The decline of quantitative EEG goes along with neuropathology in Alzheimer’s Disease

Background Few studies investigate the correlation between the quantitative EEG (QEEG) and the neuropathological picture. The purpose of this study is to explore how QEEG can recognize the type and extent of neuropathological changes. Method The EEG traces and brains belonging to 14 donors of the Abbiategrasso Brain Bank were analyzed. The subjects suffered from neurocognitive disorders due to AD, LBD or AD/vascular lesions (mixed dementia‐MD), with different stages of clinical and neuropathological severity. Clinical and neuropathological characterization was performed according to our protocol; biochemical measurements to determine the amount of proteinopathies are in runtime on frozen samples. QEEG analysis considered the relative power distribution (RPD) of the frequency bands (β, α, θ, δ) and the peak frequency (PF), i.e. the most represented frequency considering all the leads. The PF was measured every 2 seconds for 200‐400 samples, and then averaged. The Kruskall‐Wallis test was used for the comparison between groups. Result The clinical diagnosis included: 2 MCI, 4 AD, 6 MD, and 2 LBD. The neuropathological definite diagnosis demonstrated frequent co‐pathologies, and some discrepancies compared to the clinical diagnosis. The neuropathological characterization identified 2 cases with low AD pathology (corresponding to the 2 MCI), 8 cases with intermediate or high AD pathology (4 MD with concomitant cerebrovascular disease), and 4 cases with prevalent LBD pathology. Considering both clinical and neuropathological diagnoses, the comparison between groups revealed no significant differences in QEEG parameters. Nonetheless, a trend emerges towards a lower β‐RPD and a higher θ‐RPD in cases with prevalent LBD pathology. Grouping based on the severity of AD pathology (2 low, 4 intermediate, 4 high) demonstrated significant differences depending upon the neuropathological scoring with a progressive decrease of α‐RPD (p = 0.029) and PF (p = 0.019), and an increase of δ‐RPD (p = 0.020). Conclusion RPD and PF show low discriminatory capacity on etiology. Nonetheless, the presence of LBD seems to boost the EEG slowing. The PF slowing down parallels the increase of AD pathology, representing an indicator for the degenerative load. PF is a simple QEEG parameter, easily obtainable through standard digital EEG; it can be useful for monitoring neurodegenerative burden and disease evolution.