Author/Authors :
Chan، نويسنده , , Hsiao-Lung and Chu، نويسنده , , Ju-His and Fung، نويسنده , , Hon-Chung and Tsai، نويسنده , , Yu-Tai and Meng، نويسنده , , Ling-Fu and Huang، نويسنده , , Chin-Chang and Hsu، نويسنده , , Wen-Chun and Chao، نويسنده , , Pei-Kuang and Wang، نويسنده , , Jiun-Jie and Lee، نويسنده , , Jiann-Der and Wai، نويسنده , , Yau-Yau and Tsai، نويسنده , , Meng-Tsan، نويسنده ,
Abstract :
Alzheimerʹs disease (AD) is a neurodegenerative disease, usually diagnosed by neuropsychological tests, and excluded from other cerebral diseases by brain images. An electroencephalogram (EEG) provides a means of disclosing the reduced functional couplings between brain regions that occurs with AD. In the present study, 16 probable AD patients and 15 age-matched, gender-matched normal subjects were enrolled. Spectral coherence and cross mutual information (CMI) were used to analyze EEGs during intermittent photic stimulation (PS). Ocular- and heartbeat-related source components (SCs) obtained from multi-channel EEGs by the independent component analysis were discarded, and the photic-related SCs were reduced using a comb filter. The undisturbed SCs and photic-related SCs before and after photic reduction were used to reconstruct photic-preserved EEGs and photic-reduced EEGs, from which harmonic coherences (direct photic-driving response) and rhythmic coherences and CMI (indirect photic affection) were computed, respectively. Our results indicate that the rhythmic coherences (particularly in the alpha and beta bands) and CMI variables as well as the harmonic coherences (particularly related to 3-Hz PS) were significantly lower in the probable AD than in normal subjects, whereas the variables derived from the resting EEGs were not statistically significant. This finding implied that the variables obtained during PS could be used to disclose impaired intra-brain associations in probable AD.
Keywords :
Alzheimerיs disease , electroencephalogram , Cross mutual information , COHERENCE , Photic stimulation , Independent Component Analysis