Systematic Review on Resting-State EEG for Alzheimer’s Disease Diagnosis and Progression Assessment

Abstract

Alzheimer's disease (AD) is a neurodegenerative disorder that accounts for nearly 70% of the more than 46 million dementia cases estimated worldwide. Although there is no cure for AD, early diagnosis and an accurate characterization of the disease progression can improve the quality of life of AD patients and their caregivers. Currently, AD diagnosis is carried out using standardized mental status examinations, which are commonly assisted by expensive neuroimaging scans and invasive laboratory tests, thus rendering the diagnosis time consuming and costly. Notwithstanding, over the last decade, electroencephalography (EEG) has emerged as a noninvasive alternative technique for the study of AD, competing with more expensive neuroimaging tools, such as MRI and PET. This paper reports on the results of a systematic review on the utilization of resting-state EEG signals for AD diagnosis and progression assessment. Recent journal articles obtained from four major bibliographic databases were analyzed. A total of 112 journal articles published from January 2010 to February 2018 were meticulously reviewed, and relevant aspects of these papers were compared across articles to provide a general overview of the research on this noninvasive AD diagnosis technique. Finally, recommendations for future studies with resting-state EEG were presented to improve and facilitate the knowledge transfer among research groups.

The Power of EEG to Predict Conversion from Mild Cognitive Impairment and Subjective Cognitive Decline to Dementia

“…It turned out that using the qEEG DI, the dis criminatory power was of moderate degree, correspond ing to a sensitivity of 71%, specificity of 68%, and accu racy of 69%. It is difficult to compare our results with those of other EEG studies that have examined the power of EEG to predict conversion as the populations differ in size and cognition, the analytic methods differ, and ROC analyses have not always been done [26][27][28][29][30]. However, Poil et al [26] could report a sensitivity of 88% and spec ificity of 87% applying several βrelated frequencies (13-30 HZ), whereas Moretti [27] found the α3/α2 frequency power ratio corresponded well with MRI findings indi cating AD.…”

“…Electroencephalography (EEG), on the other hand, is a lowcost, noninvasive, simple examination that can be used in most clinics and even in primary care settings, especially if an automatic reading method is applied. In the last decade, studies were published which examined the power of EEG to detect those persons with MCI that will convert to dementia [26][27][28][29][30]. Further, our Nordic group has examined the validity of automated quantita tive EEG (qEEG) using the statistical pattern recogni tion (SPR) method, and various results have demon strated how this method can be used to separate patients with dementia from healthy controls (HC) [31][32][33][34][35][36][37].…”

Reproducibility of EEG functional connectivity in Alzheimer’s disease

“…As a result, there is a broad consensus concerning the typical spectral changes in AD. Functional connectivity and network analyses on the other hand require more complex calculations and are subject to choices in the use of different properties of the EEG signal [9]. A broad and general consensus about changes in functional connectivity or brain networks is therefore more complicated.…”

Potential New Approaches for Diagnosis of Alzheimer's Disease and Related Dementias

“…Since the patient is not required to perform a behavioral task, it is more comfortable and less stressful for patients (24). There are four effects of AD that have been reported in repeated studies in resting state EEG (25). There is a slowing of the power spectrum from high frequency (alpha, beta, gamma) to a low frequency in patients with AD (26).…”