Dynamic Functional Connectivity of EEG: From Identifying Fingerprints to Gender Differences to a General Blueprint for the Brain's Functional Organization.

An individual's brain functional organization is unique and can reliably be observed using modalities such as functional magnetic resonance imaging (fMRI). Here we demonstrate that a quantification of the dynamics of functional connectivity (FC) as measured using electroencephalography (EEG) offers an alternative means of observing an individual's brain functional organization. Using data from both healthy individuals as well as from patients with Parkinson's disease (PD) (n = 103 healthy individuals, n = 57 PD patients), we show that "dynamic FC" (DFC) profiles can be used to identify individuals in a large group. Furthermore, we show that DFC profiles predict gender and exhibit characteristics shared both among individuals as well as between both hemispheres. Furthermore, DFC profile characteristics are frequency band specific, indicating that they reflect distinct processes in the brain. Our empirically derived method of DFC demonstrates the potential of studying the dynamics of the functional organization of the brain using EEG.

EEG Slowing and Axial Motor Impairment Are Independent Predictors of Cognitive Worsening in a Three-Year Cohort of Patients With Parkinson's Disease.

Objective: We aimed to determine whether the combination of two parameters: (a) score of axial impairment and limb rigidity (SAILR) with (b) EEG global relative median power in the frequency range theta 4-8 Hz (GRMPT) predicted cognitive outcome in patients with Parkinson's disease (PD) better than each of these measures alone. Methods: 47 non-demented patients with PD were examined and re-examined after 3 years. At both time-points, the patients underwent a comprehensive neuropsychological and neurological assessment and EEG in eyes-closed resting-state condition. The results of cognitive tests were normalized and individually summarized to obtain a "global cognitive score" (GCS). Change of GCS was used to represent cognitive changes over time. GRMPT and SAILR was used for further analysis. Linear regression models were calculated. Results: GRMPT and SAILR independently predicted cognitive change. Combination of GRMPT and SAILR improved the significance of the regression model as compared to using each of these measures alone. GRMPT and SAILR only slightly correlate between each other. Conclusion: The combination of axial signs and rigidity with quantitative EEG improves early identification of patients with PD prone to severe cognitive decline. GRMPT and SAILR seem to reflect different disease mechanisms. Significance Combination of EEG and axial motor impairment assessment may be a valuable marker in the cognitive prognosis of PD.

A Comparison of Serial Position Effects in Patients with Mild Cognitive Impairment due to Parkinson's Disease or to Alzheimer's Disease.

OBJECTIVE: The first (primacy region) and last (recency region) items of a word list are generally better memorized than items from the middle region. The recency effect depends on short-term memory (STM) and the primacy effect on long-term memory (LTM), where verbal information is transferred from STM into LTM by maintenance rehearsal. We compared the serial position effects (SPE) between patients with mild cognitive impairment (MCI) due to Parkinson's disease (PD), i.e., PD-MCI, and patients with MCI due to Alzheimer's disease (AD-MCI), and evaluated the influence of SPE and frontostriatal deficits on verbal memory recall. METHODS: Four similar groups of subjects participated in the study: 26 PD-MCI patients, 26 cognitively normal patients with PD (PD-CN), 26 AD-MCI patients, and 26 normal controls (NC). Verbal episodic memory, verbal span, attentional capacity, executive functions, and verbal working memory performance were assessed. Measures for primacy and recency regions were defined at the first trial of a 16-items word list. Hierarchical regression models were used to investigate the contribution of frontostriatal deficits beyond SPE on verbal memory recall performance ("long-delay free recall") in PD and AD patients. RESULTS: Primacy effects were significantly diminished in both PD-MCI and AD-MCI patients relative to NC and PD-CN (all p < 0.01). Compared to PD-MCI patients, AD-MCI patients exhibited significantly worse "delayed-recall 'savings'." Reduced primacy effect was predictive for decreased recall performance in PD and AD. The conducted hierarchical regression model revealed that in PD, but not in AD patients, performance of attention and executive function significantly increased the prediction of free recalled words. CONCLUSIONS: Reduced recall performance is likely due to impaired transition of newly learned material from STM into LTM in AD and in PD. Whereas AD-MCI patients suffer from a storage deficit, the similarly reduced recall performance found in patients with PD-MCI may additionally be related to deficient attentional and executive capacity.

Phase lag index and spectral power as QEEG features for identification of patients with mild cognitive impairment in Parkinson's disease.

OBJECTIVES: To identify quantitative EEG frequency and connectivity features (Phase Lag Index) characteristic of mild cognitive impairment (MCI) in Parkinson's disease (PD) patients and to investigate if these features correlate with cognitive measures of the patients. METHODS: We recorded EEG data for a group of PD patients with MCI (n = 27) and PD patients without cognitive impairment (n = 43) using a high-resolution recording system. The EEG files were processed and 66 frequency along with 330 connectivity (phase lag index, PLI) measures were calculated. These measures were used to classify MCI vs. MCI-free patients. We also assessed correlations of these features with cognitive tests based on comprehensive scores (domains). RESULTS: PLI measures classified PD-MCI from non-MCI patients better than frequency measures. PLI in delta, theta band had highest importance for identifying patients with MCI. Amongst cognitive domains, we identified the most significant correlations between Memory and Theta PLI, Attention and Beta PLI. CONCLUSION: PLI is an effective quantitative EEG measure to identify PD patients with MCI. SIGNIFICANCE: We identified quantitative EEG measures which are important for early identification of cognitive decline in PD.

Quantitative EEG and Verbal Fluency in DBS Patients: Comparison of Stimulator-On and -Off Conditions.

Introduction: Deep brain stimulation of the subthalamic nucleus (STN-DBS) ameliorates motor function in patients with Parkinson's disease and allows reducing dopaminergic therapy. Beside effects on motor function STN-DBS influences many non-motor symptoms, among which decline of verbal fluency test performance is most consistently reported. The surgical procedure itself is the likely cause of this decline, while the influence of the electrical stimulation is still controversial. STN-DBS also produces widespread changes of cortical activity as visualized by quantitative EEG. The present study aims to link an alteration in verbal fluency performance by electrical stimulation of the STN to alterations in quantitative EEG. Methods: Sixteen patients with STN-DBS were included. All patients had a high density EEG recording (256 channels) while testing verbal fluency in the stimulator on/off situation. The phonemic, semantic, alternating phonemic and semantic fluency was tested (Regensburger Wortflüssigkeits-Test). Results: On the group level, stimulation of STN did not alter verbal fluency performance. EEG frequency analysis showed an increase of relative alpha2 (10-13 Hz) and beta (13-30 Hz) power in the parieto-occipital region (p ≤ 0.01). On the individual level, changes of verbal fluency induced by stimulation of the STN were disparate and correlated inversely with delta power in the left temporal lobe (p < 0.05). Conclusion: STN stimulation does not alter verbal fluency performance in a systematic way at group level. However, when in individual patients an alteration of verbal fluency performance is produced by electrical stimulation of the STN, it correlates inversely with left temporal delta power.

Among Early Appearing Non-Motor Signs of Parkinson's Disease, Alteration of Olfaction but Not Electroencephalographic Spectrum Correlates with Motor Function.

Olfactory decline is a frequent and early non-motor symptom in Parkinson's disease (PD), which is increasingly used for diagnostic purposes. Another early appearing sign of PD consists in electroencephalographic (EEG) alterations. The combination of olfactory and EEG assessment may improve the identification of patients with early stages of PD. We hypothesized that olfactory capacity would be correlated with EEG alterations and motor and cognitive impairment in PD patients. To the best of our knowledge, the mutual influence of both markers of PD-olfactory decrease and EEG changes-was not studied before. We assessed the function of odor identification using olfactory "Screening 12 Test" ("Sniffin' Sticks®"), between two samples: patients with PD and healthy controls (HC). We analyzed correlations between the olfactory function and demographical parameters, Unified Parkinson's Disease Rating Scale (UPDRS-III), cognitive task performance, and spectral alpha/theta ratio (α/θ). In addition, we used receiver operating characteristic-curve analysis to check the classification capacity (PD vs HC) of olfactory function, α/θ, and a combined marker (olfaction and α/θ). Olfactory capacity was significantly decreased in PD patients, and correlated with age, disease duration, UPDRS-III, and with items of UPDRS-III related to gait and axial rigidity. In HC, olfaction correlated with age only. No correlation with α/θ was identified in both samples. Combined marker showed the largest area under the curve. In addition to EEG, the assessment of olfactory function may be a useful tool in the early characterization and follow-up of PD.

Apathy in Patients with Parkinson's Disease Correlates with Alteration of Left Fronto-Polar Electroencephalographic Connectivity.

Introduction: Quantitative electroencephalography (QEEG) brain frequency and network analyses are known to differentiate between disease stages in Parkinson's disease (PD) and are possible biomarkers. They correlate with cognitive decline. Little is known about changes in brain networks in relation to apathy. Objective/Aims: To analyze changes in brain network connectivities related to apathy. Methods: 40 PD patients (14 PD with mild cognitive deficits and 26 PD with normal cognition) were included. All patients had extensive neuropsychological testing; apathy was evaluated using the apathy evaluation score (AES, median 24.5, range 18-39). Resting state EEG was recorded with 256 electrodes and analyzed using fully automated Matlab® code (TAPEEG). For estimation of the connectivities between brain regions, PLI (phase lag index) was used, enhanced by a microstates segmentation. Results: After correction for multiple comparisons, significant correlations were found for single alpha2-band connectivities with the AES (p-values < 0.05). Lower connectivities, mainly involving the left fronto-polar region, were related to higher apathy scores. Conclusions: In our sample of patients with PD, apathy correlates with a network alteration mainly involving the left fronto-polar region. This might be due to dysfunction of the cortico-basal loop, modulating motivation.

Correlation of Visuospatial Ability and EEG Slowing in Patients with Parkinson's Disease.

Background. Visuospatial dysfunction is among the first cognitive symptoms in Parkinson's disease (PD) and is often predictive for PD-dementia. Furthermore, cognitive status in PD-patients correlates with quantitative EEG. This cross-sectional study aimed to investigate the correlation between EEG slowing and visuospatial ability in nondemented PD-patients. Methods. Fifty-seven nondemented PD-patients (17 females/40 males) were evaluated with a comprehensive neuropsychological test battery and a high-resolution 256-channel EEG was recorded. A median split was performed for each cognitive test dividing the patients sample into either a normal or lower performance group. The electrodes were split into five areas: frontal, central, temporal, parietal, and occipital. A linear mixed effects model (LME) was used for correlational analyses and to control for confounding factors. Results. Subsequently, for the lower performance, LME analysis showed a significant positive correlation between ROCF score and parietal alpha/theta ratio (b = .59, p = .012) and occipital alpha/theta ratio (b = 0.50, p = .030). No correlations were found in the group of patients with normal visuospatial abilities. Conclusion. We conclude that a reduction of the parietal alpha/theta ratio is related to visuospatial impairments in PD-patients. These findings indicate that visuospatial impairment in PD-patients could be influenced by parietal dysfunction.

Quantitative EEG (QEEG) Measures Differentiate Parkinson's Disease (PD) Patients from Healthy Controls (HC).

Objectives: To find out which Quantitative EEG (QEEG) parameters could best distinguish patients with Parkinson's disease (PD) with and without Mild Cognitive Impairment from healthy individuals and to find an optimal method for feature selection. Background: Certain QEEG parameters have been seen to be associated with dementia in Parkinson's and Alzheimer's disease. Studies have also shown some parameters to be dependent on the stage of the disease. We wanted to investigate the differences in high-resolution QEEG measures between groups of PD patients and healthy individuals, and come up with a small subset of features that could accurately distinguish between the two groups. Methods: High-resolution 256-channel EEG were recorded in 50 PD patients (age 68.8 ± 7.0 year; female/male 17/33) and 41 healthy controls (age 71.1 ± 7.7 year; female/male 20/22). Data was processed to calculate the relative power in alpha, theta, delta, beta frequency bands across the different regions of the brain. Median, peak frequencies were also obtained and alpha1/theta ratios were calculated. Machine learning methods were applied to the data and compared. Additionally, penalized Logistic regression using LASSO was applied to the data in R and a subset of best-performing features was obtained. Results: Random Forest and LASSO were found to be optimal methods for feature selection. A group of six measures selected by LASSO was seen to have the most effect in differentiating healthy individuals from PD patients. The most important variables were the theta power in temporal left region and the alpha1/theta ratio in the central left region. Conclusion: The penalized regression method applied was helpful in selecting a small group of features from a dataset that had high multicollinearity.

Increase of EEG Spectral Theta Power Indicates Higher Risk of the Development of Severe Cognitive Decline in Parkinson's Disease after 3 Years.

Objective: We investigated quantitative electroencephalography (qEEG) and clinical parameters as potential risk factors of severe cognitive decline in Parkinson's disease. Methods: We prospectively investigated 37 patients with Parkinson's disease at baseline and follow-up (after 3 years). Patients had no severe cognitive impairment at baseline. We used a summary score of cognitive tests as the outcome at follow-up. At baseline we assessed motor, cognitive, and psychiatric factors; qEEG variables [global relative median power (GRMP) spectra] were obtained by a fully automated processing of high-resolution EEG (256-channels). We used linear regression models with calculation of the explained variance to evaluate the relation of baseline parameters with cognitive deterioration. Results: The following baseline parameters significantly predicted severe cognitive decline: GRMP theta (4-8 Hz), cognitive task performance in executive functions and working memory. Conclusions: Combination of neurocognitive tests and qEEG improves identification of patients with higher risk of cognitive decline in PD.

Older Candidates for Subthalamic Deep Brain Stimulation in Parkinson's Disease Have a Higher Incidence of Psychiatric Serious Adverse Events.

OBJECTIVE: To investigate the incidence of serious adverse events (SAE) of subthalamic deep brain stimulation (STN-DBS) in elderly patients with Parkinson's disease (PD). METHODS: We investigated a group of 26 patients with PD who underwent STN-DBS at mean age 63.2 ± 3.3 years. The operated patients from the EARLYSTIM study (mean age 52.9 ± 6.6) were used as a comparison group. Incidences of SAE were compared between these groups. RESULTS: A higher incidence of psychosis and hallucinations was found in these elderly patients compared to the younger patients in the EARLYSTIM study (p < 0.01). CONCLUSIONS: The higher incidence of STN-DBS-related psychiatric complications underscores the need for comprehensive psychiatric pre- and postoperative assessment in older DBS candidates. However, these psychiatric SAE were transient, and the benefits of DBS clearly outweighed its adverse effects.

Reliability of Functional Connectivity of Electroencephalography Applying Microstate-Segmented Versus Classical Calculation of Phase Lag Index.

Connectivity analysis characterizes normal and altered brain function, for example, using the phase lag index (PLI), which is based on phase relations. However, reliability of PLI over time is limited, especially for single- or regional-link analysis. One possible cause is repeated changes of network configuration during registration. These network changes may be associated with changes of the surface potential fields, which can be characterized by microstate analysis. Microstate analysis describes repeating periods of quasistable surface potential fields lasting in the subsecond time range. This study aims to describe a novel combination of PLI with microstate analysis (microstate-segmented PLI = msPLI) and to determine its impact on the reliability of single links, regional links, and derived graph measures. msPLI was calculated in a cohort of 34 healthy controls three times over 2 years. A fully automated processing of electroencephalography was used. Resulting connectomes were compared using Pearson correlation, and test-retest reliability (TRT reliability) was assessed using the intraclass correlation coefficient. msPLI resulted in higher TRT reliability than classical PLI analysis for single or regional links, average clustering coefficient, average shortest path length, and degree diversity. Combination of microstates and phase-derived connectivity measures such as PLI improves reliability of single-link, regional-link, and graph analysis.

Quantitative EEG and Cognitive Decline in Parkinson's Disease.

Cognitive decline is common with the progression of Parkinson's disease (PD). Different candidate biomarkers are currently studied for the risk of dementia in PD. Several studies have shown that quantitative EEG (QEEG) is a promising predictor of PD-related cognitive decline. In this paper we briefly outline the basics of QEEG analysis and analyze the recent publications addressing the predictive value of QEEG in the context of cognitive decline in PD. The MEDLINE database was searched for relevant publications from January 01, 2005, to March 02, 2015. Twenty-four studies reported QEEG findings in various cognitive states in PD. Spectral and connectivity markers of QEEG could help to discriminate between PD patients with different level of cognitive decline. QEEG variables correlate with tools for cognitive assessment over time and are associated with significant hazard ratios to predict PD-related dementia. QEEG analysis shows high test-retest reliability and avoids learning effects associated with some neuropsychological testing; it is noninvasive and relatively easy to repeat.

The Verbal Fluency Decline After Deep Brain Stimulation in Parkinson's Disease: Is There an Influence of Age?

BACKGROUND: DBS is commonly used to treat Parkinson's disease (PD). DBS is not considered to cause major cognitive side effects, but some research groups have reported that it can cause decreased verbal fluency. The influence of age on DBS cognitive outcome is unclear. We investigated the possible influence of patients' age, level of education, disease duration, disease progression, depression, and levodopa equivalent dose (LED) on verbal fluency performance in patients with PD who underwent DBS of the subthalamic nucleus (STN-DBS). In this article, we investigated the influence of demographic and clinical parameters, especially age, on cognitive performance post-DBS in PD patients. METHODS: Forty-three patients with PD and without major psychiatric illness (according to Diagnostic and Statistical Manual of Mental Disroders, Fourth Edition) were enrolled in the study. Median age was 64.0 years (range, 46-77). In 21 patients, the indication for DBS was established on clinical grounds in keeping with international guidelines; these patients underwent STN-DBS, and the remaining 22 did not. Cognitive performance in both groups was assessed by standard neuropsychological test batteries at baseline and after median follow-up of 7 months. RESULTS: A statistically significant decline in the semantic category of verbal fluency task was found in the STN-DBS group (P < 0.01). Linear regression model revealed an influence of age (P < 0.01) and disease duration (P < 0.01) in relation to this decline. CONCLUSIONS: This study confirms previous findings that verbal fluency declines after STN-DBS in PD patients in comparison to PD patients without DBS. This decline is related to age and disease duration.

Cognitive Behavioral Group Therapy Reduces Stress and Improves the Quality of Life in Patients with Parkinson's Disease.

Objective: The aim of this study is to compare a cognitive behavioral group therapy (CBT) with a health enhancement program (HEP) for stress reduction and the impact on quality of life (QoL) in patients with Parkinson's disease (PD). Method: Thirty patients with PD participated in the study: 16 received CBT including stress-reducing elements and 14 took part in a HEP. The two groups did not differ significantly in their baseline demographic characteristics. The patients in both groups underwent weekly sessions of 2 h duration for 9 weeks. The Parkinson's Disease Questionnaire with 39 items (PDQ-39), the Burden Questionnaire for Parkinson's Disease (translated from the original German: Belastungsfragebogen für Parkinsonpatienten (BELA) and the Disease-Related Questionnaire [Fragebogen zur krankheitsbezogenen Kommunikation (FKK)] were used for assessment. Ratings were completed at baseline and after 9 weeks (immediately after the last treatment session). Results: The patients in the CBT group achieved significantly better BELA, FKK and PDQ-39 scores (p < 0.05). Subscale analysis revealed that the scores on the BELA subscales "emotional well-being" and "somatic motor function" contributed significantly to stress reduction (p < 0.05). The FKK revealed significant improvement in social skills in the CBT group (p < 0.05). Conclusion: Cognitive Behavioral Group Therapy appears to be an effective way for patients with PD to lessen stress and improve their quality of life.

Fullerenols and glucosamine fullerenes reduce infarct volume and cerebral inflammation after ischemic stroke in normotensive and hypertensive rats.

Cerebral inflammation plays a crucial role in the pathophysiology of ischemic stroke and is involved in all stages of the ischemic cascade. Fullerene derivatives, such as fullerenol (OH-F) are radical scavengers acting as neuroprotective agents while glucosamine (GlcN) attenuates cerebral inflammation after stroke. We created novel glucosamine-fullerene conjugates (GlcN-F) to combine their protective effects and compared them to OH-F regarding stroke-induced cerebral inflammation and cellular damage. Fullerene derivatives or vehicle was administered intravenously in normotensive Wistar-Kyoto (WKY) rats and spontaneously hypertensive rats (SHR) immediately after transient middle cerebral artery occlusion (tMCAO). Infarct size was determined at day 5 and neurological outcome at days 1 and 5 after tMCAO. CD68- and NeuN-staining were performed to determine immunoreactivity and neuronal survival respectively. Cytokine and toll like receptor 4 (TLR-4) expression was assessed using quantitative real-time PCR. Magnetic resonance imaging revealed a significant reduction of infarct volume in both, WKY and SHR that were treated with fullerene derivatives. Treated rats showed an amelioration of neurological symptoms as both OH-F and GlcN-F prevented neuronal loss in the perilesional area. Cerebral immunoreactivity was reduced in treated WKY and SHR. Expression of IL-1ß and TLR-4 was attenuated in OH-F-treated WKY rats. In conclusion, OH-F and GlcN-F lead to a reduction of cellular damage and inflammation after stroke, rendering these compounds attractive therapeutics for stroke.

Correlation of EEG slowing with cognitive domains in nondemented patients with Parkinson's disease.

BACKGROUND: Cognitive deficits in Parkinson's disease (PD) are heterogeneous and can be classified into cognitive domains. Quantitative EEG is related to and predictive of cognitive status in PD. In this cross-sectional study, the relationship of cognitive domains and EEG slowing in PD patients without dementia is investigated. METHODS: A total of 48 patients with idiopathic PD were neuropsychologically tested. Cognitive domain scores were calculated combining Z-scores of test variables. Slowing of EEG was measured with median EEG frequency. Linear regression was used for correlational analyses and to control for confounding factors. RESULTS: EEG median frequency was significantly correlated to cognitive performance in most domains (episodic long-term memory, rho = 0.54; overall cognitive score, rho = 0.47; fluency, rho = 0.39; attention, rho = 0.37; executive function, rho = 0.34), but not to visuospatial functions and working memory. CONCLUSION: Global EEG slowing is a marker for overall cognitive impairment in PD and correlates with impairment in the domains attention, executive function, verbal fluency, and episodic long-term memory, but not with working memory and visuospatial functions. These disparate effects warrant further investigations.

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

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.

Slowing of EEG background activity in Parkinson's and Alzheimer's disease with early cognitive dysfunction.

BACKGROUND: Slowing of the electroencephalogram (EEG) is frequent in Parkinson's (PD) and Alzheimer's disease (AD) and correlates with cognitive decline. As overlap pathology plays a role in the pathogenesis of dementia, it is likely that demented patients in PD show similar physiological alterations as in AD. OBJECTIVE: To analyze distinctive quantitative EEG characteristics in early cognitive dysfunction in PD and AD. METHODS: Forty patients (20 PD- and 20 AD patients with early cognitive impairment) and 20 normal controls (NC) were matched for gender, age, and education. Resting state EEG was recorded from 256 electrodes. Relative power spectra, median frequency (4-14 Hz), and neuropsychological outcome were compared between groups. RESULTS: Relative theta power in left temporal region and median frequency separated the three groups significantly (p = 0.002 and p < 0.001). Relative theta power was increased and median frequency reduced in patients with both diseases compared to NC. Median frequency was higher in AD than in PD and classified groups significantly (p = 0.02). CONCLUSION: Increase of theta power in the left temporal region and a reduction of median frequency were associated with presence of AD or PD. PD patients are characterized by a pronounced slowing as compared to AD patients. Therefore, in both disorders EEG slowing might be a useful biomarker for beginning cognitive decline.

Power spectra for screening parkinsonian patients for mild cognitive impairment.

OBJECTIVE: Mild cognitive impairment in Parkinson's disease (PD-MCI) is diagnosed based on the results of a standardized set of cognitive tests. We investigate whether quantitative EEG (qEEG) measures could identify differences between cognitively normal PD (PD-CogNL) and PD-MCI patients. METHODS: High-resolution EEG was recorded in 53 patients with Parkinson's disease (PD). Relative power in five frequency bands was calculated globally and for ten regions. Peak and median frequencies were determined. qEEG results were compared between groups. Effect sizes of all variables were calculated. The best separating variable was used to demonstrate subject-wise classification. RESULTS: Lower mean values were observed in global alpha1 power and alpha1 power in five brain regions (left hemisphere: frontal, central, temporal, occipital; right hemisphere: temporal, P < 0.05), differentiating between PD-CogNL and PD-MCI groups. Effect sizes were high, ranging from 0.79 to 0.87. Median frequency was 8.56 ± 0.74 Hz and was not different between the groups. The variable with the best subject-wise classification was the power in the alpha1 band in the right temporal region. The area under the corresponding receiver operating characteristic (ROC) curve was 0.72. The optimal classification threshold yielded a sensitivity of 65.9% and a specificity of 66.7%. The positive and negative predictive values were 87.1% and 36.4%, respectively. INTERPRETATION: Reduction in alpha1 band power in nondemented PD patients, particularly in the right temporal region, is highly indicative of MCI in PD patients. The results might be used to assist in time-efficient diagnosis of PD-MCI and avoid the drawbacks of test-retest effect in repeated neuropsychological testing.