Visual evoked potentials in multiple sclerosis: P100 latency and visual pathway damage including the lateral geniculate nucleus

OBJECTIVE

To explore associations of the main component (P100) of visual evoked potentials (VEP) to pre- and postchiasmatic damage in multiple sclerosis (MS).

METHODS

31 patients (median EDSS: 2.5), 13 with previous optic neuritis (ON), and 31 healthy controls had VEP, optical coherence tomography and magnetic resonance imaging. We tested associations of P100-latency to the peripapillary retinal nerve fiber layer (pRNFL), ganglion cell/inner plexiform layers (GCIPL), lateral geniculate nucleus volume (LGN), white matter lesions of the optic radiations (OR-WML), fractional anisotropy of non-lesional optic radiations (NAOR-FA), and to the mean thickness of primary visual cortex (V1). Effect sizes are given as marginal R2 (mR2).

RESULTS

P100-latency, pRNFL, GCIPL and LGN in patients differed from controls. Within patients, P100-latency was significantly associated with GCIPL (mR2 = 0.26), and less strongly with OR-WML (mR2 = 0.17), NAOR-FA (mR2 = 0.13) and pRNFL (mR2 = 0.08). In multivariate analysis, GCIPL and NAOR-FA remained significantly associated with P100-latency (mR2 = 0.41). In ON-patients, P100-latency was significantly associated with LGN volume (mR2 = -0.56).

CONCLUSIONS

P100-latency is affected by anterior and posterior visual pathway damage. In ON-patients, damage at the synapse-level (LGN) may additionally contribute to latency delay.

SIGNIFICANCE

Our findings corroborate post-chiasmatic contributions to the VEP-signal, which may relate to distinct pathophysiological mechanisms in MS.

Poor reactivity of posterior electroencephalographic alpha rhythms during the eyes open condition in patients with dementia due to Parkinson's disease

Here, we hypothesized that the reactivity of posterior resting-state electroencephalographic (rsEEG) alpha rhythms during the transition from eyes-closed to -open condition might be lower in patients with Parkinson's disease dementia (PDD) than in patients with Alzheimer's disease dementia (ADD). A Eurasian database provided clinical-demographic-rsEEG datasets in 73 PDD patients, 35 ADD patients, and 25 matched cognitively unimpaired (Healthy) persons. The eLORETA freeware was used to estimate cortical rsEEG sources. Results showed substantial (greater than -10%) reduction (reactivity) in the posterior alpha source activities from the eyes-closed to the eyes-open condition in 88% of the Healthy seniors, 57% of the ADD patients, and only 35% of the PDD patients. In these alpha-reactive participants, there was lower reactivity in the parietal alpha source activities in the PDD group than in the healthy control seniors and the ADD patients. These results suggest that PDD patients show poor reactivity of mechanisms desynchronizing posterior rsEEG alpha rhythms in response to visual inputs. That neurophysiological biomarker may provide an endpoint for (non) pharmacological interventions for improving vigilance regulation in those patients.

High-frequency multimodal training with a focus on Tai Chi in people with Parkinson's disease: a pilot study

Background and objectives

Cognitive decline is an important and common complication in patients with Parkinson's disease (PD) since it significantly reduces the quality of life. A breakthrough in treating and preventing cognitive decline in PD remains to be achieved. This study aimed to evaluate the effectiveness of high-frequency and intensive multimodal training in improving motor and cognitive function.

Methods

Twenty-eight patients diagnosed with idiopathic PD completed a comprehensive neuropsychological test battery and were neurologically examined. The patients of the intervention group (n = 15) underwent 2 weekly sessions of Tai Chi therapy over 4 weeks and participated in an individually tailored training program consisting of two modules (smartphone-based speech training and cognitive training). A matched control group consisted of n = 13 patients with PD who received computer-assisted cognitive training. The data were analyzed with repeated-measures ANOVA.

Results

Four weeks of high-frequency training showed significant effects on verbal and figural episodic memory and visuospatial function in the intervention group. Compared to the control group, the cognitive performance of the intervention group improved significantly in visuospatial function and figural episodic memory. A significant improvement was also shown in the intervention group in the Tinetti Mobility Test and the Epworth Sleepiness Scale. The significant effects in the Tinetti mobility test remained after the 6 months follow-up. After the intervention, the patients reported high motivation and satisfaction with the multimodal training.

Conclusion

In patients with PD, a multimodal training program not only improves gait and stability but may also contribute to improving cognition.

Clinical trial registration

ClinicalTrials.gov Identifier: NCT04103255; https://register.clinicaltrials.gov/prs/app/action/LoginUser?ts=1&cx=-jg9qo4.

Electrophysiological signatures of anxiety in Parkinson's disease

Anxiety is a common non-motor symptom in Parkinson's disease (PD) occurring in up to 31% of the patients and affecting their quality of life. Despite the high prevalence, anxiety symptoms in PD are often underdiagnosed and, therefore, undertreated. To date, functional and structural neuroimaging studies have contributed to our understanding of the motor and cognitive symptomatology of PD. Yet, the underlying pathophysiology of anxiety symptoms in PD remains largely unknown and studies on their neural correlates are missing. Here, we used resting-state electroencephalography (RS-EEG) of 68 non-demented PD patients with or without clinically-defined anxiety and 25 healthy controls (HC) to assess spectral and functional connectivity fingerprints characterizing the PD-related anxiety. When comparing the brain activity of the PD anxious group (PD-A, N = 18) to both PD non-anxious (PD-NA, N = 50) and HC groups (N = 25) at baseline, our results showed increased fronto-parietal delta power and decreased frontal beta power depicting the PD-A group. Results also revealed hyper-connectivity networks predominating in delta, theta and gamma bands against prominent hypo-connectivity networks in alpha and beta bands as network signatures of anxiety in PD where the frontal, temporal, limbic and insular lobes exhibited the majority of significant connections. Moreover, the revealed EEG-based electrophysiological signatures were strongly associated with the clinical scores of anxiety and followed their progression trend over the course of the disease. We believe that the identification of the electrophysiological correlates of anxiety in PD using EEG is conducive toward more accurate prognosis and can ultimately support personalized psychiatric follow-up and the development of new therapeutic strategies.

Identification of Parkinson's Disease Subtypes from Resting-State Electroencephalography

BACKGROUND

Parkinson's disease (PD) patients present with a heterogeneous clinical phenotype, including motor, cognitive, sleep, and affective disruptions. However, this heterogeneity is often either ignored or assessed using only clinical assessments.

OBJECTIVES

We aimed to identify different PD sub-phenotypes in a longitudinal follow-up analysis and their electrophysiological profile based on resting-state electroencephalography (RS-EEG) and to assess their clinical significance over the course of the disease.

METHODS

Using electrophysiological features obtained from RS-EEG recordings and data-driven methods (similarity network fusion and source-space spectral analysis), we have performed a clustering analysis to identify disease sub-phenotypes and we examined whether their different patterns of disruption are predictive of disease outcome.

RESULTS

We showed that PD patients (n = 44) can be sub-grouped into three phenotypes with distinct electrophysiological profiles. These clusters are characterized by different levels of disruptions in the somatomotor network (Δ and β band), the frontotemporal network (α2 band) and the default mode network (α1 band), which consistently correlate with clinical profiles and disease courses. These clusters are classified into either moderate (only-motor) or mild-to-severe (diffuse) disease. We showed that EEG features can predict cognitive evolution of PD patients from baseline, when the cognitive clinical scores were overlapped.

CONCLUSIONS

The identification of novel PD subtypes based on electrical brain activity signatures may provide a more accurate prognosis in individual patients in clinical practice and help to stratify subgroups in clinical trials. Innovative profiling in PD can also support new therapeutic strategies that are brain-based and designed to modulate brain activity disruption. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Prediction of cognitive decline in Parkinson's disease (PD) patients with electroencephalography (EEG) connectivity characterized by time-between-phase-crossing (TBPC)

The aim of the study is to identify the dynamic change pattern of EEG to predict cognitive decline in patients with Parkinson's disease. Here we demonstrate that the quantification of synchrony-pattern changes across the scalp, measured using electroencephalography (EEG), offers an alternative approach of observing an individual's functional brain organization. This method, called "Time-Between-Phase-Crossing" (TBPC), is based on the same phenomenon as the phase-lag-index (PLI); it also considers intermittent changes in the signals of phase differences between pairs of EEG signals, but additionally analyzes dynamic connectivity changes. We used data from 75 non-demented Parkinson's disease patients and 72 healthy controls, who were followed over a period of 3 years. Statistics were calculated using connectome-based modeling (CPM) and receiver operating characteristic (ROC). We show that TBPC profiles, via the use of intermittent changes in signals of analytic phase differences of pairs of EEG signals, can be used to predict cognitive decline in Parkinson's disease (p < 0.05).

Information Contained in EEG Allows Characterization of Cognitive Decline in Neurodegenerative Disorders

Over the last few decades, electroencephalography (EEG) has evolved from being a method that purely relies on visual inspection into a quantitative method. Quantitative EEG, or QEEG, enables the assessment of neurological disorders based on spectral features, dynamic characterizations of EEG resting-state activity, brain connectivity analyzes or quantification of EEG signal complexity. The information contained in EEG is multidimensional: Electrodes, positioned at different scalp locations, provide a spatial dimension to the analysis of EEG while time provides a dynamic dimension: This multidimensional property of EEG makes its quantification a challenging task. In this narrative review we present quantitative models focused on different aspects of EEG: While microstate models focus more on the quantification of the dynamic aspects of EEG, spectral methods, connectivity analysis and entropy based models are more concerned with its spatial aspects. Nevertheless, these diverse approaches have provided neurophysiology based biomarkers, especially for monitoring and predicting the course of various neurodegenerative disorders. However, their translation into clinical practice crucially depends on the ability to automate the analysis of EEG in a user-friendly manner, without compromising on the validity of the provided results. Once this has been accomplished, EEG would provide an inexpensive and widely available method for monitoring disease progression, identifying patients at risk of neurodegeneration-especially before the onset of clinical symptoms, and predicting future cognition. For stratification of patients to clinical trials, EEG would allow shortening the trial duration and lowering the number of necessary participants by identifying patients at risk of fast cognitive decline.

Functional Brain Dysconnectivity in Parkinson's Disease: A 5-Year Longitudinal Study

Background

Tracking longitudinal functional brain dysconnectivity in Parkinson's disease (PD) is a key element to decoding the underlying physiopathology and understanding PD progression.

Objectives

The objectives of this follow‐up study were to explore, for the first time, the longitudinal changes in the functional brain networks of PD patients over 5 years and to associate them with their cognitive performance and the lateralization of motor symptoms.

Methods

We used a 5‐year longitudinal cohort of PD patients (n = 35) who completed motor and non‐motor assessments and sequent resting state (RS) high‐density electroencephalography (HD‐EEG) recordings at three timepoints: baseline (BL), 3 years follow‐up (3YFU) and 5 years follow‐up (5YFU). We assessed disruptions in frequency‐dependent functional networks over the course of the disease and explored their relation to clinical symptomatology.

Results

In contrast with HC (n = 32), PD patients showed a gradual connectivity impairment in α2 (10‐13 Hz) and β (13–30 Hz) frequency bands. The deterioration in the global cognitive assessment was strongly correlated with the disconnected networks. These disconnected networks were also associated with the lateralization of motor symptoms, revealing a dominance of the right hemisphere in terms of impaired connections in the left‐affected PD patients in contrast to dominance of the left hemisphere in the right‐affected PD patients.

Conclusions

Taken together, our findings suggest that with disease progression, dysconnectivity in the brain networks in PD can reflect the deterioration of global cognitive deficits and the lateralization of motor symptoms. RS HD‐EEG may be an early biomarker of PD motor and non‐motor progression. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

Anxiety, Depression, and Apathy as Predictors of Cognitive Decline in Patients With Parkinson's Disease-A Three-Year Follow-Up Study

Objective

Anxiety, depression, and apathy are the most common neuropsychiatric symptoms in Parkinson's disease (PD) patients. They impair cognitive functioning and have a profound impact on quality of life. This follow-up study aims to investigate the predictive value of anxiety, depression, and apathy on the development of Mild Cognitive Impairment (MCI) in PD patients.

Methods

Twenty-nine cognitively unimpaired PD patients (mean age 68.2 SD ± 7.12 years; 13 women) participated in this study. At Baseline (BL) levels of apathy (Apathy Evaluation Scale, AES), depression (Beck Depression Inventory, BDI-II), and anxiety (Beck Anxiety Inventory, BAI), were assessed. Cognitive status was reassessed three years later according to MCI/non-MCI status. For statistics, we used binary logistic regression and receiver operating characteristic curve (ROC) analysis to examine anxiety, apathy, and depression at BL as a predictor of MCI status three years later.

Results

Eight of the 29 patients developed MCI. Anxiety level at BL was found to predict MCI status at three-year follow-up (OR = 1.20, CI = 1.02–1.41, p = 0.02), while depression (OR = 1.16, CI = 0.93–1.47, p = 0.20) and apathy (OR = 1.06, CI = 0.92–1.23, p = 0.40) did not predict MCI status. The area under the ROC curve (AUC) of BAI for discriminating PD-non-MCI from PD-MCI was 0.79 (CI = 0.61–0.98). The optimal classification threshold yielded a sensitivity of 75.0 % and a specificity of 76.2 %. Neither apathy nor depression at BL discriminated between PD-non-MCI patients from PD-MCI three years later.

Conclusions

This study shows an association between anxiety and the development of MCI in PD patients, although the association between apathy, depression, and MCI did not reach a significant level.

Evaluating a Speech-Specific and a Computerized Step-Training-Specific Rhythmic Intervention in Parkinson's Disease: A Cross-Over, Multi-Arms Parallel Study

Background:

Recent studies suggest movements of speech and gait in patients with Parkinson's Disease (PD) are impaired by a common underlying rhythmic dysfunction. If this being the case, motor deficits in speech and gait should equally benefit from rhythmic interventions regardless of whether it is a speech-specific or step-training-specific approach.

Objective:

In this intervention trial, we studied the effects of two rhythmic interventions on speech and gait. These rhythmic intervention programs are similar in terms of intensity and frequency (i.e., 3x per week, 45 min-long sessions for 4 weeks in total), but differ regarding therapeutic approach (rhythmic speech vs. rhythmic balance-mobility training).

Methods:

This study is a cross-over, parallel multi-arms, single blind intervention trial, in which PD patients treated with rhythmic speech-language therapy (rSLT; N = 16), rhythmic balance-mobility training (rBMT; N = 10), or no therapy (NT; N = 18) were compared to healthy controls (HC; N = 17; matched by age, sex, and education: p > 0.82). Velocity and cadence in speech and gait were evaluated at baseline (BL), 4 weeks (4W-T1), and 6 months (6M-T2) and correlated.

Results:

Parameters in speech and gait (i.e., speaking and walking velocity, as well as speech rhythm with gait cadence) were positively correlated across groups (p < 0.01). Statistical analyses involved repeated measures ANOVA across groups and time, as well as independent and one-samples t-tests for within groups analyses. Statistical analyses were amplified using Reliable Change (RC) and Reliable Change Indexes (RCI) to calculate true clinically significant changes due to the treatment on a patient individual level. Rhythmic intervention groups improved across variables and time (total Mean Difference: 3.07 [SD 1.8]; 95% CI 0.2–11.36]) compared to the NT group, whose performance declined significantly at 6 months (p < 0.01). HC outperformed rBMT and NT groups across variables and time (p < 0.001); the rSLT performed similarly to HC at 4 weeks and 6 months in speech rhythm and respiration.

Conclusions:

Speech and gait deficits in PD may share a common mechanism in the underlying cortical circuits. Further, rSLT was more beneficial to dysrhythmic PD patients than rBMT, likely because of the nature of the rhythmic cue.

Does Quantitative Electroencephalography Refine Preoperative Cognitive Assessment in Parkinson's Disease Patients Treated with Deep Brain Stimulation? A Follow-Up Study

OBJECTIVE

Deep brain stimulation (DBS) in Parkinson's disease (PD) is associated with an increased risk of post-operative cognitive deterioration. Preoperative neuropsychological testing can be affected and limited by the patient's collaboration in advanced disease. The purpose of this study was to determine whether preoperative quantitative electroencephalography (qEEG) may be a useful complementary examination technique during preoperative assessment to predict cognitive changes in PD patients treated with DBS.

METHODS

We compared the cognitive performance of 16 PD patients who underwent bilateral subthalamic nucleus DBS to the performance of 15 PD controls (matched for age, sex, and education) at baseline and at 24 months. Cognitive scores were calculated for all patients across 5 domains. A preoperative 256-channel resting EEG was recorded from each patient. We computed the global relative power spectra. Correlation and linear regression models were used to assess associations of preoperative EEG measures with post-operative cognitive scores.

RESULTS

Slow waves (relative delta and theta band power) were negatively correlated with post-operative cognitive performance, while faster waves (alpha 1) were strongly positively correlated with the same scores (the overall cognitive score, attention, and executive function). Linear models revealed an association of delta power with the overall cognitive score (p = 0.00409, adjusted R2 = 0.6341). Verbal fluency (VF) showed a significant decline after DBS surgery, which was correlated with qEEG measures.

CONCLUSIONS

To analyse the side effects after DBS in PD patients, the most important parameter is verbal fluency capacity. In addition, correlation with EEG frequency bands might be useful to detect particularly vulnerable patients for cognitive impairment and be supportive in the selection process of patients considered for DBS.

Effects of Rhythmic Interventions on Cognitive Abilities in Parkinson's Disease

OBJECTIVE

The objective of this study is to compare 2 different rhythmic, high-intensive interventions, that is, rhythmic speech-language therapy (rSLT) versus rhythmic balance-mobility training (rBMT), against a no-therapy (NT) condition in patients with Parkinson's disease and against healthy controls (HCs) with regard to the change in or enhancement of cognitive abilities.

METHODS

The 4 groups (rSLT: N = 16; rBMT: N = 10; NT: N = 18; and HC: N = 17) were matched for age, sex, and educational level and were tested in 6 cognitive domains: working memory, executive function, visuo-construction, episodic memory, attention, and word retrieval. Assessments took place at baseline, at 4 weeks (T1), and at 6 months (T2). Rhythmic interventions were provided 3 times per week for 4 weeks in total. To analyze true intervention effects between groups and across time, statistical analyses included reliable change index. Intergroup differences were assessed with multivariate assessment of variance, while differences within groups were assessed with 95% confidence intervals of mean difference.

RESULTS

The rSLT improved working memory and word retrieval (p < 0.05), possibly a beneficial transfer effect of the training method per se. In contrast, the NT group worsened in phonemic and semantic shifting (p < 0.01). Observed improvements in flexibility and in episodic memory in the HC may be linked to training effects of retesting.

CONCLUSIONS

Rhythmic cues are resistant to neurodegeneration and have a strong motivating factor. As thus, these may facilitate high-intensive and demanding training. Although both trainings were superior to NT, the improvement of cognitive abilities depends on the specific training method. Further, therapy may be more effective when delivered by a therapist rather than by an impersonal computer program.

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.

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.

Encephalitis with Autoantibodies against the Glutamate Kainate Receptors GluK2

OBJECTIVE

The objective of this study was to report the identification of antibodies against the glutamate kainate receptor subunit 2 (GluK2-abs) in patients with autoimmune encephalitis, and describe the clinical-immunological features and antibody effects.

METHODS

Two sera from 8 patients with similar rat brain immunostaining were used to precipitate the antigen from neuronal cultures. A cell-based assay (CBA) with GluK2-expressing HEK293 cells was used to assess 596 patients with different neurological disorders, and 23 healthy controls. GluK2-ab effects were determined by confocal microscopy in cultured neurons and electrophysiology in GluK2-expressing HEK293 cells.

RESULTS

Patients' antibodies precipitated GluK2. GluK2 antibody-specificity was confirmed by CBA, immunoprecipitation, GluK2-immunoabsorption, and GluK2 knockout brain immunohistochemistry. In 2 of 8 samples, antibodies reacted with additional GluK2 epitopes present in GluK1 or GluK3; in both, the reactivity was abrogated after GluK2 immuno-absorption. Six of 8 patients developed acute encephalitis and clinical or magnetic resonance imaging (MRI) features of predominant cerebellar involvement (4 presenting as cerebellitis, which in 2 patients caused obstructive hydrocephalus), and 2 patients had other syndromes (1 with cerebellar symptoms). One of the samples showed mild reactivity with non-kainate receptors (alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors [AMPAR] and N-methyl-D-aspartate receptors [NMDAR]) leading to identify 6 additional cases with GluK2-abs among patients with anti-AMPAR (5/71) or anti-NMDAR encephalitis (1/73). GluK2-abs internalized GluK2 in HEK293 cells and neurons; these antibody-effects were reversible in neurons. A significant reduction of GluK2-mediated currents was observed in cells treated with patients' GluK2 serum following the time frame of antibody-mediated GluK2 internalization.

INTERPRETATION

GluK2-abs associate with an encephalitis with prominent clinicoradiological cerebellar involvement. The antibody effects are predominantly mediated by internalization of GluK2. ANN NEUROL 2021;90:107-123.

Cognitive decline in Parkinson's disease is associated with reduced complexity of EEG at baseline

Parkinson’s disease is a neurodegenerative disorder requiring motor signs for diagnosis, but showing more widespread pathological alterations from its beginning. Compared to age-matched healthy individuals, patients with Parkinson’s disease bear a 6-fold lifetime risk of dementia. For individualized counselling and treatment, prognostic biomarkers for assessing future cognitive deterioration in early stages of Parkinson’s disease are needed. In a case–control study, 42 cognitively normal patients with Parkinson’s disease were compared with 24 healthy control participants matched for age, sex and education. Tsallis entropy and band power of the δ, θ, α, β and γ-band were evaluated in baseline EEG at eyes-open and eyes-closed condition. As the θ-band showed the most pronounced differences between Parkinson’s disease and healthy control groups, further analysis focussed on this band. Tsallis entropy was then compared across groups with 16 psychological test scores at baseline and follow-ups at 6 months and 3 years. In group comparison, patients with Parkinson’s disease showed lower Tsallis entropy than healthy control participants. Cognitive deterioration at 3 years was correlated with Tsallis entropy in the eyes-open condition (P < 0.00079), whereas correlation at 6 months was not yet significant. Tsallis entropy measured in the eyes-closed condition did not correlate with cognitive outcome. In conclusion, the lower the EEG entropy levels at baseline in the eyes-open condition, the higher the probability of cognitive decline over 3 years. This makes Tsallis entropy a candidate prognostic biomarker for dementia in Parkinson’s disease. The ability of the cortex to execute complex functions underlies cognitive health, whereas cognitive decline might clinically appear when compensatory capacity is exhausted.

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.

Validation of Quantitative Scores Derived From Motor Evoked Potentials in the Assessment of Primary Progressive Multiple Sclerosis: A Longitudinal Study

Objective: To evaluate the sensitivity to change of differently calculated quantitative scores from motor evoked potentials (MEP) in patients with primary progressive multiple sclerosis (PPMS). Methods: Twenty patients with PPMS had MEP to upper and lower limbs at baseline, years 1 and 2 measured in addition to clinical assessment [Expanded Disability Status Scale (EDSS), ambulation score]; a subsample (n = 9) had a nine-hole peg test (NHPT) and a timed 25-foot walk (T25FW). Quantitative MEP scores for upper limbs (qMEP-UL), lower limbs (qMEP-LL), and all limbs (qMEP) were calculated in three different ways, based on z-transformed central motor conduction time (CMCT), shortest corticomuscular latency (CxM-sh), and mean CxM (CxM-mn). Changes in clinical measures and qMEP metrics were analyzed by repeated-measures analysis of variance (rANOVA), and a factor analysis was performed on change in qMEP metrics. Results: Expanded Disability Status Scale and ambulation score progressed in the rANOVA model (p < 0.05; post-hoc comparison baseline-year 2, p < 0.1). Lower limb and combined qMEP scores showed significant deterioration of latency (p < 0.01, MEP-LL_CxM-sh: p < 0.05) and in post-hoc comparisons (baseline-year 2, p < 0.05), qMEP_CxM-mn even over 1 year (p < 0.05). Effect sizes were higher for qMEP scores than for clinical measures, and slightly but consistently higher when based on CxM-mn compared to CxM-sh or CMCT. Subgroup analysis yielded no indication of higher sensitivity of timed clinical measures over qMEP scores. Two independent factors were detected, the first mainly associated with qMEP-LL, the second with qMEP-UL, explaining 65 and 29% of total variability, respectively. Conclusions: Deterioration in qMEP scores occurs earlier than EDSS progression in patients with PPMS. Upper and lower limb qMEP scores contribute independently to measuring change, and qMEP scores based on mean CxM are advantageous. The capability to detect subclinical changes longitudinally is a unique property of EP and complementary to clinical assessment. These features underline the role of EP as candidate biomarkers to measure effects of therapeutic interventions in PPMS.

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.

Effects of Cognitive Performance and Affective Status on Fatigue in Parkinson's Disease

Background

Fatigue is a common non-motor symptom in Parkinson's disease (PD) and is typically assessed via self-reported questionnaires such as the Parkinson's Fatigue Scale (PFS). The PFS captures the presence of subjective experience of physical fatigue as well as its impact on daily functioning.

Objectives

We aimed to investigate whether different variables (cognition, neuropsychiatric symptoms, disease-related measures) are associated with the experience of physical fatigue in comparison to fatigue affecting daily functioning.

Method

Sixty-two non-demented PD patients were evaluated through questionnaires assessing fatigue, daytime sleepiness, apathy, depression, anxiety, and cognition. Items of fatigue were classified and summarized into two index variables measuring either the subjective experience of physical fatigue or the impact of fatigue on daily functioning. Linear regression with a stepwise elimination procedure was conducted to select the significant predictors for each index variable separately.

Results

Subjective experience of physical fatigue (Model 1; r² = 0.46; p <0.01) was significantly associated with higher levels of depression (b =0.07; p <0.01), anxiety (b =0.03; p <0.05), and lower performances in verbal episodic memory (b =-0.16; p <0.05). Fatigue affecting daily functioning (Model 2; r² = 0.44; p <0.05) was significantly related to higher levels of depression (b = 0.07; p < 0.01), anxiety (b = 0.03; p > 0.05), and lower motor functioning (b = 0.01; p = 0.05).

Conclusions

In conclusion, our work supports associations between fatigue and other neuropsychiatric symptoms in PD and extends prior work suggesting that motor disturbances are specifically linked to fatigue-related impairment of daily functioning, but not to the subjective experience of physical fatigue.

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.

Multicentre assessment of motor and sensory evoked potentials in multiple sclerosis: reliability and implications for clinical trials

Background

Motor and sensory evoked potentials (EP) are potential candidate biomarkers for clinical trials in multiple sclerosis.

Objective

To determine test -retest reliability of motor EP (MEP) and sensory EP (SEP) and associated EP-scores in patients with multiple sclerosis.

Methods

In three centres, 16 relapsing and five progressive multiple sclerosis patients had MEPs and SEPs 1-29 days apart. Five neurophysiologists independently marked latencies by central reading. By variance component analysis, we estimated the critical difference (absolute reliability) for cross-sectional group comparison, comparison of longitudinal group changes, within-subject minimal detectable change and defined within-subject improvement.

Results

Cortical SEP responses and cortico-muscular MEP latencies were more reliable than central conduction times. For comparison of 20 subjects per arm, cross-sectional group difference ranged from 0.7 to 3.9 ms and 1.1 to 1.7, group difference in longitudinal changes from 0.4 to 1.8 ms and 0.36 to 0.62, within-subject minimal detectable change from 1.2 to 5.8 ms and 1.2 to 2.0, within-subject improvement from 0.8 to 3.8ms and 0.8 to 1.3, for single EP modalities and EP scores, respectively.

Conclusions

Multicentre EP assessment with central EP reading is feasible and reliable. The critical difference is reasonably low to detect significant group changes and to define responders. The results support the concept of using EP and EP-scores as candidate response biomarkers for quantification of disease progression and for studying remyelination in multiple sclerosis.

Abnormalities of Resting State Cortical EEG Rhythms in Subjects with Mild Cognitive Impairment Due to Alzheimer's and Lewy Body Diseases

The present study tested the hypothesis that cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms reveal different abnormalities in cortical neural synchronization in groups of patients with mild cognitive impairment due to Alzheimer's disease (ADMCI) and dementia with Lewy bodies (DLBMCI) as compared to cognitively normal elderly (Nold) subjects. Clinical and rsEEG data in 30 ADMCI, 23 DLBMCI, and 30 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) score was matched between the ADMCI and DLBMCI 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 (ROCC) classified these sources across individuals. Compared to Nold, IAF showed marked slowing in DLBMCI and moderate in ADMCI. Furthermore, the posterior alpha 2 and alpha 3 source activities were more abnormal in the ADMCI than the DLBMCI group, while widespread delta source activities were more abnormal in the DLBMCI than the ADMCI group. The posterior delta and alpha sources correlated with the MMSE score and correctly classified the Nold and MCI individuals (area under the ROCC >0.85). In conclusion, the ADMCI and DLBMCI 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 the clinical validity of these rsEEG markers.

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.

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.

Fine Motor Function Skills in Patients with Parkinson Disease with and without Mild Cognitive Impairment

AIMS

The objective of this study was to investigate the relation between impaired fine motor skills in Parkinson disease (PD) patients and their cognitive status, and to determine whether fine motor skills are more impaired in PD patients with mild cognitive impairment (MCI) than in non-MCI patients.

METHODS

Twenty PD MCI and 31 PD non-MCI patients (mean age 66.7 years, range 50-84, 36 males/15 females), all right-handed, took part in a motor performance test battery. Steadiness, precision, dexterity, velocity of arm-hand movements, and velocity of wrist-finger movements were measured and compared across groups and analyzed for confounders (age, sex, education, severity of motor symptoms, and disease duration). Statistical analysis included t tests corrected for multiple testing, and a linear regression with stepwise elimination procedure was used to select significant predictors for fine motor function.

RESULTS

PD MCI patients performed significantly worse in precision (p < 0.05), dexterity (p < 0.05), and velocity (arm-hand movements; p < 0.05) compared to PD non-MCI patients. The fine motor function skills were confounded by age.

CONCLUSIONS

Fine motor skills in PD MCI patients are impaired compared to PD non-MCI patients. Investigating the relation between the fine motor performance and MCI in PD might be a relevant subject for future research.

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.