MEG spectral analysis in subtypes of mild cognitive impairment

Abstract

Mild cognitive impairment (MCI) has been described as an intermediate stage between normal aging and dementia. Previous studies characterized the alterations of brain oscillatory activity at this stage, but little is known about the differences between single and multidomain amnestic MCI patients. In order to study the patterns of oscillatory magnetic activity in amnestic MCI subtypes, a total of 105 subjects underwent an eyes-closed resting-state magnetoencephalographic recording: 36 healthy controls, 33 amnestic single domain MCIs (a-sd-MCI), and 36 amnestic multidomain MCIs (a-md-MCI). Relative power values were calculated and AGE (2014) compared among groups. Subsequently, relative power values were correlated with neuropsychological tests scores and hippocampal volumes. Both MCI groups showed an increase in relative power in lower frequency bands (delta and theta frequency ranges) and a decrease in power values in higher frequency bands (alpha and beta frequency ranges), as compared with the control group. More importantly, clear differences emerged from the comparison between the two amnestic MCI subtypes. The a-md-MCI group showed a significant power increase within delta and theta ranges and reduced relative power within alpha and beta ranges. Such pattern correlated with the neuropsychological performance, indicating that the a-md-MCI subtype is associated not only with a "slowing" of the spectrum but also with a poorer cognitive status. These results suggest that a-md-MCI patients are characterized by a brain activity profile that is closer to that observed in Alzheimer disease. Therefore, it might be hypothesized that the likelihood of conversion to dementia would be higher within this subtype.

Alpha band disruption in the AD-continuum starts in the Subjective Cognitive Decline stage: a MEG study

“…Reduction in alpha band power in MCI has been largely reported in the literature as one of the most robust and consistent changes in the MCI power spectrum2126. However the present work adds valuable spatial information as MEG data was reconstructed in the source space.…”

“…EEG and MEG have been proven useful in characterizing different stages of the AD continuum2021. The most characteristic finding regarding the spectral profile of AD is the slowing of the brain rhythms22.…”

“…Furthermore, mean alpha frequency in MEG power spectra is reduced in MCI patients indicating that the beginning of this slowing may take place in the pre-dementia stage25. MCI patients, both amnestic single and multi-domain show a similar pattern, with an increase in delta and theta power and decremented alpha and beta power212627. Alpha rhythm is of crucial importance.…”

Circulating IGF-1 deficiency exacerbates hypertension-induced microvascular rarefaction in the mouse hippocampus and retrosplenial cortex: implications for cerebromicrovascular and brain aging

“…Circulating IGF-1 levels and blood pressure measurements Although the factors responsible for the deleterious effects of aging on behavior and neuronal function (Baciu et al 2016;Berghuis et al 2015;Campbell et al 2014;Doi et al 2015;Haider et al 2014;Hofmann et al 2014;Kumar and Thakur 2015;Lopez et al 2014;Manich et al 2014;Salminen et al 2014;Samaras et al 2014;Sarubbo et al 2015;Loprinzi 2016;Wallis et al 2016) are not completely understood, there is strong evidence that in elderly humans a decline in circulating IGF-1 levels (Franco et al 2014) plays a critical pathophysiological role. To understand the effects of IGF-1 deficiency on the cerebral microcirculation in the present study, we used a novel mouse model of adult-onset isolated endocrine IGF-1 deficiency, which phenotypically better mimics age-related IGF-1 deficiency observed in humans that most other available rodent models of GH/IGF-1 deficiency (Arum et al 2014a;Hill et al 2015;Rojanathammanee et al 2014;Wiesenborn et al 2014;Arum et al 2014b;Schneider et al 2014).…”

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

“…There is particular potential in EEG and MEG methods to provide such a surrogate biomarker for clinical outcome. Moreover, there is evidence that some MEG markers of functional brain networks may be predictive of the conversion from MCI to AD dementia [397, 400, 404]. …”