Memorization test and resting state EEG components in mild and subjective cognitive impairment

BACKGROUND: Mild (MCI) and Subjective Cognitive Impairment (SCI) are conditions at risk of developing Alzheimer's disease (AD). Differential between normal aging at early stages can be really challenging; available biomarkers need to be combined and can be quite invasive and expensive. OBJECTIVE: The aim of this pilot study is to examine possible EEG alterations in MCI and SCI compared to controls, analyzing if a cognitive task could highlight early AD hallmarks. METHOD: We recruited 11 MCI, 8 SCI and 7 healthy subjects as controls (CS), all matched for age and education. Neuropsychological assessment and EEG recording, at resting state and during a mental memory task, were performed. Classical spectral measures and nonlinear parameters were used to characterize EEGs. RESULTS: During cognitive task, \u3b1-band power reduction was found predominantly in frontal regions in SCI and CS, diffused to all regions in MCI; moreover, decreased EEG complexity was found in SCI compared to controls. The \u3b1 -band power attenuation restricted to frontal regions in SCI during a free recall task (involving frontal areas), suggests that MCI patients compensate for encoding deficit by activating different brain networks to perform the same task. Furthermore, EEG complexity reduction - that has been found already in SCI - could be a possible early hallmark of AD. CONCLUSION: This study draws attention on the importance of nonlinear approach in EEG analysis and the potential role of cognitive task in highlighting EEG alterations at very early stages of cognitive impairment; EEG could therefore have a practical impact on dementia diagnosis

Linear and non-linear parameterization of EEG during monitoring of carotid endarterectomy

In this paper, new quantitative linear (HLF ratio: high frequency/low frequency spectral power ratio) and non-linear parameters (ZC: zero crossing and FD: fractal dimension) which can assist the physician in real-time decision whether a shunt is required or not during intra-operative EEG monitoring of carotid endarterectomy are presented. The results obtained with the new parameters are compared with those achieved by other indexes proposed in the literature. The HLF ratio and ZC parameters yielded the best results with a 100% of correct identification of both shunt and no-shunt situations. The ZC can be also easily implemented in the real-time monitoring of EEG