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Microstate connectivity alterations in patients with early Alzheimer's disease.

Hatz F, Hardmeier M, Benz N, Ehrensperger M, Gschwandtner U, Rüegg S, Schindler C, Monsch AU, Fuhr P - Alzheimers Res Ther (2015)

Bottom Line: Networks were reduced to 22 nodes for statistical analysis.The domain score for verbal learning and memory and the microstate segmented PLI between the left centro-lateral and parieto-occipital regions in the theta band at baseline differentiated significantly between the groups.Combining neuropsychological and quantitative EEG test results allows differentiation between subjects with aMCI remaining stable and subjects with aMCI deteriorating over 30 months.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurology, University Hospital of Basel, Petersgraben 4, 4031, Basel, Switzerland. florian.hatz@usb.ch.

ABSTRACT

Introduction: Electroencephalography (EEG) microstates and brain network are altered in patients with Alzheimer's disease (AD) and discussed as potential biomarkers for AD. Microstates correspond to defined states of brain activity, and their connectivity patterns may change accordingly. Little is known about alteration of connectivity in microstates, especially in patients with amnestic mild cognitive impairment with stable or improving cognition within 30 months (aMCI).

Methods: Thirty-five outpatients with aMCI or mild dementia (mean age 77 ± 7 years, 47% male, Mini Mental State Examination score ≥24) had comprehensive neuropsychological and clinical examinations. Subjects with cognitive decline over 30 months were allocated to the AD group, subjects with stable or improving cognition to the MCI-stable group. Results of neuropsychological testing at baseline were summarized in six domain scores. Resting state EEG was recorded with 256 electrodes and analyzed using TAPEEG. Five microstates were defined and individual data fitted. After phase transformation, the phase lag index (PLI) was calculated for the five microstates in every subject. Networks were reduced to 22 nodes for statistical analysis.

Results: The domain score for verbal learning and memory and the microstate segmented PLI between the left centro-lateral and parieto-occipital regions in the theta band at baseline differentiated significantly between the groups. In the present sample, they separated in a logistic regression model with a 100% positive predictive value, 60% negative predictive value, 100% specificity and 77% sensitivity between AD and MCI-stable.

Conclusions: Combining neuropsychological and quantitative EEG test results allows differentiation between subjects with aMCI remaining stable and subjects with aMCI deteriorating over 30 months.

No MeSH data available.


Related in: MedlinePlus

Significant correlations of regional relative theta power and domain scores. FP frontal parieto-occipital left, FM frontal midline, FL frontal lateral, CM central midline, CL central lateral, TA temporal anterior, TP temporal posterior, PL parietal lateral, PM parietal midline, PO parieto-occipital, O occipital, L left, R right. Violet: p < 0.05; red: p < 0.01 (corrected for multiple comparisons, all subjects included)
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Fig3: Significant correlations of regional relative theta power and domain scores. FP frontal parieto-occipital left, FM frontal midline, FL frontal lateral, CM central midline, CL central lateral, TA temporal anterior, TP temporal posterior, PL parietal lateral, PM parietal midline, PO parieto-occipital, O occipital, L left, R right. Violet: p < 0.05; red: p < 0.01 (corrected for multiple comparisons, all subjects included)

Mentions: HC subjects and MCI-stable patients had significantly lower theta power and higher median frequency than patients with AD and tended to have higher alpha2 power. The results of regional analysis are shown in Fig. 2. Theta power differentiated most significantly between AD and MCI-stable (Table 3), classified with a sensitivity of 67 %, specificity of 85 %, positive predictive value of 88 %, and negative predictive value of 60 %. A higher relative theta power correlated with lower z-score for verbal learning and memory, visual learning and memory, executive motor ability, and verbal language production (Fig. 3).Fig. 2


Microstate connectivity alterations in patients with early Alzheimer's disease.

Hatz F, Hardmeier M, Benz N, Ehrensperger M, Gschwandtner U, Rüegg S, Schindler C, Monsch AU, Fuhr P - Alzheimers Res Ther (2015)

Significant correlations of regional relative theta power and domain scores. FP frontal parieto-occipital left, FM frontal midline, FL frontal lateral, CM central midline, CL central lateral, TA temporal anterior, TP temporal posterior, PL parietal lateral, PM parietal midline, PO parieto-occipital, O occipital, L left, R right. Violet: p < 0.05; red: p < 0.01 (corrected for multiple comparisons, all subjects included)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4697314&req=5

Fig3: Significant correlations of regional relative theta power and domain scores. FP frontal parieto-occipital left, FM frontal midline, FL frontal lateral, CM central midline, CL central lateral, TA temporal anterior, TP temporal posterior, PL parietal lateral, PM parietal midline, PO parieto-occipital, O occipital, L left, R right. Violet: p < 0.05; red: p < 0.01 (corrected for multiple comparisons, all subjects included)
Mentions: HC subjects and MCI-stable patients had significantly lower theta power and higher median frequency than patients with AD and tended to have higher alpha2 power. The results of regional analysis are shown in Fig. 2. Theta power differentiated most significantly between AD and MCI-stable (Table 3), classified with a sensitivity of 67 %, specificity of 85 %, positive predictive value of 88 %, and negative predictive value of 60 %. A higher relative theta power correlated with lower z-score for verbal learning and memory, visual learning and memory, executive motor ability, and verbal language production (Fig. 3).Fig. 2

Bottom Line: Networks were reduced to 22 nodes for statistical analysis.The domain score for verbal learning and memory and the microstate segmented PLI between the left centro-lateral and parieto-occipital regions in the theta band at baseline differentiated significantly between the groups.Combining neuropsychological and quantitative EEG test results allows differentiation between subjects with aMCI remaining stable and subjects with aMCI deteriorating over 30 months.

View Article: PubMed Central - PubMed

Affiliation: Department of Neurology, University Hospital of Basel, Petersgraben 4, 4031, Basel, Switzerland. florian.hatz@usb.ch.

ABSTRACT

Introduction: Electroencephalography (EEG) microstates and brain network are altered in patients with Alzheimer's disease (AD) and discussed as potential biomarkers for AD. Microstates correspond to defined states of brain activity, and their connectivity patterns may change accordingly. Little is known about alteration of connectivity in microstates, especially in patients with amnestic mild cognitive impairment with stable or improving cognition within 30 months (aMCI).

Methods: Thirty-five outpatients with aMCI or mild dementia (mean age 77 ± 7 years, 47% male, Mini Mental State Examination score ≥24) had comprehensive neuropsychological and clinical examinations. Subjects with cognitive decline over 30 months were allocated to the AD group, subjects with stable or improving cognition to the MCI-stable group. Results of neuropsychological testing at baseline were summarized in six domain scores. Resting state EEG was recorded with 256 electrodes and analyzed using TAPEEG. Five microstates were defined and individual data fitted. After phase transformation, the phase lag index (PLI) was calculated for the five microstates in every subject. Networks were reduced to 22 nodes for statistical analysis.

Results: The domain score for verbal learning and memory and the microstate segmented PLI between the left centro-lateral and parieto-occipital regions in the theta band at baseline differentiated significantly between the groups. In the present sample, they separated in a logistic regression model with a 100% positive predictive value, 60% negative predictive value, 100% specificity and 77% sensitivity between AD and MCI-stable.

Conclusions: Combining neuropsychological and quantitative EEG test results allows differentiation between subjects with aMCI remaining stable and subjects with aMCI deteriorating over 30 months.

No MeSH data available.


Related in: MedlinePlus