Abstract
Mild cognitive impairment (MCI) is a neurological disorder that degenerates into Alzheimer’s disease (AD) in 8–15% of cases. The MCI to AD conversion is due to a loss of connectivity between different areas of the brain. In this paper, a wavelet coherence approach is proposed for investigating how the brain connectivity evolves among cortical regions with the disease progression. We studied Electroencephalograph (EEG) recordings acquired from eight patients affected by MCI at time T0 and we also studied their follow up at time T1 (three months later): three of them converted to AD, five remained MCI. The EEGs were analyzed over delta, theta, alpha 1, alpha 2, beta 1 and beta 2 sub-bands. Differently from MCI stable subjects, MCI patients who converted to AD, showed a strong reduction of cortical connectivity in theta, alpha(s) and beta(s) sub-bands. Delta band showed high coherence values in each pair of electrodes in every patient.
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This work was funded by the Italian Ministry of Health, project code: GR-2011-02351397.
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Ieracitano, C., Mammone, N., La Foresta, F., Morabito, F.C. (2018). Investigating the Brain Connectivity Evolution in AD and MCI Patients Through the EEG Signals’ Wavelet Coherence. In: Esposito, A., Faudez-Zanuy, M., Morabito, F., Pasero, E. (eds) Multidisciplinary Approaches to Neural Computing. Smart Innovation, Systems and Technologies, vol 69. Springer, Cham. https://doi.org/10.1007/978-3-319-56904-8_25
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DOI: https://doi.org/10.1007/978-3-319-56904-8_25
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