長者認知退化與記憶表現之腦波新特徵

本篇研究中，主要針對阿茲罕默失智症和其他種類的失智症長者去和正常長者去做比較，從單一頻道的整晚睡眠腦波中發展了新的腦波特徵去做辨識。睡眠腦波根據不同頻帶被轉換成五條能量時間序列，分別對應delta、theta、alpha、sigma、beta各個頻帶，然後採用互消息法與小波相干頻譜去發展一套演算法：針對不同的能量時間序列之間去求他們的相似度，這個相似度的指標我們命名為半相位變異數(PV)。PV值在本篇研究中被用來當作辨認失智症長者腦波的特徵。首先，在本篇研究中量測四個不同位置的腦波頻道，分別為C3-A2、C4-A1、O1-A2、O2-A1，受試者主要由7位失智症長者(包含阿茲罕默失智症和其他種類的失智症)，19位年紀相仿的正常長者和5位年輕人來當作演算法中的基線。結果發現，在C3和O1頻道，各自的alpha和theta頻帶的能量時間序列的PV值，失智症長者比起正常長者皆有顯著性的增加(p<0.001)，特別是對於阿茲罕默失智症長者更為顯著。除此之外，在C4頻道此兩頻帶的能量時間序列的PV值同樣對於失智症長者有顯著性的增加(p<0.01)。這些PV值似乎可以反映出神經生理與認知的退化，因此，似乎能當作辨別失智症長者的特徵。與傳統的10-20系統腦波量測比較起來，此方在於只要單一頻道量測即可進行失智症的辨識。此外如同先前研究定義的不同頻道之間的量測方法，在依照本篇研究法後同樣也有展示出分析結果。PV值有顯著性差異的只有出現在left local posterior區域(C3-A2 & O1-A2)的兩個不同頻道之間的alpha頻帶，其中的PV值失智症長者稍微比正常長者高(p<0.05)。另外對於right local posterior區域(C4-A1 & O2-A1)的兩個頻道之間的alpha頻帶，其PV值也呈現出相同的結果。因此，對於左右兩半腦的parietal-occipital區域，其不同頻道間alpha頻帶的相似度似乎可能當作另一個去辨別失智症長者的特徵。基於以上所得出較顯著的腦波特徵，特定頻帶之間的PV值與認知表現之間的關係也有被評估。結果顯示出PV值和MMSE分數有高度的相關性，除此之外和魏氏測驗底下的分測驗也有顯著的相關性。這些結果展現出，本篇所提出的方法似乎能有效地連結到一些臨床心理測驗。這表示對於做進一步的研究，我們所提出的方法有很好的延伸性。最後由於在我們的資料庫中有年輕人的受試者，於是針對與年齡相關的PV值的改變同樣也被列入討論，主要想去了解年齡對於腦波相似度的影響。對於不同頻道之間的相似度量測，兩個頻道同樣頻帶之間的PV值呈現出較小的值普遍發生在年輕人的群組，然而較大的值普遍發生在失智症長者。整體來說，從年輕人到正常長者到失智症長者，他們PV值的分布趨近於正相關。對於單一頻道不同頻帶之間相似度的量測，alpha和theta頻帶能量時間序列之間的PV值也呈現出相同的結果。這些一致的趨勢可以得出結論：從腦波相似性的分析來看，對於老化和失智症的症狀，其背後的病理原因可能是相似的。

關鍵字

阿茲罕默症；睡眠腦波；相似性；互消息法；小波相干頻譜；認知表現；老化

並列摘要

This study develops new markers of the Alzheimer's disease and other types of dementia for the elderly based on the all-night EEG of a single channel. The sleep EEG is transformed into 5 power time series corresponding to the delta, theta, alpha, sigma and beta frequency bands. Then, the mutual information and wavelet coherence are adopted to develop a measurement for the similarity between the power time series of a frequency band pair, denoted as the half phase variance (PV). The PV values are used as markers of the Alzheimer's disease and other types of dementia for the elderly. First of all, the sleep EEG from electrodes C3-A2, C4-A1, O1-A2 and O2-A1 have been recorded for 7 dementia's patients (including AD patients and non-AD type patients), 19 age-matched normal controls, and 5 normal young people as baseline in our algorithm. It is found that the PV of theta and alpha band power time series prominently increases in dementia's patients as compared with the controls in the C3 and O1 channels with p-value<0.001, especially for AD patients. In addition, it also increases significantly in dementia's patients in the C4 channel with p-value<0.01. These PV values seem to be able to reflect neurophysiological degeneration and thus may serve as a marker to identify dementias. Compared with conventional approach, this method is advantageous because only one channel measurement is required. Furthermore, the results of cross-similarity defined as previous studies have also been shown in the study. The significant difference of PV values only appears in the band pair of alpha of the left local posterior (C3-A2 & O1-A2) that the PV values are slightly higher in dementias than in controls (p<0.05) and the right local posterior (C4-A1 & O2-A1) have shown the same results. Thus, for the bilateral parietal-occipital regions, the PV values of alpha band pair might be another maker to identify dementias. Based on above markers, the relationships between PV of certain band pairs and cognitive performance are assessed as well. The results demonstrate that the PV values are strongly correlated with MMSE scores. In addition, the relations with the subtests of WMS scores and the PV values are also quantitative correlated. These results demonstrate our proposed method seems to be able to effectively link to well-documented neuropsychological tests. Thus, it indicates that the proposed PV possess a superior extension for further research. Lastly, the age-related changes of PV are considered to try to figure out the age effects on the EEG similarity. For cross-similarity, the PV values of the same frequency band present the lower value commonly in young people and the higher values commonly in patients. Generally, the distributions of PV from the young, the normal elderly to dementias of above cases approach the positive relations. For the auto-similarity of C3 and C4 channels, the PV values of alpha and theta band-power time series also shows the same result. These consistent trends can be concluded that some sources of pathological reason might be similar between dementias and aging.

並列關鍵字

Sleep EEG ； Similarity ； Mutual Information ； Wavelet Coherence ； Cognitive Performance ； Aging

參考文獻

Adler, G., Brassen, S., and Jajcevic A., “EEG coherence in Alzheimer’s dementia,” J.Neural Transm., vol. 110, pp.1051–1058, 2003.

Abasolo, D., Escudero, J., Hornero, R., Gomez, C., Espino, P., “Approximate entropy and auto mutual information analysis of the electroencephalogram in Alzheimer’s disease patients,” Med. Biol. Eng. Comput., vol. 46, pp. 1019-1028, 2008.

Ako, M., Kawara, T., Uchida, S., Miyazaki, S., Nishihara, K., Mukai, J., Hirao, K., Ako, J., and Okubo, Y., “Correlation between electroencephalography and heart rate variability during sleep,” Psychiatry and Clinical Neurosciences, vol.57, pp.59-65, 2003

Bennys, K., Rondouin, G., Vergnes, C., and Touchon, J., “Diagnostic value of Quantitative EEG in Alzheimer’s disease,” Neurophysiol. Clin., vol. 31, pp.153-60, 2001.

Besthorn, C., Forstl, H., Geiger-Kabisch, C., Sattel, H., Gasser, T., Schreiter-Gasser, U.,“EEG coherence in Alzheimer disease,” Electroenceph. Clin. Neurophysiol., vol.90, pp. 242-245, 1994.

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長者認知退化與記憶表現之腦波新特徵

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