Evaluation of spectral ratio measures from spontaneous MEG recordings in patients with Alzheimer's disease

Poza, Jesús; Hornero, Roberto; Abásolo, Daniel; Fernández, Alberto; Mayo, A.

doi:10.1016/j.cmpb.2007.12.004

Cited by 38 publications

(37 citation statements)

References 48 publications

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“…Spectral changes can also be characterized in terms of ratios between power in different frequency bands. In a later study Poza et al [34] showed that a ratio of relative power in fast (alpha, beta and gamma) and slow (delta theta) relative power had a sensitivity of 75% and a specificity of 95%. A comparison of spectral median frequency with various nonlinear measures showed that median frequency was the single best discriminator between AD patients and controls [35].…”

Section: Spectral Analysismentioning

confidence: 97%

Use of magnetoencephalography (MEG) to study functional brain networks in neurodegenerative disorders

Stam

2010

Journal of the Neurological Sciences

236

178

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Section: Spectral Analysismentioning

confidence: 97%

Use of magnetoencephalography (MEG) to study functional brain networks in neurodegenerative disorders

Stam

2010

Journal of the Neurological Sciences

236

178

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“…AD) [29],[30]. In many cases, group differences can be demonstrated, but group means are not sufficiently different to allow for diagnostic identification of an individual with a specific group [31]–[37]. If EEG technology can be developed to discriminate MCI from normal EEG for individuals and to show changes over relatively short time periods in and individual, it will be transformative in the early detection of MCI, AD, and other dementias, as it is more sensitive than behavioral testing, inexpensive, noninvasive, and can be made practical for primary care settings.…”

Section: Introductionmentioning

confidence: 99%

Spectral and complexity analysis of scalp EEG characteristics for mild cognitive impairment and early Alzheimer's disease

McBride

Zhao

Munro

et al. 2014

Computer Methods and Programs in Biomedicine

139

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Amnestic mild cognitive impairment (aMCI) often is an early stage of Alzheimer’s disease (AD). MCI is characterized by cognitive decline departing from normal cognitive aging but that does not significantly interfere with daily activities. This study explores the potential of scalp EEG for early detection of alterations from cognitively normal status of older adults signifying MCI and AD. Resting 32-channel EEG records from 48 age-matched participants (mean age 75.7 years)–15 normal controls (NC), 16 early MCI, and 17 early stage AD–are examined. Regional spectral and complexity features are computed and used in a support vector machine model to discriminate between groups. Analyses based on three-way classifications demonstrate discrimination accuracies of 83.9%–96.8% for MCI vs. NC (p-value<0.0029), 71.9%–96.9% for AD vs. NC (p-value<0.0333), and 87.9%–90.9% for AD vs. MCI (pvalue<0.0136), depending on the EEG protocol condition employed. These results demonstrate the great promise for scalp EEG spectral and complexity features as noninvasive biomarkers for detection of MCI and early AD.

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“…; LPS mice that showed delta power similar to controls, see figure 4H). Significantly increased delta power has been reported in Alzheimer’s patients (Poza et al, 2008). The findings of the Poza et al, studies not only indicate that spectral ratios could be useful descriptors to help in diagnosis but also correlate significantly with the severity of dementia.…”

Section: Discussionmentioning

confidence: 84%

“…Quantitative spectral EEGs are now being regularly used to identify diagnostic and prognostic markers in neurodegenerative diseases associated with dementia (Claus et al, 1998;Poza et al, 2008). Slow wave activity during NREM (i.e.…”

Section: Discussionmentioning

confidence: 99%

Circadian cycle-dependent EEG biomarkers of pathogenicity in adult mice following prenatal exposure to in utero inflammation

Adler¹,

Ammanuel²,

Lei³

et al. 2014

Neuroscience

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Intrauterine infection or inflammation in preterm neonates is a known risk for adverse neurological outcomes, including cognitive, motor and behavioral disabilities. Our previous data suggest that there is acute fetal brain inflammation in a mouse model of intrauterine exposure to lipopolysaccharides (LPS). We hypothesized that the in utero inflammation induced by LPS produces long-term EEG biomarkers of neurodegeneration in the exposed mice that could be determined by using continuous quantitative video-EEG-EMG analyses. A single LPS injection at E17 was performed in pregnant CD1 dams. Control dams were injected with same volumes of saline (LPS n=10, Control n=8). At postnatal age of P90-100, 24h synchronous video/EEG/EMG recordings were done using a tethered recording system and implanted subdural electrodes. Behavioral state scoring was performed blind to treatment group, on each 10 second EEG epochs using synchronous video, EMG and EEG trace signatures to generate individual hypnograms. Automated EEG power spectrums were analyzed for delta and theta-beta power ratios during wake vs. sleep cycles. Both control and LPS hypnograms showed an ultradian wake/sleep cycling. Since rodents are nocturnal animals, control mice showed the expected diurnal variation with significantly longer time spent in wake states during the dark cycle phase. In contrast, the LPS treated mice lost this circadian rhythm. Sleep microstructure also showed significant alteration in the LPS mice specifically during the dark cycle, caused by significantly longer average NREM cycle durations. No significance was found between treatment groups for the delta power data; however, significant activity dependent changes in theta-beta power ratios seen in controls were absent in the LPS-exposed mice. In conclusion, exposure to in utero inflammation in CD1 mice resulted in significantly altered sleep architecture as adults that were circadian cycle and activity state dependent.

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Evaluation of spectral ratio measures from spontaneous MEG recordings in patients with Alzheimer's disease

Cited by 38 publications

References 48 publications

Use of magnetoencephalography (MEG) to study functional brain networks in neurodegenerative disorders

Use of magnetoencephalography (MEG) to study functional brain networks in neurodegenerative disorders

Spectral and complexity analysis of scalp EEG characteristics for mild cognitive impairment and early Alzheimer's disease

Circadian cycle-dependent EEG biomarkers of pathogenicity in adult mice following prenatal exposure to in utero inflammation

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