Conversion from mild cognitive impairment to Alzheimer’s disease is predicted by sources and coherence of brain electroencephalography rhythms

Rossini, Paolo Maria; Percio, Claudio Del; Pasqualetti, Patrizio; Cassetta, Emanuele; Binetti, Giuliano; Forno, Gloria Dal; Ferreri, Florinda; Frisoni, Giovanni B.; Chiovenda, Paola; Miniussi, Carlo; Parisi, Laura; Tombini, Mario; Vecchio, Fabrizio; Babiloni, Claudio

doi:10.1016/j.neuroscience.2006.08.049

Cited by 248 publications

(225 citation statements)

References 79 publications

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“…Similar to our findings, Spiegel et al (2006) have found that cognitive impairment of AD is characterized by decreased power and coherence in the alpha/beta frequency band while increased power and coherence in the delta/theta frequency band. Rossini et al (2006) have also distinguished subjects of mild cognitive impairment (MCI) from AD subjects reliably by the analysis of EEG power and coherence. However, these studies only apply one separate feature, either PSD or coherence, to classify AD patients and the normal controls.…”

Section: Discussionmentioning

confidence: 99%

Power spectral density and coherence analysis of Alzheimer’s EEG

et al. 2014

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In this paper, we investigate the abnormalities of electroencephalograph (EEG) signals in the Alzheimer's disease (AD) by analyzing 16-scalp electrodes EEG signals and make a comparison with the normal controls. The power spectral density (PSD) which represents the power distribution of EEG series in the frequency domain is used to evaluate the abnormalities of AD brain. Spectrum analysis based on autoregressive Burg method shows that the relative PSD of AD group is increased in the theta frequency band while significantly reduced in the alpha2 frequency bands, particularly in parietal, temporal, and occipital areas. Furthermore, the coherence of two EEG series among different electrodes is analyzed in the alpha2 frequency band. It is demonstrated that the pair-wise coherence between different brain areas in AD group are remarkably decreased. Interestingly, this decrease of pairwise electrodes is much more significant in inter-hemispheric areas than that in intra-hemispheric areas. Moreover, the linear cortico-cortical functional connectivity can be extracted based on coherence matrix, from which it is shown that the functional connections are obviously decreased, the same variation trend as relative PSD. In addition, we combine both features of the relative PSD and the normalized degree of functional network to discriminate AD patients from the normal controls by applying a support vector machine model in the alpha2 frequency band. It is indicated that the two groups can be clearly classified by the combined feature. Importantly, the accuracy of the classification is higher than that of any one feature. The obtained results show that analysis of PSD and coherence-based functional network can be taken as a potential comprehensive measure to distinguish AD patients from the normal, which may benefit our understanding of the disease.

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Section: Discussionmentioning

confidence: 99%

Power spectral density and coherence analysis of Alzheimer’s EEG

et al. 2014

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“…Increase of relative theta power by itself or in combination with changes in other frequencies has in several studies differentiated early forms of AD from controls, and has showed intermediate characteristics in MCI [11,29,30,33,44,48]. A suggested sequence of changes in EEG frequencies during AD development could be extrapolated from current published data on MCI samples.…”

Section: Introductionmentioning

confidence: 96%

Slowing of EEG correlates with CSF biomarkers and reduced cognitive speed in elderly with normal cognition over 4 years

Stomrud

Hansson

Minthon

et al. 2010

Neurobiology of Aging

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“…Bajo et al (2010) found higher interhemispheric synchronization likelihood in MCI between left and right temporo-frontal sensors in most frequency bands during a short-term memory task and higher connectivity for those that later on developed dementia (Bajo et al 2012). This increase in functional connectivity is usually interpreted as a compensatory mechanism and is associated with the risk for the progression to AD (Rossini et al 2006). Indeed, it seems to indicate a loss of brain efficiency (Buldú et al 2011).…”

Section: Introductionmentioning

confidence: 98%

Synchronization during an internally directed cognitive state in healthy aging and mild cognitive impairment: a MEG study

López

Garcés

Cuesta

et al. 2014

AGE

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Mild cognitive impairment (MCI) is a stage between healthy aging and dementia. It is known that in this condition the connectivity patterns are altered in the resting state and during cognitive tasks, where an extra effort seems to be necessary to overcome cognitive decline. We aimed to determine the functional connectivity AGE (2014) pattern required to deal with an internally directed cognitive state (IDICS) in healthy aging and MCI. This task differs from the most commonly employed ones in neurophysiology, since inhibition from external stimuli is needed, allowing the study of this control mechanism. To this end, magnetoencephalographic (MEG) signals were acquired from 32 healthy individuals and 38 MCI patients, both in resting state and while performing a subtraction task of two levels of difficulty. Functional connectivity was assessed with phase locking value (PLV) in five frequency bands. Compared to controls, MCIs showed higher PLV values in delta, theta, and gamma bands and an opposite pattern in alpha, beta, and gamma bands in resting state. These changes were associated with poorer neuropsychological performance. During the task, this group exhibited a hypersynchronization in delta, theta, beta, and gamma bands, which was also related to a lower cognitive performance, suggesting an abnormal functioning in this group. Contrary to controls, MCIs presented a lack of synchronization in the alpha band which may denote an inhibition deficit. Additionally, the magnitude of connectivity changes rose with the task difficulty in controls but not in MCIs, in line with the compensation-related utilization of neural circuits hypothesis (CRUNCH) model.

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Conversion from mild cognitive impairment to Alzheimer’s disease is predicted by sources and coherence of brain electroencephalography rhythms

Cited by 248 publications

References 79 publications

Power spectral density and coherence analysis of Alzheimer’s EEG

Power spectral density and coherence analysis of Alzheimer’s EEG

Slowing of EEG correlates with CSF biomarkers and reduced cognitive speed in elderly with normal cognition over 4 years

Synchronization during an internally directed cognitive state in healthy aging and mild cognitive impairment: a MEG study

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