Hippocampal volume and cortical sources of EEG alpha rhythms in mild cognitive impairment and Alzheimer disease

Babiloni, Claudio; Frisoni, Giovanni B.; Pievani, Michela; Vecchio, Fabrizio; Lizio, Roberta; Buttiglione, Maura; Geroldi, Cristina; Fracassi, Claudia; Eusebi, Fabrizio; Ferri, Raffaele; Rossini, Paolo Maria

doi:10.1016/j.neuroimage.2008.08.005

Cited by 153 publications

(152 citation statements)

References 121 publications

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“…Moreover, virtually none of those methods incorporate biophysical knowledge about AD (but see [37]); detailed mathematical models of the pathology of AD, in conjunction with EEG data analysis, may help us to improve the diagnosis of AD. Along the same lines, one may expect further improvement by combining EEG with other imaging modalities, such as MRI (see, e.g., [31][32][33]), dMRI [34], TMS [35], and SPECT [36].…”

Section: Discussionmentioning

confidence: 99%

On the Early Diagnosis of Alzheimer’s Disease from EEG Signals: A Mini-Review

Dauwels

Vialatte

Cichocki

2010

Advances in Cognitive Neurodynamics (II)

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Section: Discussionmentioning

confidence: 99%

On the Early Diagnosis of Alzheimer’s Disease from EEG Signals: A Mini-Review

Dauwels

Vialatte

Cichocki

2010

Advances in Cognitive Neurodynamics (II)

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“…Interestingly, various studies have constructed source models from the EEG of MCI and AD patients [108,153,154,155,156,157,158,159,160]. We will discuss some of those studies later on in this paper.…”

Section: Perturbations In Eeg Synchrony: Discussionmentioning

confidence: 99%

Diagnosis of Alzheimers Disease from EEG Signals: Where Are We Standing?

Dauwels¹,

Vialatte²,

Cichocki³

2010

CAR

379

188

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This paper reviews recent progress in the diagnosis of Alzheimer's disease (AD) from electroencephalograms (EEG). Three major effects of AD on EEG have been observed: slowing of the EEG, reduced complexity of the EEG signals, and perturbations in EEG synchrony. In recent years, a variety of sophisticated computational approaches has been proposed to detect those subtle perturbations in the EEG of AD patients. The paper first describes methods that try to detect slowing of the EEG. Next the paper deals with several measures for EEG complexity, and explains how those measures have been used to study fluctuations in EEG complexity in AD patients. Then various measures of EEG synchrony are considered in the context of AD diagnosis.Also the issue of EEG pre-processing is briefly addressed. Before one can analyze EEG, it is necessary to remove artifacts due to for example head and eye movement or interference from electronic equipment. Pre-processing of EEG has in recent years received much attention. In this paper, several state-of-the-art pre-processing techniques are outlined, for example, based on blind source separation and other non-linear filtering paradigms.In addition, the paper outlines opportunities and limitations of computational approaches for diagnosing AD based on EEG. At last, future challenges and open problems are discussed.

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“…The most stable pattern of EEG activity in MCI patients is defined by an increase in theta accompanied by a decrease of alpha and beta power, which correlates with APOE genotype, and hippocampal volumes (Babiloni et al 2006b(Babiloni et al , c, 2009Grunwald et al 2002;Prichep et al 2006). When the progression to AD was investigated, alpha and theta relative power in left temporooccipital derivation correctly classified 85 % of MCI subjects who would suffer dementia .…”

Section: Introductionmentioning

confidence: 99%

“…Of note, the investigation of differential neurophysiological patterns in MCI subtypes is scarce. This issue was indirectly addressed by Babiloni et al (2009) within the background of a research on the relationship between hippocampal volumes and alpha rhythms. The authors assessed a potential influence of the clinical subtype (i.e., a-MCI vs. na-MCI) and found no significant differences.…”

Section: Introductionmentioning

confidence: 99%

MEG spectral analysis in subtypes of mild cognitive impairment

López

Cuesta

Garcés

et al. 2014

AGE

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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.

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Hippocampal volume and cortical sources of EEG alpha rhythms in mild cognitive impairment and Alzheimer disease

Cited by 153 publications

References 121 publications

On the Early Diagnosis of Alzheimer’s Disease from EEG Signals: A Mini-Review

On the Early Diagnosis of Alzheimer’s Disease from EEG Signals: A Mini-Review

Diagnosis of Alzheimers Disease from EEG Signals: Where Are We Standing?

MEG spectral analysis in subtypes of mild cognitive impairment

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