Cortical phosphorylated α-Synuclein levels correlate with brain wave spectra in Parkinson's disease

Resting-state EEG predicts cognitive decline in a neuropathologically diagnosed longitudinal community autopsied cohort

OBJECTIVE

To assess correlative strengths of quantitative electroencephalography (qEEG) and visual rating scale EEG features on cognitive outcomes in only autopsied cases from the Arizona Study of Neurodegenerative Disorders (AZSAND). We hypothesized that autopsy proven Parkinson Disease will show distinct EEG features from Alzheimer's Disease prior to dementia (mild cognitive impairment).

BACKGROUND

Cognitive decline is debilitating across neurodegenerative diseases. Resting-state EEG analysis, including spectral power across frequency bins (qEEG), has shown significant associations with neurodegenerative disease classification and cognitive status, with autopsy confirmed diagnosis relatively lacking.

METHODS

Biannual EEG was analyzed from autopsied cases in AZSAND who had at least one rsEEG (>1 min eyes closed±eyes open). Analysis included global relative spectral power and a previously described visual rating scale (VRS). Linear mixed regression was performed for neuropsychological assessment and testing within 2 years of death (n = 236, 594 EEG exams) in a mixed linear regression model.

RESULTS

The cohort included cases with final clinicopathologic diagnoses of Parkinson's disease (n = 73), Alzheimer disease (n = 65), and tauopathy not otherwise specified (n = 56). A VRS score of 3 diffuse or frequent generalized slowing) over the study duration was associated with an increase in consensus diagnosis cognitive worsening at 4.9 (3.1) years (HR 2.02, CI 1.05-3.87). Increases in global theta power% and VRS were the most consistently associated with large regression coefficients inversely with cognitive performance measures.

CONCLUSION

Resting-state EEG analysis was meaningfully related to cognitive performance measures in a community-based autopsy cohort. EEG deserves further study and use as a cognitive biomarker.

Network disruption based on multi-modal EEG-MRI in α-synucleinopathies

Background

Brain network dysfunction has been characterized by resting-state electroencephalography (EEG) and magnetic resonance imaging (MRI) in the prodromal stage. This study aimed to identify multi-modal electrophysiological and neuroimaging biomarkers for differential diagnosis in synucleinopathies and phenoconversion in isolated rapid eye movement sleep behavior disorder (iRBD).

Methods

We enrolled 35 patients with multiple system atrophy (MSA), 32 with Parkinson's disease (PD), 30 with iRBD and 30 matched healthy controls (HC). Power spectral density (PSD) was calculated in different frequency bands. EEG functional connectivity (FC) was calculated using the weighted Phase Lag Index (wPLI) after source localization. Significant network disruptions were further confirmed by MRI FC analysis.

Results

Quantitative EEG analysis demonstrated that delta and theta power spectral density significantly differed among MSA, PD and HC. The increased PSD was correlated with cognitive decline and olfactory dysfunction in PD. Band-specific FC profiles were observed in theta, alpha, and gamma bands. The hypoconnected alpha network significantly correlated with motor dysfunction, while the gamma FC distinguished PD from MSA. By integrating EEG and MRI network analyses, we found that FC between the olfactory cortex and dorsolateral prefrontal cortex was significantly different between MSA and PD. A multimodal discriminative model for MSA and PD, integrating spectral and FC attributes of EEG and MRI, yielded an area under the receiver operating characteristic curve of 0.900. Simultaneously, we found the FC abnormalities were more prominent than spectral features in iRBD indicating prodromal dysfunction. The decreased FC between the angular gyrus and striatum was identified in α-synucleinopathies. This hypoconnectivity was associated with dopaminergic degeneration in iRBD examined by dopamine transporter imaging.

Discussion

Our study demonstrated EEG spectral and functional profiles in prodromal and clinical-defined synucleinopathies. Multimodal EEG and MRI provided a novel approach to discriminate MSA and PD, and monitor neurodegenerative progression in the preclinical phase.

Functional aspects of the brain lymphatic drainage system in aging and neurodegenerative diseases

The phenomenon of an aging population is advancing at a precipitous rate. Alzheimer's disease (AD) and Parkinson's disease (PD) are two of the most common age-associated neurodegenerative diseases, both of which are primarily characterized by the accumulation of toxic proteins and the progressive demise of neuronal structures. Recent discoveries about the brain lymphatic drainage system have precipitated a growing body of investigations substantiating its novel roles, including the clearance of macromolecular waste and the trafficking of immune cells. Notably, aquaporin 4-mediated glymphatic transport, crucial for maintaining neural homeostasis, becomes disrupted during the aging process and is further compromised in the pathogenesis of AD and PD. Functional meningeal lymphatic vessels, which facilitate the drainage of cerebrospinal fluid into the deep cervical lymph nodes, are integral in bridging the central nervous system with peripheral immune responses. Dysfunction in these meningeal lymphatic vessels exacerbates pathological trajectory of the age-related neurodegenerative disease. This review explores modulatory influence of the glymphatic system and meningeal lymphatic vessels on the aging brain and its associated neurodegenerative disorders. It also encapsulates the insights of potential mechanisms and prospects of the targeted non-pharmacological interventions.

QEEG Signatures are Associated with Nonmotor Dysfunctions in Parkinson's Disease and Atypical Parkinsonism: An Integrative Analysis

Parkinson's disease (PD) and atypical parkinsonism (AP), including progressive supranuclear palsy (PSP) and multiple system atrophy (MSA), share similar nonmotor symptoms. Quantitative electroencephalography (QEEG) can be used to examine the nonmotor symptoms. This study aimed to characterize the patterns of QEEG and functional connectivity (FC) that differentiate PD from PSP or MSA, and explore the correlation between the differential QEEG indices and nonmotor dysfunctions in PD and AP. We enrolled 52 patients with PD, 31 with MSA, 22 with PSP, and 50 age-matched health controls to compare QEEG indices among specific brain regions. One-way analysis of variance was applied to assess QEEG indices between groups; Spearman's correlations were used to examine the relationship between QEEG indices and nonmotor symptoms scale (NMSS) and mini-mental state examination (MMSE). FCs using weighted phase lag index were compared between patients with PD and those with MSA/PSP. Patients with PSP revealed higher scores on the NMSS and lower MMSE scores than those with PD and MSA, with similar disease duration. The delta and theta powers revealed a significant increase in PSP, followed by PD and MSA. Patients with PD presented a significantly lower slow-to-fast ratio than those with PSP in the frontal region, while patients with PD presented significantly higher EEG-slowing indices than patients with MSA. The frontal slow-to-fast ratio showed a negative correlation with MMSE scores in patients with PD and PSP, and a positive correlation with NMSS in the perception and mood domain in patients with PSP but not in those with PD. Compared to PD, MSA presented enhanced FC in theta and delta bands in the posterior region, while PSP revealed decreased FC in the delta band within the frontal-temporal cortex. These findings suggest that QEEG might be a useful tool for evaluating the nonmotor dysfunctions in PD and AP. Our QEEG results suggested that with similar disease duration, the cortical neurodegenerative process was likely exacerbated in patients with PSP, followed by those with PD, and lastly in patients with MSA.

Loss of the Synuclein Family Members Differentially Affects Baseline- and Apomorphine-Associated EEG Determinants in Single-, Double- and Triple-Knockout Mice

Synucleins comprise a family of small proteins highly expressed in the nervous system of vertebrates and involved in various intraneuronal processes. The malfunction of alpha-synuclein is one of the key events in pathogenesis of Parkinson disease and certain other neurodegenerative diseases, and there is a growing body of evidence that malfunction of other two synucleins might be involved in pathological processes in the nervous system. The modulation of various presynaptic mechanisms of neurotransmission is an important function of synucleins, and therefore, it is feasible that their deficiency might affect global electrical activity detected of the brain. However, the effects of the loss of synucleins on the frequency spectra of electroencephalograms (EEGs) have not been systematically studied so far. In the current study, we assessed changes in such spectra in single-, double- and triple-knockout mice lacking alpha-, beta- and gamma-synucleins in all possible combinations. EEGs were recorded from the motor cortex, the putamen, the ventral tegmental area and the substantia nigra of 78 3-month-old male mice from seven knockout groups maintained on the C57BL/6J genetic background, and 10 wild-type C57BL/6J mice for 30 min before and for 60 min after the systemic injection of a DA receptor agonist, apomorphine (APO). We found that almost any variant of synuclein deficiency causes multiple changes in both basal and APO-induced EEG oscillation profiles. Therefore, it is not the absence of any particular synuclein but rather a disbalance of synucleins that causes widespread changes in EEG spectral profiles.

QEEG indices are associated with inflammatory and metabolic risk factors in Parkinson's disease dementia: An observational study

BACKGROUND

Quantitative electroencephalography (QEEG) is a reliable and non-invasive diagnostic tool to quantify cortical synaptic injury or loss in the clinical assessment of neurodegenerative diseases, and may be able to differentiate various types of dementia. We investigated if QEEG indices can differentiate Parkinson's Disease (PD) with nondementia (PD-ND) from PD with dementia (PDD), and to determine if QEEG indices correlate with inflammation and lipid metabolism markers in PD.

METHODS

This clinical study collected data between July 1, 2018 and July 1, 2021 in Zhujiang Hospital of Southern Medical University in China and data was analysed. A total of 125 individuals comprising of 31 PDD, 47 patients with PD-ND and 47 healthy controls were included. We calculated the absolute spectral power (ASP) of frequency bands and the slow-to-fast frequency ratios of specific brain regions. Plasma levels of hypersensitive C-reactive protein (Hs-CRP), superoxide dismutase (SOD), and high-density lipoprotein cholesterol (HDL-C) were measured and correlations with QEEG indices were examined.

FINDINGS

A significantly higher ASP of delta frequency especially in the frontal region was observed in patients with PDD compared to PD-ND (P=0.004) and controls (P=0.000). Decreased HDL-C (OR=0.186, P=0.030), and increased Hs-CRP (OR =2.856, P=0.015) were associated with PDD. Frontal-delta ASP was negatively correlated with plasma HDL-C (r=-0.353, P=0.000) and SOD (r=-0.322, P=0.001), and positively correlated with Hs-CRP (r=0.342, P=0.000).

INTERPRETATION

We highlight novel correlations between QEEG indices and inflammation and lipid metabolism markers in PD-ND and PDD. QEEG indices, HDL-C and Hs-CRP are potentially useful for the evaluation of PDD. Our current findings suggest that peripheral inflammation might contribute to the pathogenesis of cognitive impairment and EEG slowing in PDD. The mechanism underlying frontal-delta ASP and its correlation with neuro-inflammatory and metabolic markers in PDD should be further investigated.

FUNDING

The National Natural Science Foundation of China (NO: 81873777, 82071414); the Scientific Research Foundation of Guangzhou (NO: 202206010005); the Science and Technology Program of Guangdong of China (NO: 2020A0505100037); the High-level Hospital Construction Research Project of Maoming People's Hospital (NO: xz2020009); the Science and Technology Program of Maoming City (NO: 2021S0026). Dr EK Tan is supported by the National Medical Research Council, Singapore.

Association of Plasma and Electroencephalography Markers With Motor Subtypes of Parkinson’s Disease

Objective

The aim of this study was to investigate the correlations of plasma neurodegenerative proteins and electroencephalography (EEG) dynamic functional network (DFN) parameters with disease progression in early Parkinson’s disease (PD) with different motor subtypes, including tremor-dominant (TD) and postural instability and gait disorder (PIGD).

Methods

In our study, 33 patients with PD (21 TD and 12 PIGD) and 33 healthy controls (HCs) were enrolled. Plasma neurofilament light chain (NfL), α-synuclein (α-syn), total-tau (t-tau), β-amyloid 42 (Aβ42), and β-amyloid 40 (Aβ40) levels were measured using an ultrasensitive single-molecule array (Simoa) immunoassay. All the patients with PD underwent EEG quantified by DFN analysis. The motor and non-motor performances were evaluated by a series of clinical assessments. Subsequently, a correlation analysis of plasma biomarkers and EEG measures with clinical scales was conducted.

Results

In the TD group, plasma NfL exhibited a significant association with MDS-UPDRS III and Montreal Cognitive Assessment (MoCA). A higher Aβ42/40 level was significantly related to a decrease in Hamilton Depression Rating Scale (HAMD) and Hamilton Anxiety Rating Scale (HAMA) in the PIGD group. In terms of the correlation between EEG characteristic parameters and clinical outcomes, trapping time (TT) delta was positively correlated with MDS-UPDRS III and MoCA scores in the TD group, especially in the prefrontal and frontal regions. For other non-motor symptoms, there were significant direct associations of k_PLI theta with HAMD and HAMA, especially in the prefrontal region, and k_PLI gamma was particularly correlated with Rapid Eye Movement Sleep Behavior Disorder Screening Questionnaire (RBDSQ) scores in the prefrontal, frontal, and parietal regions in the TD group. Furthermore, there was a significant positive correlation between plasma t-tau and k_PLI, and pairwise correlations were found among plasma NfL, theta TT, and MoCA scores in the TD group.

Conclusion

These results provide evidence that plasma neurodegenerative proteins and EEG measures have great potential in predicting the disease progression of PD subtypes, especially for the TD subtype. A combination of these two kinds of markers may have a superposition effect on monitoring and estimating the prognosis of PD subtypes and deserves further research in larger, follow-up PD cohorts.

α-Synuclein Impacts on Intrinsic Neuronal Network Activity Through Reduced Levels of Cyclic AMP and Diminished Numbers of Active Presynaptic Terminals

α-synuclein (α-Syn) is intimately linked to synucleinopathies like Parkinson’s disease and dementia with Lewy bodies. However, the pathophysiological mechanisms that are triggered by this protein are still largely enigmatic. α-Syn overabundance may cause neurodegeneration through protein accumulation and mitochondrial deterioration but may also result in pathomechanisms independent from neuronal cell death. One such proposed pathological mechanism is the influence of α-Syn on non-stimulated, intrinsic brain activity. This activity is responsible for more than 90% of the brain’s energyconsumption, and is thus thought to play an eminent role in basic brain functionality. Here we report that α-Syn substantially disrupts intrinsic neuronal network burst activity in a long-term neuronal cell culture model. Mechanistically, the impairment of network activity originates from reduced levels of cyclic AMP and cyclic AMP-mediated signaling as well as from diminished numbers of active presynaptic terminals. The profound reduction of network activity due to α-Syn was mediated only by intracellularly expressed α-Syn, but not by α-Syn that is naturally released by neurons. Conversely, extracellular pre-formed fibrils of α-Syn mimicked the effect of intracellular α-Syn, suggesting that they trigger an off-target mechanism that is not activated by naturally released α-Syn. A simulation-based model of the network activity in our cultures demonstrated that even subtle effect sizes in reducing outbound connectivity, i.e., loss of active synapses, can cause substantial global reductions in non-stimulated network activity. These results suggest that even low-level loss of synaptic output capabilities caused by α-Syn may result in significant functional impairments in terms of intrinsic neuronal network activity. Provided that our model holds true for the human brain, then α-Syn may cause significant functional lesions independent from neurodegeneration.

Cortical circuit dysfunction in a mouse model of alpha-synucleinopathy in vivo

Considerable fluctuations in cognitive performance and eventual dementia are an important characteristic of alpha-synucleinopathies, such as Parkinson's disease and Lewy Body dementia and are linked to cortical dysfunction. The presence of misfolded and aggregated alpha-synuclein in the cerebral cortex of patients has been suggested to play a crucial role in this process. However, the consequences of a-synuclein accumulation on the function of cortical networks at cellular resolution in vivo are largely unknown. Here, we induced robust a-synuclein pathology in the cerebral cortex using the striatal seeding model in wild-type mice. Nine months after a single intrastriatal injection of a-synuclein preformed fibrils, we observed profound alterations of the function of layer 2/3 cortical neurons in somatosensory cortex by in vivo two-photon calcium imaging in awake mice. We detected increased spontaneous activity levels, an enhanced response to whisking and increased synchrony. Stereological analyses revealed a reduction in glutamic acid decarboxylase 67-positive inhibitory neurons in the somatosensory cortex of mice injected with preformed fibrils. Importantly, these findings point to a disturbed excitation/inhibition balance as a relevant driver of circuit dysfunction, potentially underlying cognitive changes in alpha-synucleinopathies.

Identifying Mild Cognitive Impairment in Parkinson's Disease With Electroencephalogram Functional Connectivity

Objective

Cognitive impairment occurs frequently in Parkinson’s disease (PD) and negatively impacts the patient’s quality of life. However, its pathophysiological mechanism remains unclear, hindering the development of new therapies. Changes in brain connectivity are related to cognitive impairment in patients with PD, with the dorsolateral prefrontal cortex (DLPFC) being considered the essential region related to PD cognitive impairment. Nevertheless, few studies have focused on the global connectivity responsible for communication with the DLPFC node, the posterior division of the middle frontal gyrus (PMFG) in patients with PD; this was the focus of this study.

Methods

We applied resting-state electroencephalography (EEG) and calculated a reliable functional connectivity measurement, the debiased weighted phase lag index (dWPLI), to examine inter-regional functional connectivity in 68 patients with PD who were classified into two groups according to their cognitive condition.

Results

We observed that altered left and right PMFG-based functional connectivity associated with cognitive impairment in patients with PD in the theta frequency bands under the eyes closed condition (r = −0.426, p < 0.001 and r = −0.437, p < 0.001, respectively). Exploratory results based on the MoCA subdomains indicated that poorer visuospatial function was associated with higher right PMFG-based functional connectivity (r = −0.335, p = 0.005), and poorer attention function was associated with higher left and right PMFG-based functional connectivity (r = −0.380, p = 0.001 and r = −0.256, p = 0.035, respectively). Further analysis using logistic regression and receiver operating characteristic (ROC) curves found that this abnormal functional connectivity was an independent risk factor for cognitive impairment [odds ratio (OR): 2.949, 95% confidence interval (CI): 1.294–6.725, p = 0.01 for left PMFG; OR: 11.278, 95% CI: 2.578–49.335, p = 0.001 for right PMFG, per 0.1 U], and provided moderate classification power to discriminate between cognitive abilities in patients with PD [area under the ROC curve (AUC) = 0.770 for left PMFG; AUC = 0.809 for right PMFG].

Conclusion

These preliminary findings indicate that abnormal PMFG-based functional connectivity patterns associated with cognitive impairment in the theta frequency bands under the eyes closed condition and altered functional connectivity patterns have the potential to act as reliable biomarkers for identifying cognitive impairment in patients with PD.

Dementia with Lewy bodies-associated ß-synuclein mutations V70M and P123H cause mutation-specific neuropathological lesions

Beta (ß)-synuclein (ß-Syn) has long been considered to be an attenuator for the neuropathological effects caused by the Parkinson's disease-related alpha (α)-synuclein (α-Syn) protein. However, recent studies demonstrated that overabundant ß-Syn can form aggregates and induce neurodegeneration in central nervous system (CNS) neurons in vitro and in vivo, albeit at a slower pace as compared with α-Syn. Here, we demonstrate that ß-Syn mutants V70M, detected in a sporadic case of dementia with Lewy bodies (DLB), and P123H, detected in a familial case of DLB, robustly aggravate the neurotoxic potential of ß-Syn. Intriguingly, the two mutations trigger mutually exclusive pathways. ß-Syn V70M enhances morphological mitochondrial deterioration and degeneration of dopaminergic and non-dopaminergic neurons, but it has no influence on neuronal network activity. Conversely, ß-Syn P123H silences neuronal network activity, but it does not aggravate neurodegeneration. ß-Syn wild type (WT), V70M and P123H formed proteinase K-resistant intracellular fibrils within neurons, albeit with less stable C-termini as compared with α-Syn. Under cell-free conditions, ß-Syn V70M demonstrated a much slower pace of fibril formation as compared with WT ß-Syn, and P123H fibrils present with a unique phenotype characterized by large numbers of short, truncated fibrils. Thus, it is possible that V70M and P123H cause structural alterations in ß-Syn, which are linked to their distinct neuropathological profiles. The extent of the lesions caused by these neuropathological profiles is almost identical to that of overabundant α-Syn and is thus likely to be directly involved into the etiology of DLB. Overall, this study provides insights into distinct disease mechanisms caused by mutations of ß-Syn.

Identifying Parkinson's disease with mild cognitive impairment by using combined MR imaging and electroencephalogram

OBJECTIVES

To analyse the changes of quantitative electroencephalogram (qEEG) and cortex structural magnetic resonance (MR) imaging in Parkinson's disease with mild cognitive impairment (PD-MCI) and to explore the "composite marker"-based machine learning model in identifying PD-MCI.

METHODS

Retrospective analysis of patients with PD identified 36 PD-MCI and 35 PD with normal cognition (PD-NC). QEEG features of power spectrum and structural MR features of cortex based on surface-based morphometry (SBM) were extracted. Support vector machine (SVM) was established using combined features of structural MR and qEEG to identify PD-MCI. Feature importance evaluation algorithm of mean impact value (MIV) was established to sort the vital characteristics of qEEG and structural MR.

RESULTS

Compared with PD-NC, PD-MCI showed a statistically significant difference in 5 leads and waves of qEEG and 7 cortical region features of structural MR. The SVM model based on these qEEG and structural MR features yielded an accuracy of 0.80 in the training set and had a high prediction accuracy of 0.80 in the test set (sensitivity was 0.78, specificity was 0.83, area under the receiver operating characteristic curve was 0.77), which was higher than the model built by the feature separately. QEEG features of theta wave in C3 had a marked impact on the model for classification according to the MIV algorithm.

CONCLUSIONS

PD-MCI is characterized by widespread structural and EEG abnormality. "Composite markers" could be valuable for the individualized diagnosis of PD-MCI by machine learning.

KEY POINTS

• Explore the brain abnormalities in Parkinson's disease with mild cognitive impairment by using the quantitative electroencephalogram and cortex structural MR simultaneously. • Multimodal features based support vector machine for identifying Parkinson's disease with mild cognitive impairment has an acceptable performance. • Theta wave in C3 is the most influential feature of qEEG and cortex structure MR imaging in identifying Parkinson's disease with mild cognitive impairment using support vector machine.

Abnormalities of resting-state EEG in patients with prodromal and overt dementia with Lewy bodies: Relation to clinical symptoms

OBJECTIVE

Here we tested if cortical sources of resting state electroencephalographic (rsEEG) rhythms may differ in sub-groups of patients with prodromal and overt dementia with Lewy bodies (DLB) as a function of relevant clinical symptoms.

METHODS

We extracted clinical, demographic and rsEEG datasets in matched DLB patients (N = 60) and control Alzheimer's disease (AD, N = 60) and healthy elderly (Nold, N = 60) seniors from our international database. The eLORETA freeware was used to estimate cortical rsEEG sources.

RESULTS

As compared to the Nold group, the DLB and AD groups generally exhibited greater spatially distributed delta source activities (DLB > AD) and lower alpha source activities posteriorly (AD > DLB). As compared to the DLB "controls", the DLB patients with (1) rapid eye movement (REM) sleep behavior disorders showed lower central alpha source activities (p < 0.005); (2) greater cognitive deficits exhibited higher parietal and central theta source activities as well as higher central, parietal, and occipital alpha source activities (p < 0.01); (3) visual hallucinations pointed to greater parietal delta source activities (p < 0.005).

CONCLUSIONS

Relevant clinical features were associated with abnormalities in spatial and frequency features of rsEEG source activities in DLB patients.

SIGNIFICANCE

Those features may be used as neurophysiological surrogate endpoints of clinical symptoms in DLB patients in future cross-validation prospective studies.

Neurophysiological Biomarkers of Parkinson's Disease

BACKGROUND

There is a need for reliable and robust Parkinson's disease biomarkers that reflect severity and are sensitive to disease modifying investigational therapeutics.

OBJECTIVE

To demonstrate the utility of EEG as a reliable, quantitative biomarker with potential as a pharmacodynamic endpoint for use in clinical assessments of neuroprotective therapeutics for Parkison's disease.

METHODS

A multi modal study was performed including aquisition of resting state EEG data and dopamine transporter PET imaging from Parkinson's disease patients off medication and compared against age-matched controls.

RESULTS

Qualitative and test/retest analysis of the EEG data demonstrated the reliability of the methods. Source localization using low resolution brain electromagnetic tomography identified significant differences in Parkinson's patients versus control subjects in the anterior cingulate and temporal lobe, areas with established association to Parkinson's disease pathology. Changes in cortico-cortical and cortico-thalamic coupling were observed as excessive EEG beta coherence in Parkinson's disease patients, and correlated with UPDRS scores and dopamine transporter activity, supporting the potential for cortical EEG coherence to serve as a reliable measure of disease severity. Using machine learning approaches, an EEG discriminant function analysis classifier was identified that parallels the loss of dopamine synapses as measured by dopamine transporter PET.

CONCLUSION

Our results support the utility of EEG in characterizing alterations in neurophysiological oscillatory activity associated with Parkinson's disease and highlight potential as a reliable method for monitoring disease progression and as a pharmacodynamic endpoint for Parkinson's disease modification therapy.

Automatic anesthesia depth staging using entropy measures and relative power of electroencephalogram frequency bands

Many of the surgeries performed under general anesthesia are aided by electroencephalogram (EEG) monitoring. With increased focus on detecting the anesthesia states of patients in the course of surgery, more attention has been paid to analyzing the power spectra and entropy measures of EEG signal during anesthesia. In this paper, by using the relative power of EEG frequency bands and the EEG entropy measures, a new method for detecting the depth of anesthesia states has been presented based on the least squares support vector machine (LS-SVM) classifiers. EEG signals were recorded from 20 patients before, during and after general anesthesia in the operating room at a sampling rate of 200 Hz. Then, 12 features were extracted from each EEG segment, 10 s in length, which are used for anesthesia state monitoring. No significant difference was observed (p > 0.05) between these features and the bispectral index (BIS), which is the commonly used measure of anesthetic effect. The used LS-SVM classifier based method is able to identify the anesthesia states with an accuracy of 80% with reference to the BIS index. Since the underlying equation of the utilized LS-SVM is linear, the computational time of the algorithm is not significant and therefore it can be used for online application in operation rooms.

Association Between Pathology and Electroencephalographic Activity in Parkinson's Disease

INTRODUCTION

The key mechanisms that connect Parkinson's disease pathology with dementia are unclear. We tested the hypothesis that the quantitative spectral electroencephalographic measure, delta bandpower, correlates with Lewy type synucleinopathy on pathological examination in Parkinson's disease. As a corollary hypothesis, we analyzed whether there would be delta bandpower electroencephalographic differences between Parkinson's disease dementia cases with and without pathological criteria for Alzheimer's disease.

METHODS

We used pathological examination results from 44 Parkinson's disease subjects from our brain bank with various degrees of cognitive decline, who had undergone electroencephalography. Pathological grading for Lewy type synucleinopathy, plaques, tangles, and indications of vascular pathology in subcortical and cortical areas were correlated with the most associated electroencephalographic biomarker with Parkinson's disease dementia in our laboratory, delta bandpower. Group differences for all spectral electroencephalographic measures were also analyzed between cases with and without pathological criteria for Alzheimer's disease.

RESULTS

Findings revealed significant correlations between delta bandpower with Lewy type synucleinopathy, whereas indications of Alzheimer's disease or vascular pathology had nonsignificant correlation. The strongest association was with delta bandpower and Lewy type synucleinopathy in the anterior cingulate region. Mean delta bandpower was higher in the group for Parkinson's disease dementia with Alzheimer's disease pathology criteria than without.

CONCLUSIONS

Lewy type synucleinopathy severity appears to be more associated with increased delta bandpower than with Alzheimer's disease pathology or indications of vascular pathology over all cases. However, the presence of Alzheimer's pathology may associate with more cortex physiological disruption in a subset of cases.

Abnormalities of Cortical Neural Synchronization Mechanisms in Subjects with Mild Cognitive Impairment due to Alzheimer's and Parkinson's Diseases: An EEG Study

The aim of this retrospective and exploratory study was that the cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms might reveal different abnormalities in cortical neural synchronization in groups of patients with mild cognitive impairment due to Alzheimer's disease (ADMCI) and Parkinson's disease (PDMCI) as compared to healthy subjects. Clinical and rsEEG data of 75 ADMCI, 75 PDMCI, and 75 cognitively normal elderly (Nold) subjects were available in an international archive. Age, gender, and education were carefully matched in the three groups. The Mini-Mental State Evaluation (MMSE) was matched between the ADMCI and PDMCI groups. Individual alpha frequency peak (IAF) was used to determine the delta, theta, alpha1, alpha2, and alpha3 frequency band ranges. Fixed beta1, beta2, and gamma bands were also considered. eLORETA estimated the rsEEG cortical sources. Receiver operating characteristic curve (ROC) classified these sources across individuals. Results showed that compared to the Nold group, the posterior alpha2 and alpha3 source activities were more abnormal in the ADMCI than the PDMCI group, while the parietal delta source activities were more abnormal in the PDMCI than the ADMCI group. The parietal delta and alpha sources correlated with MMSE score and correctly classified the Nold and diseased individuals (area under the ROC = 0.77-0.79). In conclusion, the PDMCI and ADMCI patients showed different features of cortical neural synchronization at delta and alpha frequencies underpinning brain arousal and vigilance in the quiet wakefulness. Future prospective cross-validation studies will have to test these rsEEG markers for clinical applications and drug discovery.

Abnormalities of resting-state functional cortical connectivity in patients with dementia due to Alzheimer's and Lewy body diseases: an EEG study

Previous evidence showed abnormal posterior sources of resting-state delta (<4 Hz) and alpha (8-12 Hz) rhythms in patients with Alzheimer's disease with dementia (ADD), Parkinson's disease with dementia (PDD), and Lewy body dementia (DLB), as cortical neural synchronization markers in quiet wakefulness. Here, we tested the hypothesis of additional abnormalities in functional cortical connectivity computed in those sources, in ADD, considered as a "disconnection cortical syndrome", in comparison with PDD and DLB. Resting-state eyes-closed electroencephalographic (rsEEG) rhythms had been collected in 42 ADD, 42 PDD, 34 DLB, and 40 normal healthy older (Nold) participants. Exact low-resolution brain electromagnetic tomography (eLORETA) freeware estimated the functional lagged linear connectivity (LLC) from rsEEG cortical sources in delta, theta, alpha, beta, and gamma bands. The area under receiver operating characteristic (AUROC) curve indexed the classification accuracy between Nold and diseased individuals (only values >0.7 were considered). Interhemispheric and intrahemispheric LLCs in widespread delta sources were abnormally higher in the ADD group and, unexpectedly, normal in DLB and PDD groups. Intrahemispheric LLC was reduced in widespread alpha sources dramatically in ADD, markedly in DLB, and moderately in PDD group. Furthermore, the interhemispheric LLC in widespread alpha sources showed lower values in ADD and DLB than PDD groups. At the individual level, AUROC curves of LLC in alpha sources exhibited better classification accuracies for the discrimination of ADD versus Nold individuals (0.84) than for DLB versus Nold participants (0.78) and PDD versus Nold participants (0.75). Functional cortical connectivity markers in delta and alpha sources suggest a more compromised neurophysiological reserve in ADD than DLB, at both group and individual levels.

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.

Contribution of Quantitative EEG to the Diagnosis of Early Cognitive Impairment in Patients With Idiopathic Parkinson's Disease

Cognitive dysfunction can emerge during the clinical course of Parkinson's disease (PD) even beginning in early stages, which requires extended neuropsychological tests for diagnosis. There is need for rapid, feasible, and practical tests in clinical practice to diagnose and monitor the patients without causing any discomfort. We investigated the utility of quantitative analysis of digital EEG (qEEG) for diagnosing subtle cognitive impairment in PD patients without evident cognitive deficits (ie, "normal cognition"). We enrolled 45 patients with PD and age- matched 39 healthy controls in the study. All participants had Mini-Mental State Examination (MMSE) score greater than 25. qEEG analysis and extensive neuropsychological assessment battery were applied to all participants. Test scores for frontal executive functions, verbal memory processes, attention span, and visuospatial functions were significantly lower than healthy controls ( P < .01). qEEG analysis revealed a significant increase in delta, theta, and beta frequencies, and decrease in alpha frequency band in cerebral bioelectrical activity in patient group. In addition, power spectral ratios ([alpha + beta] / [delta + theta]) in frontal, central, temporal, parietal, and occipital regions were significantly decreased in patients compared with the controls. The slowing in EEG was moderately correlated with MMSE scores ( r = 0.411-0.593; P < .01). However, qEEG analysis and extensive neuropsychological assessment battery were only in weak correlation ( r = 0.230-0.486; P < .05). In conclusion, qEEG analysis could increase the diagnostic power in detecting subtle cognitive impairment in PD patients without evident cognitive deficit, perhaps years before the clinical onset of dementia.

Abnormalities of cortical neural synchronization mechanisms in patients with dementia due to Alzheimer's and Lewy body diseases: an EEG study

The aim of this retrospective exploratory study was that resting state eyes-closed electroencephalographic (rsEEG) rhythms might reflect brain arousal in patients with dementia due to Alzheimer's disease dementia (ADD), Parkinson's disease dementia (PDD), and dementia with Lewy body (DLB). Clinical and rsEEG data of 42 ADD, 42 PDD, 34 DLB, and 40 healthy elderly (Nold) subjects were available in an international archive. Demography, education, and Mini-Mental State Evaluation score were not different between the patient groups. Individual alpha frequency peak (IAF) determined the delta, theta, alpha 1, alpha 2, and alpha 3 frequency bands. Fixed beta 1, beta 2, and gamma bands were also considered. rsEEG cortical sources were estimated by means of the exact low-resolution brain electromagnetic source tomography and were then classified across individuals, on the basis of the receiver operating characteristic curves. Compared to Nold, IAF showed marked slowing in PDD and DLB and moderate slowing in ADD. Furthermore, all patient groups showed lower posterior alpha 2 source activities. This effect was dramatic in ADD, marked in DLB, and moderate in PDD. These groups also showed higher occipital delta source activities, but this effect was dramatic in PDD, marked in DLB, and moderate in ADD. The posterior delta and alpha sources allowed good classification accuracy (approximately 0.85-0.90) between the Nold subjects and patients, and between ADD and PDD patients. In quiet wakefulness, delta and alpha sources unveiled different spatial and frequency features of the cortical neural synchronization underpinning brain arousal in ADD, PDD, and DLB patients. Future prospective cross-validation studies should test these rsEEG markers for clinical applications and drug discovery.

Mitochondrial dysfunction in Parkinson's disease

Parkinson's disease (PD) is the second most common neurodegenerative disease. About 2% of the population above the age of 60 is affected by the disease. The pathological hallmarks of the disease include the loss of dopaminergic neurons in the substantia nigra and the presence of Lewy bodies that are made of α-synuclein. Several theories have been suggested for the pathogenesis of PD, of which mitochondrial dysfunction plays a pivotal role in both sporadic and familial forms of the disease. Dysfunction of the mitochondria that is caused by bioenergetic defects, mutations in mitochondrial DNA, nuclear DNA gene mutations linked to mitochondria, and changes in dynamics of the mitochondria such fusion or fission, changes in size and morphology, alterations in trafficking or transport, altered movement of mitochondria, impairment of transcription, and the presence of mutated proteins associated with mitochondria are implicated in PD. In this review, we provide a detailed overview of the mechanisms that can cause mitochondrial dysfunction in PD. We bring to the forefront, new signaling pathways such as the retromer-trafficking pathway and its implication in the disease and also provide a brief overview of therapeutic strategies to improve mitochondrial defects in PD. Bioenergetic defects, mutations in mitochondrial DNA, nuclear DNA gene mutations, alterations in mitochondrial dynamics, alterations in trafficking/transport and mitochondrial movement, abnormal size and morphology, impairment of transcription and the presence of mutated proteins associated with mitochondria are implicated in PD. In this review, we focus on the mechanisms underlying mitochondrial dysfunction in PD and bring to the forefront new signaling pathways that may be involved in PD. We also provide an overview of therapeutic strategies to improve mitochondrial defects in PD. This article is part of a special issue on Parkinson disease.