Altered motor performance in Alzheimer's disease: a dynamic analysis using EEG

被引:0
|
作者
Allouch, Sahar [1 ]
Tabbal, Judie [1 ,2 ]
Nasser, Assef [3 ]
Hassan, Mahmoud [2 ]
Khalil, Mohamad [1 ,4 ]
Kabbara, Aya [2 ]
机构
[1] Lebanese Univ, EDST, Azm Ctr Res Biotechnol & Its Applicat, Tripoli, Lebanon
[2] INSERM, U1099, LTSI, F-35000 Rennes, France
[3] Vita Nova Polyclin, Tripoli, Lebanon
[4] Lebanese Univ, Fac Engn, CRSI Res Ctr, Tripoli, Lebanon
关键词
Alzheimer' s disease; Electroencephalography; motor task; static analysis; dynamic analysis; BRAIN NETWORKS; MEG; SYNCHRONIZATION; CONNECTIVITY; ATROPHY;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive memory impairment and cognitive deficits. Many previous studies assumed stationarity of the brain activity while quantifying differences between AD patients and controls. However, the human brain is a dynamic system, and cognitive processes may change at sub-second timescale. The main objective of this study is to investigate the advantage of dynamic analysis over static analysis in detecting the brain alterations occurred in AD. Therefore, using electroencephalography data recorded from 10 AD patients and 12 healthy elderly controls while performing a motor task, we investigated the channel-level differences in voltage distribution between AD and controls with both, static and dynamic approaches. While static analysis showed similar response for both groups, dynamic analysis revealed significant differences in different brain regions during the first 200 ms following stimulus onset. These findings highlight the necessity of adopting a dynamic analysis when exploring brain activity differences between AD and controls.
引用
收藏
页码:176 / 179
页数:4
相关论文
共 50 条
  • [41] EEG Multifractal Analysis in Mild Cognitive Impairment/Alzheimer's Disease
    Zorick, Todd
    Leuchter, Andrew
    Mandelkern, Mark
    NEUROPSYCHOPHARMACOLOGY, 2019, 44 (SUPPL 1) : 156 - 156
  • [42] EEG spectral analysis in normal aging and mild Alzheimer's disease
    Luongo, C.
    Paone, G.
    Russo, G.
    Vescia, S.
    JOURNAL OF PSYCHOPHYSIOLOGY, 2006, 20 (03) : 220 - 220
  • [43] EEG spectral analysis in Alzheimer's disease and different degenerative dementias
    Pucci, E
    Cacchiò, G
    Angeloni, R
    Belardinelli, N
    Nolfe, G
    Signorino, M
    Angeleri, F
    ARCHIVES OF GERONTOLOGY AND GERIATRICS, 1998, 26 (03) : 283 - 297
  • [44] Entropy analysis of the EEG background activity in Alzheimer's disease patients
    Abásolo, D
    Hornero, R
    Espino, P
    Alvarez, D
    Poza, J
    PHYSIOLOGICAL MEASUREMENT, 2006, 27 (03) : 241 - 253
  • [45] Computational methods of EEG signals analysis for Alzheimer's disease classification
    Vicchietti, Mario L.
    Ramos, Fernando M.
    Betting, Luiz E.
    Campanharo, Andriana S. L. O.
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [46] Computational methods of EEG signals analysis for Alzheimer’s disease classification
    Mário L. Vicchietti
    Fernando M. Ramos
    Luiz E. Betting
    Andriana S. L. O. Campanharo
    Scientific Reports, 13
  • [47] Signature Execution in Alzheimer's Disease: An Analysis of Motor Features
    Fernandes, Carina
    Montalvo, Gemma
    Pertsinakis, Michael
    Guimaraes, Joana
    INTERTWINING GRAPHONOMICS WITH HUMAN MOVEMENTS, IGS 2021, 2022, 13424 : 349 - 354
  • [48] Grand Total EEG analysis in frontotemporal dementia and Alzheimer's disease
    Ioannidis, P.
    Papadopoulos, G.
    Mpakirtzis, C.
    Koufou, E.
    Afrantou, T.
    Karakostas, D.
    EUROPEAN JOURNAL OF NEUROLOGY, 2015, 22 : 682 - 682
  • [49] Alzheimer's classification using dynamic ensemble of classifiers selection algorithms: A performance analysis
    Niyas, Muhammed K. P.
    Thiyagarajan, P.
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2021, 68
  • [50] Quantitative EEG and dynamic susceptibility contrast MRI in Alzheimer's disease: a correlative study
    Mattia, D
    Babilonia, F
    Romigi, A
    Cincotti, F
    Bianchi, L
    Sperli, F
    Placidi, F
    Bozzao, A
    Glacomini, P
    Floris, R
    Marciani, MG
    CLINICAL NEUROPHYSIOLOGY, 2003, 114 (07) : 1210 - 1216