test. Normative values for the Italian population (2013) Neurol. Sci., 34 (2), pp. 173-180; Iriarte, J., Urrestarazu, E., Valencia, M., Independent component analysis as A tool to eliminate artifacts in EEG: A quantitative study (2003) J. Clin. Neurophysiol., 20 (4), pp. 249-257; Vecchio, F., Miraglia, F., Marra, C., Human brain networks in cognitive decline: A graph theoretical analysis of cortical connectivity from EEG data (2014) J. Alzheimers Dis., 41 (1), pp. 113-127; Vecchio, F., Miraglia, F., Iberite, F., Sustainable method for Alzheimer dementia prediction in mild cognitive impairment: Electroencephalographic connectivity and graph theory combined with apolipoprotein e (2018) Ann. Neurol., 84 (2), pp. 302-314; Vecchio, F., Caliandro, P., Reale, G., Acute cerebellar stroke and middle cerebral artery stroke exert distinctive modifications on functional cortical connectivity: A comparative study via EEG graph theory (2019) Clin. Neurophysiol., 130 (6), pp. 997-1007; Miraglia, F., Vecchio, F., Bramanti, P., Rossini, P.M., EEG characteristics in "eyes-open" versus "eyes-closed" conditions: Small-world network architecture in healthy aging and age-related brain degeneration (2016) Clin. Neurophysiol., 127 (2), pp. 1261-1268; Vecchio, F., Miraglia, F., Quaranta, D., Cortical connectivity and memory performance in cognitive decline: A study via graph theory from EEG data (2016) Neuroscience, 316, pp. 143-150; Vecchio, F., Miraglia, F., Gorgoni, M., Cortical connectivity modulation during sleep onset: A study via graph theory on EEG data (2017) Hum. Brain Mapp., 38 (11), pp. 5456-5464; Pascual-Marqui, R.D., (2007) Discrete 3D Distributed, Linear Imaging Methods of Electric Neuronal Activity. Part 1: Exact, Zero Error Localization, , arXiv e-prints. 2007. Accessed October 01; Vecchio, F., Lacidogna, G., Miraglia, F., Bramanti, P., Ferreri, F., Rossini, P.M., Prestimulus interhemispheric coupling of brain rhythms predicts cognitive-motor performance in healthy humans (2014) J. Cogn. Neurosci., 26 (9), pp. 1883-1890; Fuchs, M., Kastner, J., Wagner, M., Hawes, S., Ebersole, J.S., A standardized boundary element method volume conductor model (2002) Clin. Neurophysiol., 113 (5), pp. 702-712; Mazziotta, J., Toga, A., Evans, A., A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM) (2001) Philos. Trans. R. Soc. Lond. B Biol. Sci., 356 (1412), pp. 1293-1322; Lancaster, J.L., Woldorff, M.G., Parsons, L.M., Automated Talairach atlas labels for functional brain mapping (2000) Hum. Brain Mapp., 10 (3), pp. 120-131; Jurcak, V., Tsuzuki, D., Dan, I., 10/20, 10/10, and 10/5 systems revisited: Their validity as relative head-surface-based positioning systems (2007) Neuroimage, 34 (4), pp. 1600-1611; Oostenveld, R., Praamstra, P., The five percent electrode system for high-resolution EEG and ERP measurements (2001) Clin. Neurophysiol., 112 (4), pp. 713-719; Brett, M., Johnsrude, I.S., Owen, A.M., The problem of functional localization in the human brain (2002) Nat. Rev. Neurosci., 3 (3), pp. 243-249; Agosta, F., Pievani, M., Geroldi, C., Copetti, M., Frisoni, G.B., Filippi, M., Resting state fMRI in Alzheimer's disease: Beyond the default mode network (2012) Neurobiol. Aging, 33 (8), pp. 1564-1578; Allen, E.A., Erhardt, E.B., Damaraju, E., A baseline for the multivariate comparison of resting-state networks (2011) Front. Syst. Neurosci., 5, p. 2; Miraglia, F., Vecchio, F., Bramanti, P., Rossini, P.M., Small-worldness characteristics and its gender relation in specific hemispheric networks (2015) Neuroscience, 310, pp. 1-11; Pascual-Marqui, R.D., (2007) Instantaneous and Lagged Measurements of Linear and Nonlinear Dependence between Groups of Multivariate Time Series: Frequency Decomposition, , arXiv: 0711. 1455; Vecchio, F., Pellicciari, M.C., Miraglia, F., Brignani, D., Miniussi, C., Rossini, P.M., Effects of transcranial direct current stimulation on the functional coupling of the sensorimotor cortical network (2016) Neuroimage, 140, pp. 50-56; Nolte, G., Bai, O., Wheaton, L., Mari, Z., Vorbach, S., Hallett, M., Identifying true brain interaction from EEG data using the imaginary part of coherency (2004) Clin. Neurophysiol., 115 (10), pp. 2292-2307; Tecchio, F., Vecchio, F., Ventriglia, M., Nonceruloplasmin copper distinguishes A distinct subtype of Alzheimer's disease: A study of EEGderived brain activity (2016) Curr. Alzheimer Res., 13 (12), pp. 1374-1384; Miraglia, F., Vecchio, F., Rossini, P.M., Brain electroencephalographic segregation as A biomarker of learning (2018) Neural Netw., 106, pp. 168-174; Onnela, J.P., Saramäki, J., Kertész, J., Kaski, K., Intensity and coherence of motifs in weighted complex networks (2005) Phys. Rev. e Stat. Nonlin. Soft Matter Phys., 71 (6), p. 065103; Pascual-Marqui, R.D., Standardized low-resolution brain electromagnetic tomography (sLORETA): Technical details (2002) Methods Find Exp. Clin. Pharmacol., 24, pp. 5-12; Pascual-Marqui, R.D., (2009) Theory of the EEG Inverse Problem, , ArtechHouse Boston; Greenblatt, R.E., Ossadtchi, A., Pflieger, M.E., Local linear estimators for the bioelectromagnetic inverse problem (2005) IEEE Trans. Signal Processing, 53 (9), pp. 3403-3412; Sekihara, K., Sahani, M., Nagarajan, S.S., A simple nonparametric statistical thresholding for MEG spatial-filter source reconstruction images (2005) Neuroimage, 27 (2), pp. 368-376; Tallon-Baudry, C., Bertrand, O., Peronnet, F., Pernier, J., Induced gamma-band activity during the delay of A visual short-term memory task in humans (1998) J. Neurosci., 18 (11), pp. 4244-4254; Gruber, T., Müller, M.M., Keil, A., Elbert, T., Selective visual-spatial attention alters induced gamma band responses in the human EEG (1999) Clin. Neurophysiol., 110 (12), pp. 2074-2085; Keil, A., Müller, M.M., Ray, W.J., Gruber, T., Elbert, T., Human gamma band activity and perception of A gestalt (1999) J. Neurosci., 19 (16), pp. 7152-7161; Nyhus, E., Curran, T., Functional role of gamma and theta oscillations in episodic memory (2010) Neurosci. Biobehav. Rev., 34 (7), pp. 1023-1035; Gruber, T., Tsivilis, D., Montaldi, D., Müller, M.M., Induced gamma band responses: An early marker of memory encoding and retrieval (2004) Neuroreport, 15 (11), pp. 1837-1841; Kaiser, J., Heidegger, T., Lutzenberger, W., Behavioral relevance of gamma-band activity for short-term memory-based auditory decisionmaking (2008) Eur. J. Neurosci., 27 (12), pp. 3322-3328; Busch, N.A., Groh-Bordin, C., Zimmer, H.D., Herrmann, C.S., Modes of memory: Early electrophysiological markers of repetition suppression and recognition enhancement predict behavioral performance (2008) Psychophysiology, 45 (1), pp. 25-35; Wang, Y., Zhang, X., Huang, J., Zhu, M., Guan, Q., Liu, C., Associations between EEG beta power abnormality and diagnosis in cognitive impairment post cerebral infarcts (2013) J. Mol. Neurosci., 49 (3), pp. 632-638; Brenner, E.K., Hampstead, B.M., Grossner, E.C., Diminished neural network dynamics in amnestic mild cognitive impairment (2018) Int. J. Psychophysiol., 130, pp. 63-72; Laufs, H., Krakow, K., Sterzer, P., Electroencephalographic signatures of attentional and cognitive default modes in spontaneous brain activity fluctuations at rest (2003) Proc. Natl. Acad. Sci. USA, 100 (19), pp. 11053-11058; Broyd, S.J., Demanuele, C., Debener, S., Helps, S.K., James, C.J., Sonuga-Barke, E.J., Default-mode brain dysfunction in mental disorders: A systematic review (2009) Neurosci. Biobehav. Rev., 33 (3), pp. 279-296; Klimesch, W., EEG alpha and theta oscillations reflect cognitive and memory performance: A review and analysis (1999) Brain Res. Brain Res. Rev., 29 (2-3), pp. 169-195; Vecchio, F., Babiloni, C., Lizio, R., Resting state cortical EEG rhythms in Alzheimer's disease: Toward EEG markers for clinical applications: A review (2013) Suppl. Clin. Neurophysiol., 62, pp. 223-236; Ouchi, Y., Kikuchi, M., A review of the default mode network in aging and dementia based on molecular imaging (2012) Rev. Neurosci., 23 (3), pp. 263-268; Ouchi, Y., Akanuma, K., Meguro, M., Kasai, M., Ishii, H., Meguro, K., Impaired instrumental activities of daily living affect conversion from mild cognitive impairment to dementia: The Osaki-Tajiri project (2012) Psychogeriatrics, 12 (1), pp. 34-42; Song, J., Birn, R.M., Boly, M., Age-related reorganizational changes in modularity and functional connectivity of human brain networks (2014) Brain Connect., 4 (9), pp. 662-676; Liang, Z., Liu, X., Zhang, N., Dynamic resting state functional connectivity in awake and anesthetized rodents (2015) Neuroimage, 104, pp. 89-99; Qi, Z., Wu, X., Wang, Z., Impairment and compensation coexist in amnestic MCI default mode network (2010) Neuroimage, 50 (1), pp. 48-55; Esposito, R., Cieri, F., Chiacchiaretta, P., Modifications in resting state functional anticorrelation between default mode network and dorsal attention network: Comparison among young adults healthy elders and mild cognitive impairment patients (2018) Brain Imaging Behav., 12 (1), pp. 127-141; Angel, L., Fay, S., Bouazzaoui, B., Isingrini, M., Individual differences in executive functioning modulate age effects on the ERP correlates of retrieval success (2010) Neuropsychologia, 48 (12), pp. 3540-3553; Bouazzaoui, B., Angel, L., Fay, S., Taconnat, L., Charlotte, F., Isingrini, M., Does the greater involvement of executive control in memory with age act as A compensatory mechanism? (2014) Can. J. Exp. Psychol., 68 (1), pp. 59-66; Fleck, J.I., Kuti, J., Brown, J., Mahon, J.R., Gayda-Chelder, C., Frontal-posterior coherence and cognitive function in older adults (2016) Int. J. Psychophysiol., 110, pp. 217-230; Zanchi, D., Montandon, M.L., Sinanaj, I., Decreased fronto-parietal and increased default mode network activation is associated with subtle cognitive deficits in elderly controls (2017) Neurosignals, 25 (1), pp. 127-138; Marra, C., Silveri, M.C., Gainotti, G., Predictors of cognitive decline in the early stage of probable Alzheimer's disease (2000) Dement. Geriatr. Cogn. Disord., 11 (4), pp. 212-218; Vuksanovíc, V., Staff, R.T., Ahearn, T., Murray, A.D., Wischik, C.M., Cortical thickness and surface area networks in healthy aging, Alzheimer's disease and behavioral variant frontotemporal dementia (2019) Int. J. Neural Syst., 29 (6), p. 1850055; Gaubert, S., Raimondo, F., Houot, M., EEG evidence of compensatory mechanisms in preclinical Alzheimer's disease (2019) Brain, 142 (7), pp. 2096-2112; Mohan, A., Roberto, A.J., Lorenzo, A., The significance of the default mode network (DMN) in neurological and neuropsychiatric disorders: A review (2016) Yale J. Biol. Med., 89 (1), pp. 49-57; Bassett, D.S., Bullmore, E., Small-world brain networks (2006) Neuroscientist, 12 (6), pp. 512-523; Rossini, P.M., Di Iorio, R., Granata, G., Miraglia, F., Vecchio, F., From mild cognitive impairment to Alzheimer's disease: A new perspective in the "land" of human brain reactivity and connectivity (2016) J. Alzheimers Dis., 53 (4), pp. 1389-1393; Mulert, C., Jäger, L., Schmitt, R., Integration of fMRI and simultaneous EEG: Towards A comprehensive understanding of localization and timecourse of brain activity in target detection (2004) Neuroimage, 22 (1), pp. 83-94; Vitacco, D., Brandeis, D., Pascual-Marqui, R., Martin, E., Correspondence of event-related potential tomography and functional magnetic resonance imaging during language processing (2002) Hum. Brain Mapp., 17 (1), pp. 4-12; Worrell, G.A., Lagerlund, T.D., Sharbrough, F.W., Localization of the epileptic focus by lowresolution electromagnetic tomography in patients with A lesion demonstrated by MRI (2000) Brain Topogr., 12 (4), pp. 273-282; Dierks, T., Jelic, V., Pascual-Marqui, R.D., Spatial pattern of cerebral glucose metabolism (PET) correlates with localization of intracerebral EEG-generators in Alzheimer's disease (2000) Clin. Neurophysiol., 111 (10), pp. 1817-1824; Pizzagalli, D.A., Oakes, T.R., Fox, A.S., Functional but not structural subgenual prefrontal cortex abnormalities in melancholia (2004) Mol. Psychiatry, 9 (4), p. 325. , 393-405; Zumsteg, D., Wennberg, R.A., Treyer, V., Buck, A., Wieser, H.G., H2(15)O or 13NH3 PET and electromagnetic tomography (LORETA) during partial status epilepticus (2005) Neurology, 65 (10), pp. 1657-1660; Zumsteg, D., Lozano, A.M., Wieser, H.G., Wennberg, R.A., Cortical activation with deep brain stimulation of the anterior thalamus for epilepsy (2006) Clin. Neurophysiol., 117 (1), pp. 192-207; Zumsteg, D., Lozano, A.M., Wennberg, R.A., Depth electrode recorded cerebral responses with deep brain stimulation of the anterior thalamus for epilepsy (2006) Clin. Neurophysiol., 117 (7), pp. 1602-1609; Zumsteg, D., Friedman, A., Wieser, H.G., Wennberg, R.A., Propagation of interictal discharges in temporal lobe epilepsy: Correlation of spatiotemporal mapping with intracranial foramen ovale electrode recordings (2006) Clin. Neurophysiol., 117 (12), pp. 2615-2626; Volpe, U., Mucci, A., Bucci, P., Merlotti, E., Galderisi, S., Maj, M., The cortical generators of P3a and P3b: A LORETA study (2007) Brain Res. Bull., 73 (4-6), pp. 220-230
PY - 2020
Y1 - 2020
N2 - Aim of this study was to explore the EEG functional connectivity in amnesic mild cognitive impairments (MCI) subjects with multidomain impairment in order to characterize the Default Mode Network (DMN) in converted MCI (cMCI), which converted to Alzheimer's disease (AD), compared to stable MCI (sMCI) subjects. A total of 59 MCI subjects were recruited and divided -after appropriate follow-up- into cMCI or sMCI. They were further divided in MCI with linguistic domain (LD) impairment and in MCI with executive domain (ED) impairment. Small World (SW) index was measured as index of balance between integration and segregation brain processes. SW, computed restricting to nodes of DMN regions for all frequency bands, evaluated how they differ between MCI subgroups assessed through clinical and neuropsychological four-years follow-up. In addition, SW evaluated how this pattern differs between MCI with LD and MCI with ED. Results showed that SW index significantly decreased in gamma band in cMCI compared to sMCI. In cMCI with LD impairment, the SW index significantly decreased in delta band, while in cMCI with ED impairment the SW index decreased in delta and gamma bands and increased in alpha1 band. We propose that the DMN functional alterations in cognitive impairment could reflect an abnormal flow of brain information processing during resting state possibly associated to a status of pre-dementia. © 2020 World Scientific Publishing Company.
AB - Aim of this study was to explore the EEG functional connectivity in amnesic mild cognitive impairments (MCI) subjects with multidomain impairment in order to characterize the Default Mode Network (DMN) in converted MCI (cMCI), which converted to Alzheimer's disease (AD), compared to stable MCI (sMCI) subjects. A total of 59 MCI subjects were recruited and divided -after appropriate follow-up- into cMCI or sMCI. They were further divided in MCI with linguistic domain (LD) impairment and in MCI with executive domain (ED) impairment. Small World (SW) index was measured as index of balance between integration and segregation brain processes. SW, computed restricting to nodes of DMN regions for all frequency bands, evaluated how they differ between MCI subgroups assessed through clinical and neuropsychological four-years follow-up. In addition, SW evaluated how this pattern differs between MCI with LD and MCI with ED. Results showed that SW index significantly decreased in gamma band in cMCI compared to sMCI. In cMCI with LD impairment, the SW index significantly decreased in delta band, while in cMCI with ED impairment the SW index decreased in delta and gamma bands and increased in alpha1 band. We propose that the DMN functional alterations in cognitive impairment could reflect an abnormal flow of brain information processing during resting state possibly associated to a status of pre-dementia. © 2020 World Scientific Publishing Company.
KW - Alzheimer's disease
KW - default mode network
KW - dementia
KW - EEG
KW - graph theory
KW - mild cognitve impairment
KW - neuropsychological test
KW - Electroencephalography
KW - Graph theory
KW - Default-mode networks
KW - Neuropsychological tests
KW - Neurodegenerative diseases
KW - aged
KW - Alzheimer disease
KW - amnesia
KW - brain
KW - cognitive defect
KW - disease exacerbation
KW - electroencephalography
KW - follow up
KW - human
KW - middle aged
KW - nerve tract
KW - pathophysiology
KW - prognosis
KW - rest
KW - signal processing
KW - very elderly
KW - Aged
KW - Aged, 80 and over
KW - Alzheimer Disease
KW - Amnesia
KW - Brain
KW - Cognitive Dysfunction
KW - Disease Progression
KW - Follow-Up Studies
KW - Humans
KW - Middle Aged
KW - Neural Pathways
KW - Neuropsychological Tests
KW - Prognosis
KW - Rest
KW - Signal Processing, Computer-Assisted
U2 - 10.1142/S0129065720500045
DO - 10.1142/S0129065720500045
M3 - Article
VL - 30
JO - Int. J. Neural Syst.
JF - Int. J. Neural Syst.
SN - 0129-0657
IS - 2
M1 - 2050004
ER -