Neurophysiological Hallmarks of Neurodegenerative Cognitive Decline: The Study of Brain Connectivity as a Biomarker of Early Dementia

被引:32
作者
Rossini, Paolo Maria [1 ]
Miraglia, Francesca [1 ]
Alu, Francesca [1 ]
Cotelli, Maria [2 ]
Ferreri, Florinda [3 ,4 ]
Di Iorio, Riccardo [5 ]
Iodice, Francesco [1 ,5 ]
Vecchio, Fabrizio [1 ]
机构
[1] IRCCS San Raffaele Pisana, Dept Neurosci & Neurorehabil, Brain Connect Lab, I-00167 Rome, Italy
[2] IRCCS Ist Ctr San Giovanni DioFatebenefratelli, Neuropsychol Unit, I-25125 Brescia, Italy
[3] Univ Padua, Dept Neurosci, Unit Neurol & Neurophysiol, I-35100 Padua, Italy
[4] Univ Eastern Finland, Kuopio Univ Hosp, Dept Clin Neurophysiol, Kuopio 70100, Finland
[5] IRCCS Polyclin A Gemelli Fdn, Neurol Unit, I-00168 Rome, Italy
来源
JOURNAL OF PERSONALIZED MEDICINE | 2020年 / 10卷 / 02期
关键词
Alzheimer's disease; mild cognitive impairment; EEG; TMS; TRANSCRANIAL MAGNETIC STIMULATION; GRAPH-THEORETICAL ANALYSIS; ALZHEIMERS-DISEASE; CORTICAL SOURCES; ALPHA RHYTHMS; ELECTROMAGNETIC TOMOGRAPHY; FUNCTIONAL CONNECTIVITY; CORTEX EXCITABILITY; SOURCE SEPARATION; TIME-SERIES;
D O I
10.3390/jpm10020034
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Neurodegenerative processes of various types of dementia start years before symptoms, but the presence of a "neural reserve", which continuously feeds and supports neuroplastic mechanisms, helps the aging brain to preserve most of its functions within the "normality" frame. Mild cognitive impairment (MCI) is an intermediate stage between dementia and normal brain aging. About 50% of MCI subjects are already in a stage that is prodromal-to-dementia and during the following 3 to 5 years will develop clinically evident symptoms, while the other 50% remains at MCI or returns to normal. If the risk factors favoring degenerative mechanisms are modified during early stages (i.e., in the prodromal), the degenerative process and the loss of abilities in daily living activities will be delayed. It is therefore extremely important to have biomarkers able to identify-in association with neuropsychological tests-prodromal-to-dementia MCI subjects as early as possible. MCI is a large (i.e., several million in EU) and substantially healthy population; therefore, biomarkers should be financially affordable, largely available and non-invasive, but still accurate in their diagnostic prediction. Neurodegeneration initially affects synaptic transmission and brain connectivity; methods exploring them would represent a 1st line screening. Neurophysiological techniques able to evaluate mechanisms of synaptic function and brain connectivity are attracting general interest and are described here. Results are quite encouraging and suggest that by the application of artificial intelligence (i.e., learning-machine), neurophysiological techniques represent valid biomarkers for screening campaigns of the MCI population.
引用
收藏
页数:27
相关论文
共 162 条
  • [1] Abeles M., CORTICONICS NEURAL C
  • [2] EEG coherence in Alzheimer's dementia
    Adler, G
    Brassen, S
    Jajcevic, A
    [J]. JOURNAL OF NEURAL TRANSMISSION, 2003, 110 (09) : 1051 - 1058
  • [3] Impulses in the pyramidal tract
    Adrian, ED
    Moruzzi, G
    [J]. JOURNAL OF PHYSIOLOGY-LONDON, 1939, 97 (02): : 153 - 199
  • [4] Multivariate multiscale entropy: A tool for complexity analysis of multichannel data
    Ahmed, Mosabber Uddin
    Mandic, Danilo P.
    [J]. PHYSICAL REVIEW E, 2011, 84 (06):
  • [5] Aoki Y, 2015, FRONT HUM NEUROSCI, V9, DOI [10.3389/fnhurn.2015.00031, 10.3389/fnhum.2015.00031]
  • [6] Oscillatory Activities in Neurological Disorders of Elderly: Biomarkers to Target for Neuromodulation (vol 9, 189, 2017)
    Assenza, Giovanni
    Capone, Fioravante
    di Biase, Lazzaro
    Ferreri, Florinda
    Florio, Lucia
    Guerra, Andrea
    Marano, Massimo
    Paolucci, Matteo
    Ranieri, Federico
    Salomone, Gaetano
    Tombini, Mario
    Thut, Gregor
    Di Lazzaro, Vincenzo
    [J]. FRONTIERS IN AGING NEUROSCIENCE, 2017, 9
  • [7] Azami H, 2017, IEEE ENG MED BIO, P3182, DOI 10.1109/EMBC.2017.8037533
  • [8] Univariate and Multivariate Generalized Multiscale Entropy to Characterise EEG Signals in Alzheimer's Disease
    Azami, Hamed
    Abasolo, Daniel
    Simons, Samantha
    Escudero, Javier
    [J]. ENTROPY, 2017, 19 (01)
  • [9] Azami H, 2016, 2016 INTERNATIONAL CONFERENCE FOR STUDENTS ON APPLIED ENGINEERING (ICSAE), P413, DOI 10.1109/ICSAE.2016.7810227
  • [10] Improved multiscale permutation entropy for biomedical signal analysis: Interpretation and application to electroencephalogram recordings
    Azami, Hamed
    Escudero, Javier
    [J]. BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2016, 23 : 28 - 41